surface learning approaches: Topics by Science.gov

Sample records for surface learning approaches

Deep and surface learning in problem-based learning: a review of the literature.

PubMed

Dolmans, Diana H J M; Loyens, Sofie M M; Marcq, Hélène; Gijbels, David

2016-12-01

In problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested and try to understand what is being studied. This review investigates: (1) the effects of PBL on students' deep and surface approaches to learning, (2) whether and why these effects do differ across (a) the context of the learning environment (single vs. curriculum wide implementation), and (b) study quality. Studies were searched dealing with PBL and students' approaches to learning. Twenty-one studies were included. The results indicate that PBL does enhance deep learning with a small positive average effect size of .11 and a positive effect in eleven of the 21 studies. Four studies show a decrease in deep learning and six studies show no effect. PBL does not seem to have an effect on surface learning as indicated by a very small average effect size (.08) and eleven studies showing no increase in the surface approach. Six studies demonstrate a decrease and four an increase in surface learning. It is concluded that PBL does seem to enhance deep learning and has little effect on surface learning, although more longitudinal research using high quality measurement instruments is needed to support this conclusion with stronger evidence. Differences cannot be explained by the study quality but a curriculum wide implementation of PBL has a more positive impact on the deep approach (effect size .18) compared to an implementation within a single course (effect size of -.05). PBL is assumed to enhance active learning and students' intrinsic motivation, which enhances deep learning. A high perceived workload and assessment that is perceived as not rewarding deep learning are assumed to enhance surface learning.
Dental students' perception of their approaches to learning in a PBL programme.

PubMed

Haghparast, H; Ghorbani, A; Rohlin, M

2017-08-01

To compare dental students' perceptions of their learning approaches between different years of a problem-based learning (PBL) programme. The hypothesis was that in a comparison between senior and junior students, the senior students would perceive themselves as having a higher level of deep learning approach and a lower level of surface learning approach than junior students would. This hypothesis was based on the fact that senior students have longer experience of a student-centred educational context, which is supposed to underpin student learning. Students of three cohorts (first year, third year and fifth year) of a PBL-based dental programme were asked to respond to a questionnaire (R-SPQ-2F) developed to analyse students' learning approaches, that is deep approach and surface approach, using four subscales including deep strategy, surface strategy, deep motive and surface motive. The results of the three cohorts were compared using a one-way analysis of variance (ANOVA). A P-value was set at <0.05 for statistical significance. The fifth-year students demonstrated a lower surface approach than the first-year students (P = 0.020). There was a significant decrease in surface strategy from the first to the fifth year (P = 0.003). No differences were found concerning deep approach or its subscales (deep strategy and deep motive) between the mean scores of the three cohorts. The results did not show the expected increased depth in learning approaches over the programme years. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Approach to Learning of Sub-Degree Students in Hong Kong

ERIC Educational Resources Information Center

Chan, Yiu Man; Chan, Christine Mei Sheung

2010-01-01

The learning approaches and learning experiences of 404 sub-degree students were assessed by using a Study Process Questionnaire and a Learning Experience Questionnaire. While the learning approaches in this study meant whether students used a deep learning or surface learning approach, the learning experiences referred to students' perceptions…
Learning approach among health sciences students in a medical college in Nepal: a cross-sectional study.

PubMed

Shah, Dev Kumar; Yadav, Ram Lochan; Sharma, Deepak; Yadav, Prakash Kumar; Sapkota, Niraj Khatri; Jha, Rajesh Kumar; Islam, Md Nazrul

2016-01-01

Many factors shape the quality of learning. The intrinsically motivated students adopt a deep approach to learning, while students who fear failure in assessments adopt a surface approach to learning. In the area of health science education in Nepal, there is still a lack of studies on learning approach that can be used to transform the students to become better learners and improve the effectiveness of teaching. Therefore, we aimed to explore the learning approaches among medical, dental, and nursing students of Chitwan Medical College, Nepal using Biggs's Revised Two-Factor Study Process Questionnaire (R-SPQ-2F) after testing its reliability. R-SPQ-2F containing 20 items represented two main scales of learning approaches, deep and surface, with four subscales: deep motive, deep strategy, surface motive, and surface strategy. Each subscale had five items and each item was rated on a 5-point Likert scale. The data were analyzed using Student's t-test and analysis of variance. Reliability of the administered questionnaire was checked using Cronbach's alpha. The Cronbach's alpha value (0.6) for 20 items of R-SPQ-2F was found to be acceptable for its use. The participants predominantly had a deep approach to learning regardless of their age and sex (deep: 32.62±6.33 versus surface: 25.14±6.81, P<0.001). The level of deep approach among medical students (33.26±6.40) was significantly higher than among dental (31.71±6.51) and nursing (31.36±4.72) students. In comparison to first-year students, deep approach among second-year medical (34.63±6.51 to 31.73±5.93; P<0.001) and dental (33.47±6.73 to 29.09±5.62; P=0.002) students was found to be significantly decreased. On the other hand, surface approach significantly increased (25.55±8.19 to 29.34±6.25; P=0.023) among second-year dental students compared to first-year dental students. Medical students were found to adopt a deeper approach to learning than dental and nursing students. However, irrespective of disciplines and personal characteristics of participants, the primarily deep learning approach was found to be shifting progressively toward a surface approach after completion of an academic year, which should be avoided.
Self-regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison Between Professional Training and English Learning.

PubMed

Tseng, Min-Chen; Chen, Chia-Cheng

2017-06-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.
Moving beyond the Deep and Surface Dichotomy; Using Q Methodology to Explore Students' Approaches to Studying

ERIC Educational Resources Information Center

Godor, Brian P.

2016-01-01

Student learning approaches research has been built upon the notions of deep and surface learning. Despite its status as part of the educational research canon, the dichotomy of deep/surface has been critiqued as constraining the debate surrounding student learning. Additionally, issues of content validity have been expressed concerning…
Learning approaches as predictors of academic performance in first year health and science students.

PubMed

Salamonson, Yenna; Weaver, Roslyn; Chang, Sungwon; Koch, Jane; Bhathal, Ragbir; Khoo, Cheang; Wilson, Ian

2013-07-01

To compare health and science students' demographic characteristics and learning approaches across different disciplines, and to examine the relationship between learning approaches and academic performance. While there is increasing recognition of a need to foster learning approaches that improve the quality of student learning, little is known about students' learning approaches across different disciplines, and their relationships with academic performance. Prospective, correlational design. Using a survey design, a total of 919 first year health and science students studying in a university located in the western region of Sydney from the following disciplines were recruited to participate in the study - i) Nursing: n = 476, ii) Engineering: n = 75, iii) Medicine: n = 77, iv) Health Sciences: n = 204, and v) Medicinal Chemistry: n = 87. Although there was no statistically significant difference in the use of surface learning among the five discipline groups, there were wide variations in the use of deep learning approach. Furthermore, older students and those with English as an additional language were more likely to use deep learning approach. Controlling for hours spent in paid work during term-time and English language usage, both surface learning approach (β = -0.13, p = 0.001) and deep learning approach (β = 0.11, p = 0.009) emerged as independent and significant predictors of academic performance. Findings from this study provide further empirical evidence that underscore the importance for faculty to use teaching methods that foster deep instead of surface learning approaches, to improve the quality of student learning and academic performance. Copyright © 2013 Elsevier Ltd. All rights reserved.
Adapting a Framework for Assessing Students' Approaches to Modeling

ERIC Educational Resources Information Center

Bennett, Steven Carl

2017-01-01

We used an "approach to learning" theoretical framework to explicate the ways students engage in scientific modeling. Approach to learning theory suggests that when students approach learning deeply, they link science concepts with prior knowledge and experiences. Conversely, when students engage in a surface approach to learning, they…
Investigating the interrelationships among conceptions of, approaches to, and self-efficacy in learning science

NASA Astrophysics Data System (ADS)

Zheng, Lanqin; Dong, Yan; Huang, Ronghuai; Chang, Chun-Yen; Bhagat, Kaushal Kumar

2018-01-01

The purpose of this study was to examine the relations between primary school students' conceptions of, approaches to, and self-efficacy in learning science in Mainland China. A total of 1049 primary school students from Mainland China participated in this study. Three instruments were adapted to measure students' conceptions of learning science, approaches to learning science, and self-efficacy. The exploratory factor analysis and confirmatory factor analysis were adopted to validate three instruments. The path analysis was employed to understand the relationships between conceptions of learning science, approaches to learning science, and self-efficacy. The findings indicated that students' lower level conceptions of learning science positively influenced their surface approaches in learning science. Higher level conceptions of learning science had a positive influence on deep approaches and a negative influence on surface approaches to learning science. Furthermore, self-efficacy was also a hierarchical construct and can be divided into the lower level and higher level. Only students' deep approaches to learning science had a positive influence on their lower and higher level of self-efficacy in learning science. The results were discussed in the context of the implications for teachers and future studies.
Student perceptions about learning anatomy

NASA Astrophysics Data System (ADS)

Notebaert, Andrew John

This research study was conducted to examine student perceptions about learning anatomy and to explore how these perceptions shape the learning experience. This study utilized a mixed-methods design in order to better understand how students approach learning anatomy. Two sets of data were collected at two time periods; one at the beginning and one at the end of the academic semester. Data consisted of results from a survey instrument that contained open-ended questions and a questionnaire and individual student interviews. The questionnaire scored students on a surface approach to learning (relying on rote memorization and knowing factual information) scale and a deep approach to learning (understanding concepts and deeper meaning behind the material) scale. Students were asked to volunteer from four different anatomy classes; two entry-level undergraduate courses from two different departments, an upper-level undergraduate course, and a graduate level course. Results indicate that students perceive that they will learn anatomy through memorization regardless of the level of class being taken. This is generally supported by the learning environment and thus students leave the classroom believing that anatomy is about memorizing structures and remembering anatomical terminology. When comparing this class experience to other academic classes, many students believed that anatomy was more reliant on memorization techniques for learning although many indicated that memorization is their primary learning method for most courses. Results from the questionnaire indicate that most students had decreases in both their deep approach and surface approach scores with the exception of students that had no previous anatomy experience. These students had an average increase in surface approach and so relied more on memorization and repetition for learning. The implication of these results is that the learning environment may actually amplify students' perceptions of the anatomy course at all levels and experiences of enrolled students. Instructors wanting to foster deeper approaches to learning may need to apply instructional techniques that both support deeper approaches to learning and strive to change students' perceptions away from believing that anatomy is strictly memorization and thus utilizing surface approaches to learning.
Superficial and deep learning approaches among medical students in an interdisciplinary integrated curriculum.

PubMed

Mirghani, Hisham M; Ezimokhai, Mutairu; Shaban, Sami; van Berkel, Henk J M

2014-01-01

Students' learning approaches have a significant impact on the success of the educational experience, and a mismatch between instructional methods and the learning approach is very likely to create an obstacle to learning. Educational institutes' understanding of students' learning approaches allows those institutes to introduce changes in their curriculum content, instructional format, and assessment methods that will allow students to adopt deep learning techniques and critical thinking. The objective of this study was to determine and compare learning approaches among medical students following an interdisciplinary integrated curriculum. This was a cross-sectional study in which an electronic questionnaire using the Biggs two-factor Study Process Questionnaire (SPQ) with 20 questions was administered. Of a total of 402 students at the medical school, 214 (53.2%) completed the questionnaire. There was a significant difference in the mean score of superficial approach, motive and strategy between students in the six medical school years. However, no significant difference was observed in the mean score of deep approach, motive and strategy. The mean score for years 1 and 2 showed a significantly higher surface approach, surface motive and surface strategy when compared with students in years 4-6 in medical school. The superficial approach to learning was mostly preferred among first and second year medical students, and the least preferred among students in the final clinical years. These results may be useful in creating future teaching, learning and assessment strategies aiming to enhance a deep learning approach among medical students. Future studies are needed to investigate the reason for the preferred superficial approach among medical students in their early years of study.
Student Learning Approaches in the UAE: The Case for the Achieving Domain

ERIC Educational Resources Information Center

McLaughlin, James; Durrant, Philip

2017-01-01

The deep versus surface learning approach dichotomy has dominated recent research in student learning approach dimensions. However, the achievement dimension may differ in importance in non-Western and vocational tertiary settings. The aim was to assess how Emirati tertiary students could be characterized in terms of their learning approaches. The…
Self-Regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison between Professional Training and English Learning

ERIC Educational Resources Information Center

Tseng, Min-chen; Chen, Chia-cheng

2017-01-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between…
Using Computer Technology to Foster Learning for Understanding

PubMed Central

VAN MELLE, ELAINE; TOMALTY, LEWIS

2000-01-01

The literature shows that students typically use either a surface approach to learning, in which the emphasis is on memorization of facts, or a deep approach to learning, in which learning for understanding is the primary focus. This paper describes how computer technology, specifically the use of a multimedia CD-ROM, was integrated into a microbiology curriculum as part of the transition from focusing on facts to fostering learning for understanding. Evaluation of the changes in approaches to learning over the course of the term showed a statistically significant shift in a deep approach to learning, as measured by the Study Process Questionnaire. Additional data collected showed that the use of computer technology supported this shift by providing students with the opportunity to apply what they had learned in class to order tests and interpret the test results in relation to specific patient-focused case studies. The extent of the impact, however, varied among different groups of students in the class. For example, students who were recent high school graduates did not show a statistically significant increase in deep learning scores over the course of the term and did not perform as well in the course. The results also showed that a surface approach to learning was an important aspect of learning for understanding, although only those students who were able to combine a surface with a deep approach to learning were successfully able to learn for understanding. Implications of this finding for the future use of computer technology and learning for understanding are considered. PMID:23653533
Influence of a veterinary curriculum on the approaches and study skills of veterinary medical students.

PubMed

Chigerwe, Munashe; Ilkiw, Jan E; Boudreaux, Karen A

2011-01-01

The objectives of the present study were to evaluate first-, second-, third-, and fourth-year veterinary medical students' approaches to studying and learning as well as the factors within the curriculum that may influence these approaches. A questionnaire consisting of the short version of the Approaches and Study Skills Inventory for Students (ASSIST) was completed by 405 students, and it included questions relating to conceptions about learning, approaches to studying, and preferences for different types of courses and teaching. Descriptive statistics, factor analysis, Cronbach's alpha analysis, and log-linear analysis were performed on the data. Deep, strategic, and surface learning approaches emerged. There were a few differences between our findings and those presented in previous studies in terms of the correlation of the subscale monitoring effectiveness, which showed loading with both the deep and strategic learning approaches. In addition, the subscale alertness to assessment demands showed correlation with the surface learning approach. The perception of high workloads, the use of previous test files as a method for studying, and examinations that are based only on material provided in lecture notes were positively associated with the surface learning approach. Focusing on improving specific teaching and assessment methods that enhance deep learning is anticipated to enhance students' positive learning experience. These teaching methods include instructors who encourage students to be critical thinkers, the integration of course material in other disciplines, courses that encourage thinking and reading about the learning material, and books and articles that challenge students while providing explanations beyond lecture material.
Exploring the relationships between epistemic beliefs about medicine and approaches to learning medicine: a structural equation modeling analysis.

PubMed

Chiu, Yen-Lin; Liang, Jyh-Chong; Hou, Cheng-Yen; Tsai, Chin-Chung

2016-07-18

Students' epistemic beliefs may vary in different domains; therefore, it may be beneficial for medical educators to better understand medical students' epistemic beliefs regarding medicine. Understanding how medical students are aware of medical knowledge and how they learn medicine is a critical issue of medical education. The main purposes of this study were to investigate medical students' epistemic beliefs relating to medical knowledge, and to examine their relationships with students' approaches to learning medicine. A total of 340 undergraduate medical students from 9 medical colleges in Taiwan were surveyed with the Medical-Specific Epistemic Beliefs (MSEB) questionnaire (i.e., multi-source, uncertainty, development, justification) and the Approach to Learning Medicine (ALM) questionnaire (i.e., surface motive, surface strategy, deep motive, and deep strategy). By employing the structural equation modeling technique, the confirmatory factor analysis and path analysis were conducted to validate the questionnaires and explore the structural relations between these two constructs. It was indicated that medical students with multi-source beliefs who were suspicious of medical knowledge transmitted from authorities were less likely to possess a surface motive and deep strategies. Students with beliefs regarding uncertain medical knowledge tended to utilize flexible approaches, that is, they were inclined to possess a surface motive but adopt deep strategies. Students with beliefs relating to justifying medical knowledge were more likely to have mixed motives (both surface and deep motives) and mixed strategies (both surface and deep strategies). However, epistemic beliefs regarding development did not have significant relations with approaches to learning. Unexpectedly, it was found that medical students with sophisticated epistemic beliefs (e.g., suspecting knowledge from medical experts) did not necessarily engage in deep approaches to learning medicine. Instead of a deep approach, medical students with sophisticated epistemic beliefs in uncertain and justifying medical knowledge intended to employ a flexible approach and a mixed approach, respectively.
Progress testing in the medical curriculum: students' approaches to learning and perceived stress.

PubMed

Chen, Yan; Henning, Marcus; Yielder, Jill; Jones, Rhys; Wearn, Andy; Weller, Jennifer

2015-09-11

Progress Tests (PTs) draw on a common question bank to assess all students in a programme against graduate outcomes. Theoretically PTs drive deep approaches to learning and reduce assessment-related stress. In 2013, PTs were introduced to two year groups of medical students (Years 2 and 4), whereas students in Years 3 and 5 were taking traditional high-stakes assessments. Staged introduction of PTs into our medical curriculum provided a time-limited opportunity for a comparative study. The main purpose of the current study was to compare the impact of PTs on undergraduate medical students' approaches to learning and perceived stress with that of traditional high-stakes assessments. We also aimed to investigate the associations between approaches to learning, stress and PT scores. Undergraduate medical students (N = 333 and N = 298 at Time 1 and Time 2 respectively) answered the Revised Study Process Questionnaire (R-SPQ-2F) and the Perceived Stress Scale (PSS) at two time points to evaluate change over time. The R-SPQ-2F generated a surface approach and a deep approach score; the PSS generated an overall perceived stress score. We found no significant differences between the two groups in approaches to learning at either time point, and no significant changes in approaches to learning over time in either cohort. Levels of stress increased significantly at the end of the year (Time 2) for students in the traditional assessment cohort, but not in the PT cohort. In the PT cohort, surface approach to learning, but not stress, was a significant negative predictor of students' PT scores. While confirming an association between surface approaches to learning and lower PT scores, we failed to demonstrate an effect of PTs on approaches to learning. However, a reduction in assessment-associated stress is an important finding.
On the Role of Discipline-Related Self-Concept in Deep and Surface Approaches to Learning among University Students

ERIC Educational Resources Information Center

Platow, Michael J.; Mavor, Kenneth I.; Grace, Diana M.

2013-01-01

The current research examined the role that students' discipline-related self-concepts may play in their deep and surface approaches to learning, their overall learning outcomes, and continued engagement in the discipline itself. Using a cross-lagged panel design of first-year university psychology students, a causal path was observed in which…
Do Students Develop towards More Deep Approaches to Learning during Studies? A Systematic Review on the Development of Students' Deep and Surface Approaches to Learning in Higher Education

ERIC Educational Resources Information Center

Asikainen, Henna; Gijbels, David

2017-01-01

The focus of the present paper is on the contribution of the research in the student approaches to learning tradition. Several studies in this field have started from the assumption that students' approaches to learning develop towards more deep approaches to learning in higher education. This paper reports on a systematic review of longitudinal…
Constructive, collaborative, contextual, and self-directed learning in surface anatomy education.

PubMed

Bergman, Esther M; Sieben, Judith M; Smailbegovic, Ida; de Bruin, Anique B H; Scherpbier, Albert J J A; van der Vleuten, Cees P M

2013-01-01

Anatomy education often consists of a combination of lectures and laboratory sessions, the latter frequently including surface anatomy. Studying surface anatomy enables students to elaborate on their knowledge of the cadaver's static anatomy by enabling the visualization of structures, especially those of the musculoskeletal system, move and function in a living human being. A recent development in teaching methods for surface anatomy is body painting, which several studies suggest increases both student motivation and knowledge acquisition. This article focuses on a teaching approach and is a translational contribution to existing literature. In line with best evidence medical education, the aim of this article is twofold: to briefly inform teachers about constructivist learning theory and elaborate on the principles of constructive, collaborative, contextual, and self-directed learning; and to provide teachers with an example of how to implement these learning principles to change the approach to teaching surface anatomy. Student evaluations of this new approach demonstrate that the application of these learning principles leads to higher student satisfaction. However, research suggests that even better results could be achieved by further adjustments in the application of contextual and self-directed learning principles. Successful implementation and guidance of peer physical examination is crucial for the described approach, but research shows that other options, like using life models, seem to work equally well. Future research on surface anatomy should focus on increasing the students' ability to apply anatomical knowledge and defining the setting in which certain teaching methods and approaches have a positive effect. Copyright © 2012 American Association of Anatomists.

Approaches to learning for the ANZCA Final Examination and validation of the revised Study Process Questionnaire in specialist medical training.

PubMed

Weller, J M; Henning, M; Civil, N; Lavery, L; Boyd, M J; Jolly, B

2013-09-01

When evaluating assessments, the impact on learning is often overlooked. Approaches to learning can be deep, surface and strategic. To provide insights into exam quality, we investigated the learning approaches taken by trainees preparing for the Australian and New Zealand College of Anaesthetists (ANZCA) Final Exam. The revised two-factor Study Process Questionnaire (R-SPQ-2F) was modified and validated for this context and was administered to ANZCA advanced trainees. Additional questions were asked about perceived value for anaesthetic practice, study time and approaches to learning for each exam component. Overall, 236 of 690 trainees responded (34%). Responses indicated both deep and surface approaches to learning with a clear preponderance of deep approaches. The anaesthetic viva was valued most highly and the multiple choice question component the least. Despite this, respondents spent the most time studying for the multiple choice questions. The traditionally low short answer questions pass rate could not be explained by limited study time, perceived lack of value or study approaches. Written responses suggested that preparation for multiple choice questions was characterised by a surface approach, with rote memorisation of past questions. Minimal reference was made to the ANZCA syllabus as a guide for learning. These findings indicate that, although trainees found the exam generally relevant to practice and adopted predominantly deep learning approaches, there was considerable variation between the four components. These results provide data with which to review the existing ANZCA Final Exam and comparative data for future studies of the revisions to the ANZCA curriculum and exam process.
Learning in First-Year Biology: Approaches of Distance and On-Campus Students

NASA Astrophysics Data System (ADS)

Quinn, Frances Catherine

2011-01-01

This paper aims to extend previous research into learning of tertiary biology, by exploring the learning approaches adopted by two groups of students studying the same first-year biology topic in either on-campus or off-campus "distance" modes. The research involved 302 participants, who responded to a topic-specific version of the Study Process Questionnaire, and in-depth interviews with 16 of these students. Several quantitative analytic techniques, including cluster analysis and Rasch differential item functioning analysis, showed that the younger, on-campus cohort made less use of deep approaches, and more use of surface approaches than the older, off-campus group. At a finer scale, clusters of students within these categories demonstrated different patterns of learning approach. Students' descriptions of their learning approaches at interview provided richer complementary descriptions of the approach they took to their study in the topic, showing how deep and surface approaches were manifested in the study context. These findings are critically analysed in terms of recent literature questioning the applicability of learning approaches theory in mass education, and their implications for teaching and research in undergraduate biology.
Learning from Tutorials: A Qualitative Study of Approaches to Learning and Perceptions of Tutorial Interaction

ERIC Educational Resources Information Center

Herrmann, Kim Jesper

2014-01-01

This study examines differences in university students' approaches to learning when attending tutorials as well as variation in students' perceptions of tutorials as an educational arena. In-depth qualitative analysis of semi-structured interviews with undergraduates showed how surface and deep approaches to learning were revealed in the…
Are Chinese University Students More Likely to Exhibit a Surface Approach to Learning than Other International Students in Finland?

ERIC Educational Resources Information Center

Sakurai, Yusuke; Pyhältö, Kirsi; Lindblom-Ylänne, Sari

2014-01-01

This article is based on a study which investigated whether Chinese international students at a university in Finland are more likely to rely on a Surface approach to learning and dismiss a Deep approach than are other international students in the same university educational context. In responding to a survey, students' scores with respect to the…
Deep and Surface Processing of Instructor's Feedback in an Online Course

ERIC Educational Resources Information Center

Huang, Kun; Ge, Xun; Law, Victor

2017-01-01

This study investigated the characteristics of deep and surface approaches to learning in online students' responses to instructor's qualitative feedback given to a multi-stage, ill-structured design project. Further, the study examined the relationships between approaches to learning and two learner characteristics: epistemic beliefs (EB) and…
Problematic Smartphone Use, Deep and Surface Approaches to Learning, and Social Media Use in Lectures.

PubMed

Rozgonjuk, Dmitri; Saal, Kristiina; Täht, Karin

2018-01-08

Several studies have shown that problematic smartphone use (PSU) is related to detrimental outcomes, such as worse psychological well-being, higher cognitive distraction, and poorer academic outcomes. In addition, many studies have shown that PSU is strongly related to social media use. Despite this, the relationships between PSU, as well as the frequency of social media use in lectures, and different approaches to learning have not been previously studied. In our study, we hypothesized that both PSU and the frequency of social media use in lectures are negatively correlated with a deep approach to learning (defined as learning for understanding) and positively correlated with a surface approach to learning (defined as superficial learning). The study participants were 415 Estonian university students aged 19-46 years (78.8% females; age M = 23.37, SD = 4.19); the effective sample comprised 405 participants aged 19-46 years (79.0% females; age M = 23.33, SD = 4.21). In addition to basic socio-demographics, participants were asked about the frequency of their social media use in lectures, and they filled out the Estonian Smartphone Addiction Proneness Scale and the Estonian Revised Study Process Questionnaire. Bivariate correlation analysis showed that PSU and the frequency of social media use in lectures were negatively correlated with a deep approach to learning and positively correlated with a surface approach to learning. Mediation analysis showed that social media use in lectures completely mediates the relationship between PSU and approaches to learning. These results indicate that the frequency of social media use in lectures might explain the relationships between poorer academic outcomes and PSU.
Problematic Smartphone Use, Deep and Surface Approaches to Learning, and Social Media Use in Lectures †

PubMed Central

Rozgonjuk, Dmitri; Saal, Kristiina

2018-01-01

Several studies have shown that problematic smartphone use (PSU) is related to detrimental outcomes, such as worse psychological well-being, higher cognitive distraction, and poorer academic outcomes. In addition, many studies have shown that PSU is strongly related to social media use. Despite this, the relationships between PSU, as well as the frequency of social media use in lectures, and different approaches to learning have not been previously studied. In our study, we hypothesized that both PSU and the frequency of social media use in lectures are negatively correlated with a deep approach to learning (defined as learning for understanding) and positively correlated with a surface approach to learning (defined as superficial learning). The study participants were 415 Estonian university students aged 19–46 years (78.8% females; age M = 23.37, SD = 4.19); the effective sample comprised 405 participants aged 19–46 years (79.0% females; age M = 23.33, SD = 4.21). In addition to basic socio-demographics, participants were asked about the frequency of their social media use in lectures, and they filled out the Estonian Smartphone Addiction Proneness Scale and the Estonian Revised Study Process Questionnaire. Bivariate correlation analysis showed that PSU and the frequency of social media use in lectures were negatively correlated with a deep approach to learning and positively correlated with a surface approach to learning. Mediation analysis showed that social media use in lectures completely mediates the relationship between PSU and approaches to learning. These results indicate that the frequency of social media use in lectures might explain the relationships between poorer academic outcomes and PSU. PMID:29316697
First-Year Students' Approaches to Learning, and Factors Related to Change or Stability in Their Deep Approach during a Pharmacy Course

ERIC Educational Resources Information Center

Varunki, Maaret; Katajavuori, Nina; Postareff, Liisa

2017-01-01

Research shows that a surface approach to learning is more common among students in the natural sciences, while students representing the "soft" sciences are more likely to apply a deep approach. However, findings conflict concerning the stability of approaches to learning in general. This study explores the variation in students'…
Students' Studying and Approaches to Learning in Introductory Biology

PubMed Central

2004-01-01

This exploratory study was conducted in an introductory biology course to determine 1) how students used the large lecture environment to create their own learning tasks during studying and 2) whether meaningful learning resulted from the students' efforts. Academic task research from the K–12 education literature and student approaches to learning research from the postsecondary education literature provided the theoretical framework for the mixed methods study. The subject topic was cell division. Findings showed that students 1) valued lectures to develop what they believed to be their own understanding of the topic; 2) deliberately created and engaged in learning tasks for themselves only in preparation for the unit exam; 3) used course resources, cognitive operations, and study strategies that were compatible with surface and strategic, rather than deep, approaches to learning; 4) successfully demonstrated competence in answering familiar test questions aligned with their surface and strategic approaches to studying and learning; and 5) demonstrated limited meaningful understanding of the significance of cell division processes. Implications for introductory biology education are discussed. PMID:15592598
Morningness-eveningness preferences, learning approach and academic achievement of undergraduate medical students.

PubMed

Akram, Nimra; Khan, Naheed; Ameen, Mehreen; Mahmood, Shahmeera; Shamim, Komal; Amin, Marium; Rana, Qurrat Ul Ain

2018-05-15

Several studies have focused on determining the effect of chronotype and learning approach on academic achievement separately indicating that morning types have an academic advantage over the evening types and so have the deep learners over the surface learners. But, surprisingly none have assessed the possible relationship between chronotype and learning approach. So, the current study aimed to evaluate this association and their individual influence on academic performance as indicated by the Cumulative Grade Point Average (CGPA) as well as the effect of their interaction on academic performance. The study included 345 undergraduate medical students who responded to reduced Morningness-Eveningness Questionnaire and Biggs Revised Two-Factor Study Process Questionnaire. Morning types indulged in deep learning while evening types in surface learning. Morning and evening types did not differ on academic performance but deep learners had better academic outcomes than their counterparts. The interaction between chronotype and learning approach was significant on determining academic achievement. Our findings gave the impression that chronotype could have an impact on academic performance not directly but indirectly through learning approaches.
Examining Learning Approaches of Science Student Teachers According to the Class Level and Gender

ERIC Educational Resources Information Center

Tural Dincer, Guner; Akdeniz, Ali Riza

2008-01-01

There are many factors influence the level of students' achievement in education. Studies show that one of these factors is "learning approach of a student". Research findings generally have identified two approaches of learning: deep and surface. When a student uses the deep approach, he/she has an intrinsic interest in subject matter and is…
Revisiting Approaches to Learning in Science and Engineering: A Case Study

ERIC Educational Resources Information Center

Gynnild, V.; Myrhaug, D.

2012-01-01

Several studies have applied the dichotomy of deep and surface approaches to learning in a range of disciplinary contexts. Existing questionnaires have largely assumed the existence of these constructs; however, in a recent study Case and Marshall (2004) described two additional context-specific approaches to learning in engineering. The current…
Learning Approaches and Cultural Influences: A Comparative Study of Confucian and Western-Heritage Students

ERIC Educational Resources Information Center

Dennehy, Edward

2015-01-01

With the advent of increasingly multinational student cohorts in many higher education institutes, the possible influence of 'national culture' on students' learning approaches has become a focal point of attention. In particular, the claim that Asian (Confucian) students adopt (primarily) surface learning approaches has attracted much debate…
The educational impact of assessment: A comparison of DOPS and MCQs

PubMed Central

Cobb, Kate A.; Brown, George; Jaarsma, Debbie A. D. C.; Hammond, Richard A.

2013-01-01

Aim To evaluate the impact of two different assessment formats on the approaches to learning of final year veterinary students. The relationship between approach to learning and examination performance was also investigated. Method An 18-item version of the Study Process Questionnaire (SPQ) was sent to 87 final year students. Each student responded to the questionnaire with regards to DOPS (Direct Observation of Procedural Skills) and a Multiple Choice Examination (MCQ). Semi-structured interviews were conducted with 16 of the respondents to gain a deeper insight into the students’ perception of assessment. Results Students’ adopted a deeper approach to learning for DOPS and a more surface approach with MCQs. There was a positive correlation between an achieving approach to learning and examination performance. Analysis of the qualitative data revealed that deep, surface and achieving approaches were reported by the students and seven major influences on their approaches to learning were identified: motivation, purpose, consequence, acceptability, feedback, time pressure and the individual difference of the students. Conclusions The format of DOPS has a positive influence on approaches to learning. There is a conflict for students between preparing for final examinations and preparing for clinical practice. PMID:23808609
The Relationship between Motivation, Learning Approaches, Academic Performance and Time Spent

ERIC Educational Resources Information Center

Everaert, Patricia; Opdecam, Evelien; Maussen, Sophie

2017-01-01

Previous literature calls for further investigation in terms of precedents and consequences of learning approaches (deep learning and surface learning). Motivation as precedent and time spent and academic performance as consequences are addressed in this paper. The study is administered in a first-year undergraduate course. Results show that the…
Students' approaches to learning in a clinical practicum: A psychometric evaluation based on item response theory.

PubMed

Zhao, Yue; Kuan, Hoi Kei; Chung, Joyce O K; Chan, Cecilia K Y; Li, William H C

2018-07-01

The investigation of learning approaches in the clinical workplace context has remained an under-researched area. Despite the validation of learning approach instruments and their applications in various clinical contexts, little is known about the extent to which an individual item, that reflects a specific learning strategy and motive, effectively contributes to characterizing students' learning approaches. This study aimed to measure nursing students' approaches to learning in a clinical practicum using the Approaches to Learning at Work Questionnaire (ALWQ). Survey research design was used in the study. A sample of year 3 nursing students (n = 208) who undertook a 6-week clinical practicum course participated in the study. Factor analyses were conducted, followed by an item response theory analysis, including model assumption evaluation (unidimensionality and local independence), item calibration and goodness-of-fit assessment. Two subscales, deep and surface, were derived. Findings suggested that: (a) items measuring the deep motive from intrinsic interest and deep strategies of relating new ideas to similar situations, and that of concept mapping served as the strongest discriminating indicators; (b) the surface strategy of memorizing facts and details without an overall picture exhibited the highest discriminating power among all surface items; and, (c) both subscales appeared to be informative in assessing a broad range of the corresponding latent trait. The 21-item ALWQ derived from this study presented an efficient, internally consistent and precise measure. Findings provided a useful psychometric evaluation of the ALWQ in the clinical practicum context, added evidence to the utility of the ALWQ for nursing education practice and research, and echoed the discussions from previous studies on the role of the contextual factors in influencing student choices of different learning strategies. They provided insights for clinical educators to measure nursing students' approaches to learning and facilitate their learning in the clinical practicum setting. Copyright © 2018. Published by Elsevier Ltd.
Mathematical Tasks, Study Approaches, and Course Grades in Undergraduate Mathematics: A Year-by-Year Analysis

ERIC Educational Resources Information Center

Maciejewski, Wes; Merchant, Sandra

2016-01-01

Students approach learning in different ways, depending on the experienced learning situation. A deep approach is geared toward long-term retention and conceptual change while a surface approach focuses on quickly acquiring knowledge for immediate use. These approaches ultimately affect the students' academic outcomes. This study takes a…
Learning strategies, study habits and social networking activity of undergraduate medical students.

PubMed

Bickerdike, Andrea; O'Deasmhunaigh, Conall; O'Flynn, Siun; O'Tuathaigh, Colm

2016-07-17

To determine learning strategies, study habits, and online social networking use of undergraduates at an Irish medical school, and their relationship with academic performance. A cross-sectional study was conducted in Year 2 and final year undergraduate-entry and graduate-entry students at an Irish medical school. Data about participants' demographics and educational background, study habits (including time management), and use of online media was collected using a self-report questionnaire. Participants' learning strategies were measured using the 18-item Approaches to Learning and Studying Inventory (ALSI). Year score percentage was the measure of academic achievement. The association between demographic/educational factors, learning strategies, study habits, and academic achievement was statistically analysed using regression analysis. Forty-two percent of students were included in this analysis (n=376). A last-minute "cramming" time management study strategy was associated with increased use of online social networks. Learning strategies differed between undergraduate- and graduate-entrants, with the latter less likely to adopt a 'surface approach' and more likely adopt a 'study monitoring' approach. Year score percentage was positively correlated with the 'effort management/organised studying' learning style. Poorer academic performance was associated with a poor time management approach to studying ("cramming") and increased use of the 'surface learning' strategy. Our study demonstrates that effort management and organised studying should be promoted, and surface learning discouraged, as part of any effort to optimise academic performance in medical school. Excessive use of social networking contributes to poor study habits, which are associated with reduced academic achievement.
Attitudes toward and approaches to learning first-year university mathematics.

PubMed

Alkhateeb, Haitham M; Hammoudi, Lakhdar

2006-08-01

This study examined the relationship for 180 undergraduate students enrolled in a first-year university calculus course between attitudes toward mathematics and approaches to learning mathematics using the Mathematics Attitude Scale and the Approaches to Learning Mathematics Questionnaire, respectively. Regression analyses indicated that scores for the Mathematics Attitude Scale were negatively related to scores for the Surface Approach and accounted for 10.4% of the variance and scores for the Mathematics Attitude Scale were positively related to scores for the Deep Approach to learning mathematics and accounted for 31.7% of the variance.
Effects of a Metacognitive Intervention on Students' Approaches to Learning and Self-Efficacy in a First Year Medical Course

ERIC Educational Resources Information Center

Papinczak, Tracey; Young, Louise; Groves, Michele; Haynes, Michele

2008-01-01

Aim: To determine the influence of metacognitive activities within the PBL tutorial environment on the development of deep learning approach, reduction in surface approach, and enhancement of individual learning self-efficacy. Method: Participants were first-year medical students (N = 213). A pre-test, post-test design was implemented with…

Interaction of learning approach with concept integration and achievement in a large guided inquiry organic class

NASA Astrophysics Data System (ADS)

Mewhinney, Christina

A study was conducted to investigate the relationship of students' concept integration and achievement with time spent within a topic and across related topics in a large first semester guided inquiry organic chemistry class. Achievement was based on evidence of algorithmic problem solving; and concept integration was based on demonstrated performance explaining, applying, and relating concepts to each other. Twelve individual assessments were made of both variables over three related topics---acid/base, nucleophilic substitution and electrophilic addition reactions. Measurements included written, free response and ordered multiple answer questions using a classroom response system. Results demonstrated that students can solve problems without conceptual understanding. A second study was conducted to compare the students' learning approach at the beginning and end of the course. Students were scored on their preferences for a deep, strategic, or surface approach to learning based on their responses to a pre and post survey. Results suggest that students significantly decreased their preference for a surface approach during the semester. Analysis of the data collected was performed to determine the relationship between students' learning approach and their concept integration and achievement in this class. Results show a correlation between a deep approach and concept integration and a strong negative correlation between a surface approach and concept integration.
Learning styles and approaches to learning mathematics of students majoring in elementary education: a three-year study.

PubMed

Alkhateeb, Haitham M; Mji, Andile

2009-10-01

The goal of this 3-yr. study was to explore the learning styles and approaches to learning mathematics of elementary education majors. Two questionnaires, the Learning Style Inventory and the Approaches to Learning Mathematics Questionnaire, were administered to 149 women and 32 men (M = 20.1 yr., SD. = 2.1; range = 18-31). All were in their first or second years of college and enrolled in Mathematics for Elementary School Teachers at a Midwestern U.S. university. Results on the Learning Style Inventory indicated that a majority scored as either Accommodators, i.e., they primarily followed learning modes involving Active Experimentation and Concrete Experience, or as Divergers, i.e., approaching learning by focusing on Concrete Experience and Reflective Observation. A weak but statistically significant association was observed on the Approaches questionnaire between the Surface Approach and Reflective Observation.
Preferences for Deep-Surface Learning: A Vocational Education Case Study Using a Multimedia Assessment Activity

ERIC Educational Resources Information Center

Hamm, Simon; Robertson, Ian

2010-01-01

This research tests the proposition that the integration of a multimedia assessment activity into a Diploma of Events Management program promotes a deep learning approach. Firstly, learners' preferences for deep or surface learning were evaluated using the revised two-factor Study Process Questionnaire. Secondly, after completion of an assessment…
Measuring self-reported studying and learning for university students: linking attitudes and behaviours on the same scale.

PubMed

Waugh, Russell F

2002-12-01

The relationships between self-reported Approaches to Studying and Self-concept, Self-capability and Studying and Learning Behaviour are usually studied by measuring the variables separately (using factor analysis and Cronbach Alphas) and then using various correlation techniques (such as multiple regression and path analysis). This procedure has measurement problems and is called into question. To create a single scale of Studying and Learning using a model with subsets of ordered stem-items based on a Deep Approach, a Surface Approach and a Strategic Approach, integrated with three self-reported aspects (an Ideal Self-view, a Capability Self-view and a Studying and Learning Behaviour Self-view). The stem-item sample was 33, all answered in three aspects, that produced an effective item sample of 99. The person convenience sample was 431 students in education (1(st) to 4(th) year) at an Australian university during 2000. The latest Rasch Unidimensional Measurement Model Computer Program (Andrich, Lyne, Sheridan, & Luo, 2000) was used to analyse the data and create a single scale of Studying and Learning. Altogether 77 items fitted a Rasch Measurement Model and formed a scale in which the 'difficulties' of the items were ordered from 'easy' to 'hard' and the student measures of Studying and Learning were ordered from 'low' to 'high'. The proportion of observed student variance considered true was 0.96. The response categories were answered consistently and logically and the results supported many, but not all, the conceptualised ordering of the subscales. Students found it 'easy' to report a high Ideal Self-view, 'much harder' to report a high Capability Self-view, and 'harder still' to report a high Studying and Learning Behaviour for the stem-items, in accordance with the model, where items fit the measurement model. The Ideal Self-view Surface Approach items provided the most non-fit to the model. This method was highly successful in producing a single scale of Studying and Learning from self-reported Self-concepts, Self-capabilities, and Studying and Learning Behaviours, based on a Deep Approach, a Surface Approach and a Strategic Approach.
Variation in Student Reflections on their Conceptions of and Approaches to Learning Biochemistry in a First-year Health Sciences' Service Subject

NASA Astrophysics Data System (ADS)

Minasian-Batmanian, Laura C.; Lingard, Jennifer; Prosser, Michael

2006-12-01

Many factors affect students’ learning approaches, including topic conceptions and prior study. This research, undertaken after a first-semester compulsory subject, explores students’ conceptions of biochemistry and how they approached their studies. Students (n=151) completed an open-ended survey analysed phenomenographically. Those with cohesive conceptions were found to be more likely to adopt deeper approaches to study than those with fragmented conceptions, a result unaffected by various demographic parameters. Compared with earlier research, a semester of study increased the percentage of students with a cohesive view, with no concomitant change in learning approaches, suggesting that cohesive conceptions are a necessary but not sufficient criterion for deep learning outcomes. Compared with results for a science major subject, more of the students with cohesive conceptions used surface approaches. This may reflect a regression to safe surface approaches when faced with an unfamiliar topic or high total workload driving a strategic approach to learning. It could also reflect a perception that this material is only a tool for later application. The present findings indicate the crucial importance, when university studies begin, of enabling students to build an overarching conception of the topic’s place in professional practice. This concept building should be applied across the entire curriculum to emphasize application and integration of material (key graduate attributes). Improved conceptions may provide crucial motivation for students to achieve deeper learning, especially in these foundation service subjects. These essential changes to the learning context may also better prepare students for increasing self-directed/life-long learning.
Students' Adoption of Course-Specific Approaches to Learning in Two Parallel Courses

ERIC Educational Resources Information Center

Öhrstedt, Maria; Lindfors, Petra

2016-01-01

Research on students' adoption of course-specific approaches to learning in parallel courses is limited and inconsistent. This study investigated second-semester psychology students' levels of deep, surface and strategic approaches in two courses running in parallel within a real-life university setting. The results showed significant differences…
Older Women, Deeper Learning, and Greater Satisfaction at University: Age and Gender Predict University Students' Learning Approach and Degree Satisfaction

ERIC Educational Resources Information Center

Rubin, Mark; Scevak, Jill; Southgate, Erica; Macqueen, Suzanne; Williams, Paul; Douglas, Heather

2018-01-01

The present study explored the interactive effect of age and gender in predicting surface and deep learning approaches. It also investigated how these variables related to degree satisfaction. Participants were 983 undergraduate students at a large public Australian university. They completed a research survey either online or on paper. Consistent…
The Centre Cannot Hold: Untangling Two Different Trajectories of the "Approaches to Learning" Framework

ERIC Educational Resources Information Center

Tormey, Roland

2014-01-01

The "deep/surface approach to learning" framework is widely used in higher education. Its perceived strength is that it is regarded as having two functions: both being (1) a useful metaphor for development of teaching and learning in higher education and (2) a valid concept for researchers. In this paper, I present a critical review of…
Implementation of training programs in self-regulated learning strategies in Moodle format: results of a experience in higher education.

PubMed

Núñez, José Carlos; Cerezo, Rebeca; Bernardo, Ana; Rosário, Pedro; Valle, Antonio; Fernández, Estrella; Suárez, Natalia

2011-04-01

This paper tests the efficacy of an intervention program in virtual format intended to train studying and self-regulation strategies in university students. The aim of this intervention is to promote a series of strategies which allow students to manage their learning processes in a more proficient and autonomous way. The program has been developed in Moodle format and hosted by the Virtual Campus of the University of Oviedo. The present study had a semi-experimental design, included an experimental group (n=167) and a control one (n=206), and used pretest and posttest measures (self-regulated learning strategies' declarative knowledge, self-regulated learning macro-strategy planning-execution-assessment, self-regulated learning strategies on text, surface and deep learning approaches, and academic achievement). Data suggest that the students enrolled in the training program, comparing with students in the control group, showed a significant improvement in their declarative knowledge, general and on text use of learning strategies, increased their deep approach to learning, decreased their use of a surface approach and, in what concerns to academic achievement, statistically significant differences have been found in favour of the experimental group.
Dyslexia, authorial identity, and approaches to learning and writing: a mixed methods study.

PubMed

Kinder, Julianne; Elander, James

2012-06-01

Dyslexia may lead to difficulties with academic writing as well as reading. The authorial identity approach aims to help students improve their academic writing and avoid unintentional plagiarism, and could help to understand dyslexic students' approaches to writing. (1) To compare dyslexic and non-dyslexic students' authorial identity and approaches to learning and writing; (2) to compare correlations between approaches to writing and approaches to learning among dyslexic and non-dyslexic students; (3) to explore dyslexic students' understandings of authorship and beliefs about dyslexia, writing and plagiarism. Dyslexic (n= 31) and non-dyslexic (n= 31) university students. Questionnaire measures of self-rated confidence in writing, understanding of authorship, knowledge to avoid plagiarism, and top-down, bottom-up and pragmatic approaches to writing (Student Authorship Questionnaire; SAQ), and deep, surface and strategic approaches to learning (Approaches and Study Skills Inventory for Students; ASSIST), plus qualitative interviews with dyslexic students with high and low SAQ scores. Dyslexic students scored lower for confidence in writing, understanding authorship, and strategic approaches to learning, and higher for surface approaches to learning. Correlations among SAQ and ASSIST scores were larger and more frequently significant among non-dyslexic students. Self-rated knowledge to avoid plagiarism was associated with a top-down approach to writing among dyslexic students and with a bottom-up approach to writing among non-dyslexic students. All the dyslexic students interviewed described how dyslexia made writing more difficult and reduced their confidence in academic writing, but they had varying views about whether dyslexia increased the risk of plagiarism. Dyslexic students have less strong authorial identities, and less congruent approaches to learning and writing. Knowledge to avoid plagiarism may be more salient for dyslexic students, who may benefit from specific interventions to increase confidence in writing and understanding of authorship. Further research could investigate how dyslexic students develop approaches to academic writing, and how that could be affected by perceived knowledge to avoid plagiarism. ©2011 The British Psychological Society.
Evoked prior learning experience and approach to learning as predictors of academic achievement.

PubMed

Trigwell, Keith; Ashwin, Paul; Millan, Elena S

2013-09-01

In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students' perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. To investigate how students' evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. A 77-item questionnaire was used to gather students' self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was not related to academic achievement, and teaching quality and conceptions of learning were only indirectly related to achievement. Research aimed at understanding how students experience their learning environment and how that experience relates to the quality of their learning needs to be conducted using a wider range of variables and more sophisticated analytical methods. In this study of one context, some of the relations found in earlier bivariate studies, and on which learning intervention strategies have been built, are not confirmed when more holistic teaching-learning contexts are analysed using multi-variable methods. © 2012 The British Psychological Society.
Machine Learning Approach to Deconvolution of Thermal Infrared (TIR) Spectrum of Mercury Supporting MERTIS Onboard ESA/JAXA BepiColombo

NASA Astrophysics Data System (ADS)

Varatharajan, I.; D'Amore, M.; Maturilli, A.; Helbert, J.; Hiesinger, H.

2018-04-01

Machine learning approach to spectral unmixing of emissivity spectra of Mercury is carried out using endmember spectral library measured at simulated daytime surface conditions of Mercury. Study supports MERTIS payload onboard ESA/JAXA BepiColombo.
Differences in students' perceptions of learning compulsory foundation biochemistry in the health sciences professions.

PubMed

Minasian-Batmanian, Laura C; Lingard, Jennifer; Prosser, Michael

2005-11-01

Student approaches to learning vary from surface approaches to meaningful, deep learning practices. Differences in approach may be related to students' conceptions of the subject, perceptions of the learning environment, prior study experiences and performance on assessment. This study aims to explore entering students' conceptions of the unit they are about to study and how they intend to approach their studies. It involved a survey of 203 (of 250) first year students in a cross disciplinary unit in the Faculty of Health Sciences. They were asked to complete an open-ended response survey, including questions on what they thought they needed to do to learn biochemistry and what they thought the study of biochemistry was about. A phenomenographic methodology was used to identify categories of description for the questions. The paper will describe the categories in detail, the structural relationship between the categories and the distribution of responses within categories. The study reports a relationship between conception of the topic and approaches to learning. Students with more complex and coherent conceptions of the topic report that they were more likely to adopt deeper approaches to study than those with more fragmented conceptions. However, compared to previous studies, a surprisingly high proportion of students with more cohesive conceptions still intended to adopt more surface approaches. This may reflect the particular context of their learning, namely in a compulsory unit involving material for which most students have minimal background and difficulty seeing its relevance. Implications for teaching such foundation material are discussed.
A Guide to Using Case-Based Learning in Biochemistry Education

ERIC Educational Resources Information Center

Kulak, Verena; Newton, Genevieve

2014-01-01

Studies indicate that the majority of students in undergraduate biochemistry take a surface approach to learning, associated with rote memorization of material, rather than a deep approach, which implies higher cognitive processing. This behavior relates to poorer outcomes, including impaired course performance and reduced knowledge retention. The…
Students Approach to Learning and Their Use of Lecture Capture

ERIC Educational Resources Information Center

Vajoczki, Susan; Watt, Susan; Marquis, Nick; Liao, Rose; Vine, Michelle

2011-01-01

This study examined lecture capture as a way of enhancing university education, and explored how students with different learning approaches used lecture capturing (i.e., podcasts and vodcasts). Results indicate that both deep and surface learners report increased course satisfaction and better retention of knowledge in courses with traditional…
Deep and Surface Learning in Problem-Based Learning: A Review of the Literature

ERIC Educational Resources Information Center

Dolmans, Diana H. J. M.; Loyens, Sofie M. M.; Marcq, Hélène; Gijbels, David

2016-01-01

In problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested and try to understand what is being studied. This review…
Academic self-handicapping: the role of self-concept clarity and students' learning strategies.

PubMed

Thomas, Cathy R; Gadbois, Shannon A

2007-03-01

Self-handicapping is linked to students' personal motivations, classroom goal structure, academic outcomes, global self-esteem and certainty of self-esteem. Academic self-handicapping has yet to be studied with respect to students' consistency in self-description and their description of themselves as learners. This study examined students' self-esteem and self-concept clarity as well as their tendencies to employ deep- or surface-learning approaches and self-regulate while learning in relation to their self-handicapping tendencies and exam performance. Participants were 161 male and female Canadian, first-year university students. Participants completed a series of questionnaires that measured their self-esteem, self-concept clarity, approaches to learning, self-regulation and reflections on performance prior to and following their exam. Self-handicapping was negatively correlated with self-concept clarity, deep learning, self-regulated learning and exam grades, and positively correlated with surface learning and test anxiety. Regression analyses showed that self-concept clarity, self-regulation, surface-learning and test anxiety scores predicted self-handicapping scores. Self-concept clarity, test anxiety scores, academic self-efficacy and self-regulation were predictors of mid-term exam grades. This study showed that students' self-concept clarity and learning strategies are related to their tendencies to self-handicap and their exam performance. The role of students' ways of learning and their self-concept clarity in self-handicapping and academic performance was explored.
Academic Entitlement in the Context of Learning Styles

ERIC Educational Resources Information Center

Andrey, Jean; Joakim, Erin; Schoner, Vivian; Hambly, Derrick; Silver, Amber; Jayasundera, Rohan; Nelson, Allen

2012-01-01

This study explores the linkages between students' sense of entitlement and their approaches to learning, based on survey research at a large public university in Canada. Through literature review and pilot testing, a questionnaire instrument was developed that measures four constructs: academic entitlement, deep learning, surface learning and…
Changing the Metacognitive Orientation of a Classroom Environment to Stimulate Metacognitive Reflection Regarding the Nature of Physics Learning

ERIC Educational Resources Information Center

Thomas, Gregory P.

2013-01-01

Problems persist with physics learning in relation to students' understanding and use of representations for making sense of physics concepts. Further, students' views of physics learning and their physics learning processes have been predominantly found to reflect a "surface" approach to learning that focuses on mathematical aspects of…
Problem-Based Learning to Foster Deep Learning in Preservice Geography Teacher Education

ERIC Educational Resources Information Center

Golightly, Aubrey; Raath, Schalk

2015-01-01

In South Africa, geography education students' approach to deep learning has received little attention. Therefore the purpose of this one-shot experimental case study was to evaluate the extent to which first-year geography education students used deep or surface learning in an embedded problem-based learning (PBL) format. The researchers measured…

Learning Approaches of Undergraduate Computer Technology Students: Strategies for Improvement

ERIC Educational Resources Information Center

Malakolunthu, Suseela; Joshua, Alice

2012-01-01

Purpose: In recent times, quality of graduates and their performance has been questioned. Students' performance is an indicator of the kind of approach (deep or surface) that is taken. This study investigates the kind of undergraduates take in their learning processes. Methodology: This quantitative survey used Revised Two-Factor Study Process…
The Relationship among Student Basic Need Satisfaction, Approaches to Learning, Reporting of Avoidance Strategies and Achievement

ERIC Educational Resources Information Center

Betoret, Fernando Domenech; Artiga, Amparo Gomez

2011-01-01

Introduction: This study examines the relationship between student basic need satisfaction (autonomy, competence, relatedness and belonging), their reporting of approaches to learning (deep and surface), their reporting of avoidance strategies (avoidance of effort and challenge, avoidance of help seeking and preference to avoid novelty) and…
Is the University System in Australia Producing Deep Thinkers?

ERIC Educational Resources Information Center

Lake, Warren W.; Boyd, William E.

2015-01-01

Teaching and learning research since the 1980s has established a trend in students' learning approach tendencies, characterised by decreasing surface learning and increasing deep learning with increasing age. This is an important trend in higher education, especially at a time of increasing numbers of older students: are we graduating more deep…
How Enterprise Education Can Promote Deep Learning to Improve Student Employability

ERIC Educational Resources Information Center

Moon, Rob; Curtis, Vic; Dupernex, Simon

2013-01-01

This paper focuses on identifying the approaches students take to their learning, with particular regard to issues of enterprise, entrepreneurship and innovation when comparing the traditional lecture format to a more applied, practice-based case study format. The notions of deep and surface learning are used to explain student learning. More…
Making Information Systems Less Scrugged: Reflecting on the Processes of Change in Teaching and Learning

ERIC Educational Resources Information Center

Houghton, Luke; Ruth, Alison

2010-01-01

Deep and shallow learner approaches are useful for different purposes. Shallow learning can be good where fact memorization is appropriate, learning how to swim or play the guitar for example. Deep learning is much more appropriate when the learning material present involves going beyond simple facts and into what lies below the surface. When…
Emergence: Complexity Pedagogy in Action

PubMed Central

Jonas-Simpson, Christine

2015-01-01

Many educators are looking for new ways to engage students and each other in order to enrich curriculum and the teaching-learning process. We describe an example of how we enacted teaching-learning approaches through the insights of complexity thinking, an approach that supports the emergence of new possibilities for teaching-learning in the classroom and online. Our story begins with an occasion to meet with 10 nursing colleagues in a three-hour workshop using four activities that engaged learning about complexity thinking and pedagogy. Guiding concepts for the collaborative workshop were nonlinearity, distributed decision-making, divergent thinking, self-organization, emergence, and creative exploration. The workshop approach considered critical questions to spark our collective inquiry. We asked, “What is emergent learning?” and “How do we, as educators and learners, engage a community so that new learning surfaces?” We integrated the arts, creative play, and perturbations within a complexity approach. PMID:25838945
An Examination of the Interrelationships between Self-Esteem, Others' Expectations, Family Support, Learning Approaches and Academic Achievement

ERIC Educational Resources Information Center

Roman, Sergio; Cuestas, Pedro J.; Fenollar, Pedro

2008-01-01

The current research represents an initial step into the analysis of the effect of self-esteem, others' (peers and teachers) expectations and family support on academic achievement through learning approaches (deep processing, surface processing and effort). Data were gathered from 553 university students from different faculties of a Spanish…
Assessing Learning Quality: Reconciling Institutional, Staff and Educational Demands.

ERIC Educational Resources Information Center

Biggs, John

1996-01-01

Two frameworks for educational assessment distinguished, which is quantitative, adequate for construing some kinds of learning, and qualitative, which is more appropriate for most objectives in higher education. The paper argues that institutions implicitly encourage quantitative assessment, thus encouraging a surface approach to learning although…
Modeling Learning Processes in Lexical CALL.

ERIC Educational Resources Information Center

Goodfellow, Robin; Laurillard, Diana

1994-01-01

Studies the performance of a novice Spanish student using a Computer-assisted language learning (CALL) system designed for vocabulary enlargement. Results indicate that introspective evidence may be used to validate performance data within a theoretical framework that characterizes the learning approach as "surface" or "deep." (25 references)…
Strategies for Effective Faculty Involvement in Online Activities Aimed at Promoting Critical Thinking and Deep Learning

ERIC Educational Resources Information Center

Abdul Razzak, Nina

2016-01-01

Highly-traditional education systems that mainly offer what is known as "direct instruction" usually result in graduates with a surface approach to learning rather than a deep one. What is meant by deep-learning is learning that involves critical analysis, the linking of ideas and concepts, creative problem solving, and application…
Conceptual Framework to Help Promote Retention and Transfer in the Introductory Chemical Engineering Course

ERIC Educational Resources Information Center

Hanyak, Michael E., Jr.

2015-01-01

In an introductory chemical engineering course, the conceptual framework of a holistic problem-solving methodology in conjunction with a problem-based learning approach has been shown to create a learning environment that nurtures deep learning rather than surface learning. Based on exam scores, student grades are either the same or better than…
The context of learning anatomy: does it make a difference?

PubMed Central

Smith, Claire F; Martinez-Álvarez, Concepción; McHanwell, Stephen

2014-01-01

This study set out to ascertain whether the context in which anatomy is learnt made a difference to students' perceptions of learning. An Approach to Learning Inventory (ASSIST) and a 31-item Anatomy Learning Experience Questionnaire (ALE) were administered to 224 students (77 dental, 132 medical and 19 speech and language) as a multi-site study. Results revealed that 45% adopted a strategic, 39% a deep and 14% a surface approach. Trends between professions are similar for a deep or strategic approach (both ∼ 40%). However, a surface approach differed between professions (7% dentistry, 16% medicine, 26% speech and language science). Dental students responded more to being able to use their knowledge than did other groups (P = 0.0001). Medical students found the dissecting environment an intimidating one and subsequently reported finding online resources helpful (P = 0.015 and P = 0.003, respectively). Speech and language science students reported that they experienced greater difficulties with learning anatomy; they reported finding the amount to learn daunting (P = 0.007), struggled to remember what they did last semester (P = 0.032) and were not confident in their knowledge base (P = 0.0001). All students responded strongly to the statement ‘I feel that working with cadaveric material is an important part of becoming a doctor/dentist/health care professional’. A strong response to this statement was associated with students adopting a deep approach (P = 0.0001). This study has elucidated that local curriculum factors are important in creating an enabling learning environment. There are also a number of generic issues that can be identified as being inherent in the learning of anatomy as a discipline and are experienced across courses, different student groups and institutions. PMID:23930933
The context of learning anatomy: does it make a difference?

PubMed

Smith, Claire F; Martinez-Álvarez, Concepción; McHanwell, Stephen

2014-03-01

This study set out to ascertain whether the context in which anatomy is learnt made a difference to students' perceptions of learning. An Approach to Learning Inventory (ASSIST) and a 31-item Anatomy Learning Experience Questionnaire (ALE) were administered to 224 students (77 dental, 132 medical and 19 speech and language) as a multi-site study. Results revealed that 45% adopted a strategic, 39% a deep and 14% a surface approach. Trends between professions are similar for a deep or strategic approach (both ~ 40%). However, a surface approach differed between professions (7% dentistry, 16% medicine, 26% speech and language science). Dental students responded more to being able to use their knowledge than did other groups (P = 0.0001). Medical students found the dissecting environment an intimidating one and subsequently reported finding online resources helpful (P = 0.015 and P = 0.003, respectively). Speech and language science students reported that they experienced greater difficulties with learning anatomy; they reported finding the amount to learn daunting (P = 0.007), struggled to remember what they did last semester (P = 0.032) and were not confident in their knowledge base (P = 0.0001). All students responded strongly to the statement 'I feel that working with cadaveric material is an important part of becoming a doctor/dentist/health care professional'. A strong response to this statement was associated with students adopting a deep approach (P = 0.0001). This study has elucidated that local curriculum factors are important in creating an enabling learning environment. There are also a number of generic issues that can be identified as being inherent in the learning of anatomy as a discipline and are experienced across courses, different student groups and institutions. © 2013 Anatomical Society.
An approach to studying scale for students in higher education: a Rasch measurement model analysis.

PubMed

Waugh, R F; Hii, T K; Islam, A

2000-01-01

A questionnaire comprising 80 self-report items was designed to measure student Approaches to Studying in a higher education context. The items were conceptualized and designed from five learning orientations: a Deep Approach, a Surface Approach, a Strategic Approach, Clarity of Direction and Academic Self-Confidence, to include 40 attitude items and 40 corresponding behavior items. The study aimed to create a scale and investigate its psychometric properties using a Rasch measurement model. The convenience sample consisted of 350 students at an Australian university in 1998. The analysis supported the conceptual structure of the Scale as involving studying attitudes and behaviors towards five orientations to learning. Attitudes are mostly easier than behaviors, in line with the theory. Sixty-eight items fit the model and have good psychometric properties. The proportion of observed variance considered true is 92% and the Scale is well-targeted against the students. Some harder items are needed to improve the targeting and some further testing work needs to be done on the Surface Approach. In the Surface Approach and Clarity of Direction in Studying, attitudes make a lesser contribution than behaviors to the variable, Approaches to Studying.
Factorial Validity of a Questionnaire to Evaluate University Students' Initial Perception of Learning Evaluation

ERIC Educational Resources Information Center

Doménech-Betoret, Fernando; Fortea-Bagán, Miguel Angel

2015-01-01

Introduction: Education research has clearly verified that a student's perception of the system to evaluate the subject matter will play a fundamental role in his/her implication (deep approach vs. surface approach) in the teaching/learning process of the subject matter. The present work aims to examine the factorial validity and reliability of a…
Learning strategies during clerkships and their effects on clinical performance.

PubMed

van Lohuizen, M T; Kuks, J B M; van Hell, E A; Raat, A N; Cohen-Schotanus, J

2009-11-01

Previous research revealed relationships between learning strategies and knowledge acquisition. During clerkships, however, students' focus widens beyond mere knowledge acquisition as they further develop overall competence. This shift in focus can influence learning strategy use. We explored which learning strategies were used during clerkships and their relationship to clinical performance. Participants were 113 (78%) clerks at the university hospital or one of six affiliated hospitals. Learning strategies were assessed using the 'Approaches to Learning at Work Questionnaire' (deep, surface-rational and surface-disorganised learning). Clinical performance was calculated by taking the mean of clinical assessment marks. The relationship between learning strategies and clinical performance was explored using regression analysis. Most students (89%) did not clearly prefer a single learning strategy. No relationship was found between learning strategies and clinical performance. Since overall competence comprises integration of knowledge, skills and professional behaviour, we assume that students without a clear preference use more than one learning strategy. Finding no relationship between learning strategies and clinical performance reflects the complexity of clinical learning. Depending on circumstances it may be important to obtain relevant information quickly (surface-rational) or understand material thoroughly (deep). In future research we will examine when and why students use different learning strategies.
A mediation analysis of achievement motives, goals, learning strategies, and academic achievement.

PubMed

Diseth, Age; Kobbeltvedt, Therese

2010-12-01

Previous research is inconclusive regarding antecedents and consequences of achievement goals, and there is a need for more research in order to examine the joint effects of different types of motives and learning strategies as predictors of academic achievement. To investigate the relationship between achievement motives, achievement goals, learning strategies (deep, surface, and strategic), and academic achievement in a hierarchical model. Participants were 229 undergraduate students (mean age: 21.2 years) of psychology and economics at the University of Bergen, Norway. Variables were measured by means of items from the Achievement Motives Scale (AMS), the Approaches and Study Skills Inventory for Students, and an achievement goal scale. Correlation analysis showed that academic achievement (examination grade) was positively correlated with performance-approach goal, mastery goal, and strategic learning strategies, and negatively correlated with performance-avoidance goal and surface learning strategy. A path analysis (structural equation model) showed that achievement goals were mediators between achievement motives and learning strategies, and that strategic learning strategies mediated the relationship between achievement goals and academic achievement. This study integrated previous findings from several studies and provided new evidence on the direct and indirect effects of different types of motives and learning strategies as predictors of academic achievement.
[Efficacy of the program "Testas's (mis)adventures" to promote the deep approach to learning].

PubMed

Rosário, Pedro; González-Pienda, Julio Antonio; Cerezo, Rebeca; Pinto, Ricardo; Ferreira, Pedro; Abilio, Lourenço; Paiva, Olimpia

2010-11-01

This paper provides information about the efficacy of a tutorial training program intended to enhance elementary fifth graders' study processes and foster their deep approaches to learning. The program "Testas's (mis)adventures" consists of a set of books in which Testas, a typical student, reveals and reflects upon his life experiences during school years. These life stories are nothing but an opportunity to present and train a wide range of learning strategies and self-regulatory processes, designed to insure students' deeper preparation for present and future learning challenges. The program has been developed along a school year, in a one hour weekly tutorial sessions. The training program had a semi-experimental design, included an experimental group (n=50) and a control one (n=50), and used pre- and posttest measures (learning strategies' declarative knowledge, learning approaches and academic achievement). Data suggest that the students enrolled in the training program, comparing with students in the control group, showed a significant improvement in their declarative knowledge of learning strategies and in their deep approach to learning, consequently lowering their use of a surface approach. In spite of this, in what concerns to academic achievement, no statistically significant differences have been found.
Sophisticated Epistemologies of Physics versus High-Stakes Tests: How Do Elite High School Students Respond to Competing Influences about How to Learn Physics?

ERIC Educational Resources Information Center

Yerdelen-Damar, Sevda; Elby, Andrew

2016-01-01

This study investigates how elite Turkish high school physics students claim to approach learning physics when they are simultaneously (i) engaged in a curriculum that led to significant gains in their epistemological sophistication and (ii) subject to a high-stakes college entrance exam. Students reported taking surface (rote) approaches to…
Magnetic Field Measurements on the Lunar Surface: Lessons Learned from Apollo and Science Enabled by Future Missions

NASA Astrophysics Data System (ADS)

Chi, P. J.

2017-10-01

We discuss the science to be enabled by new magnetometer measurements on the lunar surface, based on results from Apollo and other lunar missions. Also discussed are approaches to deploying magnetometers on the lunar surface with today's technology.

Inversion of surface parameters using fast learning neural networks

NASA Technical Reports Server (NTRS)

Dawson, M. S.; Olvera, J.; Fung, A. K.; Manry, M. T.

1992-01-01

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.
Assessing Saudi medical students learning approach using the revised two-factor study process questionnaire.

PubMed

Shaik, Shaffi Ahamed; Almarzuqi, Ahmed; Almogheer, Rakan; Alharbi, Omar; Jalal, Abdulaziz; Alorainy, Majed

2017-08-17

To assess learning approaches of 1st, 2nd, and 3rd-year medical students by using revised two-factor study process questionnaire, and to assess reliability and validity of the questionnaire. This cross-sectional study was conducted at the College of Medicine, Riyadh, Saudi Arabia in 2014. The revised two-factor study process questionnaire (R-SPQ-2F) was completed by 610 medical students of both genders, from foundation (first year), central nervous system (second year), medicine and surgery (third year) courses. The study process was evaluated by computing mean scores of two research study approaches (deep & surface) using student's t-test and one-way analysis of variance. The internal consistency and construct validity of the questionnaire were assessed using Cronbach's α and factor analysis. The mean score of deep approach was significantly higher than the surface approach among participants(t (770) =7.83, p= 0.000) for the four courses. The mean scores of deep approach were significantly higher among participants with higher grade point average (F (2,768) =13.31, p=0.001) along with more number of study hours by participants (F (2,768) =20.08, p=0.001). The Cronbach's α-values of items at 0.70 indicate the good internal consistency of questionnaire used. Factor analysis confirms two factors (deep and surface approaches) of R-SPQ-2F. The deep approach to learning was the primary approach among 1st, 2nd and 3rd-year King Saud University medical students. This study confirms reliability and validity of the revised two-factor study process questionnaire. Medical educators could use the results of such studies to make required changes in the curriculum.
Workplace-based assessment and students' approaches to learning: a qualitative inquiry.

PubMed

Al-Kadri, Hanan M; Al-Kadi, Mohammed T; Van Der Vleuten, Cees P M

2013-01-01

We have performed this research to assess the effect of work-place based assessment (WBA) practice on medical students' learning approaches. The research was conducted at the King Saud bin Abdulaziz University for Health Sciences, College of Medicine from 1 March to 31 July 2012. We conducted a qualitative, phenomenological research utilizing semi-structured individual interviews with medical students exposed to WBA. The audio-taped interviews were transcribed verbatim, analyzed, and themes were identified. We preformed investigators' triangulation, member checking with clinical supervisors and we triangulated the data with a similar research performed prior to the implementation of WBA. WBA results in variable learning approaches. Based on several affecting factors; clinical supervisors, faculty-given feedback, and assessment function, students may swing between surface, deep and effort and achievement learning approaches. Students' and supervisors' orientations on the process of WBA, utilization of peer feedback and formative rather than summative assessment facilitate successful implementation of WBA and lead to students' deeper approaches to learning. Interestingly, students and their supervisors have contradicting perceptions to WBA. A change in culture to unify students' and supervisors' perceptions of WBA, more accommodation of formative assessment, and feedback may result in students' deeper approach to learning.
Impact of Faculty Development Workshops in Student-Centered Teaching Methodologies on Faculty Members' Teaching and Their Students' Perceptions.

PubMed

Tricio, Jorge A; Montt, Juan E; Ormeño, Andrea P; Del Real, Alberto J; Naranjo, Claudia A

2017-06-01

The aim of this study was to assess, after one year, the impact of faculty development in teaching and learning skills focused on a learner-centered approach on faculty members' perceptions of and approaches to teaching and on their students' learning experiences and approaches. Before training (2014), all 176 faculty members at a dental school in Chile were invited to complete the Approaches to Teaching Inventory (ATI) to assess their teaching approaches (student- vs. teacher-focused). In 2015, all 496 students were invited to complete the Study Process Questionnaire (R-SPQ-2F) to assess their learning approaches (deep or surface) and the Course Experience Questionnaire (CEQ) to measure their teaching quality perceptions. Subsequently, faculty development workshops on student-centered teaching methodologies were delivered, followed by peer observation. In March 2016, all 176 faculty members and 491 students were invited to complete a second ATI (faculty) and R-SPQ-2 and CEQ (students). Before (2014) and after (2016) the training, 114 (65%) and 116 (66%) faculty members completed the ATI, respectively, and 89 (49%) of the then-181 faculty members completed the perceptions of skills development questionnaire in September 2016. In 2015, 373 students (75%) completed the R-SPQ-2F and CEQ; 412 (83%) completed both questionnaires in 2016. In 2014, the faculty results showed that student-focused teaching was significantly higher in preclinical and clinical courses than in the basic sciences. In 2016, teacher-focused teaching fell significantly; basic science teaching improved the most. Students in both the 2015 and 2016 cohorts had lower mean scores for deep learning approaches from year 1 on, while they increased their scores for surface learning. The students' perceptions of faculty members' good teaching, appropriate assessment, clear goals, and e-learning improved significantly, but perception of appropriate workload did not. Teaching and learning skills development produced significant gains in student-centered teaching for these faculty members and in some students' perceptions of teaching quality. However, student workload needs to be considered to support deep learning.
Mathematical tasks, study approaches, and course grades in undergraduate mathematics: a year-by-year analysis

NASA Astrophysics Data System (ADS)

Maciejewski, Wes; Merchant, Sandra

2016-04-01

Students approach learning in different ways, depending on the experienced learning situation. A deep approach is geared toward long-term retention and conceptual change while a surface approach focuses on quickly acquiring knowledge for immediate use. These approaches ultimately affect the students' academic outcomes. This study takes a cross-sectional look at the approaches to learning used by students from courses across all four years of undergraduate mathematics and analyses how these relate to the students' grades. We find that deep learning correlates with grade in the first year and not in the upper years. Surficial learning has no correlation with grades in the first year and a strong negative correlation with grades in the upper years. Using Bloom's taxonomy, we argue that the nature of the tasks given to students is fundamentally different in lower and upper year courses. We find that first-year courses emphasize tasks that require only low-level cognitive processes. Upper year courses require higher level processes but, surprisingly, have a simultaneous greater emphasis on recall and understanding. These observations explain the differences in correlations between approaches to learning and course grades. We conclude with some concerns about the disconnect between first year and upper year mathematics courses and the effect this may have on students.
Surface-Charge-Based Micro-Models--A Solid Foundation for Learning about Direct Current Circuits

ERIC Educational Resources Information Center

Hirvonen, P. E.

2007-01-01

This study explores how the use of a surface-charge-based instructional approach affects introductory university level students' understanding of direct current (dc) circuits. The introduced teaching intervention includes electrostatics, surface-charge-based micro-models that explain the existence of an electric field inside the current-carrying…
[Effects of Learning Activities on Application of Learning Portfolio in Nursing Management Course].

PubMed

Choi, So Eun; Kim, Eun A

2016-02-01

This study was conducted to examine effects of a learning portfolio by identifying the learning of nursing students taking a learning portfolio-utilized nursing management class. A non-equivalent control group pretest-posttest design was used. Participants were 83 senior students taking the nursing management course in one of the Departments of Nursing at 2 Universities. Experimental group (n=42) received a learning portfolio-utilized nursing management class 15 times over 15 weeks (3 hours weekly). Self-directed learning abilities, approaches to learning and learning flow of the participants were examined with self-report structured questionnaires. Data were collected between September 2 and December 16, 2014, and were analyzed using chi-square test, Fisher's exact test, independent t-test and ANCOVA with SPSS/PC version 21.0. After the intervention the experimental group showed significant increases in self-directed learning abilities, deep approaches to learning and learning flow compared to the control group. However, no significant difference was found between groups for surface approaches to learning. Learning activities using the learning portfolios could be effective in cultivating the learning competency for growth of knowledge, technology and professionalism by increasing personal concentration and organization ability of the nursing students so that they can react to the rapidly changing environment.
The Gender Subtext of Organizational Learning

ERIC Educational Resources Information Center

Raaijmakers, Stephan; Bleijenbergh, Inge; Fokkinga, Brigit; Visser, Max

2018-01-01

Purpose: This paper aims to challenge the alleged gender-neutral character of Argyris and Schön's theory of organizational learning (1978). While theories in organizational science seem gender neutral at the surface, a closer analysis reveals they are often based on men's experiences. Design/methodology/approach: This paper uses the method of…
Diverse assessment and active student engagement sustain deep learning: A comparative study of outcomes in two parallel introductory biochemistry courses.

PubMed

Bevan, Samantha J; Chan, Cecilia W L; Tanner, Julian A

2014-01-01

Although there is increasing evidence for a relationship between courses that emphasize student engagement and achievement of student deep learning, there is a paucity of quantitative comparative studies in a biochemistry and molecular biology context. Here, we present a pedagogical study in two contrasting parallel biochemistry introductory courses to compare student surface and deep learning. Surface and deep learning were measured quantitatively by a study process questionnaire at the start and end of the semester, and qualitatively by questionnaires and interviews with students. In the traditional lecture/examination based course, there was a dramatic shift to surface learning approaches through the semester. In the course that emphasized student engagement and adopted multiple forms of assessment, a preference for deep learning was sustained with only a small reduction through the semester. Such evidence for the benefits of implementing student engagement and more diverse non-examination based assessment has important implications for the design, delivery, and renewal of introductory courses in biochemistry and molecular biology. © 2014 The International Union of Biochemistry and Molecular Biology.
Student Orientations to Independent Learning.

ERIC Educational Resources Information Center

Jones, Alice; Jones, Douglas

1996-01-01

A study investigated the relationship of 46 college students' preferred teaching method (conventional lecture versus independent study package) and their own approaches to study (surface, deep, achieving). Results indicated that while students preferred the conventional lecture method, preference did not correlate with their study approach and…
Condition monitoring of an electro-magnetic brake using an artificial neural network

NASA Astrophysics Data System (ADS)

Gofran, T.; Neugebauer, P.; Schramm, D.

2017-10-01

This paper presents a data-driven approach to Condition Monitoring of Electromagnetic brakes without use of additional sensors. For safe and efficient operation of electric motor a regular evaluation and replacement of the friction surface of the brake is required. One such evaluation method consists of direct or indirect sensing of the air-gap between pressure plate and magnet. A larger gap is generally indicative of worn surface(s). Traditionally this has been accomplished by the use of additional sensors - making existing systems complex, cost- sensitive and difficult to maintain. In this work a feed-forward Artificial Neural Network (ANN) is learned with the electrical data of the brake by supervised learning method to estimate the air-gap. The ANN model is optimized on the training set and validated using the test set. The experimental results of estimated air-gap with accuracy of over 95% demonstrate the validity of the proposed approach.
Gender neutrality improved completion rate for all

NASA Astrophysics Data System (ADS)

Svedin, Maria; Bälter, Olle

2016-07-01

The purpose of the present study was to investigate if we could improve retention by redesigning an online programming course from a gender perspective, while maintaining the focus on preferable and sustainable learning approaches. The study builds on results from an earlier study that investigated the relationship between approaches to learning and course completion and involves 1067 students that responded to the short version of the Approaches and Study Skills Inventory for Students (ASSIST) in 2010, 2012 and 2013. Three principles for course material design were identified; gender neutral and non-biased messages, emphasize the interdisciplinary approach and link to everyday examples. Responses to ASSIST were analysed in relation to performed changes in the course literature from a gender perspective. The probability to complete the course increased with 7% points for all students, in particular for men, and decreased for students with a high score in surface approach to learning, especially among women.
Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults

NASA Technical Reports Server (NTRS)

Spikovska, Lilly; Iverson, David L.; Poll, Scott; Pryor, anna

2005-01-01

Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and inform manual maneuver decisions. Our multi-modal display of this information provides speech output to issue control surface failure warnings to a lesser-used communication channel and provides graphical displays with pilot-selectable !eve!s of details to issues additional information about the failure. We also describe a potential presentation for flight envelope reduction that can be viewed separately or integrated with an existing attitude indicator instrument. Preliminary results suggest that the inductive approach is capable of detecting that a control surface has failed and determining the type of fault. Furthermore, preliminary evaluations suggest that the interface discloses a concise summary of this information to the pilot.
The Use of Smartphones in Different Phases of Medical School and its Relationship to Internet Addiction and Learning Approaches.

PubMed

Loredo E Silva, Mathias Paulo; de Souza Matos, Brenda Dutra; da Silva Ezequiel, Oscarina; Lucchetti, Alessandra Lamas Granero; Lucchetti, Giancarlo

2018-04-26

The use of smartphones is revolutionizing the way information is acquired, leading to profound modifications in teaching medicine. Nevertheless, inadvertent use can negatively affect student learning. The present study aims to evaluate smartphone use in the educational context as well as Internet addiction and its repercussions on surface and deep learning and to compare them during the different phases of medical students' education. This is a cross-sectional study involving medical students in all phases of education. Sociodemographic data, type and frequency of smartphone use, degree of digital addiction (Internet Addiction Test - IAT), and surface and deep approaches to learning (Biggs) were analyzed. A total of 710 students were included. Almost all students had a smartphone and a total of 96.8% used it during lectures, classes, and meetings. Less than half of the students (47.3%) reported using a smartphone for more than 10 min for educational purposes, a usage that is higher among clerkship students. At least 95% reported using a smartphone in the classroom for activities not related to medicine (social media and searching for general information) and 68.2% were considered problematic Internet users according to the IAT. The most common reasons for noneducational use were that the class was uninteresting, students needed to receive or make an important call, and the educational strategy was not stimulating. The "frequency of smartphone use" and higher "internet addiction" were correlated to both higher levels of surface learning and lower levels of deep learning. Educators should advise and educate their students about conscientious use of this tool to avoid detrimental impact on the learning process.
Profiling physicochemical and planktonic features from discretely/continuously sampled surface water.

PubMed

Oita, Azusa; Tsuboi, Yuuri; Date, Yasuhiro; Oshima, Takahiro; Sakata, Kenji; Yokoyama, Akiko; Moriya, Shigeharu; Kikuchi, Jun

2018-04-24

There is an increasing need for assessing aquatic ecosystems that are globally endangered. Since aquatic ecosystems are complex, integrated consideration of multiple factors utilizing omics technologies can help us better understand aquatic ecosystems. An integrated strategy linking three analytical (machine learning, factor mapping, and forecast-error-variance decomposition) approaches for extracting the features of surface water from datasets comprising ions, metabolites, and microorganisms is proposed herein. The three developed approaches can be employed for diverse datasets of sample sizes and experimentally analyzed factors. The three approaches are applied to explore the features of bay water surrounding Odaiba, Tokyo, Japan, as a case study. Firstly, the machine learning approach separated 681 surface water samples within Japan into three clusters, categorizing Odaiba water into seawater with relatively low inorganic ions, including Mg, Ba, and B. Secondly, the factor mapping approach illustrated Odaiba water samples from the summer as rich in multiple amino acids and some other metabolites and poor in inorganic ions relative to other seasons based on their seasonal dynamics. Finally, forecast-error-variance decomposition using vector autoregressive models indicated that a type of microalgae (Raphidophyceae) grows in close correlation with alanine, succinic acid, and valine on filters and with isobutyric acid and 4-hydroxybenzoic acid in filtrate, Ba, and average wind speed. Our integrated strategy can be used to examine many biological, chemical, and environmental physical factors to analyze surface water. Copyright © 2018. Published by Elsevier B.V.
Effects of different forms of physiology instruction on the development of students' conceptions of and approaches to science learning.

PubMed

Lin, Yi-Hui; Liang, Jyh-Chong; Tsai, Chin-Chung

2012-03-01

The purpose of this study was to investigate students' conceptions of and approaches to learning science in two different forms: internet-assisted instruction and traditional (face-to-face only) instruction. The participants who took part in the study were 79 college students enrolled in a physiology class in north Taiwan. In all, 46 of the participants were from one class and 33 were from another class. Using a quasi-experimental research approach, the class of 46 students was assigned to be the "internet-assisted instruction group," whereas the class of 33 students was assigned to be the "traditional instruction group." The treatment consisted of a series of online inquiry activities. To explore the effects of different forms of instruction on students' conceptions of and approaches to learning science, two questionnaires were administered before and after the instruction: the Conceptions of Learning Science Questionnaire and the Approaches to Learning Science Questionnaire. Analysis of covariance results revealed that the students in the internet-assisted instruction group showed less agreement than the traditional instruction group in the less advanced conceptions of learning science (such as learning as memorizing and testing). In addition, the internet-assisted instruction group displayed significantly more agreement than the traditional instruction group in more sophisticated conceptions (such as learning as seeing in a new way). Moreover, the internet-assisted instruction group expressed more orientation toward the approaches of deep motive and deep strategy than the traditional instruction group. However, the students in the internet-assisted instruction group also showed more surface motive than the traditional instruction group did.
Acceleration of saddle-point searches with machine learning.

PubMed

Peterson, Andrew A

2016-08-21

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.
Acceleration of saddle-point searches with machine learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Andrew A., E-mail: andrew-peterson@brown.edu

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the numbermore » of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.« less
Integration of the subsurface and the surface sectors for a more holistic approach for sustainable redevelopment of urban brownfields.

PubMed

Norrman, Jenny; Volchko, Yevheniya; Hooimeijer, Fransje; Maring, Linda; Kain, Jaan-Henrik; Bardos, Paul; Broekx, Steven; Beames, Alistair; Rosén, Lars

2016-09-01

This paper presents a holistic approach to sustainable urban brownfield redevelopment where specific focus is put on the integration of a multitude of subsurface qualities in the early phases of the urban redevelopment process, i.e. in the initiative and plan phases. Achieving sustainability in brownfield redevelopment projects may be constrained by a failure of engagement between two key expert constituencies: urban planners/designers and subsurface engineers, leading to missed opportunities and unintended outcomes in the plan realisation phase. A more integrated approach delivers greater benefits. Three case studies in the Netherlands, Belgium and Sweden were used to test different sustainability assessment instruments in terms of the possibility for knowledge exchange between the subsurface and the surface sectors and in terms of cooperative learning among experts and stakeholders. Based on the lessons learned from the case studies, a generic decision process framework is suggested that supports holistic decision making. The suggested framework focuses on stakeholder involvement, communication, knowledge exchange and learning and provides an inventory of instruments that can support these processes. Copyright © 2016 Elsevier B.V. All rights reserved.
Automatic multi-organ segmentation using learning-based segmentation and level set optimization.

PubMed

Kohlberger, Timo; Sofka, Michal; Zhang, Jingdan; Birkbeck, Neil; Wetzl, Jens; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

We present a novel generic segmentation system for the fully automatic multi-organ segmentation from CT medical images. Thereby we combine the advantages of learning-based approaches on point cloud-based shape representation, such a speed, robustness, point correspondences, with those of PDE-optimization-based level set approaches, such as high accuracy and the straightforward prevention of segment overlaps. In a benchmark on 10-100 annotated datasets for the liver, the lungs, and the kidneys we show that the proposed system yields segmentation accuracies of 1.17-2.89 mm average surface errors. Thereby the level set segmentation (which is initialized by the learning-based segmentations) contributes with an 20%-40% increase in accuracy.

Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force

NASA Astrophysics Data System (ADS)

Sivalingam, Udhayaraj; Wels, Michael; Rempfler, Markus; Grosskopf, Stefan; Suehling, Michael; Menze, Bjoern H.

2016-03-01

In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing Active Contour Model-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the active contour model, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).
A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles.

PubMed

Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng

2016-05-01

In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.
Student-centered integrated anatomy resource sessions at Alfaisal University.

PubMed

Cowan, Michèle; Arain, Nasir Nisar; Assale, Tawfic Samer Abu; Assi, Abdulelah Hassan; Albar, Raed Alwai; Ganguly, Paul K

2010-01-01

Alfaisal University is a new medical school in Riyadh, Kingdom of Saudi Arabia that matriculates eligible students directly from high school and requires them to participate in a hybrid problem-based learning (PBL) curriculum. PBL is a well-established student-centered approach, and the authors have sought to examine if a student-centered, integrated approach to learn human structures leads to positive perceptions of learning outcomes. Ten students were divided into four groups to rotate through wet and dry laboratory stations (integrated resource sessions, IRSs) that engaged them in imaging techniques, embryology, histology, gross anatomy (dissections and prosections), surface anatomy, and self-directed learning questions. All IRSs were primarily directed by students. During two second-semester organ system blocks, forty students responded to a structured questionnaire designed to poll students' perceptions of changes in their knowledge, skills, and attitudes as a result of IRS. The majority (60%) of students felt that the student-centered approach to learning enhanced their medical knowledge. Most students also felt that the IRS approach was advantageous for formulating clear learning objectives (55%) and in preparing for examinations (65%). Despite their positive feelings toward IRS, students did not view this learning approach as an adequate replacement for the knowledge gained from lectures and textbooks. Students' performance on objective structured practical examinations improved significantly for the two curricular blocks that included IRS compared with earlier non-IRS blocks. A student-centered approach to teach human structure in a hybrid PBL curriculum may enhance understanding of the basic sciences in first-year medical students.
Automated discovery and construction of surface phase diagrams using machine learning

DOE PAGES

Ulissi, Zachary W.; Singh, Aayush R.; Tsai, Charlie; ...

2016-08-24

Surface phase diagrams are necessary for understanding surface chemistry in electrochemical catalysis, where a range of adsorbates and coverages exist at varying applied potentials. These diagrams are typically constructed using intuition, which risks missing complex coverages and configurations at potentials of interest. More accurate cluster expansion methods are often difficult to implement quickly for new surfaces. We adopt a machine learning approach to rectify both issues. Using a Gaussian process regression model, the free energy of all possible adsorbate coverages for surfaces is predicted for a finite number of adsorption sites. Our result demonstrates a rational, simple, and systematic approachmore » for generating accurate free-energy diagrams with reduced computational resources. Finally, the Pourbaix diagram for the IrO 2(110) surface (with nine coverages from fully hydrogenated to fully oxygenated surfaces) is reconstructed using just 20 electronic structure relaxations, compared to approximately 90 using typical search methods. Similar efficiency is demonstrated for the MoS 2 surface.« less
Retrieving Temperature Anomaly in the Global Subsurface and Deeper Ocean From Satellite Observations

NASA Astrophysics Data System (ADS)

Su, Hua; Li, Wene; Yan, Xiao-Hai

2018-01-01

Retrieving the subsurface and deeper ocean (SDO) dynamic parameters from satellite observations is crucial for effectively understanding ocean interior anomalies and dynamic processes, but it is challenging to accurately estimate the subsurface thermal structure over the global scale from sea surface parameters. This study proposes a new approach based on Random Forest (RF) machine learning to retrieve subsurface temperature anomaly (STA) in the global ocean from multisource satellite observations including sea surface height anomaly (SSHA), sea surface temperature anomaly (SSTA), sea surface salinity anomaly (SSSA), and sea surface wind anomaly (SSWA) via in situ Argo data for RF training and testing. RF machine-learning approach can accurately retrieve the STA in the global ocean from satellite observations of sea surface parameters (SSHA, SSTA, SSSA, SSWA). The Argo STA data were used to validate the accuracy and reliability of the results from the RF model. The results indicated that SSHA, SSTA, SSSA, and SSWA together are useful parameters for detecting SDO thermal information and obtaining accurate STA estimations. The proposed method also outperformed support vector regression (SVR) in global STA estimation. It will be a useful technique for studying SDO thermal variability and its role in global climate system from global-scale satellite observations.
Learning in fully recurrent neural networks by approaching tangent planes to constraint surfaces.

PubMed

May, P; Zhou, E; Lee, C W

2012-10-01

In this paper we present a new variant of the online real time recurrent learning algorithm proposed by Williams and Zipser (1989). Whilst the original algorithm utilises gradient information to guide the search towards the minimum training error, it is very slow in most applications and often gets stuck in local minima of the search space. It is also sensitive to the choice of learning rate and requires careful tuning. The new variant adjusts weights by moving to the tangent planes to constraint surfaces. It is simple to implement and requires no parameters to be set manually. Experimental results show that this new algorithm gives significantly faster convergence whilst avoiding problems like local minima. Copyright © 2012 Elsevier Ltd. All rights reserved.
Flipped Classrooms and Student Learning: Not Just Surface Gains

ERIC Educational Resources Information Center

McLean, Sarah; Attardi, Stefanie M.; Faden, Lisa; Goldszmidt, Mark

2016-01-01

The flipped classroom is a relatively new approach to undergraduate teaching in science. This approach repurposes class time to focus on application and discussion; the acquisition of basic concepts and principles is done on the students' own time before class. While current flipped classroom research has focused on student preferences and…
Attitudes and Perceptions of Medical Undergraduates Towards Mobile Learning (M-learning).

PubMed

Patil, Rakesh Narayan; Almale, Balaji D; Patil, Mrunal; Gujrathi, Amit; Dhakne-Palwe, Supriya; Patil, Anuradha R; Gosavi, Shriram

2016-10-01

Mobile technology is one of the latest extensions of technological innovations that can be integrated into medical education. With the aid of these devices, students learn faster outside the classroom by having quick access to the internet and easy retrieval of required health related learning resources to keep alongside of recent trend and development. In medicine practice one has to continuously update his/her medical knowledge and mobile learning will serve as a tool for self-directed learning. To explore the attitudes and perceptions of undergraduate students towards M-learning. This educational research included 90 third year MBBS students having clinical posting under the Department of Community Medicine from tertiary healthcare institute in Nashik. Students learning approach was studied with the help of pre-validated questionnaire to know whether they have deep or surface approach to learning. M-learning group was formed on mobile social app to supplement conventional teaching-learning. One subject topic (Tuberculosis, Dengue fever/DHF, Hypertension and Diabetes Mellitus etc.) per week was allotted and after conventional teaching on first day of week the learning materials for the topic chosen for that week were uploaded on the group and students could download as well as share their ideas, learning resources, ask doubts and answer questions at least twice weekly through this mobile platform anytime, anywhere. At the end of three months students attitudes and perceptions towards M-learning were studied by pre-validated structured questionnaires. A five point Likert scale was used (5= strongly agree to 1= strongly disagree) for answering each item of all three questionnaires. The score of 60% (90 out of 150) and the score of 75% (30 out of 40) for each item was considered as the measure that indicates whether or not the student had a positive attitude and perceived the importance of M-learning respectively. Utilisation of M-learning was also studied. It was found that 47 (52.2%) students had deep learning approach, 10 (11.1%) students had surface learning approach. An 80% of students had positive attitude towards M-learning and 76.7% students had perceived the importance of M-learning. A 52.2% of students were actively involved in M-learning group for learning purpose. But 57.8% students did not download (at least twice weekly) the shared reference material, 38.9% students never read and/or replied to the questions asked and 60.0% students never asked any doubts/questions related to the discussion. Students had positive attitude and perceived the importance of M-learning. But when they were provided with the opportunity, they did not show appreciable M-learning utilization. This could be because, M-learning was not implemented by all departments; also it was not the part of student's regular assessment and probably a lesser study duration.
Attitudes and Perceptions of Medical Undergraduates Towards Mobile Learning (M-learning)

PubMed Central

Almale, Balaji D; Patil, Mrunal; Gujrathi, Amit; Dhakne-Palwe, Supriya; Patil, Anuradha R; Gosavi, Shriram

2016-01-01

Introduction Mobile technology is one of the latest extensions of technological innovations that can be integrated into medical education. With the aid of these devices, students learn faster outside the classroom by having quick access to the internet and easy retrieval of required health related learning resources to keep alongside of recent trend and development. In medicine practice one has to continuously update his/her medical knowledge and mobile learning will serve as a tool for self-directed learning. Aim To explore the attitudes and perceptions of undergraduate students towards M-learning. Materials and Methods This educational research included 90 third year MBBS students having clinical posting under the Department of Community Medicine from tertiary healthcare institute in Nashik. Students learning approach was studied with the help of pre-validated questionnaire to know whether they have deep or surface approach to learning. M-learning group was formed on mobile social app to supplement conventional teaching-learning. One subject topic (Tuberculosis, Dengue fever/DHF, Hypertension and Diabetes Mellitus etc.) per week was allotted and after conventional teaching on first day of week the learning materials for the topic chosen for that week were uploaded on the group and students could download as well as share their ideas, learning resources, ask doubts and answer questions at least twice weekly through this mobile platform anytime, anywhere. At the end of three months students attitudes and perceptions towards M-learning were studied by pre-validated structured questionnaires. A five point Likert scale was used (5= strongly agree to 1= strongly disagree) for answering each item of all three questionnaires. The score of 60% (90 out of 150) and the score of 75% (30 out of 40) for each item was considered as the measure that indicates whether or not the student had a positive attitude and perceived the importance of M-learning respectively. Utilisation of M-learning was also studied. Results It was found that 47 (52.2%) students had deep learning approach, 10 (11.1%) students had surface learning approach. An 80% of students had positive attitude towards M-learning and 76.7% students had perceived the importance of M-learning. A 52.2% of students were actively involved in M-learning group for learning purpose. But 57.8% students did not download (at least twice weekly) the shared reference material, 38.9% students never read and/or replied to the questions asked and 60.0% students never asked any doubts/questions related to the discussion. Conclusion Students had positive attitude and perceived the importance of M-learning. But when they were provided with the opportunity, they did not show appreciable M-learning utilization. This could be because, M-learning was not implemented by all departments; also it was not the part of student’s regular assessment and probably a lesser study duration. PMID:27891356
Prediction of Bispectral Index during Target-controlled Infusion of Propofol and Remifentanil: A Deep Learning Approach.

PubMed

Lee, Hyung-Chul; Ryu, Ho-Geol; Chung, Eun-Jin; Jung, Chul-Woo

2018-03-01

The discrepancy between predicted effect-site concentration and measured bispectral index is problematic during intravenous anesthesia with target-controlled infusion of propofol and remifentanil. We hypothesized that bispectral index during total intravenous anesthesia would be more accurately predicted by a deep learning approach. Long short-term memory and the feed-forward neural network were sequenced to simulate the pharmacokinetic and pharmacodynamic parts of an empirical model, respectively, to predict intraoperative bispectral index during combined use of propofol and remifentanil. Inputs of long short-term memory were infusion histories of propofol and remifentanil, which were retrieved from target-controlled infusion pumps for 1,800 s at 10-s intervals. Inputs of the feed-forward network were the outputs of long short-term memory and demographic data such as age, sex, weight, and height. The final output of the feed-forward network was the bispectral index. The performance of bispectral index prediction was compared between the deep learning model and previously reported response surface model. The model hyperparameters comprised 8 memory cells in the long short-term memory layer and 16 nodes in the hidden layer of the feed-forward network. The model training and testing were performed with separate data sets of 131 and 100 cases. The concordance correlation coefficient (95% CI) were 0.561 (0.560 to 0.562) in the deep learning model, which was significantly larger than that in the response surface model (0.265 [0.263 to 0.266], P < 0.001). The deep learning model-predicted bispectral index during target-controlled infusion of propofol and remifentanil more accurately compared to the traditional model. The deep learning approach in anesthetic pharmacology seems promising because of its excellent performance and extensibility.
The structure of observed learning outcome (SOLO) taxonomy: a model to promote dental students' learning.

PubMed

Lucander, H; Bondemark, L; Brown, G; Knutsson, K

2010-08-01

Selective memorising of isolated facts or reproducing what is thought to be required - the surface approach to learning - is not the desired outcome for a dental student or a dentist in practice. The preferred outcome is a deep approach as defined by an intention to seek understanding, develop expertise and relate information and knowledge into a coherent whole. The aim of this study was to investigate whether the structure of observed learning outcome (SOLO) taxonomy could be used as a model to assist and promote the dental students to develop a deep approach to learning assessed as learning outcomes in a summative assessment. Thirty-two students, participating in course eight in 2007 at the Faculty of Odontology at Malmö University, were introduced to the SOLO taxonomy and constituted the test group. The control group consisted of 35 students participating in course eight in 2006. The effect of the introduction was measured by evaluating responses to a question in the summative assessment by using the SOLO taxonomy. The evaluators consisted of two teachers who performed the assessment of learning outcomes independently and separately on the coded material. The SOLO taxonomy as a model for learning was found to improve the quality of learning. Compared to the control group significantly more strings and structured relations between these strings were present in the test group after the SOLO taxonomy had been introduced (P < 0.01, one tailed test for both results). The SOLO taxonomy is recommended as a model for promoting and developing a deeper approach to learning in dentistry.
An Information Retrieval Approach for Robust Prediction of Road Surface States.

PubMed

Park, Jae-Hyung; Kim, Kwanho

2017-01-28

Recently, due to the increasing importance of reducing severe vehicle accidents on roads (especially on highways), the automatic identification of road surface conditions, and the provisioning of such information to drivers in advance, have recently been gaining significant momentum as a proactive solution to decrease the number of vehicle accidents. In this paper, we firstly propose an information retrieval approach that aims to identify road surface states by combining conventional machine-learning techniques and moving average methods. Specifically, when signal information is received from a radar system, our approach attempts to estimate the current state of the road surface based on the similar instances observed previously based on utilizing a given similarity function. Next, the estimated state is then calibrated by using the recently estimated states to yield both effective and robust prediction results. To validate the performances of the proposed approach, we established a real-world experimental setting on a section of actual highway in South Korea and conducted a comparison with the conventional approaches in terms of accuracy. The experimental results show that the proposed approach successfully outperforms the previously developed methods.
An Information Retrieval Approach for Robust Prediction of Road Surface States

PubMed Central

Park, Jae-Hyung; Kim, Kwanho

2017-01-01

Recently, due to the increasing importance of reducing severe vehicle accidents on roads (especially on highways), the automatic identification of road surface conditions, and the provisioning of such information to drivers in advance, have recently been gaining significant momentum as a proactive solution to decrease the number of vehicle accidents. In this paper, we firstly propose an information retrieval approach that aims to identify road surface states by combining conventional machine-learning techniques and moving average methods. Specifically, when signal information is received from a radar system, our approach attempts to estimate the current state of the road surface based on the similar instances observed previously based on utilizing a given similarity function. Next, the estimated state is then calibrated by using the recently estimated states to yield both effective and robust prediction results. To validate the performances of the proposed approach, we established a real-world experimental setting on a section of actual highway in South Korea and conducted a comparison with the conventional approaches in terms of accuracy. The experimental results show that the proposed approach successfully outperforms the previously developed methods. PMID:28134859
Deep dissection: motivating students beyond rote learning in veterinary anatomy.

PubMed

Cake, Martin A

2006-01-01

The profusion of descriptive, factual information in veterinary anatomy inevitably creates pressure on students to employ surface learning approaches and "rote learning." This phenomenon may contribute to negative perceptions of the relevance of anatomy as a discipline. Thus, encouraging deep learning outcomes will not only lead to greater satisfaction for both instructors and learners but may have the added effect of raising the profile of and respect for the discipline. Consideration of the literature reveals the broad scope of interventions required to motivate students to go beyond rote learning. While many of these are common to all disciplines (e.g., promoting active learning, making higher-order goals explicit, reducing content in favor of concepts, aligning assessment with outcomes), other factors are peculiar to anatomy, such as the benefits of incorporating clinical tidbits, "living anatomy," the anatomy museum, and dissection classes into a "learning context" that fosters deep approaches. Surprisingly, the 10 interventions discussed focus more on factors contributing to student perceptions of the course than on drastic changes to the anatomy course itself. This is because many traditional anatomy practices, such as dissection and museum-based classes, are eminently compatible with active, student-centered learning strategies and the adoption of deep learning approaches by veterinary students. Thus the key to encouraging, for example, dissection for deep learning ("deep dissection") lies more in student motivation, personal engagement, curriculum structure, and "learning context" than in the nature of the learning activity itself.
Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training

PubMed Central

Kutafina, Ekaterina; Laukamp, David; Bettermann, Ralf; Schroeder, Ulrik; Jonas, Stephan M.

2016-01-01

In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user’s hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98.30% (±1.26%) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills. PMID:27527167
Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training.

PubMed

Kutafina, Ekaterina; Laukamp, David; Bettermann, Ralf; Schroeder, Ulrik; Jonas, Stephan M

2016-08-03

In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user's hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98 . 30 % ( ± 1 . 26 % ) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills.
Structure identification in fuzzy inference using reinforcement learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap

1993-01-01

In our previous work on the GARIC architecture, we have shown that the system can start with surface structure of the knowledge base (i.e., the linguistic expression of the rules) and learn the deep structure (i.e., the fuzzy membership functions of the labels used in the rules) by using reinforcement learning. Assuming the surface structure, GARIC refines the fuzzy membership functions used in the consequents of the rules using a gradient descent procedure. This hybrid fuzzy logic and reinforcement learning approach can learn to balance a cart-pole system and to backup a truck to its docking location after a few trials. In this paper, we discuss how to do structure identification using reinforcement learning in fuzzy inference systems. This involves identifying both surface as well as deep structure of the knowledge base. The term set of fuzzy linguistic labels used in describing the values of each control variable must be derived. In this process, splitting a label refers to creating new labels which are more granular than the original label and merging two labels creates a more general label. Splitting and merging of labels directly transform the structure of the action selection network used in GARIC by increasing or decreasing the number of hidden layer nodes.
Teaching neuroanatomy using computer-aided learning: What makes for successful outcomes?

PubMed

Svirko, Elena; Mellanby, Jane

2017-11-01

Computer-aided learning (CAL) is an integral part of many medical courses. The neuroscience course at Oxford University for medical students includes CAL course of neuroanatomy. CAL is particularly suited to this since neuroanatomy requires much detailed three-dimensional visualization, which can be presented on screen. The CAL course was evaluated using the concept of approach to learning. The aims of university teaching are congruent with the deep approach-seeking meaning and relating new information to previous knowledge-rather than to the surface approach of concentrating on rote learning of detail. Seven cohorts of medical students (N = 869) filled in approach to learning scale and a questionnaire investigating their engagement with the CAL course. The students' scores on CAL-course-based neuroanatomy assessment and later university examinations were obtained. Although the students reported less use of the deep approach for the neuroanatomy CAL course than for the rest of their neuroanatomy course (mean = 24.99 vs. 31.49, P < 0.001), deep approach for CAL was positively correlated with neuroanatomy assessment performance (r = 0.12, P < 0.001). Time spent on the CAL course, enjoyment of it, the amount of CAL videos watched and quizzes completed were each significantly positively related to deep approach. The relationship between deep approach and enjoyment was particularly notable (25.5% shared variance). Reported relationships between deep approach and academic performance support the desirability of deep approach in university students. It is proposed that enjoyment of the course and the deep approach could be increased by incorporation of more clinical material which is what the students liked most. Anat Sci Educ 10: 560-569. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.
Re-approaching global iodine emissions: A novel parameterisation for sea-surface iodide concentrations using a machine learning approach

NASA Astrophysics Data System (ADS)

Sherwen, T.; Evans, M. J.; Chance, R.; Tinel, L.; Carpenter, L.

2017-12-01

Halogens (Cl, Br, I) in the troposphere have been shown to play a profound role in determining the concentrations of ozone and OH. Iodine, which is essentially oceanic in source, exerts its largest impacts on composition in both the marine boundary layer, and in the upper troposphere. This chemistry has only recently been implemented into global models and significant uncertainties remain, particularly regarding the magnitude of iodine emissions. Iodine emissions are dominated by the inorganic oxidation of iodide in the sea surface by ozone, which leads to release of gaseous inorganic iodine (HOI, I2). Critical for calculation of these fluxes is the sea-surface concentration of iodide, which is poorly constrained by observations. Previous parameterizations for sea-surface iodide concentration have focused on simple regressive relationships with sea surface temperature and another single oceanographic variables. This leads to differences in iodine fluxes of approximately a factor of two, and leads to substantial differences in the modelled impact of iodine on atmospheric composition. Here we use an expanded dataset of oceanic iodide observations, which incorporates new data that has been targeted at areas with poor coverage previously. A novel approach of multivariate machine learning techniques is applied to this expanded dataset to generate a model that yields improved estimates of the global sea surface iodide distribution. We then use a global chemical transport model (GEOS-Chem) to explore the impact of this new parameterisation on the atmospheric budget of iodine and its impact on tropospheric composition.
Machine Learning of Accurate Energy-Conserving Molecular Force Fields

NASA Astrophysics Data System (ADS)

Chmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel; Poltavsky, Igor; Schütt, Kristof; Müller, Klaus-Robert; GDML Collaboration

Efficient and accurate access to the Born-Oppenheimer potential energy surface (PES) is essential for long time scale molecular dynamics (MD) simulations. Using conservation of energy - a fundamental property of closed classical and quantum mechanical systems - we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio MD trajectories (AIMD). The GDML implementation is able to reproduce global potential-energy surfaces of intermediate-size molecules with an accuracy of 0.3 kcal/mol for energies and 1 kcal/mol/Å for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, malonaldehyde, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative MD simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods.

"Come, Follow Me": Apprenticeship in Jesus' Approach to Education

ERIC Educational Resources Information Center

Csinos, David M.

2010-01-01

Over the years, there has been a great deal of scholarly work focusing of the life, teaching, and ministry of Jesus. In this article, the author contributes to this body of literature by examining Jesus' ministry through the lens of legitimate peripheral participation, an approach to learning that surfaced during the last decade of the 20th…
Design Interactive: A Nonlinear, Multimedia Approach to Teaching Introduction to Visual Communication and Principles of Design

ERIC Educational Resources Information Center

Palilonis, Jennifer; Butler, Darrell; Leidig-Farmen, Pamela

2013-01-01

As online teaching techniques continue to evolve, new opportunities surface for research and insight regarding best practices for the development and implementation of interactive, multimedia teaching and learning tools. These tools are particularly attractive for courses that lend themselves to a rich media approach. Such is the case for visual…
Learning environment, approaches to learning and learning preferences: medical students versus general education students.

PubMed

Ullah, Raza

2016-05-01

The main objective of the study was to see whether medical students use more desirable approaches to studying than general education students. Survey method was used to collect data from both the medical students and the general education students. The survey of the medical students was carried out between January and March, 2012. The survey was administered to all the medical students present in lecture halls on day of data collection, while general education students were randomly selected from four subject areas at two universities. In total, 976 medical students and 912 general students participated in the study. Of the general students, 494(54%) were boys and 418(46%)were girls with an overall mean age of 20.53±1.77 years (range: 17-27 years). The medical students' perceptions of their learning environment and their learning preferences were broadly similar to that of general education students with the exception of workload. The medical students perceived the workload to be less appropriate (Mean = 2.06±0.72) than the students in general education (Mean = 2.84±0.90). The medical students were more likely to use the deep approach to studying (Mean = 3.66±0.59) than the students in general education (Mean = 3.16±0.91). The students in general education were slightly more likely to use the organized studying (Mean = 3.44±0.90) than the medical students (Mean =3.23±0.90). Both medical students and the students in general education tended to use the surface approaches along with other approaches to studying. There was not a great difference between the medical students and the students pursuing general education with regard to perceptions of the learning environment and approaches to learning.
The Impact of Unstructured Case Studies on Surface Learners: A Study of Second-Year Accounting Students

ERIC Educational Resources Information Center

Wynn-Williams, Kate; Beatson, Nicola; Anderson, Cameron

2016-01-01

The empirical study described here uses the R-SPQ-2F questionnaire [Biggs, J., Kember, D., & Leung, D. Y. (2001). The revised two-factor study process questionnaire: R-SPQ-2F. "British Journal of Educational Psychology," 71(1), 133-149] to test deep and surface approaches to learning in a university intermediate-level accounting…
Nonlinear programming for classification problems in machine learning

NASA Astrophysics Data System (ADS)

Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio

2016-10-01

We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.
A guide to using case-based learning in biochemistry education.

PubMed

Kulak, Verena; Newton, Genevieve

2014-01-01

Studies indicate that the majority of students in undergraduate biochemistry take a surface approach to learning, associated with rote memorization of material, rather than a deep approach, which implies higher cognitive processing. This behavior relates to poorer outcomes, including impaired course performance and reduced knowledge retention. The use of case-based learning (CBL) into biochemistry teaching may facilitate deep learning by increasing student engagement and interest. Abundant literature on CBL exists but clear guidance on how to design and implement case studies is not readily available. This guide provides a representative review of CBL uses in science and describes the process of developing CBL modules to be used in biochemistry. Included is a framework to implement a directed CBL assisted with lectures in a content-driven biochemistry course regardless of class size. Moreover, this guide can facilitate adopting CBL to other courses. Consequently, the information presented herein will be of value to undergraduate science educators with an interest in active learning pedagogies. © 2014 The International Union of Biochemistry and Molecular Biology.
The Systems Engineering Approach to Mechanical Failure Prevention. Proceedings of the Meeting of the Mechanical Failures Prevention Group (47th) Held in Virginia Beach, Virginia on April 13-15, 1993.

DTIC Science & Technology

1993-04-15

Czyryca from the Naval Surface Warfare Center gave a Plenary Aodress on Lessons Learned in Metallurgical Failure Analyses of Naval Machinery. The...processing methods take many years to implement, because of the large capital investments and the learning process involved, we feel confident that they will...signals experienced by the self. Filters are an indistinguishable part of the self. As we learn about the causes of our failures, and see that we can
Telling Stories, Landing Planes and Getting Them Moving--A Holistic Approach to Developing Students' Statistical Literacy

ERIC Educational Resources Information Center

Jones, Julie Scott; Goldring, John E.

2017-01-01

The issue of poor statistical literacy amongst undergraduates in the United Kingdom is well documented. At university level, where poor statistics skills impact particularly on social science programmes, embedding is often used as a remedy. However, embedding represents a surface approach to the problem. It ignores the barriers to learning that…
Conceptions of Biology and Approaches to Learning of First Year Biology Students: Introducing a Technique for Tracking Changes in Learner Profiles over Time

ERIC Educational Resources Information Center

Quinnell, Rosanne; May, Elizabeth; Peat, Mary

2012-01-01

We surveyed first year students at the start and at the end of their first semester of university biology (n = 285) as to their approaches to study ("surface", "deep") and their conceptions of biology ("fragmented", "cohesive"). Hierarchical cluster analysis was used to group students who responded similarly…
Hippocampal LTP and contextual learning require surface diffusion of AMPA receptors.

PubMed

Penn, A C; Zhang, C L; Georges, F; Royer, L; Breillat, C; Hosy, E; Petersen, J D; Humeau, Y; Choquet, D

2017-09-21

Long-term potentiation (LTP) of excitatory synaptic transmission has long been considered a cellular correlate for learning and memory. Early LTP (less than 1 h) had initially been explained either by presynaptic increases in glutamate release or by direct modification of postsynaptic AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptor function. Compelling models have more recently proposed that synaptic potentiation can occur by the recruitment of additional postsynaptic AMPA receptors (AMPARs), sourced either from an intracellular reserve pool by exocytosis or from nearby extra-synaptic receptors pre-existing on the neuronal surface. However, the exact mechanism through which synapses can rapidly recruit new AMPARs during early LTP remains unknown. In particular, direct evidence for a pivotal role of AMPAR surface diffusion as a trafficking mechanism in synaptic plasticity is still lacking. Here, using AMPAR immobilization approaches, we show that interfering with AMPAR surface diffusion markedly impairs synaptic potentiation of Schaffer collaterals and commissural inputs to the CA1 area of the mouse hippocampus in cultured slices, acute slices and in vivo. Our data also identify distinct contributions of various AMPAR trafficking routes to the temporal profile of synaptic potentiation. In addition, AMPAR immobilization in vivo in the dorsal hippocampus inhibited fear conditioning, indicating that AMPAR diffusion is important for the early phase of contextual learning. Therefore, our results provide a direct demonstration that the recruitment of new receptors to synapses by surface diffusion is a critical mechanism for the expression of LTP and hippocampal learning. Since AMPAR surface diffusion is dictated by weak Brownian forces that are readily perturbed by protein-protein interactions, we anticipate that this fundamental trafficking mechanism will be a key target for modulating synaptic potentiation and learning.
Does learning in clinical context in anatomical sciences improve examination results, learning motivation, or learning orientation?

PubMed

Böckers, Anja; Mayer, Christian; Böckers, Tobias Maria

2014-01-01

The preclinical compulsory elective course "Ready for the Operating Room (OR)!?" [in German]: "Fit für den OP (FOP)"] was implemented for students in their second year, who were simultaneously enrolled in the gross anatomy course. The objective of the study was to determine whether the direct practical application of anatomical knowledge within the surgical context of the course led to any improvement in learning motivation, learning orientation, and ultimately examination results in the gross anatomy course, as compared with a control group. Within the scope of five teaching sessions, the students learned surgical hand disinfection, suturing techniques, and the identification of commonly used surgical instruments. In addition, the students attended five surgical demonstrations performed by surgical colleagues on cadavers. Successful learning of these basic skills was then assessed based on an Objectively Structured Practical Examination. Learning motivation and learning orientation in both subgroups was determined using the SELLMO-ST motivation test and the Approaches and Study Skills Inventory test. While a significant increase in work avoidance was identified in the control group, this was not the case for FOP participants. Similarly, an increase in the "deep approach" to learning, as well as a decrease in the "surface approach," was able to be documented among the FOP participants following completion of the course. The results suggest that students enrolled in the gross anatomy course, who were simultaneously provided with the opportunity to learn in clinical context, were more likely to be successful at maintaining learning motivation and learning orientation required for the learning process, than students who attended the gross anatomy course alone. © 2013 American Association of Anatomists.
Properties of small-scale interfacial turbulence from a novel thermography based approach

NASA Astrophysics Data System (ADS)

Schnieders, Jana; Garbe, Christoph

2013-04-01

Oceans cover nearly two thirds of the earth's surface and exchange processes between the Atmosphere and the Ocean are of fundamental environmental importance. At the air-sea interface, complex interaction processes take place on a multitude of scales. Turbulence plays a key role in the coupling of momentum, heat and mass transfer [2]. Here we use high resolution infrared imagery to visualize near surface aqueous turbulence. Thermographic data is analized from a range of laboratory facilities and experimental conditions with wind speeds ranging from 1ms-1 to 7ms-1 and various surface conditions. The surface heat pattern is formed by distinct structures on two scales - small-scale short lived structures termed fish scales and larger scale cold streaks that are consistent with the footprints of Langmuir Circulations. There are two key characteristics of the observed surface heat patterns: (1) The surface heat patterns show characteristic features of scales. (2) The structure of these patterns change with increasing wind stress and surface conditions. We present a new image processing based approach to the analysis of the spacing of cold streaks based on a machine learning approach [4, 1] to classify the thermal footprints of near surface turbulence. Our random forest classifier is based on classical features in image processing such as gray value gradients and edge detecting features. The result is a pixel-wise classification of the surface heat pattern with a subsequent analysis of the streak spacing. This approach has been presented in [3] and can be applied to a wide range of experimental data. In spite of entirely different boundary conditions, the spacing of turbulent cells near the air-water interface seems to match the expected turbulent cell size for flow near a no-slip wall. The analysis of the spacing of cold streaks shows consistent behavior in a range of laboratory facilities when expressed as a function of water sided friction velocity, u*. The scales systematically decrease until a point of saturation at u* = 0.7 cm/s. Results suggest a saturation in the tangential stress, anticipating that similar behavior will be observed in the open ocean. A comparison with studies of small-scale Langmuir circulations and Langmuir numbers shows that thermal footprints in infrared images are consistent with Langmuir circulations and depend strongly on wind wave conditions. Our approach is not limited to laboratory measurments. In the near future, we will deploy it on in-situ measurements and verify our findings in these more challenging conditions. References [1] L. Breimann. Random forests. Machine Learning, 45:5-32, 2001. [2] S. P. McKenna and W. R. McGillis. The role of free-surface turbulence and surfactants in air-water gas transfer. Int. J. Heat Mass Transfer, 47:539-553, 2004. [3] J Schnieders, C. S. Garbe, W.L. Peirson, and C. J. Zappa. Analyzing the footprints of near surface aqueous turbulence - an image processing based approach. Journal of Geophysical Research-Oceans, 2013. [4] Christoph Sommer, Christoph Straehle, Ullrich Koethe, and Fred A. Hamprecht. ilastik: Interactive learning and segmentation toolkit. In 8th IEEE International Symposium on Biomedical Imaging (ISBI 2011), 2011. [5] W.-T. Tsai, S.-M. Chen, and C.-H. Moeng. A numerical study on the evolution and structure of a stress-driven free-surface turbulent shear flow. J. Fluid Mech., 545:163-192, 2005.
Sophisticated epistemologies of physics versus high-stakes tests: How do elite high school students respond to competing influences about how to learn physics?

NASA Astrophysics Data System (ADS)

Yerdelen-Damar, Sevda; Elby, Andrew

2016-06-01

This study investigates how elite Turkish high school physics students claim to approach learning physics when they are simultaneously (i) engaged in a curriculum that led to significant gains in their epistemological sophistication and (ii) subject to a high-stakes college entrance exam. Students reported taking surface (rote) approaches to learning physics, largely driven by college entrance exam preparation and therefore focused on algorithmic problem solving at the expense of exploring concepts and real-life examples more deeply. By contrast, in recommending study strategies to "Arzu," a hypothetical student who doesn't need to take a college entrance exam and just wants to understand physics deeply, the students focused more on linking concepts and real-life examples and on making sense of the formulas and concepts—deep approaches to learning that reflect somewhat sophisticated epistemologies. These results illustrate how students can epistemically compartmentalize, consciously taking different epistemic stances—different views of what counts as knowing and learning—in different contexts even within the same discipline.
A Generic Deep-Learning-Based Approach for Automated Surface Inspection.

PubMed

Ren, Ruoxu; Hung, Terence; Tan, Kay Chen

2018-03-01

Automated surface inspection (ASI) is a challenging task in industry, as collecting training dataset is usually costly and related methods are highly dataset-dependent. In this paper, a generic approach that requires small training data for ASI is proposed. First, this approach builds classifier on the features of image patches, where the features are transferred from a pretrained deep learning network. Next, pixel-wise prediction is obtained by convolving the trained classifier over input image. An experiment on three public and one industrial data set is carried out. The experiment involves two tasks: 1) image classification and 2) defect segmentation. The results of proposed algorithm are compared against several best benchmarks in literature. In the classification tasks, the proposed method improves accuracy by 0.66%-25.50%. In the segmentation tasks, the proposed method reduces error escape rates by 6.00%-19.00% in three defect types and improves accuracies by 2.29%-9.86% in all seven defect types. In addition, the proposed method achieves 0.0% error escape rate in the segmentation task of industrial data.
Using concept mapping principles in PowerPoint.

PubMed

Kinchin, I M; Cabot, L B

2007-11-01

The use of linear PowerPoint templates to support lectures may inadvertently encourage dental students to adopt a passive approach to learning and a narrow appreciation of the field of study. Such presentations may support short-term learning gains and validate assessment regimes that promote surface learning approaches at the expense of developing a wider appreciation of the field that is necessary for development of clinical expertise. Exploitation of concept mapping principles can provide a balance for the negative learning behaviour that is promoted by the unreflective use of PowerPoint. This increases the opportunities for students to access holistic knowledge structures that are indicators of expertise. We illustrate this using the example of partial denture design and show that undergraduates' grasp of learning and teaching issues is sufficiently sophisticated for them to appreciate the implications of varying the mode of presentation. Our findings indicate that students understand the strategic value of bullet-pointed presentations for short-term assessment goals and the benefits of deep learning mediated by concept mapping that may support longer term professional development. Students are aware of the tension between these competing agendas.
The Explorer's Guide to Impact Craters

NASA Astrophysics Data System (ADS)

Pierazzo, E.; Osinski, G.; Chuang, F.

2004-12-01

Impact cratering is a fundamental geologic process of our solar system. It competes with other processes, such as plate tectonics, volcanism, or fluvial, glacial and eolian activity, in shaping the surfaces of planetary bodies. In some cases, like the Moon and Mercury, impact craters are the dominant landform. On other planetary bodies impact craters are being continuously erased by the action of other geological processes, like volcanism on Io, erosion and plate tectonics on the Earth, tectonic and volcanic resurfacing on Venus, or ancient erosion periods on Mars. The study of crater populations is one of the principal tools for understanding the geologic history of a planetary surface. Among the general public, impact cratering has drawn wide attention through its portrayal in several Hollywood movies. Questions that are raised after watching these movies include: ``How do scientists learn about impact cratering?'', and ``What information do impact craters provide in understanding the evolution of a planetary surface?'' Fundamental approaches used by scientists to learn about impact cratering include field work at known terrestrial craters, remote sensing studies of craters on various solid surfaces of solar system bodies, and theoretical and laboratory studies using the known physics of impact cratering. We will provide students, science teachers, and the general public an opportunity to experience the scientific endeavor of understanding and exploring impact craters through a multi-level approach including images, videos, and rock samples. This type of interactive learning can also be made available to the general public in the form of a website, which can be addressed worldwide at any time.
Improving visibility of rear surface cracks during inductive thermography of metal plates using Autoencoder

NASA Astrophysics Data System (ADS)

Xie, Jing; Xu, Changhang; Chen, Guoming; Huang, Weiping

2018-06-01

Inductive thermography is one kind of infrared thermography (IRT) technique, which is effective in detection of front surface cracks in metal plates. However, rear surface cracks are usually missed due to their weak indications during inductive thermography. Here we propose a novel approach (AET: AE Thermography) to improve the visibility of rear surface cracks during inductive thermography by employing the Autoencoder (AE) algorithm, which is an important block to construct deep learning architectures. We construct an integrated framework for processing the raw inspection data of inductive thermography using the AE algorithm. Through this framework, underlying features of rear surface cracks are efficiently extracted and new clearer images are constructed. Experiments of inductive thermography were conducted on steel specimens to verify the efficacy of the proposed approach. We visually compare the raw thermograms, the empirical orthogonal functions (EOFs) of the prominent component thermography (PCT) technique and the results of AET. We further quantitatively evaluated AET by calculating crack contrast and signal-to-noise ratio (SNR). The results demonstrate that the proposed AET approach can remarkably improve the visibility of rear surface cracks and then improve the capability of inductive thermography in detecting rear surface cracks in metal plates.
Learning styles of preclinical students in a medical college in western Nepal.

PubMed

Shankar, P R; Dubey, A K; Binu, V S; Subish, P; Deshpande, V Y

2006-01-01

Information on the learning styles of medical students are lacking in medical colleges in Nepal. Learning styles may be associated with student understanding and may predict success in examination. The present study was carried out to obtain information on learning styles and preferences for teaching of fourth semester medical students and note the association, if any, between respondents' personal characteristics and preferences for learning styles and types of teaching. The correlation between preferences for learning styles and types of teaching and performance in the second year university examination was also explored. The study was carried out during October 2003 at the Manipal College of Medical Sciences, Pokhara, Nepal using the Approaches and Study Skills Inventory (ASSIST) instrument. Information on the respondents' personal characteristics was collected. Respondents had to indicate their degree of agreement with a set of statements using a modified Likert-type scale. The statements were grouped into three main learning styles and two types of teaching. The median scores among different subgroups of respondents were compared using appropriate non-parametric tests (p<0.05). Ninety-two students (92%) participated; fifty-six were male. Thirty-one respondents were Nepalese, 48 were Indians. Majority were educated in English medium schools. The median scores for deep and surface learning styles were 64 and 49 respectively (maximum score=80). The scores for strategic learning was 75.5 (maximum score=100). There was no clear preference for any particular type of teaching. Indian students used more surface apathetic learning strategies compared to others. There was a negative correlation between surface learning and marks obtained in the final examination. The students mainly used deep and strategic learning styles. Differences in preference for learning styles and types of teaching were noted according the respondents' personal characteristics. This was a preliminary study and further studies are required.
Problem-based learning: an approach to enhancing learning and understanding of optics for first-year students

NASA Astrophysics Data System (ADS)

Bowe, Brian W.; Daly, Siobhan; Flynn, Cathal; Howard, Robert

2003-03-01

In this paper a model for the implementation of a problem-based learning (PBL) course for a typical year physics one programme is described. Reference is made to how PBL has been implemented in relation to geometrical and physical optics. PBL derives from the theory that learning is an active process in which the learner constructs new knowledge on the basis of current knowledge, unlike traditional teaching practices in higher education, where the emphasis is on the transmission of factual knowledge. The course consists of a set of optics related real life problems that are carefully constructed to meet specified learning outcomes. The students, working in groups, encounter these problem-solving situations and are facilitated to produce a solution. The PBL course promotes student engagement in order to achieve higher levels of cognitive learning. Evaluation of the course indicates that the students adopt a deep learning approach and that they attain a thorough understanding of the subject instead of the superficial understanding associated with surface learning. The methodology also helps students to develop metacognitive skills. Another outcome of this teaching methodology is the development of key skills such as the ability to work in a group and to communicate, and present, information effectively.
Flight Test Approach to Adaptive Control Research

NASA Technical Reports Server (NTRS)

Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

2011-01-01

The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

PubMed

Niegowski, Maciej; Zivanovic, Miroslav

2016-03-01

We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the suitability of certain wavelet decomposition bases which provide sparse electrocardiogram time-frequency representations, with the capacity of non-negative matrix factorization (NMF) for extracting patterns from images. In order to overcome convergence problems which often arise in NMF-related applications, we design a novel robust initialization strategy which ensures proper signal decomposition in a wide range of ECG contamination levels. Moreover, the method can be readily used because no a priori knowledge or parameter adjustment is needed. The proposed method was evaluated on real surface EMG signals against two state-of-the-art unsupervised learning algorithms and a singular spectrum analysis based method. The results, expressed in terms of high-to-low energy ratio, normalized median frequency, spectral power difference and normalized average rectified value, suggest that the proposed method enables better ECG-EMG separation quality than the reference methods. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
Sensor-based monitoring and inspection of surface morphology in ultraprecision manufacturing processes

NASA Astrophysics Data System (ADS)

Rao, Prahalad Krishna

This research proposes approaches for monitoring and inspection of surface morphology with respect to two ultraprecision/nanomanufacturing processes, namely, ultraprecision machining (UPM) and chemical mechanical planarization (CMP). The methods illustrated in this dissertation are motivated from the compelling need for in situ process monitoring in nanomanufacturing and invoke concepts from diverse scientific backgrounds, such as artificial neural networks, Bayesian learning, and algebraic graph theory. From an engineering perspective, this work has the following contributions: 1. A combined neural network and Bayesian learning approach for early detection of UPM process anomalies by integrating data from multiple heterogeneous in situ sensors (force, vibration, and acoustic emission) is developed. The approach captures process drifts in UPM of aluminum 6061 discs within 15 milliseconds of their inception and is therefore valuable for minimizing yield losses. 2. CMP process dynamics are mathematically represented using a deterministic multi-scale hierarchical nonlinear differential equation model. This process-machine inter-action (PMI) model is evocative of the various physio-mechanical aspects in CMP and closely emulates experimentally acquired vibration signal patterns, including complex nonlinear dynamics manifest in the process. By combining the PMI model predictions with features gathered from wirelessly acquired CMP vibration signal patterns, CMP process anomalies, such as pad wear, and drifts in polishing were identified in their nascent stage with high fidelity (R2 ~ 75%). 3. An algebraic graph theoretic approach for quantifying nano-surface morphology from optical micrograph images is developed. The approach enables a parsimonious representation of the topological relationships between heterogeneous nano-surface fea-tures, which are enshrined in graph theoretic entities, namely, the similarity, degree, and Laplacian matrices. Topological invariant measures (e.g., Fiedler number, Kirchoff index) extracted from these matrices are shown to be sensitive to evolving nano-surface morphology. For instance, we observed that prominent nanoscale morphological changes on CMP processed Cu wafers, although discernible visually, could not be tractably quantified using statistical metrology parameters, such as arithmetic average roughness (Sa), root mean square roughness (Sq), etc. In contrast, CMP induced nanoscale surface variations were captured on invoking graph theoretic topological invariants. Consequently, the graph theoretic approach can enable timely, non-contact, and in situ metrology of semiconductor wafers by obviating the need for reticent profile mapping techniques (e.g., AFM, SEM, etc.), and thereby prevent the propagation of yield losses over long production runs.
Robots and Humans in Planetary Exploration: Working Together?

NASA Technical Reports Server (NTRS)

Landis, Geoffrey A.; Lyons, Valerie (Technical Monitor)

2002-01-01

Today's approach to human-robotic cooperation in planetary exploration focuses on using robotic probes as precursors to human exploration. A large portion of current NASA planetary surface exploration is focussed on Mars, and robotic probes are seen as precursors to human exploration in: Learning about operation and mobility on Mars; Learning about the environment of Mars; Mapping the planet and selecting landing sites for human mission; Demonstration of critical technology; Manufacture fuel before human presence, and emplace elements of human-support infrastructure
The importance of cultivating a preference for complexity in veterinarians for effective lifelong learning.

PubMed

Dale, Vicki H M; Pierce, Stephanie E; May, Stephen A

2010-01-01

Much attention has been paid to the link between students' approaches to study and the quality of their learning. Less attention has been paid to the lifelong learner. We conceptualized a tripartite relationship between three measures of learning preference: conceptions of knowledge (construction and use vs. intake), need for cognition (high vs. low), and approach to study (deep vs. surface) and hypothesized that an individual's profile on these three measures-reconceptualized as a preference for complexity versus simplicity-would affect their attitude toward continuing professional development (CPD). A questionnaire was mailed to 2,000 randomly selected, home-practicing UK veterinarians to quantify their learning preferences, motivation to engage in CPD, and perception of barriers to participation and to assess the relationships between these constructs. Analysis of 775 responses (a 38.8% response rate) confirmed our tripartite model of learning and showed that a preference for complexity was negatively correlated with barriers and positively correlated with intrinsic, social, and extrinsic motivating factors, suggesting that all play a role in the continuing education of this group of professionals. A preference for simplicity was negatively correlated with social motivation and positively correlated with barriers. This study demonstrates that approach not only affects the quality of learning but crucially affects motivation to engage in CPD and perception of barriers to lifelong learning. This should emphasize to veterinary educators the importance of fostering a preference for complexity from an early age, both in terms of its immediate benefits (better understanding) and longer-term benefits (continued engagement with learning).
Challenges in Assessing for Postsecondary Readiness

ERIC Educational Resources Information Center

Mellard, Daryl F.; Anderson, Gretchen

2007-01-01

Adult secondary education learners approach the goal of college-level postsecondary education through three assessment gateways: (a) measures of adult education program learning gains, (b) a high-school equivalency exam, and (c) college placement tests. On the surface, the assessments in this sequence might appear to work in concert and point…
Data-driven Approaches to Teaching Stable Isotopes in Hydrology and Environmental Geochemistry

NASA Astrophysics Data System (ADS)

Jefferson, A.; Merchant, W. R.; Dees, D.; Griffith, E. M.; Ortiz, J. D.

2016-12-01

Stable isotopes have revolutionized our understanding of watershed hydrology and other earth science processes. However, students may struggle to correctly interpret isotope ratios and few students understand how isotope measurements are made. New laser-based technologies lower the barrier to entry for giving students hands on experience with isotope measurements and data analysis. We hypothesizedthat integrating such activities into the curriculum would increase student content knowledge, perceptions, and motivation to learn. This project assessed the impact that different pedagogical approaches have on student learning of stable isotope concepts in upper-division geoscience courses. An isotope hydrograph separation module was developed and taught for a Watershed Hydrology course, and a Rayleigh distillation activity was developed and deployed for Environmental Geochemistry and Sedimentology/Stratigraphy classes. Groups of students were exposed to this content via (1) a lecture-only format; (2) a paper-based data analysis activity; and (3) hands-on data collection, sometimes including spectrometer analysis. Pre- and post-tests measured gains in content knowledge while approaches to learning and motivational questionnaires instruments were used to identify the effects of the classroom environment on learning approaches and motivation. Focus group interviews were also conducted to verify the quantitative data. All instructional styles appear to be equally effective at increasing student content knowledge of stable isotopes in the geosciences, but future studies need to move beyond "exam question" style assessment of learning. Our results may reflect that hands-on experiences are not new to upper-level geosciences students, because this is the way that many classes are taught in the geosciences (labs, field trips). Thus, active learning approaches may not have had the impact they would with other groups. The "messiness" of hands-on activities and authentic research experiences may be perceived as negatives by students, particularly those who use surface learning techniques and extrinsic motivation.
Cross Validation Through Two-Dimensional Solution Surface for Cost-Sensitive SVM.

PubMed

Gu, Bin; Sheng, Victor S; Tay, Keng Yeow; Romano, Walter; Li, Shuo

2017-06-01

Model selection plays an important role in cost-sensitive SVM (CS-SVM). It has been proven that the global minimum cross validation (CV) error can be efficiently computed based on the solution path for one parameter learning problems. However, it is a challenge to obtain the global minimum CV error for CS-SVM based on one-dimensional solution path and traditional grid search, because CS-SVM is with two regularization parameters. In this paper, we propose a solution and error surfaces based CV approach (CV-SES). More specifically, we first compute a two-dimensional solution surface for CS-SVM based on a bi-parameter space partition algorithm, which can fit solutions of CS-SVM for all values of both regularization parameters. Then, we compute a two-dimensional validation error surface for each CV fold, which can fit validation errors of CS-SVM for all values of both regularization parameters. Finally, we obtain the CV error surface by superposing K validation error surfaces, which can find the global minimum CV error of CS-SVM. Experiments are conducted on seven datasets for cost sensitive learning and on four datasets for imbalanced learning. Experimental results not only show that our proposed CV-SES has a better generalization ability than CS-SVM with various hybrids between grid search and solution path methods, and than recent proposed cost-sensitive hinge loss SVM with three-dimensional grid search, but also show that CV-SES uses less running time.
New perspectives on the pedagogy of programming in a developing country context

NASA Astrophysics Data System (ADS)

Apiola, Mikko; Tedre, Matti

2012-09-01

Programming education is a widely researched and intensely discussed topic. The literature proposes a broad variety of pedagogical viewpoints, practical approaches, learning theories, motivational vehicles, and other elements of the learning situation. However, little effort has been put on understanding cultural and contextual differences in pedagogy of programming. Pedagogical literature shows that educational design should account for differences in the ways of learning and teaching between industrialized and developing countries. However, the nature and implications of those differences are hitherto unclear. Using group interviews and quantitative surveys, we identified several crucial elements for contextualizing programming education. Our results reveal that students are facing many similar challenges to students in the west: they often lack deep level learning skills and problem-solving skills, which are required for learning computer programming, and, secondly, that from the students' viewpoint the standard learning environment does not offer enough support for gaining the requisite development. With inadequate support students may resort to surface learning and may adopt extrinsic sources of motivation. Learning is also hindered by many contextually unique factors, such as unfamiliar pedagogical approaches, language problems, and cultural differences. Our analysis suggests that challenges can be minimized by increasing the number of practical exercises, by carefully selecting between guided and minimally guided environments, by rigorously monitoring student progress, and by providing students timely help, repetitive exercises, clear guidelines, and emotional support.
Profiles of Motivated Self-Regulation in College Computer Science Courses: Differences in Major versus Required Non-Major Courses

NASA Astrophysics Data System (ADS)

Shell, Duane F.; Soh, Leen-Kiat

2013-12-01

The goal of the present study was to utilize a profiling approach to understand differences in motivation and strategic self-regulation among post-secondary STEM students in major versus required non-major computer science courses. Participants were 233 students from required introductory computer science courses (194 men; 35 women; 4 unknown) at a large Midwestern state university. Cluster analysis identified five profiles: (1) a strategic profile of a highly motivated by-any-means good strategy user; (2) a knowledge-building profile of an intrinsically motivated autonomous, mastery-oriented student; (3) a surface learning profile of a utility motivated minimally engaged student; (4) an apathetic profile of an amotivational disengaged student; and (5) a learned helpless profile of a motivated but unable to effectively self-regulate student. Among CS majors and students in courses in their major field, the strategic and knowledge-building profiles were the most prevalent. Among non-CS majors and students in required non-major courses, the learned helpless, surface learning, and apathetic profiles were the most prevalent. Students in the strategic and knowledge-building profiles had significantly higher retention of computational thinking knowledge than students in other profiles. Students in the apathetic and surface learning profiles saw little instrumentality of the course for their future academic and career objectives. Findings show that students in STEM fields taking required computer science courses exhibit the same constellation of motivated strategic self-regulation profiles found in other post-secondary and K-12 settings.
Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

PubMed Central

Laine, Elodie; Carbone, Alessandra

2015-01-01

Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684
Regulating approaches to learning: Testing learning strategy convergences across a year at university.

PubMed

Fryer, Luke K; Vermunt, Jan D

2018-03-01

Contemporary models of student learning within higher education are often inclusive of processing and regulation strategies. Considerable research has examined their use over time and their (person-centred) convergence. The longitudinal stability/variability of learning strategy use, however, is poorly understood, but essential to supporting student learning across university experiences. Develop and test a person-centred longitudinal model of learning strategies across the first-year university experience. Japanese university students (n = 933) completed surveys (deep and surface approaches to learning; self, external, and lack of regulation) at the beginning and end of their first year. Following invariance and cross-sectional tests, latent profile transition analysis (LPTA) was undertaken. Initial difference testing supported small but significant differences for self-/external regulation. Fit indices supported a four-group model, consistent across both measurement points. These subgroups were labelled Low Quality (low deep approaches and self-regulation), Low Quantity (low strategy use generally), Average (moderate strategy use), and High Quantity (intense use of all strategies) strategies. The stability of these groups ranged from stable to variable: Average (93% stayers), Low Quality (90% stayers), High Quantity (72% stayers), and Low Quantity (40% stayers). The three largest transitions presented joint shifts in processing/regulation strategy preference across the year, from adaptive to maladaptive and vice versa. Person-centred longitudinal findings presented patterns of learning transitions that different students experience during their first year at university. Stability/variability of students' strategy use was linked to the nature of initial subgroup membership. Findings also indicated strong connections between processing and regulation strategy changes across first-year university experiences. Implications for theory and practice are discussed. © 2017 The British Psychological Society.
Changing the Metacognitive Orientation of a Classroom Environment to Stimulate Metacognitive Reflection Regarding the Nature of Physics Learning

NASA Astrophysics Data System (ADS)

Thomas, Gregory P.

2013-05-01

Problems persist with physics learning in relation to students' understanding and use of representations for making sense of physics concepts. Further, students' views of physics learning and their physics learning processes have been predominantly found to reflect a 'surface' approach to learning that focuses on mathematical aspects of physics learning that are often passed on via textbooks and lecture-style teaching. This paper reports on a teacher's effort to stimulate students' metacognitive reflection regarding their views of physics learning and their physics learning processes via a pedagogical change that incorporated the use of a representational framework and metaphors. As a consequence of the teacher's pedagogical change, students metacognitively reflected on their views of physics and their learning processes and some reported changes in their views of what it meant to understand physics and how they might learn and understand physics concepts. The findings provide a basis for further explicit teaching of representational frameworks to students in physics education as a potential means of addressing issues with their physics learning.
A Theoretical Framework for the Studio as a Learning Environment

ERIC Educational Resources Information Center

Brandt, Carol B.; Cennamo, Katherine; Douglas, Sarah; Vernon, Mitzi; McGrath, Margarita; Reimer, Yolanda

2013-01-01

In this article we describe a holistic, ecological framework that takes into account the surface structures and pedagogical approaches in the studio and how these elements are connected to the construction of design knowledge: epistemology. In our development of this framework, we came to understand how disciplinary underpinnings and academic…
Designing Instruction for Speed: Qualitative Insights into Instructional Design for Accelerated Online Graduate Coursework

ERIC Educational Resources Information Center

Trekles, Anastasia M.; Sims, Roderick

2013-01-01

The purpose of this exploratory case study was to explore instructional design strategies and characteristics of online, asynchronous accelerated courses and students' choices of deep or surface learning approaches within this environment. An increasing number of university programs, particularly at the graduate level, are moving to an…
Why Blackboard's Plan to Buy a Rival Sparked a Campus Uproar

ERIC Educational Resources Information Center

Young, Jeffrey R.

2009-01-01

Jokes about "Dark Angel" and "Blackborg" surfaced almost immediately after Blackboard Inc. announced its plan to buy course-management software competitor Angel Learning, the author reports. Angel had lured away dozens of Blackboard clients in recent years with a friendly, approachable corporate culture that stood in sharp contrast to Blackboard's…
Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach

PubMed Central

Saeb, Mohammad Reza; Rezaee, Babak; Shadman, Alireza; Formela, Krzysztof; Ahmadi, Zahed; Hemmati, Farkhondeh; Kermaniyan, Tayebeh Sadat; Mohammadi, Yousef

2017-01-01

Abstract Experimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration, and melt-processing time. An in-house code was developed based on artificial neural network that learns and mimics processing torque and grafting of glycidyl methacrylate (GMA) typical vinylic monomer on high-density polyethylene (HDPE). Application of response surface and desirability function enabled concurrent optimization of processing torque and GMA grafting on HDPE, through which we quantified for the first time competition between parallel reactions taking place during melt processing: (i) desirable grafting of GMA on HDPE; (ii) undesirable cross-linking of HDPE. The proposed robust mathematical modeling approach can precisely learn the behavior of grafting reaction of vinylic monomers on polyolefins and be placed into practice in finding exact operating condition needed for efficient grafting of reactive monomers on polyolefins. PMID:29491797
Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach.

PubMed

Saeb, Mohammad Reza; Rezaee, Babak; Shadman, Alireza; Formela, Krzysztof; Ahmadi, Zahed; Hemmati, Farkhondeh; Kermaniyan, Tayebeh Sadat; Mohammadi, Yousef

2017-01-01

Experimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration, and melt-processing time. An in-house code was developed based on artificial neural network that learns and mimics processing torque and grafting of glycidyl methacrylate (GMA) typical vinylic monomer on high-density polyethylene (HDPE). Application of response surface and desirability function enabled concurrent optimization of processing torque and GMA grafting on HDPE, through which we quantified for the first time competition between parallel reactions taking place during melt processing: (i) desirable grafting of GMA on HDPE; (ii) undesirable cross-linking of HDPE. The proposed robust mathematical modeling approach can precisely learn the behavior of grafting reaction of vinylic monomers on polyolefins and be placed into practice in finding exact operating condition needed for efficient grafting of reactive monomers on polyolefins.
Charting the energy landscape of metal/organic interfaces via machine learning

NASA Astrophysics Data System (ADS)

Scherbela, Michael; Hörmann, Lukas; Jeindl, Andreas; Obersteiner, Veronika; Hofmann, Oliver T.

2018-04-01

The rich polymorphism exhibited by inorganic/organic interfaces is a major challenge for materials design. In this work, we present a method to efficiently explore the potential energy surface and predict the formation energies of polymorphs and defects. This is achieved by training a machine learning model on a list of only 100 candidate structures that are evaluated via dispersion-corrected density functional theory (DFT) calculations. We demonstrate the power of this approach for tetracyanoethylene on Ag(100) and explain the anisotropic ordering that is observed experimentally.
Charting the energy landscape of metal/organic interfaces via machine learning

DOE PAGES

Scherbela, Michael; Hormann, Lukas; Jeindl, Andreas; ...

2018-04-17

The rich polymorphism exhibited by inorganic/organic interfaces is a major challenge for materials design. Here in this work, we present a method to efficiently explore the potential energy surface and predict the formation energies of polymorphs and defects. This is achieved by training a machine learning model on a list of only 100 candidate structures that are evaluated via dispersion-corrected density functional theory (DFT) calculations. Finally, we demonstrate the power of this approach for tetracyanoethylene on Ag(100) and explain the anisotropic ordering that is observed experimentally.
Charting the energy landscape of metal/organic interfaces via machine learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scherbela, Michael; Hormann, Lukas; Jeindl, Andreas

The rich polymorphism exhibited by inorganic/organic interfaces is a major challenge for materials design. Here in this work, we present a method to efficiently explore the potential energy surface and predict the formation energies of polymorphs and defects. This is achieved by training a machine learning model on a list of only 100 candidate structures that are evaluated via dispersion-corrected density functional theory (DFT) calculations. Finally, we demonstrate the power of this approach for tetracyanoethylene on Ag(100) and explain the anisotropic ordering that is observed experimentally.

Incorporation of physical constraints in optimal surface search for renal cortex segmentation

NASA Astrophysics Data System (ADS)

Li, Xiuli; Chen, Xinjian; Yao, Jianhua; Zhang, Xing; Tian, Jie

2012-02-01

In this paper, we propose a novel approach for multiple surfaces segmentation based on the incorporation of physical constraints in optimal surface searching. We apply our new approach to solve the renal cortex segmentation problem, an important but not sufficiently researched issue. In this study, in order to better restrain the intensity proximity of the renal cortex and renal column, we extend the optimal surface search approach to allow for varying sampling distance and physical separation constraints, instead of the traditional fixed sampling distance and numerical separation constraints. The sampling distance of each vertex-column is computed according to the sparsity of the local triangular mesh. Then the physical constraint learned from a priori renal cortex thickness is applied to the inter-surface arcs as the separation constraints. Appropriate varying sampling distance and separation constraints were learnt from 6 clinical CT images. After training, the proposed approach was tested on a test set of 10 images. The manual segmentation of renal cortex was used as the reference standard. Quantitative analysis of the segmented renal cortex indicates that overall segmentation accuracy was increased after introducing the varying sampling distance and physical separation constraints (the average true positive volume fraction (TPVF) and false positive volume fraction (FPVF) were 83.96% and 2.80%, respectively, by using varying sampling distance and physical separation constraints compared to 74.10% and 0.18%, respectively, by using fixed sampling distance and numerical separation constraints). The experimental results demonstrated the effectiveness of the proposed approach.
Metric Learning for Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.
Approaches to learning among occupational therapy undergraduate students: A cross-cultural study.

PubMed

Brown, Ted; Fong, Kenneth N K; Bonsaksen, Tore; Lan, Tan Hwei; Murdolo, Yuki; Gonzalez, Pablo Cruz; Beng, Lim Hua

2017-07-01

Students may adopt various approaches to academic learning. Occupational therapy students' approaches to study and the impact of cultural context have not been formally investigated to date. To examine the approaches to study adopted by undergraduate occupational therapy students from four different cultural settings. 712 undergraduate occupational therapy students (n = 376 from Australia, n = 109 from Hong Kong, n = 160 from Norway and n = 67 from Singapore) completed the Approaches and Study Skills Inventory for Students (ASSIST). A one-way analysis of variance (ANOVA) was conducted to compare the ASSIST subscales for the students from the four countries. Post-hoc comparisons using the Tukey HSD test indicated that the mean scores for the strategic approach were significantly different between Australia and the other three countries. The mean scores for the surface approach were significantly different between Australia and Hong Kong, and Hong Kong and Norway. There were no significant differences between the deep approach to studying between Australia, Norway, Singapore and Hong Kong. Culture and educational context do appear to impact the approaches to study adopted by undergraduate occupational therapy students. Academic and practice educators need to be cognizant of what approaches to studying the students they work with adopt.
Flight Approach to Adaptive Control Research

NASA Technical Reports Server (NTRS)

Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

2011-01-01

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.
Intrinsic map dynamics exploration for uncharted effective free-energy landscapes

PubMed Central

Covino, Roberto; Coifman, Ronald R.; Gear, C. William; Georgiou, Anastasia S.; Kevrekidis, Ioannis G.

2017-01-01

We describe and implement a computer-assisted approach for accelerating the exploration of uncharted effective free-energy surfaces (FESs). More generally, the aim is the extraction of coarse-grained, macroscopic information from stochastic or atomistic simulations, such as molecular dynamics (MD). The approach functionally links the MD simulator with nonlinear manifold learning techniques. The added value comes from biasing the simulator toward unexplored phase-space regions by exploiting the smoothness of the gradually revealed intrinsic low-dimensional geometry of the FES. PMID:28634293
Reconstructed Solar-Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence

NASA Astrophysics Data System (ADS)

Gentine, P.; Alemohammad, S. H.

2018-04-01

Solar-induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment-2 (GOME-2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS-only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.
Learning object correspondences with the observed transport shape measure.

PubMed

Pitiot, Alain; Delingette, Hervé; Toga, Arthur W; Thompson, Paul M

2003-07-01

We propose a learning method which introduces explicit knowledge to the object correspondence problem. Our approach uses an a priori learning set to compute a dense correspondence field between two objects, where the characteristics of the field bear close resemblance to those in the learning set. We introduce a new local shape measure we call the "observed transport measure", whose properties make it particularly amenable to the matching problem. From the values of our measure obtained at every point of the objects to be matched, we compute a distance matrix which embeds the correspondence problem in a highly expressive and redundant construct and facilitates its manipulation. We present two learning strategies that rely on the distance matrix and discuss their applications to the matching of a variety of 1-D, 2-D and 3-D objects, including the corpus callosum and ventricular surfaces.
Machine learning of accurate energy-conserving molecular force fields.

PubMed

Chmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E; Poltavsky, Igor; Schütt, Kristof T; Müller, Klaus-Robert

2017-05-01

Using conservation of energy-a fundamental property of closed classical and quantum mechanical systems-we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of 0.3 kcal mol -1 for energies and 1 kcal mol -1 Å̊ -1 for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods.
Machine learning of accurate energy-conserving molecular force fields

PubMed Central

Chmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E.; Poltavsky, Igor; Schütt, Kristof T.; Müller, Klaus-Robert

2017-01-01

Using conservation of energy—a fundamental property of closed classical and quantum mechanical systems—we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of 0.3 kcal mol−1 for energies and 1 kcal mol−1 Å̊−1 for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods. PMID:28508076
As above, so below? Towards understanding inverse models in BCI

NASA Astrophysics Data System (ADS)

Lindgren, Jussi T.

2018-02-01

Objective. In brain-computer interfaces (BCI), measurements of the user’s brain activity are classified into commands for the computer. With EEG-based BCIs, the origins of the classified phenomena are often considered to be spatially localized in the cortical volume and mixed in the EEG. We investigate if more accurate BCIs can be obtained by reconstructing the source activities in the volume. Approach. We contrast the physiology-driven source reconstruction with data-driven representations obtained by statistical machine learning. We explain these approaches in a common linear dictionary framework and review the different ways to obtain the dictionary parameters. We consider the effect of source reconstruction on some major difficulties in BCI classification, namely information loss, feature selection and nonstationarity of the EEG. Main results. Our analysis suggests that the approaches differ mainly in their parameter estimation. Physiological source reconstruction may thus be expected to improve BCI accuracy if machine learning is not used or where it produces less optimal parameters. We argue that the considered difficulties of surface EEG classification can remain in the reconstructed volume and that data-driven techniques are still necessary. Finally, we provide some suggestions for comparing approaches. Significance. The present work illustrates the relationships between source reconstruction and machine learning-based approaches for EEG data representation. The provided analysis and discussion should help in understanding, applying, comparing and improving such techniques in the future.
Low power femtosecond tip-based nanofabrication with advanced control

NASA Astrophysics Data System (ADS)

Liu, Jiangbo; Guo, Zhixiong; Zou, Qingze

2018-02-01

In this paper, we propose an approach to enable the use of low power femtosecond laser in tip-based nanofabrication (TBN) without thermal damage. One major challenge in laser-assisted TBN is in maintaining precision control of the tip-surface positioning throughout the fabrication process. An advanced iterative learning control technique is exploited to overcome this challenge in achieving high-quality patterning of arbitrary shape on a metal surface. The experimental results are analyzed to understand the ablation mechanism involved. Specifically, the near-field radiation enhancement is examined via the surface-enhanced Raman scattering effect, and it was revealed the near-field enhanced plasma-mediated ablation. Moreover, silicon nitride tip is utilized to alleviate the adverse thermal damage. Experiment results including line patterns fabricated under different writing speeds and an "R" pattern are presented. The fabrication quality with regard to the line width, depth, and uniformity is characterized to demonstrate the efficacy of the proposed approach.
Reforms in Pedagogy and the Confucian Tradition: Looking below the Surface

ERIC Educational Resources Information Center

Ho, Felix M.

2018-01-01

This Forum article addresses some of the issues raised in the article by Ying-Syuan Huang and Anila Asghar's paper entitled: "Science education reform in Confucian learning cultures: teachers' perspectives on policy and practice in Taiwan." An attempt is made to highlight the need for a more nuanced approach in considering the Confucian…
Towards DMD-Based Estimation and Control of Flow Separation using an Array of Surface Pressure Sensors

NASA Astrophysics Data System (ADS)

Deem, Eric; Cattafesta, Louis; Zhang, Hao; Rowley, Clancy

2016-11-01

Closed-loop control of flow separation requires the spatio-temporal states of the flow to be fed back through the controller in real time. Previously, static and dynamic estimation methods have been employed that provide reduced-order model estimates of the POD-coefficients of the flow velocity using surface pressure measurements. However, this requires a "learning" dataset a priori. This approach is effective as long as the dynamics during control do not stray from the learning dataset. Since only a few dynamical features are required for feedback control of flow separation, many of the details provided by full-field snapshots are superfluous. This motivates a state-observation technique that extracts key dynamical features directly from surface pressure, without requiring PIV snapshots. The results of identifying DMD modes of separated flow through an array of surface pressure sensors in real-time are presented. This is accomplished by employing streaming DMD "on the fly" to surface pressure snapshots. These modal characteristics exhibit striking similarities to those extracted from PIV data and the pressure field obtained via solving Poisson's equation. Progress towards closed-loop separation control based on the dynamic modes of surface pressure will be discussed. Supported by AFOSR Grant FA9550-14-1-0289.
Science Operations Development for Field Analogs: Lessons Learned from the 2010 Desert RATS Test

NASA Technical Reports Server (NTRS)

Eppler, D. B.; Ming, D. W.

2011-01-01

Desert Research and Technology Studies (Desert RATS) is a multi-year series of hardware and operations tests carried out annually in the high desert of Arizona on the San Francisco Volcanic Field. Conducted since 1997, these activities are designed to exercise planetary surface hardware and operations in conditions where long-distance, multi-day roving is achievable. Such activities not only test vehicle subsystems through extended rough-terrain driving, they also stress communications and operations systems and allow testing of science operations approaches to advance human and robotic surface capabilities.
Homepage to distribute the anatomy learning contents including Visible Korean products, comics, and books.

PubMed

Chung, Beom Sun; Chung, Min Suk

2018-03-01

The authors have operated the homepage (http://anatomy.co.kr) to provide the learning contents of anatomy. From the homepage, sectioned images, volume models, and surface models-all Visible Korean products-can be downloaded. The realistic images can be interactively manipulated, which will give rise to the interest in anatomy. The various anatomy comics (learning comics, comic strips, plastination comics, etc.) are approachable. Visitors can obtain the regional anatomy book with concise contents, mnemonics, and schematics as well as the simplified dissection manual and the pleasant anatomy essay. Medical students, health allied professional students, and even laypeople are expected to utilize the easy and comforting anatomy contents. It is hoped that other anatomists successively produce and distribute their own informative contents.
The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques

NASA Astrophysics Data System (ADS)

Deng, Chengbin; Wu, Changshan

2013-12-01

Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available.
Engine classification using vibrations measured by Laser Doppler Vibrometer on different surfaces

NASA Astrophysics Data System (ADS)

Wei, J.; Liu, Chi-Him; Zhu, Zhigang; Vongsy, Karmon; Mendoza-Schrock, Olga

2015-05-01

In our previous studies, vehicle surfaces' vibrations caused by operating engines measured by Laser Doppler Vibrometer (LDV) have been effectively exploited in order to classify vehicles of different types, e.g., vans, 2-door sedans, 4-door sedans, trucks, and buses, as well as different types of engines, such as Inline-four engines, V-6 engines, 1-axle diesel engines, and 2-axle diesel engines. The results are achieved by employing methods based on an array of machine learning classifiers such as AdaBoost, random forests, neural network, and support vector machines. To achieve effective classification performance, we seek to find a more reliable approach to pick authentic vibrations of vehicle engines from a trustworthy surface. Compared with vibrations directly taken from the uncooperative vehicle surfaces that are rigidly connected to the engines, these vibrations are much weaker in magnitudes. In this work we conducted a systematic study on different types of objects. We tested different types of engines ranging from electric shavers, electric fans, and coffee machines among different surfaces such as a white board, cement wall, and steel case to investigate the characteristics of the LDV signals of these surfaces, in both the time and spectral domains. Preliminary results in engine classification using several machine learning algorithms point to the right direction on the choice of type of object surfaces to be planted for LDV measurements.
Animation control of surface motion capture.

PubMed

Tejera, Margara; Casas, Dan; Hilton, Adrian

2013-12-01

Surface motion capture (SurfCap) of actor performance from multiple view video provides reconstruction of the natural nonrigid deformation of skin and clothing. This paper introduces techniques for interactive animation control of SurfCap sequences which allow the flexibility in editing and interactive manipulation associated with existing tools for animation from skeletal motion capture (MoCap). Laplacian mesh editing is extended using a basis model learned from SurfCap sequences to constrain the surface shape to reproduce natural deformation. Three novel approaches for animation control of SurfCap sequences, which exploit the constrained Laplacian mesh editing, are introduced: 1) space–time editing for interactive sequence manipulation; 2) skeleton-driven animation to achieve natural nonrigid surface deformation; and 3) hybrid combination of skeletal MoCap driven and SurfCap sequence to extend the range of movement. These approaches are combined with high-level parametric control of SurfCap sequences in a hybrid surface and skeleton-driven animation control framework to achieve natural surface deformation with an extended range of movement by exploiting existing MoCap archives. Evaluation of each approach and the integrated animation framework are presented on real SurfCap sequences for actors performing multiple motions with a variety of clothing styles. Results demonstrate that these techniques enable flexible control for interactive animation with the natural nonrigid surface dynamics of the captured performance and provide a powerful tool to extend current SurfCap databases by incorporating new motions from MoCap sequences.
Dilemmas of reform: An exploration of science teachers' collective sensemaking of formative assessment practices

NASA Astrophysics Data System (ADS)

Heredia, Sara Catherine

Current reform efforts in science education call for significant shifts in how science is taught and learned. Teachers are important gatekeepers for reform, as they must enact these changes with students in their own classrooms. As such, professional development approaches need to be developed and studied to understand how teachers interpret and make instructional plans to implement these reforms. However, traditional approaches to studying implementation of reforms often draw on metrics such as time allotted to new activities, rather than exploring the ways in which teachers make sense of these reforms. In this dissertation I draw upon a body of work called sensemaking that has focused on locating learning in teachers' conversations in departmental work groups. I developed a conceptual and analytic framework to analyze how teachers make sense of reform given their local contexts and then used this framework to perform a case study of one group of teachers that participated in larger professional development project that examined the impact of a learning progression on science teachers' formative assessment practices. I draw upon videotapes of three years of monthly professional development meetings as my primary source of data, and used an ethnographic approach to identify dilemmas surfaced by teachers, sources of ambiguity and uncertainty, and patterns of and resources for teacher sensemaking. The case study reveals relationships between the type of dilemma surfaced by the teachers and different patterns of sensemaking for modification of teaching practices. When teachers expressed concerns about district or administrative requirements, they aligned their work in the professional development to those external forces. In contrast, teachers were able to develop and try out new practices when they perceived coherence between the professional development and school or district initiatives. These results underscore the importance of coherence between various components of teachers' work environments.
3D surface parameterization using manifold learning for medial shape representation

NASA Astrophysics Data System (ADS)

Ward, Aaron D.; Hamarneh, Ghassan

2007-03-01

The choice of 3D shape representation for anatomical structures determines the effectiveness with which segmentation, visualization, deformation, and shape statistics are performed. Medial axis-based shape representations have attracted considerable attention due to their inherent ability to encode information about the natural geometry of parts of the anatomy. In this paper, we propose a novel approach, based on nonlinear manifold learning, to the parameterization of medial sheets and object surfaces based on the results of skeletonization. For each single-sheet figure in an anatomical structure, we skeletonize the figure, and classify its surface points according to whether they lie on the upper or lower surface, based on their relationship to the skeleton points. We then perform nonlinear dimensionality reduction on the skeleton, upper, and lower surface points, to find the intrinsic 2D coordinate system of each. We then center a planar mesh over each of the low-dimensional representations of the points, and map the meshes back to 3D using the mappings obtained by manifold learning. Correspondence between mesh vertices, established in their intrinsic 2D coordinate spaces, is used in order to compute the thickness vectors emanating from the medial sheet. We show results of our algorithm on real brain and musculoskeletal structures extracted from MRI, as well as an artificial multi-sheet example. The main advantages to this method are its relative simplicity and noniterative nature, and its ability to correctly compute nonintersecting thickness vectors for a medial sheet regardless of both the amount of coincident bending and thickness in the object, and of the incidence of local concavities and convexities in the object's surface.

Global Learning Spectral Archive- A new Way to deal with Unknown Urban Spectra -

NASA Astrophysics Data System (ADS)

Jilge, M.; Heiden, U.; Habermeyer, M.; Jürgens, C.

2015-12-01

Rapid urbanization processes and the need of identifying urban materials demand urban planners and the remote sensing community since years. Urban planners cannot overcome the issue of up-to-date information of urban materials due to time-intensive fieldwork. Hyperspectral remote sensing can facilitate this issue by interpreting spectral signals to provide information of occurring materials. However, the complexity of urban areas and the occurrence of diverse urban materials vary due to regional and cultural aspects as well as the size of a city, which makes identification of surface materials a challenging analysis task. For the various surface material identification approaches, spectral libraries containing pure material spectra are commonly used, which are derived from field, laboratory or the hyperspectral image itself. One of the requirements for successful image analysis is that all spectrally different surface materials are represented by the library. Currently, a universal library, applicable in every urban area worldwide and taking each spectral variability into account, is and will not be existent. In this study, the issue of unknown surface material spectra and the demand of an urban site-specific spectral library is tackled by the development of a learning spectral archive tool. Starting with an incomplete library of labelled image spectra from several German cities, surface materials of pure image pixels will be identified in a hyperspectral image based on a similarity measure (e.g. SID-SAM). Additionally, unknown image spectra of urban objects are identified based on an object- and spectral-based-rule set. The detected unknown surface material spectra are entered with additional metadata, such as regional occurrence into the existing spectral library and thus, are reusable for further studies. Our approach is suitable for pure surface material detection of urban hyperspectral images that is globally applicable by taking incompleteness into account. The generically development enables the implementation of different hyperspectral sensors.
Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics

NASA Astrophysics Data System (ADS)

Mansbach, Rachael A.; Ferguson, Andrew L.

2015-03-01

The conformational states explored by polymers and proteins can be controlled by environmental conditions (e.g., temperature, pressure, and solvent) and molecular chemistry (e.g., molecular weight and side chain identity). We introduce an approach employing the diffusion map nonlinear machine learning technique to recover single molecule free energy landscapes from molecular simulations, quantify changes to the landscape as a function of external conditions and molecular chemistry, and relate these changes to modifications of molecular structure and dynamics. In an application to an n-eicosane chain, we quantify the thermally accessible chain configurations as a function of temperature and solvent conditions. In an application to a family of polyglutamate-derivative homopeptides, we quantify helical stability as a function of side chain length, resolve the critical side chain length for the helix-coil transition, and expose the molecular mechanisms underpinning side chain-mediated helix stability. By quantifying single molecule responses through perturbations to the underlying free energy surface, our approach provides a quantitative bridge between experimentally controllable variables and microscopic molecular behavior, guiding and informing rational engineering of desirable molecular structure and function.
Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics.

PubMed

Mansbach, Rachael A; Ferguson, Andrew L

2015-03-14

The conformational states explored by polymers and proteins can be controlled by environmental conditions (e.g., temperature, pressure, and solvent) and molecular chemistry (e.g., molecular weight and side chain identity). We introduce an approach employing the diffusion map nonlinear machine learning technique to recover single molecule free energy landscapes from molecular simulations, quantify changes to the landscape as a function of external conditions and molecular chemistry, and relate these changes to modifications of molecular structure and dynamics. In an application to an n-eicosane chain, we quantify the thermally accessible chain configurations as a function of temperature and solvent conditions. In an application to a family of polyglutamate-derivative homopeptides, we quantify helical stability as a function of side chain length, resolve the critical side chain length for the helix-coil transition, and expose the molecular mechanisms underpinning side chain-mediated helix stability. By quantifying single molecule responses through perturbations to the underlying free energy surface, our approach provides a quantitative bridge between experimentally controllable variables and microscopic molecular behavior, guiding and informing rational engineering of desirable molecular structure and function.
Amp: A modular approach to machine learning in atomistic simulations

NASA Astrophysics Data System (ADS)

Khorshidi, Alireza; Peterson, Andrew A.

2016-10-01

Electronic structure calculations, such as those employing Kohn-Sham density functional theory or ab initio wavefunction theories, have allowed for atomistic-level understandings of a wide variety of phenomena and properties of matter at small scales. However, the computational cost of electronic structure methods drastically increases with length and time scales, which makes these methods difficult for long time-scale molecular dynamics simulations or large-sized systems. Machine-learning techniques can provide accurate potentials that can match the quality of electronic structure calculations, provided sufficient training data. These potentials can then be used to rapidly simulate large and long time-scale phenomena at similar quality to the parent electronic structure approach. Machine-learning potentials usually take a bias-free mathematical form and can be readily developed for a wide variety of systems. Electronic structure calculations have favorable properties-namely that they are noiseless and targeted training data can be produced on-demand-that make them particularly well-suited for machine learning. This paper discusses our modular approach to atomistic machine learning through the development of the open-source Atomistic Machine-learning Package (Amp), which allows for representations of both the total and atom-centered potential energy surface, in both periodic and non-periodic systems. Potentials developed through the atom-centered approach are simultaneously applicable for systems with various sizes. Interpolation can be enhanced by introducing custom descriptors of the local environment. We demonstrate this in the current work for Gaussian-type, bispectrum, and Zernike-type descriptors. Amp has an intuitive and modular structure with an interface through the python scripting language yet has parallelizable fortran components for demanding tasks; it is designed to integrate closely with the widely used Atomic Simulation Environment (ASE), which makes it compatible with a wide variety of commercial and open-source electronic structure codes. We finally demonstrate that the neural network model inside Amp can accurately interpolate electronic structure energies as well as forces of thousands of multi-species atomic systems.
The Explorer's Guide to Impact Craters

NASA Technical Reports Server (NTRS)

Chuang, F.; Pierazzo, E.; Osinski, G.

2005-01-01

Impact cratering is a fundamental geologic process of our solar system. It competes with other processes, such as plate tectonics, volcanism, fluvial, glacial and eolian activity, in shaping the surfaces of planetary bodies. In some cases, like the Moon and Mercury, impact craters are the dominant landform. On other planetary bodies impact craters are being continuously erased by the action of other geological processes, like volcanism on Io, erosion and plate tectonics on the Earth, tectonic and volcanic resurfacing on Venus, or ancient erosion periods on Mars. The study of crater populations is one of the principal tools for understanding the geologic history of a planetary surface. Among the general public, impact cratering has drawn wide attention through its portrayal in several Hollywood movies. Questions that are raised after watching these movies include: How do scientists learn about impact cratering? , and What information do impact craters provide in understanding the evolution of a planetary surface? Fundamental approaches used by scientists to learn about impact cratering include field work at known terrestrial craters, remote sensing studies of craters on various solid surfaces of solar system bodies, and theoretical and laboratory studies using the known physics of impact cratering.
Generating Ground Reference Data for a Global Impervious Surface Survey

NASA Technical Reports Server (NTRS)

Tilton, James C.; De Colstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are developing an approach for generating ground reference data in support of a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. Since sufficient ground reference data for training and validation is not available from ground surveys, we are developing an interactive tool, called HSegLearn, to facilitate the photo-interpretation of 1 to 2 m spatial resolution imagery data, which we will use to generate the needed ground reference data at 30m. Through the submission of selected region objects and positive or negative examples of impervious surfaces, HSegLearn enables an analyst to automatically select groups of spectrally similar objects from a hierarchical set of image segmentations produced by the HSeg image segmentation program at an appropriate level of segmentation detail, and label these region objects as either impervious or nonimpervious.
Learning-based 3D surface optimization from medical image reconstruction

NASA Astrophysics Data System (ADS)

Wei, Mingqiang; Wang, Jun; Guo, Xianglin; Wu, Huisi; Xie, Haoran; Wang, Fu Lee; Qin, Jing

2018-04-01

Mesh optimization has been studied from the graphical point of view: It often focuses on 3D surfaces obtained by optical and laser scanners. This is despite the fact that isosurfaced meshes of medical image reconstruction suffer from both staircases and noise: Isotropic filters lead to shape distortion, while anisotropic ones maintain pseudo-features. We present a data-driven method for automatically removing these medical artifacts while not introducing additional ones. We consider mesh optimization as a combination of vertex filtering and facet filtering in two stages: Offline training and runtime optimization. In specific, we first detect staircases based on the scanning direction of CT/MRI scanners, and design a staircase-sensitive Laplacian filter (vertex-based) to remove them; and then design a unilateral filtered facet normal descriptor (uFND) for measuring the geometry features around each facet of a given mesh, and learn the regression functions from a set of medical meshes and their high-resolution reference counterparts for mapping the uFNDs to the facet normals of the reference meshes (facet-based). At runtime, we first perform staircase-sensitive Laplacian filter on an input MC (Marching Cubes) mesh, and then filter the mesh facet normal field using the learned regression functions, and finally deform it to match the new normal field for obtaining a compact approximation of the high-resolution reference model. Tests show that our algorithm achieves higher quality results than previous approaches regarding surface smoothness and surface accuracy.
The interplay between motivation, self-efficacy, and approaches to studying.

PubMed

Prat-Sala, Mercè; Redford, Paul

2010-06-01

The strategies students adopt in their study are influenced by a number of social-cognitive factors and impact upon their academic performance. The present study examined the interrelationships between motivation orientation (intrinsic and extrinsic), self-efficacy (in reading academic texts and essay writing), and approaches to studying (deep, strategic, and surface). The study also examined changes in approaches to studying over time. A total of 163 first-year undergraduate students in psychology at a UK university took part in the study. Participants completed the Work Preference Inventory motivation questionnaire, self-efficacy in reading and writing questionnaires and the short version of the Revised Approaches to Study Inventory. The results showed that both intrinsic and extrinsic motivation orientations were correlated with approaches to studying. The results also showed that students classified as high in self-efficacy (reading and writing) were more likely to adopt a deep or strategic approach to studying, while students classified as low in self-efficacy (reading and writing) were more likely to adopt a surface approach. More importantly, changes in students' approaches to studying over time were related to their self-efficacy beliefs, where students with low levels of self-efficacy decreased in their deep approach and increased their surface approach across time. Students with high levels of self-efficacy (both reading and writing) demonstrated no such change in approaches to studying. Our results demonstrate the important role of self-efficacy in understanding both motivation and learning approaches in undergraduate students. Furthermore, given that reading academic text and writing essays are essential aspects of many undergraduate degrees, our results provide some indication that focusing on self-efficacy beliefs amongst students may be beneficial to improving their approaches to study.
Development of geometry materials based on scientific approach for junior high school students

NASA Astrophysics Data System (ADS)

Nurafni; Siswanto, R. D.; Azhar, E.

2018-01-01

A scientific approach is a learning process designed so that learners can actively construct concepts, encourage learners to find out from various sources through observation, and not just be told. Therefore, learning by scientific approach offers a solution, because the goals, principles, and stages of the scientific approach allow for a good understanding of the students. Because of the absence of teaching materials “polyhedron geometry based on scientific approach” which is widely published in Indonesia, then we need to develop the teaching materials. The results obtained in this study are the tasks presented on teaching materials with a scientific approach both in defining the cube and the beam, identify and solve problems related to the properties and elements of cubes and beams, making cube and beam nets, solving problems related to cube and beam nets, solving problems related to cube and beam surface area. Beginning with the difficulties students face. Then, based on the results of interviews with teachers and analysis of student difficulties on each indicator, researchers revise the teaching materials as needed. Teaching materials that have not found any more student difficulties then the teaching materials are considered valid and ready for use by teachers and students.
The disposition to understand for oneself at university: integrating learning processes with motivation and metacognition.

PubMed

Entwistle, Noel; McCune, Velda

2013-06-01

A re-analysis of several university-level interview studies has suggested that some students show evidence of a deep and stable approach to learning, along with other characteristics that support the approach. This combination, it was argued, could be seen to indicate a disposition to understand for oneself. To identify a group of students who showed high and consistent scores on deep approach, combined with equivalently high scores on effort and monitoring studying, and to explore these students' experiences of the teaching-learning environments they had experienced. Re-analysis of data from 1,896 students from 25 undergraduate courses taking four contrasting subject areas in eleven British universities. Inventories measuring approaches to studying were given at the beginning and the end of a semester, with the second inventory also exploring students' experiences of teaching. K-means cluster analysis was used to identify groups of students with differing patterns of response on the inventory scales, with a particular focus on students showing high, stable scores. One cluster clearly showed the characteristics expected of the disposition to understand and was also fairly stable over time. Other clusters also had deep approaches, but also showed either surface elements or lower scores on organized effort or monitoring their studying. Combining these findings with interview studies previously reported reinforces the idea of there being a disposition to understand for oneself that could be identified from an inventory scale or through further interviews. © 2013 The British Psychological Society.
Metal surface corrosion grade estimation from single image

NASA Astrophysics Data System (ADS)

Chen, Yijun; Qi, Lin; Sun, Huyuan; Fan, Hao; Dong, Junyu

2018-04-01

Metal corrosion can cause many problems, how to quickly and effectively assess the grade of metal corrosion and timely remediation is a very important issue. Typically, this is done by trained surveyors at great cost. Assisting them in the inspection process by computer vision and artificial intelligence would decrease the inspection cost. In this paper, we propose a dataset of metal surface correction used for computer vision detection and present a comparison between standard computer vision techniques by using OpenCV and deep learning method for automatic metal surface corrosion grade estimation from single image on this dataset. The test has been performed by classifying images and calculating the accuracy for the two different approaches.
Habitat Demonstration Unit (HDU) Pressurized Excursion Module (PEM) Systems Integration Strategy

NASA Technical Reports Server (NTRS)

Gill, Tracy; Merbitz, Jerad; Kennedy, Kriss; Tri, Terry; Toups, Larry; Howe, A. Scott

2011-01-01

The Habitat Demonstration Unit (HDU) project team constructed an analog prototype lunar surface laboratory called the Pressurized Excursion Module (PEM). The prototype unit subsystems were integrated in a short amount of time, utilizing a rapid prototyping approach that brought together over 20 habitation-related technologies from a variety of NASA centers. This paper describes the system integration strategies and lessons learned, that allowed the PEM to be brought from paper design to working field prototype using a multi-center team. The system integration process was based on a rapid prototyping approach. Tailored design review and test and integration processes facilitated that approach. The use of collaboration tools including electronic tools as well as documentation enabled a geographically distributed team take a paper concept to an operational prototype in approximately one year. One of the major tools used in the integration strategy was a coordinated effort to accurately model all the subsystems using computer aided design (CAD), so conflicts were identified before physical components came together. A deliberate effort was made following the deployment of the HDU PEM for field operations to collect lessons learned to facilitate process improvement and inform the design of future flight or analog versions of habitat systems. Significant items within those lessons learned were limitations with the CAD integration approach and the impact of shell design on flexibility of placing systems within the HDU shell.
Cascade Error Projection with Low Bit Weight Quantization for High Order Correlation Data

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher

1998-01-01

In this paper, we reinvestigate the solution for chaotic time series prediction problem using neural network approach. The nature of this problem is such that the data sequences are never repeated, but they are rather in chaotic region. However, these data sequences are correlated between past, present, and future data in high order. We use Cascade Error Projection (CEP) learning algorithm to capture the high order correlation between past and present data to predict a future data using limited weight quantization constraints. This will help to predict a future information that will provide us better estimation in time for intelligent control system. In our earlier work, it has been shown that CEP can sufficiently learn 5-8 bit parity problem with 4- or more bits, and color segmentation problem with 7- or more bits of weight quantization. In this paper, we demonstrate that chaotic time series can be learned and generalized well with as low as 4-bit weight quantization using round-off and truncation techniques. The results show that generalization feature will suffer less as more bit weight quantization is available and error surfaces with the round-off technique are more symmetric around zero than error surfaces with the truncation technique. This study suggests that CEP is an implementable learning technique for hardware consideration.
Homepage to distribute the anatomy learning contents including Visible Korean products, comics, and books

PubMed Central

Chung, Beom Sun

2018-01-01

The authors have operated the homepage (http://anatomy.co.kr) to provide the learning contents of anatomy. From the homepage, sectioned images, volume models, and surface models—all Visible Korean products—can be downloaded. The realistic images can be interactively manipulated, which will give rise to the interest in anatomy. The various anatomy comics (learning comics, comic strips, plastination comics, etc.) are approachable. Visitors can obtain the regional anatomy book with concise contents, mnemonics, and schematics as well as the simplified dissection manual and the pleasant anatomy essay. Medical students, health allied professional students, and even laypeople are expected to utilize the easy and comforting anatomy contents. It is hoped that other anatomists successively produce and distribute their own informative contents. PMID:29644104
Effects of a blended learning approach on student outcomes in a graduate-level public health course.

PubMed

Kiviniemi, Marc T

2014-03-11

Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, "traditional" approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses.
Sociomateriality: a theoretical framework for studying distributed medical education.

PubMed

MacLeod, Anna; Kits, Olga; Whelan, Emma; Fournier, Cathy; Wilson, Keith; Power, Gregory; Mann, Karen; Tummons, Jonathan; Brown, Peggy Alexiadis

2015-11-01

Distributed medical education (DME) is a type of distance learning in which students participate in medical education from diverse geographic locations using Web conferencing, videoconferencing, e-learning, and similar tools. DME is becoming increasingly widespread in North America and around the world.Although relatively new to medical education, distance learning has a long history in the broader field of education and a related body of literature that speaks to the importance of engaging in rigorous and theoretically informed studies of distance learning. The existing DME literature is helpful, but it has been largely descriptive and lacks a critical "lens"-that is, a theoretical perspective from which to rigorously conceptualize and interrogate DME's social (relationships, people) and material (technologies, tools) aspects.The authors describe DME and theories about distance learning and show that such theories focus on social, pedagogical, and cognitive considerations without adequately taking into account material factors. They address this gap by proposing sociomateriality as a theoretical framework allowing researchers and educators to study DME and (1) understand and consider previously obscured actors, infrastructure, and other factors that, on the surface, seem unrelated and even unimportant; (2) see clearly how the social and material components of learning are intertwined in fluid, messy, and often uncertain ways; and (3) perhaps think differently, even in ways that disrupt traditional approaches, as they explore DME. The authors conclude that DME brings with it substantial investments of social and material resources, and therefore needs careful study, using approaches that embrace its complexity.
Local Minima Free Parameterized Appearance Models

PubMed Central

Nguyen, Minh Hoai; De la Torre, Fernando

2010-01-01

Parameterized Appearance Models (PAMs) (e.g. Eigentracking, Active Appearance Models, Morphable Models) are commonly used to model the appearance and shape variation of objects in images. While PAMs have numerous advantages relative to alternate approaches, they have at least two drawbacks. First, they are especially prone to local minima in the fitting process. Second, often few if any of the local minima of the cost function correspond to acceptable solutions. To solve these problems, this paper proposes a method to learn a cost function by explicitly optimizing that the local minima occur at and only at the places corresponding to the correct fitting parameters. To the best of our knowledge, this is the first paper to address the problem of learning a cost function to explicitly model local properties of the error surface to fit PAMs. Synthetic and real examples show improvement in alignment performance in comparison with traditional approaches. PMID:21804750
Super-resolution for asymmetric resolution of FIB-SEM 3D imaging using AI with deep learning.

PubMed

Hagita, Katsumi; Higuchi, Takeshi; Jinnai, Hiroshi

2018-04-12

Scanning electron microscopy equipped with a focused ion beam (FIB-SEM) is a promising three-dimensional (3D) imaging technique for nano- and meso-scale morphologies. In FIB-SEM, the specimen surface is stripped by an ion beam and imaged by an SEM installed orthogonally to the FIB. The lateral resolution is governed by the SEM, while the depth resolution, i.e., the FIB milling direction, is determined by the thickness of the stripped thin layer. In most cases, the lateral resolution is superior to the depth resolution; hence, asymmetric resolution is generated in the 3D image. Here, we propose a new approach based on an image-processing or deep-learning-based method for super-resolution of 3D images with such asymmetric resolution, so as to restore the depth resolution to achieve symmetric resolution. The deep-learning-based method learns from high-resolution sub-images obtained via SEM and recovers low-resolution sub-images parallel to the FIB milling direction. The 3D morphologies of polymeric nano-composites are used as test images, which are subjected to the deep-learning-based method as well as conventional methods. We find that the former yields superior restoration, particularly as the asymmetric resolution is increased. Our super-resolution approach for images having asymmetric resolution enables observation time reduction.
The impact of teachers' approaches to teaching and students' learning styles on students' approaches to learning in college online biology courses

NASA Astrophysics Data System (ADS)

Hong, Yuh-Fong

With the rapid growth of online courses in higher education institutions, research on quality of learning for online courses is needed. However, there is a notable lack of research in the cited literature providing evidence that online distance education promotes the quality of independent learning to which it aspires. Previous studies focused on academic outcomes and technology applications which do not monitor students' learning processes, such as their approaches to learning. Understanding students' learning processes and factors influencing quality of learning will provide valuable information for instructors and institutions in providing quality online courses and programs. The purpose of this study was to identify and investigate college biology teachers' approaches to teaching and students' learning styles, and to examine the impact of approaches to teaching and learning styles on students' approaches to learning via online instruction. Data collection included eighty-seven participants from five online biology courses at a community college in the southern area of Texas. Data analysis showed the following results. First, there were significant differences in approaches to learning among students with different learning styles. Second, there was a significant difference in students' approaches to learning between classes using different approaches to teaching. Three, the impact of learning styles on students' approaches to learning was not influenced by instructors' approaches to teaching. Two conclusions were obtained from the results. First, individuals with the ability to perceive information abstractly might be more likely to adopt deep approaches to learning than those preferring to perceive information through concrete experience in online learning environments. Second, Teaching Approach Inventory might not be suitable to measure approaches to teaching for online biology courses due to online instructional design and technology limitations. Based on the findings and conclusions of this study, implications for distance education and future research are described.
Earth Systems Science in an Integrated Science Content and Methods Course for Elementary Education Majors

NASA Astrophysics Data System (ADS)

Madsen, J. A.; Allen, D. E.; Donham, R. S.; Fifield, S. J.; Shipman, H. L.; Ford, D. J.; Dagher, Z. R.

2004-12-01

With funding from the National Science Foundation, we have designed an integrated science content and methods course for sophomore-level elementary teacher education (ETE) majors. This course, the Science Semester, is a 15-credit sequence that consists of three science content courses (Earth, Life, and Physical Science) and a science teaching methods course. The goal of this integrated science and education methods curriculum is to foster holistic understandings of science and pedagogy that future elementary teachers need to effectively use inquiry-based approaches in teaching science in their classrooms. During the Science Semester, traditional subject matter boundaries are crossed to stress shared themes that teachers must understand to teach standards-based elementary science. Exemplary approaches that support both learning science and learning how to teach science are used. In the science courses, students work collaboratively on multidisciplinary problem-based learning (PBL) activities that place science concepts in authentic contexts and build learning skills. In the methods course, students critically explore the theory and practice of elementary science teaching, drawing on their shared experiences of inquiry learning in the science courses. An earth system science approach is ideally adapted for the integrated, inquiry-based learning that takes place during the Science Semester. The PBL investigations that are the hallmark of the Science Semester provide the backdrop through which fundamental earth system interactions can be studied. For example in the PBL investigation that focuses on energy, the carbon cycle is examined as it relates to fossil fuels. In another PBL investigation centered on kids, cancer, and the environment, the hydrologic cycle with emphasis on surface runoff and ground water contamination is studied. In a PBL investigation that has students learning about the Delaware Bay ecosystem through the story of the horseshoe crab and the biome that swirls around this remarkable arthropod, students are exposed to interactions between the hydrosphere, atmosphere, and geosphere and they examine ways in which climate change can affect this ecosystem.

Beyond the "c" and the "x": Learning with algorithms in massive open online courses (MOOCs)

NASA Astrophysics Data System (ADS)

Knox, Jeremy

2018-02-01

This article examines how algorithms are shaping student learning in massive open online courses (MOOCs). Following the dramatic rise of MOOC platform organisations in 2012, over 4,500 MOOCs have been offered to date, in increasingly diverse languages, and with a growing requirement for fees. However, discussions of learning in MOOCs remain polarised around the "xMOOC" and "cMOOC" designations. In this narrative, the more recent extended or platform MOOC ("xMOOC") adopts a broadcast pedagogy, assuming a direct transmission of information to its largely passive audience (i.e. a teacher-centred approach), while the slightly older connectivist model ("cMOOC") offers only a simplistic reversal of the hierarchy, posing students as highly motivated, self-directed and collaborative learners (i.e. a learner-centred approach). The online nature of both models generates data (e.g. on how many times a particular resource was viewed, or the ways in which participants communicated with each other) which MOOC providers use for analysis, albeit only after these data have been selectively processed. Central to many learning analytics approaches is the desire to predict students' future behaviour. Educators need to be aware that MOOC learning is not just about teachers and students, but that it also involves algorithms: instructions which perform automated calculations on data. Education is becoming embroiled in an "algorithmic culture" that defines educational roles, forecasts attainment, and influences pedagogy. Established theories of learning appear wholly inadequate in addressing the agential role of algorithms in the educational domain of the MOOC. This article identifies and examines four key areas where algorithms influence the activities of the MOOC: (1) data capture and discrimination; (2) calculated learners; (3) feedback and entanglement; and (4) learning with algorithms. The article concludes with a call for further research in these areas to surface a critical discourse around the use of algorithms in MOOC education and beyond.
Effects of a blended learning approach on student outcomes in a graduate-level public health course

PubMed Central

2014-01-01

Background Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. Method The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, “traditional” approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. Results There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Conclusions Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses. PMID:24612923
Discovery learning with SAVI approach in geometry learning

NASA Astrophysics Data System (ADS)

Sahara, R.; Mardiyana; Saputro, D. R. S.

2018-05-01

Geometry is one branch of mathematics that an important role in learning mathematics in the schools. This research aims to find out about Discovery Learning with SAVI approach to achievement of learning geometry. This research was conducted at Junior High School in Surakarta city. Research data were obtained through test and questionnaire. Furthermore, the data was analyzed by using two-way Anova. The results showed that Discovery Learning with SAVI approach gives a positive influence on mathematics learning achievement. Discovery Learning with SAVI approach provides better mathematics learning outcomes than direct learning. In addition, students with high self-efficacy categories have better mathematics learning achievement than those with moderate and low self-efficacy categories, while student with moderate self-efficacy categories are better mathematics learning achievers than students with low self-efficacy categories. There is an interaction between Discovery Learning with SAVI approach and self-efficacy toward student's mathematics learning achievement. Therefore, Discovery Learning with SAVI approach can improve mathematics learning achievement.
The implementation of an elementary STEM learning team and the effect on teacher self-efficacy: An action research study

NASA Astrophysics Data System (ADS)

Hernandez, Jennifer F.

Science, technology, engineering, and math (STEM) education is part of a national movement to prepare students for the demands of a 21st century workforce. STEM uses an integrated, real-world problem solving approach to increase the levels of collaboration, communication, critical, and creative thinking in students. If expectations for students have increased to stay competitive in a global market, teachers must be equipped to meet the needs of the new 21st century learners in their classrooms. To that end, professional learning for educators is essential to ensure they are equipped with the tools necessary for success. While there are many approaches to teacher development, professional learning teams, based on the work of Garmston and Wellman, focus on teachers' instructional delivery, targeted student learning needs, planning, implementing new strategies, collaboration, and reflective dialogue. The purpose of the study is to improve instructional practice providing quality STEM instruction to students and increase teacher self-efficacy---a teachers' perception of his or her ability to instruct students in the STEM disciplines. Theoretical implications of a study on an elementary STEM learning team could affect the way schools deliver STEM professional learning opportunities to teachers and the way students are delivered a quality STEM education. Research has shown that Model I behavior would limit the change process of professional learning through a surface inspection of the issues; however model II behaviors would benefit the teachers, students and organization because teachers would be collaborating on specific objectives to develop a knowledge base and skill set to meet students' needs. Extending professional development by engaging stakeholders in a collaborative process to build model II behaviors will create an organizational structure that facilitates learning.
A Machine Learning and Cross-Validation Approach for the Discrimination of Vegetation Physiognomic Types Using Satellite Based Multispectral and Multitemporal Data.

PubMed

Sharma, Ram C; Hara, Keitarou; Hirayama, Hidetake

2017-01-01

This paper presents the performance and evaluation of a number of machine learning classifiers for the discrimination between the vegetation physiognomic classes using the satellite based time-series of the surface reflectance data. Discrimination of six vegetation physiognomic classes, Evergreen Coniferous Forest, Evergreen Broadleaf Forest, Deciduous Coniferous Forest, Deciduous Broadleaf Forest, Shrubs, and Herbs, was dealt with in the research. Rich-feature data were prepared from time-series of the satellite data for the discrimination and cross-validation of the vegetation physiognomic types using machine learning approach. A set of machine learning experiments comprised of a number of supervised classifiers with different model parameters was conducted to assess how the discrimination of vegetation physiognomic classes varies with classifiers, input features, and ground truth data size. The performance of each experiment was evaluated by using the 10-fold cross-validation method. Experiment using the Random Forests classifier provided highest overall accuracy (0.81) and kappa coefficient (0.78). However, accuracy metrics did not vary much with experiments. Accuracy metrics were found to be very sensitive to input features and size of ground truth data. The results obtained in the research are expected to be useful for improving the vegetation physiognomic mapping in Japan.
Active Learning to Understand Infectious Disease Models and Improve Policy Making

PubMed Central

Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-01-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings. PMID:24743387
Active learning to understand infectious disease models and improve policy making.

PubMed

Willem, Lander; Stijven, Sean; Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-04-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings.
Sensory Ecology of Water Detection by Bats: A Field Experiment

PubMed Central

Russo, Danilo; Cistrone, Luca; Jones, Gareth

2012-01-01

Bats face a great risk of dehydration, so sensory mechanisms for water recognition are crucial for their survival. In the laboratory, bats recognized any smooth horizontal surface as water because these provide analogous reflections of echolocation calls. We tested whether bats also approach smooth horizontal surfaces other than water to drink in nature by partly covering watering troughs used by hundreds of bats with a Perspex layer mimicking water. We aimed 1) to confirm that under natural conditions too bats mistake any horizontal smooth surface for water by testing this on large numbers of individuals from a range of species and 2) to assess the occurrence of learning effects. Eleven bat species mistook Perspex for water relying chiefly on echoacoustic information. Using black instead of transparent Perspex did not deter bats from attempting to drink. In Barbastella barbastellus no echolocation differences occurred between bats approaching the water and the Perspex surfaces respectively, confirming that bats perceive water and Perspex to be acoustically similar. The drinking attempt rates at the fake surface were often lower than those recorded in the laboratory: bats then either left the site or moved to the control water surface. This suggests that bats modified their behaviour as soon as the lack of drinking reward had overridden the influence of echoacoustic information. Regardless of which of two adjoining surfaces was covered, bats preferentially approached and attempted to drink from the first surface encountered, probably because they followed a common route, involving spatial memory and perhaps social coordination. Overall, although acoustic recognition itself is stereotyped and its importance in the drinking process overwhelming, our findings point at the role of experience in increasing behavioural flexibility under natural conditions. PMID:23133558
Prediction of delayed retention of antibodies in hydrophobic interaction chromatography from sequence using machine learning.

PubMed

Jain, Tushar; Boland, Todd; Lilov, Asparouh; Burnina, Irina; Brown, Michael; Xu, Yingda; Vásquez, Maximiliano

2017-12-01

The hydrophobicity of a monoclonal antibody is an important biophysical property relevant for its developability into a therapeutic. In addition to characterizing heterogeneity, Hydrophobic Interaction Chromatography (HIC) is an assay that is often used to quantify the hydrophobicity of an antibody to assess downstream risks. Earlier studies have shown that retention times in this assay can be correlated to amino-acid or atomic propensities weighted by the surface areas obtained from protein 3-dimensional structures. The goal of this study is to develop models to enable prediction of delayed HIC retention times directly from sequence. We utilize the randomforest machine learning approach to estimate the surface exposure of amino-acid side-chains in the variable region directly from the antibody sequence. We obtain mean-absolute errors of 4.6% for the prediction of surface exposure. Using experimental HIC data along with the estimated surface areas, we derive an amino-acid propensity scale that enables prediction of antibodies likely to have delayed retention times in the assay. We achieve a cross-validation Area Under Curve of 0.85 for the Receiver Operating Characteristic curve of our model. The low computational expense and high accuracy of this approach enables real-time assessment of hydrophobic character to enable prioritization of antibodies during the discovery process and rational engineering to reduce hydrophobic liabilities. Structure data, aligned sequences, experimental data and prediction scores for test-cases, and R scripts used in this work are provided as part of the Supplementary Material. tushar.jain@adimab.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Optimization of process parameters in CNC turning of aluminium alloy using hybrid RSM cum TLBO approach

NASA Astrophysics Data System (ADS)

Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.

2016-09-01

The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.
ChemApproach: Validation of a Questionnaire to Assess the Learning Approaches of Chemistry Students

ERIC Educational Resources Information Center

Lastusaari, Mika; Laakkonen, Eero; Murtonen, Mari

2016-01-01

The theory of learning approaches has proven to be one of the most powerful theories explaining university students' learning. However, learning approaches are sensitive to the situation and the content of learning. Chemistry has its own specific features that should be considered when exploring chemistry students' learning habits, specifically…
The Relationship between Learning Approaches of Prospective Teachers and Their Academic Achievement

ERIC Educational Resources Information Center

Gurlen, Eda; Turan, Sevgi; Senemoglu, Nuray

2013-01-01

To prepare for future professional challenges, prospective teachers should acquire the capabilities for independent learning. Prospective teachers should know how to learn effectively. In this article, prospective teachers' learning approaches, learning preference and the relationship between learning preference, learning approaches with…
Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches.

PubMed

Papa, E; Doucet, J P; Sangion, A; Doucet-Panaye, A

2016-07-01

The understanding of the mechanisms and interactions that occur when nanomaterials enter biological systems is important to improve their future use. The adsorption of proteins from biological fluids in a physiological environment to form a corona on the surface of nanoparticles represents a key step that influences nanoparticle behaviour. In this study, the quantitative description of the composition of the protein corona was used to study the effect on cell association induced by 84 surface-modified gold nanoparticles of different sizes. Quantitative relationships between the protein corona and the activity of the gold nanoparticles were modelled by using several machine learning-based linear and non-linear approaches. Models based on a selection of only six serum proteins had robust and predictive results. The Projection Pursuit Regression method had the best performances (r(2) = 0.91; Q(2)loo = 0.81; r(2)ext = 0.79). The present study confirmed the utility of protein corona composition to predict the bioactivity of gold nanoparticles and identified the main proteins that act as promoters or inhibitors of cell association. In addition, the comparison of several techniques showed which strategies offer the best results in prediction and could be used to support new toxicological studies on gold-based nanomaterials.
Identification of Functionally Related Enzymes by Learning-to-Rank Methods.

PubMed

Stock, Michiel; Fober, Thomas; Hüllermeier, Eyke; Glinca, Serghei; Klebe, Gerhard; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2014-01-01

Enzyme sequences and structures are routinely used in the biological sciences as queries to search for functionally related enzymes in online databases. To this end, one usually departs from some notion of similarity, comparing two enzymes by looking for correspondences in their sequences, structures or surfaces. For a given query, the search operation results in a ranking of the enzymes in the database, from very similar to dissimilar enzymes, while information about the biological function of annotated database enzymes is ignored. In this work, we show that rankings of that kind can be substantially improved by applying kernel-based learning algorithms. This approach enables the detection of statistical dependencies between similarities of the active cleft and the biological function of annotated enzymes. This is in contrast to search-based approaches, which do not take annotated training data into account. Similarity measures based on the active cleft are known to outperform sequence-based or structure-based measures under certain conditions. We consider the Enzyme Commission (EC) classification hierarchy for obtaining annotated enzymes during the training phase. The results of a set of sizeable experiments indicate a consistent and significant improvement for a set of similarity measures that exploit information about small cavities in the surface of enzymes.
A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks.

PubMed

Wang, Changhan; Yan, Xinchen; Smith, Max; Kochhar, Kanika; Rubin, Marcie; Warren, Stephen M; Wrobel, James; Lee, Honglak

2015-01-01

Wound surface area changes over multiple weeks are highly predictive of the wound healing process. Furthermore, the quality and quantity of the tissue in the wound bed also offer important prognostic information. Unfortunately, accurate measurements of wound surface area changes are out of reach in the busy wound practice setting. Currently, clinicians estimate wound size by estimating wound width and length using a scalpel after wound treatment, which is highly inaccurate. To address this problem, we propose an integrated system to automatically segment wound regions and analyze wound conditions in wound images. Different from previous segmentation techniques which rely on handcrafted features or unsupervised approaches, our proposed deep learning method jointly learns task-relevant visual features and performs wound segmentation. Moreover, learned features are applied to further analysis of wounds in two ways: infection detection and healing progress prediction. To the best of our knowledge, this is the first attempt to automate long-term predictions of general wound healing progress. Our method is computationally efficient and takes less than 5 seconds per wound image (480 by 640 pixels) on a typical laptop computer. Our evaluations on a large-scale wound database demonstrate the effectiveness and reliability of the proposed system.
An investigation into the effectiveness of problem-based learning in a physical chemistry laboratory course

NASA Astrophysics Data System (ADS)

Gürses, Ahmet; Açıkyıldız, Metin; Doğar, Çetin; Sözbilir, Mustafa

2007-04-01

The aim of this study was to investigate the effectiveness of a problem-based learning (PBL) approach in a physical chemistry laboratory course. The parameters investigated were students’ attitudes towards a chemistry laboratory course, scientific process skills of students and their academic achievement. The design of the study was one group pre-test post-test. Four experiments, covering the topics adsorption, viscosity, surface tension and conductivity were performed using a PBL approach in the fall semester of the 2003/04 academic year at Kazim Karabekir Education Faculty of Atatürk University. Each experiment was done over a three week period. A total of 40 students, 18 male and 22 female, participated in the study. Students took the Physical Chemistry Laboratory Concept Test (PCLCT), Attitudes towards Chemistry Laboratory (ATCL) questionnaire and Science Process Skills Test (SPST) as pre and post-tests. In addition, the effectiveness of the PBL approach was also determined through four different scales; Scales Specific to Students’ Views of PBL. A statistically significant difference between the students’ academic achievement and scientific process skills at p
Learner Performance in Multimedia Learning Arrangements: An Analysis across Instructional Approaches

ERIC Educational Resources Information Center

Eysink, Tessa H. S.; de Jong, Ton; Berthold, Kirsten; Kolloffel, Bas; Opfermann, Maria; Wouters, Pieter

2009-01-01

In this study, the authors compared four multimedia learning arrangements differing in instructional approach on effectiveness and efficiency for learning: (a) hypermedia learning, (b) observational learning, (c) self-explanation-based learning, and (d) inquiry learning. The approaches all advocate learners' active attitude toward the learning…
Assessing Online Discussions: A Holistic Approach

ERIC Educational Resources Information Center

Wang, Yu-mei; Chen, Der-Thanq

2017-01-01

This article reports a holistic approach to assessing online discussions. This holistic approach integrates three assessment methods: assessment of learning, assessment for learning, and assessment as learning. Assessment of learning directly examines students' learning products to decide whether they have achieved the expected learning through…
Implementation of Active Teaching Methods and Emerging Topics in Photogrammetry and Remote Sensing Subjects

NASA Astrophysics Data System (ADS)

Kosmatin Fras, M.; Grigillo, D.

2016-06-01

Fast technological developments in photogrammetry and remote sensing areas demand quick and steady changes in the education programme and its realization. The university teachers and assistants are faced with ensuring the learning materials, data and software for practical lessons, as well as project proposals for student's team work and bachelor or master thesis. In this paper the emerging topics that already have a considerable impact in the practice are treated mostly from the educational aspect. These relatively new topics that are considered in this paper are unmanned aerial systems for spatial data collection, terrestrial and aerial laser scanning, mobile mapping systems, and novelties in satellite remote sensing. The focus is given to practical implementation of these topics into the teaching and learning programme of Geodesy and Geoinformation at the University of Ljubljana, Faculty of Civil and Geodetic Engineering, and experiences gained by the authors so far. Together with the technological advances, the teaching approaches must be modernized as well. Classical approaches of teaching, where a lecturer gives lecture ex cathedra and students are only listeners, are not effective enough. The didactics science of teaching has developed and proved in the practice many useful approaches that can better motivate students for more active learning. We can use different methods of team work like pro et contra debate, buzzing groups, press conference, moderated discussion etc. An experimental study on active teaching methods in the class of students of the Master programme of Geodesy and Geoinformation has been made and the results are presented. After using some new teaching methods in the class, the students were asked to answer two types of a questionnaire. First questionnaire was the standard form developed by Noel Entwistle, an educational psychologist who developed the Approaches to Studying Inventory (ASI) for identifying deep and surface approaches to learning. The second questionnaire was developed for our purpose to get the feedback from students on active teaching and learning methods. Although this investigation has been done only for one class of master programme students, the results are encouraging and we could extract some recommendations for the future.
SVMs for Vibration-Based Terrain Classification

NASA Astrophysics Data System (ADS)

Weiss, Christian; Stark, Matthias; Zell, Andreas

When an outdoor mobile robot traverses different types of ground surfaces, different types of vibrations are induced in the body of the robot. These vibrations can be used to learn a discrimination between different surfaces and to classify the current terrain. Recently, we presented a method that uses Support Vector Machines for classification, and we showed results on data collected with a hand-pulled cart. In this paper, we show that our approach also works well on an outdoor robot. Furthermore, we more closely investigate in which direction the vibration should be measured. Finally, we present a simple but effective method to improve the classification by combining measurements taken in multiple directions.

Accelerating the discovery of hidden two-dimensional magnets using machine learning and first principle calculations

NASA Astrophysics Data System (ADS)

Miyazato, Itsuki; Tanaka, Yuzuru; Takahashi, Keisuke

2018-02-01

Two-dimensional (2D) magnets are explored in terms of data science and first principle calculations. Machine learning determines four descriptors for predicting the magnetic moments of 2D materials within reported 216 2D materials data. With the trained machine, 254 2D materials are predicted to have high magnetic moments. First principle calculations are performed to evaluate the predicted 254 2D materials where eight undiscovered stable 2D materials with high magnetic moments are revealed. The approach taken in this work indicates that undiscovered materials can be surfaced by utilizing data science and materials data, leading to an innovative way of discovering hidden materials.
Process-based upscaling of surface-atmosphere exchange

NASA Astrophysics Data System (ADS)

Keenan, T. F.; Prentice, I. C.; Canadell, J.; Williams, C. A.; Wang, H.; Raupach, M. R.; Collatz, G. J.; Davis, T.; Stocker, B.; Evans, B. J.

2015-12-01

Empirical upscaling techniques such as machine learning and data-mining have proven invaluable tools for the global scaling of disparate observations of surface-atmosphere exchange, but are not based on a theoretical understanding of the key processes involved. This makes spatial and temporal extrapolation outside of the training domain difficult at best. There is therefore a clear need for the incorporation of knowledge of ecosystem function, in combination with the strength of data mining. Here, we present such an approach. We describe a novel diagnostic process-based model of global photosynthesis and ecosystem respiration, which is directly informed by a variety of global datasets relevant to ecosystem state and function. We use the model framework to estimate global carbon cycling both spatially and temporally, with a specific focus on the mechanisms responsible for long-term change. Our results show the importance of incorporating process knowledge into upscaling approaches, and highlight the effect of key processes on the terrestrial carbon cycle.
The Effects of Discipline on Deep Approaches to Student Learning and College Outcomes

ERIC Educational Resources Information Center

Nelson Laird, Thomas F.; Shoup, Rick; Kuh, George D.; Schwarz, Michael J.

2008-01-01

"Deep learning" represents student engagement in approaches to learning that emphasize integration, synthesis, and reflection. Because learning is a shared responsibility between students and faculty, it is important to determine whether faculty members emphasize deep approaches to learning and to assess how much students employ these approaches.…
Inquisitivism or "The HHHMMM??? What Does This Button Do?" Approach to Learning.

ERIC Educational Resources Information Center

Harapnuik, Dwayne

This paper discusses the development of a learning approach based on the unique needs of adult learners who are required to learn and use new information technologies. It establishes how the "Inquisitivism" learning approach has evolved from a synthesis of key cognitive learning theories into one cohesive approach and how the…
Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits

PubMed Central

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris

2016-01-01

Phenotyping local crop cultivars is becoming more and more important, as they are an important genetic source for breeding – especially in regard to inherent root system architectures. Machine learning algorithms are promising tools to assist in the analysis of complex data sets; novel approaches are need to apply them on root phenotyping data of mature plants. A greenhouse experiment was conducted in large, sand-filled columns to differentiate 16 European Pisum sativum cultivars based on 36 manually derived root traits. Through combining random forest and support vector machine models, machine learning algorithms were successfully used for unbiased identification of most distinguishing root traits and subsequent pairwise cultivar differentiation. Up to 86% of pea cultivar pairs could be distinguished based on top five important root traits (Timp5) – Timp5 differed widely between cultivar pairs. Selecting top important root traits (Timp) provided a significant improved classification compared to using all available traits or randomly selected trait sets. The most frequent Timp of mature pea cultivars was total surface area of lateral roots originating from tap root segments at 0–5 cm depth. The high classification rate implies that culturing did not lead to a major loss of variability in root system architecture in the studied pea cultivars. Our results illustrate the potential of machine learning approaches for unbiased (root) trait selection and cultivar classification based on rather small, complex phenotypic data sets derived from pot experiments. Powerful statistical approaches are essential to make use of the increasing amount of (root) phenotyping information, integrating the complex trait sets describing crop cultivars. PMID:27999587
The Use of Deep and Surface Learning Strategies among Students Learning English as a Foreign Language in an Internet Environment

ERIC Educational Resources Information Center

Aharony, Noa

2006-01-01

Background: The learning context is learning English in an Internet environment. The examination of this learning process was based on the Biggs and Moore's teaching-learning model (Biggs & Moore, 1993). Aim: The research aims to explore the use of the deep and surface strategies in an Internet environment among EFL students who come from…
How are learning strategies reflected in the eyes? Combining results from self-reports and eye-tracking.

PubMed

Catrysse, Leen; Gijbels, David; Donche, Vincent; De Maeyer, Sven; Lesterhuis, Marije; Van den Bossche, Piet

2018-03-01

Up until now, empirical studies in the Student Approaches to Learning field have mainly been focused on the use of self-report instruments, such as interviews and questionnaires, to uncover differences in students' general preferences towards learning strategies, but have focused less on the use of task-specific and online measures. This study aimed at extending current research on students' learning strategies by combining general and task-specific measurements of students' learning strategies using both offline and online measures. We want to clarify how students process learning contents and to what extent this is related to their self-report of learning strategies. Twenty students with different generic learning profiles (according to self-report questionnaires) read an expository text, while their eye movements were registered to answer questions on the content afterwards. Eye-tracking data were analysed with generalized linear mixed-effects models. The results indicate that students with an all-high profile, combining both deep and surface learning strategies, spend more time on rereading the text than students with an all-low profile, scoring low on both learning strategies. This study showed that we can use eye-tracking to distinguish very strategic students, characterized using cognitive processing and regulation strategies, from low strategic students, characterized by a lack of cognitive and regulation strategies. These students processed the expository text according to how they self-reported. © 2017 The British Psychological Society.
TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, W; Sawant, A; Ruan, D

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit moremore » descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction reliability in such low dimensional manifold. The fixed-point iterative approach turns out to work well practically for the pre-image recovery. Our approach is particularly suitable to facilitate managing respiratory motion in image-guide radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.« less
Changing Students' Approaches to Learning: A Two-Year Study within a University Teacher Training Course

ERIC Educational Resources Information Center

Gijbels, David; Coertjens, Liesje; Vanthournout, Gert; Struyf, Elke; Van Petegem, Peter

2009-01-01

Inciting a deep approach to learning in students is difficult. The present research poses two questions: can a constructivist learning-assessment environment change students' approaches towards a more deep approach? What effect does additional feedback have on the changes in learning approaches? Two cohorts of students completed questionnaires…
Automatic 3D liver location and segmentation via convolutional neural network and graph cut.

PubMed

Lu, Fang; Wu, Fa; Hu, Peijun; Peng, Zhiyi; Kong, Dexing

2017-02-01

Segmentation of the liver from abdominal computed tomography (CT) images is an essential step in some computer-assisted clinical interventions, such as surgery planning for living donor liver transplant, radiotherapy and volume measurement. In this work, we develop a deep learning algorithm with graph cut refinement to automatically segment the liver in CT scans. The proposed method consists of two main steps: (i) simultaneously liver detection and probabilistic segmentation using 3D convolutional neural network; (ii) accuracy refinement of the initial segmentation with graph cut and the previously learned probability map. The proposed approach was validated on forty CT volumes taken from two public databases MICCAI-Sliver07 and 3Dircadb1. For the MICCAI-Sliver07 test dataset, the calculated mean ratios of volumetric overlap error (VOE), relative volume difference (RVD), average symmetric surface distance (ASD), root-mean-square symmetric surface distance (RMSD) and maximum symmetric surface distance (MSD) are 5.9, 2.7 %, 0.91, 1.88 and 18.94 mm, respectively. For the 3Dircadb1 dataset, the calculated mean ratios of VOE, RVD, ASD, RMSD and MSD are 9.36, 0.97 %, 1.89, 4.15 and 33.14 mm, respectively. The proposed method is fully automatic without any user interaction. Quantitative results reveal that the proposed approach is efficient and accurate for hepatic volume estimation in a clinical setup. The high correlation between the automatic and manual references shows that the proposed method can be good enough to replace the time-consuming and nonreproducible manual segmentation method.
Who Benefits from Mastery Learning?

ERIC Educational Resources Information Center

Lai, Patrick; Biggs, John

1994-01-01

Data from 95 educationally disadvantaged Hong Kong students placed in mastery-learning classes were compared with 64 control students in expository-learning classes. Results indicate that under mastery learning, deep- and surface-biased learners increasingly diverge in performance and attitude, with surface learners doing better unit to unit, and…
Health promotion in medical education: lessons from a major undergraduate curriculum implementation.

PubMed

Wylie, Ann; Leedham-Green, Kathleen

2017-11-01

Despite the economic, environmental and patient-related imperatives to prepare medical students to become health promoting doctors, health promotion remains relatively deprioritised in medical curricula. This paper uses an in-depth case study of a health promotion curriculum implementation at a large UK medical school to provide insights into the experiences of teachers and learners across a range of topics, pedagogies, and teaching & assessment modalities. Topics included smoking cessation, behavioural change approaches to obesity, exercise prescribing, social prescribing, maternal and child health, public and global health; with pedagogies ranging from e-learning to practice-based project work. Qualitative methods including focus groups, analysis of reflective learning submissions, and evaluation data are used to illuminate motivations, frustrations, practicalities, successes and limiting factors. Over this three year implementation, a range of challenges have been highlighted including: how adequately to prepare and support clinical teachers; the need to establish relevance and importance to strategic learners; the need for experiential learning in clinical environments to support classroom-based activities; and the need to rebalance competing aspects of the curriculum. Conclusions are drawn about heterogeneous deep learning over standardised surface learning, and the impacts, both positive and negative, of different assessment modalities on these types of learning.
Assessing the Impact of Learning Environments on Students' Approaches to Learning: Comparing Conventional and Action Learning Designs

ERIC Educational Resources Information Center

Wilson, Keithia; Fowler, Jane

2005-01-01

This study investigated whether students' approaches to learning were influenced by the design of university courses. Pre- and post-evaluations of the approaches to learning of the same group of students concurrently enrolled in a conventional course (lectures and tutorials) and an action learning-based course (project work, learning groups) were…
Exam Success at Undergraduate and Graduate-Entry Medical Schools: Is Learning Style or Learning Approach More Important? A Critical Review Exploring Links Between Academic Success, Learning Styles, and Learning Approaches Among School-Leaver Entry ("Traditional") and Graduate-Entry ("Nontraditional") Medical Students.

PubMed

Feeley, Anne-Marie; Biggerstaff, Deborah L

2015-01-01

PHENOMENON: The literature on learning styles over many years has been replete with debate and disagreement. Researchers have yet to elucidate exactly which underlying constructs are measured by the many learning styles questionnaires available. Some academics question whether learning styles exist at all. When it comes to establishing the value of learning styles for medical students, a further issue emerges. The demographics of medical students in the United Kingdom have changed in recent years, so past studies may not be applicable to students today. We wanted to answer a very simple, practical question: what can the literature on learning styles tell us that we can use to help today's medical students succeed academically at medical school? We conducted a literature review to synthesise the available evidence on how two different aspects of learning-the way in which students like to receive information in a learning environment (termed learning "styles") and the motivations that drive their learning (termed learning "approaches")-can impact on medical students' academic achievement. Our review confirms that although learning "styles" do not correlate with exam performance, learning "approaches" do: those with "strategic" and "deep" approaches to learning (i.e., motivated to do well and motivated to learn deeply respectively) perform consistently better in medical school examinations. Changes in medical school entrant demographics in the past decade have not altered these correlations. Optimistically, our review reveals that students' learning approaches can change and more adaptive approaches may be learned. Insights: For educators wishing to help medical students succeed academically, current evidence demonstrates that helping students develop their own positive learning approach using "growth mind-set" is a more effective (and more feasible) than attempting to alter students' learning styles. This conclusion holds true for both "traditional" and graduate-entry medical students.
Approach for Using Learner Satisfaction to Evaluate the Learning Adaptation Policy

ERIC Educational Resources Information Center

Jeghal, Adil; Oughdir, Lahcen; Tairi, Hamid; Radouane, Abdelhay

2016-01-01

The learning adaptation is a very important phase in a learning situation in human learning environments. This paper presents the authors' approach used to evaluate the effectiveness of learning adaptive systems. This approach is based on the analysis of learner satisfaction notices collected by a questionnaire on a learning situation; to analyze…
Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning

PubMed Central

Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie

2016-01-01

Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807
Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.

PubMed

Xu, Bin; Sun, Fuchun

2018-02-01

This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.
Machine Learning Estimates of Natural Product Conformational Energies

PubMed Central

Rupp, Matthias; Bauer, Matthias R.; Wilcken, Rainer; Lange, Andreas; Reutlinger, Michael; Boeckler, Frank M.; Schneider, Gisbert

2014-01-01

Machine learning has been used for estimation of potential energy surfaces to speed up molecular dynamics simulations of small systems. We demonstrate that this approach is feasible for significantly larger, structurally complex molecules, taking the natural product Archazolid A, a potent inhibitor of vacuolar-type ATPase, from the myxobacterium Archangium gephyra as an example. Our model estimates energies of new conformations by exploiting information from previous calculations via Gaussian process regression. Predictive variance is used to assess whether a conformation is in the interpolation region, allowing a controlled trade-off between prediction accuracy and computational speed-up. For energies of relaxed conformations at the density functional level of theory (implicit solvent, DFT/BLYP-disp3/def2-TZVP), mean absolute errors of less than 1 kcal/mol were achieved. The study demonstrates that predictive machine learning models can be developed for structurally complex, pharmaceutically relevant compounds, potentially enabling considerable speed-ups in simulations of larger molecular structures. PMID:24453952
Educational environment and approaches to learning of undergraduate nursing students in an Indonesian school of nursing.

PubMed

Rochmawati, Erna; Rahayu, Gandes Retno; Kumara, Amitya

2014-11-01

The aims of this study were to assess students' perceptions of their educational environment and approaches to learning, and determine if perceptions of learning environment associates with approaches to learning. A survey was conducted to collect data from a regional private university in Indonesia. A total of 232 nursing students completed two questionnaires that measured their perceptions of educational environment and approaches to learning. The measurement was based on Dundee Ready Education Environment Measurement (DREEM) and Approaches and Study Skills Inventory for Students (ASSIST). Five learning environments dimensions and three learning approaches dimensions from two measures were measured. The overall score of DREEM was 131.03/200 (SD 17.04), it was in the range considered to be favourable. The overall score is different significantly between years of study (p value = 0.01). This study indicated that the majority of undergraduate nursing students' adopt strategic approach (n = 139. 59.9%). The finding showed that perceived educational environment significantly associated with approaches to learning. This study implicated the need to maintain conducive learning environment. There is also a need to improve the management of learning activities that reflect the use of student-centered learning. Copyright © 2014 Elsevier Ltd. All rights reserved.
Academic achievement in first-year Portuguese college students: the role of academic preparation and learning strategies.

PubMed

Soares, Ana Paula; Guisande, Adelina M; Almeida, Leandro S; Páramo, Fernanda M

2009-06-01

This paper analyses the role of academic preparation and learning strategies in the prediction of first-year Portuguese college students' academic achievement, considering students' sex and academic field attended. A sample of 445 first-year college students (68.5% female) from the University of Minho (25.8% enrolled in economics, 35.3% in science/technology, and 38.9% in humanities degrees) participated in the study. Students answered a questionnaire on learning strategies in the classroom at the end of the first semester, which consisted of 44 items organized in five dimensions: comprehensive approach, surface approach, personal competency perceptions, intrinsic motivation, and organization of study activities. Academic achievement (grade point average at the end of first year) and academic preparation (students' higher education access mark) were obtained through the academic records of the university. Results showed that academic preparation was the strongest predictor of first-year academic achievement, and only marginal additional variance was explained by learning strategies as assessed by the self-reported questionnaire. There were sex and academic field differences, but these variables do not seem strong enough to affect the results, although the different percentages of variance captured by each model and the different weights associated to higher education access mark, stimulate the use of these and/or other personal and contextual variables when analysing the phenomenon.

Twenty-five-year atraumatic restorative treatment (ART) approach: a comprehensive overview.

PubMed

Frencken, Jo E; Leal, Soraya Coelho; Navarro, Maria Fidela

2012-10-01

The atraumatic restorative treatment (ART) approach was born 25 years ago in Tanzania. It has evolved into an essential caries management concept for improving quality and access to oral care globally. Meta-analyses and systematic reviews have indicated that the high effectiveness of ART sealants using high-viscosity glass ionomers in carious lesion development prevention is not different from that of resin fissure sealants. ART using high-viscosity glass ionomer can safely be used to restore single-surface cavities both in primary and in permanent posterior teeth, but its quality in restoring multiple surfaces in primary posterior teeth cavities needs to be improved. Insufficient information is available regarding the quality of ART restorations in multiple surfaces in permanent anterior and posterior teeth. There appears to be no difference in the survival of single-surface high-viscosity glass-ionomer ART restorations and amalgam restorations. The use of ART results in smaller cavities and in high acceptance of preventive and restorative care by children. Because local anaesthesia is seldom needed and only hand instruments are used, ART is considered to be a promising approach for treating children suffering from early childhood caries. ART has been implemented in the public oral health services of a number of countries, and clearly, proper implementation requires the availability of sufficient stocks of good high-viscosity glass ionomers and sets of ART instruments right from the start. Textbooks including chapters on ART are available, and the concept is being included in graduate courses at dental schools in a number of countries. Recent development and testing of e-learning modules for distance learning has increasingly facilitated the distribution of ART information amongst professionals, thus enabling more people to benefit from ART. However, this development and further research require adequate funding, which is not always easily obtainable. The next major challenge is the continuation of care to the frail elderly, in which ART may play a part. ART, as part of the Basic Package of Oral Care, is an important cornerstone for the development of global oral health and alleviating inequality in oral care.
A Tale of Two Chambers: Iterative Approaches and Lessons Learned from Life Support Systems Testing in Altitude Chambers

NASA Technical Reports Server (NTRS)

Callini, Gianluca

2016-01-01

With a brand new fire set ablaze by a serendipitous convergence of events ranging from a science fiction novel and movie ("The Martian"), to ground-breaking recent discoveries of flowing water on its surface, the drive for the journey to Mars seems to be in a higher gear than ever before. We are developing new spacecraft and support systems to take humans to the Red Planet, while scientists on Earth continue using the International Space Station as a laboratory to evaluate the effects of long duration space flight on the human body. Written from the perspective of a facility test director rather than a researcher, and using past and current life support systems tests as examples, this paper seeks to provide an overview on how facility teams approach testing, the kind of information they need to ensure efficient collaborations and successful tests, and how, together with researchers and principal investigators, we can collectively apply what we learn to execute future tests.
Assessing Students' Development in Learning Approaches According to Initial Learning Profiles: A Person-Oriented Perspective

ERIC Educational Resources Information Center

Vanthournout, Gert; Coertjens, Liesje; Gijbels, David; Donche, Vincent; Van Petegem, Peter

2013-01-01

Research regarding the development of students' learning approaches have at times reported unexpected or lack of expected changes. The current study explores the idea of differential developments in learning approaches according to students' initial learning profiles as a possible explanation for these outcomes. A learning profile is conceived as…
Bridging the Gaps between Learning and Teaching through Recognition of Students' Learning Approaches: A Case Study

ERIC Educational Resources Information Center

Malie, Senian; Akir, Oriah

2012-01-01

Learning approaches, learning methods and learning environments have different effects on students? academic performance. However, they are not the sole factors that impact students? academic achievement. The aims of this research are three-fold: to determine the learning approaches preferred by most students and the impact of the learning…
Does the acceptance of hybrid learning affect learning approaches in France?

PubMed

Marco, Lionel Di; Venot, Alain; Gillois, Pierre

2017-01-01

Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (P< 0.001), which is consistent with their declared learning strategies (personal reorganization of information; search and use of examples). There was no correlation between poor acceptance of the learning model and inadequate learning approaches. The strategy of using deep learning techniques was moderately correlated with acceptance of the learning model (r s = 0.42, P= 0.03). Learning approaches were not affected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.
Does the acceptance of hybrid learning affect learning approaches in France?

PubMed Central

2017-01-01

Purpose Acceptance of a learning technology affects students’ intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students’ way of learning. Methods We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Results Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (P< 0.001), which is consistent with their declared learning strategies (personal reorganization of information; search and use of examples). There was no correlation between poor acceptance of the learning model and inadequate learning approaches. The strategy of using deep learning techniques was moderately correlated with acceptance of the learning model (rs= 0.42, P= 0.03). Conclusion Learning approaches were not affected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students’ time utilization, which explains their neutral intention to use the system. PMID:29051406
Relationships between Learning Approach, Procrastination and Academic Achievement amongst First-Year University Students

ERIC Educational Resources Information Center

Saele, Rannveig Grøm; Dahl, Tove Irene; Sørlie, Tore; Friborg, Oddgeir

2017-01-01

Individual differences in student learning influence academic performance, and two aspects influencing the learning process are the particular learning approach the students use and procrastination behaviour. We examined the relationships between learning approaches, procrastination and academic achievement (measured 1 year later as the grade…
Synthesizing Technology Adoption and Learners' Approaches towards Active Learning in Higher Education

ERIC Educational Resources Information Center

Chan, Kevin; Cheung, George; Wan, Kelvin; Brown, Ian; Luk, Green

2015-01-01

In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners' variations, particularly regarding their styles and approaches to learning, on intention and use of learning technologies. This study contributes to further…
An Ecological Approach to Learning Dynamics

ERIC Educational Resources Information Center

Normak, Peeter; Pata, Kai; Kaipainen, Mauri

2012-01-01

New approaches to emergent learner-directed learning design can be strengthened with a theoretical framework that considers learning as a dynamic process. We propose an approach that models a learning process using a set of spatial concepts: learning space, position of a learner, niche, perspective, step, path, direction of a step and step…
Benefiting from Customer and Competitor Knowledge: A Market-Based Approach to Organizational Learning

ERIC Educational Resources Information Center

Hoe, Siu Loon

2008-01-01

Purpose: The purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market-based approach to organizational learning. Design/methodology/approach: The extant organizational learning…
Economic Gardening through Entrepreneurship Education: A Service-Learning Approach

ERIC Educational Resources Information Center

Desplaces, David E.; Wergeles, Fred; McGuigan, Patrick

2009-01-01

This article outlines the implementation of a service-learning approach in an entrepreneurship programme using an "economic gardening" strategy. Economic Gardening through Service-Learning (EGS-L) is an approach to economic development that helps local businesses and students grow through a facilitated learning process. Learning is made possible…
Comparing Team Learning Approaches through the Lens of Activity Theory

ERIC Educational Resources Information Center

Park, Sunyoung; Cho, Yonjoo; Yoon, Seung Won; Han, Heeyoung

2013-01-01

Purpose: The purpose of this study is to examine the distinctive features of three team learning approaches (action learning, problem-based learning, and project-based learning), compare and contrast them, and discuss implications for practice and research. Design/methodology/approach: The authors used Torraco's integrative literature review…
Estimation of Surface Seawater Fugacity of Carbon Dioxide Using Satellite Data and Machine Learning

NASA Astrophysics Data System (ADS)

Jang, E.; Im, J.; Park, G.; Park, Y.

2016-12-01

The ocean controls the climate of Earth by absorbing and releasing CO2 through the carbon cycle. The amount of CO2 in the ocean has increased since the industrial revolution. High CO2 concentration in the ocean has a negative influence to marine organisms and reduces the ability of absorbing CO2 in the ocean. This study estimated surface seawater fugacity of CO2 (fCO2) in the East Sea of Korea using Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, and Hybrid Coordinate Ocean Model (HYCOM) reanalysis data. GOCI is the world first geostationary ocean color observation satellite sensor, and it provides 8 images with 8 bands hourly per day from 9 am to 4 pm at 500m resolution. Two machine learning approaches (i.e., random forest and support vector regression) were used to model fCO2 in this study. While most of the existing studies used multiple linear regression to estimate the pressure of CO2 in the ocean, machine learning may handle more complex relationship between surface seawater fCO2 and ocean parameters in a dynamic spatiotemporal environment. Five ocean related parameters, colored dissolved organic matter (CDOM), chlorophyll-a (chla), sea surface temperature (SST), sea surface salinity (SSS), and mixed layer depth (MLD), were used as input variables. This study examined two schemes, one with GOCI-derived products and the other with MODIS-derived ones. Results show that random forest performed better than support vector regression regardless of satellite data used. The accuracy of GOCI-based estimation was higher than MODIS-based one, possibly thanks to the better spatiotemporal resolution of GOCI data. MLD was identified the most contributing parameter in estimating surface seawater fCO2 among the five ocean related parameters, which might be related with an active deep convection in the East Sea. The surface seawater fCO2 in summer was higher in general with some spatial variation than the other seasons because of higher SST.
Fuzzy logic path planning system for collision avoidance by an autonomous rover vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1993-01-01

The Space Exploration Initiative of the United States will make great demands upon NASA and its limited resources. One aspect of great importance will be providing for autonomous (unmanned) operation of vehicles and/or subsystems in space flight and surface exploration. An additional, complicating factor is that much of the need for autonomy of operation will take place under conditions of great uncertainty or ambiguity. Issues in developing an autonomous collision avoidance subsystem within a path planning system for application in a remote, hostile environment that does not lend itself well to remote manipulation by Earth-based telecommunications is addressed. A good focus is unmanned surface exploration of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. Four major issues addressed are (1) avoidance of a fuzzy moving obstacle; (2) backoff from a deadend in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system. Examples of the need for collision avoidance by an autonomous rover vehicle on the surface of Mars with a moving obstacle would be wind-blown debris, surface flow or anomalies due to subsurface disturbances, another vehicle, etc. The other issues of backoff, sensor fusion, and adaptive learning are important in the overall path planning system.
Student Experiences of Problem-Based Learning in Pharmacy: Conceptions of Learning, Approaches to Learning and the Integration of Face-to-Face and On-Line Activities

ERIC Educational Resources Information Center

Ellis, Robert A.; Goodyear, Peter; Brillant, Martha; Prosser, Michael

2008-01-01

This study investigates fourth-year pharmacy students' experiences of problem-based learning (PBL). It adopts a phenomenographic approach to the evaluation of problem-based learning, to shed light on the ways in which different groups of students conceive of, and approach, PBL. The study focuses on the way students approach solving problem…
Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study

PubMed Central

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex. PMID:27500640
Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.

PubMed

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex.
"Revisiting" the South Pacific Approaches to Learning: A Confirmatory Factor Analysis Study

ERIC Educational Resources Information Center

Phan, Huy P.; Deo, Bisun

2008-01-01

There has been substantial research evidence concerning the learning approaches of students in Western and non-Western contexts. Nonetheless, it has been a decade since research in the South Pacific was conducted on the learning approaches of tertiary students. The present research examined the learning approaches of Fijian and other Pacific…
Hemispheric Asymmetries in Striatal Reward Responses Relate to Approach-Avoidance Learning and Encoding of Positive-Negative Prediction Errors in Dopaminergic Midbrain Regions.

PubMed

Aberg, Kristoffer Carl; Doell, Kimberly C; Schwartz, Sophie

2015-10-28

Some individuals are better at learning about rewarding situations, whereas others are inclined to avoid punishments (i.e., enhanced approach or avoidance learning, respectively). In reinforcement learning, action values are increased when outcomes are better than predicted (positive prediction errors [PEs]) and decreased for worse than predicted outcomes (negative PEs). Because actions with high and low values are approached and avoided, respectively, individual differences in the neural encoding of PEs may influence the balance between approach-avoidance learning. Recent correlational approaches also indicate that biases in approach-avoidance learning involve hemispheric asymmetries in dopamine function. However, the computational and neural mechanisms underpinning such learning biases remain unknown. Here we assessed hemispheric reward asymmetry in striatal activity in 34 human participants who performed a task involving rewards and punishments. We show that the relative difference in reward response between hemispheres relates to individual biases in approach-avoidance learning. Moreover, using a computational modeling approach, we demonstrate that better encoding of positive (vs negative) PEs in dopaminergic midbrain regions is associated with better approach (vs avoidance) learning, specifically in participants with larger reward responses in the left (vs right) ventral striatum. Thus, individual dispositions or traits may be determined by neural processes acting to constrain learning about specific aspects of the world. Copyright © 2015 the authors 0270-6474/15/3514491-10$15.00/0.
A Janus-Faced Approach to Learning. A Critical Discussion of Habermas' Pragmatic Approach

ERIC Educational Resources Information Center

Italia, Salvatore

2017-01-01

A realist approach to learning is what I propose here. This is based on a non-epistemic dimension whose presence is a necessary assumption for a concept of learning of a life-world as complementary to learning within a life-world. I develop my approach in opposition to Jürgen Habermas' pragmatic approach, which seems to lack of something from a…

Generating Ground Reference Data for a Global Impervious Surface Survey

NASA Technical Reports Server (NTRS)

Tilton, James C.; deColstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.
Case-Based Web Learning Versus Face-to-Face Learning: A Mixed-Method Study on University Nursing Students.

PubMed

Chan, Aileen Wai-Kiu; Chair, Sek-Ying; Sit, Janet Wing-Hung; Wong, Eliza Mi-Ling; Lee, Diana Tze-Fun; Fung, Olivia Wai-Man

2016-03-01

Case-based learning (CBL) is an effective educational method for improving the learning and clinical reasoning skills of students. Advances in e-learning technology have supported the development of the Web-based CBL approach to teaching as an alternative or supplement to the traditional classroom approach. This study aims to examine the CBL experience of Hong Kong students using both traditional classroom and Web-based approaches in undergraduate nursing education. This experience is examined in terms of the perceived self-learning ability, clinical reasoning ability, and satisfaction in learning of these students. A mixture of quantitative and qualitative approaches was adopted. All Year-3 undergraduate nursing students were recruited. CBL was conducted using the traditional classroom approach in Semester 1, and the Web-based approach was conducted in Semester 2. Student evaluations were collected at the end of each semester using a self-report questionnaire. In-depth, focus-group interviews were conducted at the end of Semester 2. One hundred twenty-two students returned their questionnaires. No difference between the face-to-face and Web-based approaches was found in terms of self-learning ability (p = .947), clinical reasoning ability (p = .721), and satisfaction (p = .083). Focus group interview findings complemented survey findings and revealed five themes that reflected the CBL learning experience of Hong Kong students. These themes were (a) the structure of CBL, (b) the learning environment of Web-based CBL, (c) critical thinking and problem solving, (d) cultural influence on CBL learning experience, and (e) student-centered and teacher-centered learning. The Web-based CBL approach was comparable but not superior to the traditional classroom CBL approach. The Web-based CBL experience of these students sheds light on the impact of Chinese culture on student learning behavior and preferences.
Students' Questions: Building a Bridge between Kolb's Learning Styles and Approaches to Learning

ERIC Educational Resources Information Center

de Jesus, Helena T. Pedrosa; Almeida, Patricia Albergaria; Teixeira-Dias, Jose Joaquim; Watts, Mike

2006-01-01

Purpose: The purpose of this study is to identify the types of questions that students ask during the learning of chemistry; discuss the role of students' questions in the process of constructing knowledge, and investigate the relationship between students' questions, approaches to learning, and learning styles. Design/methodology/approach: The…
Understanding Fatty Acid Metabolism through an Active Learning Approach

ERIC Educational Resources Information Center

Fardilha, M.; Schrader, M.; da Cruz e Silva, O. A. B.; da Cruz e Silva, E. F.

2010-01-01

A multi-method active learning approach (MALA) was implemented in the Medical Biochemistry teaching unit of the Biomedical Sciences degree at the University of Aveiro, using problem-based learning as the main learning approach. In this type of learning strategy, students are involved beyond the mere exercise of being taught by listening. Less…
Variability in University Students' Use of Technology: An "Approaches to Learning" Perspective

ERIC Educational Resources Information Center

Mimirinis, Mike

2016-01-01

This study reports the results of a cross-case study analysis of how students' approaches to learning are demonstrated in blended learning environments. It was initially propositioned that approaches to learning as key determinants of the quality of student learning outcomes are demonstrated specifically in how students utilise technology in…
Actively Teaching Research Methods with a Process Oriented Guided Inquiry Learning Approach

ERIC Educational Resources Information Center

Mullins, Mary H.

2017-01-01

Active learning approaches have shown to improve student learning outcomes and improve the experience of students in the classroom. This article compares a Process Oriented Guided Inquiry Learning style approach to a more traditional teaching method in an undergraduate research methods course. Moving from a more traditional learning environment to…
Learning in the real place: medical students' learning and socialization in clerkships at one medical school.

PubMed

Han, Heeyoung; Roberts, Nicole K; Korte, Russell

2015-02-01

To understand medical students' learning experiences in clerkships: learning expectations (what they expect to learn), learning process (how they learn), and learning outcomes (what they learn). Using a longitudinal qualitative research design, the authors followed the experiences of 12 participants across their clerkship year (2011-2012) at the Southern Illinois University School of Medicine. Interview data from each participant were collected at three points (preclerkship, midclerkship, and postclerkship) and analyzed using a grounded theory approach. Additionally, the authors observed participants through a full clerkship day to augment the interviews. Before clerkships, students expected to have more hands-on experiences and become more knowledgeable by translating textbook knowledge to real patients and practicing diagnostic thinking. During clerkships, students experienced ambiguity and subjectivity of attending physicians' expectations and evaluation criteria. They perceived that impression management was important to ensure that they received learning opportunities and good evaluations. After clerkships, students perceived that their confidence increased in navigating the health care environments and interacting with patients, attendings, and residents. However, they felt that there were limited opportunities to practice diagnostic thinking. Students could not clearly discern the decision-making processes used by attending physicians. Although they saw many patients, they perceived that their learning was at the surface level. Students' experiential learning in clerkships occurred through impression management as a function of dynamic social and reciprocal relationships between students and attendings or residents. Students reported that they did not learn comprehensive clinical reasoning skills to the degree they expected in clerkships.
Comparison of student's learning achievement through realistic mathematics education (RME) approach and problem solving approach on grade VII

NASA Astrophysics Data System (ADS)

Ilyas, Muhammad; Salwah

2017-02-01

The type of this research was experiment. The purpose of this study was to determine the difference and the quality of student's learning achievement between students who obtained learning through Realistic Mathematics Education (RME) approach and students who obtained learning through problem solving approach. This study was a quasi-experimental research with non-equivalent experiment group design. The population of this study was all students of grade VII in one of junior high school in Palopo, in the second semester of academic year 2015/2016. Two classes were selected purposively as sample of research that was: year VII-5 as many as 28 students were selected as experiment group I and VII-6 as many as 23 students were selected as experiment group II. Treatment that used in the experiment group I was learning by RME Approach, whereas in the experiment group II by problem solving approach. Technique of data collection in this study gave pretest and posttest to students. The analysis used in this research was an analysis of descriptive statistics and analysis of inferential statistics using t-test. Based on the analysis of descriptive statistics, it can be concluded that the average score of students' mathematics learning after taught using problem solving approach was similar to the average results of students' mathematics learning after taught using realistic mathematics education (RME) approach, which are both at the high category. In addition, It can also be concluded that; (1) there was no difference in the results of students' mathematics learning taught using realistic mathematics education (RME) approach and students who taught using problem solving approach, (2) quality of learning achievement of students who received RME approach and problem solving approach learning was same, which was at the high category.
Changing Students' Approaches to Study through Classroom Exercises.

ERIC Educational Resources Information Center

Gibbs, Graham

1983-01-01

Differentiates among learning to study, teaching study skills, and helping people learn how to learn. Concentrates on learning to learn--a developmental process in which people's conceptions of learning evolve--and describes strategies for helping students learn how to learn to change their approaches to study tasks. (JOW)
Learning gait of quadruped robot without prior knowledge of the environment

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Qijun

2012-09-01

Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most of the walking learning methods are based on robot vision system or some external sensing equipment to estimate the walking performance of certain walking parameters, and therefore are usually only applicable under laboratory condition, where environment can be pre-defined. Inspired by the rhythmic swing movement during walking of legged animals and the behavior of their adjusting their walking gait on different walking surfaces, a concept of walking rhythmic pattern(WRP) is proposed to evaluate the walking specialty of legged robot, which is just based on the walking dynamics of the robot. Based on the onboard acceleration sensor data, a method to calculate WRP using power spectrum in frequency domain and diverse smooth filters is also presented. Since the evaluation of WRP is only based on the walking dynamics data of the robot's body, the proposed method doesn't require prior knowledge of environment and thus can be applied in unknown environment. A gait learning approach of legged robots based on WRP and evolution algorithm(EA) is introduced. By using the proposed approach, a quadruped robot can learn its locomotion by its onboard sensing in an unknown environment, where the robot has no prior knowledge about this place. The experimental result proves proportional relationship exits between WRP match score and walking performance of legged robot, which can be used to evaluate the walking performance in walking optimization under unknown environment.
An exploration of the relationship between academic and experiential learning approaches in vocational education.

PubMed

de Jong, Jan A Stavenga; Wierstra, Ronny F A; Hermanussen, José

2006-03-01

Research on individual learning approaches (or learning styles) is split in two traditions, one of which is biased towards academic learning, and the other towards learning from direct experience. In the reported study, the two traditions are linked by investigating the relationships between school-based (academic) and work-based (experiential) learning approaches of students in vocational education programs. Participants were 899 students of a Dutch school for secondary vocational education; 758 provided data on school-based learning, and 407 provided data on work-based learning, resulting in an overlap of 266 students from whom data were obtained on learning in both settings. Learning approaches in school and work settings were measured with questionnaires. Using factor analysis and cluster analysis, items and students were grouped, both with respect to school- and work-based learning. The study identified two academic learning dimensions (constructive learning and reproductive learning), and three experiential learning dimensions (analysis, initiative, and immersion). Construction and analysis were correlated positively, and reproduction and initiative negatively. Cluster analysis resulted in the identification of three school-based learning orientations and three work-based learning orientations. The relation between the two types of learning orientations, expressed in Cramér's V, appeared to be weak. It is concluded that learning approaches are relatively context specific, which implies that neither theoretical tradition can claim general applicability.
Impact of a Differential Learning Approach on Practical Exam Performance: A Controlled Study in a Preclinical Dental Course.

PubMed

Pabel, Sven-Olav; Pabel, Anne-Kathrin; Schmickler, Jan; Schulz, Xenia; Wiegand, Annette

2017-09-01

The aim of this study was to evaluate if differential learning in a preclinical dental course impacted the performance of dental students in a practical exam (preparation of a gold partial crown) immediately after the training session and 20 weeks later compared to conventional learning. This controlled study was performed in a preclinical course in operative dentistry at a dental school in Germany. Third-year students were trained in preparing gold partial crowns by using either the conventional learning (n=41) or the differential learning approach (n=32). The differential learning approach consisted of 20 movement exercises with a continuous change of movement execution during the learning session, while the conventional learning approach was mainly based on repetition, a methodological series of exercises, and correction of preparations during the training phase. Practical exams were performed immediately after the training session (T1) and 20 weeks later (T2, retention test). Preparations were rated by four independent and blinded examiners. At T1, no significant difference between the performance (exam passed) of the two groups was detected (conventional learning: 54.3%, differential learning: 68.0%). At T2, significantly more students passed the exam when trained by the differential learning approach (68.8%) than by the conventional learning approach (18.9%). Interrater reliability was moderate (Kappa: 0.57, T1) or substantial (Kappa: 0.67, T2), respectively. These results suggest that a differential learning approach can increase the manual skills of dental students.
Approaches to Learning and Kolb's Learning Styles of Undergraduates with Better Grades

NASA Astrophysics Data System (ADS)

Almeida, Patrícia; Teixeira-Dias, José Joaquim; Martinho, Mariana; Balasooriya, Chinthaka

The purpose of this study is to investigate if the teaching, learning and assessment strategies conceived and implemented in a higher education chemistry course promote the development of conceptual understanding, as intended. Thus, our aim is to analyse the learning styles and the approaches to learning of chemistry undergraduates with better grades. The overall results show that the students with better grades possess the assimilator learning style, that is usually associated to the archetypal chemist. Moreover, the students with the highest grades revealed a conception of learning emphasising understanding. However, these students diverged both in their learning approaches and in their preferences for teaching strategies. The majority of students adopted a deep approach or a combination of a deep and a strategic approach, but half of them revealed their preference for teaching-centred strategies.
The relationship between learning preferences (styles and approaches) and learning outcomes among pre-clinical undergraduate medical students.

PubMed

Liew, Siaw-Cheok; Sidhu, Jagmohni; Barua, Ankur

2015-03-11

Learning styles and approaches of individual undergraduate medical students vary considerably and as a consequence, their learning needs also differ from one student to another. This study was conducted to identify different learning styles and approaches of pre-clinical, undergraduate medical students and also to determine the relationships of learning preferences with performances in the summative examinations. A cross-sectional study was conducted among randomly selected 419 pre-clinical, undergraduate medical students of the International Medical University (IMU) in Kuala Lumpur. The number of students from Year 2 was 217 while that from Year 3 was 202. The Visual, Auditory, Read/Write, Kinesthetic (VARK) and the Approaches and Study Skills Inventory for Students (ASSIST) questionnaires were used for data collection. This study revealed that 343 students (81.9%) had unimodal learning style, while the remaining 76 (18.1%) used a multimodal learning style. Among the unimodal learners, a majority (30.1%) were of Kinesthetic (K) type. Among the middle and high achievers in summative examinations, a majority had unimodal (Kinaesthetic) learning style (30.5%) and were also strategic/deep learners (79.4%). However, the learning styles and approaches did not contribute significantly towards the learning outcomes in summative examinations. A majority of the students in this study had Unimodal (Kinesthetic) learning style. The learning preferences (styles and approaches) did not contribute significantly to the learning outcomes. Future work to re-assess the viability of these learning preferences (styles and approaches) after the incorporation of teaching-learning instructions tailored specifically to the students will be beneficial to help medical teachers in facilitating students to become more capable learners.
Do Learning Approaches of Medical Students Affect Their Satisfaction with Problem-Based Learning?

ERIC Educational Resources Information Center

Gurpinar, Erol; Kulac, Esin; Tetik, Cihat; Akdogan, Ilgaz; Mamakli, Sumer

2013-01-01

The aim of this research was to determine the satisfaction of medical students with problem-based learning (PBL) and their approaches to learning to investigate the effect of learning approaches on their levels of satisfaction. The study group was composed of medical students from three different universities, which apply PBL at different levels…
Relational Analysis of College Chemistry-Major Students' Conceptions of and Approaches to Learning Chemistry

ERIC Educational Resources Information Center

Li, Wei-Ting; Liang, Jyh-Chong; Tsai, Chin-Chung

2013-01-01

The purpose of this research was to examine the relationships between conceptions of learning and approaches to learning in chemistry. Two questionnaires, conceptions of learning chemistry (COLC) and approaches to learning chemistry (ALC), were developed to identify 369 college chemistry-major students' (220 males and 149 females) conceptions of…
Advanced recognition of explosives in traces on polymer surfaces using LIBS and supervised learning classifiers.

PubMed

Serrano, Jorge; Moros, Javier; Sánchez, Carlos; Macías, Jorge; Laserna, J Javier

2014-01-02

The large similarity existing in the spectral emissions collected from organic compounds by laser-induced breakdown spectroscopy (LIBS) is a limiting factor for the use of this technology in the real world. Specifically, among the most ambitious challenges of today's LIBS involves the recognition of an organic residue when neglected on the surface of an object of identical nature. Under these circumstances, the development of an efficient algorithm to disclose the minute differences within this highly complex spectral information is crucial for a realistic application of LIBS in countering explosive threats. An approach cemented on scatter plots of characteristic emission features has been developed to identify organic explosives when located on polymeric surfaces (teflon, nylon and polyethylene). By using selected spectral variables, the approach allows to design a concise classifier for alerting when one of four explosives (DNT, TNT, RDX and PETN) is present on the surface of the polymer. Ordinary products (butter, fuel oil, hand cream, olive oil and motor oil) cause no confusion in the decisions taken by the classifier. With rates of false negatives and false positives below 5%, results demonstrate that the classification algorithm enables to label residues according to their harmful nature in the most demanding scenario for a LIBS sensor. Copyright © 2013 Elsevier B.V. All rights reserved.
JiFUNzeni: A Blended Learning Approach for Sustainable Teachers' Professional Development

ERIC Educational Resources Information Center

Onguko, Brown Bully

2014-01-01

JiFUNzeni blended learning approach is a sustainable approach to provision of professional development (PD) for those in challenging educational contexts. JiFUNzeni approach emphasizes training regional experts to create blended learning content, working with appropriate technology while building content repositories. JiFUNzeni approach was…
Multiple Learning Approaches in the Professional Development of School Leaders -- Theoretical Perspectives and Empirical Findings on Self-assessment and Feedback

ERIC Educational Resources Information Center

Huber, Stephan Gerhard

2013-01-01

This article investigates the use of multiple learning approaches and different modes and types of learning in the (continuous) professional development (PD) of school leaders, particularly the use of self-assessment and feedback. First, formats and multiple approaches to professional learning are described. Second, a possible approach to…
Active Learning by Querying Informative and Representative Examples.

PubMed

Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua

2014-10-01

Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the abundance of unlabeled data and the high cost of labeling. Most active learning approaches select either informative or representative unlabeled instances to query their labels, which could significantly limit their performance. Although several active learning algorithms were proposed to combine the two query selection criteria, they are usually ad hoc in finding unlabeled instances that are both informative and representative. We address this limitation by developing a principled approach, termed QUIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an unlabeled instance. Further, by incorporating the correlation among labels, we extend the QUIRE approach to multi-label learning by actively querying instance-label pairs. Extensive experimental results show that the proposed QUIRE approach outperforms several state-of-the-art active learning approaches in both single-label and multi-label learning.

Effects of Collaborative Learning Styles on Performance of Students in a Ubiquitous Collaborative Mobile Learning Environment

ERIC Educational Resources Information Center

Fakomogbon, Michael Ayodele; Bolaji, Hameed Olalekan

2017-01-01

Collaborative learning is an approach employed by instructors to facilitate learning and improve learner's performance. Mobile learning can accommodate a variety of learning approaches. This study, therefore, investigated the effects of collaborative learning styles on performance of students in a mobile learning environment. The specific purposes…
Undergraduate students' earth science learning: relationships among conceptions, approaches, and learning self-efficacy in Taiwan

NASA Astrophysics Data System (ADS)

Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

2016-06-01

In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to explore the relationships among undergraduates' conceptions of, approaches to, and self-efficacy for learning earth science by adopting the structural equation modeling technique. A total of 268 Taiwanese undergraduates (144 females) participated in this study. Three instruments were modified to assess the students' conceptions of, approaches to, and self-efficacy for learning earth science. The results indicated that students' conceptions of learning made a significant contribution to their approaches to learning, which were consequently correlated with their learning self-efficacy. More specifically, students with stronger agreement that learning earth science involves applying the knowledge and skills learned to unknown problems were prone to possess higher confidence in learning earth science. Moreover, students viewing earth science learning as understanding earth science knowledge were more likely to adopt meaningful strategies to learn earth science, and hence expressed a higher sense of self-efficacy. Based on the results, practical implications and suggestions for future research are discussed.
Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-12-09

We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less
Correlational Neural Networks.

PubMed

Chandar, Sarath; Khapra, Mitesh M; Larochelle, Hugo; Ravindran, Balaraman

2016-02-01

Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when projected to the common subspace. AE-based methods learn a common representation by minimizing the error of reconstructing the two views. Each of these approaches has its own advantages and disadvantages. For example, while CCA-based approaches outperform AE-based approaches for the task of transfer learning, they are not as scalable as the latter. In this work, we propose an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace. Through a series of experiments, we demonstrate that the proposed CorrNet is better than AE and CCA with respect to its ability to learn correlated common representations. We employ CorrNet for several cross-language tasks and show that the representations learned using it perform better than the ones learned using other state-of-the-art approaches.
Approaches to Learning or Levels of Processing: What Did Marton and Säljö (1976a) Really Say? the Legacy of the Work of the Göteborg Group in the 1970s

ERIC Educational Resources Information Center

Richardson, John T.

2015-01-01

Marton and Säljö ("Br J Educ Psychol" 46:4-11, 1976a) described deep-level and surface-level processing in experiments in which students read and recalled academic texts. They did not discuss whether levels of processing had any counterparts in students' everyday studies. However, their article is often credited as the source of the…
Joint Information Theoretic and Differential Geometrical Approach for Robust Automated Target Recognition

DTIC Science & Technology

2012-02-29

surface and Swiss roll) and real-world data sets (UCI Machine Learning Repository [12] and USPS digit handwriting data). In our experiments, we use...less than µn ( say µ = 0.8), we can first use screening technique to select µn candidate nodes, and then apply BIPS on them for further selection and...identified from node j to node i. So we can say the probability for the existence of this connection is approximately 82%. Given the probability matrix
A Comparative Study of Learning Strategies Used by Romanian and Hungarian Preuniversity Students in Science Learning

ERIC Educational Resources Information Center

Lingvay, Mónika; Timofte, Roxana S.; Ciascai, Liliana; Predescu, Constantin

2015-01-01

Development of pupils' deep learning approach is an important goal of education nowadays, considering that a deep learning approach is mediating conceptual understanding and transfer. Different performance at PISA tests of Romanian and Hungarian pupils cause us to commence a study for the analysis of learning approaches employed by these pupils.…
Effects of the Digital Game-Development Approach on Elementary School Students' Learning Motivation, Problem Solving, and Learning Achievement

ERIC Educational Resources Information Center

Chu, Hui-Chun; Hung, Chun-Ming

2015-01-01

In this study, the game-based development approach is proposed for improving the learning motivation, problem solving skills, and learning achievement of students. An experiment was conducted on a learning activity of an elementary school science course to evaluate the performance of the proposed approach. A total of 59 sixth graders from two…
Using the Learners-as-Ethnographers Approach to Enhance Intercultural Learning among American College Students Learning Chinese as a Foreign Language

ERIC Educational Resources Information Center

Lu, Minhui

2012-01-01

This study explored how the learners-as-ethnographers (LAE) approach facilitated intercultural learning among American students learning Chinese as a foreign language. Two research questions addressed the effectiveness of the LAE approach and students' learning experiences in a non-immersion context. I designed six ethnographic tasks for the…
Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches

ERIC Educational Resources Information Center

Wang, Victor C. X.

2010-01-01

As adult learners and educators pioneer the use of technology in the new century, attention has been focused on developing strategic approaches to effectively integrate adult learning and technology in different learning environments. "Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches" provides innovative…
Hybrid E-Learning Tool TransLearning: Video Storytelling to Foster Vicarious Learning within Multi-Stakeholder Collaboration Networks

ERIC Educational Resources Information Center

van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.

2016-01-01

E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach "TransLearning" by investigation into how its storytelling e-tool supported informal vicarious…
Toward a Social Approach to Learning in Community Service Learning

ERIC Educational Resources Information Center

Cooks, Leda; Scharrer, Erica; Paredes, Mari Castaneda

2004-01-01

The authors describe a social approach to learning in community service learning that extends the contributions of three theoretical bodies of scholarship on learning: social constructionism, critical pedagogy, and community service learning. Building on the assumptions about learning described in each of these areas, engagement, identity, and…
PBL and beyond: trends in collaborative learning.

PubMed

Pluta, William J; Richards, Boyd F; Mutnick, Andrew

2013-01-01

Building upon the disruption to lecture-based methods triggered by the introduction of problem-based learning, approaches to promote collaborative learning are becoming increasingly diverse, widespread and generally well accepted within medical education. Examples of relatively new, structured collaborative learning methods include team-based learning and just-in-time teaching. Examples of less structured approaches include think-pair share, case discussions, and the flipped classroom. It is now common practice in medical education to employ a range of instructional approaches to support collaborative learning. We believe that the adoption of such approaches is entering a new and challenging era. We define collaborate learning by drawing on the broader literature, including Chi's ICAP framework that emphasizes the importance of sustained, interactive explanation and elaboration by learners. We distinguish collaborate learning from constructive, active, and passive learning and provide preliminary evidence documenting the growth of methods that support collaborative learning. We argue that the rate of adoption of collaborative learning methods will accelerate due to a growing emphasis on the development of team competencies and the increasing availability of digital media. At the same time, the adoption collaborative learning strategies face persistent challenges, stemming from an overdependence on comparative-effectiveness research and a lack of useful guidelines about how best to adapt collaborative learning methods to given learning contexts. The medical education community has struggled to consistently demonstrate superior outcomes when using collaborative learning methods and strategies. Despite this, support for their use will continue to expand. To select approaches with the greatest utility, instructors must carefully align conditions of the learning context with the learning approaches under consideration. Further, it is critical that modifications are made with caution and that instructors verify that modifications do not impede the desired cognitive activities needed to support meaningful collaborative learning.
Mathematics Literacy on Problem Based Learning with Indonesian Realistic Mathematics Education Approach Assisted E-Learning Edmodo

NASA Astrophysics Data System (ADS)

Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.

2016-02-01

This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.
Looking at Learning Approaches from the Angle of Student Profiles

ERIC Educational Resources Information Center

Kyndt, Eva; Dochy, Filip; Struyven, Katrien; Cascallar, Eduardo

2012-01-01

This study starts with investigating the relation of perceived workload, motivation for learning and working memory capacity (WMC) with students' approaches to learning. Secondly, this study investigates if differences exist between different student profiles concerning their approach to the learning and the influence of workloads thereon. Results…
Game-Enhanced Simulation as an Approach to Experiential Learning in Business English

ERIC Educational Resources Information Center

Punyalert, Sansanee

2017-01-01

This dissertation aims to integrate various learning approaches, i.e., multiple literacies, experiential learning, game-enhanced learning, and global simulation, into an extracurricular module, in which it remodels traditional ways of teaching input, specifically, the lexical- and grammatical-only approaches of business English at a private…
Investigative Primary Science: A Problem-Based Learning Approach

ERIC Educational Resources Information Center

Etherington, Matthew B.

2011-01-01

This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…
Approaches to Learning and Study Orchestrations in High School Students

ERIC Educational Resources Information Center

Cano, Francisco

2007-01-01

In the framework of the SAL (Students' approaches to learning) position, the learning experience (approaches to learning and study orchestrations) of 572 high school students was explored, examining its interrelationships with some personal and familial variables. Three major results emerged. First, links were found between family's intellectual…
Mayan Children's Creation of Learning Ecologies by Initiative and Cooperative Action.

PubMed

de León, Lourdes

2015-01-01

This chapter examines Mayan children's initiatives in creating their own learning environments in collaboration with others as they engage in culturally relevant endeavors of family and community life. To this end, I carry out a fine-grained ethnographic and linguistic analysis of the interactional emergence of learning ecologies. Erickson defines learning ecology as a socioecological system where participants mutually influence one another through verbal and nonverbal actions, as well as through other forms of semiotic communication (2010, 254). In analyzing learning ecologies, I adopt a "theory of action" approach, taking into account multimodal communication (e.g., talk, gesture, gaze, body positioning), participants' sociospatial organization, embodied action, objects, tools, and other culturally relevant materials brought together to build action (Goodwin, 2000, 2013; Hutchins, 1995). I use microethnographic analysis (Erickson, 1992) to bring to the surface central aspects of children's agentive roles in learning through "cooperative actions" (Goodwin, 2013) and "hands-on" experience (Ingold, 2007) the skills of competent members of their community. I examine three distinct Learning Ecologies created by children's initiatives among the Mayan children that I observed: (i) children requesting guidance to collaborate in a task, (ii) older children working on their own initiative with subsequent monitoring and correction from competent members, and (iii) children with near competence in a task with occasional monitoring and no guidance. I argue that these findings enrich and add power to models of family- and community-based learning such as Learning by Observing and Pitching In (Rogoff, 2014). © 2015 Elsevier Inc. All rights reserved.
Science of learning is learning of science: why we need a dialectical approach to science education research

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael

2012-06-01

Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed in the other. Even more interestingly, the scientists studying science learning rarely consider their own learning in relation to the phenomena they study. A dialectical, reflexive approach to learning, however, would theorize the movement of an educational science (its learning and development) as a special and general case—subject matter and method—of the phenomenon of learning (in/of) science. In the dialectical approach to the study of science learning, therefore, subject matter, method, and theory fall together. This allows for a perspective in which not only disparate fields of study—school science learning and learning in everyday life—are integrated but also where the progress in the science of science learning coincides with its topic. Following the articulation of a contradictory situation on comparing learning in different settings, I describe the dialectical approach. As a way of providing a concrete example, I then trace the historical movement of my own research group as it simultaneously and alternately studied science learning in formal and informal settings. I conclude by recommending cultural-historical, dialectical approaches to learning and interaction analysis as a context for fruitful interdisciplinary research on science learning within and across different settings.

A Blended Learning Approach to Teaching Project Management: A Model for Active Participation and Involvement--Insights from Norway

ERIC Educational Resources Information Center

Hussein, Bassam A.

2015-01-01

The paper demonstrates and evaluates the effectiveness of a blended learning approach to create a meaningful learning environment. We use the term blended learning approach in this paper to refer to the use of multiple or hybrid instructional methods that emphasize the role of learners as contributors to the learning process rather than recipients…
Approaches to Machine Learning.

DTIC Science & Technology

1984-02-16

The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. (Author)
A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

PubMed

Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne

2016-04-01

Existing evidence suggests that ambient ultrafine particles (UFPs) (<0.1µm) may contribute to acute cardiorespiratory morbidity. However, few studies have examined the long-term health effects of these pollutants owing in part to a need for exposure surfaces that can be applied in large population-based studies. To address this need, we developed a land use regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
Pre-Service English Teachers in Blended Learning Environment in Respect to Their Learning Approaches

ERIC Educational Resources Information Center

Yilmaz, M. Betul; Orhan, Feza

2010-01-01

Blended learning environment (BLE) is increasingly used in the world, especially in university degrees and it is based on integrating web-based learning and face-to-face (FTF) learning environments. Besides integrating different learning environments, BLE also addresses to students with different learning approaches. The "learning…
Immunity-Based Aircraft Fault Detection System

NASA Technical Reports Server (NTRS)

Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

2004-01-01

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.
The study of effectiveness of blended learning approach for medical training courses.

PubMed

Karamizadeh, Z; Zarifsanayei, N; Faghihi, A A; Mohammadi, H; Habibi, M

2012-01-01

Blended learning as a method of learning that includes face to face learning, pure E-learning and didactic learning. This study aims to investigate the efficacy of medical education by this approach. This interventional study was performed in 130 students at different clinical levels participating in class sessions on "congenital adrenal hyperplasia and ambiguous genitalia". Sampling was done gradually during 6 months and all of them filled a pretest questionnaire and received an educational compact disk. One week later, a presence class session was held in a question and answer and problem solving method. Two to four weeks later, they filled a posttest questionnaire. There was a significant correlation between pretest and posttest scores and the posttest scores were significantly more than the pretest ones. Sub-specialized residents had the most and the students had the least attitude towards blended learning approach. There was a significant correlation between the research samples' accessibility to computer and their attitude and satisfaction to blended learning approach. Findings generally showed that the blended learning was an effective approach in making a profound learning of academic subjects.
Characterizing water-metal interfaces and machine learning potential energy surfaces

NASA Astrophysics Data System (ADS)

Ryczko, Kevin

In this thesis, we first discuss the fundamentals of ab initio electronic structure theory and density functional theory (DFT). We also discuss statistics related to computing thermodynamic averages of molecular dynamics (MD). We then use this theory to analyze and compare the structural, dynamical, and electronic properties of liquid water next to prototypical metals including platinum, graphite, and graphene. Our results are built on Born-Oppenheimer molecular dynamics (BOMD) generated using density functional theory (DFT) which explicitly include van der Waals (vdW) interactions within a first principles approach. All calculations reported use large simulation cells, allowing for an accurate treatment of the water-electrode interfaces. We have included vdW interactions through the use of the optB86b-vdW exchange correlation functional. Comparisons with the Perdew-Burke-Ernzerhof (PBE) exchange correlation functional are also shown. We find an initial peak, due to chemisorption, in the density profile of the liquid water-Pt interface not seen in the liquid water-graphite interface, liquid watergraphene interface, nor interfaces studied previously. To further investigate this chemisorption peak, we also report differences in the electronic structure of single water molecules on both Pt and graphite surfaces. We find that a covalent bond forms between the single water molecule and the platinum surface, but not between the single water molecule and the graphite surface. We also discuss the effects that defects and dopants in the graphite and graphene surfaces have on the structure and dynamics of liquid water. Lastly, we introduce artificial neural networks (ANNs), and demonstrate how they can be used to machine learn electronic structure calculations. As a proof of principle, we show the success of an ANN potential energy surfaces for a dimer molecule with a Lennard-Jones potential.
A work-based learning approach for clinical support workers on mental health inpatient wards.

PubMed

Kemp, Philip; Gilding, Moorene; Seewooruttun, Khooseal; Walsh, Hannah

2016-09-14

Background With a rise in the number of unqualified staff providing health and social care, and reports raising concerns about the quality of care provided, there is a need to address the learning needs of clinical support workers. This article describes a qualitative evaluation of a service improvement project that involved a work-based learning approach for clinical support workers on mental health inpatient wards. Aim To investigate and identify insights in relation to the content and process of learning using a work-based learning approach for clinical support workers. Method This was a qualitative evaluation of a service improvement project involving 25 clinical support workers at the seven mental health inpatient units in South London and Maudsley NHS Foundation Trust. Three clinical skills tutors were appointed to develop, implement and evaluate the work-based learning approach. Four sources of data were used to evaluate this approach, including reflective journals, qualitative responses to questionnaires, three focus groups involving the clinical support workers and a group interview involving the clinical skills tutors. Data were analysed using thematic analysis. Findings The work-based learning approach was highly valued by the clinical support workers and enhanced learning in practice. Face-to-face learning in practice helped the clinical support workers to develop practice skills and reflective learning skills. Insights relating to the role of clinical support workers were also identified, including the benefits of face-to-face supervision in practice, particularly in relation to the interpersonal aspects of care. Conclusion A work-based learning approach has the potential to enhance care delivery by meeting the learning needs of clinical support workers and enabling them to apply learning to practice. Care providers should consider how the work-based learning approach can be used on a systematic, organisation-wide basis in the context of budgetary restrictions.
Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

PubMed

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.
Modeling Change in Learning Strategies throughout Higher Education: A Multi-Indicator Latent Growth Perspective

PubMed Central

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles – Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain. PMID:23844112
Supporting Blended-Learning: Tool Requirements and Solutions with OWLish

ERIC Educational Resources Information Center

Álvarez, Ainhoa; Martín, Maite; Fernández-Castro, Isabel; Urretavizcaya, Maite

2016-01-01

Currently, most of the educational approaches applied to higher education combine face-to-face (F2F) and computer-mediated instruction in a Blended-Learning (B-Learning) approach. One of the main challenges of these approaches is fully integrating the traditional brick-and-mortar classes with online learning environments in an efficient and…
Developing an International Distance Education Program: A Blended Learning Approach

ERIC Educational Resources Information Center

Mathur, Ravisha; Oliver, Lisa

2007-01-01

Building a dynamic international distance education program can be a complex operation. The purpose of this paper is to discuss a model for global learning that utilizes a blended learning approach. This paper will describe how a blended learning approach was implemented in an international instructional technology Master's program to the benefit…
Sequenced Integration and the Identification of a Problem-Solving Approach through a Learning Process

ERIC Educational Resources Information Center

Cormas, Peter C.

2016-01-01

Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…
Interrelations among University Students' Approaches to Learning, Regulation of Learning, and Cognitive and Attributional Strategies: A Person Oriented Approach

ERIC Educational Resources Information Center

Heikkila, Annamari; Niemivirta, Markku; Nieminen, Juha; Lonka, Kirsti

2011-01-01

This study investigated the relationships among approaches to learning, regulation of learning, cognitive and attributional strategies, stress, exhaustion, and study success. University students (N = 437) from three faculties filled in a questionnaire concerning their self-reported study behaviour, cognitive strategies, and well-being. Their…
Healthcare students' experiences when integrating e-learning and flipped classroom instructional approaches.

PubMed

Telford, Mark; Senior, Emma

2017-06-08

This article describes the experiences of undergraduate healthcare students taking a module adopting a 'flipped classroom' approach. Evidence suggests that flipped classroom as a pedagogical tool has the potential to enhance student learning and to improve healthcare practice. This innovative approach was implemented within a healthcare curriculum and in a module looking at public health delivered at the beginning of year two of a 3-year programme. The focus of the evaluation study was on the e-learning resources used in the module and the student experiences of these; with a specific aim to evaluate this element of the flipped classroom approach. A mixed-methods approach was adopted and data collected using questionnaires, which were distributed across a whole cohort, and a focus group involving ten participants. Statistical analysis of the data showed the positive student experience of engaging with e-learning. The thematic analysis identified two key themes; factors influencing a positive learning experience and the challenges when developing e-learning within a flipped classroom approach. The study provides guidance for further developments and improvements when developing e-learning as part of the flipped classroom approach.
Linking Action Learning and Inter-Organisational Learning: The Learning Journey Approach

ERIC Educational Resources Information Center

Schumacher, Thomas

2015-01-01

The article presents and illustrates the learning journey (LJ)--a new management development approach to inter-organisational learning based on observation, reflection and problem-solving. The LJ involves managers from different organisations and applies key concepts of action learning and systemic organisational development. Made up of…
Promoting Sustainable Living in the Borderless World through Blended Learning Platforms

ERIC Educational Resources Information Center

Ng, Khar Thoe; Parahakaran, Suma; Febro, Rhea; Weisheit, Egbert; Lee, Tan Luck

2013-01-01

Student-centred learning approaches like collaborative learning are needed to facilitate meaningful learning among self-motivated lifelong learners within educational institutions through interorganizational Open and Distant Learning (ODL) approaches. The purpose of this study is to develop blended learning platforms to promote sustainable living,…
Development of Scientific Approach Based on Discovery Learning Module

NASA Astrophysics Data System (ADS)

Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

2018-04-01

Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on discovery learning and scientific approach in electrolyte and non-electrolyte solution and Acid Based for the 10th and 11th grade of senior high school students were valid, practice, and effective.
Weakly supervised visual dictionary learning by harnessing image attributes.

PubMed

Gao, Yue; Ji, Rongrong; Liu, Wei; Dai, Qionghai; Hua, Gang

2014-12-01

Bag-of-features (BoFs) representation has been extensively applied to deal with various computer vision applications. To extract discriminative and descriptive BoF, one important step is to learn a good dictionary to minimize the quantization loss between local features and codewords. While most existing visual dictionary learning approaches are engaged with unsupervised feature quantization, the latest trend has turned to supervised learning by harnessing the semantic labels of images or regions. However, such labels are typically too expensive to acquire, which restricts the scalability of supervised dictionary learning approaches. In this paper, we propose to leverage image attributes to weakly supervise the dictionary learning procedure without requiring any actual labels. As a key contribution, our approach establishes a generative hidden Markov random field (HMRF), which models the quantized codewords as the observed states and the image attributes as the hidden states, respectively. Dictionary learning is then performed by supervised grouping the observed states, where the supervised information is stemmed from the hidden states of the HMRF. In such a way, the proposed dictionary learning approach incorporates the image attributes to learn a semantic-preserving BoF representation without any genuine supervision. Experiments in large-scale image retrieval and classification tasks corroborate that our approach significantly outperforms the state-of-the-art unsupervised dictionary learning approaches.
Learning styles and approaches to learning among medical undergraduates and postgraduates

PubMed Central

2013-01-01

Background The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. Methods We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. Results A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners. Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. Conclusions The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period. PMID:23521845

Learning styles and approaches to learning among medical undergraduates and postgraduates.

PubMed

Samarakoon, Lasitha; Fernando, Tharanga; Rodrigo, Chaturaka

2013-03-25

The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners.Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period.
Learning Approaches, Demographic Factors to Predict Academic Outcomes

ERIC Educational Resources Information Center

Nguyen, Tuan Minh

2016-01-01

Purpose: The purpose of this paper is to predict academic outcome in math and math-related subjects using learning approaches and demographic factors. Design/Methodology/Approach: ASSIST was used as the instrumentation to measure learning approaches. The study was conducted in the International University of Vietnam with 616 participants. An…
Portable document format file showing the surface models of cadaver whole body.

PubMed

Shin, Dong Sun; Chung, Min Suk; Park, Jin Seo; Park, Hyung Seon; Lee, Sangho; Moon, Young Lae; Jang, Hae Gwon

2012-08-01

In the Visible Korean project, 642 three-dimensional (3D) surface models have been built from the sectioned images of a male cadaver. It was recently discovered that popular PDF file enables users to approach the numerous surface models conveniently on Adobe Reader. Purpose of this study was to present a PDF file including systematized surface models of human body as the beneficial contents. To achieve the purpose, fitting software packages were employed in accordance with the procedures. Two-dimensional (2D) surface models including the original sectioned images were embedded into the 3D surface models. The surface models were categorized into systems and then groups. The adjusted surface models were inserted to a PDF file, where relevant multimedia data were added. The finalized PDF file containing comprehensive data of a whole body could be explored in varying manners. The PDF file, downloadable freely from the homepage (http://anatomy.co.kr), is expected to be used as a satisfactory self-learning tool of anatomy. Raw data of the surface models can be extracted from the PDF file and employed for various simulations for clinical practice. The technique to organize the surface models will be applied to manufacture of other PDF files containing various multimedia contents.
A Five-Stage Prediction-Observation-Explanation Inquiry-Based Learning Model to Improve Students' Learning Performance in Science Courses

ERIC Educational Resources Information Center

Hsiao, Hsien-Sheng; Chen, Jyun-Chen; Hong, Jon-Chao; Chen, Po-Hsi; Lu, Chow-Chin; Chen, Sherry Y.

2017-01-01

A five-stage prediction-observation-explanation inquiry-based learning (FPOEIL) model was developed to improve students' scientific learning performance. In order to intensify the science learning effect, the repertory grid technology-assisted learning (RGTL) approach and the collaborative learning (CL) approach were utilized. A quasi-experimental…
Transformative Education through International Service-Learning: Realising an Ethical Ecology of Learning. Routledge Research in International and Comparative Education

ERIC Educational Resources Information Center

Bamber, Philip M.

2016-01-01

Transformative learning is a compelling approach to learning that is becoming increasingly popular in a diverse range of educational settings and encounters. This book reconceptualises transformative learning through an investigation of the learning process and outcomes of International Service-Learning (ISL), a pedagogical approach that blends…
Students' Feedback of mDPBL Approach and the Learning Impact towards Computer Networks Teaching and Learning

ERIC Educational Resources Information Center

Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

2018-01-01

This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…
Demonstrating and Evaluating an Action Learning Approach to Building Project Management Competence

NASA Technical Reports Server (NTRS)

Kotnour, Tim; Starr, Stan; Steinrock, T. (Technical Monitor)

2001-01-01

This paper contributes a description of an action-learning approach to building project management competence. This approach was designed, implemented, and evaluated for use with the Dynacs Engineering Development Contract at the Kennedy Space Center. The aim of the approach was to improve three levels of competence within the organization: individual project management skills, project team performance. and organizational capabilities such as the project management process and tools. The overall steps to the approach, evaluation results, and lessons learned are presented. Managers can use this paper to design a specific action-learning approach for their organization.
Creativity of Biology Students in Online Learning: Case Study of Universitas Terbuka, Indonesia

NASA Astrophysics Data System (ADS)

Diki, Diki

This is a study about the effect of students' attitudes of creativity toward their learning achievement and persistence in an online learning program. The study also investigated if there was an effect of indirect effect of attitudes of creativity toward learning achievement and persistence through learning strategies. There are three learning strategies, which are deep-learning, strategic-learning, and surface-learning. The participants were students of the department of biology and the department of biology teacher training in Universitas Terbuka (UT -- Indonesia Open University), a distance learning university in Indonesia. The researcher sent the questionnaire through email to students who lived throughout Indonesia. There were 102 students participated in the survey. The instruments were rCAB test for value and attitudes toward creativity (Runco, 2012) and approaches and Study Skills Inventory for Students (ASSIST) test (Speth, 2013). There were four research questions (RQ) in this study. The first was if there was a relationship between attitudes of creativity and persistence. The researcher used independent samples t test technique for RQ 1. The second was if there is a relationship between attitudes of creativity and learning outcome. The researcher used multiple regressions for RQ2. The third was if there was an indirect relationship between attitudes of creativity and persistence through learning strategy. The fourth question was if there is an indirect relationship between attitudes of creativity and learning outcome through learning strategy. The researcher used multiple regression for RQ3 and path analysis for RQ 4. Controlling variables were age, income, departments, gender, high school GPA, and daily online activities. The result showed that fun, and being unconventional negatively predicted learning outcomes while high school GPA positively predicted learning outcome. Age and high school GPA negatively predicted persistence while being unconventional positively predicted persistence. Two variables of deep-learning strategy predicted learning outcome. There were indirect relationships between attitudes of creativity and learning outcomes through deep-learning strategy.
The early benefits of a problem-based approach to teaching social inclusion using an online virtual town.

PubMed

Beadle, Mary; Santy, Julie

2008-05-01

This article describes the delivery of a core pre-registration nursing and midwifery module centred on social inclusion. The module was previously delivered using a classroom-based problem-based learning approach. Difficulties with this approach led to changes to the module and its delivery. Logistic issues encouraged the module team to implement a blended learning approach using a virtual town to facilitate online learning and discussion activities. The paper describes and discusses the use of online learning technology to support student nurses and midwives. It highlights the benefits of this approach and outlines some of the experiences of the students including their evaluation of the virtual town. There is also an examination of some of the practical and theoretical issues related to both problem-based learning, online working and using a virtual town to support learning. This article outlines the approach taken and its implications.
Precision Parameter Estimation and Machine Learning

NASA Astrophysics Data System (ADS)

Wandelt, Benjamin D.

2008-12-01

I discuss the strategy of ``Acceleration by Parallel Precomputation and Learning'' (AP-PLe) that can vastly accelerate parameter estimation in high-dimensional parameter spaces and costly likelihood functions, using trivially parallel computing to speed up sequential exploration of parameter space. This strategy combines the power of distributed computing with machine learning and Markov-Chain Monte Carlo techniques efficiently to explore a likelihood function, posterior distribution or χ2-surface. This strategy is particularly successful in cases where computing the likelihood is costly and the number of parameters is moderate or large. We apply this technique to two central problems in cosmology: the solution of the cosmological parameter estimation problem with sufficient accuracy for the Planck data using PICo; and the detailed calculation of cosmological helium and hydrogen recombination with RICO. Since the APPLe approach is designed to be able to use massively parallel resources to speed up problems that are inherently serial, we can bring the power of distributed computing to bear on parameter estimation problems. We have demonstrated this with the CosmologyatHome project.
Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less
Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less
Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

NASA Astrophysics Data System (ADS)

Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

2017-11-01

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.
Understanding 3D human torso shape via manifold clustering

NASA Astrophysics Data System (ADS)

Li, Sheng; Li, Peng; Fu, Yun

2013-05-01

Discovering the variations in human torso shape plays a key role in many design-oriented applications, such as suit designing. With recent advances in 3D surface imaging technologies, people can obtain 3D human torso data that provide more information than traditional measurements. However, how to find different human shapes from 3D torso data is still an open problem. In this paper, we propose to use spectral clustering approach on torso manifold to address this problem. We first represent high-dimensional torso data in a low-dimensional space using manifold learning algorithm. Then the spectral clustering method is performed to get several disjoint clusters. Experimental results show that the clusters discovered by our approach can describe the discrepancies in both genders and human shapes, and our approach achieves better performance than the compared clustering method.
Topography and surface free energy of DPPC layers deposited on a glass, mica, or PMMA support.

PubMed

Jurak, Malgorzata; Chibowski, Emil

2006-08-15

An investigation of energetic properties of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) layers deposited on glass, mica, and PMMA (poly(methyl methacrylate)) surfaces was carried out by means of contact angles measurements (advancing and receding) for three probe liquids (diiodomethane, water, and formamide). DPPC was deposited on the surfaces from water (on glass and mica) or methanol (on PMMA) solutions. The topography of the tested surfaces was determined with a help of scanning electron microscopy (SEM) and atomic force microscopy (AFM). Using the measured contact angles, the total apparent surface free energy and its components of the studied layers were determined from van Oss et al.'s (Lifshitz-van der Waals and acid-base components, LWAB) and contact angle hysteresis (CAH) approaches. It allowed us to learn about changes in the surface free energy of the layers (hydrophobicity/hydrophilicity) depending on their number and kind of support. It was found that the changes in the energy greatly depended on the surface properties of the substrate as well as the statistical number of monolayers of DPPC. However, principal changes took place for first three monolayers.
Undergraduate Earth System Science Education: Project-Based Learning, Land-Atmosphere Interaction, and a Newly Established Student Weather Station

NASA Astrophysics Data System (ADS)

Baker, D.

2004-12-01

Undergraduate students conducted a semester-long research project as part of a special topics course that launched the Austin College Weather Station in spring 2001. The weather station is located on restored prairie roughly 100 km north of Dallas, Texas. In addition to standard meteorological observations, the Austin College Weather Station measures surface quantities such as soil moisture, soil temperature, solar radiation, infrared radiation, and soil heat flux. These additional quantities are used to calculate the surface energy balance using the Bowen ratio method. Thus, the Austin College Weather Station provides valuable information on land-atmosphere interaction in a prairie environment. This project provided a remarkable learning experience for the students. Each student supervised two instruments on the weather station. Students skillfully learned instrumentation details and the physical phenomena measured by the instruments. Team meetings were held each week to discuss issues such as station location, power requirements, telecommunication options, and data acquisition. Students made important decisions during the meetings. They would then work collaboratively on specific tasks that needed to be accomplished before the next meeting. Students also assessed the validity of their measurements after the weather station came on-line. With this approach, students became the experts. They utilized the scientific method to think critically and to solve problems. For at least a semester, students became Earth system scientists.
Web-Based Teaching and Learning Approach (WBTLA) Usability in Institutions of Higher Learning in Malaysia

ERIC Educational Resources Information Center

Nordin, Abu Bakar; Alias, Norlidah

2013-01-01

Today teachers in schools and lecturers in institutions of higher learning are endowed with a wide range of new teaching experiences through web-based teaching and learning approaches (WBTLA), which was not possible before through the traditional classroom approach. With the use of WBTLA emerged problems related to usability in technical,…
A 5E Learning Cycle Approach-Based, Multimedia-Supplemented Instructional Unit for Structured Query Language

ERIC Educational Resources Information Center

Piyayodilokchai, Hongsiri; Panjaburee, Patcharin; Laosinchai, Parames; Ketpichainarong, Watcharee; Ruenwongsa, Pintip

2013-01-01

With the benefit of multimedia and the learning cycle approach in promoting effective active learning, this paper proposed a learning cycle approach-based, multimedia-supplemented instructional unit for Structured Query Language (SQL) for second-year undergraduate students with the aim of enhancing their basic knowledge of SQL and ability to apply…
A Practice-Based Approach to Student Reflection in the Workplace during a Work-Integrated Learning Placement

ERIC Educational Resources Information Center

Sykes, Christopher; Dean, Bonnie Amelia

2013-01-01

In the Work-Integrated Learning (WIL) curriculum, reflection on workplace activities is widely used to support student learning. Recent critiques have demonstrated the limitations of current approaches to support students' reflective learning of workplace practices. By employing a practice-based approach, we seek to refocus WIL reflection on…
A Project-Based Learning Approach to Teaching Physics for Pre-Service Elementary School Teacher Education Students

ERIC Educational Resources Information Center

Goldstein, Olzan

2016-01-01

This paper describes the impact of the project-based learning (PBL) approach on learning and teaching physics from the perspective of pre-service elementary school teacher education students and an instructor. This approach promoted meaningful learning (mainly in the scope of projects), higher motivation, and active involvement of students in…

What's Wrong with Learning for the Exam? An Assessment-Based Approach for Student Engagement

ERIC Educational Resources Information Center

Ito, Hiroshi

2014-01-01

It is now widely recognized that assessment and the feedback play key roles in the learning process. However, assessment-based learning approaches are not yet commonly practiced in Japan. This paper provides an example of an assessment-based approach to teaching and learning employed for a course entitled "English as an International…
Creation of Exercises for Team-Based Learning in Business

ERIC Educational Resources Information Center

Timmerman, John E.; Morris, R. Franklin, Jr.

2015-01-01

Team-based learning (TBL) is an approach that builds on both the case method and problem-based learning and has been widely adopted in the sciences and healthcare disciplines. In recent years business disciplines have also discovered the value of this approach. One of the key characteristics of the team-based learning approach consists of…
Surface, Deep, and Transfer? Considering the Role of Content Literacy Instructional Strategies

ERIC Educational Resources Information Center

Frey, Nancy; Fisher, Douglas; Hattie, John

2017-01-01

This article provides an organizational review of content literacy instructional strategies to forward a claim that some strategies work better for surface learning, whereas others are more effective for deep learning and still others for transfer learning. The authors argue that the failure to adopt content literacy strategies by disciplinary…
Getting Inside Knowledge: The Application of Entwistle's Model of Surface/Deep Processing in Producing Open Learning Materials.

ERIC Educational Resources Information Center

Evans, Barbara; Honour, Leslie

1997-01-01

Reports on a study that required student teachers training in business education to produce open learning materials on intercultural communication. Analysis of stages and responses to this assignment revealed a distinction between "deep" and "surface" learning. Includes charts delineating the characteristics of these two types…
The Development of Approaches to Learning and Perceptions of the Teaching-Learning Environment during Bachelor Level Studies and Their Relation to Study Success

ERIC Educational Resources Information Center

Asikainen, Henna; Parpala, Anna; Lindblom-Ylänne, Sari; Vanthournout, Gert; Coertjens, Liesje

2014-01-01

The aim of the present study is to explore changes both in approaches to learning as well as in students' experiences of the teaching-learning environment and how these changes are related to each other during their Bachelor studies by using a longitudinal data set. The aim is further to explore how students' approaches to learning and their…
Investigating the Efficiency of Scenario Based Learning and Reflective Learning Approaches in Teacher Education

ERIC Educational Resources Information Center

Hursen, Cigdem; Fasli, Funda Gezer

2017-01-01

The main purpose of this research is to investigate the efficiency of scenario based learning and reflective learning approaches in teacher education. The impact of applications of scenario based learning and reflective learning on prospective teachers' academic achievement and views regarding application and professional self-competence…
Gaussian Processes for Data-Efficient Learning in Robotics and Control.

PubMed

Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward

2015-02-01

Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.
Multi-task feature learning by using trace norm regularization

NASA Astrophysics Data System (ADS)

Jiangmei, Zhang; Binfeng, Yu; Haibo, Ji; Wang, Kunpeng

2017-11-01

Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.
Presenting the Students’ Academic Achievement Causal Model based on Goal Orientation

PubMed Central

NASIRI, EBRAHIM; POUR-SAFAR, ALI; TAHERI, MAHDOKHT; SEDIGHI PASHAKY, ABDULLAH; ASADI LOUYEH, ATAOLLAH

2017-01-01

Introduction: Several factors play a role in academic achievement, individual's excellence and capability to do actions and tasks that the learner is in charge of in learning areas. The main goal of this study was to present academic achievement causal model based on the dimensions of goal orientation and learning approaches among the students of Medical Science and Dentistry courses in Guilan University of Medical Sciences in 2013. Methods: This study is based on a cross-sectional model. The participants included 175 first and second students of the Medical and Dentistry schools in Guilan University of Medical Sciences selected by random cluster sampling [121 persons (69%) Medical Basic Science students and 54 (30.9%) Dentistry students]. The measurement tool included the Goal Orientation Scale of Bouffard and Study Process Questionnaire of Biggs) and the students’ Grade Point Average. The study data were analyzed using Pearson correlation coefficient and structural equations modeling. SPSS 14 and Amos were used to analyze the data. Results: The results indicated a significant relationship between goal orientation and learning strategies (P<0.05). In addition, the results revealed that a significant relationship exists between learning strategies[Deep Learning (r=0.37, P<0.05), Surface Learning (r=-0.21,P<0.05)], and academic achievement.The suggested model of research is fitted to the data of the research. Conclusion: Results showed that the students' academic achievement model fits with experimental data, so it can be used in learning principles which lead to students’ achievement in learning. PMID:28979914
Learning Behavior and Achievement Analysis of a Digital Game-Based Learning Approach Integrating Mastery Learning Theory and Different Feedback Models

ERIC Educational Resources Information Center

Yang, Kai-Hsiang

2017-01-01

It is widely accepted that the digital game-based learning approach has the advantage of stimulating students' learning motivation, but simply using digital games in the classroom does not guarantee satisfactory learning achievement, especially in the case of the absence of a teacher. Integrating appropriate learning strategies into a game can…
From Learning Cultures to Educational Cultures: Values and Judgements in Educational Research and Educational Improvement

ERIC Educational Resources Information Center

Biesta, Gert

2011-01-01

This article outlines a new approach to the study of learning and the improvement of education. The approach consists of two elements: a theory of learning cultures and a cultural theory of learning. Learning cultures are different from learning contexts or learning environments in that they are to be understood as the social practices through…
From Continuous Improvement to Organisational Learning: Developmental Theory.

ERIC Educational Resources Information Center

Murray, Peter; Chapman, Ross

2003-01-01

Explores continuous improvement methods, which underlie total quality management, finding barriers to implementation in practice that are related to a one-dimensional approach. Suggests a multiple, unbounded learning cycle, a holistic approach that includes adaptive learning, learning styles, generative learning, and capability development.…
Revising a Design Course from a Lecture Approach to a Project-Based Learning Approach

ERIC Educational Resources Information Center

Kunberger, Tanya

2013-01-01

In order to develop the evaluative skills necessary for successful performance of design, a senior, Geotechnical Engineering course was revised to immerse students in the complexity of the design process utilising a project-based learning (PBL) approach to instruction. The student-centred approach stresses self-directed group learning, which…
Approaches to Studying and Students' Use of a Computer Supported Learning Environment

ERIC Educational Resources Information Center

Foster, Jonathan; Lin, Angela

2007-01-01

Although studies of students' study approaches in face to face learning environments are commonplace, studies investigating the role of students' study approaches in online learning environments is currently a less explored area. This paper presents the findings of a survey aimed at investigating the relationship between students' approaches to…
Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

NASA Astrophysics Data System (ADS)

Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

2017-09-01

The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.
The use of deep and surface learning strategies among students learning English as a foreign language in an Internet environment.

PubMed

Aharony, Noa

2006-12-01

The learning context is learning English in an Internet environment. The examination of this learning process was based on the Biggs and Moore's teaching-learning model (Biggs & Moore, 1993). The research aims to explore the use of the deep and surface strategies in an Internet environment among EFL students who come from different socio-economic backgrounds. The results of the research may add an additional level to the understanding of students' functioning in the Internet environment. One hundred fourty-eight Israeli junior and high school students participated in this research. The methodology was based on special computer software: Screen Cam, which recorded the students' learning process. In addition, expert judges completed a questionnaire which examined and categorized the students' learning strategies. The research findings show a clear preference of participants from all socio-economic backgrounds towards the surface learning strategy. The findings also showed that students from the medium to high socio-economic background used both learning strategies more frequently than low socio-economic students. The results reflect the habits that students acquire during their adjustment process throughout their education careers. A brief encounter with the Internet learning environment apparently cannot change norms or habits, which were acquired in the non-Internet learning environment.
Effects of web-based electrocardiography simulation on strategies and learning styles.

PubMed

Granero-Molina, José; Fernández-Sola, Cayetano; López-Domene, Esperanza; Hernández-Padilla, José Manuel; Preto, Leonel São Romão; Castro-Sánchez, Adelaida María

2015-08-01

To identify the association between the use of web simulation electrocardiography and the learning approaches, strategies and styles of nursing degree students. A descriptive and correlational design with a one-group pretest-posttest measurement was used. The study sample included 246 students in a Basic and Advanced Cardiac Life Support nursing class of nursing degree. No significant differences between genders were found in any dimension of learning styles and approaches to learning. After the introduction of web simulation electrocardiography, significant differences were found in some item scores of learning styles: theorist (p < 0.040), pragmatic (p < 0.010) and approaches to learning. The use of a web electrocardiogram (ECG) simulation is associated with the development of active and reflexive learning styles, improving motivation and a deep approach in nursing students.
Component-Based Approach in Learning Management System Development

ERIC Educational Resources Information Center

Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

2013-01-01

The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…
Testing Two Path Models to Explore Relationships between Students' Experiences of the Teaching-Learning Environment, Approaches to Learning and Academic Achievement

ERIC Educational Resources Information Center

Karagiannopoulou, Evangelia; Milienos, Fotios S.

2015-01-01

The study explores the relationships between students' experiences of the teaching-learning environment and their approaches to learning, and the effects of these variables on academic achievement. Two three-stage models were tested with structural equation modelling techniques. The "Approaches and Study Skills Inventory for Students"…
The Effects of a Problem Based Learning Approach on Students' Attitude Levels: A Meta-Analysis

ERIC Educational Resources Information Center

Batdi, Veli

2014-01-01

This research aimed to examine the effect of a problem-based learning approach in comparison to traditional learning approaches. In this context, the question "What is the effect size of problem-based learning on students' attitudes?" was tried to be answered. Among 190 studies made in national and international field between the…

The Assessment of Taiwanese College Students' Conceptions of and Approaches to Learning Computer Science and Their Relationships

ERIC Educational Resources Information Center

Liang, Jyh-Chong; Su, Yi-Ching; Tsai, Chin-Chung

2015-01-01

The aim of this study was to explore Taiwanese college students' conceptions of and approaches to learning computer science and then explore the relationships between the two. Two surveys, Conceptions of Learning Computer Science (COLCS) and Approaches to Learning Computer Science (ALCS), were administered to 421 college students majoring in…
Meta-Analysis of Jelajah Alam Sekitar (JAS) Approach Implementation in Learning Process

ERIC Educational Resources Information Center

Ngabekti, S.; Ridlo, S.; Peniati, E.; Martanto, R.

2017-01-01

The results of tracer studies on the approach of Jelajah Alam Sekitar (JAS) or environment exploring learning has been detected is used in eight provinces in Indonesia and studied in the learning begin primary school to college. Then, how the effectiveness of the implementation of the JAS approach in improving the learning process. This study uses…
A Project-Based Digital Storytelling Approach for Improving Students' Learning Motivation, Problem-Solving Competence and Learning Achievement

ERIC Educational Resources Information Center

Hung, Chun-Ming; Hwang, Gwo-Jen; Huang, Iwen

2012-01-01

Although project-based learning is a well-known and widely used instructional strategy, it remains a challenging issue to effectively apply this approach to practical settings for improving the learning performance of students. In this study, a project-based digital storytelling approach is proposed to cope with this problem. With a…
Undergraduate Students' Conceptions of and Approaches to Learning in Biology: A Study of Their Structural Models and Gender Differences

ERIC Educational Resources Information Center

Chiou, Guo-Li; Liang, Jyh-Chong; Tsai, Chin-Chung

2012-01-01

This study reports the findings of a study which examined the relationship between conceptions of learning and approaches to learning in biology. This study, which used structural equation modelling, also sorted to identify gender differences in the relationship. Two questionnaires, the Conceptions of Learning Biology (COLB) and the Approaches to…
The Role of Social Identification as University Student in Learning: Relationships between Students' Social Identity, Approaches to Learning, and Academic Achievement

ERIC Educational Resources Information Center

Bliuc, Ana-Maria; Ellis, Robert A.; Goodyear, Peter; Hendres, Daniela Muntele

2011-01-01

This article describes research exploring the relationship between students' self-perceptions in the context of university learning (i.e. student social identity), their approaches to learning, and academic achievement. The exploration of these inter-related aspects requires a mix of theoretical approaches, that is, in this research both social…
The scientific learning approach using multimedia-based maze game to improve learning outcomes

NASA Astrophysics Data System (ADS)

Setiawan, Wawan; Hafitriani, Sarah; Prabawa, Harsa Wara

2016-02-01

The objective of curriculum 2013 is to improve the quality of education in Indonesia, which leads to improving the quality of learning. The scientific approach and supported empowerment media is one approach as massaged of curriculum 2013. This research aims to design a labyrinth game based multimedia and apply in the scientific learning approach. This study was conducted in one of the Vocational School in Subjects of Computer Network on 2 (two) classes of experimental and control. The method used Mix Method Research (MMR) which combines qualitative in multimedia design, and quantitative in the study of learning impact. The results of a survey showed that the general of vocational students like of network topology material (68%), like multimedia (74%), and in particular, like interactive multimedia games and flash (84%). Multimediabased maze game developed good eligibility based on media and material aspects of each value 840% and 82%. Student learning outcomes as a result of using a scientific approach to learning with a multimediabased labyrinth game increase with an average of gain index about (58%) and higher than conventional multimedia with index average gain of 0.41 (41%). Based on these results the scientific approach to learning by using multimediabased labyrinth game can improve the quality of learning and increase understanding of students. Multimedia of learning based labyrinth game, which developed, got a positive response from the students with a good qualification level (75%).
Prediction of high-dimensional states subject to respiratory motion: a manifold learning approach

NASA Astrophysics Data System (ADS)

Liu, Wenyang; Sawant, Amit; Ruan, Dan

2016-07-01

The development of high-dimensional imaging systems in image-guided radiotherapy provides important pathways to the ultimate goal of real-time full volumetric motion monitoring. Effective motion management during radiation treatment usually requires prediction to account for system latency and extra signal/image processing time. It is challenging to predict high-dimensional respiratory motion due to the complexity of the motion pattern combined with the curse of dimensionality. Linear dimension reduction methods such as PCA have been used to construct a linear subspace from the high-dimensional data, followed by efficient predictions on the lower-dimensional subspace. In this study, we extend such rationale to a more general manifold and propose a framework for high-dimensional motion prediction with manifold learning, which allows one to learn more descriptive features compared to linear methods with comparable dimensions. Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where accurate and efficient prediction can be performed. A fixed-point iterative pre-image estimation method is used to recover the predicted value in the original state space. We evaluated and compared the proposed method with a PCA-based approach on level-set surfaces reconstructed from point clouds captured by a 3D photogrammetry system. The prediction accuracy was evaluated in terms of root-mean-squared-error. Our proposed method achieved consistent higher prediction accuracy (sub-millimeter) for both 200 ms and 600 ms lookahead lengths compared to the PCA-based approach, and the performance gain was statistically significant.
A machine-learning graph-based approach for 3D segmentation of Bruch's membrane opening from glaucomatous SD-OCT volumes.

PubMed

Miri, Mohammad Saleh; Abràmoff, Michael D; Kwon, Young H; Sonka, Milan; Garvin, Mona K

2017-07-01

Bruch's membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in the retina and is superior to other conventional structural parameters for diagnosing glaucoma. Measuring this structural parameter requires identification of BMO locations within spectral domain-optical coherence tomography (SD-OCT) volumes. While most automated approaches for segmentation of the BMO either segment the 2D projection of BMO points or identify BMO points in individual B-scans, in this work, we propose a machine-learning graph-based approach for true 3D segmentation of BMO from glaucomatous SD-OCT volumes. The problem is formulated as an optimization problem for finding a 3D path within the SD-OCT volume. In particular, the SD-OCT volumes are transferred to the radial domain where the closed loop BMO points in the original volume form a path within the radial volume. The estimated location of BMO points in 3D are identified by finding the projected location of BMO points using a graph-theoretic approach and mapping the projected locations onto the Bruch's membrane (BM) surface. Dynamic programming is employed in order to find the 3D BMO locations as the minimum-cost path within the volume. In order to compute the cost function needed for finding the minimum-cost path, a random forest classifier is utilized to learn a BMO model, obtained by extracting intensity features from the volumes in the training set, and computing the required 3D cost function. The proposed method is tested on 44 glaucoma patients and evaluated using manual delineations. Results show that the proposed method successfully identifies the 3D BMO locations and has significantly smaller errors compared to the existing 3D BMO identification approaches. Published by Elsevier B.V.
Design of Learning Objects for Concept Learning: Effects of Multimedia Learning Principles and an Instructional Approach

ERIC Educational Resources Information Center

Chiu, Thomas K. F.; Churchill, Daniel

2016-01-01

Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…
Can Learning Motivation Predict Learning Achievement? A Case Study of a Mobile Game-Based English Learning Approach

ERIC Educational Resources Information Center

Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun

2017-01-01

This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…
Learning Process Questionnaire Manual. Student Approaches to Learning and Studying.

ERIC Educational Resources Information Center

Biggs, John B.

This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…
The attractions of medicine: the generic motivations of medical school applicants in relation to demography, personality and achievement.

PubMed

McManus, I C; Livingston, G; Katona, Cornelius

2006-02-21

The motivational and other factors used by medical students in making their career choices for specific medical specialities have been looked at in a number of studies in the literature. There are however few studies that assess the generic factors which make medicine itself of interest to medical students and to potential medical students. This study describes a novel questionnaire that assesses the interests and attractions of different aspects of medical practice in a varied range of medical scenarios, and relates them to demographic, academic, personality and learning style measures in a large group of individuals considering applying to medical school. A questionnaire study was conducted among those attending Medlink, a two-day conference for individuals considering applying to medical school for a career in medicine. The main outcome measure was the Medical Situations Questionnaire, in which individuals ranked the attraction of three different aspects of medical practise in each of nine detailed, realistic medical scenarios in a wide range of medical specialities. As well as requiring clear choices, the questionnaire was also designed so that all of the possible answers were attractive and positive, thereby helping to eliminate social demand characteristics. Factor analysis of the responses found four generic motivational dimensions, which we labelled Indispensability, Helping People, Respect and Science. Background factors assessed included sex, ethnicity, class, medical parents, GCSE academic achievement, the 'Big Five' personality factors, empathy, learning styles, and a social desirability scale. 2867 individuals, broadly representative of applicants to medical schools, completed the questionnaire. The four generic motivational factors correlated with a range of background factors. These correlations were explored by multiple regression, and by path analysis, using LISREL to assess direct and indirect effects upon the factors. Helping People was particularly related to agreeableness; Indispensability to a strategic approach to learning; Respect to a surface approach to learning; and Science to openness to experience. Sex had many indirect influences upon generic motivations. Ethnic origin also had indirect influences via neuroticism and surface learning, and social class only had indirect influences via lower academic achievement. Coming from a medical family had no influence upon generic motivations. Generic motivations for medicine as a career can be assessed using the Medical Situations Questionnaire, without undue response bias due to demand characteristics. The validity of the motivational factors is suggested by the meaningful and interpretable correlations with background factors such as demographics, personality, and learning styles. Further development of the questionnaire is needed if it is to be used at an individual level, either for counselling or for student selection.
Learning Styles in the e-Learning Environment: The Approaches and Research on Longitudinal Changes

ERIC Educational Resources Information Center

Doulik, Pavel; Skoda, Jiri; Simonova, Ivana

2017-01-01

The paper focuses on the field of learning styles in e-learning. The study is structured in two main parts: (1) a brief overview of traditional approaches to learning styles is presented and their role in the process of instruction is set; this part results in the reflection of current state, when learning styles are considered within e-learning;…
Quantum-Enhanced Machine Learning

NASA Astrophysics Data System (ADS)

Dunjko, Vedran; Taylor, Jacob M.; Briegel, Hans J.

2016-09-01

The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention. Within our approach, we tackle the problem of quantum enhancements in reinforcement learning as well, and propose a systematic scheme for providing improvements. As an example, we show that quadratic improvements in learning efficiency, and exponential improvements in performance over limited time periods, can be obtained for a broad class of learning problems.
Approaches and Study Skills Inventory for Students (ASSIST) in an Introductory Course in Chemistry

ERIC Educational Resources Information Center

Brown, Stephen; White, Sue; Wakeling, Lara; Naiker, Mani

2015-01-01

Approaches to study and learning may enhance or undermine educational outcomes, and thus it is important for educators to be knowledgeable about their students' approaches to study and learning. The Approaches and Study Skills Inventory for Students (ASSIST)--a 52 item inventory which identifies three learning styles (Deep, Strategic, and…
Cyber Asynchronous versus Blended Cyber Approach in Distance English Learning

ERIC Educational Resources Information Center

Ge, Zi-Gang

2012-01-01

This study aims to compare the single cyber asynchronous learning approach with the blended cyber learning approach in distance English education. Two classes of 70 students participated in this study, which lasted one semester of about four months, with one class using the blended approach for their English study and the other only using the…
Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning

ERIC Educational Resources Information Center

Akhmetova, Daniya Z.

2014-01-01

Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…
Investigating the Relationship among Extracurricular Activities, Learning Approach and Academic Outcomes: A Case Study

ERIC Educational Resources Information Center

Chan, Yiu-Kong

2016-01-01

Learning effectiveness requires an understanding of the relationship among extracurricular activities, learning approach and academic performance and, it is argued, this helps educators develop techniques designed to enrich learning effectiveness. Biggs' Presage-Process-Product model on student learning has identified the relationship among…
Learning from and with Museum Objects: Design Perspectives, Environment, and Emerging Learning Systems

ERIC Educational Resources Information Center

Vartiainen, Henriikka; Enkenberg, Jorma

2013-01-01

Sociocultural approaches emphasize the systemic, context-bound nature of learning, which is mediated by other people, physical and conceptual artifacts, and tools. However, current educational systems tend not to approach learning from the systemic perspective, and mostly situate learning within classroom environments. This design-based research…
"Learning to Like Learning": An Appreciative Inquiry into Emotions in Education

ERIC Educational Resources Information Center

Naude, L.; van den Bergh, T. J.; Kruger, I. S.

2014-01-01

Various learning philosophies, such as humanistic, constructivist, and socio-cultural approaches, have accentuated the importance of emotion in learning. In this article, we reviewed these approaches and explored the affective dimensions of learning. We conducted focus group and individual interviews with a group of female students in the…

Student-Centred Learning Environments: An Investigation into Student Teachers' Instructional Preferences and Approaches to Learning

ERIC Educational Resources Information Center

Baeten, Marlies; Dochy, Filip; Struyven, Katrien; Parmentier, Emmeline; Vanderbruggen, Anne

2016-01-01

The use of student-centred learning environments in education has increased. This study investigated student teachers' instructional preferences for these learning environments and how these preferences are related to their approaches to learning. Participants were professional Bachelor students in teacher education. Instructional preferences and…
The brain-tumor related protein podoplanin regulates synaptic plasticity and hippocampus-dependent learning and memory.

PubMed

Cicvaric, Ana; Yang, Jiaye; Krieger, Sigurd; Khan, Deeba; Kim, Eun-Jung; Dominguez-Rodriguez, Manuel; Cabatic, Maureen; Molz, Barbara; Acevedo Aguilar, Juan Pablo; Milicevic, Radoslav; Smani, Tarik; Breuss, Johannes M; Kerjaschki, Dontscho; Pollak, Daniela D; Uhrin, Pavel; Monje, Francisco J

2016-12-01

Podoplanin is a cell-surface glycoprotein constitutively expressed in the brain and implicated in human brain tumorigenesis. The intrinsic function of podoplanin in brain neurons remains however uncharacterized. Using an established podoplanin-knockout mouse model and electrophysiological, biochemical, and behavioral approaches, we investigated the brain neuronal role of podoplanin. Ex-vivo electrophysiology showed that podoplanin deletion impairs dentate gyrus synaptic strengthening. In vivo, podoplanin deletion selectively impaired hippocampus-dependent spatial learning and memory without affecting amygdala-dependent cued fear conditioning. In vitro, neuronal overexpression of podoplanin promoted synaptic activity and neuritic outgrowth whereas podoplanin-deficient neurons exhibited stunted outgrowth and lower levels of p-Ezrin, TrkA, and CREB in response to nerve growth factor (NGF). Surface Plasmon Resonance data further indicated a physical interaction between podoplanin and NGF. This work proposes podoplanin as a novel component of the neuronal machinery underlying neuritogenesis, synaptic plasticity, and hippocampus-dependent memory functions. The existence of a relevant cross-talk between podoplanin and the NGF/TrkA signaling pathway is also for the first time proposed here, thus providing a novel molecular complex as a target for future multidisciplinary studies of the brain function in the physiology and the pathology. Key messages Podoplanin, a protein linked to the promotion of human brain tumors, is required in vivo for proper hippocampus-dependent learning and memory functions. Deletion of podoplanin selectively impairs activity-dependent synaptic strengthening at the neurogenic dentate-gyrus and hampers neuritogenesis and phospho Ezrin, TrkA and CREB protein levels upon NGF stimulation. Surface plasmon resonance data indicates a physical interaction between podoplanin and NGF. On these grounds, a relevant cross-talk between podoplanin and NGF as well as a role for podoplanin in plasticity-related brain neuronal functions is here proposed.
Arts-Based Learning: A New Approach to Nursing Education Using Andragogy.

PubMed

Nguyen, Megan; Miranda, Joyal; Lapum, Jennifer; Donald, Faith

2016-07-01

Learner-oriented strategies focusing on learning processes are needed to prepare nursing students for complex practice situations. An arts-based learning approach uses art to nurture cognitive and emotional learning. Knowles' theory of andragogy aims to develop the skill of learning and can inform the process of implementing arts-based learning. This article explores the use and evaluation of andragogy-informed arts-based learning for teaching nursing theory at the undergraduate level. Arts-based learning activities were implemented and then evaluated by students and instructors using anonymous questionnaires. Most students reported that the activities promoted learning. All instructors indicated an interest in integrating arts-based learning into the curricula. Facilitators and barriers to mainstreaming arts-based learning were highlighted. Findings stimulate implications for prospective research and education. Findings suggest that arts-based learning approaches enhance learning by supporting deep inquiry and different learning styles. Further exploration of andragogy-informed arts-based learning in nursing and other disciplines is warranted. [J Nurs Educ. 2016;55(7):407-410.]. Copyright 2016, SLACK Incorporated.
Student perceptions of independent versus facilitated small group learning approaches to compressed medical anatomy education.

PubMed

Whelan, Alexander; Leddy, John J; Mindra, Sean; Matthew Hughes, J D; El-Bialy, Safaa; Ramnanan, Christopher J

2016-01-01

The purpose of this study was to compare student perceptions regarding two, small group learning approaches to compressed (46.5 prosection-based laboratory hours), integrated anatomy education at the University of Ottawa medical program. In the facilitated active learning (FAL) approach, tutors engage students and are expected to enable and balance both active learning and progression through laboratory objectives. In contrast, the emphasized independent learning (EIL) approach stresses elements from the "flipped classroom" educational model: prelaboratory preparation, independent laboratory learning, and limited tutor involvement. Quantitative (Likert-style questions) and qualitative data (independent thematic analysis of open-ended commentary) from a survey of students who had completed the preclerkship curriculum identified strengths from the EIL (promoting student collaboration and communication) and FAL (successful progression through objectives) approaches. However, EIL led to student frustration related to a lack of direction and impaired completion of objectives, whereas active learning opportunities in FAL were highly variable and dependent on tutor teaching style. A "hidden curriculum" was also identified, where students (particularly EIL and clerkship students) commonly compared their compressed anatomy education or their anatomy learning environment with other approaches. Finally, while both groups highly regarded the efficiency of prosection-based learning and expressed value for cadaveric-based learning, student commentary noted that the lack of grade value dedicated to anatomy assessment limited student accountability. This study revealed critical insights into small group learning in compressed anatomy education, including the need to balance student active learning opportunities with appropriate direction and feedback (including assessment). © 2015 American Association of Anatomists.
Engaging students in a community of learning: Renegotiating the learning environment.

PubMed

Theobald, Karen A; Windsor, Carol A; Forster, Elizabeth M

2018-03-01

Promoting student engagement in a student led environment can be challenging. This article reports on the process of design, implementation and evaluation of a student led learning approach in a small group tutorial environment in a three year Bachelor of Nursing program at an Australian university. The research employed three phases of data collection. The first phase explored student perceptions of learning and engagement in tutorials. The results informed the development of a web based learning resource. Phase two centred on implementation of a community of learning approach where students were supported to lead tutorial learning with peers. The final phase constituted an evaluation of the new approach. Findings suggest that students have the capacity to lead and engage in a community of learning and to assume greater ownership and responsibility where scaffolding is provided. Nonetheless, an ongoing whole of course approach to pedagogical change would better support this form of teaching and learning innovation. Copyright © 2018 Elsevier Ltd. All rights reserved.
Problem Posing with Realistic Mathematics Education Approach in Geometry Learning

NASA Astrophysics Data System (ADS)

Mahendra, R.; Slamet, I.; Budiyono

2017-09-01

One of the difficulties of students in the learning of geometry is on the subject of plane that requires students to understand the abstract matter. The aim of this research is to determine the effect of Problem Posing learning model with Realistic Mathematics Education Approach in geometry learning. This quasi experimental research was conducted in one of the junior high schools in Karanganyar, Indonesia. The sample was taken using stratified cluster random sampling technique. The results of this research indicate that the model of Problem Posing learning with Realistic Mathematics Education Approach can improve students’ conceptual understanding significantly in geometry learning especially on plane topics. It is because students on the application of Problem Posing with Realistic Mathematics Education Approach are become to be active in constructing their knowledge, proposing, and problem solving in realistic, so it easier for students to understand concepts and solve the problems. Therefore, the model of Problem Posing learning with Realistic Mathematics Education Approach is appropriately applied in mathematics learning especially on geometry material. Furthermore, the impact can improve student achievement.
Transformational Education for Psychotherapy and Counselling: A Relational Dynamic Approach

ERIC Educational Resources Information Center

Macaskie, Jane; Meekums, Bonnie; Nolan, Greg

2013-01-01

An evolving relational dynamic approach to psychotherapy and counselling education is described. Key themes integrated within the approach are the learning community and transformational relationships. Learning is a reciprocal change process involving students, teachers, supervisors and therapists in overlapping learning communities. Drawing on…
Metacognition and Reading: Comparing Three Forms of Metacognition in Normally Developing Readers and Readers with Dyslexia.

PubMed

Furnes, Bjarte; Norman, Elisabeth

2015-08-01

Metacognition refers to 'cognition about cognition' and includes metacognitive knowledge, strategies and experiences (Efklides, 2008; Flavell, 1979). Research on reading has shown that better readers demonstrate more metacognitive knowledge than poor readers (Baker & Beall, 2009), and that reading ability improves through strategy instruction (Gersten, Fuchs, Williams, & Baker, 2001). The current study is the first to specifically compare the three forms of metacognition in dyslexic (N = 22) versus normally developing readers (N = 22). Participants read two factual texts, with learning outcome measured by a memory task. Metacognitive knowledge and skills were assessed by self-report. Metacognitive experiences were measured by predictions of performance and judgments of learning. Individuals with dyslexia showed insight into their reading problems, but less general knowledge of how to approach text reading. They more often reported lack of available reading strategies, but groups did not differ in the use of deep and surface strategies. Learning outcome and mean ratings of predictions of performance and judgments of learning were lower in dyslexic readers, but not the accuracy with which metacognitive experiences predicted learning. Overall, the results indicate that dyslexic reading and spelling problems are not generally associated with lower levels of metacognitive knowledge, metacognitive strategies or sensitivity to metacognitive experiences in reading situations. 2015 The Authors. Dyslexia Published by John Wiley & Sons Ltd.
Experiential Approach to Teaching and Learning at Suffolk University's College of Business Administration and Its Relationship to Selected Learning Theories.

ERIC Educational Resources Information Center

Sutherland, Lee William

The use of an experiential approach to teaching and learning by an urban business college is examined. Two texts, one in personnel and the other in small business management, were used as typical models. The relationship of the experiential approach and selected learning theories (Skinner, Gestalt, Rogers, and Knowles) was also analyzed. It is…
The role of context in preschool learning: a multilevel examination of the contribution of context-specific problem behaviors and classroom process quality to low-income children's approaches to learning.

PubMed

Domínguez, Ximena; Vitiello, Virginia E; Fuccillo, Janna M; Greenfield, Daryl B; Bulotsky-Shearer, Rebecca J

2011-04-01

Research suggests that promoting adaptive approaches to learning early in childhood may help close the gap between advantaged and disadvantaged children. Recent research has identified specific child-level and classroom-level variables that are significantly associated with preschoolers' approaches to learning. However, further research is needed to understand the interactive effects of these variables and determine whether classroom-level variables buffer the detrimental effects of child-level risk variables. Using a largely urban and minority sample (N=275) of preschool children, the present study examined the additive and interactive effects of children's context-specific problem behaviors and classroom process quality dimensions on children's approaches to learning. Teachers rated children's problem behavior and approaches to learning and independent assessors conducted classroom observations to assess process quality. Problem behaviors in structured learning situations and in peer and teacher interactions were found to negatively predict variance in approaches to learning. Classroom process quality domains did not independently predict variance in approaches to learning. Nonetheless, classroom process quality played an important role in these associations; high emotional support buffered the detrimental effects of problem behavior, whereas high instructional support exacerbated them. The findings of this study have important implications for classroom practices aimed at helping children who exhibit problem behaviors. Copyright © 2010 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Matching Vocabulary Learning Process with Learning Outcome in L2 Academic Writing: An Exploratory Case Study

ERIC Educational Resources Information Center

Ma, Qing

2013-01-01

This exploratory case study of two undergraduates links vocabulary learning approaches with lexical quality measured in academic writing. Employing an array of qualitative data, it is shown that in a "semi-language-rich" learning context, Chinese learners may dispense with rote learning and engage in a more natural learning approach in which…
Improving Learning of Programming through E-Learning by Using Asynchronous Virtual Pair Programming

ERIC Educational Resources Information Center

Zin, Abdullah Mohd; Idris, Sufian; Subramaniam, Nantha Kumar

2006-01-01

The problem of learning programming subjects, especially through distance learning and E-Learning, has been widely reported in literatures. Many attempts have been made to solve these problems. This has led to many new approaches in the techniques of learning of programming. One of the approaches that have been proposed is the use of virtual pair…
An Evaluation of a Counseling-Community Learning Approach to Foreign Language Teaching or Counseling-Learning Theory Applied to Foreign Language Learning. Final Report.

ERIC Educational Resources Information Center

Gallagher, Rosina Mena

This study evaluates the counseling-learning approach to foreign language instruction as compared with traditional methods in terms of language achievement and change in personal orientation and in attitude toward learning. Twelve students volunteered to learn Spanish or German under simultaneous exposure to both languages using the…
Students' Conception of Learning Environment and Their Approach to Learning and Its Implication on Quality Education

ERIC Educational Resources Information Center

Belaineh, Matheas Shemelis

2017-01-01

Quality of education in higher institutions can be affected by different factors. It partly rests on the learning environment created by teachers and the learning approach students are employing during their learning. The main purpose of this study is to examine the learning environment at Mizan Tepi University from students' perspective and their…
Problematizing a general physics class: Understanding student engagement

NASA Astrophysics Data System (ADS)

Spaid, Mark Randall

This research paper describes the problems in democratizing a high school physics course and the disparate engagement students during class activities that promote scientific inquiry. Results from the Learning Orientation Questionnaire (Martinez, 2000) guide the participant observations and semi-formal interviews. Approximately 60% of the participants self-report a "resistant" or "conforming" approach to learning science; they expect to receive science knowledge from the teacher, and their engagement is influenced by affective and conative factors. These surface learners exhibit second order thinking (Kegan, 1994), do not understand abstract science concepts, and learn best from structured inquiry. To sustain engagement, conforming learners require motivational and instructional discourse from their teacher and peers. Resisting learners do not value learning and do not engage in most science class activities. The "performing" learners are able to deal with abstractions and can see relationships between lessons and activities, but they do not usually self-reflect or think critically (they are between Kegan's second order and third order thinking). They may select a deeper learning strategy if they value the knowledge for a future goal; however, they are oriented toward assessment and rely on the science teacher as an authority. They are influenced by affective and conative factors during structured and guided inquiry-based teaching, and benefit from motivational discourse and sustain engagement if they are interested in the topic. The transforming learners are more independent, self-assessing and self-directed. These students are third order thinkers (Kegan, 1994) who hold a sophisticated epistemology that includes critical thinking and reflection. These students select deep learning strategies without regard to affective and conative factors. They value instructional discourse from the teacher, but prefer less structured inquiry activities. Although specific teacher interventions during inquiry lessons which promote scientific inquiry are sometimes successful in moving students from a conforming learning approach to performing, those students usually regress to a previous orientation due to affective and conative factors, especially if they believe the instructional discourse is inadequate. When working in cooperative groups, the disparate epistemologies of students from each learning orientation category becomes problematic.
Blended learning in paediatric emergency medicine: preliminary analysis of a virtual learning environment.

PubMed

Spedding, Ruth; Jenner, Rachel; Potier, Katherine; Mackway-Jones, Kevin; Carley, Simon

2013-04-01

Paediatric emergency medicine (PEM) currently faces many competing educational challenges. Recent changes to the working patterns have made the delivery of effective teaching to trainees extremely difficult. We developed a virtual learning environment, on the basis of socioconstructivist principles, which allows learning to take place regardless of time or location. The aim was to evaluate the effectiveness of a blended e-learning approach for PEM training. We evaluated the experiences of ST3 trainees in PEM using a multimodal approach. We classified and analysed message board discussions over a 6-month period to look for evidence of practice change and learning. We conducted semistructured qualitative interviews with trainees approximately 5 months after they completed the course. Trainees embraced the virtual learning environment and had positive experiences of the blended approach to learning. Socioconstructivist learning did take place through the use of message boards on the virtual learning environment. Despite their initial unfamiliarity with the online learning system, the participants found it easy to access and use. The participants found the learning relevant and there was an overlap between shop floor learning and the online content. Clinical discussion was often led by trainees on the forums and these were described as enjoyable and informative. A blended approach to e-learning in basic PEM is effective and enjoyable to trainees.
Learning spatially coherent properties of the visual world in connectionist networks

NASA Astrophysics Data System (ADS)

Becker, Suzanna; Hinton, Geoffrey E.

1991-10-01

In the unsupervised learning paradigm, a network of neuron-like units is presented with an ensemble of input patterns from a structured environment, such as the visual world, and learns to represent the regularities in that input. The major goal in developing unsupervised learning algorithms is to find objective functions that characterize the quality of the network's representation without explicitly specifying the desired outputs of any of the units. The sort of objective functions considered cause a unit to become tuned to spatially coherent features of visual images (such as texture, depth, shading, and surface orientation), by learning to predict the outputs of other units which have spatially adjacent receptive fields. Simulations show that using an information-theoretic algorithm called IMAX, a network can be trained to represent depth by observing random dot stereograms of surfaces with continuously varying disparities. Once a layer of depth-tuned units has developed, subsequent layers are trained to perform surface interpolation of curved surfaces, by learning to predict the depth of one image region based on depth measurements in surrounding regions. An extension of the basic model allows a population of competing neurons to learn a distributed code for disparity, which naturally gives rise to a representation of discontinuities.
Intelligence for Human-Assistant Planetary Surface Robots

NASA Technical Reports Server (NTRS)

Hirsh, Robert; Graham, Jeffrey; Tyree, Kimberly; Sierhuis, Maarten; Clancey, William J.

2006-01-01

The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.
Online Bimanual Manipulation Using Surface Electromyography and Incremental Learning.

PubMed

Strazzulla, Ilaria; Nowak, Markus; Controzzi, Marco; Cipriani, Christian; Castellini, Claudio

2017-03-01

The paradigm of simultaneous and proportional myocontrol of hand prostheses is gaining momentum in the rehabilitation robotics community. As opposed to the traditional surface electromyography classification schema, in simultaneous and proportional control the desired force/torque at each degree of freedom of the hand/wrist is predicted in real-time, giving to the individual a more natural experience, reducing the cognitive effort and improving his dexterity in daily-life activities. In this study we apply such an approach in a realistic manipulation scenario, using 10 non-linear incremental regression machines to predict the desired torques for each motor of two robotic hands. The prediction is enforced using two sets of surface electromyography electrodes and an incremental, non-linear machine learning technique called Incremental Ridge Regression with Random Fourier Features. Nine able-bodied subjects were engaged in a functional test with the aim to evaluate the performance of the system. The robotic hands were mounted on two hand/wrist orthopedic splints worn by healthy subjects and controlled online. An average completion rate of more than 95% was achieved in single-handed tasks and 84% in bimanual tasks. On average, 5 min of retraining were necessary on a total session duration of about 1 h and 40 min. This work sets a beginning in the study of bimanual manipulation with prostheses and will be carried on through experiments in unilateral and bilateral upper limb amputees thus increasing its scientific value.
3DSEM++: Adaptive and intelligent 3D SEM surface reconstruction.

PubMed

Tafti, Ahmad P; Holz, Jessica D; Baghaie, Ahmadreza; Owen, Heather A; He, Max M; Yu, Zeyun

2016-08-01

Structural analysis of microscopic objects is a longstanding topic in several scientific disciplines, such as biological, mechanical, and materials sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around for decades to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. Whereas SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and facts about their three-dimensional (3D) structures. 3D surface reconstruction from SEM images leads to remarkable understanding of microscopic surfaces, allowing informative and qualitative visualization of the samples being investigated. In this contribution, we integrate several computational technologies including machine learning, contrario methodology, and epipolar geometry to design and develop a novel and efficient method called 3DSEM++ for multi-view 3D SEM surface reconstruction in an adaptive and intelligent fashion. The experiments which have been performed on real and synthetic data assert the approach is able to reach a significant precision to both SEM extrinsic calibration and its 3D surface modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

NASA Astrophysics Data System (ADS)

Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.
Markov Chain Monte Carlo Bayesian Learning for Neural Networks

NASA Technical Reports Server (NTRS)

Goodrich, Michael S.

2011-01-01

Conventional training methods for neural networks involve starting al a random location in the solution space of the network weights, navigating an error hyper surface to reach a minimum, and sometime stochastic based techniques (e.g., genetic algorithms) to avoid entrapment in a local minimum. It is further typically necessary to preprocess the data (e.g., normalization) to keep the training algorithm on course. Conversely, Bayesian based learning is an epistemological approach concerned with formally updating the plausibility of competing candidate hypotheses thereby obtaining a posterior distribution for the network weights conditioned on the available data and a prior distribution. In this paper, we developed a powerful methodology for estimating the full residual uncertainty in network weights and therefore network predictions by using a modified Jeffery's prior combined with a Metropolis Markov Chain Monte Carlo method.
Towards a Standards-Based Approach to E-Learning Personalization Using Reusable Learning Objects.

ERIC Educational Resources Information Center

Conlan, Owen; Dagger, Declan; Wade, Vincent

E-Learning systems that produce personalized course offerings for the learner are often expensive, both from a time and financial perspective, to develop and maintain. Learning content personalized to a learners' cognitive preferences has been shown to produce more effective learning, however many approaches to realizing this form of…
An Expert System-based Context-Aware Ubiquitous Learning Approach for Conducting Science Learning Activities

ERIC Educational Resources Information Center

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung

2013-01-01

Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…
Engagement in Learning: A Comparison between Asian and European International University Students

ERIC Educational Resources Information Center

Sakurai, Yusuke; Parpala, Anna; Pyhältö, Kirsi; Lindblom-Ylänne, Sari

2016-01-01

Drawing on research on both engagement in learning and approaches to learning, we examine the associations between international students' approaches to learning, factors in the teaching/learning environment and self-assessed academic outcomes. A total of 307 students responded to our survey. Their experience of the purposefulness of their course…
Student-Teachers' Approaches to Learning, Academic Performance and Teaching Efficacy

ERIC Educational Resources Information Center

Swee-Choo, Pauline Goh; Kung-Teck, Wong; Osman, Rosma

2012-01-01

Purpose: It is argued that the approaches to learning of students undergoing teacher training are likely to be related to their teaching and learning environment, especially as they move from a more regimented, structured learning environment in school to a tertiary learning environment that encourages more independent thinking and perhaps…
College Students' Motivation and Learning Strategies Profiles and Academic Achievement: A Self-Determination Theory Approach

ERIC Educational Resources Information Center

Liu, Woon Chia; Wang, Chee Keng John; Kee, Ying Hwa; Koh, Caroline; Lim, Boon San Coral; Chua, Lilian

2014-01-01

The development of effective self-regulated learning strategies is of interest to educationalists. In this paper, we examine inherent individual difference in self-regulated learning based on Motivated Learning for Learning Questionnaire (MLSQ) using the cluster analytic approach and examine cluster difference in terms of self-determination theory…
The Development of Blended-Learning Teaching Portfolio Course Using TBL Approach

ERIC Educational Resources Information Center

Pardamean, Bens; Prabowo, Harjanto; Muljo, Hery Harjono; Suparyanto, Teddy; Masli, Eryadi K.; Donovan, Jerome

2017-01-01

This article was written to develop a teaching portfolio that helps lecturers maximize the benefits of blended learning, a combination of in-person and online learning, through the use of Team-Based Learning (TBL) teaching and learning approach. Studies show that TBL can provide opportunities in developing teamwork capabilities and enhancing…
The Effect of Teaching with Stories on Associate Degree Nursing Students' Approach to Learning and Reflective Practice

ERIC Educational Resources Information Center

Bradshaw, Vicki

2012-01-01

This action research study is the culmination of several action cycles investigating cognitive information processing and learning strategies based on students approach to learning theory and assessing students' meta-cognitive learning, motivation, and reflective development suggestive of deep learning. The study introduces a reading…
Active Learning in the Middle Grades Classroom: Overcoming the Barriers to Implementation

ERIC Educational Resources Information Center

Edwards, Susan

2015-01-01

The Association for Middle Level Education advocates for instruction that incorporates active learning and multiple learning approaches in middle grades classrooms. The aim of this qualitative study was to examine middle level teachers who are able to implement active learning and multiple learning approaches within the standardized testing and…
A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

NASA Astrophysics Data System (ADS)

Houborg, Rasmus; McCabe, Matthew F.

2018-01-01

With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with inherent extrapolation and transferability limitations. Explanatory VIs formed from bands in the near-infrared (NIR) and shortwave infrared domains (e.g., NDWI) were associated with the highest predictive ability, whereas Cubist models relying entirely on VIs based on NIR and red band combinations (e.g., NDVI) were associated with comparatively high uncertainties (i.e., rMAD ∼ 21%). The most transferable and best performing models were based on combinations of several predictor variables, which included both NDWI- and NDVI-like variables. In this process, prior screening of input VIs based on an assessment of variable relevance served as an effective mechanism for optimizing prediction accuracies from both Cubist and RF. While this study demonstrated benefit in combining data mining operations with physically based constraints via a hybrid training approach, the concept of transferability and portability warrants further investigations in order to realize the full potential of emerging machine-learning techniques for regression purposes.
Using an In-Class Simulation in the First Accounting Class: Moving from Surface to Deep Learning

ERIC Educational Resources Information Center

Phillips, Mary E.; Graeff, Timothy R.

2014-01-01

As students often find the first accounting class to be abstract and difficult to understand, the authors designed an in-class simulation as an intervention to move students toward deep learning and away from surface learning. The simulation consists of buying and selling merchandise and accounting for transactions. The simulation is an effective…
Development of a machine learning potential for graphene

NASA Astrophysics Data System (ADS)

Rowe, Patrick; Csányi, Gábor; Alfè, Dario; Michaelides, Angelos

2018-02-01

We present an accurate interatomic potential for graphene, constructed using the Gaussian approximation potential (GAP) machine learning methodology. This GAP model obtains a faithful representation of a density functional theory (DFT) potential energy surface, facilitating highly accurate (approaching the accuracy of ab initio methods) molecular dynamics simulations. This is achieved at a computational cost which is orders of magnitude lower than that of comparable calculations which directly invoke electronic structure methods. We evaluate the accuracy of our machine learning model alongside that of a number of popular empirical and bond-order potentials, using both experimental and ab initio data as references. We find that whilst significant discrepancies exist between the empirical interatomic potentials and the reference data—and amongst the empirical potentials themselves—the machine learning model introduced here provides exemplary performance in all of the tested areas. The calculated properties include: graphene phonon dispersion curves at 0 K (which we predict with sub-meV accuracy), phonon spectra at finite temperature, in-plane thermal expansion up to 2500 K as compared to NPT ab initio molecular dynamics simulations and a comparison of the thermally induced dispersion of graphene Raman bands to experimental observations. We have made our potential freely available online at [http://www.libatoms.org].
The Perception of Workload and Task Complexity and Its Influence on Students' Approaches to Learning: A Study in Higher Education

ERIC Educational Resources Information Center

Kyndt, Eva; Dochy, Filip; Struyven, Katrien; Cascallar, Eduardo

2011-01-01

Researchers have tried to induce a deeper approach to learning by means of student-centred learning environments. Findings did not always confirm the positive hypotheses. This has given rise to the question as to what the discouraging or encouraging factors are for inducing a deep approach to learning. The aim of this research study is to…
The Relationship between Students' Preferred Approaches to Learning and Behaviors during Learning: An Examination of the Process Stage of the 3P Model

ERIC Educational Resources Information Center

Clinton, Virginia

2014-01-01

Student approaches to learning have been a popular area of research in educational psychology. One useful framework for understanding student approaches to learning is through Biggs' presage-process-product model. The purpose of this study is to examine the process stage of the 3P model. Undergraduate students (N = 67) thought aloud while…
An Odyssey into Cooperative Learning.

ERIC Educational Resources Information Center

Lemke, Thomas L.; Basile, Carole

1997-01-01

An experiment using cooperative learning in a introductory pharmacy course in medicinal chemistry revealed general acceptance of the cooperative learning approach by students, and some perceived advantages for both students and teachers. Although quantitative evidence supporting superiority of the cooperative learning approach was not found,…
The Effects of 3D-Representation Instruction on Composite-Solid Surface-Area Learning for Elementary School Students

ERIC Educational Resources Information Center

Sung, Yao-Ting; Shih, Pao-Chen; Chang, Kuo-En

2015-01-01

Providing instruction on spatial geometry, specifically how to calculate the surface areas of composite solids, challenges many elementary school teachers. Determining the surface areas of composite solids involves complex calculations and advanced spatial concepts. The goals of this study were to build on students' learning processes for…
Investigating Elementary Students' Learning Approaches, Motivational Goals, and Achievement in Science

ERIC Educational Resources Information Center

Hacieminoglu, Esme; Yilmaz-Tuzun, Ozgul; Ertepinar, Hamide

2009-01-01

This study examined the relationships among students' learning approaches, motivational goals, previous science grades, and their science achievement for the concepts related to atomic theory and explored the effects of gender and sociodemographic variables on students' learning approaches, motivational goals, and their science achievement for the…
The Learning of Consumer Skills in Adolescents: An Eclectic Approach.

ERIC Educational Resources Information Center

Kuo, Cheng

A study investigated the learning of consumer skills by adolescents, using two theoretical approaches--the social learning and the family communication pattern approaches. It was hypothesized that (1) assuming that parents are more experienced consumers than are adolescents, frequent discussion with parents on consumption matters are likely to…
Interrelations between Self-Efficacy and Learning Approaches: A Developmental Approach

ERIC Educational Resources Information Center

Phan, Huy Phuong

2011-01-01

Two major theoretical frameworks in educational psychology, namely student approaches to learning (SAL) and self-efficacy have been used extensively to explain and predict students' learning and academic achievement. There is a substantial body of research studies, for example, that documents the positive interrelations between individuals'…

Manpower Development for Workers in Tertiary Institutions: Distance Learning Approach

ERIC Educational Resources Information Center

Hassan, Moshood Ayinde

2011-01-01

The purpose of this study is to determine the extent to which workers patronize distance learning approach to further their education. Other purposes include: determine problems facing workers in the process of improving their knowledge and skills through distance learning approach; establish the level of attainment of manpower development…
Modeling the Relations among Students' Epistemological Beliefs, Motivation, Learning Approach, and Achievement

ERIC Educational Resources Information Center

Kizilgunes, Berna; Tekkaya, Ceren; Sungur, Semra

2009-01-01

The authors proposed a model to explain how epistemological beliefs, achievement motivation, and learning approach related to achievement. The authors assumed that epistemological beliefs influence achievement indirectly through their effect on achievement motivation and learning approach. Participants were 1,041 6th-grade students. Results of the…
Education and training column: the learning collaborative.

PubMed

MacDonald-Wilson, Kim L; Nemec, Patricia B

2015-03-01

This column describes the key components of a learning collaborative, with examples from the experience of 1 organization. A learning collaborative is a method for management, learning, and improvement of products or processes, and is a useful approach to implementation of a new service design or approach. This description draws from published material on learning collaboratives and the authors' experiences. The learning collaborative approach offers an effective method to improve service provider skills, provide support, and structure environments to result in lasting change for people using behavioral health services. This approach is consistent with psychiatric rehabilitation principles and practices, and serves to increase the overall capacity of the mental health system by structuring a process for discovering and sharing knowledge and expertise across provider agencies. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
Teaching undergraduate mathematics in interactive groups: how does it fit with students' learning?

NASA Astrophysics Data System (ADS)

Sheryn, Louise; Ell, Fiona

2014-08-01

Debates about how undergraduate mathematics should be taught are informed by different views of what it is to learn and to do mathematics. In this qualitative study 10 students enrolled in an advanced undergraduate course in mathematics shared their views about how they best learn mathematics. After participating in a semester-long course in combinatorics, taught using a non-traditional, formal group work approach, the 10 students shared their views about how such an approach fitted in with their experience of learning mathematics. A descriptive thematic analysis of the students' responses revealed that despite being very comfortable with the traditional approach to learning new mathematics, most students were open to a formal group work approach and could see benefits from it after their participation. The students' prior conceptions of the goal of undergraduate mathematics learning and their view of themselves as 'mathematicians' framed their experience of learning mathematics in a non-traditional class.
Stray light lessons learned from the Mars reconnaissance orbiter's optical navigation camera

NASA Astrophysics Data System (ADS)

Lowman, Andrew E.; Stauder, John L.

2004-10-01

The Optical Navigation Camera (ONC) is a technical demonstration slated to fly on NASA"s Mars Reconnaissance Orbiter in 2005. Conventional navigation methods have reduced accuracy in the days immediately preceding Mars orbit insertion. The resulting uncertainty in spacecraft location limits rover landing sites to relatively safe areas, away from interesting features that may harbor clues to past life on the planet. The ONC will provide accurate navigation on approach for future missions by measuring the locations of the satellites of Mars relative to background stars. Because Mars will be a bright extended object just outside the camera"s field of view, stray light control at small angles is essential. The ONC optomechanical design was analyzed by stray light experts and appropriate baffles were implemented. However, stray light testing revealed significantly higher levels of light than expected at the most critical angles. The primary error source proved to be the interface between ground glass surfaces (and the paint that had been applied to them) and the polished surfaces of the lenses. This paper will describe troubleshooting and correction of the problem, as well as other lessons learned that affected stray light performance.
Self-Learning Off-Lattice Kinetic Monte Carlo method as applied to growth on metal surfaces

NASA Astrophysics Data System (ADS)

Trushin, Oleg; Kara, Abdelkader; Rahman, Talat

2007-03-01

We propose a new development in the Self-Learning Kinetic Monte Carlo (SLKMC) method with the goal of improving the accuracy with which atomic mechanisms controlling diffusive processes on metal surfaces may be identified. This is important for diffusion of small clusters (2 - 20 atoms) in which atoms may occupy Off-Lattice positions. Such a procedure is also necessary for consideration of heteroepitaxial growth. The new technique combines an earlier version of SLKMC [1] with the inclusion of off-lattice occupancy. This allows us to include arbitrary positions of adatoms in the modeling and makes the simulations more realistic and reliable. We have tested this new approach for the case of the diffusion of small 2D Cu clusters diffusion on Cu(111) and found good performance and satisfactory agreement with results obtained from previous version of SLKMC. The new method also helped reveal a novel atomic mechanism contributing to cluster migration. We have also applied this method to study the diffusion of Cu clusters on Ag(111), and find that Cu atoms generally prefer to occupy off-lattice sites. [1] O. Trushin, A. Kara, A. Karim, T.S. Rahman Phys. Rev B 2005
Exploring the impact of instructional approaches on the learning and transfer of medication dosage calculation competency.

PubMed

Glaister, Karen

2005-09-01

The ability of nurses to perform accurate drug dosage calculations has repercussions for patients' well-being. How best to assist nurses develop competency in this area is paramount. This paper presents findings of a study conducted with undergraduate nurses to determine the effect of three instructional approaches on the learning of this skill. The quasi-experimental study exposed participants to one of three instructional approaches: integrative learning, computerised learning and a combination of integrative and computerised learning. Quantitative and qualitative approaches were used to explore differences in the instructional approaches and gain further understanding of the learning process. There was no statistical difference between the three instructional approaches on knowledge acquisition and transfer measures, other than measures for procedural knowledge, which was significant (F(2,47) = 3.33 at p < .044). A least-significant difference post hoc test (alpha = 0. 10) indicated computerised learning was significantly more effective in developing procedural knowledge. The provision of instructional strategies, which facilitate development of conditional knowledge and automaticity, is necessary for competency development in dosage calculations. Furthermore, the curriculum must incorporate authentic tasks and permit time to support competency attainment.
The Effect of Two Different Cooperative Approaches on Students' Learning and Practices within the Context of a WebQuest Science Investigation

ERIC Educational Resources Information Center

Zacharia, Zacharias C.; Xenofontos, Nikoletta A.; Manoli, Constantinos C.

2011-01-01

The goal of this study was to investigate the effect of two different cooperative learning approaches, namely, the Jigsaw Cooperative Approach (JCA) and the Traditional Cooperative Approach (TCA), on students' learning and practices/actions within the context of a WebQuest science investigation. Another goal of this study was to identify possible…
Impact of Technological Advancement on Pedagogy

ERIC Educational Resources Information Center

Abik, Mounia; Ajhoun, Rachida; Ensias, Lerma

2012-01-01

To improve the quality of learning, pedagogues have prescribed different pedagogical approaches (constructivist, cognitivist...). However, the effective implementation of the majority of these approaches has not been possible only after the advent of new forms of learning (E_learning, M-learning...). These forms are closely related to…
Adventure Learning: Transformative Hybrid Online Education

ERIC Educational Resources Information Center

Doering, Aaron

2006-01-01

Adventure learning (AL) is a hybrid distance education approach that provides students with opportunities to explore real-world issues through authentic learning experiences within collaborative learning environments. This article defines this online distance education approach, outlines an AL framework, and showcases an AL archetype. In AL…
Strategies for Effective Learning.

ERIC Educational Resources Information Center

Frierson, Henry T., Jr.

Suggestions are offered for applying learning techniques for a variety of learning situations. The approaches are applicable to learning medical school content as well as other advanced educational content. Ways to control external distractors are suggested, including a systematic approach to completing large tasks, such as writing a research…
A Quantitative Inquiry into the Effects of Blended Learning on English Language Learning: The Case of Malaysian Undergraduates

ERIC Educational Resources Information Center

Thang, Siew Ming; Mustaffa, Rosniah; Wong, Fook Fei; Noor, Noorizah Mohd.; Mahmud, Najihah; Latif, Hafizah; Aziz, Mohd. Sallehhudin Abd.

2013-01-01

Blended learning has been described as a pedagogical approach that combines effectiveness and socialization opportunities of the classroom with the technologically enhanced active learning possibilities of the online environment (Dziuban, Hartman, & Moskal, 2004). It has also been depicted as an approach that combines traditional learning with…
Investigations of Students' Motivation Towards Learning Secondary School Physics through Mastery Learning Approach

ERIC Educational Resources Information Center

Changeiywo, Johnson M.; Wambugu, P. W.; Wachanga, S. W.

2011-01-01

Teaching method is a major factor that affects students' motivation to learn physics. This study investigated the effects of using mastery learning approach (MLA) on secondary school students' motivation to learn physics. Solomon four non-equivalent control group design under the quasi-experimental research method was used in which a random sample…
Approaches to Learning and School Readiness in Head Start: Applications to Preschool Science

ERIC Educational Resources Information Center

Bustamante, Andres S.; White, Lisa J.; Greenfield, Daryl B.

2017-01-01

Approaches to learning are a set of domain-general skills that encompass curiosity, persistence, planning, and engagement in group learning. These skills play a key role in preschoolers' learning and predict school readiness in math and language. Preschool science is a critical domain for early education and facilitates learning across domains.…
Data-Driven Learning of Speech Acts Based on Corpora of DVD Subtitles

ERIC Educational Resources Information Center

Kitao, S. Kathleen; Kitao, Kenji

2013-01-01

Data-driven learning (DDL) is an inductive approach to language learning in which students study examples of authentic language and use them to find patterns of language use. This inductive approach to learning has the advantages of being learner-centered, encouraging hypothesis testing and learner autonomy, and helping develop learning skills.…
Off-Balance: The Integration of Physical Education Content Learning and Irish Language Learning in English-Medium Primary Schools in Ireland

ERIC Educational Resources Information Center

Ní Chróinín, Déirdre; Ní Mhurchú, Siobhán; Ó Ceallaigh, T. J.

2016-01-01

Increased attention to integrated approaches has resulted from demands to prioritise literacy learning while maintaining a balanced curriculum in primary schools. Limited empirical evidence to support integrated approaches to teaching physical education (PE) exists. This study explored the integration of PE content learning and the learning of…
Relations between Teacher Students' Approaches to Learning, Cognitive and Attributional Strategies, Well-Being, and Study Success

ERIC Educational Resources Information Center

Heikkila, Annamari; Lonka, Kirsti; Nieminen, Juha; Niemivirta, Markku

2012-01-01

Current theories of learning emphasize the role of motivational and affective aspects in university student learning. The aim of the present study was to examine the interrelations among approaches to learning, self-regulated learning, and cognitive strategies in the context of teacher education. Cognitive-motivational profiles were identified…
Undergraduate Students' Earth Science Learning: Relationships among Conceptions, Approaches, and Learning Self-Efficacy in Taiwan

ERIC Educational Resources Information Center

Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

2016-01-01

In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to…
Learning Outcomes in Vocational Education: A Business Plan Development by Production-Based Learning Model Approach

ERIC Educational Resources Information Center

Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia

2016-01-01

This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…
Concept Based Approach for Adaptive Personalized Course Learning System

ERIC Educational Resources Information Center

Salahli, Mehmet Ali; Özdemir, Muzaffer; Yasar, Cumali

2013-01-01

One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…

Using Student-Centred Learning Environments to Stimulate Deep Approaches to Learning: Factors Encouraging or Discouraging Their Effectiveness

ERIC Educational Resources Information Center

Baeten, Marlies; Kyndt, Eva; Struyven, Katrien; Dochy, Filip

2010-01-01

This review outlines encouraging and discouraging factors in stimulating the adoption of deep approaches to learning in student-centred learning environments. Both encouraging and discouraging factors can be situated in the context of the learning environment, in students' perceptions of that context and in characteristics of the students…
Understanding Cognitive Presence in an Online and Blended Community of Inquiry: Assessing Outcomes and Processes for Deep Approaches to Learning

ERIC Educational Resources Information Center

Akyol, Zehra; Garrison, D. Randy

2011-01-01

This paper focuses on deep and meaningful learning approaches and outcomes associated with online and blended communities of inquiry. Applying mixed methodology for the research design, the study used transcript analysis, learning outcomes, perceived learning, satisfaction, and interviews to assess learning processes and outcomes. The findings for…
Problem-Based Service Learning with a Heart: Organizational and Student Expectations and Experiences in a Postgraduate Not-for-Profit Workshop Event

ERIC Educational Resources Information Center

McDonald, Sharyn; Ogden-Barnes, Stephen

2013-01-01

Service learning and problem-based learning (PBL) are distinct, yet related educational approaches. When collaborative learning events which encourage the application of the PBL principles to real world challenges faced by Not-For-Profit organizations (NFPs), these learning approaches become potentially synergistic. However, there is limited…
E-learning and blended learning in textile engineering education: a closed feedback loop approach

NASA Astrophysics Data System (ADS)

Charitopoulos, A.; Vassiliadis, S.; Rangoussi, M.; Koulouriotis, D.

2017-10-01

E-learning has gained a significant role in typical education and in professional training, thanks to the flexibility it offers to the time and location parameters of the education event framework. Purely e-learning scenarios are mostly limited either to Open University-type higher education institutions or to graduate level or professional degrees; blended learning scenarios are progressively becoming popular thanks to their balanced approach. The aim of the present work is to propose approaches that exploit the e-learning and the blended-learning scenarios for Textile Engineering education programmes, especially for multi-institutional ones. The “E-Team” European MSc degree programme organized by AUTEX is used as a case study. The proposed solution is based on (i) a free and open-source e-learning platform (moodle) and (ii) blended learning educational scenarios. Educational challenges addressed include student engagement, student error / failure handling, as well as collaborative learning promotion and support.
The Analysis of Physics Learning in Senior High School of Semarang Based on The Scientific Approach and Assessment

NASA Astrophysics Data System (ADS)

Hardyanti, R. C.; Hartono; Fianti

2018-03-01

Physics Learning in Curriculum of 2013 is closely related to the implementation of scientific approach and authentic assessment in learning. This study aims to analyze the implementation of scientific approaches and authentic assessment in physics learning, as well as to analyze the constraints of scientific approach and authentic assessment in physics learning. The data collection techniques used in this study are questionnaires, observations, interviews, and documentation. The calculation results used are percentage techniques and analyzed by using qualitative descriptive approach. Based on the results of research and discussion, the implementation of physics learning based on the scientific approach goes well with the percentage of 84.60%. Physical learning activity based on authentic assessment also goes well with the percentage of 88%. The results of the percentage of scientific approaches and authentic assessment approaches are less than 100%. It shows that there are obstacles to the implementation of the scientific approach and the constraints of authentic assessment. The obstacles to the implementation of scientific approach include time, heavy load of material, input or ability of learners, the willingness of learners in asking questions, laboratory support, and the ability of students to process data. While the obstacles to the implementation of authentic assessment include the limited time for carrying out of authentic assessment, the components of the criteria in carrying out the authentic assessment, the lack of discipline in administering the administration, the difficulty of changing habits in carrying out the assessment from traditional assessment to the authentic assessment, the obstacle to process the score in accordance with the format Curriculum of 2013.
[Learning Portfolio: A New Strategy in Health Education].

PubMed

Cheng, Yi-Chuan; Chen, Ching-Ju; Chang, Yu-Shan; Huang, Li-Chi

2015-12-01

Health education is the teaching by healthcare professionals of healthcare-related knowledge and skills to students in order that these students learn to help patients self-manage their disease and maintain health. This article introduces a new strategy in health education known as the learning portfolio and presents the theoretical basis and function of the learning portfolio and the current application of this approach in academic and health education. The learning portfolio is a learner-centric approach that collects evidence related to an individual's learning process systematically. This approach helps educators understand learner needs and conditions, while allowing the learner to observe his / her learning process in a manner that promotes self-reflection, continual inspection, and behavioral modification throughout the learning process. The results enhance the motivation of learners and strengthen their care confidence in accomplishing learning tasks.
CAMELOT: A machine learning approach for coarse-grained simulations of aggregation of block-copolymeric protein sequences

PubMed Central

Ruff, Kiersten M.; Harmon, Tyler S.; Pappu, Rohit V.

2015-01-01

We report the development and deployment of a coarse-graining method that is well suited for computer simulations of aggregation and phase separation of protein sequences with block-copolymeric architectures. Our algorithm, named CAMELOT for Coarse-grained simulations Aided by MachinE Learning Optimization and Training, leverages information from converged all atom simulations that is used to determine a suitable resolution and parameterize the coarse-grained model. To parameterize a system-specific coarse-grained model, we use a combination of Boltzmann inversion, non-linear regression, and a Gaussian process Bayesian optimization approach. The accuracy of the coarse-grained model is demonstrated through direct comparisons to results from all atom simulations. We demonstrate the utility of our coarse-graining approach using the block-copolymeric sequence from the exon 1 encoded sequence of the huntingtin protein. This sequence comprises of 17 residues from the N-terminal end of huntingtin (N17) followed by a polyglutamine (polyQ) tract. Simulations based on the CAMELOT approach are used to show that the adsorption and unfolding of the wild type N17 and its sequence variants on the surface of polyQ tracts engender a patchy colloid like architecture that promotes the formation of linear aggregates. These results provide a plausible explanation for experimental observations, which show that N17 accelerates the formation of linear aggregates in block-copolymeric N17-polyQ sequences. The CAMELOT approach is versatile and is generalizable for simulating the aggregation and phase behavior of a range of block-copolymeric protein sequences. PMID:26723608
Learning Science, Learning about Science, Doing Science: Different goals demand different learning methods

NASA Astrophysics Data System (ADS)

Hodson, Derek

2014-10-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that recognize key differences in learning goals and criticizes the common assertion that 'current wisdom advocates that students best learn science through an inquiry-oriented teaching approach' on the grounds that conflating the distinction between learning by inquiry and engaging in scientific inquiry is unhelpful in selecting appropriate teaching/learning approaches.
Contextualizing learning to improve care using collaborative communities of practices.

PubMed

Jeffs, Lianne; McShane, Julie; Flintoft, Virginia; White, Peggy; Indar, Alyssa; Maione, Maria; Lopez, A J; Bookey-Bassett, Sue; Scavuzzo, Lauren

2016-09-02

The use of interorganizational, collaborative approaches to build capacity in quality improvement (QI) in health care is showing promise as a useful model for scaling up and accelerating the implementation of interventions that bridge the "know-do" gap to improve clinical care and provider outcomes. Fundamental to a collaborative approach is interorganizational learning whereby organizations acquire, share, and combine knowledge with other organizations and have the opportunity to learn from their respective successes and challenges in improvement areas. This learning approach aims to create the conditions for collaborative, reflective, and innovative experiential systems that enable collective discussions regarding daily practice issues and finding solutions for improvement. The concepts associated with interorganizational learning and deliberate learning activities within a collaborative 'Communities-of-practice'(CoP) approach formed the foundation of the of an interactive QI knowledge translation initiative entitled PERFORM KT. Nine teams participated including seven teams from two acute care hospitals, one from a long term care center, and one from a mental health sciences center. Six monthly CoP learning sessions were held and teams, with the support of an assigned mentor, implemented a QI project and monitored their results which were presented at an end of project symposium. 47 individuals participated in either a focus group or a personal interview. Interviews were transcribed and analyzed using an iterative content analysis. Four key themes emerged from the narrative dataset around experiences and perceptions associated with the PERFORM KT initiative: 1) being successful and taking it to other levels by being systematic, structured, and mentored; 2) taking it outside the comfort zone by being exposed to new concepts and learning together; 3) hearing feedback, exchanging stories, and getting new ideas; and 4) having a pragmatic and accommodating approach to apply new learnings in local contexts. Study findings offer insights into collaborative, inter-organizational CoP learning approaches to build QI capabilities amongst clinicians, staff, and managers. In particular, our study delineates the need to contextualize QI learning by using deliberate learning activities to balance systematic and structured approaches alongside pragmatic and accommodating approaches with expert mentors.
Focusing on learning through constructive alignment with task-oriented portfolio assessment

NASA Astrophysics Data System (ADS)

Cain, A.; Grundy, J.; Woodward, C. J.

2018-07-01

Approaches to learning have been shown to have a significant impact on student success in technical units. This paper reports on an action research study that applied the principles of constructive alignment to improve student learning outcomes in programming units. The proposed model uses frequent formative feedback to engage students with unit material, and encourage them to adopt deep approaches to learning. Our results provide a set of guiding principles and a structured teaching approach that focuses students on meeting unit learning objectives, the goal of constructive alignment. The results are demonstrated via descriptions of the resulting teaching and learning environment, student results, and staff and student reflections.
The Effects of Brain Based Learning Approach on Motivation and Students Achievement in Mathematics Learning

NASA Astrophysics Data System (ADS)

Mekarina, M.; Ningsih, Y. P.

2017-09-01

This classroom action research is based by the facts that the students motivation and achievement mathematics learning is less. One of the factors causing is learning that does not provide flexibility to students to empower the potential of the brain optimally. The aim of this research was to improve the student motivation and achievement in mathematics learning by implementing brain based learning approach. The subject of this research was student of grade XI in senior high school. The research consisted of two cycles. Data of student achievement from test, and the student motivation through questionnaire. Furthermore, the finding of this research showed the result of the analysis was the implementation of brain based learning approach can improve student’s achievement and motivation in mathematics learning.
Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

PubMed Central

Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.

2016-01-01

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011
Students' Approaches to Learning in Problem-Based Learning: Taking into Account Professional Behavior in the Tutorial Groups, Self-Study Time, and Different Assessment Aspects

ERIC Educational Resources Information Center

Loyens, Sofie M. M.; Gijbels, David; Coertjens, Liesje; Cote, Daniel J.

2013-01-01

Problem-based learning (PBL) represents a major development in higher educational practice and is believed to promote deep learning in students. However, empirical findings on the promotion of deep learning in PBL remain unclear. The aim of the present study is to investigate the relationships between students' approaches to learning (SAL) and…
Demarcating Advanced Learning Approaches from Methodological and Technological Perspectives

ERIC Educational Resources Information Center

Horvath, Imre; Peck, David; Verlinden, Jouke

2009-01-01

In the field of design and engineering education, the fast and expansive evolution of information and communication technologies is steadily converting traditional learning approaches into more advanced ones. Facilitated by Broadband (high bandwidth) personal computers, distance learning has developed into web-hosted electronic learning. The…
Meaningful Learning in the Cooperative Classroom

ERIC Educational Resources Information Center

Sharan, Yael

2015-01-01

Meaningful learning is based on more than what teachers transmit; it promotes the construction of knowledge out of learners' experience, feelings and exchanges with other learners. This educational view is based on the constructivist approach to learning and the co-operative learning approach. Researchers and practitioners in various…
The Special Place Project: Efficacy of a Place-Based Case Study Approach for Teaching Geoscience

NASA Astrophysics Data System (ADS)

Moosavi, Sadredin

2014-05-01

Achieving geoscience literacy of the general population has become increasingly important world wide as ever more connected and growing societies depend more and more on our planet's limited natural resource base. Building citizen understanding of their dependence on the local environment, and the geologic processes which created and continue to change it, has become a great challenge to educators at all levels of the education system. The Special Place Project described in this presentation explores use of a place-based case study approach combining instruction in geoscience content with development of observation, reasoning, writing and presentation skills. The approach allows students to select the locations for their individual case studies affording development of personal connections between the learner and his environment. The approach gives instructors at many grade levels the ability to develop core pedagogical content and skills while exploring the unique geologic environments relevant to the local population including such critical issues as land use, resource depletion, energy, climate change and the future of communities in a changing world. The geologic reasons for the location of communities and key events in their histories can be incorporated into the students' case studies as appropriate. The project is unique in placing all course instruction in the context of the quest to explore and gain understanding of the student's chosen location by using the inherently more generalized course content required by the curriculum. By modeling how scientists approach their research questions, this pedagogical technique not only integrates knowledge and skills from across the curriculum, it captures the excitement of scientific thinking on real world questions directly relevant to students' lives, increasing student engagement and depth of learning as demonstrated in the case study reports crafted by the students and exam results. Student learning of topics directly touched upon by the case study, such as geomorphologic features and processes observable at Earth's surface, is compared to learning on more abstract topics, such as subsurface Earth structure and tectonic processes, to provide a quantitative assessment of this pedagogical approach.
From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

PubMed

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.
Forward-Oriented Design for Learning: Illustrating the Approach

ERIC Educational Resources Information Center

Dimitriadis, Yannis; Goodyear, Peter

2013-01-01

This paper concerns sustainable approaches to design for learning, emphasising the need for designs to be able to thrive outside of the protective niches of project-based innovation. It builds on the "in medias res" framework and more specifically on a forward-oriented approach to design for learning: one that takes a pro-active design…
Factors Contributing to Changes in a Deep Approach to Learning in Different Learning Environments

ERIC Educational Resources Information Center

Postareff, Liisa; Parpala, Anna; Lindblom-Ylänne, Sari

2015-01-01

The study explored factors explaining changes in a deep approach to learning. The data consisted of interviews with 12 students from four Bachelor-level courses representing different disciplines. We analysed and compared descriptions of students whose deep approach either increased, decreased or remained relatively unchanged during their courses.…
From Blaming to Learning: Re-Framing Organisational Learning from Adverse Incidents

ERIC Educational Resources Information Center

Gray, Dee; Williams, Sion

2011-01-01

Purpose: This paper aims to discuss and present research findings from a proof of concept pilot, set up to test whether a teaching intervention which incorporated a dual reporting and learning approach from adverse incidents, could contribute towards individual and organisational approaches to patient safety. Design/methodology/approach: The study…

Approaches to Learning in a Second Year Chemical Engineering Course.

ERIC Educational Resources Information Center

Case, Jennifer M.; Gunstone, Richard F.

2003-01-01

Investigates student approaches to learning in a second year chemical engineering course by means of a qualitative research project which utilized interview and journal data from a group of 11 students. Identifies three approaches to learning: (1) conceptual; (2) algorithmic; and (3) information-based. Presents student responses to a series of…
Teaching and Learning about Qualitative Research in the Social Sciences: An Experiential Learning Approach Amongst Marketing Students

ERIC Educational Resources Information Center

Hopkinson, Gillian C.; Hogg, Margaret K.

2004-01-01

There is significant evidence that student-centred approaches to learning using experiential exercises considerably enhance students' understanding of substantive theory and also aid acquisition of transferable skills, such as those pertaining to research management and investigation. We consider an experiential pedagogic approach to be…
Learning Opportunities beyond the School. 2nd Edition.

ERIC Educational Resources Information Center

Hatcher, Barbara, Ed.; Beck, Shirley S., Ed.

The fact that much of learning occurs beyond school walls points to the need for a holistic approach to education. Such an approach involves planned cooperative links between family and the formal and informal learning environments that exist in the community. This monograph advocates such a holistic approach, discussing not only the value of…
Towards a Semantic E-Learning Theory by Using a Modelling Approach

ERIC Educational Resources Information Center

Yli-Luoma, Pertti V. J.; Naeve, Ambjorn

2006-01-01

In the present study, a semantic perspective on e-learning theory is advanced and a modelling approach is used. This modelling approach towards the new learning theory is based on the four SECI phases of knowledge conversion: Socialisation, Externalisation, Combination and Internalisation, introduced by Nonaka in 1994, and involving two levels of…
Student-Centered Transformative Learning in Leadership Education: An Examination of the Teaching and Learning Process

ERIC Educational Resources Information Center

Haber-Curran, Paige; Tillapaugh, Daniel W.

2015-01-01

Innovative and learner-centered approaches to teaching and learning are vital for the applied field of leadership education, yet little research exists on such pedagogical approaches within the field. Using a phenomenological approach in analyzing 26 students' reflective narratives, the authors explore students' experiences of and process of…
Enhancing the Teaching-Learning Process: A Knowledge Management Approach

ERIC Educational Resources Information Center

Bhusry, Mamta; Ranjan, Jayanthi

2012-01-01

Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…
Exploring the Living Learning Laboratory: An Approach to Strengthen Campus Sustainability Initiatives by Using Sustainability Science Approach

ERIC Educational Resources Information Center

Zen, Irina Safitri

2017-01-01

Purpose: The paper aims to explore and analyse the potential of campus living learning laboratory (LLL) as an integrated mechanism to provide the innovative and creative teaching and learning experiences, robust research output and strengthening the campus sustainability initiatives by using the sustainability science approach.…
Organizational Approach to the Ergonomic Examination of E-Learning Modules

ERIC Educational Resources Information Center

Lavrov, Evgeniy; Kupenko, Olena; Lavryk, Tetiana; Barchenko, Natalia

2013-01-01

With a significant increase in the number of e-learning resources the issue of quality is of current importance. An analysis of existing scientific and methodological literature shows the variety of approaches, methods and tools to evaluate e-learning materials. This paper proposes an approach based on the procedure for estimating parameters of…
Micro-Macro Compatibility: When Does a Complex Systems Approach Strongly Benefit Science Learning?

ERIC Educational Resources Information Center

Samon, Sigal; Levy, Sharona T.

2017-01-01

The study explores how a complexity approach empowers science learning. A complexity approach represents systems as many interacting entities. The construct of micro-macro compatibility is introduced, the degree of similarity between behaviors at the micro- and macro-levels of the system. Seventh-grade students' learning about gases was studied…
Using storytelling as an approach to teaching and learning with diverse students.

PubMed

Koenig, Jill M; Zorn, CeCelia R

2002-09-01

Storytelling is an approach to teaching and learning that develops from the lived experiences ofteachers, clinicians, and students. This article examines thestorytelling process used to help students explore personal roles and make sense of their lives, and as an approach to help diverse undergraduate students with various learning styles.
A Guided Discovery Approach for Learning Metabolic Pathways

ERIC Educational Resources Information Center

Schultz, Emeric

2005-01-01

Learning the wealth of information in metabolic pathways is both challenging and overwhelming for students. A step-by-step guided discovery approach to the learning of the chemical steps in gluconeogenesis and the citric acid cycle is described. This approach starts from concepts the student already knows, develops these further in a logical…
How Organisations Learn from Safety Incidents: A Multifaceted Problem

ERIC Educational Resources Information Center

Lukic, Dane; Margaryan, Anoush; Littlejohn, Allison

2010-01-01

Purpose: This paper seeks to review current approaches to learning from health and safety incidents in the workplace. The aim of the paper is to identify the diversity of approaches and analyse them in terms of learning aspects. Design/methodology/approach: A literature review was conducted searching for terms incident/accident/near…
Exploring Zimbabwean Advanced Level Chemistry Students' Approaches to Investigations from a Learning Perspective

ERIC Educational Resources Information Center

Chirikure, Tamirirofa; Hobden, Paul; Hobden, Sally

2018-01-01

In this paper we report on the findings of a study on Advanced Level Chemistry students' approaches to investigations from a learning perspective in the Zimbabwean educational context. Students' approaches to investigations are inextricably linked to the quality of learning and performances in these practical activities. An explanatory…
The Formation of Conservation-Based Behaviour of Mechanical Engineering Students through Contextual Learning Approach

ERIC Educational Resources Information Center

Sudarman; Djuniadi; Sutopo, Yeri

2017-01-01

This study was aimed to figure out: (1) the implementation of contextual learning approaches; (2) the learning outcome of conservation education using contextual approach on the internship program preparation class; (3) the conservation-based behaviour of the internship program participants; (4) the contribution of conservation education results…
Three Metacognitive Approaches to Training Pre-Service Teachers in Different Learning Phases of Technological Pedagogical Content Knowledge

ERIC Educational Resources Information Center

Kramarski, Bracha; Michalsky, Tova

2009-01-01

Our study investigated 3 metacognitive approaches provided during different phases of learning technological pedagogical content knowledge (TPCK) in a Web-based learning environment. These metacognitive approaches were based on self-question prompts (Kramarski & Mevarech, 2003) which appeared in pop-up screens and fostered the Self-Regulated…
A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

PubMed

Chung, Michael Jae-Yoon; Friesen, Abram L; Fox, Dieter; Meltzoff, Andrew N; Rao, Rajesh P N

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.
A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

PubMed Central

Chung, Michael Jae-Yoon; Friesen, Abram L.; Fox, Dieter; Meltzoff, Andrew N.; Rao, Rajesh P. N.

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration. PMID:26536366
A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)

DTIC Science & Technology

2008-11-01

retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for...estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity...and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach
Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.
Learning approaches and learning difficulties: a comparison of Indian and Nepali dental science students.

PubMed

Mayya, Shreemathi S; Rao, A Krishna; Ramnarayan, K

2002-11-01

This study explored the difference in learning approaches and difficulties of Nepali and Indian undergraduate students of dental science. A locally developed inventory was used to measure learning approach and learning difficulties. Data collected from 166 Indians and 69 Nepalis were compared. The scores on various scales of the inventory indicate that Nepalis are more fearful and less confident regarding examination and course completion and have significantly less positive perception about academic capability. Indian students scored significantly higher on motivation, interest, and deep processing. The language problem was significantly greater for Nepali students. Higher percentages of Nepalis experienced various academic and nonacademic problems. The study highlights the need to consider difference in learning approach among the students of health science courses that admit students from different academic, nonacademic, and cultural backgrounds.

Machine Learning Approaches for Clinical Psychology and Psychiatry.

PubMed

Dwyer, Dominic B; Falkai, Peter; Koutsouleris, Nikolaos

2018-05-07

Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.
An Analytics-Based Approach to Managing Cognitive Load by Using Log Data of Learning Management Systems and Footprints of Social Media

ERIC Educational Resources Information Center

Yen, Cheng-Huang; Chen, I-Chuan; Lai, Su-Chun; Chuang, Yea-Ru

2015-01-01

Traces of learning behaviors generally provide insights into learners and the learning processes that they employ. In this article, a learning-analytics-based approach is proposed for managing cognitive load by adjusting the instructional strategies used in online courses. The technology-based learning environment examined in this study involved a…
Evaluation of eLearning Usage in South African Universities: A Critical Review

ERIC Educational Resources Information Center

Bagarukayo, Emily; Kalema, Billy

2015-01-01

Although eLearning is the use of technology for teaching, learning and assessment, there is no common approach to it across South African Higher Education Institutions. There is therefore a concern that the full potential of eLearning approach is not utilised. This paper examines the nature and the extent of eLearning activities in South African…
Examining the Roles of Blended Learning Approaches in Computer-Supported Collaborative Learning (CSCL) Environments: A Delphi Study

ERIC Educational Resources Information Center

So, Hyo-Jeong; Bonk, Curtis J.

2010-01-01

In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended…
Harnessing the Power of Learning Management Systems: An E-Learning Approach for Professional Development.

PubMed

White, Meagan; Shellenbarger, Teresa

E-learning provides an alternative approach to traditional professional development activities. A learning management system may help nursing professional development practitioners deliver content more efficiently and effectively; however, careful consideration is needed during planning and implementation. This article provides essential information in the selection and use of a learning management system for professional development.
"We Had a Blast!": An Empirical Affirmation of Blended Learning as the Preferred Learning Mode for Adult Learners

ERIC Educational Resources Information Center

Asunka, Stephen

2017-01-01

As many important issues pertaining to blended learning within the Sub-Saharan African context remain unexplored, this study implemented a blended learning approach in a graduate level course at a private university in Ghana, with the objective of exploring adult learners' attitudes, experiences and behaviors towards this learning approach, as…
Family, Learning Environments, Learning Approaches, and Student Outcomes in a Malaysian Private University

ERIC Educational Resources Information Center

Kek, Megan A. Yih Chyn; Darmawan, I. Gusti Ngurah; Chen, Yu Sui

2007-01-01

This article presents the quantitative findings from a mixed methods study of students and faculty at a private medical university in Malaysia. In particular, the relationships among students' individual characteristics, general self-efficacy, family context, university and classroom learning environments, curriculum, approaches to learning, and…
Democratic Practices in a Constructivist Science Classroom

ERIC Educational Resources Information Center

Daher, Wajeeh; Saifi, Abdel-Gani

2018-01-01

The constructivist learning approach is suggested as a means for facilitating students' learning of science and increasing their participation in this learning. Several studies have shown the contribution of this approach to the different aspects of students' learning of science, though little research has examined the contribution of this…
Opening Lines: Approaches to the Scholarship of Teaching and Learning.

ERIC Educational Resources Information Center

Hutchings, Pat, Ed.

This publication features reports by eight Carnegie Scholars who are working to develop a scholarship of teaching and learning that will advance the profession of teaching and improve student learning. Following the Introduction, "Approaching the Scholarship of Teaching and Learning" (Pat Hutchings), the papers are: "Investigating Student Learning…
Monitoring Collaborative Activities in Computer Supported Collaborative Learning

ERIC Educational Resources Information Center

Persico, Donatella; Pozzi, Francesca; Sarti, Luigi

2010-01-01

Monitoring the learning process in computer supported collaborative learning (CSCL) environments is a key element for supporting the efficacy of tutor actions. This article proposes an approach for analysing learning processes in a CSCL environment to support tutors in their monitoring tasks. The approach entails tracking the interactions within…
Flash Study Analysis and the Music Learning Pro-Files Project

ERIC Educational Resources Information Center

Cremata, Radio; Pignato, Joseph; Powell, Bryan; Smith, Gareth Dylan

2016-01-01

This paper introduces the Music Learning Profiles Project, and its methodological approach, flash study analysis. Flash study analysis is a method that draws heavily on extant qualitative approaches to education research, to develop broad understandings of music learning in diverse contexts. The Music Learning Profiles Project (MLPP) is an…
Starting with Worldviews: A Five-Step Preparatory Approach to Integrative Interdisciplinary Learning

ERIC Educational Resources Information Center

Augsburg, Tanya; Chitewere, Tendai

2013-01-01

In this article we propose a five-step sequenced approach to integrative interdisciplinary learning in undergraduate gateway courses. Drawing from the literature of interdisciplinarity, transformative learning theory, and theories of reflective learning, we utilize a sequence of five steps early in our respective undergraduate gateway courses to…
Project Management Approaches for Online Learning Design

ERIC Educational Resources Information Center

Eby, Gulsun; Yuzer, T. Volkan

2013-01-01

Developments in online learning and its design are areas that continue to grow in order to enhance students' learning environments and experiences. However, in the implementation of new technologies, the importance of properly and fairly overseeing these courses is often undervalued. "Project Management Approaches for Online Learning Design"…
Student Engagement and Blended Learning: Making the Assessment Connection

ERIC Educational Resources Information Center

Vaughan, Norman

2014-01-01

There is an increased focus on student engagement and blended approaches to learning in higher education. This article demonstrates how collaborative learning applications and a blended approach to learning can be used to design and support assessment activities that increase levels of student engagement with course concepts, their peers, faculty…
Adult Learning in Health and Safety: Some Issues and Approaches.

ERIC Educational Resources Information Center

O Fathaigh, Mairtin

This document, which was developed for presentation at a seminar on adult learning and safety, examines approaches to occupational safety and health (OSH) learning/training in the workplace. Section 1 examines selected factors affecting adults' learning in workplace OSH programs. The principal dimensions along which individual adult learners will…
Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming

ERIC Educational Resources Information Center

Thota, Neena; Whitfield, Richard

2010-01-01

This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…
Employees' and Managers' Accounts of Interactive Workplace Learning: A Grounded Theory of "Complex Integrative Learning"

ERIC Educational Resources Information Center

Armson, Genevieve; Whiteley, Alma

2010-01-01

Purpose: The purpose of this paper is to investigate employees' and managers' accounts of interactive learning and what might encourage or inhibit emergent learning. Design/methodology/approach: The approach taken was a constructivist/social constructivist ontology, interpretive epistemology and qualitative methodology, using grounded theory…
Enhancing the Design and Analysis of Flipped Learning Strategies

ERIC Educational Resources Information Center

Jenkins, Martin; Bokosmaty, Rena; Brown, Melanie; Browne, Chris; Gao, Qi; Hanson, Julie; Kupatadze, Ketevan

2017-01-01

There are numerous calls in the literature for research into the flipped learning approach to match the flood of popular media articles praising its impact on student learning and educational outcomes. This paper addresses those calls by proposing pedagogical strategies that promote active learning in "flipped" approaches and improved…
Micro Processes of Learning: Exploring the Interplay between Conceptions, Meanings and Expressions

ERIC Educational Resources Information Center

Anderberg, Elsie; Alvegard, Christer; Svensson, Lennart; Johansson, Thorsten

2009-01-01

The article describes qualitative variation in micro processes of learning, focusing the dynamic interplay between conceptions, expressions and meanings of expressions in students' learning in higher education. The intentional-expressive approach employed is an alternative approach to the function of language use in learning processes. In the…
A Learning Progressions Approach to Early Algebra Research and Practice

ERIC Educational Resources Information Center

Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Knuth, Eric

2015-01-01

We detail a learning progressions approach to early algebra research and how existing work around learning progressions and trajectories in mathematics and science education has informed our development of a four-component theoretical framework consisting of: a curricular progression of learning goals across big algebraic ideas; an instructional…

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