Impacts of Learning Orientation on Product Innovation Performance

ERIC Educational Resources Information Center

Calisir, Fethi; Gumussoy, Cigdem Altin; Guzelsoy, Ezgi

2013-01-01

Purpose: The present study aims to examine the effect of learning orientation (commitment to learning, shared vision, open-mindedness) on the product innovation performance (product innovation efficacy and efficiency) of companies in Turkey. Design/methodology/approach: A structural equation-modeling approach was applied to identify the variables…

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.

A Cooperative Approach To Teaching Mineral Identification.

ERIC Educational Resources Information Center

Constantopoulos, Terri Lynn

1994-01-01

Describes Jigsaw Teaching, a cooperative learning approach, in relation to mineral identification. This technique may also be applied to rock identification. Students work in groups of four and learn to identify 20 minerals, becoming an "expert" on five of them. Helping to teach other students reinforces what each student has learned.…

Online Learning: Learner Characteristics and Their Approaches to Managing Learning

ERIC Educational Resources Information Center

del Valle, Rodrigo; Duffy, Thomas M.

2009-01-01

Using cluster analysis this study investigated the characteristics of learning strategies learners use in online courses with one-on-one mentoring. Three distinct approaches were identified: "Mastery oriented", "Task focused" and "Minimalist in effort". Despite the widespread concern that students will have difficulty managing their time in online…

Supporting new graduate professional development: a clinical learning framework.

PubMed

Fitzgerald, Cate; Moores, Alis; Coleman, Allison; Fleming, Jennifer

2015-02-01

New graduate occupational therapists are required to competently deliver health-care practices within complex care environments. An occupational therapy clinical education programme within a large public sector health service sought to investigate methods to support new graduates in their clinical learning and professional development. Three cycles of an insider action research approach each using the steps of planning, action, critical observation and reflection were undertaken to investigate new graduate learning strategies, develop a learning framework and pilot its utility. Qualitative research methods were used to analyse data gathered during the action research cycles. Action research identified variations in current practices to support new graduate learning and to the development of the Occupational Therapy Clinical Learning Framework (OTCLF). Investigation into the utility of the OTCLF revealed two themes associated with its implementation namely (i) contribution to learning goal development and (ii) compatibility with existing learning supports. The action research cycles aimed to review current practices to support new graduate learning. The learning framework developed encourages reflection to identify learning needs and the review, discussion of, and engagement in, goal setting and learning strategies. Preliminary evidence indicates that the OTCLF has potential as an approach to guide new graduate goal development supported by supervision. Future opportunity to implement a similar learning framework in other allied health professions was identified, enabling a continuation of the cyclical nature of enquiry, integral to this research approach within the workplace. © 2014 Occupational Therapy Australia.

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.

Are High Achievers Successful in Collaborative Learning? An Explorative Study of College Students' Learning Approaches in Team Project-Based Learning

ERIC Educational Resources Information Center

Lee, Hye-Jung; Kim, Hyekyung; Byun, Hyunjung

2017-01-01

This study analyses how high-achieving students approach team project-based learning (TPBL) and aims to identify the implications and challenges of TPBL practice in higher education. After interviewing 32 high-achieving students and surveying 1022 additional students at a South Korean university, we found that four factors were particularly…

Qualitative Variation in Approaches to University Teaching and Learning in Large First-Year Classes

ERIC Educational Resources Information Center

Prosser, Michael; Trigwell, Keith

2014-01-01

Research on teaching from a student learning perspective has identified two qualitatively different approaches to university teaching. They are an information transmission and teacher-focused approach, and a conceptual change and student-focused approach. The fundamental difference being in the former the intention is to transfer information to…

Children's Learning in Scientific Thinking: Instructional Approaches and Roles of Variable Identification and Executive Function

NASA Astrophysics Data System (ADS)

Blums, Angela

The present study examines instructional approaches and cognitive factors involved in elementary school children's thinking and learning the Control of Variables Strategy (CVS), a critical aspect of scientific reasoning. Previous research has identified several features related to effective instruction of CVS, including using a guided learning approach, the use of self-reflective questions, and learning in individual and group contexts. The current study examined the roles of procedural and conceptual instruction in learning CVS and investigated the role of executive function in the learning process. Additionally, this study examined how learning to identify variables is a part of the CVS process. In two studies (individual and classroom experiments), 139 third, fourth, and fifth grade students participated in hands-on and paper and pencil CVS learning activities and, in each study, were assigned to either a procedural instruction, conceptual instruction, or control (no instruction) group. Participants also completed a series of executive function tasks. The study was carried out with two parts--Study 1 used an individual context and Study 2 was carried out in a group setting. Results indicated that procedural and conceptual instruction were more effective than no instruction, and the ability to identify variables was identified as a key piece to the CVS process. Executive function predicted ability to identify variables and predicted success on CVS tasks. Developmental differences were present, in that older children outperformed younger children on CVS tasks, and that conceptual instruction was slightly more effective for older children. Some differences between individual and group instruction were found, with those in the individual context showing some advantage over the those in the group setting in learning CVS concepts. Conceptual implications about scientific thinking and practical implications in science education are discussed.

Effective Implementation of E-Learning: A Case Study of the Australian Army

ERIC Educational Resources Information Center

Newton, Diane; Ellis, Allan

2005-01-01

Purpose--This case study identifies factors influencing the implementation of e-learning within the Australian Army training context. Design/methodology/approach--A grounded theory approach was used to gain an understanding of the concerns of stakeholders involved in e-learning implementation. This research included interviews with Army managers,…

Mapping Trends in Pedagogical Approaches and Learning Technologies: Perspectives from the Canadian, International, and Military Education Contexts

ERIC Educational Resources Information Center

Scoppio, Grazia; Covell, Leigha

2016-01-01

Increased technological advances, coupled with new learners' needs, have created new realities for higher education contexts. This study explored and mapped trends in pedagogical approaches and learning technologies in postsecondary education and identified how these innovations are affecting teaching and learning practices in higher education…

Face-to-Face or Distance Training: Two Different Approaches To Motivate SMEs to Learn.

ERIC Educational Resources Information Center

Lawless, Naomi; Allan, John; O'Dwyer, Michele

2000-01-01

Two approaches to training for small/medium-sized enterprises were compared: a British distance learning program and an Irish program offering face-to-face training for micro-enterprises. Both used constructivist, collaborative, and reflective methods. Advantages and disadvantages of each approach were identified. (SK)

What Do Student Learning Inventories Really Measure? A Critical Analysis of Students' Responses to the Approaches to Learning and Studying Inventory

ERIC Educational Resources Information Center

Mogashana, Disaapele; Case, Jennifer M.; Marshall, Delia

2012-01-01

Student learning inventories are used by both researchers and educators as tools to identify "at risk" students. This article critically interrogates the results of one of these inventories, the 18-item Approaches to Learning and Studying Inventory. In-depth interviews were held with a purposive sample of 10 first-year engineering…

Recognising and Validating Outcomes of Non-Accredited Learning: A Practical Approach.

ERIC Educational Resources Information Center

Greenwood, Maggie, Ed.; Hayes, Amanda, Ed.; Turner, Cheryl, Ed.; Vorhaus, John, Ed.

A group of adult educators in England conducted seven case studies to identify strategies for recognizing adult students' learning progress in nonaccredited programs. The case studies identified the following elements of good practice in the process of recording and validating achievement: (1) initial identification of learning objectives; (2)…

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.

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

ERIC Educational Resources Information Center

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

A transformative perspective on learning and professional development of Afghan physiotherapists.

PubMed

Wickford, Jenny; Edwards, Ian; Rosberg, Susanne

2012-05-01

The aim of this article is to explore factors that impacted learning of Afghan physiotherapists in a development project to improve the physiotherapy services in a disability programme implemented by a Swedish nongovernmental organisation in Afghanistan. Participant observation, recorded as field notes, was used to document the process, to gain a better understanding of professional development of physiotherapists in Afghanistan. Field notes were analysed and factors affecting learning were interpreted from a perspective inspired by transformative learning. Various factors were identified: a pattern approach to treatment, linear thinking, and socially oriented decision making affected how new things learned were put into practice; concrete representations and an instrumental view of knowledge characterised learning approaches; language barriers, different interpretations of meaning, and cultural codes challenged communication; and a prescriptive, encouraging approach of the expatriate physiotherapy development worker affected teaching and learning. Working with professional development across cultural borders is challenging, and the identified factors impacting learning can help expatriate physiotherapists in adapting training to the Afghan context. Exploring meaning perspectives and communicative learning could enhance understanding of these factors for both expatriate and Afghan physiotherapists and should be a focus in future development activities.

Organisational Issues for E-Learning: Critical Success Factors as Identified by HE Practitioners

ERIC Educational Resources Information Center

McPherson, Maggie; Nunes, Miguel Baptista

2006-01-01

Purpose: The purpose of this paper is to report on a research project that identified organisational critical success factors (CSFs) for e-learning implementation in higher education (HE). These CSFs can be used as a theoretical foundation upon which to base decision-making and strategic thinking about e-learning. Design/methodology/approach: The…

Internship-Related Learning Outcomes and Their Influential Factors: The Case of Vietnamese Tourism and Hospitality Students

ERIC Educational Resources Information Center

Nghia, Tran Le Huu; Duyen, Nguyen Thi My

2018-01-01

Purpose: The purpose of this paper is to explore the experiences of Tourism and Hospitality interns in Vietnam to identify dimensions of internship-related learning outcomes and factors influencing these learning outcomes. Design/methodology/approach: In total, 12 in-depth interviews were conducted with 12 interns to identify the dimensions of…

Distance Learning.

ERIC Educational Resources Information Center

Orey, Michael; Koenecke, Lynne; Snider, Richard C.; Perkins, Ross A.; Holmes, Glen A.; Lockee, Barbara B.; Moller, Leslie A.; Harvey, Douglas; Downs, Margaret; Godshalk, Veronica M.

2003-01-01

Contains four articles covering trends and issues on distance learning including: the experience of two learners learning via the Internet; a systematic approach to determining the scalability of a distance education program; identifying factors that affect learning community development and performance in asynchronous distance education; and…

The evaluation of student-centredness of teaching and learning: a new mixed-methods approach.

PubMed

Lemos, Ana R; Sandars, John E; Alves, Palmira; Costa, Manuel J

2014-08-14

The aim of the study was to develop and consider the usefulness of a new mixed-methods approach to evaluate the student-centredness of teaching and learning on undergraduate medical courses. An essential paradigm for the evaluation was the coherence between how teachers conceptualise their practice (espoused theories) and their actual practice (theories-in-use). The context was a module within an integrated basic sciences course in an undergraduate medical degree programme. The programme had an explicit intention of providing a student-centred curriculum. A content analysis framework based on Weimer's dimensions of student-centred teaching was used to analyze data collected from individual interviews with seven teachers to identify espoused theories and 34h of classroom observations and one student focus group to identify theories-in-use. The interviewees were identified by purposeful sampling. The findings from the three methods were triangulated to evaluate the student-centredness of teaching and learning on the course. Different, but complementary, perspectives of the student-centredness of teaching and learning were identified by each method. The triangulation of the findings revealed coherence between the teachers' espoused theories and theories-in-use. A mixed-methods approach that combined classroom observations with interviews from a purposeful sample of teachers and students offered a useful evaluation of the extent of student-centredness of teaching and learning of this basic science course. Our case study suggests that this new approach is applicable to other courses in medical education.

The evaluation of student-centredness of teaching and learning: a new mixed-methods approach

PubMed Central

Lemos, Ana R.; Sandars, John E.; Alves, Palmira

2014-01-01

Objectives The aim of the study was to develop and consider the usefulness of a new mixed-methods approach to evaluate the student-centredness of teaching and learning on undergraduate medical courses. An essential paradigm for the evaluation was the coherence between how teachers conceptualise their practice (espoused theories) and their actual practice (theories-in-use). Methods The context was a module within an integrated basic sciences course in an undergraduate medical degree programme. The programme had an explicit intention of providing a student-centred curriculum. A content analysis framework based on Weimer’s dimensions of student-centred teaching was used to analyze data collected from individual interviews with seven teachers to identify espoused theories and 34h of classroom observations and one student focus group to identify theories-in-use. The interviewees were identified by purposeful sampling. The findings from the three methods were triangulated to evaluate the student-centredness of teaching and learning on the course. Results Different, but complementary, perspectives of the student-centredness of teaching and learning were identified by each method. The triangulation of the findings revealed coherence between the teachers’ espoused theories and theories-in-use. Conclusions A mixed-methods approach that combined classroom observations with interviews from a purposeful sample of teachers and students offered a useful evaluation of the extent of student-centredness of teaching and learning of this basic science course. Our case study suggests that this new approach is applicable to other courses in medical education. PMID:25341225

Machine Learning Approaches for Detecting Diabetic Retinopathy from Clinical and Public Health Records.

PubMed

Ogunyemi, Omolola; Kermah, Dulcie

2015-01-01

Annual eye examinations are recommended for diabetic patients in order to detect diabetic retinopathy and other eye conditions that arise from diabetes. Medically underserved urban communities in the US have annual screening rates that are much lower than the national average and could benefit from informatics approaches to identify unscreened patients most at risk of developing retinopathy. Using clinical data from urban safety net clinics as well as public health data from the CDC's National Health and Nutrition Examination Survey, we examined different machine learning approaches for predicting retinopathy from clinical or public health data. All datasets utilized exhibited a class imbalance. Classifiers learned on the clinical data were modestly predictive of retinopathy with the best model having an AUC of 0.72, sensitivity of 69.2% and specificity of 55.9%. Classifiers learned on public health data were not predictive of retinopathy. Successful approaches to detecting latent retinopathy using machine learning could help safety net and other clinics identify unscreened patients who are most at risk of developing retinopathy and the use of ensemble classifiers on clinical data shows promise for this purpose.

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.

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.

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.

Developing models to predict 8th grade students' achievement levels on timss science based on opportunity-to-learn variables

NASA Astrophysics Data System (ADS)

Whitford, Melinda M.

Science educational reforms have placed major emphasis on improving science classroom instruction and it is therefore vital to study opportunity-to-learn (OTL) variables related to student science learning experiences and teacher teaching practices. This study will identify relationships between OTL and student science achievement and will identify OTL predictors of students' attainment at various distinct achievement levels (low/intermediate/high/advanced). Specifically, the study (a) address limitations of previous studies by examining a large number of independent and control variables that may impact students' science achievement and (b) it will test hypotheses of structural relations to how the identified predictors and mediating factors impact on student achievement levels. The study will follow a multi-stage and integrated bottom-up and top-down approach to identify predictors of students' achievement levels on standardized tests using TIMSS 2011 dataset. Data mining or pattern recognition, a bottom-up approach will identify the most prevalent association patterns between different student achievement levels and variables related to student science learning experiences, teacher teaching practices and home and school environments. The second stage is a top-down approach, testing structural equation models of relations between the significant predictors and students' achievement levels according.

A Conceptual Framework for Organizing Active Learning Experiences in Biology Instruction

ERIC Educational Resources Information Center

Gardner, Joel; Belland, Brian R.

2012-01-01

Introductory biology courses form a cornerstone of undergraduate instruction. However, the predominantly used lecture approach fails to produce higher-order biology learning. Research shows that active learning strategies can increase student learning, yet few biology instructors use all identified active learning strategies. In this paper, we…

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.

Avoid, Control, Succumb, or Balance: Engineering Students' Approaches to a Wicked Sustainability Problem

NASA Astrophysics Data System (ADS)

Lönngren, Johanna; Ingerman, Åke; Svanström, Magdalena

2017-08-01

Wicked sustainability problems (WSPs) are an important and particularly challenging type of problem. Science and engineering education can play an important role in preparing students to deal with such problems, but current educational practice may not adequately prepare students to do so. We address this gap by providing insights related to students' abilities to address WSPs. Specifically, we aim to (I) describe key constituents of engineering students' approaches to a WSP, (II) evaluate these approaches in relation to the normative context of education for sustainable development (ESD), and (III) identify relevant aspects of learning related to WSPs. Aim I is addressed through a phenomenographic study, while aims II and III are addressed by relating the results to research literature about human problem solving, sustainable development, and ESD. We describe four qualitatively different ways of approaching a specific WSP, as the outcome of the phenomenographic study: A. Simplify and avoid, B. Divide and control, C. Isolate and succumb, and D. Integrate and balance. We identify approach D as the most appropriate approach in the context of ESD, while A and C are not. On this basis, we identify three learning objectives related to students' abilities to address WSPs: learn to use a fully integrative approach, distinguish WSPs from tame and well-structured problems, and understand and consider the normative context of SD. Finally, we provide recommendations for how these learning objectives can be used to guide the design of science and engineering educational activities.

At the Crossroads of Learning and Culture: Identifying a Construct for Effective Computer-Assisted Language Learning for English Language Learners

ERIC Educational Resources Information Center

Shaw, Yun

2010-01-01

Many of the commercial Computer-Assisted Language Learning (CALL) programs available today typically take a generic approach. This approach standardizes the program so that it can be used to teach any language merely by translating the content from one language to another. These CALL programs rarely consider the cultural background or preferred…

Learning from Collaborative New Product Development Projects

ERIC Educational Resources Information Center

Kleinsmann, Maaike; Valkenburg, Rianne

2005-01-01

Purpose--In an empirical study learning opportunities were identified. Learning opportunities are enablers or disablers for the achievement of shared understanding. Design/methodology/approach--Actors were interviewed about their communication process. The learning history method was used to analyze and structure the data. From the learning…

Supporting Teachers in Identifying Students' Learning Styles in Learning Management Systems: An Automatic Student Modelling Approach

ERIC Educational Resources Information Center

Graf, Sabine; Kinshuk; Liu, Tzu-Chien

2009-01-01

In learning management systems (LMSs), teachers have more difficulties to notice and know how individual students behave and learn in a course, compared to face-to-face education. Enabling teachers to know their students' learning styles and making students aware of their own learning styles increases teachers' and students' understanding about…

Physician Educational Needs in Osteoporosis: An Approach to Needs Assessment.

ERIC Educational Resources Information Center

Lockyer, Jocelyn; Hanley, David; Fidler, Herta; Toews, John; Lysholm-Andrews, Elaine

1998-01-01

A literature review, focus groups (n=200), and questionnaire responses from 324 family physicians identified their learning needs related to osteoporosis. The three methods identified different learning issues, suggesting the importance of triangulation to ensure currency and relevance in continuing-education needs-assessment. (SK)

Designing a Teachable Agent System for Mathematics Learning

ERIC Educational Resources Information Center

Song, Donggil

2017-01-01

Learning-by-teaching has been identified as one of the more effective approaches to learning. Recently, educational researchers have investigated virtual environments in order to utilize the learning-by-teaching pedagogy. In a face-to-face learning-by-teaching situation, the role of the learners is to teach their peers or instructors. In virtual…

Models of Organizational Learning: Paradoxes and Best Practices in the Post Industrial Workplace.

ERIC Educational Resources Information Center

Laiken, Marilyn E.

A research project studied Canadian organizations that are using informal organizational learning approaches to embed ongoing learning within the actual work processes. Five organizations that self-identified as learning organizations at mature stages of development were studied in depth. No organization was a paragon of organizational learning.…

Use of after action reports (AARs) to promote organizational and systems learning in emergency preparedness.

PubMed

Savoia, Elena; Agboola, Foluso; Biddinger, Paul D

2012-08-01

Many public health and healthcare organizations use formal knowledge management practices to identify and disseminate the experiences gained over time. The "lessons-learned" approach is one such example of knowledge management practice applied to the wider concept of organizational learning. In the field of emergency preparedness, the lessons-learned approach stands on the assumption that learning from experience improves practice and minimizes avoidable deaths and negative economic and social consequences of disasters. In this project, we performed a structured review of AARs to analyze how lessons learned from the response to real-incidents may be used to maximize knowledge management and quality improvement practices such as the design of public health emergency preparedness (PHEP) exercises. We chose as a source of data the "Lessons Learned Information Sharing (LLIS.gov)" system, a joined program of the U.S. Department of Homeland Security DHS and FEMA that serves as the national, online repository of lessons learned, best practices, and innovative ideas. We identified recurring challenges reported by various states and local public health agencies in the response to different types of incidents. We also strove to identify the limitations of systematic learning that can be achieved due to existing weaknesses in the way AARs are developed.

Intergenerational Learning and Knowledge Transfer--Challenges and Opportunities

ERIC Educational Resources Information Center

Rupcic, Nataša

2018-01-01

Purpose: The purpose of this paper is to highlight challenges and opportunities that surround the process of intergenerational learning and knowledge transfer. Several options in this regard have been discussed from the managerial and employee perspective. Design/methodology/approach: The systems approach has been implemented to identify options…

Virtual Classroom: Reflections of Online Learning

ERIC Educational Resources Information Center

Michael, Kathy

2012-01-01

Purpose: The purpose of this study is to identify student and staff experiences with online learning at higher education (HE) using the software Elluminate Live! Design/methodology/approach: This paper adopts a qualitative approach, focusing on the reflections of participants (student and teacher) collated over a 12 month period of piloting online…

Investigating Task Design, Classroom Culture and Mathematics Learning: An Enactivist Approach

ERIC Educational Resources Information Center

Lozano, Maria-Dolores

2017-01-01

In this paper I introduce a methodological approach that can be useful for investigating relationships between mathematics tasks, mathematical classroom cultures and mathematics learning. This proposal responds to a need, identified in the literature, for "further research which uses alternative methods to understand student perspectives more…

Earthly Matters: Learning Occurs When You Hear the Grass Singing.

ERIC Educational Resources Information Center

Birt, Deborah; Krug, Don H.; Sheridan, Mary

1997-01-01

Discusses the actions and approaches advanced during the 1996 Summer Colloquium, "Art and Ecology: Interdisciplinary Approaches to the Curriculum." Illustrates how action-oriented inquiry makes learning relevant to all people through exploring the poetry of place. The colloquium identified community ecological issues that could be examined through…

RuleML-Based Learning Object Interoperability on the Semantic Web

ERIC Educational Resources Information Center

Biletskiy, Yevgen; Boley, Harold; Ranganathan, Girish R.

2008-01-01

Purpose: The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach: As proof of concept, a rule…

Organizational Learning of Higher Education Institutions: The Case of Estonia

ERIC Educational Resources Information Center

Voolaid, Karen; Ehrlich, Üllas

2017-01-01

Purpose: This paper aims to measure the organizational learning in two of Estonia's Higher Education Institutions (HEI) and identify connections between the organizational learning and various characteristics of HEI, such as ownership form and market participation rate. Design/methodology/approach: Watkins and Marsick's learning organization…

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.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

PubMed

Akkus, Zeynettin; Galimzianova, Alfiia; Hoogi, Assaf; Rubin, Daniel L; Erickson, Bradley J

2017-08-01

Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI. First we review the current deep learning architectures used for segmentation of anatomical brain structures and brain lesions. Next, the performance, speed, and properties of deep learning approaches are summarized and discussed. Finally, we provide a critical assessment of the current state and identify likely future developments and trends.

Internet-Mediated Learning in Public Affairs Programs: Issues and Implications.

ERIC Educational Resources Information Center

Rahm, Dianne; Reed, B. J.; Rydl, Teri L.

1999-01-01

An overview of Internet-mediated learning in public affairs programs identifies issues for faculty, students, and administrators, including intellectual property rights, instructional issues, learning approaches, student expectations, logistics and support, complexity of coordination, and organizational control. (DB)

Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

PubMed

Elahian, Bahareh; Yeasin, Mohammed; Mudigoudar, Basanagoud; Wheless, James W; Babajani-Feremi, Abbas

2017-10-01

Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ). We computed the PLV between the phase of the amplitude of high gamma activity (80-150Hz) and the phase of lower frequency rhythms (4-30Hz) from ECoG recordings obtained from 10 patients with epilepsy (21 seizures). We extracted five features from the PLV and used a machine learning approach based on logistic regression to build a model that classifies electrodes as SOZ or non-SOZ. More than 96% of electrodes identified as the SOZ by our algorithm were within the resected area in six seizure-free patients. In four non-seizure-free patients, more than 31% of the identified SOZ electrodes by our algorithm were outside the resected area. In addition, we observed that the seizure outcome in non-seizure-free patients correlated with the number of non-resected SOZ electrodes identified by our algorithm. This machine learning approach, based on features extracted from the PLV, effectively identified electrodes within the SOZ. The approach has the potential to assist clinicians in surgical decision-making when pre-surgical intracranial recordings are utilized. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

NASA Astrophysics Data System (ADS)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

Technologies That Capitalize on Study Skills with Learning Style Strengths

ERIC Educational Resources Information Center

Howell, Dusti D.

2008-01-01

This article addresses the tools available in the rapidly changing digital learning environment and offers a variety of approaches for how they can assist students with visual, auditory, or kinesthetic learning strengths. Teachers can use visual, auditory, and kinesthetic assessment tests to identify learning preferences and then recommend…

Context-Aware Recommender Systems for Learning: A Survey and Future Challenges

ERIC Educational Resources Information Center

Verbert, K.; Manouselis, N.; Ochoa, X.; Wolpers, M.; Drachsler, H.; Bosnic, I.; Duval, E.

2012-01-01

Recommender systems have been researched extensively by the Technology Enhanced Learning (TEL) community during the last decade. By identifying suitable resources from a potentially overwhelming variety of choices, such systems offer a promising approach to facilitate both learning and teaching tasks. As learning is taking place in extremely…

Learning Styles and Online Education

ERIC Educational Resources Information Center

Zapalska, Alina; Brozik, Dallas

2006-01-01

Purpose: The purpose of this paper is to recognize that individual learning styles must be taken into account in the instructional design template used in online education. The paper argues that when students' learning styles are identified, it is possible to define an appropriate context of learning. Design/methodology/approach: The paper…

A Review of Adventure Learning

ERIC Educational Resources Information Center

Veletsianos, George; Kleanthous, Irene

2009-01-01

Adventure learning (AL) is an approach for the design of digitally-enhanced teaching and learning environments driven by a framework of guidelines grounded on experiential and inquiry-based education. The purpose of this paper is to review the adventure learning literature and to describe the status quo of the practice by identifying the current…

NASA Space Mechanisms Handbook: Lessons Learned Documented

NASA Technical Reports Server (NTRS)

Fusaro, Robert L.

1999-01-01

The need to improve space mechanism reliability is underscored by a long history of flight failures and anomalies caused by malfunctioning mechanisms on spacecraft and launch vehicles. Some examples of these failures are listed in a table. Because much experience has been gained over the years, many specialized design practices have evolved and many unsatisfactory design approaches have been identified.NASA and the NASA Lewis Research Center conducted a Lessons Learned Study (refs. 1 and 2) and wrote a handbook to document what has been learned in the past. The primary goals of the handbook were to identify desirable and undesirable design practices for space mechanisms and to reduce the number of failures caused by the repetition of past design errors. Another goal was to identify a variety of design approaches for specific applications and to provide the associated considerations and caveats for each approach in an effort to help designers choose the approach most suitable for each application. This technical summary outlines the goals and objectives of the handbook and study as well as the contents of the handbook.

A Data Mining Approach to Improve Re-Accessibility and Delivery of Learning Knowledge Objects

ERIC Educational Resources Information Center

Sabitha, Sai; Mehrotra, Deepti; Bansal, Abhay

2014-01-01

Today Learning Management Systems (LMS) have become an integral part of learning mechanism of both learning institutes and industry. A Learning Object (LO) can be one of the atomic components of LMS. A large amount of research is conducted into identifying benchmarks for creating Learning Objects. Some of the major concerns associated with LO are…

Child-Led and Interest-Inspired Learning, Home Education, Learning Differences and the Impact of Regulation

ERIC Educational Resources Information Center

Liberto, Giuliana

2016-01-01

Research into the impact of non-consultative home education regulatory change in New South Wales (NSW), Australia, identified clear benefits of a child-led, interest-inspired approach to learning and a negative impact on student learning and well-being outcomes, particularly for learning-differenced children, of restricted practice freedom.…

Assessing Student Behaviors and Motivation for Actively Learning Biology

ERIC Educational Resources Information Center

Moore, Michael Edward

2017-01-01

Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is…

Use of After Action Reports (AARs) to Promote Organizational and Systems Learning in Emergency Preparedness

PubMed Central

Savoia, Elena; Agboola, Foluso; Biddinger, Paul D.

2012-01-01

Many public health and healthcare organizations use formal knowledge management practices to identify and disseminate the experiences gained over time. The “lessons-learned” approach is one such example of knowledge management practice applied to the wider concept of organizational learning. In the field of emergency preparedness, the lessons-learned approach stands on the assumption that learning from experience improves practice and minimizes avoidable deaths and negative economic and social consequences of disasters. In this project, we performed a structured review of AARs to analyze how lessons learned from the response to real-incidents may be used to maximize knowledge management and quality improvement practices such as the design of public health emergency preparedness (PHEP) exercises. We chose as a source of data the “Lessons Learned Information Sharing (LLIS.gov)” system, a joined program of the U.S. Department of Homeland Security DHS and FEMA that serves as the national, online repository of lessons learned, best practices, and innovative ideas. We identified recurring challenges reported by various states and local public health agencies in the response to different types of incidents. We also strived to identify the limitations of systematic learning that can be achieved due to existing weaknesses in the way AARs are developed. PMID:23066408

Adopting a blended learning approach to teaching evidence based medicine: a mixed methods study

PubMed Central

2013-01-01

Background Evidence Based Medicine (EBM) is a core unit delivered across many medical schools. Few studies have investigated the most effective method of teaching a course in EBM to medical students. The objective of this study was to identify whether a blended-learning approach to teaching EBM is more effective a didactic-based approach at increasing medical student competency in EBM. Methods A mixed-methods study was conducted consisting of a controlled trial and focus groups with second year graduate medical students. Students received the EBM course delivered using either a didactic approach (DID) to learning EBM or a blended-learning approach (BL). Student competency in EBM was assessed using the Berlin tool and a criterion-based assessment task, with student perceptions on the interventions assessed qualitatively. Results A total of 61 students (85.9%) participated in the study. Competency in EBM did not differ between the groups when assessed using the Berlin tool (p = 0.29). Students using the BL approach performed significantly better in one of the criterion-based assessment tasks (p = 0.01) and reported significantly higher self-perceived competence in critical appraisal skills. Qualitative analysis identified that students had a preference for the EBM course to be delivered using the BL approach. Conclusions Implementing a blended-learning approach to EBM teaching promotes greater student appreciation of EBM principles within the clinical setting. Integrating a variety of teaching modalities and approaches can increase student self-confidence and assist in bridging the gap between the theory and practice of EBM. PMID:24341502

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

Developing Higher Order Reading Comprehension Skills in the Learning Disabled Student: A Non-Basal Approach.

ERIC Educational Resources Information Center

Solomon, Sheila

This practicum study evaluated a non-basal, multidisciplinary, multisensory approach to teaching higher order reading comprehension skills to eight fifth-grade learning-disabled students from low socioeconomic minority group backgrounds. The four comprehension skills were: (1) identifying the main idea; (2) determining cause and effect; (3) making…

Landscape-scale carbon sampling strategy-lessons learned. Chapter 17

Treesearch

John B. Bradford; Peter Weishampel; Marie-Louise Smith; Randall Kolka; David Y. Hollinger; Richard A. Birdsey; Scott Ollinger; Michael Ryan

2008-01-01

Previous chapters examined individual processes relevant to forest carbon cycling, and characterized measurement approaches for understanding those processes at landscape scales. In this final chapter, we address our overall approach to understanding forest carbon dynamics over large areas. Our objective is to identify any lessons that we learned in the course of...

Investigating Research Approaches: Classroom-Based Interaction Studies in Physical and Virtual Contexts

ERIC Educational Resources Information Center

Hartwick, Peggy

2018-01-01

This article investigates research approaches used in traditional classroom-based interaction studies for identifying a suitable research method for studies in three-dimensional virtual learning environments (3DVLEs). As opportunities for language learning and teaching in virtual worlds emerge, so too do new research questions. An understanding of…

Investigating the Relationships between Approaches to Learning, Learner Identities and Academic Achievement in Higher Education

ERIC Educational Resources Information Center

Herrmann, K. J.; Bager-Elsborg, A.; McCune, V.

2017-01-01

This paper considers relationships between approaches to learning, learner identities, self-efficacy beliefs and academic achievement in higher education. In addition to already established survey instruments, a new scale, "subject area affinity," was developed. The scale explores the extent to which students identify with their area of…

[Learning during the early clinical years takes more than good study habits: Perceptions of students and teachers].

PubMed

Zúñiga, Denisse; Leiva, Isabel; Calderón, Maribel; Tomicic, Alemka; Padilla, Oslando; Riquelme, Arnoldo; Bitran, Marcela

2015-11-01

Teaching methods of the undergraduate medical curriculum change considerably from the first years to clinical training. Clinical learning occurs in complex and varied scenarios while caring for patients. Students have to adapt their learning approaches and strategies to be able to integrate theory and clinical practice and become experiential learners. To identify the strategies used by medical students to learn during the initial clinical years, as reported by students themselves and by their clinical tutors. We performed eight focus group discussions with 54 students enrolled in years three to six and we interviewed eight clinical tutors. Both focus group discussions and interviews were audio recorded, transcribed and analyzed according to Grounded Theory. Four main themes were identified in the discourse of both students and tutors: Strategies oriented to theoretical learning, strategies oriented to experiential learning, strategies for integrating theory and practice and strategies oriented to evaluation. The mentioning of individual differences was present across the reports of both students and tutors. Students use a rich variety of strategies to face the challenges of clinical learning. Both students and tutors recognize that the learning approaches and strategies vary according the nature of the task and individual differences. The responses of students bring particular knowledge of the approaches used for the theoretical and practical integration and delve into the social dimension of learning.

Conceptualising Teachers' Professional Learning with Web 2.0

ERIC Educational Resources Information Center

Burden, Kevin John

2010-01-01

Purpose: This paper seeks to identify and develop an exploratory framework for conceptualising how teachers might use the affordances of Web 2.0 technologies to support their own professional learning. Design/methodology/approach: The paper draws on a large corpus of literature and recent research evidence to identify the principal elements and…

The Australian Collaborative Education Network Student Scholarship for Work-Integrated Learning 2010-2014

ERIC Educational Resources Information Center

Moore, Keri; Ferns, Sonia; Peach, Deborah

2015-01-01

The increasing emphasis on embedding work-integrated learning (WIL) in the higher education curriculum has impacted on teaching and learning approaches. While the benefits of incorporating experiential learning in the student experience are recognized by all stakeholders, additional costs incurred by students have not been identified. At the same…

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…

Change In(ter)Ventions to Organizational Learning: Bravo to Leaders as Unifying Agents

ERIC Educational Resources Information Center

Yeo, Roland K.

2007-01-01

Purpose: The purpose of this research is to examine the relationship between change interventions and organizational learning. It seeks to identify the process through which team learning is developed, the factors that affect organizational learning and its influences on organizational effectiveness. Design/methodology/approach: Two groups of…

Pratique d'apprentissage en ligne aux etudes superieures (Online Learning for Higher Education).

ERIC Educational Resources Information Center

Marchand, Louise

2001-01-01

Online learning requires new approaches to teaching and learning. At the University of Montreal, 28 graduate students in education and adult students specializing in educational technology attended an experimental distance education course. Students identified advantages and disadvantages of online learning/teaching and reflected on how the course…

Exploring Diversity of Learning Outcomes in E-Learning Courses: Results of a Qualitative Study in a French Multinational Company

ERIC Educational Resources Information Center

Baudoin, Emmanuel

2010-01-01

The implementation of e-learning by companies in France is ongoing. One of their issues is to improve the learning experience of their employees. From our point of view, this implies that they must better understand the learning experience of the employees. This paper suggests a qualitative approach to learning in order to identify the diversity…

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

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.

Identifying well-formed biomedical phrases in MEDLINE® text.

PubMed

Kim, Won; Yeganova, Lana; Comeau, Donald C; Wilbur, W John

2012-12-01

In the modern world people frequently interact with retrieval systems to satisfy their information needs. Humanly understandable well-formed phrases represent a crucial interface between humans and the web, and the ability to index and search with such phrases is beneficial for human-web interactions. In this paper we consider the problem of identifying humanly understandable, well formed, and high quality biomedical phrases in MEDLINE documents. The main approaches used previously for detecting such phrases are syntactic, statistical, and a hybrid approach combining these two. In this paper we propose a supervised learning approach for identifying high quality phrases. First we obtain a set of known well-formed useful phrases from an existing source and label these phrases as positive. We then extract from MEDLINE a large set of multiword strings that do not contain stop words or punctuation. We believe this unlabeled set contains many well-formed phrases. Our goal is to identify these additional high quality phrases. We examine various feature combinations and several machine learning strategies designed to solve this problem. A proper choice of machine learning methods and features identifies in the large collection strings that are likely to be high quality phrases. We evaluate our approach by making human judgments on multiword strings extracted from MEDLINE using our methods. We find that over 85% of such extracted phrase candidates are humanly judged to be of high quality. Published by Elsevier Inc.

Personality, Organizational Orientations and Self-Reported Learning Outcomes

ERIC Educational Resources Information Center

Bamber, David; Castka, Pavel

2006-01-01

Purpose: To identify competencies connecting personality, organizational orientations and self-reported learning outcomes (as measured by concise Likert-type scales), for individuals who are learning for their organizations. Design/methodology/approach: Five concise factor scales were constructed to represent aspects of personality. Three further…

Facilitating Organizational Learning in the Russian Business Context

ERIC Educational Resources Information Center

Molodchik, Mariia; Jardon, Carlos

2015-01-01

Purpose: The paper aims to identify particular traits of the Russian context which condition two key enablers of organizational learning--organizational culture and transformational leadership. Design/methodology/approach: Drawing on a literature review, the study determines management challenges by implementation of organizational learning in the…

Student nurses' experiences of using a learning contract as a method of assessment.

PubMed

Bailey, Maria E; Tuohy, Dympna

2009-10-01

The purpose of this study was to describe final year undergraduate nurses' experiences of assessment through the use of a learning contract. Using a qualitative descriptive design, data was collected from a purposive sample of final (fourth) year undergraduate student nurses. Two approaches were taken for data collection, anonymous evaluative questionnaires and interviews. The study was approved by the local university research and ethics committee. Data was thematically analysed. This article presents and discusses the findings from the interviews. Findings suggest that students' approach to the assessment strategy influenced engagement with the learning contract. Three themes were identified: skills, perceptions, and actions. Within these themes three types of learner were identified: happy, pragmatic and fearful. Factors found to influence successful completion of the learning contract were: support, relevant skills, prior experiential learning and required theoretical knowledge. Recommendations include the need for educators to consider module assessments that recognise the learning needs and preferences of the student within a supportive environment.

Critical steps in learning from incidents: using learning potential in the process from reporting an incident to accident prevention.

PubMed

Drupsteen, Linda; Groeneweg, Jop; Zwetsloot, Gerard I J M

2013-01-01

Many incidents have occurred because organisations have failed to learn from lessons of the past. This means that there is room for improvement in the way organisations analyse incidents, generate measures to remedy identified weaknesses and prevent reoccurrence: the learning from incidents process. To improve that process, it is necessary to gain insight into the steps of this process and to identify factors that hinder learning (bottlenecks). This paper presents a model that enables organisations to analyse the steps in a learning from incidents process and to identify the bottlenecks. The study describes how this model is used in a survey and in 3 exploratory case studies in The Netherlands. The results show that there is limited use of learning potential, especially in the evaluation stage. To improve learning, an approach that considers all steps is necessary.

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.

Social Justice, Children's Needs and Rights: An Approach to Planning

ERIC Educational Resources Information Center

Sims, Margaret

2015-01-01

Commonly, planning for children involves comparing what they know against a curriculum or learning framework which identifies what they should know. Early childhood educators are then expected to create learning opportunities to help fill the gap between these two extremes. In this paper I argue that such an approach does not honour the…

Do Students' Approaches to Learning Affect Their Perceptions of Using Computing and Information Technology?

ERIC Educational Resources Information Center

Jelfs, Anne; Colbourn, Chris

2002-01-01

Discusses the use of communication and information technology (C&IT) in higher education in the United Kingdom and describes research that examined student perceptions of using C&IT for a virtual seminar series in psychology. Identified student learning approaches within the group and how it affected their adoption or rejection of the…

A Systematic Approach to Faculty Development toward Improved Capability in Tertiary Teaching in a Blended Learning Environment

ERIC Educational Resources Information Center

Badawood, Ashraf Mohammad

2011-01-01

The blended learning (BL) approach provides an efficient and effective instructional experience. However, adopting BL poses some challenge to faculty; the most important obstacle found in this research is faculty's lack of knowledge regarding the use of technology in their teaching. This challenge prompted the researcher to identify a solution…

Discrepancy Approaches for Identifying Learning Disabilities. Quick Turn Around (QTA).

ERIC Educational Resources Information Center

Schrag, Judy A.

A study reviewed recent trends, issues, and changes within the states related to the use of discrepancy formulas and other approaches for determining eligibility of students with learning disabilities (LD) for special education and related services. A survey of the 50 states and the District of Columbia found they all have a statement in their…

Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems.

PubMed

Cheng, Ching-An; Huang, Han-Pang

2016-12-01

We study the modeling of Lagrangian systems with multiple degrees of freedom. Based on system dynamics, canonical parametric models require ad hoc derivations and sometimes simplification for a computable solution; on the other hand, due to the lack of prior knowledge in the system's structure, modern nonparametric models in machine learning face the curse of dimensionality, especially in learning large systems. In this paper, we bridge this gap by unifying the theories of Lagrangian systems and vector-valued reproducing kernel Hilbert space. We reformulate Lagrangian systems with kernels that embed the governing Euler-Lagrange equation-the Lagrangian kernels-and show that these kernels span a subspace capturing the Lagrangian's projection as inverse dynamics. By such property, our model uses only inputs and outputs as in machine learning and inherits the structured form as in system dynamics, thereby removing the need for the mundane derivations for new systems as well as the generalization problem in learning from scratches. In effect, it learns the system's Lagrangian, a simpler task than directly learning the dynamics. To demonstrate, we applied the proposed kernel to identify the robot inverse dynamics in simulations and experiments. Our results present a competitive novel approach to identifying Lagrangian systems, despite using only inputs and outputs.

University students' achievement goals and approaches to learning in mathematics.

PubMed

Cano, Francisco; Berbén, A B G

2009-03-01

Achievement goals (AG) and students' approaches to learning (SAL) are two research perspectives on student motivation and learning in higher education that have until now been pursued quite independently. This study sets out: (a) to explore the relationship between the most representative variables of SAL and AG; (b) to identify subgroups (clusters) of students with multiple AG; and (c) to examine the differences between these clusters with respect to various SAL and AG characteristics. The participants were 680 male and female 1st year university students studying different subjects (e.g. mathematics, physics, economics) but all enrolled on mathematics courses (e.g. algebra, calculus). Participants completed a series of questionnaires that measured their conceptions of mathematics, approaches to learning, course experience, personal 2 x 2 AG, and perceived AG. SAL and AG variables were moderately associated and related to both the way students perceived their academic environment and the way they conceived of the nature of mathematics (i.e. the perceptual-cognitive framework). Four clusters of students with distinctive multiple AG were identified and when the differences between clusters were analysed, we were able to attribute them to various constructs including perceptual-cognitive framework, learning approaches, and academic performance. This study reveals a consistent pattern of relationships between SAL and AG perspectives across different methods of analysis, supports the relevance of the 2 x 2 AG framework in a mathematics learning context and suggests that AG and SAL may be intertwined aspects of students' experience of learning mathematics at university.

The Impact of Cognitive Dissonance on Learning Work Behavior

ERIC Educational Resources Information Center

Dechawatanapaisal, Decha; Siengthai, Sununta

2006-01-01

Purpose: This research proposes a framework, which identifies the underlying factors that shape learning behavior in the workplace. It takes organizational members' perspectives into consideration to gain better understanding on managing people and their behavior in the organizational learning process. Design/methodology/approach: Primary data…

Online Learning Programs: Evaluation's Challenging Future

ERIC Educational Resources Information Center

Nord, Derek

2011-01-01

With the vast array of contextual factors, pedagogical approaches, models of implementation, and purposes of education and training related to online learning, educators, learners, and the general public alike are seeking answers regarding utility and effectiveness of online learning. This article identifies and responds to many of the challenges…

A New Approach to Group Learning

ERIC Educational Resources Information Center

Parsons, Jerry

1976-01-01

To help teachers plan strategy for working with a learning group, 12 factors affecting a learning group are discussed and a series of check points are identified as criteria for evaluation. Concepts and principles of group dynamics are drawn from sociology and the work of Carl Rogers. (Author/AJ)

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

PubMed

Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T; Wu, Joy T; Welt, Jonathan; Foote, John; Moseley, Edward T; Grant, David W; Tyler, Patrick D; Celi, Leo A

2018-01-01

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

PubMed

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Implementing a strategy to promote lifelong learning in the primary care workforce: an evaluation of leadership roles, change management approaches, interim challenges and achievements.

PubMed

McLaren, Susan; Woods, Leslie; Boudioni, Markella; Lemma, Ferew; Tavabie, Abdol

2008-01-01

To identify and explore leadership roles and responsibilities for implementing the workforce development strategy; to identify approaches used to implement and disseminate the strategy; and to identify and explore challenges and achievements in the first 18 months following implementation. A formative evaluation with qualitative methods was used. Documentary analysis, interviews (n = 29) and two focus groups (n = 12) were conducted with a purposive sample of individuals responsible for strategy implementation. Data were transcribed and analysed thematically using framework analysis. Regional health area in Kent, Surrey and Sussex: 24 primary care trusts (PCTs) and 900 general practices. Primary care workforce tutors, lifelong learning advisors, GP tutors, patch associate GP deans and chairs of PCT education committees all had vital leadership roles, some existing and others newly developed. Approaches used to implement the strategy encompassed working within and across organisational boundaries, communication and dissemination of information. Challenges encountered by implementers were resistance to change - evident in some negative attitudes to uptake of training and development opportunities - and role diversity and influence. Achievements included successes in embedding appraisal and protected learning time, and changes in educational practices and services. The use of key leadership roles and change-management approaches had brought about early indications of positive transition in lifelong learning cultures.

Faculty Perspectives on the Inclusion of Work-Related Learning in Engineering Curricula

ERIC Educational Resources Information Center

Magnell, Marie; Geschwind, Lars; Kolmos, Anette

2017-01-01

The purpose of this paper is to identify faculty perspectives on the integration of work-related issues in engineering education. A mixed methods approach was used to explore faculty attitudes towards work-related learning, to describe activities related to working life that have been introduced into the curriculum and to identify factors that…

Indicators of Effective Student Learning in English Composition. A Review of the Literature.

ERIC Educational Resources Information Center

Ratcliff, Gary R.

Based on a literature review, this paper proposes an approach to identifying indicators of learning for English composition courses at the college level. Section 1 provides a rationale for using curricular artifacts as a means to identify indicators. Section 2 describes the proposed taxonomy of model indicators and its framework which uses the…

Learning Characteristics of Small Business Managers: Principles for Training

ERIC Educational Resources Information Center

Jeffrey, Lynn M.; Hide, Sophie; Legg, Stephen

2010-01-01

Purpose: This paper aims to report on the second half of a two-part study that identified relevant content for safety audit training in small businesses. The specific aim of the paper is to determine the preferred learning styles and approaches of managers in these businesses in order to identify some principles which could be used to tailor…

A Peer Coaching-Based Professional Development Approach to Improving the Learning Participation and Learning Design Skills of In-Service Teachers

ERIC Educational Resources Information Center

Ma, Ning; Xin, Shuang; Du, Jia-Yuan

2018-01-01

Personalized learning based on learning analytics has become increasingly important for teachers' development via providing adaptive contents and strategies for teachers by identifying their questions and needs. Currently, most studies on teachers' professional development focus on pre-service teachers, and studies on teachers' personalized…

The "Organization" as an Interdisciplinary Learning Zone: Using a Strategic Game to Integrate Learning about Supply Chain Management and Advertising

ERIC Educational Resources Information Center

Arora, Anshu Saxena

2012-01-01

Purpose: The research study seeks to explore the relationship among strategic gaming, the learning organization model and approach, and transfer of learning as key success strategies for improved individual and organizational performance and sustainable competitive advantage. This research aims to identify and elaborate on the strategic…

Students' Experiences of Blended Learning in Accounting Education at the Durban University of Technology

ERIC Educational Resources Information Center

Hiralaal, A.

2012-01-01

The Durban University of Technology guided by the Higher Education Qualifications Framework (HEQC) identified e-learning as one of their objectives in the curriculum renewal process. To explore the impact of e-learning, blended learning, a combination of online and face-to-face interaction was implemented as a teaching approach in Accounting…

Learning Outcomes and Processes in Massively Multiplayer Online Games: Exploring the Perceptions of Players

ERIC Educational Resources Information Center

Voulgari, Iro; Komis, Vassilis; Sampson, Demetrios G.

2014-01-01

Over the past decade research has recognised the learning potential of massively multiplayer online games (MMOGs). MMOGs can be used by the technology-enhanced learning research community to study and identify good educational practices that may inspire engaging, creative and motivating approaches for education and learning. To this end, in this…

A Planning Tool for Incorporating Backward Design, Active Learning, and Authentic Assessment in the College Classroom

ERIC Educational Resources Information Center

Reynolds, Heather L.; Kearns, Katherine Dowell

2017-01-01

Backward course design is a compelling strategy for achieving results-based, student-centered learning. The backward course-design approach is first to identify student-learning outcomes, then the means of assessing the outcomes, and lastly the classroom activities that would support the learning outcomes. With demonstrated success at improving…

Doing Dissections Differently: A Structured, Peer-Assisted Learning Approach to Maximizing Learning in Dissections

ERIC Educational Resources Information Center

Hall, Emma R.; Davis, Rachel C.; Weller, Renate; Powney, Sonya; Williams, Sarah B.

2013-01-01

Areas of difficulty faced by our veterinary medicine students, with respect to their learning in dissection classes, were identified. These challenges were both general adult-learning related and specific to the discipline of anatomy. Our aim was to design, implement, and evaluate a modified reciprocal peer-assisted/team-based learning…

Per-service supervised learning for identifying desired WoT apps from user requests in natural language

PubMed Central

2017-01-01

Web of Things (WoT) platforms are growing fast so as the needs for composing WoT apps more easily and efficiently. We have recently commenced the campaign to develop an interface where users can issue requests for WoT apps entirely in natural language. This requires an effort to build a system that can learn to identify relevant WoT functions that fulfill user’s requests. In our preceding work, we trained a supervised learning system with thousands of publicly-available IFTTT app recipes based on conditional random fields (CRF). However, the sub-par accuracy and excessive training time motivated us to devise a better approach. In this paper, we present a novel solution that creates a separate learning engine for each trigger service. With this approach, parallel and incremental learning becomes possible. For inference, our system first identifies the most relevant trigger service for a given user request by using an information retrieval technique. Then, the learning engine associated with the trigger service predicts the most likely pair of trigger and action functions. We expect that such two-phase inference method given parallel learning engines would improve the accuracy of identifying related WoT functions. We verify our new solution through the empirical evaluation with training and test sets sampled from a pool of refined IFTTT app recipes. We also meticulously analyze the characteristics of the recipes to find future research directions. PMID:29149217

Per-service supervised learning for identifying desired WoT apps from user requests in natural language.

PubMed

Yoon, Young

2017-01-01

Web of Things (WoT) platforms are growing fast so as the needs for composing WoT apps more easily and efficiently. We have recently commenced the campaign to develop an interface where users can issue requests for WoT apps entirely in natural language. This requires an effort to build a system that can learn to identify relevant WoT functions that fulfill user's requests. In our preceding work, we trained a supervised learning system with thousands of publicly-available IFTTT app recipes based on conditional random fields (CRF). However, the sub-par accuracy and excessive training time motivated us to devise a better approach. In this paper, we present a novel solution that creates a separate learning engine for each trigger service. With this approach, parallel and incremental learning becomes possible. For inference, our system first identifies the most relevant trigger service for a given user request by using an information retrieval technique. Then, the learning engine associated with the trigger service predicts the most likely pair of trigger and action functions. We expect that such two-phase inference method given parallel learning engines would improve the accuracy of identifying related WoT functions. We verify our new solution through the empirical evaluation with training and test sets sampled from a pool of refined IFTTT app recipes. We also meticulously analyze the characteristics of the recipes to find future research directions.

A Systematic Review Protocol on the Use of Online Learning versus Blended Learning for Teaching Clinical Skills to Undergraduate Health Professional Students

ERIC Educational Resources Information Center

McCutcheon, Karen; Lohan, Maria; Traynor, Marian

2016-01-01

Aim: This paper is a review protocol that will be used to identify, critically appraise and synthesise the best current evidence relating to the use of online learning and blended learning approaches in teaching clinical skills in undergraduate health professionals. Background: Although previous systematic reviews on online learning vs. face to…

How to Identify E-Learning Trends in Academic Teaching: Methodological Approaches and the Analysis of Scientific Discourses

ERIC Educational Resources Information Center

Fischer, Helge; Heise, Linda; Heinz, Matthias; Moebius, Kathrin; Koehler, Thomas

2015-01-01

Purpose: The purpose of this paper is to introduce methodology and findings of a trend study in the field of e-learning. The overall interest of the study was the analysis of scientific e-learning discourses. What comes next in the field of academic e-learning? Which e-learning trends dominate the discourse at universities? Answering such…

Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

PubMed

Ammenwerth, Elske; Hackl, Werner O

2017-01-01

Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

E-Learning: Ageing Workforce versus Technology-Savvy Generation

ERIC Educational Resources Information Center

Becker, Karen; Fleming, Julie; Keijsers, Wilhelmina

2012-01-01

Purpose: The purpose of this paper is to provide description and analysis of how a traditional industry is currently using e-learning, and to identify how the potential of e-learning can be realised whilst acknowledging the technological divide between younger and older workers. Design/methodology/approach: An exploratory qualitative methodology…

Enhancing Digital Literacy and Learning among Adults with Blogs

ERIC Educational Resources Information Center

Sharp, Laurie A.

2017-01-01

Digital literacy and learning among adults has been identified as an area requiring research. The purpose of the present study was to explore technology acceptance and digital collaborative learning experiences with blogs among adult learners. This analysis employed a quasi-experimental mixed-methods approach guided by a sociocultural theoretical…

Evaluating Observational Learning in a Competitive Two-Sided Crowdsourcing Market: A Bayesian Inferential Approach

ERIC Educational Resources Information Center

Ayaburi, Emmanuel Wusuhon Yanibo

2017-01-01

This dissertation investigates the effect of observational learning in crowdsourcing markets as a lens to identify appropriate mechanism(s) for sustaining this increasingly popular business model. Observational learning occurs when crowdsourcing participating agents obtain knowledge from signals they observe in the marketplace and incorporate such…

Teaching and Learning Entrepreneurship for Micro and Small Businesses in the Cultural Industries Sector.

ERIC Educational Resources Information Center

Raffo, Carlo; Lovatt, Andy; Banks, Mark; O'Connor, Justin

2000-01-01

A study of 50 entrepreneurs in small businesses (fashion design, entertainment, new media) identified factors that helped them learn and develop their business, especially situated learning, networking, and mentoring. Similar naturalistic approaches are recommended for further and higher education focused on entrepreneurship. (SK)

Mobile Collaborative Language Learning: State of the Art

ERIC Educational Resources Information Center

Kukulska-Hulme, Agnes; Viberg, Olga

2018-01-01

This paper presents a review of mobile collaborative language learning studies published in 2012-16 with the aim to improve understanding of how mobile technologies have been used to support collaborative learning among second and foreign language students. We identify affordances, general pedagogical approaches, second- and foreign-language…

Effective Spelling Instruction for Students with Learning Disabilities

ERIC Educational Resources Information Center

Sayeski, Kristin L.

2011-01-01

Difficulty with spelling is a perennial challenge for students with learning disabilities. Several decades of research, however, have identified both fundamental linguistic concepts and instructional approaches that, when understood by a teacher, can be applied to teach students with learning disabilities to spell. In this article, a brief history…

Learning Organization and Transfer: Strategies for Improving Performance

ERIC Educational Resources Information Center

Weldy, Teresa G.

2009-01-01

Purpose: This study aims to explore a relationship between the learning organization and transfer of training as strategies for learning and managing knowledge to make performance improvements and gain or maintain a competitive advantage. Design/methodology/approach: Various similarities are identified in the literature that are indicative of a…

Learning about Health

ERIC Educational Resources Information Center

Geertshuis, Susan; Cooper-Thomas, Helena

2011-01-01

This paper examines the extent of patients' health-related learning from a range of sources and aims to identify psycho-cognitive variables that predict learning. Using a survey design, we found that people higher in perceived health competence were lower in anxiety and took a more logical approach to decision making. Low perceived health…

Strategic HRD Practices as Key Factors in Organizational Learning

ERIC Educational Resources Information Center

Tseng, Chien-Chi; McLean, Gary N.

2008-01-01

Purpose: The purpose of this paper is to explore the relationships among strategic HRD (SHRD) practices and organizational learning; and the relationships among organizational learning and HRD outcomes through a literature review. Design/methodology/approach: Keywords were identified to use in the literature search: HRD, SHRD practices, and…

The Association between Learning Styles and Perception of Teaching Quality

ERIC Educational Resources Information Center

Jepsen, Denise M.; Varhegyi, Melinda M.; Teo, Stephen T. T.

2015-01-01

Purpose: Although learning styles and teaching quality have been studied separately, the association between the association between the two has yet to be identified. The purpose of this paper is to establish the relationship between students' learning styles with students' perceptions of teaching quality. Design/methodology/approach: The study…

Approaches to the Management of Large Classes. Lancaster-Leeds Language Learning in Large Classes Research Project. Report, No. 11.

ERIC Educational Resources Information Center

Coleman, Hywel

Various approaches to the management of large classes identified in the literature are categorized, with information drawn especially from earlier findings of the Lancaster-Leeds Language Learning in Large Classes Research Project. The discussion makes use of sources appearing during the last 150 years, but emphasizes the period since 1960. Three…

Interprofessional practice and learning in a youth mental health service: A case study using network analysis.

PubMed

Barnett, Tony; Hoang, Ha; Cross, Merylin; Bridgman, Heather

2015-01-01

Few studies have examined interprofessional practice (IPP) from a mental health service perspective. This study applied a mixed-method approach to examine the IPP and learning occurring in a youth mental health service in Tasmania, Australia. The aims of the study were to investigate the extent to which staff were networked, how collaboratively they practiced and supported student learning, and to elicit the organisation's strengths and opportunities regarding IPP and learning. Six data sets were collected: pre- and post-test readiness for interprofessional learning surveys, Social Network survey, organisational readiness for IPP and learning checklist, "talking wall" role clarification activity, and observations of participants working through a clinical case study. Participants (n = 19) were well-networked and demonstrated a patient-centred approach. Results confirmed participants' positive attitudes to IPP and learning and identified ways to strengthen the organisation's interprofessional capability. This mixed-method approach could assist others to investigate IPP and learning.

Machine-Learning Approach for Design of Nanomagnetic-Based Antennas

NASA Astrophysics Data System (ADS)

Gianfagna, Carmine; Yu, Huan; Swaminathan, Madhavan; Pulugurtha, Raj; Tummala, Rao; Antonini, Giulio

2017-08-01

We propose a machine-learning approach for design of planar inverted-F antennas with a magneto-dielectric nanocomposite substrate. It is shown that machine-learning techniques can be efficiently used to characterize nanomagnetic-based antennas by accurately mapping the particle radius and volume fraction of the nanomagnetic material to antenna parameters such as gain, bandwidth, radiation efficiency, and resonant frequency. A modified mixing rule model is also presented. In addition, the inverse problem is addressed through machine learning as well, where given the antenna parameters, the corresponding design space of possible material parameters is identified.

Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

PubMed

Grouin, Cyril; Zweigenbaum, Pierre

2013-01-01

In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

PubMed

Pound, Michael P; Atkinson, Jonathan A; Townsend, Alexandra J; Wilson, Michael H; Griffiths, Marcus; Jackson, Aaron S; Bulat, Adrian; Tzimiropoulos, Georgios; Wells, Darren M; Murchie, Erik H; Pridmore, Tony P; French, Andrew P

2017-10-01

In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation for finding a fully automated approach. Deep learning is an emerging field that promises unparalleled results on many data analysis problems. Building on artificial neural networks, deep approaches have many more hidden layers in the network, and hence have greater discriminative and predictive power. We demonstrate the use of such approaches as part of a plant phenotyping pipeline. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping and demonstrate state-of-the-art results (>97% accuracy) for root and shoot feature identification and localization. We use fully automated trait identification using deep learning to identify quantitative trait loci in root architecture datasets. The majority (12 out of 14) of manually identified quantitative trait loci were also discovered using our automated approach based on deep learning detection to locate plant features. We have shown deep learning-based phenotyping to have very good detection and localization accuracy in validation and testing image sets. We have shown that such features can be used to derive meaningful biological traits, which in turn can be used in quantitative trait loci discovery pipelines. This process can be completely automated. We predict a paradigm shift in image-based phenotyping bought about by such deep learning approaches, given sufficient training sets. © The Authors 2017. Published by Oxford University Press.

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.

Paid Educational Leave and Self-Directed Learning: Implications for Legislation on the Learning Leave Scheme in South Korea

ERIC Educational Resources Information Center

Oh, Jeong Rok; Park, Cho Hyun; Jo, Sung Jun

2016-01-01

Purpose: The purposes of this study are to explore paid educational leave (PEL), self-directed learning (SDL) and the relationship between them; and to identify the implications for legislation on the learning leave scheme in South Korea. Design/Methodology/Approach: The research method of the study is a literature review. Articles were identified…

Learning Styles Inequity for Small to Micro Firms (SMFs): Social Exclusion through Work-Based E-Learning Practice in Europe

ERIC Educational Resources Information Center

Hardaker, Glenn; Dockery, Richard; Sabki, Aishah

2007-01-01

Purpose: The elearn2work study of learning styles in the context of small to micro firms' (SMFs) and their perceived satisfaction has identified some important finding specific to e-learning content design, delivery and international standards development. Design/methodology/approach: The method of research adopts a deductive rather than an…

Organisational Learning Approaches to School Leadership and Management: Teachers' Values and Perceptions of Practice

ERIC Educational Resources Information Center

Pedder, David; MacBeath, John

2008-01-01

In this article, we report results of a survey of 1,397 teachers in 26 primary and 17 secondary schools in England as part of the Learning How to Learn project. We consider how school self-evaluation can be understood within an organisational learning frame. Factor analysis of teachers' responses helped us identify 4 dimensions of organisational…

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.

Integrated Learning Systems: A Primer.

ERIC Educational Resources Information Center

Wilson, Judy

1990-01-01

An overview of integrated learning systems (ILS) is provided. Twelve companies marketing products under the term ILS are identified. Philosophical approaches, curriculum areas, management systems, costs, and company stability are discussed as important considerations for schools considering these companies. (CW)

Identifying key areas for active interprofessional learning partnerships: A facilitated dialogue.

PubMed

Steven, Kathryn; Angus, Allyson; Breckenridge, Jenna; Davey, Peter; Tully, Vicki; Muir, Fiona

2016-11-01

Student and service user involvement is recognised as an important factor in creating interprofessional education (IPE) opportunities. We used a team-based learning approach to bring together undergraduate health professional students, early career professionals (ECPs), public partners, volunteers, and carers to explore learning partnerships. Influenced by evaluative inquiry, this qualitative study used a free text response to allow participants to give their own opinion. A total of 153 participants (50 public partners and 103 students and professionals representing 11 healthcare professions) took part. Participants were divided into mixed groups of six (n = 25) and asked to identify areas where students, professionals, and public could work together to improve health professional education. Each group documented their discussions by summarising agreed areas and next steps. Responses were collected and transcribed for inductive content analysis. Seven key themes (areas for joint working) were identified: communication, public as partners, standards of conduct, IPE, quality improvement, education, and learning environments. The team-based learning format enabled undergraduate and postgraduate health professionals to achieve consensus with public partners on areas for IPE and collaboration. Some of our results may be context-specific but the approach is generalisable to other areas.

The efficacy of student-centered instruction in supporting science learning.

PubMed

Granger, E M; Bevis, T H; Saka, Y; Southerland, S A; Sampson, V; Tate, R L

2012-10-05

Transforming science learning through student-centered instruction that engages students in a variety of scientific practices is central to national science-teaching reform efforts. Our study employed a large-scale, randomized-cluster experimental design to compare the effects of student-centered and teacher-centered approaches on elementary school students' understanding of space-science concepts. Data included measures of student characteristics and learning and teacher characteristics and fidelity to the instructional approach. Results reveal that learning outcomes were higher for students enrolled in classrooms engaging in scientific practices through a student-centered approach; two moderators were identified. A statistical search for potential causal mechanisms for the observed outcomes uncovered two potential mediators: students' understanding of models and evidence and the self-efficacy of teachers.

Scalable Iterative Classification for Sanitizing Large-Scale Datasets

PubMed Central

Li, Bo; Vorobeychik, Yevgeniy; Li, Muqun; Malin, Bradley

2017-01-01

Cheap ubiquitous computing enables the collection of massive amounts of personal data in a wide variety of domains. Many organizations aim to share such data while obscuring features that could disclose personally identifiable information. Much of this data exhibits weak structure (e.g., text), such that machine learning approaches have been developed to detect and remove identifiers from it. While learning is never perfect, and relying on such approaches to sanitize data can leak sensitive information, a small risk is often acceptable. Our goal is to balance the value of published data and the risk of an adversary discovering leaked identifiers. We model data sanitization as a game between 1) a publisher who chooses a set of classifiers to apply to data and publishes only instances predicted as non-sensitive and 2) an attacker who combines machine learning and manual inspection to uncover leaked identifying information. We introduce a fast iterative greedy algorithm for the publisher that ensures a low utility for a resource-limited adversary. Moreover, using five text data sets we illustrate that our algorithm leaves virtually no automatically identifiable sensitive instances for a state-of-the-art learning algorithm, while sharing over 93% of the original data, and completes after at most 5 iterations. PMID:28943741

Towards tailored teaching: using participatory action research to enhance the learning experience of Longitudinal Integrated Clerkship students in a South African rural district hospital.

PubMed

von Pressentin, Klaus B; Waggie, Firdouza; Conradie, Hoffie

2016-03-08

The introduction of Stellenbosch University's Longitudinal Integrated Clerkship (LIC) model as part of the undergraduate medical curriculum offers a unique and exciting training model to develop generalist doctors for the changing South African health landscape. At one of these LIC sites, the need for an improvement of the local learning experience became evident. This paper explores how to identify and implement a tailored teaching and learning intervention to improve workplace-based learning for LIC students. A participatory action research approach was used in a co-operative inquiry group (ten participants), consisting of the students, clinician educators and researchers, who met over a period of 5 months. Through a cyclical process of action and reflection this group identified a teaching intervention. The results demonstrate the gaps and challenges identified when implementing a LIC model of medical education. A structured learning programme for the final 6 weeks of the students' placement at the district hospital was designed by the co-operative inquiry group as an agreed intervention. The post-intervention group reflection highlighted a need to create a structured programme in the spirit of local collaboration and learning across disciplines. The results also enhance our understanding of both students and clinician educators' perceptions of this new model of workplace-based training. This paper provides practical strategies to enhance teaching and learning in a new educational context. These strategies illuminate three paradigm shifts: (1) from the traditional medical education approach towards a transformative learning approach advocated for the 21(st) century health professional; (2) from the teaching hospital context to the district hospital context; and (3) from block-based teaching towards a longitudinal integrated learning model. A programme based on balancing structured and tailored learning activities is recommended in order to address the local learning needs of students in the LIC model. We recommend that action learning sets should be developed at these LIC sites, where the relevant aspects of work-place based learning are negotiated.

Machine Learning in Radiation Oncology: Opportunities, Requirements, and Needs

PubMed Central

Feng, Mary; Valdes, Gilmer; Dixit, Nayha; Solberg, Timothy D.

2018-01-01

Machine learning (ML) has the potential to revolutionize the field of radiation oncology, but there is much work to be done. In this article, we approach the radiotherapy process from a workflow perspective, identifying specific areas where a data-centric approach using ML could improve the quality and efficiency of patient care. We highlight areas where ML has already been used, and identify areas where we should invest additional resources. We believe that this article can serve as a guide for both clinicians and researchers to start discussing issues that must be addressed in a timely manner. PMID:29719815

The Learning Behaviors Scale: National Standardization in Trinidad and Tobago

ERIC Educational Resources Information Center

Chao, Jessica L.; McDermott, Paul A.; Watkins, Marley W.; Drogalis, Anna Rhoad; Worrell, Frank C.; Hall, Tracey E.

2018-01-01

This study reports on the national standardization and validation of the Learning Behaviors Scale (LBS) for use in Trinidad and Tobago. The LBS is a teacher rating scale centering on observable behaviors relevant to identifying childhood approaches to classroom learning. Teachers observed a stratified sample of 900 students across the islands'…

Learning as Conceptual Change: Factors Mediating the Development of Preservice Elementary Teachers' Views of Nature of Science

ERIC Educational Resources Information Center

Abd-El-Khalick, Fouad; Akerson, Valarie L.

2004-01-01

This study assessed, and identified factors in participants' learning ecologies that mediated, the effectiveness of an explicit reflective instructional approach that satisfied conditions for learning as conceptual change on preservice elementary teachers' views of nature of science (NOS). Participants were 28 undergraduate students enrolled in an…

Affordances of Augmented Reality in Science Learning: Suggestions for Future Research

ERIC Educational Resources Information Center

Cheng, Kun-Hung; Tsai, Chin-Chung

2013-01-01

Augmented reality (AR) is currently considered as having potential for pedagogical applications. However, in science education, research regarding AR-aided learning is in its infancy. To understand how AR could help science learning, this review paper firstly has identified two major approaches of utilizing AR technology in science education,…

An Achievement Degree Analysis Approach to Identifying Learning Problems in Object-Oriented Programming

ERIC Educational Resources Information Center

Allinjawi, Arwa A.; Al-Nuaim, Hana A.; Krause, Paul

2014-01-01

Students often face difficulties while learning object-oriented programming (OOP) concepts. Many papers have presented various assessment methods for diagnosing learning problems to improve the teaching of programming in computer science (CS) higher education. The research presented in this article illustrates that although max-min composition is…

Analyzing Educators' Online Interactions: A Framework of Online Learning Support Roles

ERIC Educational Resources Information Center

Nacu, Denise C.; Martin, Caitlin K.; Pinkard, Nichole; Gray, Tené

2016-01-01

While the potential benefits of participating in online learning communities are documented, so too are inequities in terms of how different populations access and use them. We present the online learning support roles (OLSR) framework, an approach using both automated analytics and qualitative interpretation to identify and explore online…

Learning to Teach: What Do Pre-Service Teachers Report

ERIC Educational Resources Information Center

Naylor, Dawn A.; Campbell-Evans, Glenda; Maloney, Maloney

2015-01-01

Taking a sociocultural approach to understanding the phenomenon of learning to teach, this study examined the extent to which seven pre-service teachers, in their final year of a Bachelor of Education course in a regional Australian university campus, identified personal, professional and contextual aspects as significant influences on learning to…

Assessing Students' Learning of Internal Controls: Closing the Loop

ERIC Educational Resources Information Center

Amer, T. S.; Mohrweis, Lawrence C.

2009-01-01

This study describes the multifaceted components of an assessment process. The paper explains a novel approach in which an advisory council participated in a "fun," hands-on activity to rank-order learning outcomes. The top ranked learning competency, as identified by the advisory council, was the need for students to gain a better…

Engaging Past and Present: Service-Learning in the College History Classroom

ERIC Educational Resources Information Center

Straus, Emily E.; Eckenrode, Dawn M.

2014-01-01

Service-learning as a pedagogical approach has become a popular trend in undergraduate teaching. according to Robert Bringle and Julie Hatcher, service-learning is a "course-based, credit-bearing educational experience that allows students to (a) participate in an organized service activity that meets identified community needs and (b)…

The Good CPD Guide Janet Grant The Good CPD Guide Radcliffe Publishing £29.99 190pp 9781846195709 1846195705 [Formula: see text].

PubMed

2012-08-31

THE AUTHOR provides a four-step approach to coherent and relevant continuing professional development programmes. Content includes: identifying what and how best to learn, how to relate this learning to personal development planning and demonstrating the effects of learning in practice.

Understanding Students' Experiences of Professionalism Learning: A "Threshold" Approach

ERIC Educational Resources Information Center

Neve, Hilary; Lloyd, Helen; Collett, Tracey

2017-01-01

Professionalism is a core element of curricula in many disciplines but can be difficult to teach and learn. This study used audio-diary methodology to identify professionalism threshold concepts in a small group learning setting in undergraduate medicine and to understand factors that might facilitate students to "get" such concepts.…

Learning polynomial feedforward neural networks by genetic programming and backpropagation.

PubMed

Nikolaev, N Y; Iba, H

2003-01-01

This paper presents an approach to learning polynomial feedforward neural networks (PFNNs). The approach suggests, first, finding the polynomial network structure by means of a population-based search technique relying on the genetic programming paradigm, and second, further adjustment of the best discovered network weights by an especially derived backpropagation algorithm for higher order networks with polynomial activation functions. These two stages of the PFNN learning process enable us to identify networks with good training as well as generalization performance. Empirical results show that this approach finds PFNN which outperform considerably some previous constructive polynomial network algorithms on processing benchmark time series.

Learning in Earth and Space Science: A Review of Conceptual Change Instructional Approaches

ERIC Educational Resources Information Center

Mills, Reece; Tomas, Louisa; Lewthwaite, Brian

2016-01-01

In response to calls for research into effective instruction in the Earth and space sciences, and to identify directions for future research, this systematic review of the literature explores research into instructional approaches designed to facilitate conceptual change. In total, 52 studies were identified and analyzed. Analysis focused on the…

Building a Community Memory in Communities of Practice of E-Learning: A Knowledge Engineering Approach

ERIC Educational Resources Information Center

Sarirete, Akila; Chikh, Azeddine; Noble, Elizabeth

2011-01-01

Purpose: The purpose of this paper is to define a community memory for a virtual communities of practice (CoP) based on organizational learning (OL) concept and ontologies. Design/methodology/approach: The paper focuses on applying the OL concept to virtual CoP and proposes a framework for building the CoP memory by identifying several layers of…

Decision Process to Identify Lessons for Transition to a Distributed (or Blended) Learning Instructional Format

DTIC Science & Technology

2009-09-01

instructional format. Using a mixed- method coding and analysis approach, the sample of POIs were categorized, coded, statistically analyzed, and a... Method SECURITY CLASSIFICATION OF 19. LIMITATION OF 20. NUMBER 21. RESPONSIBLE PERSON 16. REPORT Unclassified 17. ABSTRACT...transition to a distributed (or blended) learning format. Procedure: A mixed- methods approach, combining qualitative coding procedures with basic

Effective and Promising Summer Learning Programs and Approaches for Economically-Disadvantaged Children and Youth: A White Paper for the Wallace Foundation

ERIC Educational Resources Information Center

Terzian, Mary; Moore, Kristin Anderson; Hamilton, Kathleen

2009-01-01

This White Paper summarizes findings from an extensive literature review that was conducted to identify the most promising models and approaches for meeting the needs of low-income children, youth, and families during the summer months. Special attention is paid to summer learning programs that serve diverse, urban low-income children and youth.…

Improving Science Pedagogic Quality in Elementary School Using Process Skill Approach Can Motivate Student to Be Active in Learning

ERIC Educational Resources Information Center

Sukiniarti

2016-01-01

On global era todays, as the professional teacher should be improving their pedagogic competency, including to improve their science pedagogy quality. This study is aimed to identify: (1) Process skill approach which has been used by Elementary School Teacher in science learning; (2) Teacher's opinion that process skill can motivate the student to…

Partitioned learning of deep Boltzmann machines for SNP data.

PubMed

Hess, Moritz; Lenz, Stefan; Blätte, Tamara J; Bullinger, Lars; Binder, Harald

2017-10-15

Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen the joint distribution of SNPs, followed by training several DBMs on SNP partitions that were identified by the screening. Aggregate features representing SNP patterns and the corresponding SNPs are extracted from the DBMs by a combination of statistical tests and sparse regression. In simulated case-control data, we show how this can uncover complex SNP patterns and augment results from univariate approaches, while maintaining type 1 error control. Time-to-event endpoints are considered in an application with acute myeloid leukemia patients, where SNP patterns are modeled after a pre-screening based on gene expression data. The proposed approach identified three SNPs that seem to jointly influence survival in a validation dataset. This indicates the added value of jointly investigating SNPs compared to standard univariate analyses and makes partitioned learning of DBMs an interesting complementary approach when analyzing SNP data. A Julia package is provided at 'http://github.com/binderh/BoltzmannMachines.jl'. binderh@imbi.uni-freiburg.de. 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

Learning by Doing Approach in the Internet Environment to Improve the Teaching Efficiency of Information Technology

NASA Astrophysics Data System (ADS)

Zhang, X.-S.; Xie, Hua

This paper presents a learning-by-doing method in the Internet environment to enhance the results of information technology education by experimental work in the classroom of colleges. In this research, an practical approach to apply the "learning by doing" paradigm in Internet-based learning, both for higher educational environments and life-long training systems, taking into account available computer and network resources, such as blogging, podcasting, social networks, wiki etc. We first introduce the different phases in the learning process, which aimed at showing to the readers that the importance of the learning by doing paradigm, which is not implemented in many Internet-based educational environments. Secondly, we give the concept of learning by doing in the different perfective. Then, we identify the most important trends in this field, and give a real practical case for the application of this approach. The results show that the attempt methods are much better than traditional teaching methods.

Influence of Psychosocial Classroom Environment on Students' Motivation and Self-Regulation in Science Learning: A Structural Equation Modeling Approach

ERIC Educational Resources Information Center

Velayutham, Sunitadevi; Aldridge, Jill M.

2013-01-01

The primary aim of this study was two-fold: 1) to identify salient psychosocial features of the classroom environment that influence students' motivation and self-regulation in science learning; and 2) to examine the effect of the motivational constructs of learning goal orientation, science task value and self-efficacy in science learning on…

[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.

Using Active Learning to Identify Health Information Technology Related Patient Safety Events.

PubMed

Fong, Allan; Howe, Jessica L; Adams, Katharine T; Ratwani, Raj M

2017-01-18

The widespread adoption of health information technology (HIT) has led to new patient safety hazards that are often difficult to identify. Patient safety event reports, which are self-reported descriptions of safety hazards, provide one view of potential HIT-related safety events. However, identifying HIT-related reports can be challenging as they are often categorized under other more predominate clinical categories. This challenge of identifying HIT-related reports is exacerbated by the increasing number and complexity of reports which pose challenges to human annotators that must manually review reports. In this paper, we apply active learning techniques to support classification of patient safety event reports as HIT-related. We evaluated different strategies and demonstrated a 30% increase in average precision of a confirmatory sampling strategy over a baseline no active learning approach after 10 learning iterations.

Comparing and Combining Traditional Teaching Approaches and the Use of Video Clips for Learning How to Identify Species in an Aquarium

ERIC Educational Resources Information Center

Pfeiffer, Vanessa D. I.; Scheiter, Katharina; Gemballa, Sven

2012-01-01

This study investigated the effectiveness of three different instructional materials for learning how to identify fish at the species level in a blended classroom and out-of-classroom scenario. A sample of 195 first-year students of biology or geoecology at the University of Tuebingen participated in a course on identification of European…

Identifying clinical learning needs using structured group feedback: first year evaluation of pre-registration nursing and midwifery degree programmes.

PubMed

Frazer, Kate; Connolly, Michael; Naughton, Corina; Kow, Veronica

2014-07-01

Facilitating and supporting clinical learning for student nurses and midwives are essential within their practice environments. Clinical placements provide unique opportunities in preparation for future roles. Understanding the experiences of first year student nurses and midwives following clinical exposures and examining the clinical facilitators and barriers can assist in maintaining and developing clinical supports. The study used a structured group feedback approach with a convenience sample of 223 first year nursing and midwifery students in one Irish university in April 2011 to ascertain feedback on the clinical aspects of their degree programme. Approximately 200 students participated in the process. Two key clinical issues were identified by students: facilitating clinical learning and learning experiences and needs. Positive learning environments, supportive staff and increased opportunities for reflection were important issues for first year students. The role of supportive mentoring staff in clinical practice is essential to enhance student learning. Students value reflection in practice and require more opportunities to engage during placements. More collaborative approaches are required to ensure evolving and adapting practice environments can accommodate student learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Technology Toolkit.

ERIC Educational Resources Information Center

Brooklyn Public Library, NY.

This reference resource identifies issues concerning technology use in library literacy programs and describes approaches that work at the Brooklyn (New York) Public Library. Section 1 discusses the learning centers at the library, including its mission, philosophy, curriculum, technology, volunteer tutors, and active learning environment. Section…

Airline Passenger Profiling Based on Fuzzy Deep Machine Learning.

PubMed

Zheng, Yu-Jun; Sheng, Wei-Guo; Sun, Xing-Ming; Chen, Sheng-Yong

2017-12-01

Passenger profiling plays a vital part of commercial aviation security, but classical methods become very inefficient in handling the rapidly increasing amounts of electronic records. This paper proposes a deep learning approach to passenger profiling. The center of our approach is a Pythagorean fuzzy deep Boltzmann machine (PFDBM), whose parameters are expressed by Pythagorean fuzzy numbers such that each neuron can learn how a feature affects the production of the correct output from both the positive and negative sides. We propose a hybrid algorithm combining a gradient-based method and an evolutionary algorithm for training the PFDBM. Based on the novel learning model, we develop a deep neural network (DNN) for classifying normal passengers and potential attackers, and further develop an integrated DNN for identifying group attackers whose individual features are insufficient to reveal the abnormality. Experiments on data sets from Air China show that our approach provides much higher learning ability and classification accuracy than existing profilers. It is expected that the fuzzy deep learning approach can be adapted for a variety of complex pattern analysis tasks.

Using Instructional Design, Analyze, Design, Develop, Implement, and Evaluate, to Develop e-Learning Modules to Disseminate Supported Employment for Community Behavioral Health Treatment Programs in New York State.

PubMed

Patel, Sapana R; Margolies, Paul J; Covell, Nancy H; Lipscomb, Cristine; Dixon, Lisa B

2018-01-01

Implementation science lacks a systematic approach to the development of learning strategies for online training in evidence-based practices (EBPs) that takes the context of real-world practice into account. The field of instructional design offers ecologically valid and systematic processes to develop learning strategies for workforce development and performance support. This report describes the application of an instructional design framework-Analyze, Design, Develop, Implement, and Evaluate (ADDIE) model-in the development and evaluation of e-learning modules as one strategy among a multifaceted approach to the implementation of individual placement and support (IPS), a model of supported employment for community behavioral health treatment programs, in New York State. We applied quantitative and qualitative methods to develop and evaluate three IPS e-learning modules. Throughout the ADDIE process, we conducted formative and summative evaluations and identified determinants of implementation using the Consolidated Framework for Implementation Research (CFIR). Formative evaluations consisted of qualitative feedback received from recipients and providers during early pilot work. The summative evaluation consisted of levels 1 and 2 (reaction to the training, self-reported knowledge, and practice change) quantitative and qualitative data and was guided by the Kirkpatrick model for training evaluation. Formative evaluation with key stakeholders identified a range of learning needs that informed the development of a pilot training program in IPS. Feedback on this pilot training program informed the design document of three e-learning modules on IPS: Introduction to IPS, IPS Job development, and Using the IPS Employment Resource Book . Each module was developed iteratively and provided an assessment of learning needs that informed successive modules. All modules were disseminated and evaluated through a learning management system. Summative evaluation revealed that learners rated the modules positively, and self-report of knowledge acquisition was high (mean range: 4.4-4.6 out of 5). About half of learners indicated that they would change their practice after watching the modules (range: 48-51%). All learners who completed the level 1 evaluation demonstrated 80% or better mastery of knowledge on the level 2 evaluation embedded in each module. The CFIR was used to identify implementation barriers and facilitators among the evaluation data which facilitated planning for subsequent implementation support activities in the IPS initiative. Instructional design approaches such as ADDIE may offer implementation scientists and practitioners a flexible and systematic approach for the development of e-learning modules as a single component or one strategy in a multifaceted approach for training in EBPs.

Functioning at the Edge of Knowledge: A Study of Learning Processes in New Product Development

ERIC Educational Resources Information Center

Doos, Marianne; Wilhelmson, Lena; Backlund, Thomas; Dixon, Nancy

2005-01-01

Purpose: In the telecommunication industry, companies gain a competitive edge through the competence of their employees, making issues of learning critical. The study aims to identify specific learning processes necessary when working at the edge both of one's own knowledge and of that of the branch. Design/methodology/approach: This research…

In the Driver's Seat: Teacher-Led Model Moves Learning in the Right Direction

ERIC Educational Resources Information Center

Sullivan, Lisa; Westover, Theresa

2015-01-01

What happens when teachers are given funding and time to identify and develop targeted and innovative professional learning? This article focuses on lessons learned from grants funded through the California Department of Education that were designed to do just this. As the state and the nation consider the best approaches to professional learning…

A Novel Approach for Assisting Teachers in Analyzing Student Web-Searching Behaviors

ERIC Educational Resources Information Center

Hwang, G. J.; Tsai, P. S.; Tsai, C. C.; Tseng, J. C. R.

2008-01-01

Although previous research has demonstrated the benefits of applying the Internet facilities to the learning process, problems with this strategy have also been identified. One of the major difficulties is owing to the lack of an online learning environment that can record the learning portfolio of using the Internet facilities in education, such…

Do Undergraduate Paramedic Students Embrace Case Based Learning Using a Blended Teaching Approach? A 3-Year Review

ERIC Educational Resources Information Center

Williams, Brett

2009-01-01

This paper presents the results of a descriptive longitudinal study which aimed to identify student paramedic perceptions of case based learning used in the clinical curriculum of the Bachelor of Emergency Health (BEH) degree at Monash University, Victoria, Australia. Case based learning and its integration within clinical curriculum is an…

Bare Bones: An Introduction to Physical Anthropology. Alternative Techniques for Teaching Physical Anthropology to Learning Disabled Students in the University.

ERIC Educational Resources Information Center

Sands, Catherine J. MacMillan

The booklet describes approaches to teaching learning disabled students introductory physical anthropology, as related by a professor involved in the Higher Education for Learning Disabled Students (HELDS) program. The author suggests ways to identify LD students through observation of short attention span, restlessness, and marked discrepancies…

Motivation for Learning and Performance. Symposium 3. [Concurrent Symposium Session at AHRD Annual Conference, 2000.

ERIC Educational Resources Information Center

2000

This document contains three papers from a symposium on motivation for learning and performance that was conducted as part of a conference on human resource development (HRD). "A Holistic Approach towards Motivation To Learn" (Constantine Kontoghiorghes) reports on a study that identified the following key variables within and outside…

A Comparison of Educational Statistics and Data Mining Approaches to Identify Characteristics That Impact Online Learning

ERIC Educational Resources Information Center

Miller, L. Dee; Soh, Leen-Kiat; Samal, Ashok; Kupzyk, Kevin; Nugent, Gwen

2015-01-01

Learning objects (LOs) are important online resources for both learners and instructors and usage for LOs is growing. Automatic LO tracking collects large amounts of metadata about individual students as well as data aggregated across courses, learning objects, and other demographic characteristics (e.g. gender). The challenge becomes identifying…

A Dynamic Programming Approach to Identifying the Shortest Path in Virtual Learning Environments

ERIC Educational Resources Information Center

Fazlollahtabar, Hamed

2008-01-01

E-learning has been widely adopted as a promising solution by many organizations to offer learning-on-demand opportunities to individual employees (learners) in order to reduce training time and cost. While successful information systems models have received much attention among researchers, little research has been conducted to assess the success…

Learning in Earth and space science: a review of conceptual change instructional approaches

NASA Astrophysics Data System (ADS)

Mills, Reece; Tomas, Louisa; Lewthwaite, Brian

2016-03-01

In response to calls for research into effective instruction in the Earth and space sciences, and to identify directions for future research, this systematic review of the literature explores research into instructional approaches designed to facilitate conceptual change. In total, 52 studies were identified and analyzed. Analysis focused on the general characteristics of the research, the conceptual change instructional approaches that were used, and the methods employed to evaluate the effectiveness of these approaches. The findings of this review support four assertions about the existing research: (1) astronomical phenomena have received greater attention than geological phenomena; (2) most studies have viewed conceptual change from a cognitive perspective only; (3) data about conceptual change were generated pre- and post-intervention only; and (4) the interventions reviewed presented limited opportunities to involve students in the construction and manipulation of multiple representations of the phenomenon being investigated. Based upon these assertions, the authors recommend that new research in the Earth and space science disciplines challenges traditional notions of conceptual change by exploring the role of affective variables on learning, focuses on the learning of geological phenomena through the construction of multiple representations, and employs qualitative data collection throughout the implementation of an instructional approach.

Bridging the gap between self-directed learning of nurse educators and effective student support.

PubMed

Van Rensburg, Gisela H; Botma, Yvonne

2015-11-26

Self-directed learning requires the ability to identify one's own learning needs, develop and implement a plan to gain knowledge and to monitor one's own progress. A lifelong learning approach cannot be forced, since it is in essence an internally driven process. Nurse educators can, however, act as role models to empower their students to become independent learners by modelling their own self-directed learning and applying a number of techniques in supporting their students in becoming ready for self-directed learning.  The aim of the article is to describe the manifestations and implications of the gap between self-directed learning readiness of nurse educators and educational trends in supporting students.  An instrumental case study design was used to gain insight into the manifestations and implications of self-directed learning of nurse educators. Based on the authentic foci of various critical incidents and literature, data were collected and constructed into a fictitious case. The authors then deductively analysed the case by using the literature on self-directed learning readiness as departure point. Four constructs of self-directed learning were identified, namely internal motivation, planning and implementation, self-monitoring and interpersonal communication. Supportive strategies were identified from the available literature.  Nine responses by nurse educators based on the fictitious case were analysed.Analysis showed that readiness for self-directed learning in terms of the identified constructswas interrelated and not mutually exclusive of one other.  The success of lifelong learning is the ability to engage in self-directed learning which requires openness to learning opportunities, good self-concept, taking initiative and illustrating independence in learning. Conscientiousness, an informed acceptance of a responsibility for one's own learning and creativity, is vital to one's future orientation towards goal-directed learning. Knowledge and understanding of one's own and students' selfdirected learning abilities are critical for nurse educators. In the nursing profession, it has been shown that self-directed learning by the nurse educators has a direct relationship towards the development of a lifelong learning approach by their students. Supporting students towards becoming self-directed learners throughout their professional life, in turn, will impact directly on the quality of nursing and midwifery practice. (Article to follow).

Two Essays on Increasing the Learning Effectiveness of Economics Education

ERIC Educational Resources Information Center

McLean, William J.

2010-01-01

Scope and Method of Study: This study develops, implements, and evaluates a new economics teaching pedagogy based on the U.S. Army's systems approach to training model. Using the approach, tasks are identified that compose the task domain for the Principles of Microeconomics course. From the 130 identified tasks, 73 are used by Economics of…

Embedding learning from adverse incidents: a UK case study.

PubMed

Eshareturi, Cyril; Serrant, Laura

2017-04-18

Purpose This paper reports on a regionally based UK study uncovering what has worked well in learning from adverse incidents in hospitals. The purpose of this paper is to review the incident investigation methodology used in identifying strengths or weaknesses and explore the use of a database as a tool to embed learning. Design/methodology/approach Documentary examination was conducted of all adverse incidents reported between 1 June 2011 and 30 June 2012 by three UK National Health Service hospitals. One root cause analysis report per adverse incident for each individual hospital was sent to an advisory group for a review. Using terms of reference supplied, the advisory group feedback was analysed using an inductive thematic approach. The emergent themes led to the generation of questions which informed seven in-depth semi-structured interviews. Findings "Time" and "work pressures" were identified as barriers to using adverse incident investigations as tools for quality enhancement. Methodologically, a weakness in approach was that no criteria influenced the techniques which were used in investigating adverse incidents. Regarding the sharing of learning, the use of a database as a tool to embed learning across the region was not supported. Practical implications Softer intelligence from adverse incident investigations could be usefully shared between hospitals through a regional forum. Originality/value The use of a database as a tool to facilitate the sharing of learning from adverse incidents across the health economy is not supported.

Teachers' learning on the workshop of STS approach as a way of enhancing inventive thinking skills

NASA Astrophysics Data System (ADS)

Ngaewkoodrua, Nophakun; Yuenyong, Chokchai

2018-01-01

To improve science teachers to develop the STS lesson plans for enhancing the students' inventive thinking skills, the workshop of improving science teachers to develop the STS lesson plans for enhancing the Inventive thinking skills were organized. The paper aimed to clarify what teachers learn from the workshop. The goal of the activity of the workshop aimed to: 1) improve participants a better understanding of the relationship between the Inquiry based learning with STS approach, 2) understand the meaning and importance of the STS approach and identify the various stages of Yuenyong (2006) STS learning process, 3) discuss what they learned from the examples of Yuenyong (2006) lesson plan, 4) develop some activities for each stage of Yuenyong (2006) STS approach, and 5) ideas of providing STS approach activities for enhancing inventive thinking skills. Participants included 3 science teachers who work in Khon Kaen, Thailand. Methodology regarded interpretive paradigm. Teachers' learning about pedagogy of enhancing the students' inventive thinking skills will be interpreted through participant observation, teachers' tasks, and interview. The finding revealed that all participants could demonstrate their ideas how to generate the STS lesson plans as a way of enhancing inventive thinking skills. Teachers could mention some element of inventive thinking skills which could be generated on their STS learning activities.

A pilot study on conducting mobile learning activities for clinical nursing courses based on the repertory grid approach.

PubMed

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Chin-Chung; Chen, Ya-Chun; Huang, Yueh-Min

2011-11-01

In clinical nursing courses, students are trained to identify the status of the target patients. The mastery of such ability and skills is very important since patients frequently need to be cared for immediately. In this pilot study, a repertory grid-oriented clinical mobile learning system is developed for a nursing training program. With the assistance of the mobile learning system, the nursing school students are able to learn in an authentic learning scenario, in which they can physically face the target patients, with the personal guidance and supplementary materials from the learning system to support them. To show the effectiveness of this innovative approach, an experiment has been conducted on the "respiratory system" unit of a nursing course. The experimental results show that the innovative approach is helpful to students in improving their learning achievements. Moreover, from the questionnaire surveys, it was found that most students showed favorable attitudes toward the usage of the mobile learning system and their participation in the training program. Copyright © 2010 Elsevier Ltd. All rights reserved.

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

PubMed Central

Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki

2013-01-01

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846

Using Biology Education Research and Qualitative Inquiry to Inform Genomic Nursing Education.

PubMed

Ward, Linda D

Decades of research in biology education show that learning genetics is difficult and reveals specific sources of learning difficulty. Little is known about how nursing students learn in this domain, although they likely encounter similar difficulties as nonnursing students. Using qualitative approaches, this study investigated challenges to learning genetics among nursing students. Findings indicate that nursing students face learning difficulties already identified among biology students, suggesting that nurse educators might benefit from biology education research.

A multidimensional approach to examine student interdisciplinary learning in science and engineering in higher education

NASA Astrophysics Data System (ADS)

Spelt, Elisabeth Jacoba Hendrika; Luning, Pieternelleke Arianne; van Boekel, Martinus A. J. S.; Mulder, Martin

2017-11-01

Preparing science and engineering students to work in interdisciplinary teams necessitates research on teaching and learning of interdisciplinary thinking. A multidimensional approach was taken to examine student interdisciplinary learning in a master course on food quality management. The collected 615 student experiences were analysed for the cognitive, emotional, and social learning dimensions using the learning theory of Illeris. Of these 615 experiences, the analysis showed that students reported 214, 194, and 207 times on, respectively, the emotional, the cognitive, and the social dimension. Per learning dimension, key learning experiences featuring interdisciplinary learning were identified such as 'frustrations in selecting and matching disciplinary knowledge to complex problems' (emotional), 'understanding how to apply theoretical models or concepts to real-world situations' (cognitive), and 'socially engaging with peers to recognise similarities in perceptions and experiences' (social). Furthermore, the results showed that students appreciated the cognitive dimension relatively more than the emotional and social dimensions.

Learning in context: identifying gaps in research on the transfer of medical communication skills to the clinical workplace.

PubMed

van den Eertwegh, Valerie; van Dulmen, Sandra; van Dalen, Jan; Scherpbier, Albert J J A; van der Vleuten, Cees P M

2013-02-01

In order to reduce the inconsistencies of findings and the apparent low transfer of communication skills from training to medical practice, this narrative review identifies some main gaps in research on medical communication skills training and presents insights from theories on learning and transfer to broaden the view for future research. Relevant literature was identified using Pubmed, GoogleScholar, Cochrane database, and Web of Science; and analyzed using an iterative procedure. Research findings on the effectiveness of medical communication training still show inconsistencies and variability. Contemporary theories on learning based on a constructivist paradigm offer the following insights: acquisition of knowledge and skills should be viewed as an ongoing process of exchange between the learner and his environment, so called lifelong learning. This process can neither be atomized nor separated from the context in which it occurs. Four contemporary approaches are presented as examples. The following shift in focus for future research is proposed: beyond isolated single factor effectiveness studies toward constructivist, non-reductionistic studies integrating the context. Future research should investigate how constructivist approaches can be used in the medical context to increase effective learning and transition of communication skills. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Learning mechanisms to limit medication administration errors.

PubMed

Drach-Zahavy, Anat; Pud, Dorit

2010-04-01

This paper is a report of a study conducted to identify and test the effectiveness of learning mechanisms applied by the nursing staff of hospital wards as a means of limiting medication administration errors. Since the influential report ;To Err Is Human', research has emphasized the role of team learning in reducing medication administration errors. Nevertheless, little is known about the mechanisms underlying team learning. Thirty-two hospital wards were randomly recruited. Data were collected during 2006 in Israel by a multi-method (observations, interviews and administrative data), multi-source (head nurses, bedside nurses) approach. Medication administration error was defined as any deviation from procedures, policies and/or best practices for medication administration, and was identified using semi-structured observations of nurses administering medication. Organizational learning was measured using semi-structured interviews with head nurses, and the previous year's reported medication administration errors were assessed using administrative data. The interview data revealed four learning mechanism patterns employed in an attempt to learn from medication administration errors: integrated, non-integrated, supervisory and patchy learning. Regression analysis results demonstrated that whereas the integrated pattern of learning mechanisms was associated with decreased errors, the non-integrated pattern was associated with increased errors. Supervisory and patchy learning mechanisms were not associated with errors. Superior learning mechanisms are those that represent the whole cycle of team learning, are enacted by nurses who administer medications to patients, and emphasize a system approach to data analysis instead of analysis of individual cases.

Automated recognition of stratigraphic marker shales from geophysical logs in iron ore deposits

NASA Astrophysics Data System (ADS)

Silversides, Katherine; Melkumyan, Arman; Wyman, Derek; Hatherly, Peter

2015-04-01

The mining of stratiform ore deposits requires a means of determining the location of stratigraphic boundaries. A variety of geophysical logs may provide the required data but, in the case of banded iron formation hosted iron ore deposits in the Hamersley Ranges of Western Australia, only one geophysical log type (natural gamma) is collected for this purpose. The information from these logs is currently processed by slow manual interpretation. In this paper we present an alternative method of automatically identifying recurring stratigraphic markers in natural gamma logs from multiple drill holes. Our approach is demonstrated using natural gamma geophysical logs that contain features corresponding to the presence of stratigraphically important marker shales. The host stratigraphic sequence is highly consistent throughout the Hamersley and the marker shales can therefore be used to identify the stratigraphic location of the banded iron formation (BIF) or BIF hosted ore. The marker shales are identified using Gaussian Processes (GP) trained by either manual or active learning methods and the results are compared to the existing geological interpretation. The manual method involves the user selecting the signatures for improving the library, whereas the active learning method uses the measure of uncertainty provided by the GP to select specific examples for the user to consider for addition. The results demonstrate that both GP methods can identify a feature, but the active learning approach has several benefits over the manual method. These benefits include greater accuracy in the identified signatures, faster library building, and an objective approach for selecting signatures that includes the full range of signatures across a deposit in the library. When using the active learning method, it was found that the current manual interpretation could be replaced in 78.4% of the holes with an accuracy of 95.7%.

Prediction of bacterial small RNAs in the RsmA (CsrA) and ToxT pathways: a machine learning approach.

PubMed

Fakhry, Carl Tony; Kulkarni, Prajna; Chen, Ping; Kulkarni, Rahul; Zarringhalam, Kourosh

2017-08-22

Small RNAs (sRNAs) constitute an important class of post-transcriptional regulators that control critical cellular processes in bacteria. Recent research using high-throughput transcriptomic approaches has led to a dramatic increase in the discovery of bacterial sRNAs. However, it is generally believed that the currently identified sRNAs constitute a limited subset of the bacterial sRNA repertoire. In several cases, sRNAs belonging to a specific class are already known and the challenge is to identify additional sRNAs belonging to the same class. In such cases, machine-learning approaches can be used to predict novel sRNAs in a given class. In this work, we develop novel bioinformatics approaches that integrate sequence and structure-based features to train machine-learning models for the discovery of bacterial sRNAs. We show that features derived from recurrent structural motifs in the ensemble of low energy secondary structures can distinguish the RNA classes with high accuracy. We apply this approach to predict new members in two broad classes of bacterial small RNAs: 1) sRNAs that bind to the RNA-binding protein RsmA/CsrA in diverse bacterial species and 2) sRNAs regulated by the master regulator of virulence, ToxT, in Vibrio cholerae. The involvement of sRNAs in bacterial adaptation to changing environments is an increasingly recurring theme in current research in microbiology. It is likely that future research, combining experimental and computational approaches, will discover many more examples of sRNAs as components of critical regulatory pathways in bacteria. We have developed a novel approach for prediction of small RNA regulators in important bacterial pathways. This approach can be applied to specific classes of sRNAs for which several members have been identified and the challenge is to identify additional sRNAs.

Biosignature Discovery for Substance Use Disorders Using Statistical Learning.

PubMed

Baurley, James W; McMahan, Christopher S; Ervin, Carolyn M; Pardamean, Bens; Bergen, Andrew W

2018-02-01

There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identifying Green Infrastructure from Social Media and Crowdsourcing- An Image Based Machine-Learning Approach.

NASA Astrophysics Data System (ADS)

Rai, A.; Minsker, B. S.

2016-12-01

In this work we introduce a novel dataset GRID: GReen Infrastructure Detection Dataset and a framework for identifying urban green storm water infrastructure (GI) designs (wetlands/ponds, urban trees, and rain gardens/bioswales) from social media and satellite aerial images using computer vision and machine learning methods. Along with the hydrologic benefits of GI, such as reducing runoff volumes and urban heat islands, GI also provides important socio-economic benefits such as stress recovery and community cohesion. However, GI is installed by many different parties and cities typically do not know where GI is located, making study of its impacts or siting new GI difficult. We use object recognition learning methods (template matching, sliding window approach, and Random Hough Forest method) and supervised machine learning algorithms (e.g., support vector machines) as initial screening approaches to detect potential GI sites, which can then be investigated in more detail using on-site surveys. Training data were collected from GPS locations of Flickr and Instagram image postings and Amazon Mechanical Turk identification of each GI type. Sliding window method outperformed other methods and achieved an average F measure, which is combined metric for precision and recall performance measure of 0.78.

Master surgeons' operative teaching philosophies: a qualitative analysis of parallels to learning theory.

PubMed

Pernar, Luise I M; Ashley, Stanley W; Smink, Douglas S; Zinner, Michael J; Peyre, Sarah E

2012-01-01

Practicing within the Halstedian model of surgical education, academic surgeons serve dual roles as physicians to their patients and educators of their trainees. Despite this significant responsibility, few surgeons receive formal training in educational theory to inform their practice. The goal of this work was to gain an understanding of how master surgeons approach teaching uncommon and highly complex operations and to determine the educational constructs that frame their teaching philosophies and approaches. Individuals included in the study were queried using electronically distributed open-ended, structured surveys. Responses to the surveys were analyzed and grouped using grounded theory and were examined for parallels to concepts of learning theory. Academic teaching hospital. Twenty-two individuals identified as master surgeons. Twenty-one (95.5%) individuals responded to the survey. Two primary thematic clusters were identified: global approach to teaching (90.5% of respondents) and approach to intraoperative teaching (76.2%). Many of the emergent themes paralleled principles of transfer learning theory outlined in the psychology and education literature. Key elements included: conferring graduated responsibility (57.1%), encouraging development of a mental set (47.6%), fostering or expecting deliberate practice (42.9%), deconstructing complex tasks (38.1%), vertical transfer of information (33.3%), and identifying general principles to structure knowledge (9.5%). Master surgeons employ many of the principles of learning theory when teaching uncommon and highly complex operations. The findings may hold significant implications for faculty development in surgical education. Copyright © 2012 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

A Belgian Approach to Learning Disabilities.

ERIC Educational Resources Information Center

Hayes, Cheryl W.

The paper reviews Belgian philosophy toward the education of learning disabled students and cites the differences between American behaviorally-oriented theory and Belgian emphasis on identifying the underlying causes of the disability. Academic methods observed in Belgium (including psychodrama and perceptual motor training) are discussed and are…

Academic Achievement Standards and Quality Assurance

ERIC Educational Resources Information Center

Sadler, D. Royce

2017-01-01

Quality assurance processes have been applied to many aspects of higher education, including teaching, learning and assessment. At least in the latter domain, quality assurance needs its fundamental tenets critically scrutinised. A common but inadequate approach has been to identify and promote learning environment changes "likely to…

A Systematic Mapping on the Learning Analytics Field and Its Analysis in the Massive Open Online Courses Context

ERIC Educational Resources Information Center

Moissa, Barbara; Gasparini, Isabela; Kemczinski, Avanilde

2015-01-01

Learning Analytics (LA) is a field that aims to optimize learning through the study of dynamical processes occurring in the students' context. It covers the measurement, collection, analysis and reporting of data about students and their contexts. This study aims at surveying existing research on LA to identify approaches, topics, and needs for…

Learning as an Apprentice in Sweden: A Comparative Study on Affordances for Vocational Learning in School and Work Life Apprentice Education

ERIC Educational Resources Information Center

Fjellström, Magnus; Kristmansson, Per

2016-01-01

Purpose: The purpose of this paper is to compare, and identify both similarities and differences in, affordances for vocational learning in two contrasting education systems, for construction worker and shop salesperson apprentices, in Swedish contexts. Design/methodology/approach: Data were collected through interviews and observations in two…

Second Language Developmental Dynamics: How Dynamic Systems Theory Accounts for Issues in Second Language Learning

ERIC Educational Resources Information Center

Rosmawati

2014-01-01

Dynamic systems theory (DST) is presented in this article as a suitable approach to research the acquisition of second language (L2) because of its close alignment with the process of second language learning. Through a process of identifying and comparing the characteristics of a dynamic system with the process of L2 learning, this article…

Benefits, Barriers and Prerequisites for Web 2.0 Learning Activities in the Classroom: The View of Greek Pioneer Teachers

ERIC Educational Resources Information Center

Palaigeorgiou, George; Grammatikopoulou, Athina

2016-01-01

Purpose: This paper aims to identify the learning benefits and the challenges of Web 2.0 educational activities when applied in typical learning settings and as perceived by pioneer educators with extensive Web 2.0 experience. Design/Methodology/Approach: The testimonies of 26 Greek primary and secondary education teachers were collected. All…

Analyzing Students' Learning Progressions throughout a Teaching Sequence on Acoustic Properties of Materials with a Model-Based Inquiry Approach

ERIC Educational Resources Information Center

Hernández, María Isabel; Couso, Digna; Pintó, Roser

2015-01-01

The study we have carried out aims to characterize 15-to 16-year-old students' learning progressions throughout the implementation of a teaching-learning sequence on the acoustic properties of materials. Our purpose is to better understand students' modeling processes about this topic and to identify how the instructional design and actual…

A Qualitative Study on the Obstacles Preventing the Successful Implementation of Web 2.0 in Corporate Learning

ERIC Educational Resources Information Center

Estrada, Luis

2012-01-01

The purpose of this study was to identify the obstacles to the adoption of Web 2.0 technologies as part of corporate learning solutions and strategies. The study followed a qualitative inquiry approach. The sample consisted of 20 corporate learning professionals who are members of the American Society for Training and Development (ASTD) social…

Looking Back and Looking Forward: A Glimpse of Blended Learning in Higher Education from 2007-2017

ERIC Educational Resources Information Center

Taylor, Maurice; Vaughan, Norman; Ghani, Shehzad K.; Atas, Sait; Fairbrother, Michael

2018-01-01

Using an engagement in research approach this article explores the landscape of blended learning in higher education over the last decade by comparing the results of a critical literature review by Vaughan to an instrumental case study that identified key factors that led to the implementation of a blended learning initiative in one medium sized…

Is Learning Only a Cognitive Process? Or Does It Occur in a Sociocultural Environment?: "Constructivism" in the Eyes of Preschool Teachers

ERIC Educational Resources Information Center

Öztürk, Duygu Saniye

2016-01-01

This study aims to identify the views of preschool teachers about learning within the framework of the cognitive and sociocultural constructivist approach and reveal the practical applications of constructivist learning in the 2006 Preschool Curriculum. Participants were ten preschool teachers working at three preschools in Bolu, Turkey and data…

Validation of learning style measures: implications for medical education practice.

PubMed

Chapman, Dane M; Calhoun, Judith G

2006-06-01

It is unclear which learners would most benefit from the more individualised, student-structured, interactive approaches characteristic of problem-based and computer-assisted learning. The validity of learning style measures is uncertain, and there is no unifying learning style construct identified to predict such learners. This study was conducted to validate learning style constructs and to identify the learners most likely to benefit from problem-based and computer-assisted curricula. Using a cross-sectional design, 3 established learning style inventories were administered to 97 post-Year 2 medical students. Cognitive personality was measured by the Group Embedded Figures Test, information processing by the Learning Styles Inventory, and instructional preference by the Learning Preference Inventory. The 11 subscales from the 3 inventories were factor-analysed to identify common learning constructs and to verify construct validity. Concurrent validity was determined by intercorrelations of the 11 subscales. A total of 94 pre-clinical medical students completed all 3 inventories. Five meaningful learning style constructs were derived from the 11 subscales: student- versus teacher-structured learning; concrete versus abstract learning; passive versus active learning; individual versus group learning, and field-dependence versus field-independence. The concurrent validity of 10 of 11 subscales was supported by correlation analysis. Medical students most likely to thrive in a problem-based or computer-assisted learning environment would be expected to score highly on abstract, active and individual learning constructs and would be more field-independent. Learning style measures were validated in a medical student population and learning constructs were established for identifying learners who would most likely benefit from a problem-based or computer-assisted curriculum.

Experimental studies illuminate the cultural transmission of percussive technologies in Homo and Pan

PubMed Central

Whiten, Andrew

2015-01-01

The complexity of Stone Age tool-making is assumed to have relied upon cultural transmission, but direct evidence is lacking. This paper reviews evidence bearing on this question provided through five related empirical perspectives. Controlled experimental studies offer special power in identifying and dissecting social learning into its diverse component forms, such as imitation and emulation. The first approach focuses on experimental studies that have discriminated social learning processes in nut-cracking by chimpanzees. Second come experiments that have identified and dissected the processes of cultural transmission involved in a variety of other force-based forms of chimpanzee tool use. A third perspective is provided by field studies that have revealed a range of forms of forceful, targeted tool use by chimpanzees, that set percussion in its broader cognitive context. Fourth are experimental studies of the development of flint knapping to make functional sharp flakes by bonobos, implicating and defining the social learning and innovation involved. Finally, new and substantial experiments compare what different social learning processes, from observational learning to teaching, afford good quality human flake and biface manufacture. Together these complementary approaches begin to delineate the social learning processes necessary to percussive technologies within the Pan–Homo clade. PMID:26483537

Preparing mental health professionals for new directions in mental health practice: Evaluating the sensory approaches e-learning training package.

PubMed

Meredith, Pamela; Yeates, Harriet; Greaves, Amanda; Taylor, Michelle; Slattery, Maddy; Charters, Michelle; Hill, Melissa

2018-02-01

The application of sensory modulation approaches in mental health settings is growing in recognition internationally. However, a number of barriers have been identified as limiting the implementation of the approach, including workplace culture and a lack of accessible and effective sensory approaches training. The aim of this project was to investigate the efficacy of providing this training through a custom-designed e-learning package. Participants in the present study were predominately nurses and occupational therapists working in mental health settings in Queensland, Australia. Data were collected from 121 participants using an online survey. Significant improvements were found between pre- and post-training in participants' real and perceived levels of knowledge, their perceived levels of confidence, and their attitudes towards using sensory modulation approaches in mental health settings. The findings of the study suggest that the custom-designed sensory approaches e-learning package is an effective, accessible, acceptable, and usable method to train health professionals in sensory modulation approaches. As this study is the first to analyse the efficacy of an e-learning sensory approaches package, the results are considered preliminary, and further investigation is required. © 2017 Australian College of Mental Health Nurses Inc.

A case-based, problem-based learning approach to prepare master of public health candidates for the complexities of global health.

PubMed

Leon, Juan S; Winskell, Kate; McFarland, Deborah A; del Rio, Carlos

2015-03-01

Global health is a dynamic, emerging, and interdisciplinary field. To address current and emerging global health challenges, we need a public health workforce with adaptable and collaborative problem-solving skills. In the 2013-2014 academic year, the Hubert Department of Global Health at the Rollins School of Public Health-Emory University launched an innovative required core course for its first-year Master of Public Health students in the global health track. The course uses a case-based, problem-based learning approach to develop global health competencies. Small teams of students propose solutions to these problems by identifying learning issues and critically analyzing and synthesizing new information. We describe the course structure and logistics used to apply this approach in the context of a large class and share lessons learned.

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.

Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning.

PubMed

Zu, Chen; Gao, Yue; Munsell, Brent; Kim, Minjeong; Peng, Ziwen; Cohen, Jessica R; Zhang, Daoqiang; Wu, Guorong

2018-06-14

The functional brain network has gained increased attention in the neuroscience community because of its ability to reveal the underlying architecture of human brain. In general, majority work of functional network connectivity is built based on the correlations between discrete-time-series signals that link only two different brain regions. However, these simple region-to-region connectivity models do not capture complex connectivity patterns between three or more brain regions that form a connectivity subnetwork, or subnetwork for short. To overcome this current limitation, a hypergraph learning-based method is proposed to identify subnetwork differences between two different cohorts. To achieve our goal, a hypergraph is constructed, where each vertex represents a subject and also a hyperedge encodes a subnetwork with similar functional connectivity patterns between different subjects. Unlike previous learning-based methods, our approach is designed to jointly optimize the weights for all hyperedges such that the learned representation is in consensus with the distribution of phenotype data, i.e. clinical labels. In order to suppress the spurious subnetwork biomarkers, we further enforce a sparsity constraint on the hyperedge weights, where a larger hyperedge weight indicates the subnetwork with the capability of identifying the disorder condition. We apply our hypergraph learning-based method to identify subnetwork biomarkers in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). A comprehensive quantitative and qualitative analysis is performed, and the results show that our approach can correctly classify ASD and ADHD subjects from normal controls with 87.65 and 65.08% accuracies, respectively.

Linking teaching and research in an undergraduate course and exploring student learning experiences

NASA Astrophysics Data System (ADS)

Wallin, Patric; Adawi, Tom; Gold, Julie

2017-01-01

In this case study, we first describe how teaching and research are linked in a master's course on tissue engineering. A central component of the course is an authentic research project that the students carry out in smaller groups and in collaboration with faculty. We then explore how the students experience learning in this kind of discovery-oriented environment. Data were collected through a survey, reflective writing, and interviews. Using a general inductive approach for qualitative analysis, we identified three themes related to the students' learning experiences: learning to navigate the field, learning to do real research, and learning to work with others. Overall, the students strongly valued learning in a discovery-oriented environment and three aspects of the course contributed to much of its success: taking a holistic approach to linking teaching and research, engaging students in the whole inquiry process, and situating authentic problems in an authentic physical and social context.

Leadership Decision Making and the Use of Data

ERIC Educational Resources Information Center

Guerra-Lopez, Ingrid; Blake, Anne M.

2011-01-01

Intelligence gathering, or data collection, is a preliminary and critical stage of decision making. Two key approaches to intelligence gathering are "discovery" and "idea imposition." The discovery approach allows us to learn about possibilities by gathering intelligence in order to identify and weigh options. The idea imposition approach limits…

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.

Areas of Learning

ERIC Educational Resources Information Center

Coe, John

2010-01-01

This article examines the recommendations made by the Independent Review of the Primary Curriculum (the Rose Report in 2009) that the curriculum should be organised into areas of learning. The implications for teachers are considered. By drawing upon past experience some major weaknesses and strengths implicit in the approach are identified and…

Researching in Classrooms: Getting beyond "What Works"

ERIC Educational Resources Information Center

Dudley-Marling, Curt

2011-01-01

The dominant approach to research in learning disabilities utilizes experimental and quasi-experimental designs to identify the most effective instructional strategies for students with learning disabilities. Research is always undertaken from a point of view, yet the discourse on "what works?" is generally silent on how theoretical frameworks…

Design of a Blended Learning Environment: Considerations and Implementation Issues

ERIC Educational Resources Information Center

Gedik, Nuray; Kiraz, Ercan; Ozden, M. Yasar

2013-01-01

This study identified critical issues in the design of a blended learning environment by examining basic design considerations and implementation issues. Following a design-based research approach with the phenomenological tradition of qualitative research, the study investigated instructor experiences relating to the design, development, and…

Alternative Classroom Management and Instructional Delivery Systems in Business Education.

ERIC Educational Resources Information Center

Smith, Douglas C.; Davis, Diane C.; Everett, Donna R.; Kruger, Diane; McLaren, Constance H.; Morse, H. Pauletta; Nelson, Sandra J.; Smith, Gloria Jean; Yacht, Carol; Yohon, Teresa

Identifies and assesses various nontraditional approaches to business education in high school, university, and graduate school. "Block Scheduling: Considerations for Business Education" (Gloria Jean Smith, Douglas C. Smith) describes ways to maximize learning for high school students by restructuring class time. "Distance Learning: Challenges and…

Competing Processes of Sibling Influence: Observational Learning and Sibling Deidentification

ERIC Educational Resources Information Center

Whiteman, Shawn D.; McHale, Susan M.; Crouter, Ann C.

2007-01-01

Although commonly cited as explanations for patterns of sibling similarity and difference, observational learning and sibling deidentification processes have rarely been examined directly. Using a person-oriented approach, we identified patterns in adolescents' perceptions of sibling influences and connected these patterns to sibling similarities…

Understanding the challenges to facilitating active learning in the resident conferences: a qualitative study of internal medicine faculty and resident perspectives.

PubMed

Sawatsky, Adam P; Zickmund, Susan L; Berlacher, Kathryn; Lesky, Dan; Granieri, Rosanne

2015-01-01

In the Next Accreditation System, the Accreditation Council for Graduate Medical Education outlines milestones for medical knowledge and requires regular didactic sessions in residency training. There are many challenges to facilitating active learning in resident conferences, and we need to better understand resident learning preferences and faculty perspectives on facilitating active learning. The goal of this study was to identify challenges to facilitating active learning in resident conferences, both through identifying specific implementation barriers and identifying differences in perspective between faculty and residents on effective teaching and learning strategies. The investigators invited core residency faculty to participate in focus groups. The investigators used a semistructured guide to facilitate discussion about learning preferences and teaching perspectives in the conference setting and used an 'editing approach' within a grounded theory framework to qualitative analysis to code the transcripts and analyze the results. Data were compared to previously collected data from seven resident focus groups. Three focus groups with 20 core faculty were conducted. We identified three domains pertaining to facilitating active learning in resident conferences: barriers to facilitating active learning formats, similarities and differences in faculty and resident learning preferences, and divergence between faculty and resident opinions about effective teaching strategies. Faculty identified several setting, faculty, and resident barriers to facilitating active learning in resident conferences. When compared to residents, faculty expressed similar learning preferences; the main differences were in motivations for conference attendance and type of content. Resident preferences and faculty perspectives differed on the amount of information appropriate for lecture and the role of active participation in resident conferences. This study highlights several challenges to facilitating active learning in resident conferences and provides insights for residency faculty who seek to transform the conference learning environment within their residency program.

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

Knowledge sharing and organizational learning in the context of hospital infection prevention.

PubMed

Rangachari, Pavani

2010-01-01

Recently, hospitals that have been successful in preventing infections have labeled their improvement approaches as either the Toyota Production System (TPS) approach or the Positive Deviance (PD) approach. PD has been distinguished from TPS as being a bottom-up approach to improvement, as against top-down. Facilities that have employed both approaches have suggested that PD may be more effective than TPS for infection prevention. This article integrates organizational learning, institutional, and knowledge network theories to develop a theoretical framework for understanding the structure and evolution of effective knowledge-sharing networks in health care organizations, that is, networks most conducive to learning and improvement. Contrary to arguments put forth by hospital success stories, the framework suggests that networks rich in brokerage and hierarchy (ie, top-down, "TPS-like" structures) may be more effective for learning and improvement in health care organizations, compared with a networks rich in density (ie, bottom-up, "PD-like" structures). The theoretical framework and ensuing analysis help identify several gaps in the literature related to organization learning and improvement in the infection prevention context. This, in turn, helps put forth recommendations for health management research and practice.

Boosting compound-protein interaction prediction by deep learning.

PubMed

Tian, Kai; Shao, Mingyu; Wang, Yang; Guan, Jihong; Zhou, Shuigeng

2016-11-01

The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear and imbalanced nature of biological data, many machine learning approaches have their own limitations. Recently, deep learning techniques show advantages over many state-of-the-art machine learning methods in some applications. In this study, we aim at improving the performance of CPI prediction based on deep learning, and propose a method called DL-CPI (the abbreviation of Deep Learning for Compound-Protein Interactions prediction), which employs deep neural network (DNN) to effectively learn the representations of compound-protein pairs. Extensive experiments show that DL-CPI can learn useful features of compound-protein pairs by a layerwise abstraction, and thus achieves better prediction performance than existing methods on both balanced and imbalanced datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

Teaching EFL Writing: An Approach Based on the Learner's Context Model

ERIC Educational Resources Information Center

Lin, Zheng

2017-01-01

This study aims to examine qualitatively a new approach to teaching English as a foreign language (EFL) writing based on the learner's context model. It investigates the context model-based approach in class and identifies key characteristics of the approach delivered through a four-phase teaching and learning cycle. The model collects research…

Teacher change in implementing a research-developed representation construction pedagogy

NASA Astrophysics Data System (ADS)

Hubber, Peter; Chittleborough, Gail

2016-05-01

The Representations in Learning Science (RiLS) project developed a representation construction approach to teaching and learning in science, which has successfully demonstrated enhanced student learning through sustained engagement with ideas, and enhancement of teachers' pedagogical knowledge and understandings of how knowledge in science is developed and communicated. The current Constructing Representations in Science Pedagogy (CRISP) project aims at wider scale implementation of the representation construction approach. This paper explores a range of issues that confronted four Year-8 teachers in implementing this research-developed approach, such as: preparedness of the teacher in terms of epistemological positioning and positioning as a learner, significant support for planning and modelling by the university expert, and a team ethos where teachers share ideas and plan jointly. The Year-8 teachers implemented a representation construction approach to the teaching of the topic of astronomy. The Interconnected Model of Teacher Growth (IMTG) (Clarke and Hollingworth, Teach. Educ., 18 (2001) 947) was used to analyse the teachers' experience in planning and delivering the teaching sequence. This model was found to be flexible in identifying the experiences of teachers in different situations and useful in identifying issues for implementation of a research-developed pedagogy.

Self-Regulated Learning: Examining the Baccalaureate Millennial Nursing Student's Approach.

PubMed

Robb, Meigan K

2016-01-01

Pre-licensure baccalaureate nursing programs are facing the demand to retain and graduate students with the skills needed for the complex health care environment. Nursing faculty are challenged to identify the best pedagogical methods for educating the current generation of students. The influence of student-centered approaches is documented in the literature. However, the effective use of these methods requires a collaborative partnership. The cognitive, self-regulated approaches used by millennial nursing students is not well understood. This article describes the findings of a study that examined the relationship between self-regulated approaches to learning, self-efficacy, independent study behaviors, and grade point average.

Individual and Contextual Factors Influencing Engagement in Learning Activities after Errors at Work: A Replication Study in a German Retail Bank

ERIC Educational Resources Information Center

Leicher, Veronika; Mulder, Regina H.

2016-01-01

Purpose: The purpose of this replication study is to identify relevant individual and contextual factors influencing learning from errors at work and to determine if the predictors for learning activities are the same for the domains of nursing and retail banking. Design/methodology/approach: A cross-sectional replication study was carried out in…

A Study to Determine Non-Academic Traits of a Successful Student in an Open Learning Center Environment at John Wood Community College.

ERIC Educational Resources Information Center

Kronquist, Shirley; And Others

John Wood Community College's Open Learning Center (OLC) offers an alternative to traditional classroom approaches using one-to-one instruction, a competency-based learning format, and flexible scheduling. Due to concern over the high attrition rate in OLC courses, a study was conducted to identify the characteristics and variables contributing to…

Obstaculos al aprendizaje--obstaculos a la ensenanza en contextos (Barriers to Learning--Barriers to Teaching in Multicultural Contexts). Papers on Teacher Training and Multicultural/Intercultural Education 25.

ERIC Educational Resources Information Center

Gagliardi, Raul

This study focused on identifying learning difficulties with a view to incorporating both understanding of those difficulties and methods for minimizing or neutralizing them in multicultural classroom settings. Discussion gives guidelines for teachers to use in analyzing student concepts and approaches to learning, particularly in the…

Practice guidelines in the context of primary care, learning and usability in the physicians' decision-making process--a qualitative study.

PubMed

Ingemansson, Maria; Bastholm-Rahmner, Pia; Kiessling, Anna

2014-08-20

Decision-making is central for general practitioners (GP). Practice guidelines are important tools in this process but implementation of them in the complex context of primary care is a challenge. The purpose of this study was to explore how GPs approach, learn from and use practice guidelines in their day-to-day decision-making process in primary care. A qualitative approach using focus-group interviews was chosen in order to provide in-depth information. The participants were 22 GPs with a median of seven years of experience in primary care, representing seven primary healthcare centres in Stockholm, Sweden in 2011. The interviews focused on how the GPs use guidelines in their decision-making, factors that influence their decision how to approach these guidelines, and how they could encourage the learning process in routine practice.Data were analysed by qualitative content analysis. Meaning units were condensed and grouped in categories. After interpreting the content in the categories, themes were created. Three themes were conceptualized. The first theme emphasized to use guidelines by interactive contextualized dialogues. The categories underpinning this theme: 1. Feedback by peer-learning 2. Feedback by collaboration, mutual learning, and equality between specialties, identified important ways to achieve this learning dialogue. Confidence was central in the second theme, learning that establishes confidence to provide high quality care. Three aspects of confidence were identified in the categories of this theme: 1. Confidence by confirmation, 2. Confidence by reliability and 3. Confidence by evaluation of own results. In the third theme, learning by use of relevant evidence in the decision-making process, we identified two categories: 1. Design and lay-out visualizing the evidence 2. Accessibility adapted to the clinical decision-making process as prerequisites for using the practice guidelines. Decision-making in primary care is a dual process that involves use of intuitive and analytic thinking in a balanced way in order to provide high quality care. Key aspects of effective learning in this clinical decision-making process were: contextualized dialogue, which was based on the GPs' own experiences, feedback on own results and easy access to short guidelines perceived as trustworthy.

Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective.

PubMed

Kim, Yong-Ku; Na, Kyoung-Sae

2018-01-03

Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic burden. There are various methodological approaches for identifying the underlying mechanisms of the etiology, symptomatology, and therapeutics of mood disorders; however, neuroimaging studies have provided the most direct evidence for mood disorder neural substrates by visualizing the brains of living individuals. The prefrontal cortex, hippocampus, amygdala, thalamus, ventral striatum, and corpus callosum are associated with depression and bipolar disorder. Identifying the distinct and common contributions of these anatomical regions to depression and bipolar disorder have broadened and deepened our understanding of mood disorders. However, the extent to which neuroimaging research findings contribute to clinical practice in the real-world setting is unclear. As traditional or non-machine learning MRI studies have analyzed group-level differences, it is not possible to directly translate findings from research to clinical practice; the knowledge gained pertains to the disorder, but not to individuals. On the other hand, a machine learning approach makes it possible to provide individual-level classifications. For the past two decades, many studies have reported on the classification accuracy of machine learning-based neuroimaging studies from the perspective of diagnosis and treatment response. However, for the application of a machine learning-based brain MRI approach in real world clinical settings, several major issues should be considered. Secondary changes due to illness duration and medication, clinical subtypes and heterogeneity, comorbidities, and cost-effectiveness restrict the generalization of the current machine learning findings. Sophisticated classification of clinical and diagnostic subtypes is needed. Additionally, as the approach is inevitably limited by sample size, multi-site participation and data-sharing are needed in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

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 Guided Inquiry Activity for Teaching Ligand Field Theory

ERIC Educational Resources Information Center

Johnson, Brian J.; Graham, Kate J.

2015-01-01

This paper will describe a guided inquiry activity for teaching ligand field theory. Previous research suggests the guided inquiry approach is highly effective for student learning. This activity familiarizes students with the key concepts of molecular orbital theory applied to coordination complexes. Students will learn to identify factors that…

The Role of Principals in Professional Learning Communities

ERIC Educational Resources Information Center

Buttram, Joan L.; Farley-Ripple, Elizabeth N.

2016-01-01

The purpose of this article is to identify how principals shape the adoption and implementation of professional learning communities. The study employed a sequential mixed-methods approach in which interviews, observations, and document analysis informed survey design. Teachers were surveyed in four elementary schools about the practices and…

Unseen and Unheard? Women Managers and Organizational Learning

ERIC Educational Resources Information Center

Martin, Lynn M.; Lord, Gemma; Warren-Smith, Izzy

2018-01-01

Purpose: This paper aims to use (in)visibility as a lens to understand the lived experience of six women managers in the headquarters of a large multinational organization in the UK to identify how "gender" is expressed in the context of organizational learning. Design/methodology/approach: The researchers take a phenomenological…

Wikipedia Writing as Praxis: Computer-Mediated Socialization of Second-Language Writers

ERIC Educational Resources Information Center

King, Brian W.

2015-01-01

This study explores the writing of Wikipedia articles as a form of authentic writing for learners of English in Hong Kong. Adopting "Second Language Socialization and Language Learning & Identity" approaches to language learning inquiry, it responds to an identified shortage of research on computer-mediated language socialization.…

Intersectional Computer-Supported Collaboration in Business Writing: Learning through Challenged Performance

ERIC Educational Resources Information Center

Remley, Dirk

2009-01-01

Carter (2007) identifies four meta-genres associated with writing activities that can help students learn discipline-specific writing skills relative to standards within a given field: these include problem solving, empirical approaches to analysis, selection of sources to use within research, and production of materials that meet accepted…

Identifying Key Components of Teaching and Learning in a STEM School

ERIC Educational Resources Information Center

Morrison, Judith; Roth McDuffie, Amy; French, Brian

2015-01-01

This study was conducted at an innovative science, technology, engineering, and mathematics high school, providing a rich contextual description of the teaching and learning at the school, specifically focusing on problem solving and inquiry approaches, and students' motivation, social interactions, and collaborative work. Data were collected…

Personal Factors Impacting College Student Success: Constructing College Learning Effectiveness Inventory (CLEI)

ERIC Educational Resources Information Center

Kim, Eunhee; Newton, Fred B.; Downey, Ronald G.; Benton, Stephen L.

2010-01-01

The College Learning Effectiveness Inventory, a new assessment tool identifying personal variables important to college student success, was constructed using empirical approaches grounded in a conceptual model. The exploratory and confirmatory studies revealed the six-underlying factors: Academic Self-Efficacy, Organization and Attention to…

Dimensional Integration of Assessment Outcomes with Intervention Services for Children with Specific Learning Disabilities

ERIC Educational Resources Information Center

Decker, Scott

2012-01-01

This article reviews critical issues with integrating different procedures for identifying children with specific learning disabilities permitted in the federal regulations of the 2004 Individual With Disabilities Education Act 2004. Theoretical differences between behavioral approaches that focus on recording behavioral responses based on…

Rote Memorization of Vocabulary and Vocabulary Development

ERIC Educational Resources Information Center

Yang, Weidong; Dai, Weiping

2011-01-01

Rote memorization of vocabulary has long been a common way for Chinese students to learn lexical items. Cultural, educational background and traditional teaching practice in China are identified to be the factors that contribute to many students' heavy reliance on memorization as their sole approach to vocabulary learning. In addition to rote…

A Low-Tech, Hands-On Approach To Teaching Sorting Algorithms to Working Students.

ERIC Educational Resources Information Center

Dios, R.; Geller, J.

1998-01-01

Focuses on identifying the educational effects of "activity oriented" instructional techniques. Examines which instructional methods produce enhanced learning and comprehension. Discusses the problem of learning "sorting algorithms," a major topic in every Computer Science curriculum. Presents a low-tech, hands-on teaching method for sorting…

Predicting Contextual Informativeness for Vocabulary Learning

ERIC Educational Resources Information Center

Kapelner, Adam; Soterwood, Jeanine; Nessaiver, Shalev; Adlof, Suzanne

2018-01-01

Vocabulary knowledge is essential to educational progress. High quality vocabulary instruction requires supportive contextual examples to teach word meaning and proper usage. Identifying such contexts by hand for a large number of words can be difficult. In this work, we take a statistical learning approach to engineer a system that predicts…

Effectiveness of Problem-Based Learning in Introductory Business Courses

ERIC Educational Resources Information Center

Hartman, Katherine B.; Moberg, Christopher R.; Lambert, Jamie M.

2013-01-01

Problem-based learning (PBL) is an instructional approach that provides learners with opportunities to identify solutions to ill-structured, real-world problems. Previous research provides evidence to support claims about the positive effects of PBL on cognitive skill development and knowledge retention. This study contributes to existing…

Knowledge Strategies for Enhancing School Learning Capacity

ERIC Educational Resources Information Center

Cheng, Eric

2012-01-01

Purpose: The purpose of this paper is to identify the knowledge strategies applied in aided secondary schools in Hong Kong and to explore the predictive relationship between knowledge strategies and school learning capacity. Design/methodology/approach: A cross-sectional quantitative survey was designed to collect data from 427 teachers at 15…

Metacognition in Upper-Division Biology Students: Awareness Does Not Always Lead to Control

PubMed Central

Dye, Kathryn Morris; Stanton, Julie Dangremond

2017-01-01

Students with awareness and control of their own thinking can learn more and perform better than students who are not metacognitive. Metacognitive regulation is how you control your thinking in order to learn. It includes the skill of evaluation, which is the ability to appraise your approaches to learning and then modify future plans based on those appraisals. We asked when, why, and how upper-division biology students evaluated their approaches to learning. We used self-evaluation assignments to identify students with potentially high metacognition and conducted semistructured interviews to collect rich qualitative data from them. Through content analysis, we found that students evaluated their approaches to learning when their courses presented novel challenges. Most students evaluated in response to an unsatisfactory grade. While evaluating study strategies, many students considered performance and learning simultaneously. We gained insights on the barriers students face when they try to change their approaches to learning based on their evaluations. A few students continued to use ineffective study strategies even though they were aware of the ineffectiveness of those strategies. A desire to avoid feeling uncomfortable was the primary reason they avoided strategies that they knew were more effective. We examined the behavioral change literature to help interpret these findings. PMID:28495935

A Bridge to Active Learning: A Summer Bridge Program Helps Students Maximize Their Active-Learning Experiences and the Active-Learning Experiences of Others

PubMed Central

Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.

2017-01-01

National calls to improve student academic success in college have sparked the development of bridge programs designed to help students transition from high school to college. We designed a 2-week Summer Bridge program that taught introductory biology content in an active-learning way. Through a set of exploratory interviews, we unexpectedly identified that Bridge students had developed sophisticated views of active learning, even though this was not an explicit goal of the program. We conducted an additional set of semistructured interviews that focused on active learning and compared the interviews of Bridge students with those from non-Bridge students who had been eligible for but did not participate in the program. We used the constant comparative method to identify themes from the interviews. We found that Bridge students perceived that, because they knew how to approach active learning and viewed it as important, they benefited more from active learning in introductory biology than non-Bridge students. Specifically, Bridge students seemed to be more aware of their own learning gains from participating in active learning. Compared with the majority of non-Bridge students, the majority of Bridge students described using a greater variety of strategies to maximize their experiences in active learning. Finally, in contrast to non-Bridge students, Bridge students indicated that they take an equitable approach to group work. These findings suggest that we may be able to prime students to maximize their own and other’s experiences in active learning. PMID:28232588

Contemporary Issues in Group Learning in Undergraduate Science Classrooms: A Perspective from Student Engagement.

PubMed

Hodges, Linda C

2018-06-01

As the use of collaborative-learning methods such as group work in science, technology, engineering, and mathematics classes has grown, so has the research into factors impacting effectiveness, the kinds of learning engendered, and demographic differences in student response. Generalizing across the range of this research is complicated by the diversity of group-learning approaches used. In this overview, I discuss theories of how group-work formats support or hinder learning based on the ICAP (interactive, constructive, active, passive) framework of student engagement. I then use this model to analyze current issues in group learning, such as the nature of student discourse during group work, the role of group learning in making our classrooms inclusive, and how classroom spaces factor into group learning. I identify key gaps for further research and propose implications from this research for teaching practice. This analysis helps identify essential, effective, and efficient features of group learning, thus providing faculty with constructive guidelines to support their work and affirm their efforts.

A Case-Based, Problem-Based Learning Approach to Prepare Master of Public Health Candidates for the Complexities of Global Health

PubMed Central

Winskell, Kate; McFarland, Deborah A.; del Rio, Carlos

2015-01-01

Global health is a dynamic, emerging, and interdisciplinary field. To address current and emerging global health challenges, we need a public health workforce with adaptable and collaborative problem-solving skills. In the 2013–2014 academic year, the Hubert Department of Global Health at the Rollins School of Public Health–Emory University launched an innovative required core course for its first-year Master of Public Health students in the global health track. The course uses a case-based, problem-based learning approach to develop global health competencies. Small teams of students propose solutions to these problems by identifying learning issues and critically analyzing and synthesizing new information. We describe the course structure and logistics used to apply this approach in the context of a large class and share lessons learned. PMID:25706029

A review of active learning approaches to experimental design for uncovering biological networks

PubMed Central

2017-01-01

Various types of biological knowledge describe networks of interactions among elementary entities. For example, transcriptional regulatory networks consist of interactions among proteins and genes. Current knowledge about the exact structure of such networks is highly incomplete, and laboratory experiments that manipulate the entities involved are conducted to test hypotheses about these networks. In recent years, various automated approaches to experiment selection have been proposed. Many of these approaches can be characterized as active machine learning algorithms. Active learning is an iterative process in which a model is learned from data, hypotheses are generated from the model to propose informative experiments, and the experiments yield new data that is used to update the model. This review describes the various models, experiment selection strategies, validation techniques, and successful applications described in the literature; highlights common themes and notable distinctions among methods; and identifies likely directions of future research and open problems in the area. PMID:28570593

An adaptive learning control system for large flexible structures

NASA Technical Reports Server (NTRS)

Thau, F. E.

1985-01-01

The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

How GPs learn.

PubMed

MacLeod, Sheona

2009-07-01

As the requirements for the revalidation of general practitioners (GPs) unfold, there is an increasing emphasis on demonstrating effective continued medical education (CME) based on identified learning needs. This qualitative study aimed to promote understanding of how GPs currently approach their learning. The behaviour of one group of GPs was studied to explore how they assessed and met individual learning needs. The GPs studied showed a pragmatic approach, valuing learning that gave them practical advice and instant access to information for patient-specific problems. The main driver for the GPs' learning was discomfort during their daily work if a possible lack of knowledge or skills was perceived. However, some learning benchmarked current good practice or ensured continued expertise. Learning purely for interest was also described. The GPs in this study all demonstrated a commitment to personal learning, although they were not yet thinking about demonstrating the effectiveness of this for revalidation. The GPs prioritised their learning needs and were beginning to use some objective assessment methods to do this and the GP appraisal process was found to have a mainly positive effect on learning.

A New Approach to Teaching Biomechanics Through Active, Adaptive, and Experiential Learning.

PubMed

Singh, Anita

2017-07-01

Demand of biomedical engineers continues to rise to meet the needs of healthcare industry. Current training of bioengineers follows the traditional and dominant model of theory-focused curricula. However, the unmet needs of the healthcare industry warrant newer skill sets in these engineers. Translational training strategies such as solving real world problems through active, adaptive, and experiential learning hold promise. In this paper, we report our findings of adding a real-world 4-week problem-based learning unit into a biomechanics capstone course for engineering students. Surveys assessed student perceptions of the activity and learning experience. While students, across three cohorts, felt challenged to solve a real-world problem identified during the simulation lab visit, they felt more confident in utilizing knowledge learned in the biomechanics course and self-directed research. Instructor evaluations indicated that the active and experiential learning approach fostered their technical knowledge and life-long learning skills while exposing them to the components of adaptive learning and innovation.

Teaching Research Methods in Communication Disorders: "A Problem-Based Learning Approach"

ERIC Educational Resources Information Center

Greenwald, Margaret L.

2006-01-01

A critical professional issue in speech-language pathology and audiology is the current shortage of researchers. In this context, the most effective methods for training graduate students in research must be identified and implemented. This article describes a problem-based approach to teaching research methods. In this approach, the instructor…

Developing and Applying Green Building Technology in an Indigenous Community: An Engaged Approach to Sustainability Education

ERIC Educational Resources Information Center

Riley, David R.; Thatcher, Corinne E.; Workman, Elizabeth A.

2006-01-01

Purpose: This paper aims to disseminate an innovative approach to sustainability education in construction-related fields in which teaching, research, and service are integrated to provide a unique learning experience for undergraduate students, faculty members, and community partners. Design/methodology/approach: The paper identifies the need for…

Conserving the Circus? An Alternative Approach to Teaching and Learning about Energy.

ERIC Educational Resources Information Center

Brook, Angela J.; Wells, Peter

1988-01-01

Critiques the "energy circus," an approach to the introduction of ideas of energy transformation and conservation which is in common use in secondary schools. Identifies some practical and conceptual difficulties and outlines an alternative approach used in introducing ideas about energy using real devices and arrow notation. (CW)

An Inquiry-Based Approach of Traditional "Step-by-Step" Experiments

ERIC Educational Resources Information Center

Szalay, L.; Tóth, Z.

2016-01-01

This is the start of a road map for the effective introduction of inquiry-based learning in chemistry. Advantages of inquiry-based approaches to the development of scientific literacy are widely discussed in the literature. However, unless chemistry educators take account of teachers' reservations and identified disadvantages such approaches will…

Using research evidence to inform staff learning needs in cross-cultural communication in aged care homes.

PubMed

Gillham, David; De Bellis, Anita; Xiao, Lily; Willis, Eileen; Harrington, Ann; Morey, Wendy; Jeffers, Lesley

2018-04-01

Developed countries worldwide are facing an unprecedented demand for aged care services, with recent migrants of diverse linguistic and cultural backgrounds increasingly recruited as care workers while at the same time there is growing cultural diversity among aged care residents. This situation is compounded by rapidly changing technology and varied educational levels of care workers from diverse backgrounds. The objectives were threefold: to identify staff learning needs to enable them to provide high-quality cross-cultural care; to improve team cohesion; and identify preferred learning approaches. An interpretive qualitative study utilising focus group and interview data informed the development of an education resource. Fifty six care workers from four residential aged care facilities participated in either focus groups or interviews conducted in private meeting rooms within the care facilities. Participants included personal care attendants, registered and clinical nurses, managers, hospitality staff and allied health professionals. Focus group and interview data were categorised and thematically analysed. Data relevant to cross-cultural care, team cohesion and preferred learning approaches informed education resource development, including case studies. Major themes identified the need to promote cultural awareness and understanding, and strategies for cross-cultural care and communication. Themes related to team cohesion demonstrated that staff were already sympathetic and sensitive to cross-cultural issues, and that culturally and linguistically diverse staff add value to the workforce and are supported by the organisation. Staff required clear, uncomplicated education resources to equip them with skills to address problematic cultural situations. Preferred learning approaches varied and highlighted the need for varied educational materials and approaches, as well as time efficient, opportunistic education strategies for the busy workplace. An education package was developed to value cultural diversity in the aged care workplace for staff and residents, and provide an exemplar for evidence informed education. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

PubMed

Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

2015-01-01

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.

Innovative intelligent technology of distance learning for visually impaired people

NASA Astrophysics Data System (ADS)

Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet

2017-12-01

The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV). To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.

A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.

PubMed

Ambastha, Abhinit Kumar; Leong, Tze-Yun

2017-01-01

Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain. The proposed technique has a classification accuracy of 81.79% for AD against healthy subjects using a single modality imaging dataset.

School-community learning partnerships for sustainability: Recommended best practice and reality

NASA Astrophysics Data System (ADS)

Wheeler, Leone; Guevara, Jose Roberto; Smith, Jodi-Anne

2018-05-01

Effective partnerships across different stakeholders are essential to the collaboration required for learning cities to contribute to sustainable development. Through partnerships, formal educational institutions, such as schools and universities, play a vital role in establishing and sustaining learning cities, often by facilitating the meaningful participation of different local community members. The research presented in this article examines the characteristics of effective school-community partnerships in the literature and compares it to the results of a three-year research study which examined 16 case studies of school-community partnerships in the state of Victoria in Australia. Using participatory action research, the researchers identified four approaches to implementing partnerships for sustainability, explored challenges to achieving an idealised partnership, and made recommendations for establishing successful partnership networks. The researchers propose that partnerships be viewed as a dynamic resource rather than merely a transactional arrangement that addresses the identified challenges of time, funding, skills and personnel. Furthermore, the use of "partnership brokers", such as local government or non-government organisations, is recommended to expand the current school-centred approach to partnerships. These insights aim to contribute to providing quality education and lifelong learning through partnerships - outcomes crucial for establishing and sustaining learning cities.

Novice medical students: individual patterns in the use of learning strategies and how they change during the first academic year.

PubMed

Fabry, Götz; Giesler, Marianne

2012-01-01

Adequate use of different learning strategies is one of the most important prerequisites of academic success. The actual use of learning strategies is the result of an interaction between individual and situational variables. Against this background we conducted a longitudinal study with first year medical students to investigate whether individuals show different patterns in their use of learning strategies and whether these patterns change during the first academic year. Medical students (N=175, 58% female) were surveyed three times in their first academic year regarding their use of learning strategies. A hierarchical cluster analysis (Ward) was conducted in order to identify groups of students with different patterns of learning strategies. We identified four different patterns in approaches to learning among novice medical students ("easy-going", "flexible", "problematic" and "hardworking" learners). Compared to their peers, the problematic learners had the worst final school grades. In addition changes in the use of learning strategies were identified, most of them occurred during the first term. Students start their academic studies with different patterns of learning strategies; the characteristics of these patterns change during the first academic year. Further research is necessary to better understand how individual and situational variables determine students' learning.

Novice medical students: Individual patterns in the use of learning strategies and how they change during the first academic year

PubMed Central

Fabry, Götz; Giesler, Marianne

2012-01-01

Background: Adequate use of different learning strategies is one of the most important prerequisites of academic success. The actual use of learning strategies is the result of an interaction between individual and situational variables. Against this background we conducted a longitudinal study with first year medical students to investigate whether individuals show different patterns in their use of learning strategies and whether these patterns change during the first academic year. Methods: Medical students (N=175, 58% female) were surveyed three times in their first academic year regarding their use of learning strategies. A hierarchical cluster analysis (Ward) was conducted in order to identify groups of students with different patterns of learning strategies. Results: We identified four different patterns in approaches to learning among novice medical students (“easy-going”, “flexible”, “problematic” and “hardworking” learners). Compared to their peers, the problematic learners had the worst final school grades. In addition changes in the use of learning strategies were identified, most of them occurred during the first term. Conclusion: Students start their academic studies with different patterns of learning strategies; the characteristics of these patterns change during the first academic year. Further research is necessary to better understand how individual and situational variables determine students’ learning. PMID:22916082

Preliminary Development of the Parent Involvement in Early Learning Scale for Low-Income Families Enrolled in a Child-Development-Focused Home Visiting Program

ERIC Educational Resources Information Center

Manz, Patricia H.; Gernhart, Amanda L.; Bracaliello, Catherine B.; Pressimone, Vanessa J.; Eisenberg, Rachel A.

2014-01-01

Salient early intervention approaches for children below the age of 3 years, such as home visiting, seek to strengthen the pivotal role that parents play in fostering their young children's early learning. Yet, measures that identify and monitor the ways in which low-income parents support toddlers' learning experiences are lacking. Without parent…

Interactive Multimedia Instruction for Training Self-Directed Learning Techniques

DTIC Science & Technology

2016-06-01

feedback and input on the content, format, and pedagogical approach of the lesson. This survey could be e-mailed to the principal ARI researcher for...peers in self-directed learning. Some examples of the metaphorical relationships and common examples woven into this IMI are identified in Table 1...20 Table 1 Metaphorical Relationships and Illustrations Used in Self-Directed Learning Training Military or Common Example Self-Directed

Vocational trainees' views and experiences regarding the learning and teaching of communication skills in general practice.

PubMed

Van Nuland, Marc; Thijs, Gabie; Van Royen, Paul; Van den Noortgate, Wim; Goedhuys, Jo

2010-01-01

To explore the views and experiences of general practice (GP) vocational trainees regarding communication skills (CS) and the teaching and learning of these skills. A purposive sample of second and third (final) year GP trainees took part in six focus group (FG) discussions. Transcripts were coded and analysed in accordance with a grounded theory approach by two investigators using Alas-ti software. Finally results were triangulated by means of semi-structured telephone interviews. The analysis led to three thematic clusters: (1) trainees acknowledge the essential importance of communication skills and identified contextual factors influencing the learning and application of these skills; (2) trainees identified preferences for learning and receiving feedback on their communication skills; and (3) trainees perceived that the assessment of communication skills is subjective. These themes are organised into a framework for a better understanding of trainees' communication skills as part of their vocational training. The framework helps in leading to a better understanding of the way in which trainees learn and apply communication skills. The unique context of vocational training should be taken into account when trainees' communication skills are assessed. The teaching and learning should be guided by a learner-centred approach. The framework is valuable for informing curricular reform and future research.

Creative teaching method as a learning strategy for student midwives: A qualitative study.

PubMed

Rankin, Jean; Brown, Val

2016-03-01

Traditional ways of teaching in Higher Education are enhanced with adult-based approaches to learning within the curriculum. Adult-based learning enables students to take ownership of their own learning, working in independence using a holistic approach. Introducing creative activities promotes students to think in alternative ways to the traditional learning models. The study aimed to explore student midwives perceptions of a creative teaching method as a learning strategy. A qualitative design was used adopting a phenomenological approach to gain the lived experience of students within this learning culture. Purposive sampling was used to recruit student midwives (n=30). Individual interviews were conducted using semi-structured interviews with open-ended questions to gain subjective information. Data were transcribed and analyzed into useful and meaningful themes and emerging themes using Colaizzi's framework for analyzing qualitative data in a logical and systematic way. Over 500 meaningful statements were identified from the transcripts. Three key themes strongly emerged from the transcriptions. These included'meaningful learning','inspired to learn and achieve', and 'being connected'. A deep meaningful learning experience was found to be authentic in the context of theory and practice. Students were inspired to learn and achieve and positively highlighted the safe learning environment. The abilities of the facilitators were viewed positively in supporting student learning. This approach strengthened the relationships and social engagement with others in the peer group and the facilitators. On a less positive note, tensions and conflict were noted in group work and indirect negative comments about the approach from the teaching team. Incorporating creative teaching activities is a positive addition to the healthcare curriculum. Creativity is clearly an asset to the range of contemporary learning strategies. In doing so, higher education will continue to keep abreast of the needs of graduating students in a complex and rapidly changing professional environment. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study.

PubMed

Del Fiol, Guilherme; Michelson, Matthew; Iorio, Alfonso; Cotoi, Chris; Haynes, R Brian

2018-06-25

A major barrier to the practice of evidence-based medicine is efficiently finding scientifically sound studies on a given clinical topic. To investigate a deep learning approach to retrieve scientifically sound treatment studies from the biomedical literature. We trained a Convolutional Neural Network using a noisy dataset of 403,216 PubMed citations with title and abstract as features. The deep learning model was compared with state-of-the-art search filters, such as PubMed's Clinical Query Broad treatment filter, McMaster's textword search strategy (no Medical Subject Heading, MeSH, terms), and Clinical Query Balanced treatment filter. A previously annotated dataset (Clinical Hedges) was used as the gold standard. The deep learning model obtained significantly lower recall than the Clinical Queries Broad treatment filter (96.9% vs 98.4%; P<.001); and equivalent recall to McMaster's textword search (96.9% vs 97.1%; P=.57) and Clinical Queries Balanced filter (96.9% vs 97.0%; P=.63). Deep learning obtained significantly higher precision than the Clinical Queries Broad filter (34.6% vs 22.4%; P<.001) and McMaster's textword search (34.6% vs 11.8%; P<.001), but was significantly lower than the Clinical Queries Balanced filter (34.6% vs 40.9%; P<.001). Deep learning performed well compared to state-of-the-art search filters, especially when citations were not indexed. Unlike previous machine learning approaches, the proposed deep learning model does not require feature engineering, or time-sensitive or proprietary features, such as MeSH terms and bibliometrics. Deep learning is a promising approach to identifying reports of scientifically rigorous clinical research. Further work is needed to optimize the deep learning model and to assess generalizability to other areas, such as diagnosis, etiology, and prognosis. ©Guilherme Del Fiol, Matthew Michelson, Alfonso Iorio, Chris Cotoi, R Brian Haynes. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.06.2018.

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome.

PubMed

Higuera, Clara; Gardiner, Katheleen J; Cios, Krzysztof J

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets.

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

PubMed Central

Higuera, Clara; Gardiner, Katheleen J.; Cios, Krzysztof J.

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets. PMID:26111164

Workplace Learning for the Public Good: Implementation of a Standardized, Competency-Based Curriculum in Texas WIC

ERIC Educational Resources Information Center

Kessler, Seth A.; Horton, Karissa D.; Gottlieb, Nell H.; Atwood, Robin

2012-01-01

Purpose: The purpose of this study is to describe preceptors' implementation experiences after implementing a workplace learning program in Texas WIC (women, infant, and children) agencies and identify implementation best practices. Design/methodology/approach: This research used qualitative description methodology. Data collection consisted of 11…

A Spreadsheet-Based Visualized Mindtool for Improving Students' Learning Performance in Identifying Relationships between Numerical Variables

ERIC Educational Resources Information Center

Lai, Chiu-Lin; Hwang, Gwo-Jen

2015-01-01

In this study, a spreadsheet-based visualized Mindtool was developed for improving students' learning performance when finding relationships between numerical variables by engaging them in reasoning and decision-making activities. To evaluate the effectiveness of the proposed approach, an experiment was conducted on the "phenomena of climate…

Leadership through Fellowship: Distributed Leadership in a Professional Recognition Scheme for University Educators

ERIC Educational Resources Information Center

Beckmann, Elizabeth A.

2017-01-01

Researchers in the field of teaching and learning in higher education have identified concerns with top-down leadership models. Distributed (or shared) leadership approaches may provide more successful engagement with institutional change agendas, and provide more options to reward and recognise staff leading teaching and learning initiatives.…

A Socio-Cognitive Approach to Knowledge Construction in Design Studio through Blended Learning

ERIC Educational Resources Information Center

Kocaturk, Tuba

2017-01-01

This paper results from an educational research project that was undertaken by the School of Architecture, at the University of Liverpool funded by the Higher Education Academy in UK. The research explored technology driven shifts in architectural design studio education, identified their cognitive effects on design learning and developed an…

Problem Solving Learning Environments and Assessment: A Knowledge Space Theory Approach

ERIC Educational Resources Information Center

Reimann, Peter; Kickmeier-Rust, Michael; Albert, Dietrich

2013-01-01

This paper explores the relation between problem solving learning environments (PSLEs) and assessment concepts. The general framework of evidence-centered assessment design is used to describe PSLEs in terms of assessment concepts, and to identify similarities between the process of assessment design and of PSLE design. We use a recently developed…

Transforming Traditional Lectures into Problem-Based Blended Learning: Challenges and Experiences

ERIC Educational Resources Information Center

Dalsgaard, Christian; Godsk, Mikkel

2007-01-01

This paper presents our experiences and the challenges identified in transforming traditional lecture-based modules at a university into problem-based blended learning within a social constructivist approach. Our experiment was, among other factors, motivated by an urgent need to meet new curriculum requirements by reducing the lecturing time in a…

Evaluating What Works in Blended Learning

ERIC Educational Resources Information Center

Education Week, 2012

2012-01-01

Blended learning--the mix of virtual education and face-to-face instruction--is evolving quickly in schools across the country, generating a variety of different models. This special report, the second in a three-part 2012-13 series on virtual education, examines several of those approaches and aims to identify what is working and where…

Valuing the Adult Learner in E-Learning: Part One--A Conceptual Model for Corporate Settings

ERIC Educational Resources Information Center

Waight, Consuelo L.; Stewart, Barbara L.

2005-01-01

Purpose: To illustrate how the interdependence among four championing factors, five antecedents, and four moderators affect companies' efforts in valuing the adult learner in e-learning. Design/methodology/approach: A literature review was conducted to identify the championing factors, antecedents, and moderators that can assist teams in designing…

Matching Learning Style Preferences with Suitable Delivery Methods on Textile Design Programmes

ERIC Educational Resources Information Center

Sayer, Kate; Studd, Rachel

2006-01-01

Textile design is a subject that encompasses both design and technology; aesthetically pleasing patterns and forms must be set within technical parameters to create successful fabrics. When considering education methods in design programmes, identifying the most relevant learning approach is key to creating future successes. Yet are the most…

Innovation Need Survey: Implementing a Technology Tool to Improve Early Data-Based Decisions to Address and Prevent Learning Disabilities. Technical Report #1602

ERIC Educational Resources Information Center

Irvin, P. Shawn; Pilger, Marissa; Sáez, Leilani; Alonzo, Julie

2016-01-01

Identifying and measuring indicators of learning difficulties among young children and implementing effective instructional approaches are complicated, particularly during the transition to kindergarten. Purposeful school-based transition policies and practices support teacher and school decision-making and, thus, can ease the…

Work-Integrated Learning and Professional Accreditation Policies: An Environmental Health Higher Education Perspective

ERIC Educational Resources Information Center

Dunn, Louise; Nicholson, Rosemary; Ross, Kirstin; Bricknell, Lisa; Davies, Belinda; Hannelly, Toni; Lampard, Jane-Louise; Murray, Zoe; Oosthuizen, Jacques; Roiko, Anne; Wood, James

2018-01-01

The introduction of a new work-integrated learning (WIL) policy for university environmental health education programs seeking professional accreditation identified a number of problems. This included how to evaluate the acceptability of differing approaches to WIL for course accreditation purposes and a need to develop an agreed understanding of…

Towards Next Generation Activity-Based Learning Systems

ERIC Educational Resources Information Center

Sampson, Demetrios G.; Karampiperis, Pythagoras

2006-01-01

The need for e-learning systems that support a diverse set of pedagogical requirements has been identified as an important issue in web-based education. Until now, significant research and development effort has been devoted to aiming towards web-based educational systems tailored to specific pedagogical approaches. The most advanced of them are…

Empowering At-Risk Students through Appreciative Inquiry

ERIC Educational Resources Information Center

San Martin, Teresa L.; Calabrese, Raymond L.

2011-01-01

Purpose: The purpose of this study is to identify how at-risk high school students in an alternative school describe how they best learn and to extrapolate their preferred learning practices to improve teacher pedagogical practices. Design/methodology/approach: The authors used a qualitative case study design to facilitate the first two stages of…

School Innovation: The Mutual Impacts of Organizational Learning and Creativity

ERIC Educational Resources Information Center

McCharen, Belinda; Song, JiHoon; Martens, Jon

2011-01-01

The primary aim of this research is to identify cultural determinants of organizational learning and knowledge creation practices, which could be the driving factors for the innovation process in school settings (Mulford, 1998; Silins et al., 2002). A conceptual process model for school innovation was developed. In contrast to previous approaches,…

An Alternative Approach to Identifying Students with Learning Disabilities in Australian Schools

ERIC Educational Resources Information Center

Skues, Jason L.; Cunningham, Everarda G.

2013-01-01

This study examined the validity of using teacher-administered educational and intelligence tests to screen students for learning disabilities (LDs). Twenty-seven Technical and Further Education (TAFE) students from regional Victoria who were enrolled in a program that was designed to reconnect school dropouts with education via TAFE participated…

Use of Case Studies for Stimulating Thinking and Learning.

ERIC Educational Resources Information Center

Zeakes, Samuel J.

Noting that a case-study approach can stimulate student thinking and learning, this paper describes how students in a writing-intensive course on parasitology wrote brief medical case studies of parasites already studied for other students to read, evaluate, and identify the parasite. The paper presents a brief description of the course, an…

An Approach to Meeting the Needs of Medical Students with Learning Disabilities.

ERIC Educational Resources Information Center

Walters, Janice A.; Croen, Lila G.

1993-01-01

A study at the Albert Einstein College of Medicine (Yeshiva University, New York) has identified students from each medical class with previously unidentified learning disabilities. In three case studies, the importance of early identification and support is illustrated. In each case, dramatic improvement occurred with student awareness and…

Introducing a technology-enabled problem-based learning approach into a health informatics curriculum.

PubMed

Green, Carolyn J; van Gyn, Geraldine H; Moehr, Jochen R; Lau, Francis Y; Coward, Patricia M

2004-03-18

To investigate the effect on learner satisfaction of introducing a technology-enabled problem-based learning (PBL) approach into a health informatics curriculum. Course redesign was undertaken to prepare students for three 4-month work terms and a rapidly changing professional environment upon graduation. Twenty-six Canadian undergraduate students of a redesigned course in biomedical fundamentals completed a midterm questionnaire in 2002. Eight of these students participated in a focus group. Students agreed that seven of nine functions provided by the web-based online course management system enhanced their learning: private email (92.3%), calendaring (88.5%), course notes (88.5%), discussion forums (84.5%), online grades (84.5%) assignment descriptions (80.8%) and online quizzes (80.8%). Although students agreed that two PBL activities enhanced learning (learning to present information) (84.5%) and learning to identify information needed (73.1%), the majority of students (69.2%) expressed a preference for the traditional lecture approach over the PBL approach. Students reported feeling uncertain of what was required of them and related anxiety accounted for most of the negative feedback. These findings give us clear goals for improvement in the course beginning with a comprehensive, carefully guided introduction to the processes of PBL. The positive trends are encouraging for the use of web-enabled courseware and for the further development of the PBL approach.

Exploring student learning profiles in algebra-based studio physics: A person-centered approach

NASA Astrophysics Data System (ADS)

Pond, Jarrad W. T.; Chini, Jacquelyn J.

2017-06-01

In this study, we explore the strategic self-regulatory and motivational characteristics of students in studio-mode physics courses at three universities with varying student populations and varying levels of success in their studio-mode courses. We survey students using questions compiled from several existing questionnaires designed to measure students' study strategies, attitudes toward and motivations for learning physics, organization of scientific knowledge, experiences outside the classroom, and demographics. Using a person-centered approach, we utilize cluster analysis methods to group students into learning profiles based on their individual responses to better understand the strategies and motives of algebra-based studio physics students. Previous studies have identified five distinct learning profiles across several student populations using similar methods. We present results from first-semester and second-semester studio-mode introductory physics courses across three universities. We identify these five distinct learning profiles found in previous studies to be present within our population of introductory physics students. In addition, we investigate interactions between these learning profiles and student demographics. We find significant interactions between a student's learning profile and their experience with high school physics, major, gender, grade expectation, and institution. Ultimately, we aim to use this method of analysis to take the characteristics of students into account in the investigation of successful strategies for using studio methods of physics instruction within and across institutions.

Investigating the Language of Engineering Education

NASA Astrophysics Data System (ADS)

Variawa, Chirag

A significant part of professional communication development in engineering is the ability to learn and understand technical vocabulary. Mastering such vocabulary is often a desired learning outcome of engineering education. In promoting this goal, this research investigates the development of a tool that creates wordlists of characteristic discipline-specific vocabulary for a given course. These wordlists explicitly highlight requisite vocabulary learning and, when used as a teaching aid, can promote greater accessibility in the learning environment. Literature, including work in higher education, diversity and language learning, suggest that designing accessible learning environments can increase the quality of instruction and learning for all students. Studying the student/instructor interface using the framework of Universal Instructional Design identified vocabulary learning as an invisible barrier in engineering education. A preliminary investigation of this barrier suggested that students have difficulty assessing their understanding of technical vocabulary. Subsequently, computing word frequency on engineering course material was investigated as an approach for characterizing this barrier. However, it was concluded that a more nuanced method was necessary. This research program was built on previous work in the fields of linguistics and computer science, and lead to the design of an algorithm. The developed algorithm is based on a statistical technique called, Term Frequency-Inverse Document Frequency. Comparator sets of documents are used to hierarchically identify characteristic terms on a target document, such as course materials from a previous term of study. The approach draws on a standardized artifact of the engineering learning environment as its dataset; a repository of 2254 engineering final exams from the University of Toronto, to process the target material. After producing wordlists for ten courses, with the goal of highlighting characteristic discipline-specific terms, the effectiveness of the approach was evaluated by comparing the computed results to the judgment of subject-matter experts. The overall data show a good correlation between the program and the subject-matter experts. The results indicated a balance between accuracy and feasibility, and suggested that this approach could mimic subject-matter expertise to create a list discipline-specific vocabulary from course materials.

A Perceptuo-Cognitive-Motor Approach to the Special Child.

ERIC Educational Resources Information Center

Kornblum, Rena Beth

A movement therapist reviews ways in which a perceptuo-cognitive approach can help handicapped children in learning and in social adjustment. She identifies specific auditory problems (hearing loss, sound-ground confusion, auditory discrimination, auditory localization, auditory memory, auditory sequencing), visual problems (visual acuity,…

Machine Learning Approaches for Predicting Human Skin Sensitization Hazard

EPA Science Inventory

One of ICCVAM’s top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary for a substance to elicit a skin sensitization reaction suggests that no single in chemico, in vit...

Analysis of a physics teacher's pedagogical `micro-actions' that support 17-year-olds' learning of free body diagrams via a modelling approach

NASA Astrophysics Data System (ADS)

Tay, Su Lynn; Yeo, Jennifer

2018-01-01

Great teaching is characterised by the specific actions a teacher takes in the classroom to bring about learning. In the context of model-based teaching (MBT), teachers' difficulty in working with students' models that are not scientifically consistent is troubling. To address this problem, the aim of this study is to identify the pedagogical micro-actions to support the development of scientific models and modelling skills during the evaluation and modification stages of MBT. Taking the perspective of pedagogical content knowing (PCKg), it identifies these micro-actions as an in-situ, dynamic transformation of knowledges of content, pedagogy, student and environment context. Through a case study approach, a lesson conducted by an experienced high-school physics teacher was examined. Audio and video recordings of the lesson contributed to the data sources. Taking a grounded approach in the analysis, eight pedagogical micro-actions enacted by the teacher were identified, namely 'clarification', 'evaluation', 'explanation', 'modification', 'exploration', 'referencing conventions', 'focusing' and 'meta-representing'. These micro-actions support students' learning related to the conceptual, cognitive, discursive and epistemological aspects of modelling. From the micro-actions, we identify the aspects of knowledges of PCKg that teachers need in order to competently select and enact these micro-actions. The in-situ and dynamic transformation of these knowledges implies that professional development should also be situated in the context in which these micro-actions are meaningful.

Candidate gene prioritization by network analysis of differential expression using machine learning approaches

PubMed Central

2010-01-01

Background Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals. To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network. Results We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (Simple Expression Ranking). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the Heat Kernel Diffusion Ranking leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%. Conclusion In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype. PMID:20840752

An exploration of the factors that contribute to learning satisfaction of first-year anatomy and physiology students.

PubMed

Eagleton, Saramarie

2015-09-01

Lecturers have reverted to using a "blended" approach when teaching anatomy and physiology. Student responses as to how this contributes to their learning satisfaction were investigated using a self-administered questionnaire. The questionnaire consisted of closed- and open-ended questions that were based on three determinants of learning satisfaction: perceived course learnability, learning community support, and perceived learning effectiveness. Regarding course learnability, students responded positively on questions regarding the relevance of the subject for their future careers. However, students identified a number of distractions that prevented them from paying full attention to their studies. As far as learning community support was concerned, respondents indicated that they were more comfortable asking a peer for support if they were unsure of concepts than approaching the lecturing staff. Most of the students study in their second language, and this was identified as a stumbling block for success. There was a difference in opinion among students regarding the use of technology for teaching and learning of anatomy and physiology. From students' perceptions regarding learning effectiveness, it became clear that students' expectations of anatomy and physiology were unrealistic; they did not expect the module to be so comprehensive. Many of the students were also "grade oriented" rather than "learning oriented" as they indicated that they were more concerned about results than "owning" the content of the module. Asking students to evaluate aspects of the teaching and learning process have provided valuable information to improve future offerings of anatomy and physiology. Copyright © 2015 The American Physiological Society.

Aligning Theory and Design: The Development of an Online Learning Intervention to Teach Evidence-based Practice for Maximal Reach.

PubMed

Delagran, Louise; Vihstadt, Corrie; Evans, Roni

2015-09-01

Online educational interventions to teach evidence-based practice (EBP) are a promising mechanism for overcoming some of the barriers to incorporating research into practice. However, attention must be paid to aligning strategies with adult learning theories to achieve optimal outcomes. We describe the development of a series of short self-study modules, each covering a small set of learning objectives. Our approach, informed by design-based research (DBR), involved 6 phases: analysis, design, design evaluation, redesign, development/implementation, and evaluation. Participants were faculty and students in 3 health programs at a complementary and integrative educational institution. We chose a reusable learning object approach that allowed us to apply 4 main learning theories: events of instruction, cognitive load, dual processing, and ARCS (attention, relevance, confidence, satisfaction). A formative design evaluation suggested that the identified theories and instructional approaches were likely to facilitate learning and motivation. Summative evaluation was based on a student survey (N=116) that addressed how these theories supported learning. Results suggest that, overall, the selected theories helped students learn. The DBR approach allowed us to evaluate the specific intervention and theories for general applicability. This process also helped us define and document the intervention at a level of detail that covers almost all the proposed Guideline for Reporting Evidence-based practice Educational intervention and Teaching (GREET) items. This thorough description will facilitate the interpretation of future research and implementation of the intervention. Our approach can also serve as a model for others considering online EBP intervention development.

Aligning Theory and Design: The Development of an Online Learning Intervention to Teach Evidence-based Practice for Maximal Reach

PubMed Central

Vihstadt, Corrie; Evans, Roni

2015-01-01

Background: Online educational interventions to teach evidence-based practice (EBP) are a promising mechanism for overcoming some of the barriers to incorporating research into practice. However, attention must be paid to aligning strategies with adult learning theories to achieve optimal outcomes. Methods: We describe the development of a series of short self-study modules, each covering a small set of learning objectives. Our approach, informed by design-based research (DBR), involved 6 phases: analysis, design, design evaluation, redesign, development/implementation, and evaluation. Participants were faculty and students in 3 health programs at a complementary and integrative educational institution. Results: We chose a reusable learning object approach that allowed us to apply 4 main learning theories: events of instruction, cognitive load, dual processing, and ARCS (attention, relevance, confidence, satisfaction). A formative design evaluation suggested that the identified theories and instructional approaches were likely to facilitate learning and motivation. Summative evaluation was based on a student survey (N=116) that addressed how these theories supported learning. Results suggest that, overall, the selected theories helped students learn. Conclusion: The DBR approach allowed us to evaluate the specific intervention and theories for general applicability. This process also helped us define and document the intervention at a level of detail that covers almost all the proposed Guideline for Reporting Evidence-based practice Educational intervention and Teaching (GREET) items. This thorough description will facilitate the interpretation of future research and implementation of the intervention. Our approach can also serve as a model for others considering online EBP intervention development. PMID:26421233

Informatics and machine learning to define the phenotype.

PubMed

Basile, Anna Okula; Ritchie, Marylyn DeRiggi

2018-03-01

For the past decade, the focus of complex disease research has been the genotype. From technological advancements to the development of analysis methods, great progress has been made. However, advances in our definition of the phenotype have remained stagnant. Phenotype characterization has recently emerged as an exciting area of informatics and machine learning. The copious amounts of diverse biomedical data that have been collected may be leveraged with data-driven approaches to elucidate trait-related features and patterns. Areas covered: In this review, the authors discuss the phenotype in traditional genetic associations and the challenges this has imposed.Approaches for phenotype refinement that can aid in more accurate characterization of traits are also discussed. Further, the authors highlight promising machine learning approaches for establishing a phenotype and the challenges of electronic health record (EHR)-derived data. Expert commentary: The authors hypothesize that through unsupervised machine learning, data-driven approaches can be used to define phenotypes rather than relying on expert clinician knowledge. Through the use of machine learning and an unbiased set of features extracted from clinical repositories, researchers will have the potential to further understand complex traits and identify patient subgroups. This knowledge may lead to more preventative and precise clinical care.

Adaptive Role Playing Games: An Immersive Approach for Problem Based Learning

ERIC Educational Resources Information Center

Sancho, Pilar; Moreno-Ger, Pablo; Fuentes-Fernandez, Ruben; Fernandez-Manjon, Baltasar

2009-01-01

In this paper we present a general framework, called NUCLEO, for the application of socio-constructive educational approaches in higher education. The underlying pedagogical approach relies on an adaptation model in order to improve group dynamics, as this has been identified as one of the key features in the success of collaborative learning…

Stirring up the Mud: Using a Community-Based Participatory Approach to Address Health Disparities through a Faith-Based Initiative

PubMed Central

Kaplan, Sue A.; Ruddock, Charmaine; Golub, Maxine; Davis, Joyce; Foley, Robert; Devia, Carlos; Rosen, Rosa; Berry, Carolyn; Barretto, Brenda; Carter, Toni; Irish-Spencer, Evalina; Marchena, Maria; Purcaro, Ellenrita; Calman, Neil

2011-01-01

This case study provides a mid-course assessment of the Bronx Health REACH faith-based initiative four years into its implementation. The study uses qualitative methods to identify lessons learned and to reflect on the benefits and challenges of using a community-based participatory approach for the development and evaluation of a faith-based program designed to address health disparities. Key findings concern the role of pastoral leadership, the importance of providing a religious context for health promotion and health equality messages, the challenges of creating a bilingual/bi-cultural program, and the need to provide management support to the lay program coordinators. The study also identifies lessons learned about community-based evaluation and the importance of addressing community concern about the balance between evaluation and program. Finally, the study identifies the challenges that lie ahead, including issues of program institution-alization and sustainability. PMID:20168022

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

PubMed

Wu, Mon-Ju; Mwangi, Benson; Bauer, Isabelle E; Passos, Ives C; Sanches, Marsal; Zunta-Soares, Giovana B; Meyer, Thomas D; Hasan, Khader M; Soares, Jair C

2017-01-15

Diagnosis, clinical management and research of psychiatric disorders remain subjective - largely guided by historically developed categories which may not effectively capture underlying pathophysiological mechanisms of dysfunction. Here, we report a novel approach of identifying and validating distinct and biologically meaningful clinical phenotypes of bipolar disorders using both unsupervised and supervised machine learning techniques. First, neurocognitive data were analyzed using an unsupervised machine learning approach and two distinct clinical phenotypes identified namely; phenotype I and phenotype II. Second, diffusion weighted imaging scans were pre-processed using the tract-based spatial statistics (TBSS) method and 'skeletonized' white matter fractional anisotropy (FA) and mean diffusivity (MD) maps extracted. The 'skeletonized' white matter FA and MD maps were entered into the Elastic Net machine learning algorithm to distinguish individual subjects' phenotypic labels (e.g. phenotype I vs. phenotype II). This calculation was performed to ascertain whether the identified clinical phenotypes were biologically distinct. Original neurocognitive measurements distinguished individual subjects' phenotypic labels with 94% accuracy (sensitivity=92%, specificity=97%). TBSS derived FA and MD measurements predicted individual subjects' phenotypic labels with 76% and 65% accuracy respectively. In addition, individual subjects belonging to phenotypes I and II were distinguished from healthy controls with 57% and 92% accuracy respectively. Neurocognitive task variables identified as most relevant in distinguishing phenotypic labels included; Affective Go/No-Go (AGN), Cambridge Gambling Task (CGT) coupled with inferior fronto-occipital fasciculus and callosal white matter pathways. These results suggest that there may exist two biologically distinct clinical phenotypes in bipolar disorders which can be identified from healthy controls with high accuracy and at an individual subject level. We suggest a strong clinical utility of the proposed approach in defining and validating biologically meaningful and less heterogeneous clinical sub-phenotypes of major psychiatric disorders. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

PubMed

Park, Chihyun; Ahn, Jaegyoon; Kim, Hyunjin; Park, Sanghyun

2014-01-01

The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

Music Listening Is Creative

ERIC Educational Resources Information Center

Kratus, John

2017-01-01

Active music listening is a creative activity in that the listener constructs a uniquely personal musical experience. Most approaches to teaching music listening emphasize a conceptual approach in which students learn to identify various characteristics of musical sound. Unfortunately, this type of listening is rarely done outside of schools. This…

Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach.

PubMed

Fraccaro, Paolo; Nicolo, Massimo; Bonetto, Monica; Giacomini, Mauro; Weller, Peter; Traverso, Carlo Enrico; Prosperi, Mattia; OSullivan, Dympna

2015-01-27

To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.

Understanding the challenges to facilitating active learning in the resident conferences: a qualitative study of internal medicine faculty and resident perspectives.

PubMed

Sawatsky, Adam P; Zickmund, Susan L; Berlacher, Kathryn; Lesky, Dan; Granieri, Rosanne

2015-01-01

Background In the Next Accreditation System, the Accreditation Council for Graduate Medical Education outlines milestones for medical knowledge and requires regular didactic sessions in residency training. There are many challenges to facilitating active learning in resident conferences, and we need to better understand resident learning preferences and faculty perspectives on facilitating active learning. The goal of this study was to identify challenges to facilitating active learning in resident conferences, both through identifying specific implementation barriers and identifying differences in perspective between faculty and residents on effective teaching and learning strategies. Methods The investigators invited core residency faculty to participate in focus groups. The investigators used a semistructured guide to facilitate discussion about learning preferences and teaching perspectives in the conference setting and used an 'editing approach' within a grounded theory framework to qualitative analysis to code the transcripts and analyze the results. Data were compared to previously collected data from seven resident focus groups. Results Three focus groups with 20 core faculty were conducted. We identified three domains pertaining to facilitating active learning in resident conferences: barriers to facilitating active learning formats, similarities and differences in faculty and resident learning preferences, and divergence between faculty and resident opinions about effective teaching strategies. Faculty identified several setting, faculty, and resident barriers to facilitating active learning in resident conferences. When compared to residents, faculty expressed similar learning preferences; the main differences were in motivations for conference attendance and type of content. Resident preferences and faculty perspectives differed on the amount of information appropriate for lecture and the role of active participation in resident conferences. Conclusion This study highlights several challenges to facilitating active learning in resident conferences and provides insights for residency faculty who seek to transform the conference learning environment within their residency program.

The knowledge-learning-instruction framework: bridging the science-practice chasm to enhance robust student learning.

PubMed

Koedinger, Kenneth R; Corbett, Albert T; Perfetti, Charles

2012-07-01

Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. Copyright © 2012 Cognitive Science Society, Inc.

Relational machine learning for electronic health record-driven phenotyping.

PubMed

Peissig, Peggy L; Santos Costa, Vitor; Caldwell, Michael D; Rottscheit, Carla; Berg, Richard L; Mendonca, Eneida A; Page, David

2014-12-01

Electronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient's clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. Two relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. We developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). ILP has the potential to improve phenotyping by independently delivering clinically expert interpretable rules for phenotype definitions, or intuitive phenotypes to assist experts. Relational learning using ILP offers a viable approach to EHR-driven phenotyping. Copyright © 2014 Elsevier Inc. All rights reserved.

Topic categorisation of statements in suicide notes with integrated rules and machine learning.

PubMed

Kovačević, Aleksandar; Dehghan, Azad; Keane, John A; Nenadic, Goran

2012-01-01

We describe and evaluate an automated approach used as part of the i2b2 2011 challenge to identify and categorise statements in suicide notes into one of 15 topics, including Love, Guilt, Thankfulness, Hopelessness and Instructions. The approach combines a set of lexico-syntactic rules with a set of models derived by machine learning from a training dataset. The machine learning models rely on named entities, lexical, lexico-semantic and presentation features, as well as the rules that are applicable to a given statement. On a testing set of 300 suicide notes, the approach showed the overall best micro F-measure of up to 53.36%. The best precision achieved was 67.17% when only rules are used, whereas best recall of 50.57% was with integrated rules and machine learning. While some topics (eg, Sorrow, Anger, Blame) prove challenging, the performance for relatively frequent (eg, Love) and well-scoped categories (eg, Thankfulness) was comparatively higher (precision between 68% and 79%), suggesting that automated text mining approaches can be effective in topic categorisation of suicide notes.

Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.

PubMed

Shah, M; Marchand, M; Corbeil, J

2012-01-01

One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance guarantees. There are few, if any, approaches that successfully address the two goals simultaneously. To the best of our knowledge, such algorithms that give theoretical bounds on the future performance have not been proposed so far in the context of the classification of gene expression data. In this work, we investigate the premise of learning a conjunction (or disjunction) of decision stumps in Occam's Razor, Sample Compression, and PAC-Bayes learning settings for identifying a small subset of attributes that can be used to perform reliable classification tasks. We apply the proposed approaches for gene identification from DNA microarray data and compare our results to those of the well-known successful approaches proposed for the task. We show that our algorithm not only finds hypotheses with a much smaller number of genes while giving competitive classification accuracy but also having tight risk guarantees on future performance, unlike other approaches. The proposed approaches are general and extensible in terms of both designing novel algorithms and application to other domains.

Hourly air pollution concentrations and their important predictors over Houston, Texas using deep neural networks: case study of DISCOVER-AQ time period

NASA Astrophysics Data System (ADS)

Eslami, E.; Choi, Y.; Roy, A.

2017-12-01

Air quality forecasting carried out by chemical transport models often show significant error. This study uses a deep-learning approach over the Houston-Galveston-Brazoria (HGB) area to overcome this forecasting challenge, for the DISCOVER-AQ period (September 2013). Two approaches, deep neural network (DNN) using a Multi-Layer Perceptron (MLP) and Restricted Boltzmann Machine (RBM) were utilized. The proposed approaches analyzed input data by identifying features abstracted from its previous layer using a stepwise method. The approaches predicted hourly ozone and PM in September 2013 using several predictors of prior three days, including wind fields, temperature, relative humidity, cloud fraction, precipitation along with PM, ozone, and NOx concentrations. Model-measurement comparisons for available monitoring sites reported Indexes of Agreement (IOA) of around 0.95 for both DNN and RBM. A standard artificial neural network (ANN) (IOA=0.90) with similar architecture showed poorer performance than the deep networks, clearly demonstrating the superiority of the deep approaches. Additionally, each network (both deep and standard) performed significantly better than a previous CMAQ study, which showed an IOA of less than 0.80. The most influential input variables were identified using their associated weights, which represented the sensitivity of ozone to input parameters. The results indicate deep learning approaches can achieve more accurate ozone forecasting and identify the important input variables for ozone predictions in metropolitan areas.

Using Students' Experiences to Derive Quality in an E-Learning System: An Institution's Perspective

ERIC Educational Resources Information Center

Alexander, Shirley; Golja, Tanja

2007-01-01

Higher education institutions undertake a range of approaches to evaluating and making judgments about the quality of their e-learning provision. This paper begins by exploring benchmarking as one current strategy in common use in universities to identify and implement quality practices: from the use of checklists (for example, of best practices…

The Relationship between Organizational Learning and SME Performance in Poland

ERIC Educational Resources Information Center

Michna, Anna

2009-01-01

Purpose: The purpose of this paper is to identify and define dimensions of organizational learning and the way it affects small- or medium-size enterprise (SME) performance. Design/methodology/approach: The empirical research is carried out in Polish SMEs (the sample size is 211 enterprises). In order to test the constructed hypotheses we use…

Supporting Professional Development in Special Education with Web-Based Professional Learning Communities: New Possibilities with Web 2.0

ERIC Educational Resources Information Center

Hardman, Elizabeth L.

2012-01-01

This article describes the challenges in organizing professional learning communities (PLCs) in special education, identifies the teacher and student benefits of using a PLC approach to professional development, and discusses the promise and pitfalls of organizing web-based PLCs to engage distributed stakeholders in the practice of special…

The Legal Meaning of Specific Learning Disability for IDEA Eligibility: The Latest Case Law

ERIC Educational Resources Information Center

Zirkel, Perry A.

2013-01-01

Specific learning disability (SLD), although moderately declining in recent years, continues to be the largest of the eligibility classifications under the Individuals with Disabilities Education Act (IDEA; NCES, 2012). The recognition of response to intervention (RTI) in the 2004 amendments of the IDEA as an approach for identifying students with…

A Co-Citation Network of Young Children's Learning with Technology

ERIC Educational Resources Information Center

Tang, Kai-Yu; Li, Ming-Chaun; Hsin, Ching-Ting; Tsai, Chin-Chung

2016-01-01

This paper used a novel literature review approach--co-citation network analysis--to illuminate the latent structure of 87 empirical papers in the field of young children's learning with technology (YCLT). Based on the document co-citation analysis, a total of 206 co-citation relationships among the 87 papers were identified and then graphically…

A Framework for Simplifying Educator Tasks Related to the Integration of Games in the Learning Flow

ERIC Educational Resources Information Center

del Blanco, Angel; Torrente, Javier; Marchiori, Eugenio J.; Martinez-Ortiz, Ivan; Moreno-Ger, Pablo; Fernandez-Manjon, Baltasar

2012-01-01

The integration of educational video games in educational settings in general, and e-learning systems in particular, can be challenging for educators. We propose a framework that aims to facilitate educators' participation in the creation and modification of courses that use educational games. Our approach addresses problems identified by previous…

Outdoor Fieldwork in Higher Education: Learning from Multidisciplinary Experience

ERIC Educational Resources Information Center

Munge, Brendon; Thomas, Glyn; Heck, Deborah

2018-01-01

Background: Many disciplines use outdoor fieldwork (OFW) as an experiential learning method in higher education. Although there has been an increase in research into the pedagogical approaches of OFW, the use of OFW is contested. Purpose: The purpose of the study was to synthesize the OFW literature across a range of disciplines to identify common…

The Effect of Problem-Based Learning in Nursing Education: A Meta-Analysis

ERIC Educational Resources Information Center

Shin, In-Soo; Kim, Jung-Hee

2013-01-01

Problem-based learning (PBL) has been identified as an approach that improves the training of nurses by teaching them how to apply theory to clinical practice and by developing their problem-solving skills, which could be used to overcome environmental constraints within clinical practice. A consensus is emerging that there is a need for…

Professional Development and Learning by General Teachers Implementing Functional Behavioural Assessment in Thai Inclusive Classrooms

ERIC Educational Resources Information Center

Opartkiattikul, Watinee; Arthur-Kelly, Michael; Dempsey, Ian

2016-01-01

Functional Behavioural Assessment (FBA) is identified as a research-based approach used in many Western schools to support student behaviour. This study aimed to assist Thai classroom teachers by providing a professional development and learning programme in FBA to develop an effective and efficient process to address behaviour problems and allow…

Learning Organizations: Diagnosis and Measurement in a Developing Country Context--The Case of Lebanon

ERIC Educational Resources Information Center

Jamali, Dima; Sidani, Yusuf

2008-01-01

Purpose: The purpose of this paper is to assess the performance of a sample of Lebanese organizations vis-a-vis some of the core learning organization dimensions identified in the literature, focusing specifically on those dimensions that are considered most salient and relevant in the Lebanese context. Design/methodology/approach: The paper…

Classification Agreement Analysis of Cross-Battery Assessment in the Identification of Specific Learning Disorders in Children and Youth

ERIC Educational Resources Information Center

Kranzler, John H.; Floyd, Randy G.; Benson, Nicholas; Zaboski, Brian; Thibodaux, Lia

2016-01-01

The Cross-Battery Assessment (XBA) approach to identifying a specific learning disorder (SLD) is based on the postulate that deficits in cognitive abilities in the presence of otherwise average general intelligence are causally related to academic achievement weaknesses. To examine this postulate, we conducted a classification agreement analysis…

At Issue: An Award-Winning Community College Instructor's Approach to Teaching and Learning

ERIC Educational Resources Information Center

Welsh, Hilarie B.

2015-01-01

The author presents themes that were identified from a case study that focused on the instructional practices of an award-winning community college composition/literature teacher. The themes for this case study focus on the importance of student-centered learning which involve: (1) writing peer response strategies; (2) student engagement in using…

An Integrated Academic Literacy Approach to Improving Students' Understanding of Plagiarism in an Accounting Course

ERIC Educational Resources Information Center

Powell, Lisa; Singh, Nishani

2016-01-01

Plagiarism in higher education is a widespread and complex issue. Students' understanding of plagiarism differs as a result of combining their prior learning about referencing with their current experience of institutional policies and generic resources. Plagiarism was identified as a major learning issue in a core second-year undergraduate…

Examining Student Opinions on Computer Use Based on the Learning Styles in Mathematics Education

ERIC Educational Resources Information Center

Ozgen, Kemal; Bindak, Recep

2012-01-01

The purpose of this study is to identify the opinions of high school students, who have different learning styles, related to computer use in mathematics education. High school students' opinions on computer use in mathematics education were collected with both qualitative and quantitative approaches in the study conducted with a survey model. For…

Reorienting Self-Directed Learning for the Creative Digital Era

ERIC Educational Resources Information Center

Karakas, Fahri; Manisaligil, Alperen

2012-01-01

Purpose: The purpose of this paper is to identify the new role that human resource developers play in the globally connected workplace. Towards that end, this paper explores the changing landscape of self-directed learning (SDL) within the digital ecosystem based on the concept of World 2.0. Design/methodology/approach: This paper reviews and…

Taking a Step Back: Learning without the Facilitator on Solo Activities

ERIC Educational Resources Information Center

Williams, Andy

2012-01-01

The purpose of this study is to report on the nature of student learning resulting from an open facilitation approach to solo activities. Three key moments of facilitator intervention were identified at which the facilitator was encouraged to take a step back from directing the experience. They are the pre-activity brief, the mid-activity visit…

Determinants of User Demand for Lifelong Learning in Institutions of Higher Education

ERIC Educational Resources Information Center

Sabrià-Bernadó, Betlem; LLinàs-Audet, Xavier; Isus, Sofia

2017-01-01

The main objective of this study is to identify the determinants that influence user demand for lifelong learning in institutions of higher education. Qualitative methodology was used to develop an instrument and a quantitative approach was used for the remainder of the study. After a literature review and in-depth interviews with experts in…

Supporting Teachers to Embed Numeracy across the Curriculum: A Sociocultural Approach

ERIC Educational Resources Information Center

Bennison, Anne

2015-01-01

Numeracy is an integral part of subjects across the curriculum. If all teachers are able to identify and exploit the numeracy learning opportunities that exist in the subjects they teach, then students' numeracy capabilities along with learning in each subject is likely to be enhanced. This article builds on previous research where it was…

Impact of pedagogical approaches on cognitive complexity and motivation to learn: Comparing nursing and engineering undergraduate students.

PubMed

McComb, Sara A; Kirkpatrick, Jane M

2016-01-01

The changing higher education landscape is prompting nurses to rethink educational strategies. Looking beyond traditional professional boundaries may be beneficial. We compare nursing to engineering because engineering has similar accreditation outcome goals and different pedagogical approaches. We compare students' cognitive complexity and motivation to learn to identify opportunities to share pedagogical approaches between nursing and engineering. Cross-sectional data were collected from 1,167 freshmen through super senior students. Comparisons were made across years and between majors. Overall nursing and engineering students advance in cognitive complexity while maintaining motivation for learning. Sophomores reported the lowest scores on many dimensions indicating that their experiences need review. The strong influence of the National Council Licensure Examination on nursing students may drive their classroom preferences. Increased intrinsic motivation, coupled with decreased extrinsic motivation, suggests that we are graduating burgeoning life-long learners equipped to maintain currency. The disciplines' strategies for incorporating real-world learning opportunities differ, yet the students similarly advance in cognitive complexity and maintain motivation to learn. Lessons can be exchanged across professional boundaries. Copyright © 2016 Elsevier Inc. All rights reserved.

Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

PubMed

Patel, Nihir; Wang, Jason T L

2015-10-01

Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

Collaborative learning framework for online stakeholder engagement.

PubMed

Khodyakov, Dmitry; Savitsky, Terrance D; Dalal, Siddhartha

2016-08-01

Public and stakeholder engagement can improve the quality of both research and policy decision making. However, such engagement poses significant methodological challenges in terms of collecting and analysing input from large, diverse groups. To explain how online approaches can facilitate iterative stakeholder engagement, to describe how input from large and diverse stakeholder groups can be analysed and to propose a collaborative learning framework (CLF) to interpret stakeholder engagement results. We use 'A National Conversation on Reducing the Burden of Suicide in the United States' as a case study of online stakeholder engagement and employ a Bayesian data modelling approach to develop a CLF. Our data modelling results identified six distinct stakeholder clusters that varied in the degree of individual articulation and group agreement and exhibited one of the three learning styles: learning towards consensus, learning by contrast and groupthink. Learning by contrast was the most common, or dominant, learning style in this study. Study results were used to develop a CLF, which helps explore multitude of stakeholder perspectives; identifies clusters of participants with similar shifts in beliefs; offers an empirically derived indicator of engagement quality; and helps determine the dominant learning style. The ability to detect learning by contrast helps illustrate differences in stakeholder perspectives, which may help policymakers, including Patient-Centered Outcomes Research Institute, make better decisions by soliciting and incorporating input from patients, caregivers, health-care providers and researchers. Study results have important implications for soliciting and incorporating input from stakeholders with different interests and perspectives. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Learning styles and teaching/learning strategy preferences: implications for educating nurses in critical care, the operating room, and infection control.

PubMed

Goldrick, B; Gruendemann, B; Larson, E

1993-01-01

To assess the learning styles and educational strategy preferences among critical care nurses, operating room nurses, and infection control practitioners. Descriptive multicenter survey using a self-report questionnaire. 108 hospitals from nine geographic regions of the United States. A random sample of 303 (93%) nurses in the three specialties responded to the survey questionnaires. The majority of participants (64%) had an abstract learning style and preferred the self-directed, discovery approach to learning. Nurses may be more abstract in their learning styles than previously reported. Experiential learning theory is an effective means of identifying nurses' learning styles and teaching/learning preferences, which can then be used to plan basic and continuing educational programs.

A deep learning framework to discern and count microscopic nematode eggs.

PubMed

Akintayo, Adedotun; Tylka, Gregory L; Singh, Asheesh K; Ganapathysubramanian, Baskar; Singh, Arti; Sarkar, Soumik

2018-06-14

In order to identify and control the menace of destructive pests via microscopic image-based identification state-of-the art deep learning architecture is demonstrated on the parasitic worm, the soybean cyst nematode (SCN), Heterodera glycines. Soybean yield loss is negatively correlated with the density of SCN eggs that are present in the soil. While there has been progress in automating extraction of egg-filled cysts and eggs from soil samples counting SCN eggs obtained from soil samples using computer vision techniques has proven to be an extremely difficult challenge. Here we show that a deep learning architecture developed for rare object identification in clutter-filled images can identify and count the SCN eggs. The architecture is trained with expert-labeled data to effectively build a machine learning model for quantifying SCN eggs via microscopic image analysis. We show dramatic improvements in the quantification time of eggs while maintaining human-level accuracy and avoiding inter-rater and intra-rater variabilities. The nematode eggs are correctly identified even in complex, debris-filled images that are often difficult for experts to identify quickly. Our results illustrate the remarkable promise of applying deep learning approaches to phenotyping for pest assessment and management.

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue.

PubMed

Macedo, Nayana Damiani; Buzin, Aline Rodrigues; de Araujo, Isabela Bastos Binotti Abreu; Nogueira, Breno Valentim; de Andrade, Tadeu Uggere; Endringer, Denise Coutinho; Lenz, Dominik

2017-02-01

The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation. A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software. Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively. Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Specific Cognitive Predictors of Early Math Problem Solving

ERIC Educational Resources Information Center

Decker, Scott L.; Roberts, Alycia M.

2015-01-01

Development of early math skill depends on a prerequisite level of cognitive development. Identification of specific cognitive skills that are important for math development may not only inform instructional approaches but also inform assessment approaches to identifying children with specific learning problems in math. This study investigated the…

From Band Rooms to Choral Risers.

ERIC Educational Resources Information Center

Washington, William Lee

1999-01-01

Offers suggestions for instrumentalists who have become choral instructors explaining that their first goal should be to learn how to identify and understand an ideal vocal sound. Finds that the hardest aspect of choral instruction is developing a teaching approach. Offers five steps to assist instrumentalists in molding their own approach. (CMK)

New Approaches to the Education of Older Adults.

ERIC Educational Resources Information Center

Wolf, Mary Alice

New approaches to the education of older adults can be identified through a review of the literature on the following topics: developmental perspectives (including generativity and integrity) and adult development, life span habits (as determined by longitudinal research), gender roles, reminiscence, cognitive, and need-based learning. One of the…

Creative Inspiration for Preschoolers from Museums

ERIC Educational Resources Information Center

Rönkkö, Marja-Leena; Aerila, Juli-Anna; Grönman, Satu

2016-01-01

This research explores the learning outcomes of preschool children produced through visits to an historic house museum environment. The new Finnish preschool curriculum identifies the importance of arts-based approaches for children and that these approaches should be closely aligned to experiential and holistic education. The aim of the research…

An Investigational Analysis of Problem Drinking among a Commuter College Population.

ERIC Educational Resources Information Center

Bebo, Joseph A.

2003-01-01

Previous literature has identified a number of variables that lead to substance abuse behavior. Studies that take a multifaceted, theoretical approach are limited. This study proposes the integration of differential association, social learning, social bonding, seduction and self-control theories. Proposes that a multifaceted approach contributes…

Student approaches for learning in medicine: what does it tell us about the informal curriculum?

PubMed

Zhang, Jianzhen; Peterson, Raymond F; Ozolins, Ieva Z

2011-10-21

It has long been acknowledged that medical students frequently focus their learning on that which will enable them to pass examinations, and that they use a range of study approaches and resources in preparing for their examinations. A recent qualitative study identified that in addition to the formal curriculum, students are using a range of resources and study strategies which could be attributed to the informal curriculum. What is not clearly established is the extent to which these informal learning resources and strategies are utilized by medical students. The aim of this study was to establish the extent to which students in a graduate-entry medical program use various learning approaches to assist their learning and preparation for examinations, apart from those resources offered as part of the formal curriculum. A validated survey instrument was administered to 522 medical students. Factor analysis and internal consistence, descriptive analysis and comparisons with demographic variables were completed. The factor analysis identified eight scales with acceptable levels of internal consistency with an alpha coefficient between 0.72 and 0.96. Nearly 80% of the students reported that they were overwhelmed by the amount of work that was perceived necessary to complete the formal curriculum, with 74.3% believing that the informal learning approaches helped them pass the examinations. 61.3% believed that they prepared them to be good doctors. A variety of informal learning activities utilized by students included using past student notes (85.8%) and PBL tutor guides (62.7%), and being part of self-organised study groups (62.6%), and peer-led tutorials (60.2%). Almost all students accessed the formal school resources for at least 10% of their study time. Students in the first year of the program were more likely to rely on the formal curriculum resources compared to those of Year 2 (p = 0.008). Curriculum planners should examine the level of use of informal learning activities in their schools, and investigate whether this is to enhance student progress, a result of perceived weakness in the delivery and effectiveness of formal resources, or to overcome anxiety about the volume of work expected by medical programs.

Are Asian international medical students just rote learners?

PubMed

Tavakol, Mohsen; Dennick, Reg

2010-08-01

A wide variety of countries are seeking to attract international medical students. This could be due to the fact that their universities not only receive the economic benefit from these students, but also because they recognise the issues of cultural diversity and pedagogical practice. This review paper draws on literature to understand more fully the learning process of Asian international students. Whereas views on learning are different across cultures, medical school teachers must understand how Asian international students learn based on their culture. Two general themes emerged from the literature review: firstly culture's influence on learning and secondly memorisation versus understanding, both of which relate to the learning process of Asian international students. This study shows that Asian international students have a different approach to learning, which is not just about rote learning. Changes in attitudes towards Asian international students may stimulate the internationalisation of a more culturally sensitive form of medical education. The paper suggests further work on the area of appreciative thinking in order to identify the epistemological and ontological dimensions for a flexible approach to learning.

A Mock Randomized Controlled Trial With Audience Response Technology for Teaching and Learning Epidemiology.

PubMed

Baker, Philip R A; Francis, Daniel P; Cathcart, Abby

2017-04-01

The study's objective was to apply and assess an active learning approach to epidemiology and critical appraisal. Active learning comprised a mock, randomized controlled trial (RCT) conducted with learners in 3 countries. The mock trial consisted of blindly eating red Smarties candy (intervention) compared to yellow Smarties (control) to determine whether red Smarties increase happiness. Audience response devices were employed with the 3-fold purposes to produce outcome data for analysis of the effects of red Smarties, identify baseline and subsequent changes in participant's knowledge and confidence in understanding of RCTs, and assess the teaching approach. Of those attending, 82% (117 of 143 learners) participated in the trial component. Participating in the mock trial was a positive experience, and the use of the technology aided learning. The trial produced data that learners analyzed in "real time" during the class. The mock RCT is a fun and engaging approach to teaching RCTs and helping students to develop skills in critical appraisal.

Imitative and Direct Learning as Interacting Factors in Life History Evolution.

PubMed

Bullinaria, John A

2017-01-01

The idea that lifetime learning can have a significant effect on life history evolution has recently been explored using a series of artificial life simulations. These involved populations of competing individuals evolving by natural selection to learn to perform well on simplified abstract tasks, with the learning consisting of identifying regularities in their environment. In reality, there is more to learning than that type of direct individual experience, because it often includes a substantial degree of social learning that involves various forms of imitation of what other individuals have learned before them. This article rectifies that omission by incorporating memes and imitative learning into revised versions of the previous approach. To do this reliably requires formulating and testing a general framework for meme-based simulations that will enable more complete investigations of learning as a factor in any life history evolution scenarios. It does that by simulating imitative information transfer in terms of memes being passed between individuals, and developing a process for merging that information with the (possibly inconsistent) information acquired by direct experience, leading to a consistent overall body of learning. The proposed framework is tested on a range of learning variations and a representative set of life history factors to confirm the robustness of the approach. The simulations presented illustrate the types of interactions and tradeoffs that can emerge, and indicate the kinds of species-specific models that could be developed with this approach in the future.

Bridging Theory and Practice: Using Hip-Hop Pedagogy As A Culturally Relevant Approach In The Urban Science Classroom

NASA Astrophysics Data System (ADS)

Adjapong, Edmund S.

This dissertation explores the context of urban science education as it relates to the achievement and engagement of urban youth. This study provides a framework for Hip-Hop Pedagogy, an approach to teaching and learning anchored in the creative elements of Hip-Hop culture, in STEM as an innovative approach to teaching and learning demonstrates the effect that Hip-Hop Pedagogy, as a culturally relevant approach to teaching has on teaching and learning in an urban science classroom. This study establishes practical tools and approaches, which were formed from by theory and research that transcend the traditional monolithic approaches to teaching science. Participants in this study are middle school students who attend an urban school in one of the largest school systems in the country. This research showed that as result of utilizing Hip-Hop pedagogical practices, students reported that they developed a deeper understanding of science content, students were more likely to identify as scientists, and students were provided a space and opportunities to deconstruct traditional classroom spaces and structures.

Faculty perspectives on the inclusion of work-related learning in engineering curricula

NASA Astrophysics Data System (ADS)

Magnell, Marie; Geschwind, Lars; Kolmos, Anette

2017-11-01

The purpose of this paper is to identify faculty perspectives on the integration of work-related issues in engineering education. A mixed methods approach was used to explore faculty attitudes towards work-related learning, to describe activities related to working life that have been introduced into the curriculum and to identify factors that faculty see as important if the amount of work-related learning is to increase. The results show that faculty members are positive about integrating work-related issues into the curriculum. Programmes with more extensive connections to industry offer more integrated activities, such as projects with external actors, and use professional contacts established through research in their teaching. In order to increase work-related learning in engineering curricula, faculty request clear goals and pedagogical tools. Other options to increase work-related learning include offering faculty the opportunity to work outside academia.

How Do University Teachers Combine Different Approaches to Teaching in a Specific Course? A Qualitative Multi-Case Study

ERIC Educational Resources Information Center

Uiboleht, Kaire; Karm, Mari; Postareff, Liisa

2016-01-01

Teaching approaches in higher education are at the general level well researched and have identified not only the two broad categories of content-focused and learning-focused approaches to teaching but also consonance and dissonance between the aspects of teaching. Consonance means that theoretically coherent teaching practices are employed, but…

Diagnosing and treating Enquiry Based Learning fatigue in Graduate Entry Nursing students.

PubMed

Stacey, Gemma; Wilson, Claire; Reddy, Helen; Palmer, Chris; Henderson, James; Little, Hannah; Bull, Heather

2018-01-01

The use of student directed study approaches such as Enquiry Based Learning (EBL) in the design and implementation of Graduate Entry Nursing Circular is well established. The rational relates to the maximisation of graduate attributes such as motivation to learn, the ability to identify, search and assimilate relevant literature and the desire to take ownership of the direction and pace of learning. Existing alongside this however, is the observation that students remain under confident in the application of knowledge to a clinical context and frustrated with learning approaches which do not appear directly related to improving their competence in this area. We suggest the result of this is a gradual disengagement and dissatisfaction the learning forum amongst students and faculty, which we have defined as EBL fatigue. The symptoms and consequences of EBL fatigue amongst students and faculty are discussed alongside strategies which we suggest may act as preventative measures in reducing the risk of a local epidemic. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving the quality of educational strategies in postgraduate dental education using student and graduate feedback: findings from a qualitative study in New Zealand.

PubMed

Subramanian, J; Anderson, V R; Morgaine, K C; Thomson, W M

2013-02-01

Research suggests that students' perceptions should be considered in any discussion of their education. However, to date, there has been no systematic examination of New Zealand postgraduate dental students' learning processes in both the research and clinical settings. This study aimed to obtain in-depth qualitative insights into student and graduate perspectives of effective and ineffective learning experiences during their postgraduate dental education. Data were collected in 2010 using semi-structured individual interviews. Participants included 2010 final-year students and 2009 graduates of the University of Otago Doctor of Clinical Dentistry programme. Using the Critical Incident Technique, participants were asked to describe at least one effective and one ineffective learning experience in detail. Interview transcripts were analysed using a general inductive approach. Broad themes which emerged included supervisory approaches, characteristics of the learning process and characteristics of the physical learning environment. The focus of this article is to report and discuss the learning processes that participants identified as promoting and precluding effective learning experiences in the clinical and research settings. Students and graduates in the study had largely similar perspectives of learning processes likely to result in effective clinical and research learning. These included self-directed and collaborative learning; timely, constructive and detailed feedback with directions for further improvement; and discreet clinical feedback. Learning processes that precluded effective learning included unsupported and isolated learning, delayed and overly critical/destructive feedback and open criticism in the clinical context. The in-depth findings of this study contribute to the scientific literature that identifies learning process characteristics which facilitate effective learning from New Zealand postgraduate students' and graduates' perspectives. Additional cross-sectional and longitudinal studies (both qualitative and quantitative) would lead to a better understanding of what constitutes effective teaching in postgraduate dental education. © 2012 John Wiley & Sons A/S.

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.

Work-based learning: a leadership development example from an action research study of shared governance implementation.

PubMed

Williamson, Tracey

2005-11-01

An empowering action research study was undertaken to evaluate and strengthen the implementation of shared governance. One aim was to identify factors that acted as aids or barriers to effective decision-making by clinical leaders. As a work-based learning approach, action research was expected to lead to integration of learning into practice by researcher and participants alike. Shared governance replaces traditional hierarchies and requires and develops clinical leaders. Strategies are needed to maximize learning from introduction of such initiatives at the individual, group and organizational level. Participant-observations and interviews were undertaken with shared governance council members from one model in north-west England. Leadership skills and knowledge and shared governance practices were significantly enhanced. Preparation for council roles was considered inadequate. Increased structured time for reflection and action planning was indicated. Implementation of shared governance has succeeded in developing leadership capacity. Evaluation findings have led to improvements in the overall shared governance model. Action research has been found to have great utility at optimizing work-based learning. Nurse Managers need to develop their coaching and facilitating skills and recognize there is no "quick fix" for developing clinical leaders. Implications include the need to support learners in identifying and implementing changes arising from work-based learning activities, the significant resource implications and the need to optimize the organizational climate if work-based learning approaches to leadership and management development are to succeed.

Machine learning approaches to analysing textual injury surveillance data: a systematic review.

PubMed

Vallmuur, Kirsten

2015-06-01

To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Systematic review. The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field. Copyright © 2015 Elsevier Ltd. All rights reserved.

Medical students' opportunities to participate and learn from activities at an internal medicine ward: an ethnographic study

PubMed Central

Hägg-Martinell, A; Hult, H; Henriksson, P; Kiessling, A

2017-01-01

Objectives To optimise medical students’ early clerkship is a complex task since it is conducted in a context primarily organised to take care of patients. Previous studies have explored medical students’ perceptions of facilitation and hindrance of learning. However, the opportunities for medical student to learn within the culture of acute medicine care have not been fully investigated. This study aimed to explore how medical students approach, interact and socialise in an acute internal medicine ward context, and how spaces for learning are created and used in such a culture. Design and setting Ethnographic observations were performed of medical students' interactions and learning during early clerkship at an acute internal medicine care ward. Field notes were taken, transcribed and analysed qualitatively. Data analysis was guided by Wenger's theory of communities of practice. Participants 21 medical students and 30 supervisors participated. Results Two themes were identified: Nervousness and curiosity—students acted nervously and stressed, especially when they could not answer questions. Over time curiosity could evolve. Unexplored opportunities to support students in developing competence to judge and approach more complex patient-related problems were identified. Invited and involved—students were exposed to a huge variation of opportunities to learn, and to interact and to be involved. Short placements seemed to disrupt the learning process. If and how students became involved also depended on supervisors' activities and students' initiatives. Conclusions This study shed light on how an acute internal medicine ward culture can facilitate medical students' possibilities to participate and learn. Medical students' learning situations were characterised by questions and answers rather than challenging dialogues related to the complexity of presented patient cases. Further, students experienced continuous transfers between learning situations where the potential to be involved differed in a wide variety of ways. PMID:28196948

The Challenges of Nursing Students in the Clinical Learning Environment: A Qualitative Study

PubMed Central

Jamshidi, Nahid; Molazem, Zahra; Sharif, Farkhondeh; Torabizadeh, Camellia; Najafi Kalyani, Majid

2016-01-01

Background/Aim. Clinical learning is a main part of nursing education. Students' exposure to clinical learning environment is one of the most important factors affecting the teaching-learning process in clinical settings. Identifying challenges of nursing students in the clinical learning environment could improve training and enhance the quality of its planning and promotion of the students. We aimed to explore Iranian nursing students' challenges in the clinical learning environment. Materials and Methods. This is a qualitative study using the content analysis approach. The participants consisted of seventeen nursing students and three nursing instructors. The participants were selected through purposive sampling method and attended semistructured interviews and focus groups. Results. Three themes emerged after data analysis, including ineffective communications, inadequate readiness, and emotional reactions. Conclusion. Nursing students in Iran are faced with many challenges in the clinical learning environment. All challenges identified in this study affected the students' learning in clinical setting. Therefore, we recommend that the instructors prepare students with a specific focus on their communication and psychological needs. PMID:27366787

Identification of Learning Mechanisms in a Wild Meerkat Population

PubMed Central

Hoppitt, Will; Samson, Jamie; Laland, Kevin N.; Thornton, Alex

2012-01-01

Vigorous debates as to the evolutionary origins of culture remain unresolved due to an absence of methods for identifying learning mechanisms in natural populations. While laboratory experiments on captive animals have revealed evidence for a number of mechanisms, these may not necessarily reflect the processes typically operating in nature. We developed a novel method that allows social and asocial learning mechanisms to be determined in animal groups from the patterns of interaction with, and solving of, a task. We deployed it to analyse learning in groups of wild meerkats (Suricata suricatta) presented with a novel foraging apparatus. We identify nine separate learning processes underlying the meerkats’ foraging behaviour, in each case precisely quantifying their strength and duration, including local enhancement, emulation, and a hitherto unrecognized form of social learning, which we term ‘observational perseverance’. Our analysis suggests a key factor underlying the stability of behavioural traditions is a high ratio of specific to generalized social learning effects. The approach has widespread potential as an ecologically valid tool to investigate learning mechanisms in natural groups of animals, including humans. PMID:22905113

A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

PubMed

Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

2016-12-01

The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

Exploring the potential of a multi-level approach to improve capability for continuous organizational improvement and learning in a Swedish healthcare region.

PubMed

Nyström, M E; Höög, E; Garvare, R; Andersson Bäck, M; Terris, D D; Hansson, J

2018-05-24

Eldercare and care of people with functional impairments is organized by the municipalities in Sweden. Improving care in these areas is complex, with multiple stakeholders and organizations. Appropriate strategies to develop capability for continuing organizational improvement and learning (COIL) are needed. The purpose of our study was to develop and pilot-test a flexible, multilevel approach for COIL capability building and to identify what it takes to achieve changes in key actors' approaches to COIL. The approach, named "Sustainable Improvement and Development through Strategic and Systematic Approaches" (SIDSSA), was applied through an action-research and action-learning intervention. The SIDSSA approach was tested in a regional research and development (R&D) unit, and in two municipalities handling care of the elderly and people with functional impairments. Our approach included a multilevel strategy, development loops of five flexible phases, and an action-learning loop. The approach was designed to support systems understanding, strategic focus, methodological practices, and change process knowledge - all of which required double-loop learning. Multiple qualitative methods, i.e., repeated interviews, process diaries, and documents, provided data for conventional content analyses. The new approach was successfully tested on all cases and adopted and sustained by the R&D unit. Participants reported new insights and skills. The development loop facilitated a sense of coherence and control during uncertainty, improved planning and problem analysis, enhanced mapping of context and conditions, and supported problem-solving at both the individual and unit levels. The systems-level view and structured approach helped participants to explain, motivate, and implement change initiatives, especially after working more systematically with mapping, analyses, and goal setting. An easily understood and generalizable model internalized by key organizational actors is an important step before more complex development models can be implemented. SIDSSA facilitated individual and group learning through action-learning and supported systems-level views and structured approaches across multiple organizational levels. Active involvement of diverse organizational functions and levels in the learning process was facilitated. However, the time frame was too short to fully test all aspects of the approach, specifically in reaching beyond the involved managers to front-line staff and patients.

Fostering interprofessional learning in a rehabilitation setting: development of an interprofessional clinical learning unit.

PubMed

Vanderzalm, Jeanne; Hall, Mark D; McFarlane, Lu-Anne; Rutherford, Laurie; Patterson, Steven K

2013-01-01

The development and implementation of interprofessional (IP) clinical learning units as a method to enhance IP clinical education and improve patient care in a rehabilitation setting are described. Using a community-based participatory research approach, academia and healthcare delivery agencies formed a partnership to create an IP clinical learning unit in a rehabilitation setting. Preimplementation data from surveys and focus group data identified areas for improvement to enhance IP understanding and collaboration. A working group developed and implemented initiatives to enhance IP practice. Preimplementation, eight themes emerged from which the working group identified goals and implemented strategies to strengthen IP learning. Goals included Creation of an IP Learning Environment, Increased Awareness of IP Practice, Role Clarification, Enhanced IP Communication, and Reflection and Evaluation. Postimplementation data revealed six themes: Communication, Informal IP Learning, Role Awareness, Positive Learning Environment, Logistics, and Challenges. The development of the IP clinical learning unit was successful and rewarding, but not without its challenges. Formal IP education was necessary to enhance collaborative practice, even in a multidisciplinary environment. Commitment and support from all participants, particularly managers and administrators from the healthcare agency, were critical to success. The focus of this unit was on a stroke rehabilitation unit; however, the development and implementation principles identified may be applicable to any team-based clinical setting. © 2013 Association of Rehabilitation Nurses.

Basic Skills Resource Center. Part 2

DTIC Science & Technology

1985-05-01

side if neceseary and Identify by block number) Basic Skills Education Curriculum Development Learning Strategies Reading Comprehension Motivational ... Motivational Skills Training for Military Technical Training Students ...... Barbara L. McCombs 25 Problem 27 Purpose 27 Approach 28 - Phase 1 28 - Phase...and Learning ...... John J. Hedl , Jr. 53 Purpose of Project 55 Description of Work 55 V Products 56 Virtual Videodisc Software Requirements ...... J.D

Open and Distance Learning for Health: Supporting Health Workers through Education and Training

ERIC Educational Resources Information Center

Dodds, Tony

2011-01-01

This case study surveys the growing use of open and distance learning approaches to the provision of support, education and training to health workers over the past few decades. It classifies such uses under four headings, providing brief descriptions from the literature of a few examples of each group. In conclusion, it identifies key lessons…

Using an Intention/Reflection Practice to Focus Students towards Future Professions in a Short-Term International Travel Experience

ERIC Educational Resources Information Center

Fierke, Kerry K.; Lepp, Gardner A.; Bastianelli, Karen; Vogelsang, Lisa; Tornabene, Ladona

2016-01-01

The article describes a student-centered approach to generating meaningful learning outcomes in a short-term study abroad program. A practice named Intention/Reflection (I/R) was used to help students to identify, articulate, and reflect upon learning objectives that were personally meaningful, within the broader framework of the intended outcomes…

The Learning of Visually Guided Action: An Information-Space Analysis of Pole Balancing

ERIC Educational Resources Information Center

Jacobs, David M.; Vaz, Daniela V.; Michaels, Claire F.

2012-01-01

In cart-pole balancing, one moves a cart in 1 dimension so as to balance an attached inverted pendulum. We approached perception-action and learning in this task from an ecological perspective. This entailed identifying a space of informational variables that balancers use as they perform the task and demonstrating that they improve by traversing…

Patterns of Auditory Perception Skills in Children with Learning Disabilities: A Computer-Assisted Approach.

ERIC Educational Resources Information Center

Pressman, E.; And Others

1986-01-01

The auditory receptive language skills of 40 learning disabled (LD) and 40 non-disabled boys (all 7 - 11 years old) were assessed via computerized versions of subtests of the Goldman-Fristoe-Woodcock Auditory Skills Test Battery. The computerized assessment correctly identified 92.5% of the LD group and 65% of the normal control children. (DB)

Facilitating Engaged Learning in the Interaction Age Taking a Pedagogically-Disciplined Approach to Innovation with Emergent Technologies

ERIC Educational Resources Information Center

Brill, Jennifer M.; Park, Yeonjeong

2008-01-01

The purposes of this paper are to explore emerging technologies, engaged learning, and features and students of the Interaction Age and to identify connections across these three realms for future research and practice. We begin by highlighting those elements of the Interaction Age that suggest a shift in the affordances and applications of…

Identifying Needs and Enhancing Learning about Climate Change Adaptation for Water Professionals at the Post-Graduate Level

ERIC Educational Resources Information Center

George, David Alan; Tan, Poh-Ling; Clewett, Jeffrey Frank

2016-01-01

Using a participatory learning approach, we report on the delivery and evaluation of a climate change and risk assessment tool to help manage water risks within the agricultural sector. Post-graduate water-professional students from a range of countries, from both developed and emerging economies were involved in using this tool. Our approach…

Identification and Analysis of Learning Preferences of Mentally Ill Adults in Rehabilitative Psychosocial Therapy at the Anderson Mental Health Center.

ERIC Educational Resources Information Center

Newman, Michael K.

A study identified and analyzed the learning preferences of 17 seriously and chronically mentally ill adults participating in the rehabilitative psychosocial therapy program at the Toxaway Church Site of the Anderson Mental Health Center. Staff perceived as boring and unfocused the traditional treatment approach that relied mainly upon…

Planning and Designing Academic Library Learning Spaces: Expert Perspectives of Architects, Librarians, and Library Consultants. Project Information Literacy Research Report. The Practitioner Series

ERIC Educational Resources Information Center

Head, Alison J.

2016-01-01

This paper identifies approaches, challenges, and best practices related to planning and designing today's academic library learning spaces. As part of the Project Information Literacy (PIL) Practitioner Series, qualitative data is presented from 49 interviews conducted with a sample of academic librarians, architects, and library consultants.…

Curricular Approaches to Connecting Subtraction to Addition and Fostering Fluency with Basic Differences in Grade 1

ERIC Educational Resources Information Center

Baroody, Arthur J.

2016-01-01

Six widely used US Grade 1 curricula do not adequately address the following three developmental prerequisites identified by a proposed learning trajectory for the meaningful learning of the subtraction-as-addition strategy (e.g., for 13-8 think "what + 8 = 13?"): (a) reverse operations (adding 8 is undone by subtracting 8); (b) common…

Alzheimer's Disease and Other Dementias: An Organizational Approach to Identifying and Addressing Practices and Learning Needs of Family Physicians

ERIC Educational Resources Information Center

Allen, Michael; Ferrier, Suzanne; Sargeant, Joan; Loney, Elaine; Bethune, Graeme; Murphy, Gerard

2005-01-01

Caring for patients with dementia is complex and demanding. Since family physicians (FPs) provide much of this care, we examined their practices, learning needs, and barriers to care concerning Alzheimer's disease and other dementias. We surveyed 392 (approximately 50%) Nova Scotia FPs and conducted focus groups and interviews with: FPs; staff of…

Strategies for Digital Inclusion: Towards a Pedagogy for Embracing and Sustaining Student Diversity and Engagement with Online Learning

ERIC Educational Resources Information Center

Clarida, Baylie Hart; Bobeva, Milena; Hutchings, Maggie; Taylor, Jacqui

2016-01-01

This paper reports on the progress of a current PhD research study. The research study will evolve through four phases and eventually develop a conceptual framework for effective teaching and learning approaches that influence digital inclusion and exclusion of students from diverse backgrounds. It will also seek to identify differences in learner…

A Specialist Professional Experience Learning Community for Primary Pre-Service Teachers Focussed on Mathematical Problem Solving

ERIC Educational Resources Information Center

Cavanagh, Michael; McMaster, Heather

2017-01-01

Problem solving has been identified as an important approach to learning and teaching mathematics, yet many primary pre-service teachers (PSTs) struggle to implement it during their professional experience. In this paper, we report the experiences of a group of four primary PSTs who, in an additional professional experience placement, formed a…

Problem-Based Learning: Using Ill-Structured Problems in Biology Project Work

ERIC Educational Resources Information Center

Chin, Christine; Chia, Li-Gek

2006-01-01

This case study involved year 9 students carrying out project work in biology via problem-based learning. The purpose of the study was to (a) find out how students approach and work through ill-structured problems, (b) identify some issues and challenges related to the use of such problems, and (c) offer some practical suggestions on the…

Training tomorrow's clinicians today--managed care essentials: a process for curriculum development.

PubMed

Colenda, C C; Wadland, W; Hayes, O; Anderson, W; Priester, F; Pearson, R; Keefe, C; Fleck, L

2000-05-01

To develop a managed care curriculum for primary care residents. This article outlines a 4-stage curriculum development process focusing on concepts of managed care organization and finance. The stages consist of: (1) identifying the curriculum development work group and framing the scope of the curriculum, (2) identifying stakeholder buy-in and expectations, (3) choosing curricular topics and delivery mechanisms, and (4) outlining the evaluation process. Key elements of building a curriculum development team, content objectives of the curriculum, the rationale for using problem-based learning, and finally, lessons learned from the partnership among the stakeholders are reviewed. The curriculum was delivered to an entering group of postgraduate-year 1 primary care residents. Attitudes among residents toward managed care remained relatively negative and stable over the yearlong curriculum, especially over issues relating to finance, quality of care, control and autonomy of practitioners, time spent with patients, and managed care's impact on the doctor-patient relationship. Residents' baseline knowledge of core concepts about managed care organization and finance improved during the year that the curriculum was delivered. Satisfaction with a problem-based learning approach was high. Problem-based learning, using real-life clinical examples, is a successful approach to resident instruction about managed care.

Assessment approaches in massive open online courses: Possibilities, challenges and future directions

NASA Astrophysics Data System (ADS)

Xiong, Yao; Suen, Hoi K.

2018-03-01

The development of massive open online courses (MOOCs) has launched an era of large-scale interactive participation in education. While massive open enrolment and the advances of learning technology are creating exciting potentials for lifelong learning in formal and informal ways, the implementation of efficient and effective assessment is still problematic. To ensure that genuine learning occurs, both assessments for learning (formative assessments), which evaluate students' current progress, and assessments of learning (summative assessments), which record students' cumulative progress, are needed. Providers' more recent shift towards the granting of certificates and digital badges for course accomplishments also indicates the need for proper, secure and accurate assessment results to ensure accountability. This article examines possible assessment approaches that fit open online education from formative and summative assessment perspectives. The authors discuss the importance of, and challenges to, implementing assessments of MOOC learners' progress for both purposes. Various formative and summative assessment approaches are then identified. The authors examine and analyse their respective advantages and disadvantages. They conclude that peer assessment is quite possibly the only universally applicable approach in massive open online education. They discuss the promises, practical and technical challenges, current developments in and recommendations for implementing peer assessment. They also suggest some possible future research directions.

Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning.

PubMed

Wu, Bian; Wang, Minhong; Grotzer, Tina A; Liu, Jun; Johnson, Janice M

2016-08-22

Practical experience with clinical cases has played an important role in supporting the learning of clinical reasoning. However, learning through practical experience involves complex processes difficult to be captured by students. This study aimed to examine the effects of a computer-based cognitive-mapping approach that helps students to externalize the reasoning process and the knowledge underlying the reasoning process when they work with clinical cases. A comparison between the cognitive-mapping approach and the verbal-text approach was made by analyzing their effects on learning outcomes. Fifty-two third-year or higher students from two medical schools participated in the study. Students in the experimental group used the computer-base cognitive-mapping approach, while the control group used the verbal-text approach, to make sense of their thinking and actions when they worked with four simulated cases over 4 weeks. For each case, students in both groups reported their reasoning process (involving data capture, hypotheses formulation, and reasoning with justifications) and the underlying knowledge (involving identified concepts and the relationships between the concepts) using the given approach. The learning products (cognitive maps or verbal text) revealed that students in the cognitive-mapping group outperformed those in the verbal-text group in the reasoning process, but not in making sense of the knowledge underlying the reasoning process. No significant differences were found in a knowledge posttest between the two groups. The computer-based cognitive-mapping approach has shown a promising advantage over the verbal-text approach in improving students' reasoning performance. Further studies are needed to examine the effects of the cognitive-mapping approach in improving the construction of subject-matter knowledge on the basis of practical experience.

Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

NASA Astrophysics Data System (ADS)

Rap, Shelley; Blonder, Ron

2016-02-01

We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse events were tallied in the different groups. We analyzed the different events that were found in chemistry learning Facebook groups (CLFGs). The analysis revealed that seven types of interactions were observed in the CLFGs: The most common interaction (47 %) dealt with organizing learning (e.g., announcements regarding homework, the location of the next class); learning interactions were observed in 22 % of the posts, and links to learning materials and social interactions constituted about 20 % each. The learning events that were ascertained underwent a deeper examination and three different types of chemistry learning interactions were identified. This examination was based on the theoretical framework of the commognitive approach to learning (Sfard in Thinking as communicating. Cambridge University Press, Cambridge, 2008), which will be explained. The identified learning interactions that were observed in the Facebook groups illustrate the potential of SNs to serve as an additional tool for teachers to advance their students' learning of chemistry.

Implementation of a flipped classroom approach to promote active learning in the third-year surgery clerkship.

PubMed

Lewis, Catherine E; Chen, David C; Relan, Anju

2018-02-01

Constructivist student-centered instructional models such as the flipped classroom (FC) have been shown to improve learning. A FC approach was implemented for the surgery clerkship. Data was collected in phase 1 to evaluate student learning and attitudes. Based on these results, questions for the phase 2 open-ended survey were developed to improve understanding of learner attitudes, and ascertain how well the FC aligns with constructivist principles. There was no significant difference in shelf exam performance between the control and intervention groups. A majority of students agreed that they preferred the FC over lectures, and that their learning improved. Open-ended survey analysis demonstrated that the FC fostered self-directed, active learning, and that the in-class sessions facilitated application of concepts and deeper learning. Areas identified for improvement included better alignment with learning preferences through greater variety of pre-class learning options, improvement of podcast technical quality, and utilization of smaller in-class discussion groups. Students had a positive perception of the FC. The FC supports self-directed and more active and deeper in-class learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantum adiabatic machine learning

NASA Astrophysics Data System (ADS)

Pudenz, Kristen L.; Lidar, Daniel A.

2013-05-01

We develop an approach to machine learning and anomaly detection via quantum adiabatic evolution. This approach consists of two quantum phases, with some amount of classical preprocessing to set up the quantum problems. In the training phase we identify an optimal set of weak classifiers, to form a single strong classifier. In the testing phase we adiabatically evolve one or more strong classifiers on a superposition of inputs in order to find certain anomalous elements in the classification space. Both the training and testing phases are executed via quantum adiabatic evolution. All quantum processing is strictly limited to two-qubit interactions so as to ensure physical feasibility. We apply and illustrate this approach in detail to the problem of software verification and validation, with a specific example of the learning phase applied to a problem of interest in flight control systems. Beyond this example, the algorithm can be used to attack a broad class of anomaly detection problems.

A Theoretical Framework for Media Law Courses (Approaches to Teaching Freedom of Expression).

ERIC Educational Resources Information Center

Helle, Steven

1991-01-01

Suggests that most students prefer teachers have a theme that provides coherence and cohesiveness to media law courses. Explains how libertarian and neoliberal themes can guide learning and enumerates some of the principles of the two theories. Identifies drawbacks of the case analysis approach to such courses. (SG)

Process and Product Explanations for What Works for LD and Why

ERIC Educational Resources Information Center

Womack, Sid T.; Hanna, Shellie L.; Woodall, Peggy; Callaway, Rebecca

2011-01-01

In the history of learning disabilities education, practitioners and researchers alike have been mired in controversies about product and process approaches. This review of literature attempts to identify the most useful research about product and process approaches and to suggest situations in which each may be most appropriate. Some literature…

Identifying Effective Pedagogical Approaches for Online Workplace Training: A Case Study of the South African Wood Products Manufacturing Sector

ERIC Educational Resources Information Center

Macdonald, Ian S.; Bullen, Mark; Kozak, R. A.

2007-01-01

This study investigated appropriate pedagogical techniques for workplace e-learning programs in the South African wood products (furniture) manufacturing sector. The study found that learners responded favourably to constructivist teaching approaches, such as asynchronous discussions, open-ended task-based activities, and assignments incorporating…

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.

How transformational learning promotes caring, consultation and creativity, and ultimately contributes to sustainable development: Lessons from the Partnership for Education and Research about Responsible Living (PERL) network

NASA Astrophysics Data System (ADS)

Thoresen, Victoria Wyszynski

2017-12-01

Oases of learning which are transformative and lead to significant behavioural change can be found around the globe. Transformational learning has helped learners not only to understand what they have been taught but also to re-conceptualise and re-apply this understanding to their daily lives. Unfortunately, as many global reports indicate, inspirational transformational learning approaches for sustainable development are rare and have yet to become the norm - despite calls for such approaches by several outstanding educators and organisations. This article examines three learning approaches developed by the network of the Partnership for Education and Research about Responsible Living (PERL). These approaches are structured around core elements of transformative learning for sustainable development, yet focus particularly on the ability to care, consult with others and be creative. They seem to depend on the learners' ability to articulate their perceptions of sustainable development in relation to their own values and to identify how these are actualised in their daily life. Together with other core elements of transformative learning, an almost magical (not precisely measurable) synergy then emerges. The intensity of this synergy appears to be directly related to the individual learner's understanding of the contradictions, interlinkages and interdependencies of modern society. The impact of this synergy seems to be concurrent with the extent to which the learner engages in a continual learning process with those with whom he/she has contact. The findings of this study suggest that mainstreaming transformational learning for sustainable development in ways that release the "magic synergy of creative caring" can result in the emergence of individuals who are willing and able to move from "business as usual" towards more socially just, economically equitable, and environmentally sensitive behaviour.

A Novel Local Learning based Approach With Application to Breast Cancer Diagnosis

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

Xu, Songhua; Tourassi, Georgia

2012-01-01

The purpose of this study is to develop and evaluate a novel local learning-based approach for computer-assisted diagnosis of breast cancer. Our new local learning based algorithm using the linear logistic regression method as its base learner is described. Overall, our algorithm will perform its stochastic searching process until the total allowed computing time is used up by our random walk process in identifying the most suitable population subdivision scheme and their corresponding individual base learners. The proposed local learning-based approach was applied for the prediction of breast cancer given 11 mammographic and clinical findings reported by physicians using themore » BI-RADS lexicon. Our database consisted of 850 patients with biopsy confirmed diagnosis (290 malignant and 560 benign). We also compared the performance of our method with a collection of publicly available state-of-the-art machine learning methods. Predictive performance for all classifiers was evaluated using 10-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Figure 1 reports the performance of 54 machine learning methods implemented in the machine learning toolkit Weka (version 3.0). We introduced a novel local learning-based classifier and compared it with an extensive list of other classifiers for the problem of breast cancer diagnosis. Our experiments show that the algorithm superior prediction performance outperforming a wide range of other well established machine learning techniques. Our conclusion complements the existing understanding in the machine learning field that local learning may capture complicated, non-linear relationships exhibited by real-world datasets.« less

Enhancing meaningful learning and self-efficacy through collaboration between dental hygienist and physiotherapist students - a scholarship project.

PubMed

Johannsen, A; Bolander-Laksov, K; Bjurshammar, N; Nordgren, B; Fridén, C; Hagströmer, M

2012-11-01

Within the field of Dental Hygiene (DH) and Physiotherapy (PT), students are taught to use an evidence-based approach. Educators need to consider the nature of evidence-based practice from the perspective of content knowledge and learning strategies. Such effort to seek best available evidence and to apply a systematic and scholarly approach to teaching and learning is called scholarship of teaching and learning. To evaluate the application of the scholarship model including an evidence-based approach to enhance meaningful learning and self-efficacy among DH and PT students. Based on the research on student learning, three central theories were identified (constructivism, meaningful learning and self-efficacy). These were applied in our context to support learner engagement and the application of prior knowledge in a new situation. The DH students performed an oral health examination on the PT students, and the PT students performed an individual health test on the DH students; both groups used motivational interviewing. Documentation of student's learning experience was carried out through seminars and questionnaires. The students were overall satisfied with the learning experience. Most appreciated are that it reflected a 'real' professional situation and that it also reinforced important learning from their seminars. The scholarship model made the teachers aware of the importance of evidence-based teaching. Furthermore, the indicators for meaningful learning and increased self-efficacy were high, and the students became more engaged by practising in a real situation, more aware of other health professions and reflected about tacit knowledge. © 2012 John Wiley & Sons A/S.

Integrating Response to Intervention (RTI) with Neuropsychology: A Scientific Approach to Reading

ERIC Educational Resources Information Center

Feifer, Steven G.

2008-01-01

This article integrates the fundamental components of both "Response to Intervention" (RTI) and cognitive neuropsychology when identifying reading disorders in children. Both proponents of RTI and cognitive neuropsychology agree the "discrepancy model" is not a reliable or valid method to identify learning disorders in school. In addition, both…

Identifying Teacher Needs for Promoting Education through Science as a Paradigm Shift in Science Education

ERIC Educational Resources Information Center

Holbrook, J.; Rannikmae, M.; Valdmann, A.

2014-01-01

This paper identifies an "education through science" philosophy for school science teaching at the secondary level and determines its interrelationship with approaches to student acquisition of key educational competences and the identification of teacher needs to promote meaningful learning during science lessons. Based on the…

Translating theory into practice: integrating the affective and cognitive learning dimensions for effective instruction in engineering education

NASA Astrophysics Data System (ADS)

Alias, Maizam; Lashari, Tahira Anwar; Abidin Akasah, Zainal; Jahaya Kesot, Mohd.

2014-03-01

Learning in the cognitive domain is highly emphasised and has been widely investigated in engineering education. Lesser emphasis is placed on the affective dimension although the role of affects has been supported by research. The lack of understanding on learning theories and how they may be translated into classroom application of teaching and learning is one factor that contributes to this situation. This paper proposes a working framework for integrating the affective dimension of learning into engineering education that is expected to promote better learning within the cognitive domain. Four major learning theories namely behaviourism, cognitivism, socio-culturalism, and constructivism were analysed and how affects are postulated to influence cognition are identified. The affective domain constructs identified to be important are self-efficacy, attitude and locus of control. Based on the results of the analysis, a framework that integrates methodologies for achieving learning in the cognitive domain with the support of the affective dimension of learning is proposed. It is expected that integrated approach can be used as a guideline to engineering educators in designing effective and sustainable instructional material that would result in the effective engineers for future development.

Didactical Design Material Units of Distance and Speed to Developed Mathematical Connection in Elementary School

NASA Astrophysics Data System (ADS)

Jannah, R. R.; Apriliya, S.; Karlimah

2017-03-01

This study aims to develop alternative instructional design based of barriers learning which identified by developing mathematical connection capabilities to the material unit of distance and speed. The research was conducted in the fifth grade elementary school Instructional design is complemented with a hypothetical learning trajectory in the form of a pedagogical didactic anticipation. The method used is descriptive method with qualitative approach. Techniques data collection used were observation, interviews, and documentation. The instrument used the researchers themselves are equipped with an instrument written test. The data were analyzed qualitatively to determine the student learning obstacles, then arrange hypothetical learning trajectory and pedagogical didactic anticipation. Learning obstacle are identified, it is learning obstacle related the connections between mathematical topics, learning obstacle related with other disciplines, and learning obstacle related with everyday life. The results of this research are improvement and development of didactic design in mathematics which has activities mathematical connection to the material unit of distance and speed in elementary school. The learning activities are carried out is using varied methods include method lectures, demonstrations, practice and exercise, as well as using the modified instructional media.

Bridging theory and practice: Mixed methods approach to instruction of law and ethics within the pharmaceutical sciences.

PubMed

Wilby, Kyle John; Nasr, Ziad Ghantous

2016-11-01

Background: Professional responsibilities are guided by laws and ethics that must be introduced and mastered within pharmaceutical sciences training. Instructional design to teaching typically introduces concepts in a traditional didactic approach and requires student memorization prior to application within practice settings. Additionally, many centers rely on best practices from abroad, due to lack of locally published laws and guidance documents. Objectives: The aim of this paper was to summarize and critically evaluate a professional skills laboratory designed to enhance learning through diversity in instructional methods relating to pharmacy law and best practices regarding narcotics, controlled medications, and benzodiazepines. Setting: This study took place within the Professional Skills Laboratory at the College of Pharmacy at Qatar University. Method: A total of 25 students participated in a redesigned laboratory session administered by a faculty member, clinical lecturer, teaching assistant, and a professional skills laboratory technician. The laboratory consisted of eight independent stations that students rotated during the 3-h session. Stations were highly interactive in nature and were designed using non-traditional approaches such as charades, role-plays, and reflective drawings. All stations attempted to have students relate learned concepts to practice within Qatar. Main outcome measures: Student perceptions of the laboratory were measured on a post-questionnaire and were summarized descriptively. Using reflection and consensus techniques, two faculty members completed a SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis in preparation for future cycles. Results: 100% (25/25) of students somewhat or strongly agreed that their knowledge regarding laws and best practices increased and that their learning experience was enhanced by a mixed-methods approach. A total of 96% (24/25) of students stated that the mixed-methods instructional approach should be continued in the future. The SWOC analysis identified the mixed methods approach and student feedback as strengths and opportunities, while resource shortages and lack of impact assessment were identified as weaknesses and challenges. Conclusion: Creative redesign of instructional methods pertaining to law and best practices was effective to achieve positive student perceptions regarding instructional methods and learning. Future cycles should include rigorous assessment methods to evaluate impact on student learning and practice.

A Call for an Integrated Program of Assessment

PubMed Central

Regehr, Glenn

2017-01-01

An integrated curriculum that does not incorporate equally integrated assessment strategies is likely to prove ineffective in achieving the desired educational outcomes. We suggest it is time for colleges and schools of pharmacy to re-engineer their approach to assessment. To build the case, we first discuss the challenges leading to the need for curricular developments in pharmacy education. We then turn to the literature that informs how assessment can influence learning, introduce an approach to learning assessment that is being used by several medical education programs, and provide some examples of this approach in operation. Finally, we identify some of the challenges faced in adopting such an integrated approach to assessment and suggest that this is an area ripe with research opportunities for pharmacy educators. PMID:28630518

Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics.

PubMed

Ding, Michael Q; Chen, Lujia; Cooper, Gregory F; Young, Jonathan D; Lu, Xinghua

2018-02-01

Precision oncology involves identifying drugs that will effectively treat a tumor and then prescribing an optimal clinical treatment regimen. However, most first-line chemotherapy drugs do not have biomarkers to guide their application. For molecularly targeted drugs, using the genomic status of a drug target as a therapeutic indicator has limitations. In this study, machine learning methods (e.g., deep learning) were used to identify informative features from genome-scale omics data and to train classifiers for predicting the effectiveness of drugs in cancer cell lines. The methodology introduced here can accurately predict the efficacy of drugs, regardless of whether they are molecularly targeted or nonspecific chemotherapy drugs. This approach, on a per-drug basis, can identify sensitive cancer cells with an average sensitivity of 0.82 and specificity of 0.82; on a per-cell line basis, it can identify effective drugs with an average sensitivity of 0.80 and specificity of 0.82. This report describes a data-driven precision medicine approach that is not only generalizable but also optimizes therapeutic efficacy. The framework detailed herein, when successfully translated to clinical environments, could significantly broaden the scope of precision oncology beyond targeted therapies, benefiting an expanded proportion of cancer patients. Mol Cancer Res; 16(2); 269-78. ©2017 AACR . ©2017 American Association for Cancer Research.

Advancing clinical reasoning in virtual patients - development and application of a conceptual framework.

PubMed

Hege, Inga; Kononowicz, Andrzej A; Berman, Norman B; Lenzer, Benedikt; Kiesewetter, Jan

2018-01-01

Background: Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key concepts of the clinical reasoning process in a qualitative approach and draw conclusions on how each concept can be enhanced to advance the learning of clinical reasoning with virtual patients. Methods: We chose a grounded theory approach to identify key categories and concepts of learning clinical reasoning and develop a framework. Throughout this process, the emerging codes were discussed with a panel of interdisciplinary experts. In a second step we applied the framework to virtual patients. Results: Based on the data we identified the core category as the "multifactorial nature of learning clinical reasoning". This category is reflected in the following five main categories: Psychological Theories, Patient-centeredness, Context, Learner-centeredness, and Teaching/Assessment. Each category encompasses between four and six related concepts. Conclusions: With our approach we were able to elaborate how key categories and concepts of clinical reasoning can be applied to virtual patients. This includes aspects such as allowing learners to access a large number of VPs with adaptable levels of complexity and feedback or emphasizing dual processing, errors, and uncertainty.

Advancing clinical reasoning in virtual patients – development and application of a conceptual framework

PubMed Central

Hege, Inga; Kononowicz, Andrzej A.; Berman, Norman B.; Lenzer, Benedikt; Kiesewetter, Jan

2018-01-01

Background: Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key concepts of the clinical reasoning process in a qualitative approach and draw conclusions on how each concept can be enhanced to advance the learning of clinical reasoning with virtual patients. Methods: We chose a grounded theory approach to identify key categories and concepts of learning clinical reasoning and develop a framework. Throughout this process, the emerging codes were discussed with a panel of interdisciplinary experts. In a second step we applied the framework to virtual patients. Results: Based on the data we identified the core category as the "multifactorial nature of learning clinical reasoning". This category is reflected in the following five main categories: Psychological Theories, Patient-centeredness, Context, Learner-centeredness, and Teaching/Assessment. Each category encompasses between four and six related concepts. Conclusions: With our approach we were able to elaborate how key categories and concepts of clinical reasoning can be applied to virtual patients. This includes aspects such as allowing learners to access a large number of VPs with adaptable levels of complexity and feedback or emphasizing dual processing, errors, and uncertainty. PMID:29497697

Links between motor control and classroom behaviors: Moderation by low birth weight

PubMed Central

Razza, Rachel A.; Martin, Anne; Brooks-Gunn, Jeanne

2016-01-01

It is unclear from past research on effortful control whether one of its components, motor control, independently contributes to adaptive classroom behaviors. The goal of this study was to identify associations between early motor control, measured by the walk-a-line task at age 3, and teacher-reported learning-related behaviors (approaches to learning and attention problems) and behavior problems in kindergarten classrooms. Models tested whether children who were vulnerable to poorer learning behaviors and more behavior problems due to having been born low birth weight benefited more, less, or the same as other children from better motor control. Data were drawn from the national Fragile Families and Child-Wellbeing Study (n = 751). Regression models indicated that motor control was significantly associated with better approaches to learning and fewer behavior problems. Children who were low birth weight benefitted more than normal birth weight children from better motor control with respect to their approaches to learning, but equally with respect to behavior problems. Additionally, for low but not normal birth weight children, better motor control predicted fewer attention problems. These findings suggest that motor control follows a compensatory model of development for low birth weight children and classroom behaviors. PMID:27594776

Deep learning with non-medical training used for chest pathology identification

NASA Astrophysics Data System (ADS)

Bar, Yaniv; Diamant, Idit; Wolf, Lior; Greenspan, Hayit

2015-03-01

In this work, we examine the strength of deep learning approaches for pathology detection in chest radiograph data. Convolutional neural networks (CNN) deep architecture classification approaches have gained popularity due to their ability to learn mid and high level image representations. We explore the ability of a CNN to identify different types of pathologies in chest x-ray images. Moreover, since very large training sets are generally not available in the medical domain, we explore the feasibility of using a deep learning approach based on non-medical learning. We tested our algorithm on a dataset of 93 images. We use a CNN that was trained with ImageNet, a well-known large scale nonmedical image database. The best performance was achieved using a combination of features extracted from the CNN and a set of low-level features. We obtained an area under curve (AUC) of 0.93 for Right Pleural Effusion detection, 0.89 for Enlarged heart detection and 0.79 for classification between healthy and abnormal chest x-ray, where all pathologies are combined into one large class. This is a first-of-its-kind experiment that shows that deep learning with large scale non-medical image databases may be sufficient for general medical image recognition tasks.

Improving Group Work Practices in Teaching Life Sciences: Trialogical Learning

NASA Astrophysics Data System (ADS)

Tammeorg, Priit; Mykkänen, Anna; Rantamäki, Tomi; Lakkala, Minna; Muukkonen, Hanni

2017-08-01

Trialogical learning, a collaborative and iterative knowledge creation process using real-life artefacts or problems, familiarizes students with working life environments and aims to teach skills required in the professional world. We target one of the major limitation factors for optimal trialogical learning in university settings, inefficient group work. We propose a course design combining effective group working practices with trialogical learning principles in life sciences. We assess the usability of our design in (a) a case study on crop science education and (b) a questionnaire for university teachers in life science fields. Our approach was considered useful and supportive of the learning process by all the participants in the case study: the students, the stakeholders and the facilitator. Correspondingly, a group of university teachers expressed that the trialogical approach and the involvement of stakeholders could promote efficient learning. In our case in life sciences, we identified the key issues in facilitating effective group work to be the design of meaningful tasks and the allowance of sufficient time to take action based on formative feedback. Even though trialogical courses can be time consuming, the experience of applying knowledge in real-life cases justifies using the approach, particularly for students just about to enter their professional careers.

The Desired Learning Outcomes of School-Based Nutrition/Physical Activity Health Education: A Health Literacy Constructed Delphi Survey of Finnish Experts

ERIC Educational Resources Information Center

Ormshaw, Michael James; Kokko, Sami Petteri; Villberg, Jari; Kannas, Lasse

2016-01-01

Purpose: The purpose of this paper is to utilise the collective opinion of a group of Finnish experts to identify the most important learning outcomes of secondary-level school-based health education, in the specific domains of physical activity and nutrition. Design/ Methodology/ Approach: The study uses a Delphi survey technique to collect the…

Generation Y Students: Appropriate Learning Styles and Teaching Approaches in the Economic and Management Sciences Faculty

ERIC Educational Resources Information Center

Wessels, P. L.; Steenkamp, L. P.

2009-01-01

Generation Y students (born after 1982) have developed a different set of attitudes and aptitudes as a result of growing up in an IT and media-rich environment. This article has two objectives: firstly to discuss the learning styles preferred by generation Y students in order to identify the effect of these preferences on tertiary education in…

Hands-On or Video-Based Learning with ANTicipation? A Comparative Approach to Identifying Student Motivation and Learning Enjoyment during a Lesson about Ants

ERIC Educational Resources Information Center

Sammet, Rebecca; Kutta, Anna-Maria; Dreesmann, Daniel

2015-01-01

The observation of living animals in school laboratories provides authentic views of biological research. Various studies stress the importance of primary experiences in biology classes. However, educational films may serve as an alternative in some cases. The aim of this study was to investigate student motivation before and after treatments,…

Differential Learning as a Key Training Approach to Improve Creative and Tactical Behavior in Soccer

ERIC Educational Resources Information Center

Santos, Sara; Coutinho, Diogo; Gonçalves, Bruno; Schöllhorn, Wolfgang; Sampaio, Jaime; Leite, Nuno

2018-01-01

Purpose: The aim of this study was to identify the effects of a differential-learning program, embedded in small-sided games, on the creative and tactical behavior of youth soccer players. Forty players from under-13 (U13) and under-15 (U15) were allocated into control and experimental groups and were tested using a randomized pretest to posttest…

Exploring Online Students' Self-Regulated Learning with Self-Reported Surveys and Log Files: A Data Mining Approach

ERIC Educational Resources Information Center

Cho, Moon-Heum; Yoo, Jin Soung

2017-01-01

Many researchers who are interested in studying students' online self-regulated learning (SRL) have heavily relied on self-reported surveys. Data mining is an alternative technique that can be used to discover students' SRL patterns from large data logs saved on a course management system. The purpose of this study was to identify students' online…

A Bridge to Active Learning: A Summer Bridge Program Helps Students Maximize Their Active-Learning Experiences and the Active-Learning Experiences of Others.

PubMed

Cooper, Katelyn M; Ashley, Michael; Brownell, Sara E

2017-01-01

National calls to improve student academic success in college have sparked the development of bridge programs designed to help students transition from high school to college. We designed a 2-week Summer Bridge program that taught introductory biology content in an active-learning way. Through a set of exploratory interviews, we unexpectedly identified that Bridge students had developed sophisticated views of active learning, even though this was not an explicit goal of the program. We conducted an additional set of semistructured interviews that focused on active learning and compared the interviews of Bridge students with those from non-Bridge students who had been eligible for but did not participate in the program. We used the constant comparative method to identify themes from the interviews. We found that Bridge students perceived that, because they knew how to approach active learning and viewed it as important, they benefited more from active learning in introductory biology than non-Bridge students. Specifically, Bridge students seemed to be more aware of their own learning gains from participating in active learning. Compared with the majority of non-Bridge students, the majority of Bridge students described using a greater variety of strategies to maximize their experiences in active learning. Finally, in contrast to non-Bridge students, Bridge students indicated that they take an equitable approach to group work. These findings suggest that we may be able to prime students to maximize their own and other's experiences in active learning. © 2017 K. M. Cooper et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Interactive Cumulative Burden Assessment: Engaging Stakeholders in an Adaptive, Participatory and Transdisciplinary Approach

PubMed Central

Shrestha, Rehana; van Maarseveen, Martin

2018-01-01

Cumulative burden assessment (CuBA) has the potential to inform planning and decision-making on health disparities related to multiple environmental burdens. However, scholars have raised concerns about the social complexity to be dealt with while conducting CuBA, suggesting that it should be addressed in an adaptive, participatory and transdisciplinary (APT) approach. APT calls for deliberation among stakeholders by engaging them in a process of social learning and knowledge co-production. We propose an interactive stakeholder-based approach that facilitates a science-based stakeholder dialogue as an interface for combining different knowledge domains and engendering social learning in CuBA processes. Our approach allows participants to interact with each other using a flexible and auditable CuBA model implemented within a shared workspace. In two workshops we explored the usefulness and practicality of the approach. Results show that stakeholders were enabled to deliberate on cumulative burdens collaboratively, to learn about the technical uncertainties and social challenges associated with CuBA, and to co-produce knowledge in a realm of both technical and societal challenges. The paper identifies potential benefits relevant for responding to social complexity in the CuBA and further recommends exploration of how our approach can enable or constraint social learning and knowledge co-production in CuBA processes under various institutional, social and political contexts. PMID:29401676

Problem based learning in midwifery - the teachers perspective.

PubMed

Rowan, Catherine J; McCourt, Christine; Bick, Debra; Beake, Sarah

2007-02-01

Problem- or evidence-based learning (PBL or EBL) has become more widely used in the education of health professionals. Although there has been research exploring its effectiveness and the student's perspective, there has been little research exploring the perceptions of the teacher. The objective of this study was to investigate the experiences of teachers facilitating a problem based learning curriculum in midwifery. The study took place at Thames Valley University, which has implemented this approach across the entire curriculum. Semi-structured interviews were undertaken following random selection from two groups of teachers; those more experienced as teachers and those who had entered teaching more recently. Aspects of the teacher's role identified included questioning students to draw out their knowledge and understanding and to help students challenge each other, discuss and evaluate their learning. Strategies used varied depending on the stage of the programme. Difficulties encountered were mostly in relation to facilitating groups of differing backgrounds and ability and seeking to enable the students to work well together. Key challenges for teachers were in relation to developing facilitation skills, balancing input or guidance with facilitating independent learning. Problem based learning was perceived to be beneficial in helping students relate theory to practice and in encouraging an active and enquiring approach to evidence, but teachers raised important questions about its practice. Tensions were identified between the constructivist theories on which the model of PBL rests and the formal requirements of an externally regulated professional curriculum.

Media Matter: The Effect of Medium of Presentation on Student's Recognition of Histopathology.

PubMed

Telang, Ajay; Jong, Nynke De; Dalen, Jan Van

2016-12-01

Pathology teaching has undergone transformation with the introduction of virtual microscopy as a teaching and learning tool. To assess if dental students can identify histopathology irrespective of the media of presentation and if the media affect student's oral pathology case based learning scores. The perception of students towards "hybrid" approach in teaching and learning histopathology in oral pathology was also assessed. A controlled experiment was conduc-ted on year 4 and year 5 dental student groups using a perfor-mance test and a questionnaire survey. A response rate of 81% was noted for the performance test as well as the questionnaire survey. Results show a significant effect of media on performance of students with virtual microscopy bringing out the best performance across all student groups in case based learning scenarios. The order of preference for media was found to be virtual microscopy followed by photomicrographs and light microscopy. However, 94% of students still prefer the present hybrid system for teaching and learning of oral pathology. The study shows that identification of histo-pathology by students is dependent on media and the type of media has a significant effect on the performance. Virtual microscopy is strongly perceived as a useful tool for learning which thus brings out the best performance, however; the hybrid approach still remains the most preferred approach for histopathology learning.

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

NASA Astrophysics Data System (ADS)

Lotte, F.; Bougrain, L.; Cichocki, A.; Clerc, M.; Congedo, M.; Rakotomamonjy, A.; Yger, F.

2018-06-01

Objective. Most current electroencephalography (EEG)-based brain–computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately ten years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. Approach. We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. Main results. We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. Significance. This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.

Missed opportunities for diagnosis: lessons learned from diagnostic errors in primary care.

PubMed

Goyder, Clare R; Jones, Caroline H D; Heneghan, Carl J; Thompson, Matthew J

2015-12-01

Because of the difficulties inherent in diagnosis in primary care, it is inevitable that diagnostic errors will occur. However, despite the important consequences associated with diagnostic errors and their estimated high prevalence, teaching and research on diagnostic error is a neglected area. To ascertain the key learning points from GPs' experiences of diagnostic errors and approaches to clinical decision making associated with these. Secondary analysis of 36 qualitative interviews with GPs in Oxfordshire, UK. Two datasets of semi-structured interviews were combined. Questions focused on GPs' experiences of diagnosis and diagnostic errors (or near misses) in routine primary care and out of hours. Interviews were audiorecorded, transcribed verbatim, and analysed thematically. Learning points include GPs' reliance on 'pattern recognition' and the failure of this strategy to identify atypical presentations; the importance of considering all potentially serious conditions using a 'restricted rule out' approach; and identifying and acting on a sense of unease. Strategies to help manage uncertainty in primary care were also discussed. Learning from previous examples of diagnostic errors is essential if these events are to be reduced in the future and this should be incorporated into GP training. At a practice level, learning points from experiences of diagnostic errors should be discussed more frequently; and more should be done to integrate these lessons nationally to understand and characterise diagnostic errors. © British Journal of General Practice 2015.

Cognitive Clusters in Specific Learning Disorder.

PubMed

Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo

The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The introduction of the single overarching diagnostic category of specific learning disorder (SLD) could underemphasize interindividual clinical differences regarding intracategory cognitive functioning and learning proficiency, according to current models of multiple cognitive deficits at the basis of neurodevelopmental disorders. The characterization of specific cognitive profiles associated with an already manifest SLD could help identify possible early cognitive markers of SLD risk and distinct trajectories of atypical cognitive development leading to SLD. In this perspective, we applied a cluster analysis to identify groups of children with a Diagnostic and Statistical Manual-based diagnosis of SLD with similar cognitive profiles and to describe the association between clusters and SLD subtypes. A sample of 205 children with a diagnosis of SLD were enrolled. Cluster analyses (agglomerative hierarchical and nonhierarchical iterative clustering technique) were used successively on 10 core subtests of the Wechsler Intelligence Scale for Children-Fourth Edition. The 4-cluster solution was adopted, and external validation found differences in terms of SLD subtype frequencies and learning proficiency among clusters. Clinical implications of these findings are discussed, tracing directions for further studies.

The effectiveness of Internet-based e-learning on clinician behaviour and patient outcomes: A systematic review.

PubMed

Sinclair, Peter M; Kable, Ashley; Levett-Jones, Tracy; Booth, Debbie

2016-05-01

The contemporary health workforce has a professional responsibility to maintain competency in practice. However, some difficulties exist with access to ongoing professional development opportunities, particularly for staff in rural and remote areas and those not enrolled in a formal programme of study. E-learning is at the nexus of overcoming these challenges. The benefits of e-learning have been reported in terms of increased accessibility to education, improved self-efficacy, knowledge generation, cost effectiveness, learner flexibility and interactivity. What is less clear, is whether improved self-efficacy or knowledge gained through e-learning influences healthcare professional behaviour or skill development, whether these changes are sustained, and whether these changes improve patient outcomes. To identify, appraise and synthesise the best available evidence for the effectiveness of e-learning programmes on health care professional behaviour and patient outcomes. A systematic review of randomised controlled trials was conducted to assess the effectiveness of e-learning programmes on clinician behaviour and patient outcomes. Electronic databases including CINAHL, Embase, ERIC, MEDLINE, Mosby's Index, Scopus and Cochrane - CENTRAL were searched in July 2014 and again in July 2015. Studies were reviewed and data extracted by two independent reviewers using the Joanna Briggs Institute standardised critical appraisal and data extraction instruments. Seven trials met the inclusion criteria for the analysis. Due to substantial instructional design, subject matter, study population, and methodological variation between the identified studies, statistical pooling was not possible and a meta-analysis could not be performed. Consequently, the findings of this systematic review are presented as a narrative review. The results suggest that e-learning was at least as effective as traditional learning approaches, and superior to no instruction at all in improving health care professional behaviour. There was variation in behavioural outcomes depending on the skill being taught, and the learning approach utilised. No papers were identified that reported the effectiveness of an e-learning programme on patient outcomes. This review found insufficient evidence regarding the effectiveness of e-learning on healthcare professional behaviour or patient outcomes, consequently further research in this area is warranted. Future randomised controlled trials should adhere to the CONSORT reporting guidelines in order to improve the quality of reporting, to allow evaluation of the effectiveness of e-learning programmes on healthcare professional behaviour and patient outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development and Evaluation of a Multimedia e-Learning Resource for Electrolyte and Acid-Base Disorders

ERIC Educational Resources Information Center

Davids, Mogamat Razeen; Chikte, Usuf M. E.; Halperin, Mitchell L.

2011-01-01

This article reports on the development and evaluation of a Web-based application that provides instruction and hands-on practice in managing electrolyte and acid-base disorders. Our teaching approach, which focuses on concepts rather than details, encourages quantitative analysis and a logical problem-solving approach. Identifying any dangers to…

University Teachers' Conceptions of "Changemaker": A Starting Point for Embedding Social Innovation in Learning and Teaching

ERIC Educational Resources Information Center

Alden Rivers, Bethany; Nie, Ming; Armellini, Alejandro

2015-01-01

Purpose: The purpose of this paper is to report on a study aimed at understanding the different conceptions that University of Northampton teachers hold of "Changemaker", an institutional initiative to develop capacities for social innovation. Design/methodology/approach: The study took a phenomenographic approach to identify a small…

Topical versus Chronological Organization of Lifespan Development: Does It Make a Difference in Student Retention and Understanding?

ERIC Educational Resources Information Center

Spangler, Brooke R.; Kiel, Elizabeth J.

2015-01-01

This study aimed to determine whether taking a chronological approach (CA) or topical approach (TA) to teaching developmental psychology resulted in different learning outcomes. Across two semesters, in four classes, 354 students participated (M[subscript age] = 19.76, SD[subscript age] = 2.93 years), 66% identifying as female. One instructor…

The Interrelationship of Emotion and Cognition when Students Undertake Collaborative Group Work Online: An Interdisciplinary Approach

ERIC Educational Resources Information Center

Robinson, Kathy

2013-01-01

In order to determine how emotions and cognition are experienced during collaborative group work online students' descriptions of their learning experience were interpreted using a qualitative approach. A common feature of these accounts was reference to difficulties and problems. Four main themes were identified from this data set. Two of the…

Spike sorting based upon machine learning algorithms (SOMA).

PubMed

Horton, P M; Nicol, A U; Kendrick, K M; Feng, J F

2007-02-15

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would only identify a known number of clusters. Our extra techniques automatically identify the number of clusters within the dataset, and their sizes, thereby reducing the chance of misclassification. We also discuss a new pre-processing technique, which transforms the data into a higher dimensional feature space revealing separable clusters. Using principal component analysis (PCA) alone may not achieve this. Our new approach appends the features acquired using PCA with features describing the geometric shapes that constitute a spike waveform. To validate our new spike sorting approach, we have applied it to multi-electrode array datasets acquired from the rat olfactory bulb, and from the sheep infero-temporal cortex, and using simulated data. The SOMA sofware is available at http://www.sussex.ac.uk/Users/pmh20/spikes.

Modeling and forecasting US presidential election using learning algorithms

NASA Astrophysics Data System (ADS)

Zolghadr, Mohammad; Niaki, Seyed Armin Akhavan; Niaki, S. T. A.

2017-09-01

The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president's approval rate, and others are considered in a stepwise regression to identify significant variables. The president's approval rate is identified as the most significant variable, based on which eight other variables are identified and considered in the model development. Preprocessing methods are applied to prepare the data for the learning algorithms. The proposed procedure significantly increases the accuracy of the model by 50%. The learning algorithms (ANN and SVR) proved to be superior to linear regression based on each method's calculated performance measures. The SVR model is identified as the most accurate model among the other models as this model successfully predicted the outcome of the election in the last three elections (2004, 2008, and 2012). The proposed approach significantly increases the accuracy of the forecast.

Novel Active Learning Experiences for Students to Identify Barriers to Independent Living for People with Disabilities.

PubMed

McArthur, Polly; Burch, Lillian; Moore, Katherine; Hodges, Mary Sue

2016-07-01

This article describes interactive learning about independent living for people with disabilities and features the partnership of the College of Nursing and a Center for Independent Living (CIL). Using qualitative descriptive approach, students' written reflections were analyzed. Through "Xtreme Challenge," 82 undergraduate nursing students participated in aspects of independent living as well as identifying barriers. Students were engaged and learned to consider the person before the disability. Moreover, students valued the activity leaders' openness, which facilitated understanding the point of view of a person with disability. The value of partnership was evident as it allowed students to participate in active learning, which led to growth in the affective domain. Students became aware of potential education resources through the CIL. This article will guide educators in designing experiences that teach nursing care at the individual, family, and community level for people living with disabilities. © 2015 Association of Rehabilitation Nurses.

The behaviours of nurses that increase student accountability for learning in clinical practice: An integrative review.

PubMed

Perry, Christina; Henderson, Amanda; Grealish, Laurie

2018-06-01

To identify nurses' behaviours that promote student accountability for learning in clinical practice. Health care services are experiencing significant strain in meeting clinical education requirements of increasing numbers of nursing students enrolled in undergraduate nursing programs. Internationally, the transition to university based education for nurses has seen the emergence of issues for busy clinicians trying to manage increasing workloads with responsibility for student learning. An understanding of what types of supervisor behaviours promote student accountability for learning, may support clinicians to more effectively manage their dual roles of clinical care and student support. An integrative approach was adopted for this review. A search of the Cumulative Index of Nursing and Allied Health Literature, Pubmed, Scopus and Embase was undertaken, limited to articles published between 2000 and March 2017. Whittemore and Knafls' (2005) framework for conducting integrative reviews was used to ensure a methodological and rigorous approach. Nine studies were considered. Behaviours emerged in relation to four themes including: belongingness associated with a genuine partnership; empowerment and increasing student self-efficacy; trust linked to increasing and staged independence; and balancing clinical and educational requirements. Behaviours of nurses significantly influence students' accountability for learning and accordingly, their ability to be adequately prepared for professional nursing practice. Understanding behaviours that impact on students' approach to clinical placement can guide nurses in their approach to facilitating student learning, in particular, behaviours that increase student responsibility and independence over the continuum of clinical education. Copyright © 2018 Elsevier Ltd. All rights reserved.

Teaching and learning based on peer review: a realistic approach in forensic sciences.

PubMed

Dinis-Oliveira, Ricardo Jorge; Magalhães, Teresa

2016-01-01

Teaching and learning methods need a continuous upgrade in higher education. However it is also true that some of the modern methodologies do not reduce or prevent school failure. Perhaps the real limitation is the inability to identify the true reasons that may explain it or ignore/undervalue the problem. In our opinion, one of the current constraints of the teaching/learning process is the excess of and inadequate bibliography recommended by the teacher, which results in continuous student difficulties and waste of time in searching and selecting useful information. The need to change the paradigm of the teaching/learning process comes also from employers. They claim forensic experts armed with useful knowledge to face professional life. It is therefore mandatory to identify the new needs and opportunities regarding pedagogical methodologies. This article reflects on the recent importance of peer review in teaching/learning forensic sciences based on the last 10 years of pedagogical experience inseparably from the scientific activity.

Storytelling and professional learning: a phenomenographic study of students' experience of patient digital stories in nurse education.

PubMed

Christiansen, Angela

2011-04-01

This paper reports the findings of a phenomenographic study which sought to identify the different ways in which patient digital stories influence students' professional learning. Patient digital stories are short multimedia presentations that combine personal narratives, images and music to create a unique and often emotional story of a patients' experience of health care. While these are increasingly used in professional education little is known about how and what students learn through engagement with patient digital stories. Drawing upon interviews with 20 students within a pre-registration nursing programme in the UK, the study identifies four qualitatively different ways in which students approach and make sense of patient digital stories with implications for learning and professional identity development. Through an identification of the critical aspects of this variation valuable insights are generated into the pedagogic principles likely to engender transformational learning and patient centred practice. Copyright © 2010 Elsevier Ltd. All rights reserved.

Teaching and learning based on peer review: a realistic approach in forensic sciences

PubMed Central

Dinis-Oliveira, Ricardo Jorge; Magalhães, Teresa

2016-01-01

Teaching and learning methods need a continuous upgrade in higher education. However it is also true that some of the modern methodologies do not reduce or prevent school failure. Perhaps the real limitation is the inability to identify the true reasons that may explain it or ignore/undervalue the problem. In our opinion, one of the current constraints of the teaching/learning process is the excess of and inadequate bibliography recommended by the teacher, which results in continuous student difficulties and waste of time in searching and selecting useful information. The need to change the paradigm of the teaching/learning process comes also from employers. They claim forensic experts armed with useful knowledge to face professional life. It is therefore mandatory to identify the new needs and opportunities regarding pedagogical methodologies. This article reflects on the recent importance of peer review in teaching/learning forensic sciences based on the last 10 years of pedagogical experience inseparably from the scientific activity. PMID:27547377

Student approaches for learning in medicine: What does it tell us about the informal curriculum?

PubMed Central

2011-01-01

Background It has long been acknowledged that medical students frequently focus their learning on that which will enable them to pass examinations, and that they use a range of study approaches and resources in preparing for their examinations. A recent qualitative study identified that in addition to the formal curriculum, students are using a range of resources and study strategies which could be attributed to the informal curriculum. What is not clearly established is the extent to which these informal learning resources and strategies are utilized by medical students. The aim of this study was to establish the extent to which students in a graduate-entry medical program use various learning approaches to assist their learning and preparation for examinations, apart from those resources offered as part of the formal curriculum. Methods A validated survey instrument was administered to 522 medical students. Factor analysis and internal consistence, descriptive analysis and comparisons with demographic variables were completed. The factor analysis identified eight scales with acceptable levels of internal consistency with an alpha coefficient between 0.72 and 0.96. Results Nearly 80% of the students reported that they were overwhelmed by the amount of work that was perceived necessary to complete the formal curriculum, with 74.3% believing that the informal learning approaches helped them pass the examinations. 61.3% believed that they prepared them to be good doctors. A variety of informal learning activities utilized by students included using past student notes (85.8%) and PBL tutor guides (62.7%), and being part of self-organised study groups (62.6%), and peer-led tutorials (60.2%). Almost all students accessed the formal school resources for at least 10% of their study time. Students in the first year of the program were more likely to rely on the formal curriculum resources compared to those of Year 2 (p = 0.008). Conclusions Curriculum planners should examine the level of use of informal learning activities in their schools, and investigate whether this is to enhance student progress, a result of perceived weakness in the delivery and effectiveness of formal resources, or to overcome anxiety about the volume of work expected by medical programs. PMID:22013994

Innovative Graduate Research Education for Advancement of Implementation Science in Adolescent Behavioral Health

PubMed Central

Levin, Bruce Lubotsky; Massey, Tom; Baldwin, Julie; Williamson, Heather

2016-01-01

An innovative approach to research education that integrates the theory and principles of implementation science, participatory research, and service learning in the area of adolescent behavioral health is presented. Qualitative interviews and surveys of program participants have been conducted to assess the program’s curricula, service-learning partnerships, student (scholar) satisfaction, and views of community partnerships and academic mentors. The Institute has experienced the successful completion of its first and second cohorts and enrollment of a third cohort of scholars. Community partners are utilizing results of service-learning projects to influence agency operations. Institute scholars have identified research and service learning experiences as key factors in the decision to apply to the Institute graduate certificate program. The availability of tuition support is identified as valuable but not ranked as the most important reason for scholar interest in the program. Academic mentors report positive relationships with community agencies. Future iterations of the program will expand options for distance learning and alternatives to traditional graduate education for community-based scholars. Community partner agency capacity for participation is expected to change over time. Methods are being identified to both sustain existing partnerships and develop new community partnership relationships. PMID:26746638

Innovative Graduate Research Education for Advancement of Implementation Science in Adolescent Behavioral Health.

PubMed

Burton, Donna L; Levin, Bruce Lubotsky; Massey, Tom; Baldwin, Julie; Williamson, Heather

2016-04-01

An innovative approach to research education that integrates the theory and principles of implementation science, participatory research, and service learning in the area of adolescent behavioral health is presented. Qualitative interviews and surveys of program participants have been conducted to assess the program's curricula, service-learning partnerships, student (scholar) satisfaction, and views of community partnerships and academic mentors. The Institute has experienced the successful completion of its first and second cohorts and enrollment of a third cohort of scholars. Community partners are utilizing results of service-learning projects to influence agency operations. Institute scholars have identified research and service learning experiences as key factors in the decision to apply to the Institute graduate certificate program. The availability of tuition support is identified as valuable but not ranked as the most important reason for scholar interest in the program. Academic mentors report positive relationships with community agencies. Future iterations of the program will expand options for distance learning and alternatives to traditional graduate education for community-based scholars. Community partner agency capacity for participation is expected to change over time. Methods are being identified to both sustain existing partnerships and develop new community partnership relationships.

Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

PubMed Central

Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan

2013-01-01

Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388

Errorless Learning in Cognitive Rehabilitation: A Critical Review

PubMed Central

Middleton, Erica L.; Schwartz, Myrna F.

2012-01-01

Cognitive rehabilitation research is increasingly exploring errorless learning interventions, which prioritize the avoidance of errors during treatment. The errorless learning approach was originally developed for patients with severe anterograde amnesia, who were deemed to be at particular risk for error learning. Errorless learning has since been investigated in other memory-impaired populations (e.g., Alzheimer's disease) and acquired aphasia. In typical errorless training, target information is presented to the participant for study or immediate reproduction, a method that prevents participants from attempting to retrieve target information from long-term memory (i.e., retrieval practice). However, assuring error elimination by preventing difficult (and error-permitting) retrieval practice is a potential major drawback of the errorless approach. This review begins with discussion of research in the psychology of learning and memory that demonstrates the importance of difficult (and potentially errorful) retrieval practice for robust learning and prolonged performance gains. We then review treatment research comparing errorless and errorful methods in amnesia and aphasia, where only the latter provides (difficult) retrieval practice opportunities. In each clinical domain we find the advantage of the errorless approach is limited and may be offset by the therapeutic potential of retrieval practice. Gaps in current knowledge are identified that preclude strong conclusions regarding a preference for errorless treatments over methods that prioritize difficult retrieval practice. We offer recommendations for future research aimed at a strong test of errorless learning treatments, which involves direct comparison with methods where retrieval practice effects are maximized for long-term gains. PMID:22247957

Machine learning bandgaps of double perovskites

PubMed Central

Pilania, G.; Mannodi-Kanakkithodi, A.; Uberuaga, B. P.; Ramprasad, R.; Gubernatis, J. E.; Lookman, T.

2016-01-01

The ability to make rapid and accurate predictions on bandgaps of double perovskites is of much practical interest for a range of applications. While quantum mechanical computations for high-fidelity bandgaps are enormously computation-time intensive and thus impractical in high throughput studies, informatics-based statistical learning approaches can be a promising alternative. Here we demonstrate a systematic feature-engineering approach and a robust learning framework for efficient and accurate predictions of electronic bandgaps of double perovskites. After evaluating a set of more than 1.2 million features, we identify lowest occupied Kohn-Sham levels and elemental electronegativities of the constituent atomic species as the most crucial and relevant predictors. The developed models are validated and tested using the best practices of data science and further analyzed to rationalize their prediction performance. PMID:26783247

Teaching, Learning and Assessing HRD: Findings from a BMAF/UFHRD Research Project

ERIC Educational Resources Information Center

Sambrook, Sally; Stewart, Jim

2010-01-01

Purpose: This paper seeks to analyse and explore the results of a research project, which aimed to identify recent and current research on TLA within HRD programmes. From that base the project also intended to identify areas for future research and a basis for establishing a Special Interest Group. Design/methodology/approach: A comprehensive…

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment

PubMed Central

Uddin, Raihan; Singh, Shiva M.

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in “learning and memory” related functions and pathways. Subsequent differential network analysis of this “learning and memory” module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they provide a new insight and generate new hypotheses into the molecular mechanisms responsible for age associated learning impairment, including spatial learning. PMID:29066959

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

PubMed

Uddin, Raihan; Singh, Shiva M

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they provide a new insight and generate new hypotheses into the molecular mechanisms responsible for age associated learning impairment, including spatial learning.

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

PubMed

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg .

VIOLENT FRAMES IN ACTION

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

Sanfilippo, Antonio P.; McGrath, Liam R.; Whitney, Paul D.

2011-11-17

We present a computational approach to radical rhetoric that leverages the co-expression of rhetoric and action features in discourse to identify violent intent. The approach combines text mining and machine learning techniques with insights from Frame Analysis and theories that explain the emergence of violence in terms of moral disengagement, the violation of sacred values and social isolation in order to build computational models that identify messages from terrorist sources and estimate their proximity to an attack. We discuss a specific application of this approach to a body of documents from and about radical and terrorist groups in the Middlemore » East and present the results achieved.« less

Oceanic eddy detection and lifetime forecast using machine learning methods

NASA Astrophysics Data System (ADS)

Ashkezari, Mohammad D.; Hill, Christopher N.; Follett, Christopher N.; Forget, Gaël.; Follows, Michael J.

2016-12-01

We report a novel altimetry-based machine learning approach for eddy identification and characterization. The machine learning models use daily maps of geostrophic velocity anomalies and are trained according to the phase angle between the zonal and meridional components at each grid point. The trained models are then used to identify the corresponding eddy phase patterns and to predict the lifetime of a detected eddy structure. The performance of the proposed method is examined at two dynamically different regions to demonstrate its robust behavior and region independency.

Matching student personality types and learning preferences to teaching methodologies.

PubMed

Jessee, Stephen A; O'Neill, Paula N; Dosch, Robert O

2006-06-01

The purpose of this study was to identify teaching styles that complement the learning preferences of undergraduate dental students while enhancing the quality of patient care. A formidable challenge to reform in dental education has been overcoming the resistance by faculty and administration to recommended changes. The organizational structure of dental institutions, with their independent departments, makes obtaining consensus on educational issues difficult. For beneficial change to occur, clear evidence of the benefits to all within the organization must be presented. The objectives of the study were to 1) identify the most common personality types among first- and second-year undergraduate dental students at the University of Texas Dental Branch at Houston using the Myers-Briggs Type Indicator (MBTI); 2) identify the learning preferences of these personality types; and 3) determine a more effective approach to teaching clinical dentistry based upon student personality types and learning preferences. Four common personality types were identified among respondents: ISTJ, ESFJ, ESTJ, and ISFJ, with a predisposition for Sensing (S) (desire for facts, use of senses) over Intuition (N) (look for possibilities, relationships) and Judging (J) (prefers decisiveness, closure) over Perceiving (P) (desire flexibility, spontaneity). The most common occurring personality type, ISTJ, represents an Introverted, Sensing, Thinking, Judging individual. Specific clinical curricular techniques that would appeal to these common personality types are identified, and an explanation of their benefit is provided. Results of this study demonstrate the importance of faculty understanding and acknowledging different student personality types and related learning preferences as a way to initiate improvement of undergraduate dental education, promote student motivation, and allow for an expression of learning style preference.

Machine Learning in Medicine

PubMed Central

Deo, Rahul C.

2015-01-01

Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games – tasks which would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in healthcare. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades – and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome. PMID:26572668

What Does Evidence-Based Instruction in Social and Emotional Learning Actually Look Like in Practice? A Brief on Findings from CASEL's Program Reviews

ERIC Educational Resources Information Center

Dusenbury, Linda; Calin, Sophia; Domitrovich, Celene; Weissberg, Roger P.

2015-01-01

In this brief we use the CASEL reviews of evidence-based programs to answer the question, "What do teachers and other adults actually need to do in the classroom and school to help students achieve the goals laid out in social and emotional learning (SEL) standards?" Specifically, we identify and describe four approaches that have been…

From Common Sense Concepts to Scientifically Conditioned Concepts of Chemical Bonding: An Historical and Textbook Approach Designed to Address Learning and Teaching Issues at the Secondary School Level

ERIC Educational Resources Information Center

Croft, Michael; de Berg, Kevin

2014-01-01

This paper selects six key alternative conceptions identified in the literature on student understandings of chemical bonding and illustrates how a historical analysis and a textbook analysis can inform these conceptions and lead to recommendations for improving the teaching and learning of chemical bonding at the secondary school level. The…

Pedagogical, Curricular and Didactic Elements Involved in the Creation of an E-Learning Environment: The Case of a Costa Rican University

ERIC Educational Resources Information Center

Baltodano, Manuel; Gomez-Zermeno, Marcela Georgina

2017-01-01

This article presents the results of a descriptive phenomenological study with mixed approach carried out to identify the pedagogical, curricular and didactic elements involved in the creation of an e-learning environment for the students of the course Directed Research I at the State Distance University in Costa Rica (UNED). As for the method, it…

The Need for Innovative Methods of Teaching and Learning Chemistry in Higher Education--Reflections from a Project of the European Chemistry Thematic Network

ERIC Educational Resources Information Center

Eilks, Ingo; Byers, Bill

2010-01-01

This paper summarizes the work and conclusions of a working group established by the European Chemistry Thematic Network (ECTN). The aim of the working group was to identify potential areas for innovative approaches to the teaching and learning of chemistry in Higher Education, and to survey good practice throughout the EU. The paper starts by…

Analysis of a Physics Teacher's Pedagogical "Micro-Actions" That Support 17-Year-Olds' Learning of Free Body Diagrams via a Modelling Approach

ERIC Educational Resources Information Center

Tay, Su Lynn; Yeo, Jennifer

2018-01-01

Great teaching is characterised by the specific actions a teacher takes in the classroom to bring about learning. In the context of model-based teaching (MBT), teachers' difficulty in working with students' models that are not scientifically consistent is troubling. To address this problem, the aim of this study is to identify the pedagogical…

K-Means Clustering to Study How Student Reasoning Lines Can Be Modified by a Learning Activity Based on Feynman's Unifying Approach

ERIC Educational Resources Information Center

Battaglia, Onofrio Rosario; Di Paola, Benedetto; Fazio, Claudio

2017-01-01

Research in Science Education has shown that often students need to learn how to identify differences and similarities between descriptive and explicative models. The development and use of explicative skills in the field of thermal science has always been a difficult objective to reach. A way to develop analogical reasoning is to use in Science…

An interview study of how clinical teachers develop skills to attend to different level learners.

PubMed

Chen, H Carrie; Fogh, Shannon; Kobashi, Brent; Teherani, Arianne; Ten Cate, Olle; O'Sullivan, Patricia

2016-06-01

One clinical teaching challenge is the engagement of learners at different levels. Faculty development offerings mostly address general strategies applicable to all learners. This study examined how clinical faculty members develop the skills to work with different level learners. We conducted semi-structured interviews with medical school faculty members identified as excellent clinical teachers teaching multiple levels of learners. They discussed how they developed their approach to teaching different level learners and how their teaching evolved over time. We performed thematic analysis of the interview transcripts using open and axial coding. We interviewed 19 faculty members and identified three themes related to development of teaching practices: teacher agency and work-based learning of teaching strategies, developmental trajectory of clinical teachers, and interplay between clinical confidence and teaching skills. Faculty members were proactive in using on-the-job experiences to develop their teaching practices. Their teaching practices followed a developmental trajectory towards learner centeredness, and this evolution was associated with the development of clinical skills and confidence. Learning skills to teach multi-level learners requires workplace learning. Faculty development should include workplace learning opportunities and use a developmental approach that accounts for the trajectory of teaching as well as clinical skills attainment.

Utilising database-driven interactive software to enhance independent home-study in a flipped classroom setting: going beyond visualising engineering concepts to ensuring formative assessment

NASA Astrophysics Data System (ADS)

Comerford, Liam; Mannis, Adam; DeAngelis, Marco; Kougioumtzoglou, Ioannis A.; Beer, Michael

2018-07-01

The concept of formative assessment is considered by many to play an important role in enhancing teaching in higher engineering education. In this paper, the concept of the flipped classroom as part of a blended learning curriculum is highlighted as an ideal medium through which formative assessment practices arise. Whilst the advantages of greater interaction between students and lecturers in classes are numerous, there are often clear disadvantages associated with the independent home-study component that complements timetabled sessions in a flipped classroom setting, specifically, the popular method of replacing traditional classroom teaching with video lectures. This leads to a clear lack of assurances that the cited benefits of a flipped classroom approach are echoed in the home-study arena. Over the past three years, the authors have sought to address identified deficiencies in this area of blended learning through the development of database-driven e-learning software with the capability of introducing formative assessment practices to independent home-study. This paper maps out aspects of two specific evolving practices at separate institutions, from which guiding principles of incorporating formative assessment aspects into e-learning software are identified and highlighted in the context of independent home-study as part of a flipped classroom approach.

Fear conditioning leads to alteration in specific genes expression in cortical and thalamic neurons that project to the lateral amygdala.

PubMed

Katz, Ira K; Lamprecht, Raphael

2015-02-01

RNA transcription is needed for memory formation. However, the ability to identify genes whose expression is altered by learning is greatly impaired because of methodological difficulties in profiling gene expression in specific neurons involved in memory formation. Here, we report a novel approach to monitor the expression of genes after learning in neurons in specific brain pathways needed for memory formation. In this study, we aimed to monitor gene expression after fear learning. We retrogradely labeled discrete thalamic neurons that project to the lateral amygdala (LA) of rats. The labeled neurons were dissected, using laser microdissection microscopy, after fear conditioning learning or unpaired training. The RNAs from the dissected neurons were subjected to microarray analysis. The levels of selected RNAs detected by the microarray analysis to be altered by fear conditioning were also assessed by nanostring analysis. We observed that the expression of genes involved in the regulation of translation, maturation and degradation of proteins was increased 6 h after fear conditioning compared to unpaired or naïve trained rats. These genes were not expressed 24 h after training or in cortical neurons that project to the LA. The expression of genes involved in transcription regulation and neuronal development was altered after fear conditioning learning in the cortical-LA pathway. The present study provides key information on the identity of genes expressed in discrete thalamic and cortical neurons that project to the LA after fear conditioning. Such an approach could also serve to identify gene products as targets for the development of a new generation of therapeutic agents that could be aimed to functionally identified brain circuits to treat memory-related disorders. © 2014 International Society for Neurochemistry.

State Identification for Planetary Rovers: Learning and Recognition

NASA Technical Reports Server (NTRS)

Aycard, Olivier; Washington, Richard

1999-01-01

A planetary rover must be able to identify states where it should stop or change its plan. With limited and infrequent communication from ground, the rover must recognize states accurately. However, the sensor data is inherently noisy, so identifying the temporal patterns of data that correspond to interesting or important states becomes a complex problem. In this paper, we present an approach to state identification using second-order Hidden Markov Models. Models are trained automatically on a set of labeled training data; the rover uses those models to identify its state from the observed data. The approach is demonstrated on data from a planetary rover platform.

Variables that impact the implementation of project-based learning in high school science

NASA Astrophysics Data System (ADS)

Cunningham, Kellie

Wagner and colleagues (2006) state the mediocrity of teaching and instructional leadership is the central problem that must be addressed if we are to improve student achievement. Educational reform efforts have been initiated to improve student performance and to hold teachers and school leaders accountable for student achievement (Wagner et al., 2006). Specifically, in the area of science, goals for improving student learning have led reformers to establish standards for what students should know and be able to do, as well as what instructional methods should be used. Key concepts and principles have been identified for student learning. Additionally, reformers recommend student-centered, inquiry-based practices that promote a deep understanding of how science is embedded in the everyday world. These new approaches to science education emphasize inquiry as an essential element for student learning (Schneider, Krajcik, Marx, & Soloway, 2002). Project-based learning (PBL) is an inquiry-based instructional approach that addresses these recommendations for science education reform. The objective of this research was to study the implementation of project-based learning (PBL) in an urban school undergoing reform efforts and identify the variables that positively or negatively impacted the PBL implementation process and its outcomes. This study responded to the need to change how science is taught by focusing on the implementation of project-based learning as an instructional approach to improve student achievement in science and identify the role of both school leaders and teachers in the creation of a school environment that supports project-based learning. A case study design using a mixed-method approach was used in this study. Data were collected through individual interviews with the school principal, science instructional coach, and PBL facilitator. A survey, classroom observations and interviews involving three high school science teachers teaching grades 9--12, were also used in the data collection process. The results of the study indicated that the use of PBL increased student engagement, ability to problem-solve, and to some extent academic performance. The results also revealed several factors that impacted the implementation of project-based learning: (a) Student attributes such as high student absenteeism, lack of motivation, and poor behavior prevented teachers from completing the PBL unit in a timely fashion. (b) Certain school and district policies and requirements were not conducive to PBL implementation. Policies and practices impacting instructional time and teaching supplies acquisition made it difficult for teachers to plan lessons and obtain necessary supplies. (c) Teachers did not receive PBL training in a timely fashion. Teachers received training approximately two months prior to implementation. (d) Teacher collaboration influenced PBL implementation as it enabled teachers to share and discuss ideas, resources, and lessons. Implications for practice include: (a) School and district leaders must create and follow policies and procedures that support conditions that support inquiry learning, (b) Teachers need resources to overcome the challenges associated with project-based learning, (c) Teachers must have the freedom to have a vision for the implementation of PBL that fits their particular classroom context, and (d) Steps should be taken to ensure students have the prior knowledge and skills to successfully engage in PBL.

An evaluation of the role of the clinical education facilitator.

PubMed

McCormack, Brendan; Slater, Paul

2006-02-01

The objective of the study was to identify whether clinical education facilitators made a difference to the learning experiences of nurses in a large teaching hospital. Strategies for enabling continuous professional development are well established in health care organizations as key components of approaches to lifelong learning. The benefits of continuous professional development include the maintenance of high standards of care, the improvement and development of services, ensuring the competency of all nursing staff and guaranteeing the accountability of nurses for their actions. The role of clinical education facilitator is relatively new and little evaluation of this role has been undertaken. This study highlights important issues to be considered in developing a 'learning culture' in a hospital organization, through the adoption of such roles as clinical education facilitators. Whilst the roles have had an important function in the active coordination of learning activities in the hospital, there is little evidence of the role directly impacting on the learning culture of clinical settings. Learning mechanisms have been identified. The results of this evaluation can be subjected to further testing through ongoing evaluation of the outcomes arising from the learning mechanisms in place. Given the emphasis on work-based learning and continuing professional development in health care, then this ongoing evaluation can yield important information about future directions for nurse education. The study highlights the importance of supported learning in the workplace. However, more importantly, it identifies the need for a culture of professional practice to be developed in order to sustain learning in practice. Classroom-based learning alone, cannot create a culture of development in nursing and there is thus a need for models of work-based learning to be integrated into practice environments.

Research on Pictures in Instructional Texts: The Need for a Broadened Perspective.

ERIC Educational Resources Information Center

Brody, Philip J.

1981-01-01

Reviews research examining the effects of pictorial illustrations on learning from textbooks; notes differences in purpose, approach, and methodology; identifies some shortcomings; and offers suggestions for future research. Forty references are listed. (FM)

The ongoing search for best practice in clinical teaching and learning: a model of nursing students' evolution to proficient novice registered nurses.

PubMed

Edgecombe, Kay; Bowden, Margaret

2009-03-01

This article describes the development of a model of nursing students as evolving registered nurses (RNs). It aims to generate critical debate about innovations in nursing teaching and learning. The model is the outcome of research conducted with undergraduate nursing students (n=111) from Flinders University, Adelaide, South Australia. It identifies the positive and negative intrinsic and extrinsic factors that impact on nursing students' clinical learning development and progression from students to proficient novice RNs. This model has implications for future curriculum development, staff development, placement approaches and research in relation to clinical teaching and learning.

Divide and Conquer-Based 1D CNN Human Activity Recognition Using Test Data Sharpening †

PubMed Central

Yoon, Sang Min

2018-01-01

Human Activity Recognition (HAR) aims to identify the actions performed by humans using signals collected from various sensors embedded in mobile devices. In recent years, deep learning techniques have further improved HAR performance on several benchmark datasets. In this paper, we propose one-dimensional Convolutional Neural Network (1D CNN) for HAR that employs a divide and conquer-based classifier learning coupled with test data sharpening. Our approach leverages a two-stage learning of multiple 1D CNN models; we first build a binary classifier for recognizing abstract activities, and then build two multi-class 1D CNN models for recognizing individual activities. We then introduce test data sharpening during prediction phase to further improve the activity recognition accuracy. While there have been numerous researches exploring the benefits of activity signal denoising for HAR, few researches have examined the effect of test data sharpening for HAR. We evaluate the effectiveness of our approach on two popular HAR benchmark datasets, and show that our approach outperforms both the two-stage 1D CNN-only method and other state of the art approaches. PMID:29614767

Divide and Conquer-Based 1D CNN Human Activity Recognition Using Test Data Sharpening.

PubMed

Cho, Heeryon; Yoon, Sang Min

2018-04-01

Human Activity Recognition (HAR) aims to identify the actions performed by humans using signals collected from various sensors embedded in mobile devices. In recent years, deep learning techniques have further improved HAR performance on several benchmark datasets. In this paper, we propose one-dimensional Convolutional Neural Network (1D CNN) for HAR that employs a divide and conquer-based classifier learning coupled with test data sharpening. Our approach leverages a two-stage learning of multiple 1D CNN models; we first build a binary classifier for recognizing abstract activities, and then build two multi-class 1D CNN models for recognizing individual activities. We then introduce test data sharpening during prediction phase to further improve the activity recognition accuracy. While there have been numerous researches exploring the benefits of activity signal denoising for HAR, few researches have examined the effect of test data sharpening for HAR. We evaluate the effectiveness of our approach on two popular HAR benchmark datasets, and show that our approach outperforms both the two-stage 1D CNN-only method and other state of the art approaches.

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.

Toward accelerating landslide mapping with interactive machine learning techniques

NASA Astrophysics Data System (ADS)

Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

2013-04-01

Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also included an experimental evaluation of the uncertainties of manual mappings from multiple experts and demonstrated strong relationships between the uncertainty of the experts and the machine learning model.

Learning Evaluation: blending quality improvement and implementation research methods to study healthcare innovations.

PubMed

Balasubramanian, Bijal A; Cohen, Deborah J; Davis, Melinda M; Gunn, Rose; Dickinson, L Miriam; Miller, William L; Crabtree, Benjamin F; Stange, Kurt C

2015-03-10

In healthcare change interventions, on-the-ground learning about the implementation process is often lost because of a primary focus on outcome improvements. This paper describes the Learning Evaluation, a methodological approach that blends quality improvement and implementation research methods to study healthcare innovations. Learning Evaluation is an approach to multi-organization assessment. Qualitative and quantitative data are collected to conduct real-time assessment of implementation processes while also assessing changes in context, facilitating quality improvement using run charts and audit and feedback, and generating transportable lessons. Five principles are the foundation of this approach: (1) gather data to describe changes made by healthcare organizations and how changes are implemented; (2) collect process and outcome data relevant to healthcare organizations and to the research team; (3) assess multi-level contextual factors that affect implementation, process, outcome, and transportability; (4) assist healthcare organizations in using data for continuous quality improvement; and (5) operationalize common measurement strategies to generate transportable results. Learning Evaluation principles are applied across organizations by the following: (1) establishing a detailed understanding of the baseline implementation plan; (2) identifying target populations and tracking relevant process measures; (3) collecting and analyzing real-time quantitative and qualitative data on important contextual factors; (4) synthesizing data and emerging findings and sharing with stakeholders on an ongoing basis; and (5) harmonizing and fostering learning from process and outcome data. Application to a multi-site program focused on primary care and behavioral health integration shows the feasibility and utility of Learning Evaluation for generating real-time insights into evolving implementation processes. Learning Evaluation generates systematic and rigorous cross-organizational findings about implementing healthcare innovations while also enhancing organizational capacity and accelerating translation of findings by facilitating continuous learning within individual sites. Researchers evaluating change initiatives and healthcare organizations implementing improvement initiatives may benefit from a Learning Evaluation approach.

Medical students' opportunities to participate and learn from activities at an internal medicine ward: an ethnographic study.

PubMed

Hägg-Martinell, A; Hult, H; Henriksson, P; Kiessling, A

2017-02-14

To optimise medical students' early clerkship is a complex task since it is conducted in a context primarily organised to take care of patients. Previous studies have explored medical students' perceptions of facilitation and hindrance of learning. However, the opportunities for medical student to learn within the culture of acute medicine care have not been fully investigated. This study aimed to explore how medical students approach, interact and socialise in an acute internal medicine ward context, and how spaces for learning are created and used in such a culture. Ethnographic observations were performed of medical students' interactions and learning during early clerkship at an acute internal medicine care ward. Field notes were taken, transcribed and analysed qualitatively. Data analysis was guided by Wenger's theory of communities of practice. 21 medical students and 30 supervisors participated. Two themes were identified: Nervousness and curiosity- students acted nervously and stressed, especially when they could not answer questions. Over time curiosity could evolve. Unexplored opportunities to support students in developing competence to judge and approach more complex patient-related problems were identified. Invited and involved -students were exposed to a huge variation of opportunities to learn, and to interact and to be involved. Short placements seemed to disrupt the learning process. If and how students became involved also depended on supervisors' activities and students' initiatives. This study shed light on how an acute internal medicine ward culture can facilitate medical students' possibilities to participate and learn. Medical students' learning situations were characterised by questions and answers rather than challenging dialogues related to the complexity of presented patient cases. Further, students experienced continuous transfers between learning situations where the potential to be involved differed in a wide variety of ways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Predictive validity of curriculum-based measurement and teacher ratings of academic achievement.

PubMed

Kettler, Ryan J; Albers, Craig A

2013-08-01

Two alternative universal screening approaches to identify students with early learning difficulties were examined, along with a combination of these approaches. These approaches, consisting of (a) curriculum-based measurement (CBM) and (b) teacher ratings using Performance Screening Guides (PSGs), served as predictors of achievement tests in reading and mathematics. Participants included 413 students in grades 1, 2, and 3 in Tennessee (n=118) and Wisconsin (n=295) who were divided into six subsamples defined by grade and state. Reading and mathematics achievement tests with established psychometric properties were used as criteria within a concurrent and predictive validity framework. Across both achievement areas, CBM probes shared more variance with criterion measures than did teacher ratings, although teacher ratings added incremental validity among most subsamples. PSGs tended to be more accurate for identifying students in need of assistance at a 1-month interval, whereas CBM probes were more accurate at a 6-month interval. Teachers indicated that (a) false negatives are more problematic than are false positives, (b) both screening methods are useful for identifying early learning difficulties, and (c) both screening methods are useful for identifying students in need of interventions. Collectively, these findings suggest that the two types of measures, when used together, yield valuable information about students who need assistance in reading and mathematics. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Factors affecting learning and teaching for medicines supply management training in Pacific Island Countries--a realist review.

PubMed

Brown, Andrew N; Ward-Panckhurst, Liane; Cooper, Gabrielle

2013-01-01

Limited human resources are a major impediment to achieving the UN health-related Millennium Development Goals in a number of Pacific Island Countries (PICs). Lack of education capacity to support competency development in medicine supply management is one of the main issues affecting workforce development in this region, which is characterised by disparate service delivery due to the range of environments in which supply occurs (ie urban, rural and remote), geographical challenges and cultural practices associated with teaching and learning. The supply of medicines, and an adequate pharmacy workforce with appropriate competencies is crucial to ensuring a well-functioning pharmaceutical system. In this region approximately 80% of patients access healthcare in rural areas without a pharmacist, thus local health personnel must be competent in pharmaceutical management relevant to the local context and culture. A new approach involves a partnership between the UN Population Fund Suva Sub-Regional Office, University of Canberra, Ministry of Health officials and the heath personnel within identified PICs, starting with the need to understand local culture and its impact on learning and teaching, and the mapping of competency requirements and an understanding of currently available information and materials. This information will be used to develop and trial new pedagogical approaches to training health personnel involved in essential medicines supply management, to improve medicines availability for patients in their own environment. The focus of this review was to determine what cultural and learning factors need to be considered when developing a curriculum for South Pacific pharmaceutical health personnel who work across a range of practice environments. A 'realist methodology' consisting of a systematic investigation of the published literature and a targeted review of the 'grey' literature was used. All relevant literature was retrieved and coded manually using broad thematic analysis. The combined bibliographic and 'grey' literature search strategy resulted in the inclusion of 17 full text articles, 44 documents and 10 books. The five themes identified as key to optimising the cultural and learning approaches for the study population included recognition of: (1) past regional experiences of health related training; (2) the impact of South Pacific culture on learning styles; (3) the impact of external influences on curriculum; (4) the challenges of open and distance education in the Pacific; and (5) a distinct South Pacific student learning approach. The results of this 'realist methodology' review provide insights into learning approaches and cultural influences on student learning within PICs. The themes generated will be used to develop a set of principles to inform educators and health personnel involved in pharmaceutical training within PICs.

Transforming Teacher-Family Relationships: Shifting Roles and Perceptions of Home Visits through the Funds of Knowledge Approach

ERIC Educational Resources Information Center

Whyte, Kristin Lyn; Karabon, Anne

2016-01-01

Education has embraced the idea of an "asset approach" to working with families and children, creating a focus on developing collaborative relationships with families by building on what they bring to the table. In this paper we explore what happened when early childhood teachers entered homes to learn from families and identify their…

"Which Pathway Am I?" Using a Game Approach to Teach Students about Biochemical Pathways

ERIC Educational Resources Information Center

Ooi, Beng Guat; Sanger, Michael J.

2009-01-01

This game was designed to provide students with an alternative way to learn biochemical pathways through an interactive approach. In this game, students worked in pairs to help each other identify pathways taped to each other's backs by asking simple "yes or no" questions related to these pathways. This exercise was conducted after the traditional…

The Assessment of Math Learning Difficulties in a Primary Grade-4 Child with High Support Needs: Mixed Methods Approach

ERIC Educational Resources Information Center

Mundia, Lawrence

2012-01-01

This mixed-methods study incorporated elements of survey, case study and action research approaches in investigating an at-risk child. Using an in-take interview, a diagnostic test, an error analysis, and a think-aloud clinical interview, the study identified the child's major presenting difficulties. These included: inability to use the four…

Addressing vaccine hesitancy: The potential value of commercial and social marketing principles and practices.

PubMed

Nowak, Glen J; Gellin, Bruce G; MacDonald, Noni E; Butler, Robb

2015-08-14

Many countries and communities are dealing with groups and growing numbers of individuals who are delaying or refusing recommended vaccinations for themselves or their children. This has created a need for immunization programs to find approaches and strategies to address vaccine hesitancy. An important source of useful approaches and strategies is found in the frameworks, practices, and principles used by commercial and social marketers, many of which have been used by immunization programs. This review examines how social and commercial marketing principles and practices can be used to help address vaccine hesitancy. It provides an introduction to key marketing and social marketing concepts, identifies some of the major challenges to applying commercial and social marketing approaches to immunization programs, illustrates how immunization advocates and programs can use marketing and social marketing approaches to address vaccine hesitancy, and identifies some of the lessons that commercial and non-immunization sectors have learned that may have relevance for immunization. While the use of commercial and social marketing practices and principles does not guarantee success, the evidence, lessons learned, and applications to date indicate that they have considerable value in fostering vaccine acceptance. Copyright © 2015. Published by Elsevier Ltd.

Beyond Cumulative Risk: A Dimensional Approach to Childhood Adversity.

PubMed

McLaughlin, Katie A; Sheridan, Margaret A

2016-08-01

Children who have experienced environmental adversity-such as abuse, neglect, or poverty-are more likely to develop physical and mental health problems, perform poorly at school, and have difficulties in social relationships than children who have not encountered adversity. What is less clear is how and why adverse early experiences exert such a profound influence on children's development. Identifying developmental processes that are disrupted by adverse early environments is the key to developing better intervention strategies for children who have experienced adversity. Yet, much existing research relies on a cumulative risk approach that is unlikely to reveal these mechanisms. This approach tallies the number of distinct adversities experienced to create a risk score. This risk score fails to distinguish between distinct types of environmental experience, implicitly assuming that very different experiences influence development through the same underlying mechanisms. We advance an alternative model. This novel approach conceptualizes adversity along distinct dimensions, emphasizes the central role of learning mechanisms, and distinguishes between different forms of adversity that might influence learning in distinct ways. A key advantage of this approach is that learning mechanisms provide clear targets for interventions aimed at preventing negative developmental outcomes in children who have experienced adversity.

Experiencing teaching and learning quantitative reasoning in a project-based context

NASA Astrophysics Data System (ADS)

Muir, Tracey; Beswick, Kim; Callingham, Rosemary; Jade, Katara

2016-12-01

This paper presents the findings of a small-scale study that investigated the issues and challenges of teaching and learning about quantitative reasoning (QR) within a project-based learning (PjBL) context. Students and teachers were surveyed and interviewed about their experiences of learning and teaching QR in that context in contrast to teaching and learning mathematics in more traditional settings. The grade 9-12 student participants were characterised by a history of disengagement with mathematics and school in general, and the teacher participants were non-mathematics specialist teachers. Both students and teachers were new to the PjBL situation, which resulted in the teaching/learning relationship being a reciprocal one. The findings indicated that students and teachers viewed QR positively, particularly when compared with traditional mathematics teaching, yet tensions were identified for aspects such as implementation of curriculum and integration of relevant mathematics into projects. Both sets of participants identified situations where learning QR was particularly successful, along with concerns or difficulties about integrating QR into project work. The findings have implications for educators, who may need to examine their own approaches to mathematics teaching, particularly in terms of facilitating student engagement with the subject.

Learning difficulties of senior high school students based on probability understanding levels

NASA Astrophysics Data System (ADS)

Anggara, B.; Priatna, N.; Juandi, D.

2018-05-01

Identifying students' difficulties in learning concept of probability is important for teachers to prepare the appropriate learning processes and can overcome obstacles that may arise in the next learning processes. This study revealed the level of students' understanding of the concept of probability and identified their difficulties as a part of the epistemological obstacles identification of the concept of probability. This study employed a qualitative approach that tends to be the character of descriptive research involving 55 students of class XII. In this case, the writer used the diagnostic test of probability concept learning difficulty, observation, and interview as the techniques to collect the data needed. The data was used to determine levels of understanding and the learning difficulties experienced by the students. From the result of students' test result and learning observation, it was found that the mean cognitive level was at level 2. The findings indicated that students had appropriate quantitative information of probability concept but it might be incomplete or incorrectly used. The difficulties found are the ones in arranging sample space, events, and mathematical models related to probability problems. Besides, students had difficulties in understanding the principles of events and prerequisite concept.

Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

PubMed

Kagawa, Rina; Kawazoe, Yoshimasa; Ida, Yusuke; Shinohara, Emiko; Tanaka, Katsuya; Imai, Takeshi; Ohe, Kazuhiko

2017-07-01

Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects. We employ expert knowledge as rules to exclude obvious control patients and machine learning to increase accuracy for complicated patients. We developed phenotyping algorithms on the basis of our framework and performed binary classification to determine whether a patient has T2DM. To facilitate development of practical phenotyping algorithms, this study introduces new evaluation metrics: area under the precision-sensitivity curve (AUPS) with a high sensitivity and AUPS with a high positive predictive value. The proposed phenotyping algorithms based on our framework show higher performance than baseline algorithms. Our proposed framework can be used to develop 2 types of phenotyping algorithms depending on the tuning approach: one for screening, the other for identifying research subjects. We develop a novel phenotyping framework that can be easily implemented on the basis of proper evaluation metrics, which are in accordance with users' objectives. The phenotyping algorithms based on our framework are useful for extraction of T2DM patients in retrospective studies.

Applying Advanced Analytical Approaches to Characterize the Impact of Specific Clinical Gaps and Profiles on the Management of Rheumatoid Arthritis.

PubMed

Ruiz-Cordell, Karyn D; Joubin, Kathy; Haimowitz, Steven

2016-01-01

The goal of this study was to add a predictive modeling approach to the meta-analysis of continuing medical education curricula to determine whether this technique can be used to better understand clinical decision making. Using the education of rheumatologists on rheumatoid arthritis management as a model, this study demonstrates how the combined methodology has the ability to not only characterize learning gaps but also identify those proficiency areas that have the greatest impact on clinical behavior. The meta-analysis included seven curricula with 25 activities. Learners who identified as rheumatologists were evaluated across multiple learning domains, using a uniform methodology to characterize learning gains and gaps. A performance composite variable (called the treatment individualization and optimization score) was then established as a target upon which predictive analytics were conducted. Significant predictors of the target included items related to the knowledge of rheumatologists and confidence concerning 1) treatment guidelines and 2) tests that measure disease activity. In addition, a striking demographic predictor related to geographic practice setting was also identified. The results demonstrate the power of advanced analytics to identify key predictors that influence clinical behaviors. Furthermore, the ability to provide an expected magnitude of change if these predictors are addressed has the potential to substantially refine educational priorities to those drivers that, if targeted, will most effectively overcome clinical barriers and lead to the greatest success in achieving treatment goals.

The Value of Identifying and Recovering Lost GN&C Lessons Learned: Aeronautical, Spacecraft, and Launch Vehicle Examples

NASA Technical Reports Server (NTRS)

Dennehy, Cornelius J.; Labbe, Steve; Lebsock, Kenneth L.

2010-01-01

Within the broad aerospace community the importance of identifying, documenting and widely sharing lessons learned during system development, flight test, operational or research programs/projects is broadly acknowledged. Documenting and sharing lessons learned helps managers and engineers to minimize project risk and improve performance of their systems. Often significant lessons learned on a project fail to get captured even though they are well known 'tribal knowledge' amongst the project team members. The physical act of actually writing down and documenting these lessons learned for the next generation of NASA GN&C engineers fails to happen on some projects for various reasons. In this paper we will first review the importance of capturing lessons learned and then will discuss reasons why some lessons are not documented. A simple proven approach called 'Pause and Learn' will be highlighted as a proven low-impact method of organizational learning that could foster the timely capture of critical lessons learned. Lastly some examples of 'lost' GN&C lessons learned from the aeronautics, spacecraft and launch vehicle domains are briefly highlighted. In the context of this paper 'lost' refers to lessons that have not achieved broad visibility within the NASA-wide GN&C CoP because they are either undocumented, masked or poorly documented in the NASA Lessons Learned Information System (LLIS).

Fault detection and diagnosis using neural network approaches

NASA Technical Reports Server (NTRS)

Kramer, Mark A.

1992-01-01

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

Pedagogical principles underpinning undergraduate Nurse Education in the UK: A review.

PubMed

Mackintosh-Franklin, Carolyn

2016-05-01

This review provides a contextual report of the current use of pedagogy in undergraduate nursing programmes run by Higher Education Institutes (HEIs) in the United Kingdom (UK). Pedagogy provides the framework for educators to add shape and structure to the educational process, and to support student learning and programme development. Traditionally nurse education has used a behaviourist approach focusing on learning outcomes and competency based education, although there is also increasing support for the cognitive/student learning focused pedagogic approach. The keywords andragogy, pedagogy and student centred learning were used in a systematic stepwise descriptive content analysis of the programme specifications and programme handbooks of 40 current undergraduate programme documents, leading to an undergraduate award and professional registration as a nurse. 42% (17) of documents contained reference to the words, pedagogy and student centred learning, whilst no documents used the word andragogy. Where identified, pedagogy was used in a superficial manner, with only three documents identifying a specific pedagogical philosophy: one HEI citing a value based curriculum and two HEIs referencing social constructionism. Nine HEIs made reference to student centred learning but with no additional pedagogic information. A review of teaching, learning and assessment strategies indicated no difference between the documented strategies used by HEIs when comparing those with an espoused pedagogy and those without. Although educational literature supports the use of pedagogic principles in curriculum design, this is not explicit in undergraduate nursing programme documentation, and suggests that nurse educators do not view pedagogy as important to their programmes. Instead programmes appear to be developed based on operational and functional requirements with a focus on acquisition of knowledge and skills, and the fitness to practice of graduates entering the nursing workforce. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structure-activity models of oral clearance, cytotoxicity, and LD50: a screen for promising anticancer compounds

PubMed Central

Boik, John C; Newman, Robert A

2008-01-01

Background Quantitative structure-activity relationship (QSAR) models have become popular tools to help identify promising lead compounds in anticancer drug development. Few QSAR studies have investigated multitask learning, however. Multitask learning is an approach that allows distinct but related data sets to be used in training. In this paper, a suite of three QSAR models is developed to identify compounds that are likely to (a) exhibit cytotoxic behavior against cancer cells, (b) exhibit high rat LD50 values (low systemic toxicity), and (c) exhibit low to modest human oral clearance (favorable pharmacokinetic characteristics). Models were constructed using Kernel Multitask Latent Analysis (KMLA), an approach that can effectively handle a large number of correlated data features, nonlinear relationships between features and responses, and multitask learning. Multitask learning is particularly useful when the number of available training records is small relative to the number of features, as was the case with the oral clearance data. Results Multitask learning modestly but significantly improved the classification precision for the oral clearance model. For the cytotoxicity model, which was constructed using a large number of records, multitask learning did not affect precision but did reduce computation time. The models developed here were used to predict activities for 115,000 natural compounds. Hundreds of natural compounds, particularly in the anthraquinone and flavonoids groups, were predicted to be cytotoxic, have high LD50 values, and have low to moderate oral clearance. Conclusion Multitask learning can be useful in some QSAR models. A suite of QSAR models was constructed and used to screen a large drug library for compounds likely to be cytotoxic to multiple cancer cell lines in vitro, have low systemic toxicity in rats, and have favorable pharmacokinetic properties in humans. PMID:18554402

Structure-activity models of oral clearance, cytotoxicity, and LD50: a screen for promising anticancer compounds.

PubMed

Boik, John C; Newman, Robert A

2008-06-13

Quantitative structure-activity relationship (QSAR) models have become popular tools to help identify promising lead compounds in anticancer drug development. Few QSAR studies have investigated multitask learning, however. Multitask learning is an approach that allows distinct but related data sets to be used in training. In this paper, a suite of three QSAR models is developed to identify compounds that are likely to (a) exhibit cytotoxic behavior against cancer cells, (b) exhibit high rat LD50 values (low systemic toxicity), and (c) exhibit low to modest human oral clearance (favorable pharmacokinetic characteristics). Models were constructed using Kernel Multitask Latent Analysis (KMLA), an approach that can effectively handle a large number of correlated data features, nonlinear relationships between features and responses, and multitask learning. Multitask learning is particularly useful when the number of available training records is small relative to the number of features, as was the case with the oral clearance data. Multitask learning modestly but significantly improved the classification precision for the oral clearance model. For the cytotoxicity model, which was constructed using a large number of records, multitask learning did not affect precision but did reduce computation time. The models developed here were used to predict activities for 115,000 natural compounds. Hundreds of natural compounds, particularly in the anthraquinone and flavonoids groups, were predicted to be cytotoxic, have high LD50 values, and have low to moderate oral clearance. Multitask learning can be useful in some QSAR models. A suite of QSAR models was constructed and used to screen a large drug library for compounds likely to be cytotoxic to multiple cancer cell lines in vitro, have low systemic toxicity in rats, and have favorable pharmacokinetic properties in humans.

Quantitative Predictive Models for Systemic Toxicity (SOT)

EPA Science Inventory

Models to identify systemic and specific target organ toxicity were developed to help transition the field of toxicology towards computational models. By leveraging multiple data sources to incorporate read-across and machine learning approaches, a quantitative model of systemic ...

Strategies for de-identification and anonymization of electronic health record data for use in multicenter research studies.

PubMed

Kushida, Clete A; Nichols, Deborah A; Jadrnicek, Rik; Miller, Ric; Walsh, James K; Griffin, Kara

2012-07-01

De-identification and anonymization are strategies that are used to remove patient identifiers in electronic health record data. The use of these strategies in multicenter research studies is paramount in importance, given the need to share electronic health record data across multiple environments and institutions while safeguarding patient privacy. Systematic literature search using keywords of de-identify, deidentify, de-identification, deidentification, anonymize, anonymization, data scrubbing, and text scrubbing. Search was conducted up to June 30, 2011 and involved 6 different common literature databases. A total of 1798 prospective citations were identified, and 94 full-text articles met the criteria for review and the corresponding articles were obtained. Search results were supplemented by review of 26 additional full-text articles; a total of 120 full-text articles were reviewed. A final sample of 45 articles met inclusion criteria for review and discussion. Articles were grouped into text, images, and biological sample categories. For text-based strategies, the approaches were segregated into heuristic, lexical, and pattern-based systems versus statistical learning-based systems. For images, approaches that de-identified photographic facial images and magnetic resonance image data were described. For biological samples, approaches that managed the identifiers linked with these samples were discussed, particularly with respect to meeting the anonymization requirements needed for Institutional Review Board exemption under the Common Rule. Current de-identification strategies have their limitations, and statistical learning-based systems have distinct advantages over other approaches for the de-identification of free text. True anonymization is challenging, and further work is needed in the areas of de-identification of datasets and protection of genetic information.

Transductive multi-view zero-shot learning.

PubMed

Fu, Yanwei; Hospedales, Timothy M; Xiang, Tao; Gong, Shaogang

2015-11-01

Most existing zero-shot learning approaches exploit transfer learning via an intermediate semantic representation shared between an annotated auxiliary dataset and a target dataset with different classes and no annotation. A projection from a low-level feature space to the semantic representation space is learned from the auxiliary dataset and applied without adaptation to the target dataset. In this paper we identify two inherent limitations with these approaches. First, due to having disjoint and potentially unrelated classes, the projection functions learned from the auxiliary dataset/domain are biased when applied directly to the target dataset/domain. We call this problem the projection domain shift problem and propose a novel framework, transductive multi-view embedding, to solve it. The second limitation is the prototype sparsity problem which refers to the fact that for each target class, only a single prototype is available for zero-shot learning given a semantic representation. To overcome this problem, a novel heterogeneous multi-view hypergraph label propagation method is formulated for zero-shot learning in the transductive embedding space. It effectively exploits the complementary information offered by different semantic representations and takes advantage of the manifold structures of multiple representation spaces in a coherent manner. We demonstrate through extensive experiments that the proposed approach (1) rectifies the projection shift between the auxiliary and target domains, (2) exploits the complementarity of multiple semantic representations, (3) significantly outperforms existing methods for both zero-shot and N-shot recognition on three image and video benchmark datasets, and (4) enables novel cross-view annotation tasks.

A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems.

PubMed

Yin, Weiwei; Garimalla, Swetha; Moreno, Alberto; Galinski, Mary R; Styczynski, Mark P

2015-08-28

There are increasing efforts to bring high-throughput systems biology techniques to bear on complex animal model systems, often with a goal of learning about underlying regulatory network structures (e.g., gene regulatory networks). However, complex animal model systems typically have significant limitations on cohort sizes, number of samples, and the ability to perform follow-up and validation experiments. These constraints are particularly problematic for many current network learning approaches, which require large numbers of samples and may predict many more regulatory relationships than actually exist. Here, we test the idea that by leveraging the accuracy and efficiency of classifiers, we can construct high-quality networks that capture important interactions between variables in datasets with few samples. We start from a previously-developed tree-like Bayesian classifier and generalize its network learning approach to allow for arbitrary depth and complexity of tree-like networks. Using four diverse sample networks, we demonstrate that this approach performs consistently better at low sample sizes than the Sparse Candidate Algorithm, a representative approach for comparison because it is known to generate Bayesian networks with high positive predictive value. We develop and demonstrate a resampling-based approach to enable the identification of a viable root for the learned tree-like network, important for cases where the root of a network is not known a priori. We also develop and demonstrate an integrated resampling-based approach to the reduction of variable space for the learning of the network. Finally, we demonstrate the utility of this approach via the analysis of a transcriptional dataset of a malaria challenge in a non-human primate model system, Macaca mulatta, suggesting the potential to capture indicators of the earliest stages of cellular differentiation during leukopoiesis. We demonstrate that by starting from effective and efficient approaches for creating classifiers, we can identify interesting tree-like network structures with significant ability to capture the relationships in the training data. This approach represents a promising strategy for inferring networks with high positive predictive value under the constraint of small numbers of samples, meeting a need that will only continue to grow as more high-throughput studies are applied to complex model systems.

Informal learning in postgraduate medical education: from cognitivism to 'culturism'.

PubMed

Swanwick, Tim

2005-08-01

Work-based learning occupies a central role in the training and ongoing development of the medical workforce. With this arises the need to understand the processes involved, particularly those relating to informal learning. Approaches to informal learning in postgraduate medical education have tended to consider the mind as an independent processor of information. In this paper, such cognitive approaches are critiqued and an alternative socio-cultural view on informal learning described. Recent and imminent changes in postgraduate medical education are identified, namely the reduction in patient experience, the fragmentation of teaching, and the development of competency frameworks and structured curricula. It is argued that although the latter may be useful in the construction of formal learning programmes, they will do little to enhance the progression of the individual from newcomer to old-timer or the cultural assimilation of the learner into a profession. Strategies for enhancing informal learning in the workplace are recommended in which increased attention is paid to the development of the medical apprentice within a community of social practice. These include the establishment of strong goals, the use of improvised learning practices, attention to levels of individual engagement and workplace affordances, immersion in professional discourse and behaviours, support in relation to the development of a professional identity and the provision of opportunities to transform social practice.

Jet-images — deep learning edition

DOE PAGES

de Oliveira, Luke; Kagan, Michael; Mackey, Lester; ...

2016-07-13

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Jet-images — deep learning edition

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

de Oliveira, Luke; Kagan, Michael; Mackey, Lester

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Classifying smoking urges via machine learning

PubMed Central

Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin

2016-01-01

Background and objective Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. Methods To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. Results The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. Conclusions In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms’ performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions. PMID:28110725

Classifying smoking urges via machine learning.

PubMed

Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin

2016-12-01

Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms' performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Building Common Ground for Environmental Flows using Traditional Techniques and Novel Engagement Approaches.

PubMed

Mott Lacroix, Kelly E; Xiu, Brittany C; Megdal, Sharon B

2016-04-01

Despite increased understanding of the science of environmental flows, identification and implementation of effective environmental flow policies remains elusive. Perhaps the greatest barrier to implementing flow policies is the framework for water management. An alternative management approach is needed when legal rights for environmental flows do not exist, or are ineffective at protecting ecosystems. The research presented here, conducted in the U.S. state of Arizona, provides an empirical example of engagement to promote social learning as an approach to finding ways to provide water for the environment where legal rights for environmental flows are inadequate. Based on our engagement process we propose that identifying and then building common ground require attention to the process of analyzing qualitative data and the methods for displaying complex information, two aspects not frequently discussed in the social learning or stakeholder engagement literature. The results and methods from this study can help communities develop an engagement process that will find and build common ground, increase stakeholder involvement, and identify innovative solutions to provide water for the environment that reflect the concerns of current water users.

Precepting 101: Teaching Strategies and Tips for Success for Preceptors.

PubMed

Lazarus, Judy

2016-11-01

The current shortage of certified nurse-midwives and certified midwives willing to serve as preceptors for midwifery education programs limits the number of students accepted into education programs. Preceptors are an essential link between academic programs and clinical practice and are indispensable to the growth of the midwifery profession. Preceptors create a safe environment for learning and teach adult learners through a variety of clinical teaching strategies. Novice preceptors need training and support to learn a new role, and experienced preceptors desire continued support and training. Before starting, preceptors need to identify sources of support and mentoring as well as understand the academic program's expectations for the student. This article draws on the clinical education literature to describe approaches to teaching all types of students. Practical strategies for integrating all levels of students into busy clinical settings are identified. Two approaches for clinical teaching, the Five Minute Preceptor and SNAPPS, are discussed in detail. Strategies for providing effective feedback and approaches to student evaluation are provided. © 2016 by the American College of Nurse-Midwives.

Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach.

PubMed

Sartori, Juliana M; Reckziegel, Ramiro; Passos, Ives Cavalcante; Czepielewski, Leticia S; Fijtman, Adam; Sodré, Leonardo A; Massuda, Raffael; Goi, Pedro D; Vianna-Sulzbach, Miréia; Cardoso, Taiane de Azevedo; Kapczinski, Flávio; Mwangi, Benson; Gama, Clarissa S

2018-08-01

Neuroimaging studies have been steadily explored in Bipolar Disorder (BD) in the last decades. Neuroanatomical changes tend to be more pronounced in patients with repeated episodes. Although the role of such changes in cognition and memory is well established, daily-life functioning impairments bulge among the consequences of the proposed progression. The objective of this study was to analyze MRI volumetric modifications in BD and healthy controls (HC) as possible predictors of daily-life functioning through a machine learning approach. Ninety-four participants (35 DSM-IV BD type I and 59 HC) underwent clinical and functioning assessments, and structural MRI. Functioning was assessed using the Functioning Assessment Short Test (FAST). The machine learning analysis was used to identify possible candidates of regional brain volumes that could predict functioning status, through a support vector regression algorithm. Patients with BD and HC did not differ in age, education and marital status. There were significant differences between groups in gender, BMI, FAST score, and employment status. There was significant correlation between observed and predicted FAST score for patients with BD, but not for controls. According to the model, the brain structures volumes that could predict FAST scores were: left superior frontal cortex, left rostral medial frontal cortex, right white matter total volume and right lateral ventricle volume. The machine learning approach demonstrated that brain volume changes in MRI were predictors of FAST score in patients with BD and could identify specific brain areas related to functioning impairment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Digital learning objects in nursing consultation: technology assessment by undergraduate students.

PubMed

Silveira, DeniseTolfo; Catalan, Vanessa Menezes; Neutzling, Agnes Ludwig; Martinato, Luísa Helena Machado

2010-01-01

This study followed the teaching-learning process about the nursing consultation, based on digital learning objects developed through the active Problem Based Learning method. The goals were to evaluate the digital learning objects about nursing consultation, develop cognitive skills on the subject using problem based learning and identify the students' opinions on the use of technology. This is an exploratory and descriptive study with a quantitative approach. The sample consisted of 71 students in the sixth period of the nursing program at the Federal University of Rio Grande do Sul. The data was collected through a questionnaire to evaluate the learning objects. The results showed positive agreement (58%) on the content, usability and didactics of the proposed computer-mediated activity regarding the nursing consultation. The application of materials to the students is considered positive.

Accelerated nursing students and theater students: creating a safe environment by acting the part.

PubMed

Cangelosi, Pamela R

2008-01-01

Traditional approaches to teaching basic nursing skills are being questioned for accelerated, or second-degree, nursing students. Since accelerated nursing students have demonstrated the ability to quickly assimilate new information and to transfer skills from a previous career into a new field, it is thought that they may benefit from teaching strategies that promote experiential learning. Through a hermeneutic phenomenological approach, this study inquired into the experiences of 22 accelerated baccalaureate nursing students to determine if narrative learning in a campus laboratory setting helped them integrate content from classroom and clinical practica and move quickly along the pathway to the competencies that are needed for safe nursing practice. Data analysis revealed the teaching/learning significance of narratives for these students and is identified in the theme, "Creating a Safe Environment".

Machine learning bandgaps of double perovskites

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Pilania, G.; Mannodi-Kanakkithodi, A.; Uberuaga, B. P.; ...

2016-01-19

The ability to make rapid and accurate predictions on bandgaps of double perovskites is of much practical interest for a range of applications. While quantum mechanical computations for high-fidelity bandgaps are enormously computation-time intensive and thus impractical in high throughput studies, informatics-based statistical learning approaches can be a promising alternative. Here we demonstrate a systematic feature-engineering approach and a robust learning framework for efficient and accurate predictions of electronic bandgaps of double perovskites. After evaluating a set of more than 1.2 million features, we identify lowest occupied Kohn-Sham levels and elemental electronegativities of the constituent atomic species as the mostmore » crucial and relevant predictors. As a result, the developed models are validated and tested using the best practices of data science and further analyzed to rationalize their prediction performance.« less

Outcomes of a clinical partnership model for undergraduate nursing students.

PubMed

Newton, Jennifer M; Cross, Wendy M; White, Karin; Ockerby, Cherene; Billett, Stephen

2011-08-01

Over the last decade several innovative approaches to enhance students' transition to graduate nurse year have been implemented or piloted. This paper describes a study that investigated how the social practices of clinical partnership placement model underpin workplace learning for undergraduate students as they transitioned to graduate. A mixed method approach was utilized comprising individual interviews with students, observation of clinical workplaces across six different areas of nursing practice, student surveys of the clinical learning environment and participant workshops. Three themes were identified that influenced participants' preparedness for work and enhanced the transition into the workplace: 'organizational familiarity', 'continuity' and 'social participation'. A clinical partnership model offers a degree of work readiness for novices when commencing their professional practice role. It enables individuals to participate and engage in workplace activities which are a central component of their learning.

Integrated approach to e-learning enhanced both subjective and objective knowledge of aEEG in a neonatal intensive care unit.

PubMed

Poon, W B; Tagamolila, V; Toh, Y P; Cheng, Z R

2015-03-01

Various meta-analyses have shown that e-learning is as effective as traditional methods of continuing professional education. However, there are some disadvantages to e-learning, such as possible technical problems, the need for greater self-discipline, cost involved in developing programmes and limited direct interaction. Currently, most strategies for teaching amplitude-integrated electroencephalography (aEEG) in neonatal intensive care units (NICUs) worldwide depend on traditional teaching methods. We implemented a programme that utilised an integrated approach to e-learning. The programme consisted of three sessions of supervised protected time e-learning in an NICU. The objective and subjective effectiveness of the approach was assessed through surveys administered to participants before and after the programme. A total of 37 NICU staff (32 nurses and 5 doctors) participated in the study. 93.1% of the participants appreciated the need to acquire knowledge of aEEG. We also saw a statistically significant improvement in the subjective knowledge score (p = 0.041) of the participants. The passing rates for identifying abnormal aEEG tracings (defined as ≥ 3 correct answers out of 5) also showed a statistically significant improvement (from 13.6% to 81.8%, p < 0.001). Among the participants who completed the survey, 96.0% felt the teaching was well structured, 77.8% felt the duration was optimal, 80.0% felt that they had learnt how to systematically interpret aEEGs, and 70.4% felt that they could interpret normal aEEG with confidence. An integrated approach to e-learning can help improve subjective and objective knowledge of aEEG.

A Big Data and Learning Analytics Approach to Process-Level Feedback in Cognitive Simulations.

PubMed

Pecaric, Martin; Boutis, Kathy; Beckstead, Jason; Pusic, Martin

2017-02-01

Collecting and analyzing large amounts of process data for the purposes of education can be considered a big data/learning analytics (BD/LA) approach to improving learning. However, in the education of health care professionals, the application of BD/LA is limited to date. The authors discuss the potential advantages of the BD/LA approach for the process of learning via cognitive simulations. Using the lens of a cognitive model of radiograph interpretation with four phases (orientation, searching/scanning, feature detection, and decision making), they reanalyzed process data from a cognitive simulation of pediatric ankle radiography where 46 practitioners from three expertise levels classified 234 cases online. To illustrate the big data component, they highlight the data available in a digital environment (time-stamped, click-level process data). Learning analytics were illustrated using algorithmic computer-enabled approaches to process-level feedback.For each phase, the authors were able to identify examples of potentially useful BD/LA measures. For orientation, the trackable behavior of re-reviewing the clinical history was associated with increased diagnostic accuracy. For searching/scanning, evidence of skipping views was associated with an increased false-negative rate. For feature detection, heat maps overlaid on the radiograph can provide a metacognitive visualization of common novice errors. For decision making, the measured influence of sequence effects can reflect susceptibility to bias, whereas computer-generated path maps can provide insights into learners' diagnostic strategies.In conclusion, the augmented collection and dynamic analysis of learning process data within a cognitive simulation can improve feedback and prompt more precise reflection on a novice clinician's skill development.

Knowledge-rich temporal relation identification and classification in clinical notes

PubMed Central

D’Souza, Jennifer; Ng, Vincent

2014-01-01

Motivation: We examine the task of temporal relation classification for the clinical domain. Our approach to this task departs from existing ones in that it is (i) ‘knowledge-rich’, employing sophisticated knowledge derived from discourse relations as well as both domain-independent and domain-dependent semantic relations, and (ii) ‘hybrid’, combining the strengths of rule-based and learning-based approaches. Evaluation results on the i2b2 Clinical Temporal Relations Challenge corpus show that our approach yields a 17–24% and 8–14% relative reduction in error over a state-of-the-art learning-based baseline system when gold-standard and automatically identified temporal relations are used, respectively. Database URL: http://www.hlt.utdallas.edu/~jld082000/temporal-relations/ PMID:25414383

'I now have a visual image in my mind and it is something I will never forget': an analysis of an arts-informed approach to health professions ethics education.

PubMed

Kinsella, Elizabeth Anne; Bidinosti, Susan

2016-05-01

This paper reports on a study of an arts informed approach to ethics education in a health professions education context. The purpose of this study was to investigate students' reported learning experiences as a result of engagement with an arts-informed project in a health professions' ethics course. A hermeneutic phenomenological methodological approach was adopted for the study. The data were collected over 5 years, and involved analysis of 234 occupational therapy students' written reflections on learning. Phenomenological methods were used. Five key themes were identified with respect to students' reported learning including: becoming aware of values, (re) discovering creativity, coming to value reflection in professional life, deepening self-awareness, and developing capacities to imagine future practices. There appear to be a number of unique ways in which arts-informed approaches can contribute to health professions education including: activating imaginative engagement, fostering interpretive capacity, inspiring transformative understandings, offering new ways of knowing, deepening reflection, and heightening consciousness, while also enriching the inner life of practitioners. Innovative approaches are being used to introduce arts-informed practices in health professions curricula programs. The findings point to the promise of arts-informed approaches for advancing health sciences education.

Off-site training of laparoscopic skills, a scoping review using a thematic analysis.

PubMed

Thinggaard, Ebbe; Kleif, Jakob; Bjerrum, Flemming; Strandbygaard, Jeanett; Gögenur, Ismail; Matthew Ritter, E; Konge, Lars

2016-11-01

The focus of research in simulation-based laparoscopic training has changed from examining whether simulation training works to examining how best to implement it. In laparoscopic skills training, portable and affordable box trainers allow for off-site training. Training outside simulation centers and hospitals can increase access to training, but also poses new challenges to implementation. This review aims to guide implementation of off-site training of laparoscopic skills by critically reviewing the existing literature. An iterative systematic search was carried out in MEDLINE, EMBASE, ERIC, Scopus, and PsychINFO, following a scoping review methodology. The included literature was analyzed iteratively using a thematic analysis approach. The study was reported in accordance with the STructured apprOach to the Reporting In healthcare education of Evidence Synthesis statement. From the search, 22 records were identified and included for analysis. A thematic analysis revealed the themes: access to training, protected training time, distribution of training, goal setting and testing, task design, and unsupervised training. The identified themes were based on learning theories including proficiency-based learning, deliberate practice, and self-regulated learning. Methods of instructional design vary widely in off-site training of laparoscopic skills. Implementation can be facilitated by organizing courses and training curricula following sound education theories such as proficiency-based learning and deliberate practice. Directed self-regulated learning has the potential to improve off-site laparoscopic skills training; however, further studies are needed to demonstrate the effect of this type of instructional design.

Analysis of mathematical literacy ability based on self-efficacy in model eliciting activities using metaphorical thinking approach

NASA Astrophysics Data System (ADS)

Setiani, C.; Waluya, S. B.; Wardono

2018-03-01

The purposes of this research are: (1) to identify learning quality in Model Eliciting Activities (MEAs) using a Metaphorical Thinking (MT) approach regarding qualitative and quantitative; (2) to analyze mathematical literacy of students based on Self-Efficacy (SE). This research is mixed method concurrent embedded design with qualitative research as the primary method. The quantitative research used quasi-experimental with non-equivalent control group design. The population is VIII grade students of SMP Negeri 3 Semarang Indonesia. Quantitative data is examined by conducting completeness mean test, standard completeness test, mean differentiation test and proportional differentiation test. Qualitative data is analyzed descriptively. The result of this research shows that MEAs learning using MT approach accomplishes good criteria both quantitatively and qualitatively. Students with low self-efficacy can identify problems, but they are lack ability to arrange problem-solving strategy on mathematical literacy questions. Students with medium self-efficacy can identify information provided in issues, but they find difficulties to use math symbols in making a representation. Students with high self-efficacy are excellent to represent problems into mathematical models as well as figures by using appropriate symbols and tools, so they can arrange strategy easily to solve mathematical literacy questions.