LOL Teacher! Using Humor to Enhance Student Learning

ERIC Educational Resources Information Center

Terrell, Shelly

2015-01-01

Laughing with students can help them connect on a deeper level with the teacher and the learning. This article offers the following four strategies to incorporate humor into teaching: (1) Integrate humorous bits to boost engagement; (2) Choose humorous materials; (3) Create interest with humorous web tools and apps; and (4) Teach with silly…

From Professional Development to Implementation: What Teachers Say Makes Change Happen

ERIC Educational Resources Information Center

Depka, Eileen M.

2012-01-01

The success of students across the nation is reliant on the expertise and talents of teachers. Continuous growth and lifelong learning are expectations within the teaching profession. Learning new strategies in order to meet student needs and boost achievement is a constant target. Each year school districts spend millions of dollars on…

A Better Blend: A Vision for Boosting Student Outcomes with Digital Learning

ERIC Educational Resources Information Center

Public Impact, 2013

2013-01-01

Blended learning that combines digital instruction with live, accountable teachers holds unique promise to improve student outcomes dramatically. Schools will not realize this promise at large scale with technology improvements alone, though, or with technology and today's typical teaching roles. This brief explains how schools can use blended…

Can Performance Feedback during Instruction Boost Knowledge Acquisition? Contrasting Criterion-Based and Social Comparison Feedback

ERIC Educational Resources Information Center

Kollöffel, Bas; de Jong, Ton

2016-01-01

Feedback indicating how well students are performing during a learning task can be very stimulating. In this study with a pre- and post-test design, the effects of two types of performance feedback on learning results were compared: feedback during a learning task was either stated in terms of how well the students were performing relative to…

Champions: District Leaders Build Skills to Boost Educator Practice

ERIC Educational Resources Information Center

Psencik, Kay; Brown, Frederick; Cain, Laura; Coleman, Ramona; Cummings, C. Todd

2014-01-01

Fort Wayne Community Schools continue to increase student learning and meet state and national standards and expectations annually based on several factors that have made a difference for educators within the system: district and principal leadership, learning teams, effective learning designs, and deep commitment to a culture of learning. Fort…

Classroom Management. Make Your Students Teachers, Too.

ERIC Educational Resources Information Center

Gomoll, Judith A.

1993-01-01

Describes how to boost elementary students' confidence and nurture responsibility by making students resident experts at review stations. Students rotate from station to station where the experts are learning at their own pace, spending more time on material they do not understand, and receiving personal attention and immediate feedback. (SM)

Boosting Financial Literacy: Benefits from Learning Study

ERIC Educational Resources Information Center

Pang, Ming Fai

2010-01-01

This paper reports on a study that employed a theory-based approach in the form of a learning study to enhance a domain-specific generic capability, financial literacy, of Grade 12 students to empower them to make informed and independent financial decisions. Financial literacy is seen in this study as a function of student understanding of a…

Curriculum Boosters. Social Studies, Math, Language Arts.

ERIC Educational Resources Information Center

Reissman, Rose; And Others

1994-01-01

Presents three curriculum boosting activities for elementary classes. A social studies activity builds bridges to other cultures via literature. A math activity teaches students about percentages using baseball card statistics. A language arts activity helps students learn to appreciate the language of Shakespeare. A student page presents a…

Knocking Down Barriers: How California Superintendents Are Implementing Blended Learning

ERIC Educational Resources Information Center

Horn, Michael B.; Gu, Anna; Evans, Meg

2014-01-01

School districts across the United States are implementing blended learning to boost student achievement. The authors convened several California school district superintendents to answer the questions: "What are the barriers, real or perceived, to implementing blended learning in your district?" and "Have you found solutions to or…

Building a Comprehensive System to Support All Students Getting to High School Graduation and beyond. Forum Brief

ERIC Educational Resources Information Center

American Youth Policy Forum, 2012

2012-01-01

If the U.S. is to increase the number of college graduates and boost our national competitiveness, we must redouble our efforts to ensure all students graduate from high school prepared for postsecondary learning and careers. This means creating comprehensive education systems that provide learning options that enable a range of pathways to…

Supporting the Language Development of Limited English Proficient Students through Arts Integration in the Primary Grades

ERIC Educational Resources Information Center

Brouillette, Liane

2012-01-01

This article looks at how arts integration can boost the language development of limited English proficient students in kindergarten through second grade. I first review existing research on how young children learn and describe the special challenges faced by children who must learn in an unfamiliar language. I then identify arts-based mechanisms…

Student Engagements Help Educate and Boost Workforce Development -

Science.gov Websites

Continuum Magazine | NREL Two young men assemble the model of a house. Two students assemble the future by having students learn about building renewable energy technologies, as well as offering estimated $65 billion in damages. The disaster also inspired students from New Jersey's Stevens Institute of

Boosting Student Attendance: Beyond Stickers, Stars, and Candy Bars

ERIC Educational Resources Information Center

Dill, Vicky; Lopez, Patrick; Stahlke, Tim; Stamp, Jeanne

2016-01-01

We know that students cannot learn if they are not in school, and that students with economic challenges miss school more frequently than other students. What obstacles create this attendance gap, and how can school districts provide the supports to improve attendance for these students? The authors of this article, who work with the Texas…

Best Practices in Preparing Students for Mock Interviews

ERIC Educational Resources Information Center

Hansen, Katharine; Oliphant, Gary C.; Oliphant, Becky J.; Hansen, Randall S.

2009-01-01

Studies have shown the importance of employment interview preparation in boosting the confidence and performance of students and jobseekers when they interview. This article reviews several techniques for preparing students for mock job interviews and, hence, actual job interviews. For instructors who would like to enhance the learning value of…

Game-Based Learning: Increasing the Logical-Mathematical, Naturalistic, and Linguistic Learning Levels of Primary School Students

ERIC Educational Resources Information Center

del Moral Pérez, M. Esther; Duque, Alba P. Guzmán; García, L. Carlota Fernández

2018-01-01

Game-based learning is an innovative methodology that takes advantage of the educational potential offered by videogames in general and serious games in particular to boost training processes, thus making it easier for users to achieve motivated learning. The present paper focuses on the description of the Game to Learn Project, which has as its…

A State for Excellence: New Jersey Boosts Learning Power with Online Video Resources

ERIC Educational Resources Information Center

Duff, Victoria; Sauer, Wendy; Gleason, Sonia Caus

2011-01-01

The New Jersey Department of Education supports all districts with a tool kit of valuable resources for planning and creating collaborative learning structures that focus on getting results for all students. This tool kit was the basis for the creation of Learning Forward's "Becoming a Learning School" (2009). The tool kit helps…

Problem Solved: Middle School Math Instruction Gets a Boost from a Flexible Model for Learning

ERIC Educational Resources Information Center

Jacobs, Jennifer; Koellner, Karen; Funderburk, Joanie

2012-01-01

Education researchers frequently seek out districts, schools, and teachers as partners for professional learning projects. They share their ambitious vision--a new model of professional learning that will support an empowered community, instructional improvement, and student achievement. The authors, along with other members of their research…

Developing Competencies by Playing Digital Sports-Games

ERIC Educational Resources Information Center

Kretschmann, Rolf

2010-01-01

The idea of digital game-based learning (DGBL) is that students (or players) learn something by playing a computer or video game and that an educator can employ digital games to assist and boost both formal and informal learning. There is game software that is not specifically produced for educational use but which is nonetheless regularly…

"We've Got to Keep Meeting Like This": A Pilot Study Comparing Academic Performance in Shifting-Membership Cooperative Groups versus Stable-Membership Cooperative Groups in an Introductory-Level Lab

ERIC Educational Resources Information Center

Walker, Alicia; Bush, Amy; Sanchagrin, Ken; Holland, Jonathon

2017-01-01

This study examined possible ways to increase student engagement in small sections of a large, introductory-level, required university course. Research shows that cooperative group learning boosts achievement through fostering better interpersonal relationships between students. Cooperative group learning is an evidence-based instructional…

Elements of Scenario-Based Learning on Suicidal Patient Care Using Real-Time Video.

PubMed

Lu, Chuehfen; Lee, Hueying; Hsu, Shuhui; Shu, Inmei

2016-01-01

This study aims understanding of students' learning experiences when receiving scenario-based learning combined with real-time video. Videos that recorded student nurses intervention with a suicidal standardized patient (SP) were replayed immediately as teaching materials. Videos clips and field notes from ten classes were analysed. Investigators and method triangulation were used to boost the robustness of the study. Three key elements, emotional involvement, concretizing of the teaching material and substitute learning were identified. Emotions were evoked among the SP, the student performer and the students who were observing, thus facilitating a learning effect. Concretizing of the teaching material refers to students were able to focus on the discussions using visual and verbal information. Substitute learning occurred when the students watching the videos, both the strengths and weaknesses represented were similar to those that would be likely to occur. These key elements explicate their learning experience and suggested a strategic teaching method.

Addressing Achievement Gaps with Psychological Interventions

ERIC Educational Resources Information Center

Yeager, David; Walton, Gregory; Cohen, Geoffrey L.

2013-01-01

Student psychology--how the classroom looks and feels from the perspective of the student--can powerfully affect motivation and learning, and experiments are increasingly showing that even brief interventions to change psychology can boost achievement over months or years. When paired with other structural reforms, social-psychological…

University 100 Orientation Courses and Living-Learning Communities Boost Academic Retention and Graduation via Enhanced Self-Efficacy and Self-Regulated Learning

ERIC Educational Resources Information Center

Cambridge-Williams, Tiffany; Winsler, Adam; Kitsantas, Anastasia; Bernard, Elizabeth

2013-01-01

Nationwide, almost a third of 1st-year college students do not return to begin their sophomore year, and the 5-year graduation rate for undergraduates is only around 40%. It is important for universities to implement interventions, such as freshman transition courses, to help new students adjust to college life and succeed, and it is critical that…

Moving Edtech Forward: Upstart School Networks Are Betting on a Breakthrough

ERIC Educational Resources Information Center

Horn, Michael B.

2016-01-01

The digital revolution occurring in schools has focused predominantly on online education in its various forms--including fully online courses, learning management systems, games, and mobile applications--to personalize learning and boost the performance of all students. Companies have been experimenting with technologies for years, yet these…

Experience of nursing students with standardized patients in simulation-based learning: Q-methodology study.

PubMed

Ha, Eun-Ho

2018-04-23

Standardized patients (SPs) boost self-confidence, improve problem solving, enhance critical thinking, and advance clinical judgment of nursing students. The aim of this study was to examine nursing students' experience with SPs in simulation-based learning. Q-methodology was used. Department of nursing in Seoul, South Korea. Fourth-year undergraduate nursing students (n = 47). A total of 47 fourth-year undergraduate nursing students ranked 42 Q statements about experiences with SPs into a normal distribution grid. The following three viewpoints were obtained: 1) SPs are helpful for patient care (patient-centered view), 2) SPs roles are important for nursing student learning (SPs roles-centered view), and 3) SPs can promote competency of nursing students (student-centered view). These results indicate that SPs may improve nursing students' confidence and nursing competency. Professors should reflect these three viewpoints in simulation-based learning to effectively engage SPs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Can We Pay for Current Education Reform?

ERIC Educational Resources Information Center

Odden, Allan

2012-01-01

For more than 30 years, the United States has been engaged in education reform efforts designed to dramatically boost student performance and close achievement gaps linked to poverty and ethnicity. Can schools afford those education ambitions? Most educators have their doubts. The author believes educators can improve student learning even when…

Can Tag Help Schools Teach?

ERIC Educational Resources Information Center

Robert Wood Johnson Foundation, 2012

2012-01-01

Elementary schools are faced with a challenge: boosting student learning in an era when students face far more than schoolwork-related difficulties. Too often today, kids enter the classroom contending with issues ranging from bullying and emotional trauma to family instability and economic hardship--which can lead to behavioral problems that…

Mastery, Maladaptive Learning Behaviour, and Academic Achievement: An Intervention Approach

ERIC Educational Resources Information Center

Ranellucci, John; Hall, Nathan; Muis, Krista; Lajoie, Susanne; Robinson, Kristy

2017-01-01

The effects of three interventions designed to boost academic achievement among mastery-oriented students were evaluated on interest-based studying, social desirability, and perceived goal difficulty. Undergraduate students (N = 177) completed relevant self-report measures at the beginning and the end of the semester and were randomly assigned to…

More Technology, Better Learning Resources, Better Learning? Lessons from Adopting Virtual Microscopy in Undergraduate Medical Education

ERIC Educational Resources Information Center

Helle, Laura; Nivala, Markus; Kronqvist, Pauliina

2013-01-01

The adoption of virtual microscopy at the University of Turku, Finland, created a unique real-world laboratory for exploring ways of reforming the learning environment. The purpose of this study was to evaluate the students' reactions and the impact of a set of measures designed to boost an experimental group's understanding of abnormal histology…

Math Puzzlers: 25 Reproducible Puzzles, Games, and Activities that Boost the Math Skills and Up the Fun! Grades 2-5.

ERIC Educational Resources Information Center

Kimble-Ellis, Sonya

Puzzles, games, and activities provide perfect opportunities for students to work in groups, interact, communicate with each other, and discuss strategies. The activities, games, and puzzles contained in this book are designed to help students learn mathematics in a fun yet challenging way. The activities are designed to encourage students to…

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept.

PubMed

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

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning.

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept

PubMed Central

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

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning. PMID:28861130

Think Summer: Early Planning, Teacher Support Boost Summer Learning Programs

ERIC Educational Resources Information Center

Browne, Daniel

2013-01-01

A fundamental problem that continues to plague educators is the achievement gap between low-income and higher-income students. In the ongoing search for solutions, one of the more promising approaches is expanding opportunities for learning, particularly in the summer. This article describes a project funded by The Wallace Foundation that offers…

Finding a Way: Learning Activities in Geography for Grades 7-11.

ERIC Educational Resources Information Center

National Council for Geographic Education.

This set of curriculum modules contains geography learning activities that emphasize strategies to encourage young women in geography and social studies classes. Compiled in an effort to improve the motivation and achievement levels of students in geography classrooms, grades 7-11, the modules aim to boost academic performance and overall interest…

If You Show Up, They'll Surprise You

ERIC Educational Resources Information Center

Snow, Carrie C.

2017-01-01

One essential way to support students with autism is to "show up" for them. Showing up means connecting and building relationships with learners and trusting students to show us what they most need to boost their learning and social growth. Snow shares scenarios from her years as a special educator that showcase ways educators can…

A Balancing Act: School Budgeting and Resource Allocation on a New Dual Language Campus

ERIC Educational Resources Information Center

Knight, David S.; Izquierdo, Elena; DeMatthews, David E.

2016-01-01

Dual language instructional models have great potential to create inclusive learning environments for traditional under-served students and boost student outcomes. However, principals face many barriers to implementation. One of the key challenges is aligning resources to ensure that the school has (a) an appropriate number of certificated…

Factors Affecting the Learning of English as a Second Language in Israel.

ERIC Educational Resources Information Center

Abu-Rabia, Salim

1996-01-01

Explores the effects of the attitudes and culture of Israeli-Jewish English-language students on their reading comprehension. Eighth-grade students read stories in Hebrew and English and answered questions both about the stories and their own attitudes. Reveals that culturally familiar texts boost reading comprehension scores. (MJP)

Active Engagement with Assessment and Feedback Can Improve Group-Work Outcomes and Boost Student Confidence

ERIC Educational Resources Information Center

Scott, G. W.

2017-01-01

This study involves evaluation of a novel iterative group-based learning task developed to enable students to actively engage with assessment and feedback in order to improve the quality of their written work. The students were all in the final semester of their final year of study and enrolled on either BSc Zoology or BSc Marine and Freshwater…

The Contribution of Email Exchanges to Second Language Acquisition: A Case of Cross-Cultural Communication between Africa and North America

ERIC Educational Resources Information Center

Ndemanu, Michael Takafor

2012-01-01

An online epistolary project was conducted with Cameroonian French-speaking students in order to boost English language learning. The project involved email exchanges (in English) between a small group of students from Cameroon and Canada, and it was coordinated by their teachers in both countries. At the end of the study, student emails were…

Blog construction as an effective tool in biochemistry active learning.

PubMed

Cubas Rolim, Estêvão; Martins de Oliveira, Julia; Dalvi, Luana T; Moreira, Daniel C; Garcia Caldas, Natasha; Fernandes Lobo, Felipe; André Polli, Démerson; Campos, Élida G; Hermes-Lima, Marcelo

2017-05-01

To boost active learning in undergraduate students, they were given the task of preparing blogs on topics of clinical biochemistry. This "experiment" lasted for 12 teaching-semesters (from 2008 to 2013), and included a survey on the blogs' usefulness at the end of each semester. The survey (applied in the 2008-2010 period) used a Likert-like questionnaire with eight questions and a 1-to-6 scale, from "totally disagree" to "fully agree." Answers of 428 students were analyzed and indicated overall approval of the blog activity: 86% and 35% of the responses scored 4-to-6 and 6, respectively. Considering the survey results, the high grades obtained by students on their blogs (averaging 8.3 in 2008-2010), and the significant increase in average grades of the clinical biochemistry exam after the beginning of the blog system (from 5.5 in 2007 to 6.4 in 2008-2010), we concluded that blogging activity on biochemistry is a promising tool for boosting active learning. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(3):205-215, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

Blog Construction as an Effective Tool in Biochemistry Active Learning

ERIC Educational Resources Information Center

Cubas Rolim, Estêvão; Martins de Oliveira, Julia; Dalvi, Luana T.; Moreira, Daniel C.; Garcia Caldas, Natasha; Fernandes Lobo, Felipe; André Polli, Démerson; Campos, Élida G.; Hermes-Lima, Marcelo

2017-01-01

To boost active learning in undergraduate students, they were given the task of preparing blogs on topics of clinical biochemistry. This "experiment" lasted for 12 teaching-semesters (from 2008 to 2013), and included a survey on the blogs' usefulness at the end of each semester. The survey (applied in the 2008-2010 period) used a…

Sports Business Unit Meets Cross-Curricular Learning Goals: Grades 9-12

ERIC Educational Resources Information Center

Curriculum Review, 2006

2006-01-01

A new online learning tool called the eCommSports Kit links a seven-step sports marketing curriculum with a school team to give students real-life experience in developing and executing a plan to boost game attendance. The kit, available through http://www.ecommsports.com, takes teens on a cross-curricular journey through conducting business…

See It, Be It, Write It: Using Performing Arts to Improve Writing Skills and Test Scores

ERIC Educational Resources Information Center

Blecher-Sass, Hope Sara; Moffitt, Maryellen

2010-01-01

Improve students' writing skills and boost their assessment scores while adding arts education, creativity, and fun to your writing curriculum. With this vibrant resource, improving writing skills goes hand-in-hand with improving test scores. Students learn how to use acting and visualization as prewriting activities to help them connect writing…

Improving Student Outcomes: Restoring America's Education Potential. Strategy Paper

ERIC Educational Resources Information Center

Greenstone, Michael; Looney, Adam; Shevlin, Paige

2011-01-01

For decades, investments in public education have boosted U.S. productivity and earnings, forged a path out of poverty for many families, helped disadvantaged students narrow the learning gap with their peers, and developed a workforce that continues to be among the most productive and innovative on Earth. More recently, this engine of growth has…

Word Travelers: Using Digital Tools to Explore Vocabulary and Develop Independent Learners

ERIC Educational Resources Information Center

Tysseling, Lee Ann

2012-01-01

The Internet is full of tools for vocabulary development, but the quality and usefulness for teachers and students vary greatly. With a traditionalist's respect for word knowledge and an adventurer's spirit for discovering new routes to learning, Lee Ann Tysseling shares an exciting array of technology-assisted resources that can boost students'…

Significant Changes in the Environment and in Teaching Methodology of an E-Learning Discipline to Avoid Dropouts in a Course at the Federal Institute

ERIC Educational Resources Information Center

Oliveira, Gustavo Prado; Aarreniemi-Jokipelto, Päivi; Boaventura, Ricardo Soares

2015-01-01

The research is conducted in a public institute of education and technology to boost graduation especially with the help of an e-learning environment adopted. The Directory of E-learning Education from Federal Institute of Triangulo Mineiro coordinates all administrative and pedagogical aspects of 4,000 students registered in 11 e-learning…

In the Background

ERIC Educational Resources Information Center

Garibay, Pat

2007-01-01

Educators and administrators are looking for new ways to boost student performance and eliminate barriers to learning. When working to improve the classroom environment, facility managers typically target the physical structure, temperature controls, humidity levels and ventilation. Many heating, ventilating and air conditioning (HVAC) consultants…

Daylight Makes a Difference: Daylight in the Classroom Can Boost Standardized Test Scores and Learning. [Audiotape].

ERIC Educational Resources Information Center

Kosik, Kenneth S.; Heschong, Lisa

An audiotape presents study analysis of the effect of daylighting on student performance. The study includes a focus on skylighting as a way to isolate daylight as an illumination source, and separate illumination effects from other qualities associated with daylighting from windows. Results from test scores of over 21,000 student records, along…

Finding Time for Teams: Student Achievement Grows as District Support Boosts Collaboration

ERIC Educational Resources Information Center

Johnston, Jef; Knight, Mary; Miller, Laura

2007-01-01

Finding time for teams to work in schools is both a necessity and a responsibility. If educators are sincere about efforts to improve student learning, leaders must take responsibility for providing team time for teachers and a structure in which they are able to work collaboratively. The Papillion-La Vista (Nebraska) Public Schools took to heart…

Negating Stereotype Threat: Autonomy Support and Academic Identification Boost Performance of African American College Students

ERIC Educational Resources Information Center

Nadler, Dustin R.; Komarraju, Meera

2016-01-01

Using a 2 × 2 factorial design, we examined the effects of stereotype threat and autonomy support on the test performance of 190 African American college students. Participants completed a set of 7 easy and 7 difficult problems from Raven's Progressive Matrices and a survey including measures of Academic Self-Concept, Learning Climate, and…

The Chicken Soup Effect: The Role of Recreation and Intramural Participation in Boosting Freshman Grade Point Average

ERIC Educational Resources Information Center

Gibbison, Godfrey A.; Henry, Tracyann L.; Perkins-Brown, Jayne

2011-01-01

Freshman grade point average, in particular first semester grade point average, is an important predictor of survival and eventual student success in college. As many institutions of higher learning are searching for ways to improve student success, one would hope that policies geared towards the success of freshmen have long term benefits…

Learning autonomy in writing class: Implementation of project-based learning in english for spesific purposes

NASA Astrophysics Data System (ADS)

Ayu Sukerti, G. N.; Yuliantini, Ny

2018-01-01

This research was aimed to analyze students’ attitude on learning autonomy through the implementation of project-based learning (PBL). Writing has been considered one of the most difficult competencies to master as it incorporates several integrated language skills. Thus, teaching writing in English for Specific Class posts a huge challenge as students often feel discouraged by the complex series of processes involved in producing a well-structured piece of writing. This research implemented PBL as the learning model to boost students’ learning outcomes and construct self-directed learning. Participants were 25 second semester students enrolled in a three-year undergraduate program in Informatics Management. The implementation of PBL in writing class contributed real advantages since it allowed students to collaboratively arrange outline in order to produce individual drafts and final essays. The study revealed that students were able to be involved in a more deep and autonomous learning as they helped each other during group discussion. The students autonomously engaged in the completion of the project in a more positive attitude. They also acquired more knowledge in the aspect of grammar and learned how to use language in proper context based on the feedbacks they got during revising their writing.

The learning environment as a mediating variable between self-directed learning readiness and academic performance of a sample of saudi nursing and medical emergency students.

PubMed

Alotaibi, Khaled N

2016-01-01

There has been some ground-breaking research on self-directed learning (SDL) in nursing education which reveals the superiority of SDL to traditional learning methods in terms of students' academic performance and the development of positive attitudes toward the learning process on the part of both students and teachers. The relationship between students' self-directed learning readiness (SDLR) and students' academic performance, and the mediating role of students' perceptions of the learning environment needs further investigation. In this study, it is proposed that students' perceptions of their learning environment could enhance their SDLR and thus boost their academic performance (in terms of their GPA). A descriptive design was used to examine the relationships between the domains of SDLR, which are self-management, desire to learn and self-control and students' perceptions of the learning environment (SPLE) and students' GPA. A survey involving 342 [Corrected] Saudi students from nursing and emergency medical services undergraduate programs in King Saud University was used for this research. The results showed that SDLR level positively influenced students' academic performance positively, and that students' perceptions of their learning environment played a significant role in determining their level of SDLR and academic performance. It is recommended that nursing and emergency medical services educators provide a supportive learning environment in terms of good teaching, clear goals and standards, appropriate assessment, appropriate workload, and emphasis on independence to encourage students to engage in the process of SDL which can, in turn, enhance their academic performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Literacy Gets "a" Makeover: Engaged Learning Boosts Student Achievement at Michigan High School

ERIC Educational Resources Information Center

Wood, Richard E.; Burz, Helen L.

2013-01-01

E.A. Johnson High School is located in Mt. Morris, Michigan, near Flint, where the city has felt deeply the impact of the area's economic decline. 72% of the student population qualify for free and reduced lunch. The staff was willing to make the changes necessary for success, but needed more than a book study. Many of the structures for…

Social-Emotional Skills Can Boost Common Core Implementation

ERIC Educational Resources Information Center

Elias, Maurice J.

2014-01-01

The same competencies neglected in the implementation of the Common Core are those that ultimately most help students become what the author calls college-ready, career-ready, and contribution-ready. These include communication, meta-cognition, resilient mindset, responsible character, and social-emotional learning, intertwined with academic…

Incorporating E-learning in teaching English language to medical students: exploring its potential contributions.

PubMed

Navidinia, Hossein; Zare Bidaki, Majid; Hekmati, Nargess

2016-01-01

Background: The spread of technology has influenced different aspects of human life, and teaching and learning are not exceptions. This study aimed to examine the potential contribution of the use of technology in teaching English language to medical students. Methods: This qualitative-action research study was conducted in Birjand University of Medical Sciences (BUMS), with 60 medical students taking a general English course in the Fall Semester of 2015. The class favored different tools and multimedia facilities such as a tube channel, e-dictionaries, educational films, and etextbooks to enhance students' learning. In addition, the class had a weblog in which students could upload assignments and receive feedback from peers and the instructors. Results: The results revealed that e-learning could enhance students' language proficiency and facilitate the teaching process. Learners preferred to use more e-dictionaries to learn the meaning of the new words, watch English medical films to boost their speaking and listening skills, and use the electronic version of their textbook as they could carry it wherever they wanted. Conclusion: The students preferred this method of learning English as they became more independent by using the electronic facilities. They found that learning English did not have a fixed institutionalized method, and e-learning activities could provide them with authentic input for language learning even outside of the classroom.

Principals: Human Capital Managers at Every School

ERIC Educational Resources Information Center

Kimball, Steven M.

2011-01-01

Being a principal is more than just being an instructional leader. Principals also must manage their schools' teaching talent in a strategic way so that it is linked to school instructional improvement strategies, to the competencies needed to enact the strategies, and to success in boosting student learning. Teacher acquisition and performance…

Technology in Adult Education ESOL Classes

ERIC Educational Resources Information Center

Ball, Nancy

2011-01-01

Today's world is filled with technology resources such as cellphones, iPods, laptops and the internet. By using these technological resources, adult education ESOL teachers can improve instruction, boost learning and better prepare students for real world English use. This article examines advantages of technology use and offers examples of…

Now We Get It! Boosting Comprehension with Collaborative Strategic Reading

ERIC Educational Resources Information Center

Klingner, Janette K.; Vaughn, Sharon; Boardman, Alison; Swanson, Elizabeth

2012-01-01

Collaborative Strategic Reading is an innovative new approach to teaching reading that weaves together two instructional programs: cooperative learning and reading comprehension strategy instruction. In small groups, students work through the four main steps-Preview, "Click and Clunk," Get the Gist, and Wrap Up-helping each other improve…

Theoretical Framework for Educational Assessment: A Synoptic Review

ERIC Educational Resources Information Center

Ghaicha, Abdallah

2016-01-01

At this age of accountability, it is acknowledged that assessment is a powerful lever that can either boost or undermine students' learning. Hitherto, much of the regular institutional and instructional practices show that assessments remain inhibitory or void rather than constructive as these lack the assessment formative aspect. This denotes…

The Crucial Coaching Relationship

ERIC Educational Resources Information Center

Scales, Peter C.

2016-01-01

One of the most powerful ways to boost the payoff from school sports lays in helping coaches build developmental relationships with student-athletes. Developmental relationships are close connections through which young people develop character skills to discover who they are, gain the ability to shape their own lives, and learn how to interact…

Design Software Gives Rocketry a Boost in the Classroom

ERIC Educational Resources Information Center

Wilson, Spencer C.

2005-01-01

Building and launching model rockets makes a great activity for a technology education class. A model rocket curriculum provides a valuable tool for improving students' technical skills, including following technical instructions and procedures while learning about aerospace technology. This article describes a way of making model rocketry more…

Design Software Gives Rocketry a Boost in the Classroom

ERIC Educational Resources Information Center

Wilson, Spencer C.

2005-01-01

Building and launching model rockets makes a great activity for a technology education class. A model rocket curriculum provides a valuable tool for improving students' technical skills that includes, but is not limited to, following technical instructions and procedures while learning about aerospace technology. This article describes a way that…

Boosting Social and Emotional Development In and Out of School.

PubMed

Wallace, Ashley; Palmer, Jennifer

2017-11-01

(1) Illinois' state ESSA plan reflects the state’s whole-child approach, adding references to the social, emotional and behavioral needs of students, along with high expectations for student achievement. (2) Massachusetts' state ESSA plan lists supporting socialemotional learning, health and safety as among the state's core educational strategies. (3) South Carolina's ESSA plan develops a framework identifying self-direction, perseverance, global perspective and interpersonal skills to be among the characteristics that every student should have when he or she graduates from high school.

Mathematics Boot Camps: A Strategy for Helping Students to Bypass Remedial Courses

NASA Astrophysics Data System (ADS)

Hamilton, Marilyn A. L.

Many community colleges struggle to find the best strategy to help incoming at-risk students prepare for the placement test. The purpose of this quantitative quasi-experimental study, was to answer the question as to which of 2 programs, a 2-week, face-to-face mathematics refresher program, Math Boost-Up, or an online-only program, might increase the ACCUPLACER posttest scores of incoming community college students. The study used archival data for 136 students who self-selected to either participate in the Math Boost-Up program (the experiment group), or in the online-only program (the comparison group). Knowles's theory of adult learning, andragogy, served as the theoretical framework. Spearman, Kruskal-Wallis, Mann-Whitney, and chi-square tests were used to measure the effect of 4 moderator variables (age, high school GPA, number of minutes spent in MyFoundationsLab, and number of days spent in face-to-face sessions) on the pre- and posttest scores of students in each group. The results indicated that students in the Math Boost-Up program experienced statistically significant gains in arithmetic and elementary algebra than did those students in the online-only program. The results also indicated that the 4 moderator variables affected gains in posttest scores. Additionally, the results disproved the andragogical premise that students would be self-directed and would self-select to participate in the intervention. A recommendation was that participation in the face-to-face refresher program should be mandatory. The study contributes to social change by providing evidence that short-term refresher programs could increase the scores of students on placement tests.

Boosted ARTMAP: modifications to fuzzy ARTMAP motivated by boosting theory.

PubMed

Verzi, Stephen J; Heileman, Gregory L; Georgiopoulos, Michael

2006-05-01

In this paper, several modifications to the Fuzzy ARTMAP neural network architecture are proposed for conducting classification in complex, possibly noisy, environments. The goal of these modifications is to improve upon the generalization performance of Fuzzy ART-based neural networks, such as Fuzzy ARTMAP, in these situations. One of the major difficulties of employing Fuzzy ARTMAP on such learning problems involves over-fitting of the training data. Structural risk minimization is a machine-learning framework that addresses the issue of over-fitting by providing a backbone for analysis as well as an impetus for the design of better learning algorithms. The theory of structural risk minimization reveals a trade-off between training error and classifier complexity in reducing generalization error, which will be exploited in the learning algorithms proposed in this paper. Boosted ART extends Fuzzy ART by allowing the spatial extent of each cluster formed to be adjusted independently. Boosted ARTMAP generalizes upon Fuzzy ARTMAP by allowing non-zero training error in an effort to reduce the hypothesis complexity and hence improve overall generalization performance. Although Boosted ARTMAP is strictly speaking not a boosting algorithm, the changes it encompasses were motivated by the goals that one strives to achieve when employing boosting. Boosted ARTMAP is an on-line learner, it does not require excessive parameter tuning to operate, and it reduces precisely to Fuzzy ARTMAP for particular parameter values. Another architecture described in this paper is Structural Boosted ARTMAP, which uses both Boosted ART and Boosted ARTMAP to perform structural risk minimization learning. Structural Boosted ARTMAP will allow comparison of the capabilities of off-line versus on-line learning as well as empirical risk minimization versus structural risk minimization using Fuzzy ARTMAP-based neural network architectures. Both empirical and theoretical results are presented to enhance the understanding of these architectures.

Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions.

PubMed

Chen, Ke; Wang, Shihai

2011-01-01

Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learning with various strategies. To our knowledge, however, none of them takes all three semi-supervised assumptions, i.e., smoothness, cluster, and manifold assumptions, together into account during boosting learning. In this paper, we propose a novel cost functional consisting of the margin cost on labeled data and the regularization penalty on unlabeled data based on three fundamental semi-supervised assumptions. Thus, minimizing our proposed cost functional with a greedy yet stagewise functional optimization procedure leads to a generic boosting framework for semi-supervised learning. Extensive experiments demonstrate that our algorithm yields favorite results for benchmark and real-world classification tasks in comparison to state-of-the-art semi-supervised learning algorithms, including newly developed boosting algorithms. Finally, we discuss relevant issues and relate our algorithm to the previous work.

Problem-based learning through field investigation: Boosting questioning skill, biological literacy, and academic achievement

NASA Astrophysics Data System (ADS)

Suwono, Hadi; Wibowo, Agung

2018-01-01

Biology learning emphasizes problem-based learning as a learning strategy to develop students ability in identifying and solving problems in the surrounding environment. Problem identification skills are closely correlated with questioning skills. By holding this skill, students tend to deliver a procedural question instead of the descriptive one. Problem-based learning through field investigation is an instruction model which directly exposes the students to problems or phenomena that occur in the environment, and then the students design the field investigation activities to solve these problems. The purpose of this research was to describe the improvement of undergraduate biology students on questioning skills, biological literacy, and academic achievement through problem-based learning through field investigation (PBFI) compared with the lecture-based instruction (LBI). This research was a time series quasi-experimental design. The research was conducted on August - December 2015 and involved 26 undergraduate biology students at the State University of Malang on the Freshwater Ecology course. The data were collected during the learning with LBI and PBFI, in which questioning skills, biological literacy, and academic achievement were collected 3 times in each learning model. The data showed that the procedural correlative and causal types of questions are produced by the students to guide them in conducting investigations and problem-solving in PBFI. The biological literacy and academic achievement of the students at PBFI are significantly higher than those at LBI. The results show that PBFI increases the questioning skill, biological literacy, and the academic achievement of undergraduate biology students.

Lifewide Learning for Early Reading Development.

PubMed

Dowd, Amy Jo; Friedlander, Elliott; Jonason, Christine; Leer, Jane; Sorensen, Lisa Zook; Guajardo, Jarrett; D'Sa, Nikhit; Pava, Clara; Pisani, Lauren

2017-03-01

The authors examine the relationships between children's reading abilities and the enabling environment for learning in the context of Save the Children's Literacy Boost program. They conceptualize the enabling environment at a micro level, with two components: the home literacy environment, represented by reading materials/habits at home, and the community learning environment (community reading activities). Using longitudinal reading scores of 6,874 students in 424 schools in 12 sites across Africa and Asia, there was 1) a modest but consistent relationship between students' home literacy environments and reading scores, and 2) a strong relationship between reading gains and participation in community reading activities, suggesting that interventions should consider both home and community learning environments and their differential influences on interventions across different low-resource settings. © 2017 Wiley Periodicals, Inc.

Students interest in learning science through fieldwork activity encourage critical thinking and problem solving skills among UPSI pre-university students

NASA Astrophysics Data System (ADS)

Jamil, Siti Zaheera Muhamad; Khairuddin, Raja Farhana Raja

2017-05-01

Graduates with good critical thinking and problem solving (CTPS) skills are likely to boost their employability to live in 21st century. The demands of graduates to be equipped with CTPS skills have shifted our education system in focusing on these elements in all levels of education, from primary, the secondary, and up to the tertiary education, by fostering interesting teaching and learning activities such as fieldwork activity in science classes. Despite the importance of the CTPS skills, little is known about whether students' interests in teaching and learning activities, such as fieldwork activity, have any influence on the students CTPS skills. Therefore, in this investigation, firstly to examine students interests in learning science through fieldwork activity. Secondly, this study examined whether the students' interest in learning science through fieldwork activity have affect on how the students employ CTPS skills. About 100 Diploma of Science students in Universiti Pendidikan Sultan Idris (UPSI) were randomly chosen to participate in this study. All of the participants completed a survey on how they find the fieldwork activity implemented in their science classes and it relevents towards their CTPS skills development. From our findings, majority of the students (91%) find that fieldwork activity is interesting and helpful in increasing their interest in learning science (learning factor) and accommodate their learning process (utility). Results suggest that students' interest on the fieldwork activity in science classes does have some influence on the students development of CTPS skills. The findings could be used as an initial guideline by incorporating students' interest on other teaching and learning activities that being implemented in science classes in order to know the impacts of these learning activities in enhancing their CTPS skills.

The United State of Wyoming: Teacher-to-Teacher Initiative Boosts Reading Scores Statewide

ERIC Educational Resources Information Center

Lain, Sheryl

2014-01-01

When teachers collaborate in schools, taking collective responsibility to improve instruction and achieve goals, student performance improves and good results happen. Wyoming is one example of a state that uses peer-to-peer professional learning with notable results. Teachers joined together to form a statewide professional community and saw the…

Re-Imagining Science Education: Engaging Students in Science for Australia's Future. Australian Education Review 51

ERIC Educational Resources Information Center

Tytler, Russell

2007-01-01

Australian Education Review (AER) 51 elaborates on issues raised by the Australian Council for Educational Research (ACER) Research Conference 2006: "Boosting Science Learning--What Will It Take?" It challenges current orthodoxies in science education and proposes a re-imagining that charts new directions for science teaching and…

Within Our Reach: How America Can Educate Every Child

ERIC Educational Resources Information Center

Chubb, John E.

2005-01-01

The No Child Left Behind Act (NCLB) is bolder than all previous federal education laws, setting ambitious goals for universal student achievement and authorizing severe remedies for schools not reaching them. In a nation where most youngsters are far from proficient in reading and mathematics and where innumerable efforts to boost learning levels…

Supporting Success: Why and How to Improve Quality in After-School Programs

ERIC Educational Resources Information Center

Sheldon, Jessica; Hopkins, Leigh

2008-01-01

This report examines the program improvement strategies, step-by-step, that allowed The James Irvine Foundation's Communities Organizing to Advance Learning (CORAL) initiative to achieve the levels of quality needed to boost the academic success of participating students, and makes policy and funding suggestions for improving program performance.…

Modeling and Simulation: PowerBoosting Productivity with Simulation.

ERIC Educational Resources Information Center

Riley, Suzanne

Minnesota high school students and teachers are learning the technology of simulation and integrating it into business and industrial technology courses. Modeling and simulation is the science of using software to construct a system within an organization and then running simulations of proposed changes to assess results before funds are spent. In…

Integrating the Performing Arts in Grades K-5

ERIC Educational Resources Information Center

Rajan, Rekha S.

2012-01-01

Research documents that the arts boost learning, build confidence, and motivate students to participate in class. How do we keep the performing arts alive in this era of increased accountability and decreased funding? Rekha S. Rajan sets the stage for a creative and practical solution with detailed, concrete examples of how to integrate the…

SemiBoost: boosting for semi-supervised learning.

PubMed

Mallapragada, Pavan Kumar; Jin, Rong; Jain, Anil K; Liu, Yi

2009-11-01

Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most previous studies have focused on designing special algorithms to effectively exploit the unlabeled data in conjunction with labeled data. Our goal is to improve the classification accuracy of any given supervised learning algorithm by using the available unlabeled examples. We call this as the Semi-supervised improvement problem, to distinguish the proposed approach from the existing approaches. We design a metasemi-supervised learning algorithm that wraps around the underlying supervised algorithm and improves its performance using unlabeled data. This problem is particularly important when we need to train a supervised learning algorithm with a limited number of labeled examples and a multitude of unlabeled examples. We present a boosting framework for semi-supervised learning, termed as SemiBoost. The key advantages of the proposed semi-supervised learning approach are: 1) performance improvement of any supervised learning algorithm with a multitude of unlabeled data, 2) efficient computation by the iterative boosting algorithm, and 3) exploiting both manifold and cluster assumption in training classification models. An empirical study on 16 different data sets and text categorization demonstrates that the proposed framework improves the performance of several commonly used supervised learning algorithms, given a large number of unlabeled examples. We also show that the performance of the proposed algorithm, SemiBoost, is comparable to the state-of-the-art semi-supervised learning algorithms.

Incorporating E-learning in teaching English language to medical students: exploring its potential contributions

PubMed Central

Navidinia, Hossein; Zare Bidaki, Majid; Hekmati, Nargess

2016-01-01

Background: The spread of technology has influenced different aspects of human life, and teaching and learning are not exceptions. This study aimed to examine the potential contribution of the use of technology in teaching English language to medical students. Methods: This qualitative-action research study was conducted in Birjand University of Medical Sciences (BUMS), with 60 medical students taking a general English course in the Fall Semester of 2015. The class favored different tools and multimedia facilities such as a tube channel, e-dictionaries, educational films, and etextbooks to enhance students’ learning. In addition, the class had a weblog in which students could upload assignments and receive feedback from peers and the instructors. Results: The results revealed that e-learning could enhance students’ language proficiency and facilitate the teaching process. Learners preferred to use more e-dictionaries to learn the meaning of the new words, watch English medical films to boost their speaking and listening skills, and use the electronic version of their textbook as they could carry it wherever they wanted. Conclusion: The students preferred this method of learning English as they became more independent by using the electronic facilities. They found that learning English did not have a fixed institutionalized method, and e-learning activities could provide them with authentic input for language learning even outside of the classroom. PMID:28491837

[Behind the scenes of the didactic of nursing science knowledge: role play simulation filmed for learning through "problematic situations"].

PubMed

Gineyt, Christine

2015-12-01

clinical simulation to teach expertise to nursing students plays an important role in nursing schools (IFSI). as recommended in the training frame of reference, students must develop skills from real situations. The objective of this study was to determine the importance of role play simulation of 'problematic situations' to boost the process of appropriation of nursing science knowledge and initiate the task of conceptualization among first year students when putting up a drip. this contextual research used qualitative data collected from students who answered three open post-simulation questions in order to communicate how they felt faced with this learning technique. This data was compared with that of two executive tutors who used an observation grid during the simulation. the students' answers have shown that this learning technique offered the possibility to develop dexterity in problem solving skills, to construct new knowledge and to memorize knowledge gained from university science and nursing care. The executive tutors have observed the construction of a meta-cognitive attitude suited to the conceptualization of action. during a change in the relationship with knowledge, the executive tutors noted that students are happy to learn different types of knowledge.

Boosting Engagement and Growth with Formative Assessment: Leaders Share Their Lessons

ERIC Educational Resources Information Center

Northwest Evaluation Association, 2016

2016-01-01

Our featured leaders saw big gains when their teachers began using formative assessment practice to guide student growth minute-by-minute. Read the fourth article in our five-part series for the scoop on how committing to this high-impact instructional practice paid off for a regional agency, district, and school. Learn: (1) why our featured…

Differential Effects of Context and Feedback on Orthographic Learning: How Good Is Good Enough?

ERIC Educational Resources Information Center

Martin-Chang, Sandra; Ouellette, Gene; Bond, Linda

2017-01-01

In this study, students in Grade 2 read different sets of words under 4 experimental training conditions (context/feedback, isolation/feedback, context/no-feedback, isolation/no-feedback). Training took place over 10 trials, followed by a spelling test and a delayed reading posttest. Reading in context boosted reading accuracy initially; in…

Personal experience narratives by students: a teaching-learning tool in bioethics.

PubMed

Pandya, Radhika H; Shukla, Radha; Gor, Alpa P; Ganguly, Barna

2016-01-01

The principles of bioethics have been identified as important requirements for training basic medical doctors. Till now, various modalities have been used for teaching bioethics, such as lectures, followed by a small case-based discussion, case vignettes or debates among students. For effective teaching-learning of bioethics, it is necessary to integrate theory and practice rather than merely teach theoretical constructs without helping the students translate those constructs into practice. Classroom teaching can focus on the theoretical knowledge of professional relationships, patient-doctor relationships, issues at the beginning and end of life, reproductive technologies, etc. However, a better learning environment can be created through an experiencebased approach to complement lectures and facilitate successful teaching. Engaging students in reflective dialogue with their peers would allow them to refine their ideas with respect to learning ethics. It can help in the development both of the cognitive and affective domains of the teaching of bioethics. Real-life narratives by the interns, when used as case or situation analysis models for a particular ethical issue, can enhance other students' insight and give them a moral boost. Doing this can change the classroom atmosphere, enhance motivation, improve the students' aptitude and improve their attitude towards learning bioethics. Involving the students in this manner can prove to be a sustainable way of achieving the goal of deep reflective learning of bioethics and can serve as a new technique for maintaining the interest of students as well as teachers.

The Analysis of Learning Obstacle and Students Learning Motivation of Prospective Math Teachers in Basic Physics Class

NASA Astrophysics Data System (ADS)

Kurniawan, D. T.; Suhandi, A.; Kaniawati, I.; Rusdiana, D.

2017-02-01

Learning motivation revealed as a whole intrinsic factor that created, maintained and supported students to achieve the goal of learning. As the bigger motivation came with bigger success, motivation was considered as the main key to reach what students have planned. There were intrinsic and extrinsic factors that influence both the students and lecturers’ motivation. The factors in one hand, were essential to be defined by the lecturers in order to maintain and enhance the students’ enthusiasm. On the other hand, they also encouraged and thrilled the students to learn. The study aimed to expose and describe the motivational tendency and to knowledge and analyze learning obstacles faced by the students in basic physics class on students of prospective math teachers in FKIP Unswagati Cirebon. In addition, the study focused on the description of the six motivational components stated by Glyn and Koballa. The six were intrinsic motivation, extrinsic motivation, the relevance of studying physics for subjective purposes, willpower, self assessment and anxiety. Class responses were determined through questionnaire with four main indicators; the causes of being less popular subject, the cause of being disfavored subject, the description of the way the students draw the examination on basic physics subject and the academic background of the students. The results showed that 54% students stated that physics was disfavored because the subject was difficult to understand, 49% stated that the cause of being disfavored of the subject was because physics required complicated mathematics. Most of the students preferred to have game based activities that boosted thinking skill. According to the analysis of the students’ motivation, the findings revealed that the students’ had high level of anxiety in learning the subject. They mostly expressed their anxiety appeared from the material density and text book based assignments.

English Bar as a Venue to Boost Students' Speaking Self-Efficacy at the Tertiary Level

ERIC Educational Resources Information Center

Liu, Mingxu

2013-01-01

Research in EFL and ESL has confirmed that self-efficacy affects language learners' choices of learning tasks, persistence, motivation and achievement. As a cognitive construct, self-efficacy can be strengthened by both outcomes of behaviors and input from the environment. This paper studies the effects of an English Bar, a self-access center for…

Boosting Adolescent and Young Adult Literacy: An Examination of Literacy Teaching and Learning in Philadelphia's Accelerated High Schools

ERIC Educational Resources Information Center

Gold, Eva; Edmunds, Kimberly; Maluk, Holly; Reumann-Moore, Rebecca

2011-01-01

In 2010-11, the School District of Philadelphia (the District) operated thirteen accelerated high schools that served approximately 2,000 under-credited, over-age students. Each of the accelerated schools was managed by one of seven external providers, each with its own educational approach, and each with a contractual agreement with the…

Cellular Mechanisms of Transcranial Direct Current Stimulation

DTIC Science & Technology

2016-07-14

32 Section 3 Electrical stimulation accelerates and boosts the capacity for synaptic learning ...................... 50 Section 4...Section 3: tDCS is thought to boost the learning of tasks or therapy applied at the same time. We provide a cellular mechanism for this. Moreover, we...show that thus “boosting” is specific to the trained task. [Aim 2] Section 4: tDCS is though to boost learning by promoting synaptic plasticity. We

Investigating the Role of Computer-Supported Annotation in Problem-Solving-Based Teaching: An Empirical Study of a Scratch Programming Pedagogy

ERIC Educational Resources Information Center

Su, Addison Y. S.; Yang, Stephen J. H.; Hwang, Wu-Yuin; Huang, Chester S. J.; Tern, Ming-Yu

2014-01-01

For more than 2 years, Scratch programming has been taught in Taiwanese elementary schools. However, past studies have shown that it is difficult to find appropriate learning methods or tools to boost students' Scratch programming performance. This inability to readily identify tutoring tools has become one of the primary challenges addressed in…

Lasting Legacy for Achievement: Colorado Coaches Boost Teacher Effectiveness with a Rubric for Professional Learning

ERIC Educational Resources Information Center

Cross, Jean

2012-01-01

In 2006, the Weld County School District Re-8 in Fort Lupton, Colorado, was eager to find a way to increase teacher effectiveness and, as a result, improve student achievement. This small, semirural district about 35 miles northeast of Denver grappled with high teacher turnover (34% in 2005) and low scores on state assessments (three out of four…

Using Role-Playing Games to Teach Astronomy: An Evaluation

NASA Astrophysics Data System (ADS)

Francis, Paul

Since 1998, I've been experimenting with the use of role-playing games to teach astronomy. Students play the role of competing teams of researchers, racing to solve some astrophysical mystery. In this article, I review what has been learned from using these games around the world over the last eight years. The most common problem encountered is a tendency for students to become overly political. An unexpected benefit of these games is the boost that they give to student self- confidence. Overall, they seem to work well with a wide range of students, ranging from ninth grade to graduate school, and students exposed to this game comment repeatedly on how the games changed their attitudes toward the scientific process.

Using standardized patients versus video cases for representing clinical problems in problem-based learning.

PubMed

Yoon, Bo Young; Choi, Ikseon; Choi, Seokjin; Kim, Tae-Hee; Roh, Hyerin; Rhee, Byoung Doo; Lee, Jong-Tae

2016-06-01

The quality of problem representation is critical for developing students' problem-solving abilities in problem-based learning (PBL). This study investigates preclinical students' experience with standardized patients (SPs) as a problem representation method compared to using video cases in PBL. A cohort of 99 second-year preclinical students from Inje University College of Medicine (IUCM) responded to a Likert scale questionnaire on their learning experiences after they had experienced both video cases and SPs in PBL. The questionnaire consisted of 14 items with eight subcategories: problem identification, hypothesis generation, motivation, collaborative learning, reflective thinking, authenticity, patient-doctor communication, and attitude toward patients. The results reveal that using SPs led to the preclinical students having significantly positive experiences in boosting patient-doctor communication skills; the perceived authenticity of their clinical situations; development of proper attitudes toward patients; and motivation, reflective thinking, and collaborative learning when compared to using video cases. The SPs also provided more challenges than the video cases during problem identification and hypotheses generation. SPs are more effective than video cases in delivering higher levels of authenticity in clinical problems for PBL. The interaction with SPs engages preclinical students in deeper thinking and discussion; growth of communication skills; development of proper attitudes toward patients; and motivation. Considering the higher cost of SPs compared with video cases, SPs could be used most advantageously during the preclinical period in the IUCM curriculum.

The memorial consequences of multiple-choice testing.

PubMed

Marsh, Elizabeth J; Roediger, Henry L; Bjork, Robert A; Bjork, Elizabeth L

2007-04-01

The present article addresses whether multiple-choice tests may change knowledge even as they attempt to measure it. Overall, taking a multiple-choice test boosts performance on later tests, as compared with non-tested control conditions. This benefit is not limited to simple definitional questions, but holds true for SAT II questions and for items designed to tap concepts at a higher level in Bloom's (1956) taxonomy of educational objectives. Students, however, can also learn false facts from multiple-choice tests; testing leads to persistence of some multiple-choice lures on later general knowledge tests. Such persistence appears due to faulty reasoning rather than to an increase in the familiarity of lures. Even though students may learn false facts from multiple-choice tests, the positive effects of testing outweigh this cost.

Boosting Learning Algorithm for Stock Price Forecasting

NASA Astrophysics Data System (ADS)

Wang, Chengzhang; Bai, Xiaoming

2018-03-01

To tackle complexity and uncertainty of stock market behavior, more studies have introduced machine learning algorithms to forecast stock price. ANN (artificial neural network) is one of the most successful and promising applications. We propose a boosting-ANN model in this paper to predict the stock close price. On the basis of boosting theory, multiple weak predicting machines, i.e. ANNs, are assembled to build a stronger predictor, i.e. boosting-ANN model. New error criteria of the weak studying machine and rules of weights updating are adopted in this study. We select technical factors from financial markets as forecasting input variables. Final results demonstrate the boosting-ANN model works better than other ones for stock price forecasting.

Do Acting out Verbs with Dolls and Comparison Learning between Scenes Boost Toddlers' Verb Comprehension?

ERIC Educational Resources Information Center

Schwarz, Amy Louise; Van Kleeck, Anne; Maguire, Mandy J.; Abdi, Herve

2017-01-01

To better understand how toddlers integrate multiple learning strategies to acquire verbs, we compared sensorimotor recruitment and comparison learning because both strategies are thought to boost children's access to scene-level information. For sensorimotor recruitment, we tested having toddlers use dolls as agents and compared this strategy…

The Pearl Side of Online Portfolios: A Descriptive Study on the Rich Experience of Using PearlTrees by Master Students of Teaching English as a Foreign Language

ERIC Educational Resources Information Center

Albaiz, Tahany

2016-01-01

Teaching English to ESL teachers is a challenging task for a number of reasons, the lack of connection between the target language and the native one being one of the most challenging factors (Ferlazzo & Sypnieski, 2013). Therefore, teachers are supposed to be innovators in creating the tools that could boost the learning process, as well as…

Improving Students' Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology.

PubMed

Dunlosky, John; Rawson, Katherine A; Marsh, Elizabeth J; Nathan, Mitchell J; Willingham, Daniel T

2013-01-01

Many students are being left behind by an educational system that some people believe is in crisis. Improving educational outcomes will require efforts on many fronts, but a central premise of this monograph is that one part of a solution involves helping students to better regulate their learning through the use of effective learning techniques. Fortunately, cognitive and educational psychologists have been developing and evaluating easy-to-use learning techniques that could help students achieve their learning goals. In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility. We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work. The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice. To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension. We attempted to provide thorough reviews for each technique, so this monograph is rather lengthy. However, we also wrote the monograph in a modular fashion, so it is easy to use. In particular, each review is divided into the following sections: General description of the technique and why it should work How general are the effects of this technique?  2a. Learning conditions  2b. Student characteristics  2c. Materials  2d. Criterion tasks Effects in representative educational contexts Issues for implementation Overall assessment The review for each technique can be read independently of the others, and particular variables of interest can be easily compared across techniques. To foreshadow our final recommendations, the techniques vary widely with respect to their generalizability and promise for improving student learning. Practice testing and distributed practice received high utility assessments because they benefit learners of different ages and abilities and have been shown to boost students' performance across many criterion tasks and even in educational contexts. Elaborative interrogation, self-explanation, and interleaved practice received moderate utility assessments. The benefits of these techniques do generalize across some variables, yet despite their promise, they fell short of a high utility assessment because the evidence for their efficacy is limited. For instance, elaborative interrogation and self-explanation have not been adequately evaluated in educational contexts, and the benefits of interleaving have just begun to be systematically explored, so the ultimate effectiveness of these techniques is currently unknown. Nevertheless, the techniques that received moderate-utility ratings show enough promise for us to recommend their use in appropriate situations, which we describe in detail within the review of each technique. Five techniques received a low utility assessment: summarization, highlighting, the keyword mnemonic, imagery use for text learning, and rereading. These techniques were rated as low utility for numerous reasons. Summarization and imagery use for text learning have been shown to help some students on some criterion tasks, yet the conditions under which these techniques produce benefits are limited, and much research is still needed to fully explore their overall effectiveness. The keyword mnemonic is difficult to implement in some contexts, and it appears to benefit students for a limited number of materials and for short retention intervals. Most students report rereading and highlighting, yet these techniques do not consistently boost students' performance, so other techniques should be used in their place (e.g., practice testing instead of rereading). Our hope is that this monograph will foster improvements in student learning, not only by showcasing which learning techniques are likely to have the most generalizable effects but also by encouraging researchers to continue investigating the most promising techniques. Accordingly, in our closing remarks, we discuss some issues for how these techniques could be implemented by teachers and students, and we highlight directions for future research. © The Author(s) 2013.

GeoMapApp Learning Activities: Grab-and-go inquiry-based geoscience activities that bring cutting-edge technology to the classroom

NASA Astrophysics Data System (ADS)

Goodwillie, A. M.; Kluge, S.

2011-12-01

NSF-funded GeoMapApp Learning Activities (http://serc.carleton.edu/geomapapp) provide self-contained learning opportunities that are centred around the principles of guided inquiry. The activities allow students to interact with and analyse research-quality geoscience data to explore and enhance student understanding of underlying geoscience content and concepts. Each activity offers ready-to-use step-by-step student instructions and answer sheets that can be downloaded from the web page. Also provided are annotated teacher versions of the worksheets that include teaching tips, additional content and suggestions for further work. Downloadable pre- and post- quizzes tied to each activity help educators gauge the learning progression of their students. Short multimedia tutorials and details on content alignment with state and national teaching standards round out the package of material that comprises each "grab-and-go" activity. GeoMapApp Learning Activities expose students to content and concepts typically found at the community college, high school and introductory undergraduate levels. The activities are based upon GeoMapApp (http://www.geomapapp.org), a free, easy-to-use map-based data exploration and visualisation tool that allows students to access a wide range of geoscience data sets in a virtual lab-like environment. Activities that have so far been created under this project include student exploration of seafloor spreading rates, a study of mass wasting as revealed through geomorphological evidence, and an analysis of plate motion and hotspot traces. The step-by-step instructions and guided inquiry approach lead students through each activity, thus reducing the need for teacher intervention whilst also boosting the time that students can spend on productive exploration and learning. The activities can be used, for example, in a classroom lab with the educator present and as self-paced assignments in an out-of-class setting. GeoMapApp Learning Activities are hosted on the SERC-Carleton web site.

Conditional Random Field (CRF)-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning

PubMed Central

Yang, Ehwa; Gwak, Jeonghwan; Jeon, Moongu

2017-01-01

Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT). In particular, online MOT is more demanding due to its diverse applications in time-critical situations. A main issue of realizing online MOT is how to associate noisy object detection results on a new frame with previously being tracked objects. In this work, we propose a multi-object tracker method called CRF-boosting which utilizes a hybrid data association method based on online hybrid boosting facilitated by a conditional random field (CRF) for establishing online MOT. For data association, learned CRF is used to generate reliable low-level tracklets and then these are used as the input of the hybrid boosting. To do so, while existing data association methods based on boosting algorithms have the necessity of training data having ground truth information to improve robustness, CRF-boosting ensures sufficient robustness without such information due to the synergetic cascaded learning procedure. Further, a hierarchical feature association framework is adopted to further improve MOT accuracy. From experimental results on public datasets, we could conclude that the benefit of proposed hybrid approach compared to the other competitive MOT systems is noticeable. PMID:28304366

Experiences of nursing undergraduates on a redesigned blended communication module: A descriptive qualitative study.

PubMed

Shorey, Shefaly; Siew, An Ling; Ang, Emily

2018-02-01

Education is going through accelerated changes to accommodate the needs of contemporary students. However, there are ongoing concerns regarding the quality of education in communication skills for nurses and other healthcare professionals. Many studies have been conducted to evaluate the effectiveness of a blended learning pedagogical tool in enhancing the learning of nursing undergraduates. However, little is known about students' experiences of a blended learning model for teaching communication skills. To explore first year nursing students' experiences of the blended learning design adopted in a communication module. A descriptive qualitative design was adopted. Data were collected in the form of written reflections from 74 first year nursing undergraduates who were enrolled in a university-affiliated nursing school. Students were asked to complete an online reflective exercise regarding an undergraduate communication module on their last day of class, and the submitted reflections were analyzed. A thematic analysis was conducted and ethics approval was obtained for this study. Six overarching themes and fifteen subthemes were generated. The six overarching themes were: 1) Helpful and engaging classroom experience, 2) valuable online activities, 3) meaningful assessment, 4) appreciation for interprofessional education, 5) personal enrichment, and 6) overall feedback and recommendations. The students in this study felt that the blended pedagogy communication module enhanced their learning and boosted their confidence in facing similar situations. Interprofessional education was well-accepted among students as they attained a deeper understanding on the importance of interprofessional learning and an appreciation towards other professionals. Blended pedagogy can be used in teaching communication skills to nursing students to provide a holistic and up-to-date learning experience. Future studies should consider engaging students in face-to-face interviews to obtain a deeper understanding on their experiences of a blended pedagogy incorporated communication module. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of photography to support the learning process of science teachers of ninth through twelfth grades in the schools of Kuwait

NASA Astrophysics Data System (ADS)

Alenizi, Abdulaziz

The purpose of the study was to investigate the relevance of teachers in Kuwait when utilizing photographic aids in the classroom. Specifically, this study assessed learning outcomes of teachers amongst high school students in schools at Kuwait. The learning outcomes were then compared with teachers who are barred from using photographic aids. The research utilized a descriptive quantitative research design. The number of participants was limited to an acceptable number in the range of 250--300. Data were collected through a questionnaire and analyses were conducted using various types of statistical designs for interpretation, specifically Spearman correlation analysis. The study revealed that visual media such as images and photographs made it easy for the students to understand the concepts of science subjects, specifically biology, physics, and chemistry. Visual media should be included in the curriculum to enhance the comprehension level of students. The government of Kuwaiti, therefore, should to encourage the use of visual aids in schools to enhance learning. The research did not indicate a capacity of skills students and teachers can employ effectively when using visual aids. There also remains a gap between possessing the skills and applying them in the school. Benefits associated with visuals aids in teaching are evident in the study. With the adoption of audio-visual methods of learning, students are presented with opportunities to develop their own ideas and opinions, thus boosting their own interpersonal skills while at the same time questioning the authenticity and relevance of the concepts at hand. The major merit of audio-visual platforms in classroom learning is they cause students to break complex science concepts into finer components that can be easily understood.

An efficient ensemble learning method for gene microarray classification.

PubMed

Osareh, Alireza; Shadgar, Bita

2013-01-01

The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

A National Partnership-Based Summer Learning Initiative to Engage Underrepresented Students with Science, Technology, Engineering and Mathematics

NASA Technical Reports Server (NTRS)

Melvin, Leland

2010-01-01

In response to the White House Educate to Innovate campaign, NASA developed a new science, technology, engineering, and mathematics (STEM) education program for non-traditional audiences that also focused on public-private partnerships and nationwide participation. NASA recognized that summer break is an often overlooked but opportune time to engage youth in STEM experiences, and elevated its ongoing commitment to the cultivation of diversity. The Summer of Innovation (SoI) is the resulting initiative that uses NASA's unique missions and resources to boost summer learning, particularly for students who are underrepresented, underserved and underperforming in STEM. The SoI pilot, launched in June 2010, is a multi-faceted effort designed to improve STEM teaching and learning through partnership, multi-week summer learning programs, special events, a national concluding event, and teacher development. The SoI pilot features strategic infusion of NASA content and educational resource materials, sustainability through STEM Learning Communities, and assessments of effectiveness of SoI interventions with other pilot efforts. This paper examines the inception and development of the Summer of Innovation pilot project, including achievements and effectiveness, as well as lessons learned for future efforts.

A qualitative study on using concept maps in problem-based learning.

PubMed

Chan, Zenobia C Y

2017-05-01

The visual arts, including concept maps, have been shown to be effective tools for facilitating student learning. However, the use of concept maps in nursing education has been under-explored. The aim of this study was to explore how students develop concept maps and what these concept maps consist of, and their views on the use of concept maps as a learning activity in a PBL class. A qualitative approach consisting of an analysis of the contents of the concept maps and interviews with students. The study was conducted in a school of nursing in a university in Hong Kong. A total of 38 students who attended the morning session (20 students) and afternoon session (18 students) respectively of a nursing problem-based learning class. The students in both the morning and afternoon classes were allocated into four groups (4-5 students per group). Each group was asked to draw two concept maps based on a given scenario, and then to participate in a follow-up interview. Two raters individually assessed the concept maps, and then discussed their views with each other. Among the concept maps that were drawn, four were selected. Their four core features of those maps were: a) the integration of informative and artistic elements; b) the delivery of sensational messages; c) the use of images rather than words; and d) three-dimensional and movable. Both raters were concerned about how informative the presentation was, the composition of the elements, and the ease of comprehension, and appreciated the three-dimensional presentation and effective use of images. From the results of the interview, the pros and cons of using concept maps were discerned. This study demonstrated how concept maps could be implemented in a PBL class to boost the students' creativity and to motivate them to learn. This study suggests the use of concept maps as an initiative to motivate student to learn, participate actively, and nurture their creativity. To conclude, this study explored an alternative way for students to make presentations and pioneered the use of art-based concept maps to facilitate student learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Student-Centered Active Learning Environment for Undergraduate Programs (SCALE-UP) Project

NASA Astrophysics Data System (ADS)

Beichner, Robert J.

2011-04-01

How do you keep a classroom of 100 undergraduates actively learning? Can students practice communication and teamwork skills in a large class? How do you boost the performance of underrepresented groups? The Student-Centered Active Learning Environment for Undergraduate Programs (SCALE-UP) Project has addressed these concerns. Because of their inclusion in a leading introductory physics textbook, project materials are used by more than 1/3 of all science, math, and engineering majors nationwide. The room design and pedagogy have been adopted at more than 100 leading institutions across the country. Physics, chemistry, math, astronomy, biology, engineering, earth sciences, and even literature classes are currently being taught this way. Educational research indicates that students should collaborate on interesting tasks and be deeply involved with the material they are studying. We promote active learning in a redesigned classroom for 100 students or more. (Of course, smaller classes can also benefit.) Class time is spent primarily on "tangibles" and "ponderables"--hands-on activities, simulations, and interesting questions. Nine students sit in three teams at round tables. Instructors circulate and engage in Socratic dialogues. The setting looks like a banquet hall, with lively interactions nearly all the time. Hundreds of hours of classroom video and audio recordings, transcripts of numerous interviews and focus groups, data from conceptual learning assessments (using widely-recognized instruments in a pretest/posttest protocol), and collected portfolios of student work are part of our rigorous assessment effort. Our findings (based on data from over 16,000 students collected over five years as well as replications at adopting sites) can be summarized as the following: 1) Female failure rate is 1/5 of previous levels, even though more is demanded of students. 2) Minority failure rate is 1/4 that seen in traditionally taught courses. 3) At-risk students are more successful in later engineering courses. 4) Top students gain the most, although students at all levels benefit. 5) Conceptual learning and problem solving are significantly improved, with same content coverage. In this talk I will discuss the need for reform, the SCALE-UP classroom environment, and examine the findings of studies of learning.

New Learning Method of a Lecture of ‘Machine Fabrication’ by Self-study with Investigation and Presentation Incorporated

NASA Astrophysics Data System (ADS)

Kasuga, Yukio

A new teaching method was developed in learning ‘machine fabrication’ for the undergraduate students. This consists of a few times of lectures, grouping, decision of industrial products which each group wants to investigate, investigation work by library books and internet, arrangement of data containing characteristics of the products, employed materials and processing methods, presentation, discussions and revision followed by another presentation. This new method is derived from one of the Finland‧s way of primary school education. Their way of education is believed to have boosted up to the top ranking in PISA tests by OECD. After starting the new way of learning, students have fresh impressions on this lesson, especially for self-study, the way of investigation, collaborate work and presentation. Also, after four years of implementation, some improvements have been made including less use of internet, and determination of products and fabricating methods in advance which should be investigated. By this, students‧ lecture assessment shows further encouraging results.

Early boost and slow consolidation in motor skill learning.

PubMed

Hotermans, Christophe; Peigneux, Philippe; Maertens de Noordhout, Alain; Moonen, Gustave; Maquet, Pierre

2006-01-01

Motorskill learning is a dynamic process that continues covertly after training has ended and eventually leads to delayed increments in performance. Current theories suggest that this off-line improvement takes time and appears only after several hours. Here we show an early transient and short-lived boost in performance, emerging as early as 5-30 min after training but no longer observed 4 h later. This early boost is predictive of the performance achieved 48 h later, suggesting its functional relevance for memory processes.

Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

PubMed

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Early Boost and Slow Consolidation in Motor Skill Learning

ERIC Educational Resources Information Center

Hotermans, Christophe; Peigneux, Philippe; de Noordhout, Alain Maertens; Moonen, Gustave; Maquet, Pierre

2006-01-01

Motor skill learning is a dynamic process that continues covertly after training has ended and eventually leads to delayed increments in performance. Current theories suggest that this off-line improvement takes time and appears only after several hours. Here we show an early transient and short-lived boost in performance, emerging as early as…

Helping geoscience students improve their numeracy using online quizzes

NASA Astrophysics Data System (ADS)

Nuttall, Anne-Marie; Stott, Tim; Sparke, Shaun

2010-05-01

This project aims to help geoscience undergraduates improve their competence and confidence in numeracy using online quizzes delivered via the Blackboard virtual learning environment. Numeracy materials are being developed based on actual examples used in a range of modules in the geoscience degree programmes taught at Liverpool John Moores University. This is to ensure the subject relevance which is considered vital to maintaining student interest & motivation. These materials are delivered as a collection of Blackboard quizzes on specific numeracy topics which students can access at any point in their studies, either on or off campus. Feedback and guidance is provided immediately so that a student gains a confidence boost if they get it right or else they can learn where they have gone wrong. It is intended that positive feedback and repetition/reinforcement will help build the confidence in numeracy which so many students seem to lack. The anonymous nature of the delivery means that students avoid the common fear of ‘asking a stupid question' in class, which can hamper their progress. The fact that students can access the quizzes anytime and from anywhere means that they can use the materials flexibly to suit their individual learning needs. In preliminary research, 70% of the students asked felt that they were expected to have greater numeracy skills than they possessed and 65% said that they would use numeracy support materials on Blackboard. Once fully developed and evaluated, the Blackboard quizzes can be opened up to other departments who may wish to use them with their own students.

Exploring the use of a Facebook page in anatomy education.

PubMed

Jaffar, Akram Abood

2014-01-01

Facebook is the most popular social media site visited by university students on a daily basis. Consequently, Facebook is the logical place to start with for integrating social media technologies into education. This study explores how a faculty-administered Facebook Page can be used to supplement anatomy education beyond the traditional classroom. Observations were made on students' perceptions and effectiveness of using the Page, potential benefits and challenges of such use, and which Insights metrics best reflect user's engagement. The Human Anatomy Education Page was launched on Facebook and incorporated into anatomy resources for 157 medical students during two academic years. Students' use of Facebook and their perceptions of the Page were surveyed. Facebook's "Insights" tool was also used to evaluate Page performance during a period of 600 days. The majority of in-class students had a Facebook account which they adopted in education. Most students perceived Human Anatomy Education Page as effective in contributing to learning and favored "self-assessment" posts. The majority of students agreed that Facebook could be a suitable learning environment. The "Insights" tool revealed globally distributed fans with considerable Page interactions. The use of a faculty-administered Facebook Page provided a venue to enhance classroom teaching without intruding into students' social life. A wider educational use of Facebook should be adopted not only because students are embracing its use, but for its inherent potentials in boosting learning. The "Insights" metrics analyzed in this study might be helpful when establishing and evaluating the performance of education-oriented Facebook Pages. © 2013 American Association of Anatomists.

RBOOST: RIEMANNIAN DISTANCE BASED REGULARIZED BOOSTING

PubMed Central

Liu, Meizhu; Vemuri, Baba C.

2011-01-01

Boosting is a versatile machine learning technique that has numerous applications including but not limited to image processing, computer vision, data mining etc. It is based on the premise that the classification performance of a set of weak learners can be boosted by some weighted combination of them. There have been a number of boosting methods proposed in the literature, such as the AdaBoost, LPBoost, SoftBoost and their variations. However, the learning update strategies used in these methods usually lead to overfitting and instabilities in the classification accuracy. Improved boosting methods via regularization can overcome such difficulties. In this paper, we propose a Riemannian distance regularized LPBoost, dubbed RBoost. RBoost uses Riemannian distance between two square-root densities (in closed form) – used to represent the distribution over the training data and the classification error respectively – to regularize the error distribution in an iterative update formula. Since this distance is in closed form, RBoost requires much less computational cost compared to other regularized Boosting algorithms. We present several experimental results depicting the performance of our algorithm in comparison to recently published methods, LP-Boost and CAVIAR, on a variety of datasets including the publicly available OASIS database, a home grown Epilepsy database and the well known UCI repository. Results depict that the RBoost algorithm performs better than the competing methods in terms of accuracy and efficiency. PMID:21927643

Reflections on clinical practice whilst developing a portfolio of evidence: Perceptions of undergraduate nursing students in the Western Cape, South Africa.

PubMed

Ticha, Victoire; Fakude, Lorraine P

2015-12-09

In order to develop clinical judgement, nurses should be encouraged to become analytical and critical thinkers. Development of a portfolio of evidence (PoE) of reflection on clinical experiences is one of the strategies that can be used to enhance analytical and critical thinking amongst nursing students. Students' perceptions of the process are important in order to encourage their reflective practice. PoE compilation at a school of nursing at a university in the Western Cape includes evidence of students' clinical learning which they present in a portfolio. The students are expected to reflect on their clinical learning experiences and include these reflections in their portfolios. To describe the perceptions of fourth-year nursing students regarding reflective practice whilst compiling their PoEs. A qualitative design was used to explore the perceptions of registered fourth-year nursing students with regard to their reflective practice whilst compiling their PoEs. Purposive sampling was used for selection of participants. Three focus group discussions were held, each consisting of six to eight participants. Data saturation was reached during the third meeting. Tesch's method of data analysis was used. Findings revealed that reflection enabled the learners to gain experience and identify challenges related to the expected events and tasks carried out at the hospitals and in the classroom whilst developing their PoE. The compilation of a PoE was a good teaching and learning strategy, and the skills, experience and knowledge that the participants in this study acquired boosted their self-esteem, confidence and critical thinking. Reflection also assisted in self-directed learning.

Characterization of medical students recall of factual knowledge using learning objects and repeated testing in a novel e-learning system.

PubMed

Taveira-Gomes, Tiago; Prado-Costa, Rui; Severo, Milton; Ferreira, Maria Amélia

2015-01-24

Spaced-repetition and test-enhanced learning are two methodologies that boost knowledge retention. ALERT STUDENT is a platform that allows creation and distribution of Learning Objects named flashcards, and provides insight into student judgments-of-learning through a metric called 'recall accuracy'. This study aims to understand how the spaced-repetition and test-enhanced learning features provided by the platform affect recall accuracy, and to characterize the effect that students, flashcards and repetitions exert on this measurement. Three spaced laboratory sessions (s0, s1 and s2), were conducted with n=96 medical students. The intervention employed a study task, and a quiz task that consisted in mentally answering open-ended questions about each flashcard and grading recall accuracy. Students were randomized into study-quiz and quiz groups. On s0 both groups performed the quiz task. On s1 and s2, the study-quiz group performed the study task followed by the quiz task, whereas the quiz group only performed the quiz task. We measured differences in recall accuracy between groups/sessions, its variance components, and the G-coefficients for the flashcard component. At s0 there were no differences in recall accuracy between groups. The experiment group achieved a significant increase in recall accuracy that was superior to the quiz group in s1 and s2. In the study-quiz group, increases in recall accuracy were mainly due to the session, followed by flashcard factors and student factors. In the quiz group, increases in recall accuracy were mainly accounted by flashcard factors, followed by student and session factors. The flashcard G-coefficient indicated an agreement on recall accuracy of 91% in the quiz group, and of 47% in the study-quiz group. Recall accuracy is an easily collectible measurement that increases the educational value of Learning Objects and open-ended questions. This metric seems to vary in a way consistent with knowledge retention, but further investigation is necessary to ascertain the nature of such relationship. Recall accuracy has educational implications to students and educators, and may contribute to deliver tailored learning experiences, assess the effectiveness of instruction, and facilitate research comparing blended-learning interventions.

Explaining Charter School Effectiveness. NBER Working Paper No. 17332

ERIC Educational Resources Information Center

Angrist, Joshua D.; Pathak, Parag A.; Walters, Christopher R.

2011-01-01

Estimates using admissions lotteries suggest that urban charter schools boost student achievement, while charter schools in other settings do not. We explore student-level and school-level explanations for these differences using a large sample of Massachusetts charter schools. Our results show that urban charter schools boost achievement well…

Robust boosting via convex optimization

NASA Astrophysics Data System (ADS)

Rätsch, Gunnar

2001-12-01

In this work we consider statistical learning problems. A learning machine aims to extract information from a set of training examples such that it is able to predict the associated label on unseen examples. We consider the case where the resulting classification or regression rule is a combination of simple rules - also called base hypotheses. The so-called boosting algorithms iteratively find a weighted linear combination of base hypotheses that predict well on unseen data. We address the following issues: o The statistical learning theory framework for analyzing boosting methods. We study learning theoretic guarantees on the prediction performance on unseen examples. Recently, large margin classification techniques emerged as a practical result of the theory of generalization, in particular Boosting and Support Vector Machines. A large margin implies a good generalization performance. Hence, we analyze how large the margins in boosting are and find an improved algorithm that is able to generate the maximum margin solution. o How can boosting methods be related to mathematical optimization techniques? To analyze the properties of the resulting classification or regression rule, it is of high importance to understand whether and under which conditions boosting converges. We show that boosting can be used to solve large scale constrained optimization problems, whose solutions are well characterizable. To show this, we relate boosting methods to methods known from mathematical optimization, and derive convergence guarantees for a quite general family of boosting algorithms. o How to make Boosting noise robust? One of the problems of current boosting techniques is that they are sensitive to noise in the training sample. In order to make boosting robust, we transfer the soft margin idea from support vector learning to boosting. We develop theoretically motivated regularized algorithms that exhibit a high noise robustness. o How to adapt boosting to regression problems? Boosting methods are originally designed for classification problems. To extend the boosting idea to regression problems, we use the previous convergence results and relations to semi-infinite programming to design boosting-like algorithms for regression problems. We show that these leveraging algorithms have desirable theoretical and practical properties. o Can boosting techniques be useful in practice? The presented theoretical results are guided by simulation results either to illustrate properties of the proposed algorithms or to show that they work well in practice. We report on successful applications in a non-intrusive power monitoring system, chaotic time series analysis and a drug discovery process. --- Anmerkung: Der Autor ist Träger des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2001/2002. In dieser Arbeit werden statistische Lernprobleme betrachtet. Lernmaschinen extrahieren Informationen aus einer gegebenen Menge von Trainingsmustern, so daß sie in der Lage sind, Eigenschaften von bisher ungesehenen Mustern - z.B. eine Klassenzugehörigkeit - vorherzusagen. Wir betrachten den Fall, bei dem die resultierende Klassifikations- oder Regressionsregel aus einfachen Regeln - den Basishypothesen - zusammengesetzt ist. Die sogenannten Boosting Algorithmen erzeugen iterativ eine gewichtete Summe von Basishypothesen, die gut auf ungesehenen Mustern vorhersagen. Die Arbeit behandelt folgende Sachverhalte: o Die zur Analyse von Boosting-Methoden geeignete Statistische Lerntheorie. Wir studieren lerntheoretische Garantien zur Abschätzung der Vorhersagequalität auf ungesehenen Mustern. Kürzlich haben sich sogenannte Klassifikationstechniken mit großem Margin als ein praktisches Ergebnis dieser Theorie herausgestellt - insbesondere Boosting und Support-Vektor-Maschinen. Ein großer Margin impliziert eine hohe Vorhersagequalität der Entscheidungsregel. Deshalb wird analysiert, wie groß der Margin bei Boosting ist und ein verbesserter Algorithmus vorgeschlagen, der effizient Regeln mit maximalem Margin erzeugt. o Was ist der Zusammenhang von Boosting und Techniken der konvexen Optimierung? Um die Eigenschaften der entstehenden Klassifikations- oder Regressionsregeln zu analysieren, ist es sehr wichtig zu verstehen, ob und unter welchen Bedingungen iterative Algorithmen wie Boosting konvergieren. Wir zeigen, daß solche Algorithmen benutzt werden koennen, um sehr große Optimierungsprobleme mit Nebenbedingungen zu lösen, deren Lösung sich gut charakterisieren laesst. Dazu werden Verbindungen zum Wissenschaftsgebiet der konvexen Optimierung aufgezeigt und ausgenutzt, um Konvergenzgarantien für eine große Familie von Boosting-ähnlichen Algorithmen zu geben. o Kann man Boosting robust gegenüber Meßfehlern und Ausreissern in den Daten machen? Ein Problem bisheriger Boosting-Methoden ist die relativ hohe Sensitivität gegenüber Messungenauigkeiten und Meßfehlern in der Trainingsdatenmenge. Um dieses Problem zu beheben, wird die sogenannte 'Soft-Margin' Idee, die beim Support-Vector Lernen schon benutzt wird, auf Boosting übertragen. Das führt zu theoretisch gut motivierten, regularisierten Algorithmen, die ein hohes Maß an Robustheit aufweisen. o Wie kann man die Anwendbarkeit von Boosting auf Regressionsprobleme erweitern? Boosting-Methoden wurden ursprünglich für Klassifikationsprobleme entwickelt. Um die Anwendbarkeit auf Regressionsprobleme zu erweitern, werden die vorherigen Konvergenzresultate benutzt und neue Boosting-ähnliche Algorithmen zur Regression entwickelt. Wir zeigen, daß diese Algorithmen gute theoretische und praktische Eigenschaften haben. o Ist Boosting praktisch anwendbar? Die dargestellten theoretischen Ergebnisse werden begleitet von Simulationsergebnissen, entweder, um bestimmte Eigenschaften von Algorithmen zu illustrieren, oder um zu zeigen, daß sie in der Praxis tatsächlich gut funktionieren und direkt einsetzbar sind. Die praktische Relevanz der entwickelten Methoden wird in der Analyse chaotischer Zeitreihen und durch industrielle Anwendungen wie ein Stromverbrauch-Überwachungssystem und bei der Entwicklung neuer Medikamente illustriert.

Parental involvement and association with adolescents' fruit and vegetable intake at follow-up: Process evaluation results from the multi-component school-based Boost intervention.

PubMed

Jørgensen, Sanne Ellegård; Jørgensen, Thea Suldrup; Aarestrup, Anne Kristine; Due, Pernille; Krølner, Rikke

2016-10-26

Based on the assumption of parental influence on adolescent behavior, multicomponent school-based dietary interventions often include a parental component. The effect of this intervention component is seldom reported and the evidence is inconsistent. We conducted a systematic process evaluation of the parental component and examined whether the leveal of parental involvement in a large multi-component intervention: the Boost study was associated with adolescents' fruit and vegetable (FV) intake at follow-up. The Boost study was targeting FV intake among 1,175 Danish 7 th graders (≈13- year-olds) in the school year 2010/11. The study included a school component: free FV in class and curricular activities; a local community component: fact sheets for sports- and youth clubs; and a parental component: presentation of Boost at a parent-school meeting, 6 newsletters to parents, 3 guided student-parent curricular activities, and a student-parent Boost event. Students whose parent replied to the follow-up survey (n = 347). Questionnaire data from students, parents and teachers at 20 intervention schools. Process evaluation measures: dose delivered, dose received, appreciation and level of parental involvement. Parental involvement was trichotomized into: low/no (0-2 points), medium (3 points) and high (4-6 points). The association between level of parental involvement and self-reported FV intake (24-h recall), was analyzed using multilevel regression analyses. The Boost study was presented at a parent-school meeting at all intervention schools. The dose delivered was low to moderate for the three other parental elements. Most parents appreciated the intervention and talked with their child about Boost (83.5 %). High, medium and low parental involvement was found among 30.5 %, 29.6 % and 39.4 % of the students respectively. Parental involvement was highest among women. More men agreed that the parental newsletters provided new information. Students with a medium and high level of parental involvement ate 47.5 and 95.2 g more FV per day compared to students with low level/no parental involvement (p = 0.02). Students with a high level of parental involvement ate significantly more FV at follow-up compared to students with a low level/no parental involvement. Parental involvement in interventions may improve adolescents' FV intake if challenges of implementation can be overcome. ISRCTN11666034 . Registered 06/01/2012. Retrospectively registered.

Using standardized patients versus video cases for representing clinical problems in problem-based learning

PubMed Central

2016-01-01

Purpose: The quality of problem representation is critical for developing students’ problem-solving abilities in problem-based learning (PBL). This study investigates preclinical students’ experience with standardized patients (SPs) as a problem representation method compared to using video cases in PBL. Methods: A cohort of 99 second-year preclinical students from Inje University College of Medicine (IUCM) responded to a Likert scale questionnaire on their learning experiences after they had experienced both video cases and SPs in PBL. The questionnaire consisted of 14 items with eight subcategories: problem identification, hypothesis generation, motivation, collaborative learning, reflective thinking, authenticity, patient-doctor communication, and attitude toward patients. Results: The results reveal that using SPs led to the preclinical students having significantly positive experiences in boosting patient-doctor communication skills; the perceived authenticity of their clinical situations; development of proper attitudes toward patients; and motivation, reflective thinking, and collaborative learning when compared to using video cases. The SPs also provided more challenges than the video cases during problem identification and hypotheses generation. Conclusion: SPs are more effective than video cases in delivering higher levels of authenticity in clinical problems for PBL. The interaction with SPs engages preclinical students in deeper thinking and discussion; growth of communication skills; development of proper attitudes toward patients; and motivation. Considering the higher cost of SPs compared with video cases, SPs could be used most advantageously during the preclinical period in the IUCM curriculum. PMID:26923094

Time Series Forecasting of Daily Reference Evapotranspiration by Neural Network Ensemble Learning for Irrigation System

NASA Astrophysics Data System (ADS)

Manikumari, N.; Murugappan, A.; Vinodhini, G.

2017-07-01

Time series forecasting has gained remarkable interest of researchers in the last few decades. Neural networks based time series forecasting have been employed in various application areas. Reference Evapotranspiration (ETO) is one of the most important components of the hydrologic cycle and its precise assessment is vital in water balance and crop yield estimation, water resources system design and management. This work aimed at achieving accurate time series forecast of ETO using a combination of neural network approaches. This work was carried out using data collected in the command area of VEERANAM Tank during the period 2004 - 2014 in India. In this work, the Neural Network (NN) models were combined by ensemble learning in order to improve the accuracy for forecasting Daily ETO (for the year 2015). Bagged Neural Network (Bagged-NN) and Boosted Neural Network (Boosted-NN) ensemble learning were employed. It has been proved that Bagged-NN and Boosted-NN ensemble models are better than individual NN models in terms of accuracy. Among the ensemble models, Boosted-NN reduces the forecasting errors compared to Bagged-NN and individual NNs. Regression co-efficient, Mean Absolute Deviation, Mean Absolute Percentage error and Root Mean Square Error also ascertain that Boosted-NN lead to improved ETO forecasting performance.

Generating highly accurate prediction hypotheses through collaborative ensemble learning

NASA Astrophysics Data System (ADS)

Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

2017-03-01

Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination.

The most enjoyable way to learn the periodic table

NASA Astrophysics Data System (ADS)

Gümüşsoy, Verim; Kaya, Mustafa

2017-04-01

Constructivist learning allows students to be actively involved in the learning process and thus the learning to be permanent. It makes the lesson more interesting and enjoyable compared to classical learning where students are passive and get bored quickly. When students engage in activities during the learning process, they enjoy it more. And there is no doubt that games help this a lot. In this project, a game has been designed to make it more entertaining to learn the periodical table for the students. In this game, a huge periodical table (with empty columns) is drawn with acrylic paint in the school yard. Acrylic paint is preferred because it is resilient to outdoor conditions, quick drying and relatively durable. Besides its functionality in the game, the presence of the huge periodical table in the yard boosts students' motivation for scientific activities. Students are taught about the periodical table in their Chemistry lesson a week before the game is to be played. They are informed about the game and asked to bring some sportswear to wear during the game. On the game day, the class is divided into teams of five people. Each team wears a different color vest and is called by the color of the vest they are wearing. The starting point is drawn as far as possible from the periodical table. Furthermore, some question cards that cover the subject are used in the game. As an example from the game: one student from each team is asked to find the correct place by the atomic number of a certain element as described in the cards given to them. There is a time limit so the stopwatch is started as each student starts reading the information on the card. The student runs to the correct place of the certain element according to the clues on their given card. Then they stop and raise their hands. The teacher stops the stopwatch for that student. The teams gain points according to their speed and correct guesses. The game continues as other students are given different question cards and asked to follow same directions. In the end, the winning team is awarded. The game contains both short term goals, like allowing students to acquire the aimed learning outcome in a permanent way while having fun, and long term goals, like increasing the motivation toward the lesson and school and gaining team awareness.

AveBoost2: Boosting for Noisy Data

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.

2004-01-01

AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the pre- vious base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. In previous work, we developed an algorithm, AveBoost, that constructed distributions orthogonal to the mistake vectors of all the previous models, and then averaged them to create the next base model s distribution. Our experiments demonstrated the superior accuracy of our approach. In this paper, we slightly revise our algorithm to allow us to obtain non-trivial theoretical results: bounds on the training error and generalization error (difference between training and test error). Our averaging process has a regularizing effect which, as expected, leads us to a worse training error bound for our algorithm than for AdaBoost but a superior generalization error bound. For this paper, we experimented with the data that we used in both as originally supplied and with added label noise-a small fraction of the data has its original label changed. Noisy data are notoriously difficult for AdaBoost to learn. Our algorithm's performance improvement over AdaBoost is even greater on the noisy data than the original data.

Boosting instance prototypes to detect local dermoscopic features.

PubMed

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

Teaching Plate Tectonic Concepts using GeoMapApp Learning Activities

NASA Astrophysics Data System (ADS)

Goodwillie, A. M.; Kluge, S.

2012-12-01

GeoMapApp Learning Activities ( http://serc.carleton.edu/geomapapp/collection.html ) can help educators to expose undergraduate students to a range of earth science concepts using high-quality data sets in an easy-to-use map-based interface called GeoMapApp. GeoMapApp Learning Activities require students to interact with and analyse research-quality geoscience data as a means to explore and enhance their understanding of underlying content and concepts. Each activity is freely available through the SERC-Carleton web site and offers step-by-step student instructions and answer sheets. Also provided are annotated educator versions of the worksheets that include teaching tips, additional content and suggestions for further work. The activities can be used "off-the-shelf". Or, since the educator may require flexibility to tailor the activities, the documents are provided in Word format for easy modification. Examples of activities include one on the concept of seafloor spreading that requires students to analyse global seafloor crustal age data to calculate spreading rates in different ocean basins. Another activity has students explore hot spots using radiometric age dating of rocks along the Hawaiian-Emperor seamount chain. A third focusses upon the interactive use of contours and profiles to help students visualise 3-D topography on 2-D computer screens. A fourth activity provides a study of mass wasting as revealed through geomorphological evidence. The step-by-step instructions and guided inquiry approach reduce the need for teacher intervention whilst boosting the time that students can spend on productive exploration and learning. The activities can be used, for example, in a classroom lab with the educator present and as self-paced assignments in an out-of-class setting. GeoMapApp Learning Activities are funded through the NSF GeoEd program and are aimed at students in the introductory undergraduate, community college and high school levels. The activities are based upon GeoMapApp (http://www.geomapapp.org), a free map-based data exploration and visualisation tool that allows students to access a wide range of geoscience data in a virtual lab-like environment.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

PubMed

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming distance using the learned binary representation. A boosting algorithm is presented to efficiently learn the distance function. We evaluate the proposed algorithm on a mammographic image reference library with an Interactive Search-Assisted Decision Support (ISADS) system and on the medical image data set from ImageCLEF. Our results show that the boosting framework compares favorably to state-of-the-art approaches for distance metric learning in retrieval accuracy, with much lower computational cost. Additional evaluation with the COREL collection shows that our algorithm works well for regular image data sets.

Boosting the Numbers of STEM Majors? the Role of High Schools with a STEM Program

ERIC Educational Resources Information Center

Bottia, Martha Cecilia; Stearns, Elizabeth; Mickelson, Roslyn Arlin; Moller, Stephanie

2018-01-01

This article investigates whether attending a high school that offers a specialized science, technology, engineering, and/or mathematics program (high school with a STEM program) boosts the number of students majoring in STEM when they are in college. We use a longitudinal sample of students in North Carolina, whom we follow from middle school…

Degrees of Difficulty: Boosting College Success in New York City

ERIC Educational Resources Information Center

Hilliard, Tom

2017-01-01

This report, the latest in a series of studies by the Center for an Urban Future examining opportunities to expand economic mobility in New York City, takes an in-depth look at college readiness and success among the city's public high school students. It explores opportunities to dramatically boost the rate at which New York City's students enter…

Memory Boost from Spaced-Out Learning.

ERIC Educational Resources Information Center

Bower, B.

1987-01-01

Discusses what learning conditions promote memory stamina. Reviews study findings which suggested that spacing of practice during rote learning of a foreign language vocabulary can produce lasting memories. (ML)

The effects of academic literacy instruction on engagement and conceptual understanding of biology of ninth-grade students

NASA Astrophysics Data System (ADS)

Larson, Susan C.

Academic language, discourse, vocabulary, motivation, and comprehension of complex texts and concepts are keys to learning subject-area content. The need for a disciplinary literacy approach in high school classrooms accelerates as students become increasing disengaged in school and as content complexity increases. In the present quasi-experimental mixed-method study, a ninth-grade biology unit was designed with an emphasis on promoting academic literacy skills, discourse, meaningful constructivist learning, interest development, and positive learning experiences in order to learn science content. Quantitative and qualitative analyses on a variety of measures completed by 222 students in two high schools revealed that those who received academic literacy instruction in science class performed at significantly higher levels of conceptual understanding of biology content, academic language and vocabulary use, reasoned thought, engagement, and quality of learning experience than control-group students receiving traditionally-organized instruction. Academic literacy was embedded into biology instruction to engage students in meaning-making discourses of science to promote learning. Academic literacy activities were organized according the phases of interest development to trigger and sustain interest and goal-oriented engagement throughout the unit. Specific methods included the Generative Vocabulary Matrix (GVM), scenario-based writing, and involvement in a variety of strategically-placed discourse activities to sustain or "boost" engagement for learning. Traditional instruction for the control group included teacher lecture, whole-group discussion, a conceptual organizer, and textbook reading. Theoretical foundations include flow theory, sociocultural learning theory, and interest theory. Qualitative data were obtained from field notes and participants' journals. Quantitative survey data were collected and analyzed using the Experience Sampling Method (ESM) to measure cognitive and emotional states, revealing patterns of engagement, quality of experience, and flow over the course of the instructional unit. Conceptual understanding was measured using the state persuasive writing rubric to analyze science essays in which students supported a claim with scientific evidence. The study contributes an Engagement Model of Academic Literacy for Learning (EngageALL), a Rubric for Academic Persuasive Writing (RAPW), a unique classification system for analyzing academic vocabulary, and suggestions for situated professional development around a research-based planning framework. A discussion addresses a new direction for future research that explores academic identity development.

Investigating the Role of an Inquiry-Based Biology Lab Course on Student Attitudes and Views toward Science

PubMed Central

Jeffery, Erica; Nomme, Kathy; Deane, Thomas; Pollock, Carol; Birol, Gülnur

2016-01-01

Students’ academic experiences can influence their conceptualization of science. In contrast experts hold particular beliefs, perceptions, opinions, and attitudes about science that are often absent in first-year undergraduate students. Shifts toward more expert-like attitudes and views have been linked to improved student engagement, critical-thinking ability, conceptual understanding, and academic performance. In this study, we investigate shifts in attitudes and views toward science by students in four biology classes with differences in student enrollment, academic support, and instruction. We observe significant, positive effects of enrollment in a guided-inquiry lab course and academic performance on the percentage of expert-like student attitudes and views at the end of term. We also identify variation in two aspects of student attitudes and views: 1) confidence and interest and 2) understanding and acceptance. In particular, enrollment in the lab course boosts student confidence and interest in scientific inquiry in the short term, even for students with low academic performance or little English-language experience. Our results suggest that low-performing students in particular may require additional opportunities for experiential learning or greater academic support to develop expert-like perceptions of biology as a science. PMID:27856549

Industrial Assessment Center Helps Boost Efficiency for Small and Medium Manufacturers

ScienceCinema

Johnson, Mark; Friedman, David

2018-06-12

The Industrial Assessment Center program helps small and medium manufacturers boost efficiency and save energy. It pairs companies with universities as students perform energy assessments and provide recommendations to improve their facilities.

Industrial Assessment Center Helps Boost Efficiency for Small and Medium Manufacturers

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

Johnson, Mark; Friedman, David

The Industrial Assessment Center program helps small and medium manufacturers boost efficiency and save energy. It pairs companies with universities as students perform energy assessments and provide recommendations to improve their facilities.

Actively Encouraging Learning and Degree Persistence in Advanced Astrophysics Courses

NASA Astrophysics Data System (ADS)

McIntosh, Daniel H.

2018-01-01

The need to grow and diversify the STEM workforce remains a critical national challenge. Less than 40% of college students interested in STEM achieve a bachelor's degree. These numbers are even more dire for women and URMs, underscoring a serious concern about the country's ability to remain competitive in science and tech. A major factor is persistent performance gaps in rigorous 'gateway' and advanced STEM courses for majors from diverse backgrounds leading to discouragement, a sense of exclusion, and high dropout rates. Education research has clearly demonstrated that interactive-engagement (`active learning') strategies increase performance, boost confidence, and help build positive 'identity' in STEM. Likewise, the evidence shows that traditional science education practices do not help most students gain a genuine understanding of concepts nor the necessary skill set to succeed in their disciplines. Yet, lecture-heavy courses continue to dominate the higher-ed curriculum, thus, reinforcing the tired notion that only a small percentage of 'special' students have the inherent ability to achieve a STEM degree. In short, very capable students with less experience and confidence in science, who belong to groups that traditionally are less identified with STEM careers, are effectively and efficiently 'weeded out' by traditional education practices. I will share specific examples for how I successfully incorporate active learning in advanced astrophysics courses to encourage students from all backgrounds to synthesize complex ideas, build bedrock conceptual frameworks, gain technical communication skills, and achieve mastery learning outcomes all necessary to successfully complete rigorous degrees like astrophysics. By creating an inclusive and active learning experience in junior-level extragalactic and stellar interiors/atmospheres courses, I am helping students gain fluency in their chosen major and the ability to 'think like a scientist', both critical to improving STEM degree retention and degree-completion rates. My long-term mission is to see STEM degree programs at U.S. colleges and universities adopt active learning strategies as the curricular norm. Understanding the benefits of this evidence-based best practice is a key step to increasing and diversifying the national STEM degree recipient pool.

Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm.

PubMed

Kamath, Uday; Domeniconi, Carlotta; De Jong, Kenneth

2018-01-01

Many real-world problems involve massive amounts of data. Under these circumstances learning algorithms often become prohibitively expensive, making scalability a pressing issue to be addressed. A common approach is to perform sampling to reduce the size of the dataset and enable efficient learning. Alternatively, one customizes learning algorithms to achieve scalability. In either case, the key challenge is to obtain algorithmic efficiency without compromising the quality of the results. In this article we discuss a meta-learning algorithm (PSBML) that combines concepts from spatially structured evolutionary algorithms (SSEAs) with concepts from ensemble and boosting methodologies to achieve the desired scalability property. We present both theoretical and empirical analyses which show that PSBML preserves a critical property of boosting, specifically, convergence to a distribution centered around the margin. We then present additional empirical analyses showing that this meta-level algorithm provides a general and effective framework that can be used in combination with a variety of learning classifiers. We perform extensive experiments to investigate the trade-off achieved between scalability and accuracy, and robustness to noise, on both synthetic and real-world data. These empirical results corroborate our theoretical analysis, and demonstrate the potential of PSBML in achieving scalability without sacrificing accuracy.

Boosting physics education through mobile augmented reality

NASA Astrophysics Data System (ADS)

Crǎciun, Dana; Bunoiu, Mǎdǎlin

2017-12-01

The integration of collaborative applications, based on modern learning technologies and the Internet, of various visualization techniques and digital strategies in open, flexible modern learning environments which facilitate access to resources, represents a challenge for physics teachers in Romania in general, and for novice teachers in particular. Although large efforts have been made worldwide to invest in educational technologies, their impact on the students' learning outcomes is quite modest. In this paper, we describe and analyze various curricular and extracurricular activities specifically designed for and undertaken by pre-service physics teachers. These activities employ new educational technologies, mobile augmented reality (MAR) and are based on modern teaching and learning theories. MAR is an extension for mobile devices of augmented reality, an interactive and in real time combination, of real and virtual objects overlaid in the real environment. The obtained results show that pre-service physics teachers are confident in using MAR in their teaching and learning activities, and consider that the activities performed helped them develop the skills necessary for science teachers in a technology-based society and to reflect upon the role of technology in the current Romanian educational context.

Computer-Tailored Student Support in Introductory Physics.

PubMed

Huberth, Madeline; Chen, Patricia; Tritz, Jared; McKay, Timothy A

2015-01-01

Large introductory courses are at a disadvantage in providing personalized guidance and advice for students during the semester. We introduce E2Coach (an Expert Electronic Coaching system), which allows instructors to personalize their communication with thousands of students. We describe the E2Coach system, the nature of the personalized support it provides, and the features of the students who did (and did not) opt-in to using it during the first three terms of its use in four introductory physics courses at the University of Michigan. Defining a 'better-than-expected' measure of performance, we compare outcomes for students who used E2Coach to those who did not. We found that moderate and high E2Coach usage was associated with improved performance. This performance boost was prominent among high users, who improved by 0.18 letter grades on average when compared to nonusers with similar incoming GPAs. This improvement in performance was comparable across both genders. E2Coach represents one way to use technology to personalize education at scale, contributing to the move towards individualized learning that is becoming more attainable in the 21st century.

Reading Quizzes Improve Exam Scores for Community College Students.

PubMed

Pape-Lindstrom, Pamela; Eddy, Sarah; Freeman, Scott

2018-06-01

To test the hypothesis that adding course structure may encourage self-regulated learning skills resulting in an increase in student exam performance in the community college setting, we added daily preclass online, open-book reading quizzes to an introductory biology course. We compared three control terms without reading quizzes and three experimental terms with online, open-book reading quizzes; the instructor of record, class size, and instructional time did not vary. Analyzing the Bloom's taxonomy level of a random sample of exam questions indicated a similar cognitive level of high-stakes assessments across all six terms in the study. To control for possible changes in student preparation or ability over time, we calculated each student's grade point average in courses other than biology during the term under study and included it as a predictor variable in our regression models. Our final model showed that students in the experimental terms had significantly higher exam scores than students in the control terms. This result shows that online reading quizzes can boost achievement in community college students. We also comment on the importance of discipline-based education research in community college settings and the structure of our community college/4-year institution collaboration.

What Every Worker Wants? Evidence about Employee Demand for Learning

ERIC Educational Resources Information Center

Findlay, Jeanette; Findlay, Patricia; Warhurst, Chris

2012-01-01

In order to boost learning, recent UK governments have invested in trade union-led workplace learning. Investing in the supply of learning is useful but ignores the demand for learning by workers, about which there is little research. This paper addresses this lacunae by analysing worker demand for learning, which workers want learning, what…

The effectiveness of mentoring speech and language pathology students when they face patients with cleft palate.

PubMed

Pamplona, María del Carmen; Ysunza, Pablo Antonio; Sarre, Pilar; Morales, Santiago; Sterling, Mariana

2015-10-01

Mentoring programs can boost Speech & Language (SL) pathologists' satisfaction about their clinical skills, increasing their professional competence. A quality induction program provides a bridge for an efficient and comfortable transition between theoretical knowledge and clinical practice in front of clients. This transition can be especially difficult when the SL pathologist confronts patients with cleft palate. To study whether a mentoring program can improve SL Pathology students' performance for treating patients with cleft palate. 18 SL Pathology students coursing the third year of a SL Pathology graduate program volunteered for participating in the study. The students were divided in two groups. All SL students from both groups were equally supervised. The students were followed for two semesters during their participation in the SL Pathology intervention for patients with cleft palate. The only difference between the students from each group was that one group (active group) was mentored by an experienced SLP who had previously received specific training to become a mentor. All SL students were assessed at the onset and at the end of the study. The assessment was performed through an analysis according to a previously validated scale (Learning Continuum of Speech & Language pathologists). A Wilcoxon test demonstrated a significant improvement (P<0.05) in the levels of The Learning Continuum of Speech & Language Pathologists at the end of the follow-up period in both groups of students. When the levels of performance at the end were compared between groups, a Mann Whitney test demonstrated a significant difference (P<0.05). The students included in the active group who were receiving additional mentoring besides the usual clinical supervision, showed a greater improvement as compared with the students from the control group. Learning how to conduct an adequate and effective intervention in cleft palate patients from an integral stand point is not easy for SL students. The support and guidance of an experienced mentor seems to enhance self-confidence and improve students' performance confronting patients with cleft palate. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Improving semi-automated segmentation by integrating learning with active sampling

NASA Astrophysics Data System (ADS)

Huo, Jing; Okada, Kazunori; Brown, Matthew

2012-02-01

Interactive segmentation algorithms such as GrowCut usually require quite a few user interactions to perform well, and have poor repeatability. In this study, we developed a novel technique to boost the performance of the interactive segmentation method GrowCut involving: 1) a novel "focused sampling" approach for supervised learning, as opposed to conventional random sampling; 2) boosting GrowCut using the machine learned results. We applied the proposed technique to the glioblastoma multiforme (GBM) brain tumor segmentation, and evaluated on a dataset of ten cases from a multiple center pharmaceutical drug trial. The results showed that the proposed system has the potential to reduce user interaction while maintaining similar segmentation accuracy.

Cost-sensitive AdaBoost algorithm for ordinal regression based on extreme learning machine.

PubMed

Riccardi, Annalisa; Fernández-Navarro, Francisco; Carloni, Sante

2014-10-01

In this paper, the well known stagewise additive modeling using a multiclass exponential (SAMME) boosting algorithm is extended to address problems where there exists a natural order in the targets using a cost-sensitive approach. The proposed ensemble model uses an extreme learning machine (ELM) model as a base classifier (with the Gaussian kernel and the additional regularization parameter). The closed form of the derived weighted least squares problem is provided, and it is employed to estimate analytically the parameters connecting the hidden layer to the output layer at each iteration of the boosting algorithm. Compared to the state-of-the-art boosting algorithms, in particular those using ELM as base classifier, the suggested technique does not require the generation of a new training dataset at each iteration. The adoption of the weighted least squares formulation of the problem has been presented as an unbiased and alternative approach to the already existing ELM boosting techniques. Moreover, the addition of a cost model for weighting the patterns, according to the order of the targets, enables the classifier to tackle ordinal regression problems further. The proposed method has been validated by an experimental study by comparing it with already existing ensemble methods and ELM techniques for ordinal regression, showing competitive results.

Going beyond a First Reader: A Machine Learning Methodology for Optimizing Cost and Performance in Breast Ultrasound Diagnosis.

PubMed

Venkatesh, Santosh S; Levenback, Benjamin J; Sultan, Laith R; Bouzghar, Ghizlane; Sehgal, Chandra M

2015-12-01

The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two independent feature sets consisting of visual features based on a radiologist's interpretation of images and computer-extracted features when used as first and second readers and combined by adaptive boosting (AdaBoost) and a pruning classifier resulted in a very high level of diagnostic performance (area under the receiver operating characteristic curve = 0.98) at a cost of pruning a fraction (20%) of the cases for further evaluation by independent methods. AdaBoost also improved the diagnostic performance of the individual human observers and increased the agreement between their analyses. Pairing AdaBoost with selective pruning is a principled methodology for achieving high diagnostic performance without the added cost of an additional reader for differentiating solid breast masses by ultrasound. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Astronomy Research Seminars

NASA Astrophysics Data System (ADS)

Genet, Russell M.

2018-06-01

Astronomy Research Seminars are offered by a rapidly growing number of community colleges and universities. Over the past decade some 120 student team research papers have been published with approximately 500 coauthors. Each team manages their own research, obtains and analyzes original data, writes a team paper, obtains an external review, submits their paper for publication, and gives a public PowerPoint presentation. The student teams are supported by: (1) an extensive community-of-practice which consists of professional and amateur astronomers, educators, and Seminar graduates; (2) the Institute for Student Astronomical Research (www.in4star.org); (3) the Small Telescope Astronomy Research Handbook and (4) an in-person/online, open-source Canvas learning management system with videos, quizzes, and other, extensive supporting material. Team research projects are completed in a semester or less and are managed by the students themselves. The Seminars have expanded from double star astronomy to asteroid astrometry, eclipsing binary times of minima, and exoplanet transits. Conducting authentic research inspires students, provides them with important skills in teamwork, project management and scientific literacy, and gives them confidence in their abilities to participate in scientific research. Being coauthors of published papers boosts student educational careers with respect to admissions and scholarships.

An Update on Statistical Boosting in Biomedicine.

PubMed

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Developing workshop module of realistic mathematics education: Follow-up workshop

NASA Astrophysics Data System (ADS)

Palupi, E. L. W.; Khabibah, S.

2018-01-01

Realistic Mathematics Education (RME) is a learning approach which fits the aim of the curriculum. The success of RME in teaching mathematics concepts, triggering students’ interest in mathematics and teaching high order thinking skills to the students will make teachers start to learn RME. Hence, RME workshop is often offered and done. This study applied development model proposed by Plomp. Based on the study by RME team, there are three kinds of RME workshop: start-up workshop, follow-up workshop, and quality boost. However, there is no standardized or validated module which is used in that workshops. This study aims to develop a module of RME follow-up workshop which is valid and can be used. Plopm’s developmental model includes materials analysis, design, realization, implementation, and evaluation. Based on the validation, the developed module is valid. While field test shows that the module can be used effectively.

Applying additive modeling and gradient boosting to assess the effects of watershed and reach characteristics on riverine assemblages

USGS Publications Warehouse

Maloney, Kelly O.; Schmid, Matthias; Weller, Donald E.

2012-01-01

Issues with ecological data (e.g. non-normality of errors, nonlinear relationships and autocorrelation of variables) and modelling (e.g. overfitting, variable selection and prediction) complicate regression analyses in ecology. Flexible models, such as generalized additive models (GAMs), can address data issues, and machine learning techniques (e.g. gradient boosting) can help resolve modelling issues. Gradient boosted GAMs do both. Here, we illustrate the advantages of this technique using data on benthic macroinvertebrates and fish from 1573 small streams in Maryland, USA.

ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches.

PubMed

Lei, Tailong; Sun, Huiyong; Kang, Yu; Zhu, Feng; Liu, Hui; Zhou, Wenfang; Wang, Zhe; Li, Dan; Li, Youyong; Hou, Tingjun

2017-11-06

Xenobiotic chemicals and their metabolites are mainly excreted out of our bodies by the urinary tract through the urine. Chemical-induced urinary tract toxicity is one of the main reasons that cause failure during drug development, and it is a common adverse event for medications, natural supplements, and environmental chemicals. Despite its importance, there are only a few in silico models for assessing urinary tract toxicity for a large number of compounds with diverse chemical structures. Here, we developed a series of qualitative and quantitative structure-activity relationship (QSAR) models for predicting urinary tract toxicity. In our study, the recursive feature elimination method incorporated with random forests (RFE-RF) was used for dimension reduction, and then eight machine learning approaches were used for QSAR modeling, i.e., relevance vector machine (RVM), support vector machine (SVM), regularized random forest (RRF), C5.0 trees, eXtreme gradient boosting (XGBoost), AdaBoost.M1, SVM boosting (SVMBoost), and RVM boosting (RVMBoost). For building classification models, the synthetic minority oversampling technique was used to handle the imbalance data set problem. Among all the machine learning approaches, SVMBoost based on the RBF kernel achieves both the best quantitative (q ext 2 = 0.845) and qualitative predictions for the test set (MCC of 0.787, AUC of 0.893, sensitivity of 89.6%, specificity of 94.1%, and global accuracy of 90.8%). The application domains were then analyzed, and all of the tested chemicals fall within the application domain coverage. We also examined the structure features of the chemicals with large prediction errors. In brief, both the regression and classification models developed by the SVMBoost approach have reliable prediction capability for assessing chemical-induced urinary tract toxicity.

Minimal groups increase young children's motivation and learning on group-relevant tasks.

PubMed

Master, Allison; Walton, Gregory M

2013-01-01

Three experiments (N = 130) used a minimal group manipulation to show that just perceived membership in a social group boosts young children's motivation for and learning from group-relevant tasks. In Experiment 1, 4-year-old children assigned to a minimal "puzzles group" persisted longer on a challenging puzzle than children identified as the "puzzles child" or children in a control condition. Experiment 2 showed that this boost in motivation occurred only when the group was associated with the task. In Experiment 3, children assigned to a minimal group associated with word learning learned more words than children assigned an analogous individual identity. The studies demonstrate that fostering shared motivations may be a powerful means by which to shape young children's academic outcomes. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Flaws in Fellowships: Institutional Support Essential to Boosting Number of African American Doctoral Students.

ERIC Educational Resources Information Center

Manzo, Kathleen Kennedy

1994-01-01

An analysis of student financial aid for African American doctoral students combines discussion of problems in student recruitment and persistence, particularly for financial reasons, with data on patterns of minority group graduate student enrollment, financial aid, debt, and degree awards. (MSE)

Enhancing Online Language Learning as a Tool to Boost Employability

ERIC Educational Resources Information Center

Escobar, Sol; Krauß, Susanne

2017-01-01

Online learning is a very flexible way to build and improve language knowledge alongside other work and/or study commitments whilst at the same time encouraging autonomous learning, time management, self-motivation and other skills relevant to employability. Learning on your own, however, can also be daunting. Therefore, the Languages for All…

Boosting Orthographic Learning during Independent Reading

ERIC Educational Resources Information Center

Nielsen, Anne-Mette Veber

2016-01-01

Research has shown that phonological decoding is critical for orthographic learning of new words during independent reading. Moreover, correlational studies have demonstrated that the strength of orthographic learning is related to the orthographic knowledge with which readers approach a text. The present training study was conducted to assess…

Boosting with Averaged Weight Vectors

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)

2002-01-01

AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the previous base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. Some researchers have pointed out the intuition that it is probably better to construct a distribution that is orthogonal to the mistake vectors of all the previous base models, but that this is not always possible. We present an algorithm that attempts to come as close as possible to this goal in an efficient manner. We present experimental results demonstrating significant improvement over AdaBoost and the Totally Corrective boosting algorithm, which also attempts to satisfy this goal.

DIRBoost-an algorithm for boosting deformable image registration: application to lung CT intra-subject registration.

PubMed

Muenzing, Sascha E A; van Ginneken, Bram; Viergever, Max A; Pluim, Josien P W

2014-04-01

We introduce a boosting algorithm to improve on existing methods for deformable image registration (DIR). The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well known in the field of machine learning. DIRBoost utilizes a method for automatic registration error detection to obtain estimates of local registration quality. All areas detected as erroneously registered are subjected to boosting, i.e. undergo iterative registrations by employing boosting masks on both the fixed and moving image. We validated the DIRBoost algorithm on three different DIR methods (ANTS gSyn, NiftyReg, and DROP) on three independent reference datasets of pulmonary image scan pairs. DIRBoost reduced registration errors significantly and consistently on all reference datasets for each DIR algorithm, yielding an improvement of the registration accuracy by 5-34% depending on the dataset and the registration algorithm employed. Copyright © 2014 Elsevier B.V. All rights reserved.

Experimental study of teaching critical thinking in civic education in Taiwanese junior high school.

PubMed

Yang, Shu Ching; Chung, Tung-Yu

2009-03-01

To effectively respond to the need for greater CT (critical thinking) in the classroom, this study examines the effects of cultivating CT skills within civic education to maximize its potential. Despite realizing the importance of CT in education, schools do not tend to apply it. Furthermore, since students frequently do not raise questions or otherwise think critically, CT modules are incorporated into civic learning to encourage students to question facts, interpret and analyse evidence, make reasoned inferences regarding events, and independently develop informed opinions. These skills are fundamental to cultivating an informed and humane citizenry. This investigation examines how teaching critical thinking in civic education affects the CT skills and disposition of junior high school students. The participants were two classes of eighth grade students in southern Taiwan, and were distributed into experimental and control groups. Each group comprised 34 students, with the experimental group containing 16 boys and 18 girls and the control group containing 18 boys and 16 girls. The teaching experiment in this study was initiated and performed using equivalent pre-test and post-test group design. During the 10-week experiment, the experimental group was taught using CT instruction in civic education, while the control group was not taught with any CT programme. The data analysis included: quantitative statistics of the two main sets of instruments for measuring the CT ability and disposition of experimental treatment, qualitative analysis of learning sheets, and surveys of student perceptions of instruction in CT. Statistical analysis showed that the experimental group significantly outperformed the control group on the scales of CT skill and disposition, but did not perform well on certain subscales (e.g. recognition of assumptions and deductions, truth-seeking, analyticity, and inquisitiveness). Notably however, when triangulating with qualitative analysis of learner transcripts and surveys, learners attempted to perform various dimensions of CT skill and disposition to various degrees. Student surveys indicated that the CT programme fostered their active listening and respect for different ideas, and moreover they learned to tolerate divergent views and examine their ideas for possible bias. The programme boosted student learning interest and sense of accomplishment, and nurtured their teamwork/communicative skills. Furthermore, a few students experienced improvements in their speaking skills and courage as their confidence and ability to express themselves improved. Finally, limitations of this investigation and implications for further research are discussed.

Computer-Tailored Student Support in Introductory Physics

PubMed Central

Huberth, Madeline; Chen, Patricia; Tritz, Jared; McKay, Timothy A.

2015-01-01

Large introductory courses are at a disadvantage in providing personalized guidance and advice for students during the semester. We introduce E2Coach (an Expert Electronic Coaching system), which allows instructors to personalize their communication with thousands of students. We describe the E2Coach system, the nature of the personalized support it provides, and the features of the students who did (and did not) opt-in to using it during the first three terms of its use in four introductory physics courses at the University of Michigan. Defining a ‘better-than-expected’ measure of performance, we compare outcomes for students who used E2Coach to those who did not. We found that moderate and high E2Coach usage was associated with improved performance. This performance boost was prominent among high users, who improved by 0.18 letter grades on average when compared to nonusers with similar incoming GPAs. This improvement in performance was comparable across both genders. E2Coach represents one way to use technology to personalize education at scale, contributing to the move towards individualized learning that is becoming more attainable in the 21st century. PMID:26352403

Introduction to Small Telescope Research Communities of Practice

NASA Astrophysics Data System (ADS)

Genet, Russell M.

2016-06-01

Communities of practice are natural, usually informal groups of people who work together. Experienced members teach new members the “ropes.” Social learning theorist Etienne Wenger’s book, Communities of Practice: Learning, Meaning, and Identity, defined the field. There are, in astronomy, many communities of practice. One set of communities uses relatively small telescopes to observe brighter objects such as eclipsing binaries, intrinsically variable stars, transiting exoplanets, tumbling asteroids, and the occultation of background stars by asteroids and the Moon. Advances in low cost but increasingly powerful instrumentation and automation have greatly increased the research capabilities of smaller telescopes. These often professional-amateur (pro-am) communities engage in research projects that require a large number of observers as exemplified by the American Association of Variable Star Observers. For high school and community college students with an interest in science, joining a student-centered, small telescope community of practice can be both educational and inspirational. An example is the now decade-long Astronomy Research Seminar offered by Cuesta College in San Luis Obispo, California. Each student team is required to plan a project, obtain observations (either locally or via a remote robotic telescope), analyze their data, write a paper, and submit it for external review and publication. Well over 100 students, composed primarily of high school juniors and seniors, have been coauthors of several dozen published papers. Being published researchers has boosted these students’ educational careers with admissions to choice schools, often with scholarships. This seminar was recently expanded to serve multiple high schools with a volunteer assistant instructor at each school. The students meet regularly with their assistant instructor and also meet online with other teams and the seminar’s overall community college instructor. The seminar features a textbook, self-paced learning units, and a website sponsored by the Institute for Student Astronomical Research.

First Fiction

ERIC Educational Resources Information Center

Adults Learning, 2008

2008-01-01

In June last year, "Adults Learning" described how a small learning centre, based in an old storeroom at a bus depot, was working to transform the workplace and the lives of its staff. To boost English learning among workers, the centre launched a short story competition. The resulting stories were collected and published in the book…

An ensemble rank learning approach for gene prioritization.

PubMed

Lee, Po-Feng; Soo, Von-Wun

2013-01-01

Several different computational approaches have been developed to solve the gene prioritization problem. We intend to use the ensemble boosting learning techniques to combine variant computational approaches for gene prioritization in order to improve the overall performance. In particular we add a heuristic weighting function to the Rankboost algorithm according to: 1) the absolute ranks generated by the adopted methods for a certain gene, and 2) the ranking relationship between all gene-pairs from each prioritization result. We select 13 known prostate cancer genes in OMIM database as training set and protein coding gene data in HGNC database as test set. We adopt the leave-one-out strategy for the ensemble rank boosting learning. The experimental results show that our ensemble learning approach outperforms the four gene-prioritization methods in ToppGene suite in the ranking results of the 13 known genes in terms of mean average precision, ROC and AUC measures.

Component Pin Recognition Using Algorithms Based on Machine Learning

NASA Astrophysics Data System (ADS)

Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

2018-04-01

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

ICTNET at Web Track 2012 Ad-hoc Task

DTIC Science & Technology

2012-11-01

Model and use it as baseline this year. 3.2 Learning to rank Learning to rank (LTR) introduces machine learning to retrieval ranking problem. It...Yoram Singer. An efficient boosting algorithm  for  combining preferences [J]. The Journal of  Machine   Learning  Research. 2003. 

Online Bagging and Boosting

NASA Technical Reports Server (NTRS)

Oza, Nikunji C.

2005-01-01

Bagging and boosting are two of the most well-known ensemble learning methods due to their theoretical performance guarantees and strong experimental results. However, these algorithms have been used mainly in batch mode, i.e., they require the entire training set to be available at once and, in some cases, require random access to the data. In this paper, we present online versions of bagging and boosting that require only one pass through the training data. We build on previously presented work by presenting some theoretical results. We also compare the online and batch algorithms experimentally in terms of accuracy and running time.

Teaching methodologies to promote creativity in the professional skills related to optics knowledge

NASA Astrophysics Data System (ADS)

Fernández-Oliveras, Alicia; Fernandez, Paz; Peña-García, Antonio; Oliveras, Maria L.

2014-07-01

We present the methodologies proposed and applied in the context of a teaching-innovation project developed at the University of Granada, Spain. The main objective of the project is the implementation of teaching methodologies that promote the creativity in the learning process and, subsequently, in the acquisition of professional skills. This project involves two subjects related with optics knowledge in undergraduate students. The subjects are "Illumination Engineering" (Bachelor's degree in Civil-Engineering) and "Optical and Optometric Instrumentation" (Bachelor's degree in and Optics and Optometry). For the first subject, the activities of our project were carried out in the theoretical classes. By contrast, in the case of the second subject, such activities were designed for the laboratory sessions. For "Illumination Engineering" we applied the maieutic technique. With this method the students were encouraged to establish relationships between the main applications of the subject and concepts that apparently unrelated with the subject framework. By means of several examples, the students became aware of the importance of cross-curricular and lateral thinking. We used the technique based on protocols of control and change in "Optical and Optometric Instrumentation". The modus operandi was focused on prompting the students to adopt the role of the professionals and to pose questions to themselves concerning the practical content of the subject from that professional role. This mechanism boosted the critical capacity and the independent-learning ability of the students. In this work, we describe in detail both subject proposals and the results of their application in the 2011-2012 academic course.

High School Student Can Be Turned On to P.E.

ERIC Educational Resources Information Center

Donovan, John; Monti, Bill

1978-01-01

The Physical Education program at San Rafael High School seeks to boost students' sense of identity and self worth by abolishing rigid rules and dress codes and allowing students to choose from elective courses. The school administration has made commitments to the program and student enrollment is increasing. (SJL)

Wilberforce Power Technology in Education Program

NASA Technical Reports Server (NTRS)

Gordon, Edward M.; Buffinger, D. R.; Hehemann, D. G.; Breen, M. L.; Raffaelle, R. P.

1999-01-01

The Wilberforce Power Technology in Education Program is a multipart program. Three key parts of this program will be described. They are: (1) WISE-The Wilberforce Summer Intensive Experience. This annual offering is an educational program which is designed to provide both background reinforcement and a focus on study skills to give the participants a boost in their academic performance throughout their academic careers. It is offered to entering Wilberforce students. Those students who take advantage of WISE learn to improve important skills which enable them to work at higher levels in mathematics, science and engineering courses throughout their college careers, but most notably in the first year of college study. (2) Apply technology to reaming. This is being done in several ways including creating an electronic chemistry text with hypertext links to a glossary to help the students deal with the large new vocabulary required to describe and understand chemistry. It is also being done by converting lecture materials for the Biochemistry class to PowerPoint format. Technology is also being applied to learning by exploring simulation software of scientific instrumentation. (3) Wilberforce participation in collaborative research with NASA's John H. Glenn Research Center at Lewis Field. This research has focused on two areas in the past year. The first of these is the deposition of solar cell materials. A second area involves the development of polymeric materials for incorporation into thin film batteries.

Boosting Long-Term Memory via Wakeful Rest: Intentional Rehearsal Is Not Necessary, Consolidation Is Sufficient

PubMed Central

Dewar, Michaela; Alber, Jessica; Cowan, Nelson; Della Sala, Sergio

2014-01-01

People perform better on tests of delayed free recall if learning is followed immediately by a short wakeful rest than by a short period of sensory stimulation. Animal and human work suggests that wakeful resting provides optimal conditions for the consolidation of recently acquired memories. However, an alternative account cannot be ruled out, namely that wakeful resting provides optimal conditions for intentional rehearsal of recently acquired memories, thus driving superior memory. Here we utilised non-recallable words to examine whether wakeful rest boosts long-term memory, even when new memories could not be rehearsed intentionally during the wakeful rest delay. The probing of non-recallable words requires a recognition paradigm. Therefore, we first established, via Experiment 1, that the rest-induced boost in memory observed via free recall can be replicated in a recognition paradigm, using concrete nouns. In Experiment 2, participants heard 30 non-recallable non-words, presented as ‘foreign names in a bridge club abroad’ and then either rested wakefully or played a visual spot-the-difference game for 10 minutes. Retention was probed via recognition at two time points, 15 minutes and 7 days after presentation. As in Experiment 1, wakeful rest boosted recognition significantly, and this boost was maintained for at least 7 days. Our results indicate that the enhancement of memory via wakeful rest is not dependent upon intentional rehearsal of learned material during the rest period. We thus conclude that consolidation is sufficient for this rest-induced memory boost to emerge. We propose that wakeful resting allows for superior memory consolidation, resulting in stronger and/or more veridical representations of experienced events which can be detected via tests of free recall and recognition. PMID:25333957

Boosting long-term memory via wakeful rest: intentional rehearsal is not necessary, consolidation is sufficient.

PubMed

Dewar, Michaela; Alber, Jessica; Cowan, Nelson; Della Sala, Sergio

2014-01-01

People perform better on tests of delayed free recall if learning is followed immediately by a short wakeful rest than by a short period of sensory stimulation. Animal and human work suggests that wakeful resting provides optimal conditions for the consolidation of recently acquired memories. However, an alternative account cannot be ruled out, namely that wakeful resting provides optimal conditions for intentional rehearsal of recently acquired memories, thus driving superior memory. Here we utilised non-recallable words to examine whether wakeful rest boosts long-term memory, even when new memories could not be rehearsed intentionally during the wakeful rest delay. The probing of non-recallable words requires a recognition paradigm. Therefore, we first established, via Experiment 1, that the rest-induced boost in memory observed via free recall can be replicated in a recognition paradigm, using concrete nouns. In Experiment 2, participants heard 30 non-recallable non-words, presented as 'foreign names in a bridge club abroad' and then either rested wakefully or played a visual spot-the-difference game for 10 minutes. Retention was probed via recognition at two time points, 15 minutes and 7 days after presentation. As in Experiment 1, wakeful rest boosted recognition significantly, and this boost was maintained for at least 7 days. Our results indicate that the enhancement of memory via wakeful rest is not dependent upon intentional rehearsal of learned material during the rest period. We thus conclude that consolidation is sufficient for this rest-induced memory boost to emerge. We propose that wakeful resting allows for superior memory consolidation, resulting in stronger and/or more veridical representations of experienced events which can be detected via tests of free recall and recognition.

Access, attitudes and training in information technologies and evidence-based medicine among medical students at University of Zimbabwe College of Health Sciences.

PubMed

Parve, Swapnil; Ershadi, Ali; Karimov, Alexandr; Dougherty, Anne; Ndhlovu, Chiratidzo E; Chidzonga, Midion M; Sadigh, Majid

2016-09-01

The Medical Education Partnership Initiative, has helped to mitigate the digital divide in Africa. The aim of the study was to assess the level of access, attitude, and training concerning meaningful use of electronic resources and EBM among medical students at an African medical school. The study involved medical students at the University of Zimbabwe College of Health Sciences, Harare. The needs assessment tool consisted of a 21-question, paper-based, voluntary and anonymous survey. A total of 61/67 (91%), responded to the survey. 60% of the medical students were 'third-year medical students'. Among medical students, 85% of responders had access to digital medical resources, but 54% still preferred printed medical textbooks. Although 25% of responders had received training in EBM, but only 7% found it adequate. 98% of the participants did not receive formal training in journal club presentation or analytical reading of medical literature, but 77 % of them showed interest in learning these skills. Lack of training in EBM, journal club presentation and analytical reading skills have limited the impact of upgraded technology in enhancing the level of knowledge. This impact can be boosted by developing a curriculum with skills necessary in using EBM.

Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

ERIC Educational Resources Information Center

Niemann, Katja; Wolpers, Martin

2015-01-01

In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

Imbalanced learning for pattern recognition: an empirical study

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Man, Hong; Desai, Sachi; Quoraishee, Shafik

2010-10-01

The imbalanced learning problem (learning from imbalanced data) presents a significant new challenge to the pattern recognition and machine learning society because in most instances real-world data is imbalanced. When considering military applications, the imbalanced learning problem becomes much more critical because such skewed distributions normally carry the most interesting and critical information. This critical information is necessary to support the decision-making process in battlefield scenarios, such as anomaly or intrusion detection. The fundamental issue with imbalanced learning is the ability of imbalanced data to compromise the performance of standard learning algorithms, which assume balanced class distributions or equal misclassification penalty costs. Therefore, when presented with complex imbalanced data sets these algorithms may not be able to properly represent the distributive characteristics of the data. In this paper we present an empirical study of several popular imbalanced learning algorithms on an army relevant data set. Specifically we will conduct various experiments with SMOTE (Synthetic Minority Over-Sampling Technique), ADASYN (Adaptive Synthetic Sampling), SMOTEBoost (Synthetic Minority Over-Sampling in Boosting), and AdaCost (Misclassification Cost-Sensitive Boosting method) schemes. Detailed experimental settings and simulation results are presented in this work, and a brief discussion of future research opportunities/challenges is also presented.

Habermas, Lifeworld and Rationality: Towards a Comprehensive Model of Lifelong Learning

ERIC Educational Resources Information Center

Regmi, Kapil Dev

2017-01-01

Major supranational organisations such as the Organisation for Economic Cooperation and Development, the European Union, and the World Bank have used lifelong learning as a strategy to boost economic competitiveness both at individual and national levels. In the literature related to lifelong learning this is characterised as the economistic model…

3 Steps, 1 Goal: Teacher Teams Boost Math Instruction Using 3-Part Learning Design

ERIC Educational Resources Information Center

Mistretta, Regina M.

2012-01-01

Teacher education and professional development prepare teachers with up-to-date knowledge, skills, and dispositions necessary for effective teaching. To sustain this, however, hinges on continued professional learning within schools. Research shows that establishing long-term conditions that allow teachers to learn continuously from one another…

Wastewater quality monitoring system using sensor fusion and machine learning techniques.

PubMed

Qin, Xusong; Gao, Furong; Chen, Guohua

2012-03-15

A multi-sensor water quality monitoring system incorporating an UV/Vis spectrometer and a turbidimeter was used to monitor the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Oil & Grease (O&G) concentrations of the effluents from the Chinese restaurant on campus and an electrocoagulation-electroflotation (EC-EF) pilot plant. In order to handle the noise and information unbalance in the fused UV/Vis spectra and turbidity measurements during the calibration model building, an improved boosting method, Boosting-Iterative Predictor Weighting-Partial Least Squares (Boosting-IPW-PLS), was developed in the present study. The Boosting-IPW-PLS method incorporates IPW into boosting scheme to suppress the quality-irrelevant variables by assigning small weights, and builds up the models for the wastewater quality predictions based on the weighted variables. The monitoring system was tested in the field with satisfactory results, underlying the potential of this technique for the online monitoring of water quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Accommodating Learning Styles in Prison Writing Classes.

ERIC Educational Resources Information Center

Glasgow, Jacqueline N.

1994-01-01

Describes a developmental writing course taught in prison. Describes how the teaching styles took into account the presumed learning preferences of the African Americans in this group of inmates and resulted in a boost of both their self-confidence and the level of their writing. (SR)

Perspectives: Prior Learning Assessment Challenges the Status Quo

ERIC Educational Resources Information Center

Boilard, Steve D.

2011-01-01

Offering some relief from a raft of reports about declining education attainment and increasing college costs, Anya Kamenetz celebrates Prior Learning Assessment (PLA) for boosting higher education productivity, access, and affordability ("Change," September/October 2011). According to Kamenetz, PLA is transforming higher education by leveraging…

Using machine learning for sequence-level automated MRI protocol selection in neuroradiology.

PubMed

Brown, Andrew D; Marotta, Thomas R

2018-05-01

Incorrect imaging protocol selection can lead to important clinical findings being missed, contributing to both wasted health care resources and patient harm. We present a machine learning method for analyzing the unstructured text of clinical indications and patient demographics from magnetic resonance imaging (MRI) orders to automatically protocol MRI procedures at the sequence level. We compared 3 machine learning models - support vector machine, gradient boosting machine, and random forest - to a baseline model that predicted the most common protocol for all observations in our test set. The gradient boosting machine model significantly outperformed the baseline and demonstrated the best performance of the 3 models in terms of accuracy (95%), precision (86%), recall (80%), and Hamming loss (0.0487). This demonstrates the feasibility of automating sequence selection by applying machine learning to MRI orders. Automated sequence selection has important safety, quality, and financial implications and may facilitate improvements in the quality and safety of medical imaging service delivery.

An analysis of high-performing science students' preparation for collegiate science courses

NASA Astrophysics Data System (ADS)

Walter, Karen

This mixed-method study surveyed first year high-performing science students who participated in high-level courses such as International Baccalaureate (IB), Advanced Placement (AP), and honors science courses in high school to determine their perception of preparation for academic success at the collegiate level. The study used 52 students from an honors college campus and surveyed the students and their professors. The students reported that they felt better prepared for academic success at the collegiate level by taking these courses in high school (p<.001). There was a significant negative correlation between perception of preparation and student GPA with honors science courses (n=55 and Pearson's r=-0.336), while AP courses (n=47 and Pearson's r=0.0016) and IB courses (n=17 and Pearson's r=-0.2716) demonstrated no correlation between perception of preparation and GPA. Students reported various themes that helped or hindered their perception of academic success once at the collegiate level. Those themes that reportedly helped students were preparedness, different types of learning, and teacher qualities. Students reported in a post-hoc experience that more lab time, rigorous coursework, better teachers, and better study techniques helped prepare them for academic success at the collegiate level. Students further reported on qualities of teachers and teaching that helped foster their academic abilities at the collegiate level, including teacher knowledge, caring, teaching style, and expectations. Some reasons for taking high-level science courses in high school include boosting GPA, college credit, challenge, and getting into better colleges.

Do They Hear You?

ERIC Educational Resources Information Center

Hattie, John; Fisher, Douglas; Frey, Nancy

2016-01-01

Although research indicates that feedback can be one of the most effective instructional strategies for improving student performance, getting students to listen and act on feedback can be complicated. If feedback is vague and personal, students may pay attention only to positive comments that are positive and boost their self-image ("That…

Concept Inventories: Predicting the Wrong Answer May Boost Performance

ERIC Educational Resources Information Center

Talanquer, Vincente

2017-01-01

Several concept inventories have been developed to elicit students' alternative conceptions in chemistry. It is suggested that heuristic reasoning may bias students' answers in these types of assessments toward intuitively appealing choices. If this is the case, one could expect students to improve their performance by engaging in more analytical…

Potential Synergy: Rural School Districts and International Student Programs

ERIC Educational Resources Information Center

Casto, Hope G.; Steinhauer, Alexandra; Pollock, Pamela M.

2012-01-01

Many rural school districts face declining enrollments. A few districts have taken the unusual path of recruiting international students in order to boost their enrollments. This study examines a community using this strategy and the resulting financial, academic, and social situations for the school, community, and students, both local and…

WWC Review of the Report "Daily Online Testing in Large Classes: Boosting College Performance While Reducing Achievement Gaps." What Works Clearinghouse Single Study Review

ERIC Educational Resources Information Center

What Works Clearinghouse, 2014

2014-01-01

The 2013 study, "Daily Online Testing in Large Classes: Boosting College Performance While Reducing Achievement Gaps," examined the impact of frequent online testing and immediate feedback on the academic performance of college students. The study was conducted at the University of Texas in the fall of 2008 and 2011. Researchers found…

Semi-Supervised Projective Non-Negative Matrix Factorization for Cancer Classification.

PubMed

Zhang, Xiang; Guan, Naiyang; Jia, Zhilong; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Advances in DNA microarray technologies have made gene expression profiles a significant candidate in identifying different types of cancers. Traditional learning-based cancer identification methods utilize labeled samples to train a classifier, but they are inconvenient for practical application because labels are quite expensive in the clinical cancer research community. This paper proposes a semi-supervised projective non-negative matrix factorization method (Semi-PNMF) to learn an effective classifier from both labeled and unlabeled samples, thus boosting subsequent cancer classification performance. In particular, Semi-PNMF jointly learns a non-negative subspace from concatenated labeled and unlabeled samples and indicates classes by the positions of the maximum entries of their coefficients. Because Semi-PNMF incorporates statistical information from the large volume of unlabeled samples in the learned subspace, it can learn more representative subspaces and boost classification performance. We developed a multiplicative update rule (MUR) to optimize Semi-PNMF and proved its convergence. The experimental results of cancer classification for two multiclass cancer gene expression profile datasets show that Semi-PNMF outperforms the representative methods.

The Impact of Technology Exposure on Student Perceptions of a 1:1 Program

ERIC Educational Resources Information Center

Stone, Jeffrey A.

2017-01-01

Many school districts across the United States have enacted one-to-one (1:1) programs to boost students' "21st Century Skills". These programs provide a laptop or other personal digital device to every student, with the expectation that teachers will employ modern instructional processes and students will benefit from greater access to…

Application of Boosting Regression Trees to Preliminary Cost Estimation in Building Construction Projects

PubMed Central

2015-01-01

Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project. PMID:26339227

Application of Boosting Regression Trees to Preliminary Cost Estimation in Building Construction Projects.

PubMed

Shin, Yoonseok

2015-01-01

Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project.

Speak, Move, Play and Learn with Children on the Autism Spectrum: Activities to Boost Communication Skills, Sensory Integration and Coordination Using Simple Ideas from Speech and Language Pathology and Occupational Therapy

ERIC Educational Resources Information Center

Brady, Lois Jean; Gonzalez, America X.; Zawadzki, Maciej; Presley, Corinda

2012-01-01

This practical resource is brimming with ideas and guidance for using simple ideas from speech and language pathology and occupational therapy to boost communication, sensory integration, and coordination skills in children on the autism spectrum. Suitable for use in the classroom, at home, and in community settings, it is packed with…

Charge It! Translating Electric Vehicle Research Results to Engage 7th and 8th Grade Girls

NASA Astrophysics Data System (ADS)

Egbue, Ona; Long, Suzanna; Ng, Ean-Harn

2015-10-01

Despite attempts to generate interest in science and technology careers, US students continue to show reduced interest in science, technology, engineering and mathematics (STEM) majors at the collegiate level. If girls are not engaged in STEM learning by the middle school level, studies show that they are even less likely to choose a science- or engineering-related major. This article presents results from a workshop for 7th and 8th grade girls designed to promote knowledge building in the area of sustainability and alternative energy use in transportation and to stimulate greater interest in STEM subjects. The workshop based on research conducted at University X focused on basic concepts of electric vehicles and electric vehicles' batteries. Tests were conducted to evaluate the students' knowledge and perceptions of electric vehicles and to determine the impact of the workshop. Early exposure to meaningful engineering experiences for these young girls may boost interest and the eventual pursuit of engineering and technology education paths.

Feedback enhances the positive effects and reduces the negative effects of multiple-choice testing.

PubMed

Butler, Andrew C; Roediger, Henry L

2008-04-01

Multiple-choice tests are used frequently in higher education without much consideration of the impact this form of assessment has on learning. Multiple-choice testing enhances retention of the material tested (the testing effect); however, unlike other tests, multiple-choice can also be detrimental because it exposes students to misinformation in the form of lures. The selection of lures can lead students to acquire false knowledge (Roediger & Marsh, 2005). The present research investigated whether feedback could be used to boost the positive effects and reduce the negative effects of multiple-choice testing. Subjects studied passages and then received a multiple-choice test with immediate feedback, delayed feedback, or no feedback. In comparison with the no-feedback condition, both immediate and delayed feedback increased the proportion of correct responses and reduced the proportion of intrusions (i.e., lure responses from the initial multiple-choice test) on a delayed cued recall test. Educators should provide feedback when using multiple-choice tests.

Cosmic string detection with tree-based machine learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-07-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9'-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

Cosmic String Detection with Tree-Based Machine Learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-05-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9΄-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

Baby and Toddler Learning Fun: 50 Interactive and Developmental Activities To Enjoy with Your Child.

ERIC Educational Resources Information Center

Goldberg, Sally

Based on the view that almost every interaction a parent has with an infant is an opportunity to help the baby learn more about the world, this book provides parents with simple and effective ways to enrich their infant's environment and to boost their childs language, motor, and social skills. Introductory remarks describe the learning areas…

Optimizing Estimated Loss Reduction for Active Sampling in Rank Learning

DTIC Science & Technology

2008-01-01

active learning framework for SVM-based and boosting-based rank learning. Our approach suggests sampling based on maximizing the estimated loss differential over unlabeled data. Experimental results on two benchmark corpora show that the proposed model substantially reduces the labeling effort, and achieves superior performance rapidly with as much as 30% relative improvement over the margin-based sampling

Inspiring Curiosity and Enthusiasm for Nonfiction: A Project Designed to Boost Students' Will to Read

ERIC Educational Resources Information Center

Meth, Jessica Matthews

2010-01-01

In her role as supervisor to middle school and high school student teachers, the author has observed dozens of students who avoid reading at every turn. She has also known frustrated teachers, daunted by the challenge of getting student readers up to speed. To better encourage a desire in students to read, she sets out to experiment with themes,…

RBoost: Label Noise-Robust Boosting Algorithm Based on a Nonconvex Loss Function and the Numerically Stable Base Learners.

PubMed

Miao, Qiguang; Cao, Ying; Xia, Ge; Gong, Maoguo; Liu, Jiachen; Song, Jianfeng

2016-11-01

AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong classifiers. However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly, improving the antinoise ability of AdaBoost plays an important role in many applications. The sensitiveness to the noisy data of AdaBoost stems from the exponential loss function, which puts unrestricted penalties to the misclassified samples with very large margins. In this paper, we propose two boosting algorithms, referred to as RBoost1 and RBoost2, which are more robust to the noisy data compared with AdaBoost. RBoost1 and RBoost2 optimize a nonconvex loss function of the classification margin. Because the penalties to the misclassified samples are restricted to an amount less than one, RBoost1 and RBoost2 do not overfocus on the samples that are always misclassified by the previous base learners. Besides the loss function, at each boosting iteration, RBoost1 and RBoost2 use numerically stable ways to compute the base learners. These two improvements contribute to the robustness of the proposed algorithms to the noisy training and testing samples. Experimental results on the synthetic Gaussian data set, the UCI data sets, and a real malware behavior data set illustrate that the proposed RBoost1 and RBoost2 algorithms perform better when the training data sets contain noisy data.

Accelerating atomistic simulations through self-learning bond-boost hyperdynamics

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

Perez, Danny; Voter, Arthur F

2008-01-01

By altering the potential energy landscape on which molecular dynamics are carried out, the hyperdynamics method of Voter enables one to significantly accelerate the simulation state-to-state dynamics of physical systems. While very powerful, successful application of the method entails solving the subtle problem of the parametrization of the so-called bias potential. In this study, we first clarify the constraints that must be obeyed by the bias potential and demonstrate that fast sampling of the biased landscape is key to the obtention of proper kinetics. We then propose an approach by which the bond boost potential of Miron and Fichthorn canmore » be safely parametrized based on data acquired in the course of a molecular dynamics simulation. Finally, we introduce a procedure, the Self-Learning Bond Boost method, in which the parametrization is step efficiently carried out on-the-fly for each new state that is visited during the simulation by safely ramping up the strength of the bias potential up to its optimal value. The stability and accuracy of the method are demonstrated.« less

Play: Ten Power Boosts for Children's Early Learning

ERIC Educational Resources Information Center

Honig, Alice

2007-01-01

Play is children's work. Alice Honig enumerates from the heart 10 ways in which children learn through play, including building dexterity; social skills; cognitive and language skills; number and time concepts; spatial understanding; reasoning of cause and effect; clarification of pretend versus real; sensory and aesthetic appreciation; extended…

Net Results: Online Protocols Boost Group Learning Potential

ERIC Educational Resources Information Center

Dichter, Alan; Zydney, Janet Mannheimer

2015-01-01

Educators have begun to use protocols to facilitate professional development in online spaces--partly because people need to connect from different places, but also to take advantage of new environments for learning. For example, asynchronous tools, such as discussion forums, blogs, or Google+, where participants post messages to one another at…

Learning and Therapy--Oppositional or Complementary Processes?

ERIC Educational Resources Information Center

Hyland, Terry

2005-01-01

The idea that post-school education has been influenced by a "therapeutic turn" in recent years has been subjected to critical scrutiny by a number of commentators. Learning initiatives which are dominated by objectives linked to personal and social skills, emotional intelligence and boosting self-esteem and confidence have been labelled as…

Volunteering within Initial Teacher Education: Factors That Boost and Block Participation

ERIC Educational Resources Information Center

Forster, Daniella J.; Archer, Jennifer; Tajin, Rukhsana T.

2015-01-01

Voluntary professional experience can be a powerful way for initial teacher education (ITE) students to develop an understanding of schools and their communities. Do ITE students make use of these opportunities? There is little Australian research that explores genuine volunteering that does not "require" students to engage with the…

Boosting Achievement with Messages that Motivate

ERIC Educational Resources Information Center

Dweck, Carol S.

2007-01-01

Almost everything educators say to their students sends a message. Some messages enhance students' motivation, but other messages undermine it. What should teachers say to students to send messages that motivate? In a survey given to parents, over 80% of them thought that it was necessary to praise their children's intelligence in order to give…

Boosting Underprepared Students: Salish Kootenai College Uses Research to Build Success

ERIC Educational Resources Information Center

Sherwin, Stacey

2011-01-01

As an open-access institution and a tribal college, Salish Kootenai College (SKC, Pablo, Montana) accepts all students who walk through the doors. Part of SKC's mission is to provide educational opportunities and access for students who are historically underrepresented in higher education. In recent years, national attention has focused on the…

Boosting Students' Attitudes & Knowledge about Evolution Sets Them up for College Success

ERIC Educational Resources Information Center

Carter, B. Elijah; Infanti, Lynn M.; Wiles, Jason R.

2015-01-01

Students who enter college with a solid grounding in, and positive attitudes toward, evolutionary science are better prepared for and achieve at higher levels in university-level biology courses. We found highly significant, positive relationships between student knowledge of evolution and attitudes toward evolution, as well as between…

Physical Classroom Environment and Student Satisfaction with Courses

ERIC Educational Resources Information Center

Han, Heesup; Kiatkawsin, Kiattipoom; Kim, Wansoo; Hong, Ju Hea

2018-01-01

The higher education market in South Korea has matured over recent decades. Higher education institutions have invested in many areas to boost the student experience. Student satisfaction has been identified as a key variable in explaining the holistic evaluation of the course. This study aims to fulfil a void in research by developing a study…

L2-Boosting algorithm applied to high-dimensional problems in genomic selection.

PubMed

González-Recio, Oscar; Weigel, Kent A; Gianola, Daniel; Naya, Hugo; Rosa, Guilherme J M

2010-06-01

The L(2)-Boosting algorithm is one of the most promising machine-learning techniques that has appeared in recent decades. It may be applied to high-dimensional problems such as whole-genome studies, and it is relatively simple from a computational point of view. In this study, we used this algorithm in a genomic selection context to make predictions of yet to be observed outcomes. Two data sets were used: (1) productive lifetime predicted transmitting abilities from 4702 Holstein sires genotyped for 32 611 single nucleotide polymorphisms (SNPs) derived from the Illumina BovineSNP50 BeadChip, and (2) progeny averages of food conversion rate, pre-corrected by environmental and mate effects, in 394 broilers genotyped for 3481 SNPs. Each of these data sets was split into training and testing sets, the latter comprising dairy or broiler sires whose ancestors were in the training set. Two weak learners, ordinary least squares (OLS) and non-parametric (NP) regression were used for the L2-Boosting algorithm, to provide a stringent evaluation of the procedure. This algorithm was compared with BL [Bayesian LASSO (least absolute shrinkage and selection operator)] and BayesA regression. Learning tasks were carried out in the training set, whereas validation of the models was performed in the testing set. Pearson correlations between predicted and observed responses in the dairy cattle (broiler) data set were 0.65 (0.33), 0.53 (0.37), 0.66 (0.26) and 0.63 (0.27) for OLS-Boosting, NP-Boosting, BL and BayesA, respectively. The smallest bias and mean-squared errors (MSEs) were obtained with OLS-Boosting in both the dairy cattle (0.08 and 1.08, respectively) and broiler (-0.011 and 0.006) data sets, respectively. In the dairy cattle data set, the BL was more accurate (bias=0.10 and MSE=1.10) than BayesA (bias=1.26 and MSE=2.81), whereas no differences between these two methods were found in the broiler data set. L2-Boosting with a suitable learner was found to be a competitive alternative for genomic selection applications, providing high accuracy and low bias in genomic-assisted evaluations with a relatively short computational time.

International Students at Community Colleges: Challenges and Opportunities for This Unique Segment of U.S. Higher Education

ERIC Educational Resources Information Center

Jennings, Ross

2017-01-01

In unprecedented numbers, American community colleges are seeking to boost their recruitment and retention of international students. This chapter uncovers the challenges and opportunities based on successful experiences in community college efforts.

Boosted classification trees result in minor to modest improvement in the accuracy in classifying cardiovascular outcomes compared to conventional classification trees

PubMed Central

Austin, Peter C; Lee, Douglas S

2011-01-01

Purpose: Classification trees are increasingly being used to classifying patients according to the presence or absence of a disease or health outcome. A limitation of classification trees is their limited predictive accuracy. In the data-mining and machine learning literature, boosting has been developed to improve classification. Boosting with classification trees iteratively grows classification trees in a sequence of reweighted datasets. In a given iteration, subjects that were misclassified in the previous iteration are weighted more highly than subjects that were correctly classified. Classifications from each of the classification trees in the sequence are combined through a weighted majority vote to produce a final classification. The authors' objective was to examine whether boosting improved the accuracy of classification trees for predicting outcomes in cardiovascular patients. Methods: We examined the utility of boosting classification trees for classifying 30-day mortality outcomes in patients hospitalized with either acute myocardial infarction or congestive heart failure. Results: Improvements in the misclassification rate using boosted classification trees were at best minor compared to when conventional classification trees were used. Minor to modest improvements to sensitivity were observed, with only a negligible reduction in specificity. For predicting cardiovascular mortality, boosted classification trees had high specificity, but low sensitivity. Conclusions: Gains in predictive accuracy for predicting cardiovascular outcomes were less impressive than gains in performance observed in the data mining literature. PMID:22254181

Evaluation of Machine Learning Algorithms for Classification of Primary Biological Aerosol using a new UV-LIF spectrometer

NASA Astrophysics Data System (ADS)

Ruske, S. T.; Topping, D. O.; Foot, V. E.; Kaye, P. H.; Stanley, W. R.; Morse, A. P.; Crawford, I.; Gallagher, M. W.

2016-12-01

Characterisation of bio-aerosols has important implications within Environment and Public Health sectors. Recent developments in Ultra-Violet Light Induced Fluorescence (UV-LIF) detectors such as the Wideband Integrated bio-aerosol Spectrometer (WIBS) and the newly introduced Multiparameter bio-aerosol Spectrometer (MBS) has allowed for the real time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal Spores and pollen. This new generation of instruments has enabled ever-larger data sets to be compiled with the aim of studying more complex environments, yet the algorithms used for specie classification remain largely invalidated. It is therefore imperative that we validate the performance of different algorithms that can be used for the task of classification, which is the focus of this study. For unsupervised learning we test Hierarchical Agglomerative Clustering with various different linkages. For supervised learning, ten methods were tested; including decision trees, ensemble methods: Random Forests, Gradient Boosting and AdaBoost; two implementations for support vector machines: libsvm and liblinear; Gaussian methods: Gaussian naïve Bayesian, quadratic and linear discriminant analysis and finally the k-nearest neighbours algorithm. The methods were applied to two different data sets measured using a new Multiparameter bio-aerosol Spectrometer. We find that clustering, in general, performs slightly worse than the supervised learning methods correctly classifying, at best, only 72.7 and 91.1 percent for the two data sets. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 88.1 and 97.8 percent of the testing data respectively across the two data sets. We discuss the wider relevance of these results with regards to challenging existing classification in real-world environments.

Investigating the Role of an Inquiry-Based Biology Lab Course on Student Attitudes and Views toward Science.

PubMed

Jeffery, Erica; Nomme, Kathy; Deane, Thomas; Pollock, Carol; Birol, Gülnur

2016-01-01

Students' academic experiences can influence their conceptualization of science. In contrast experts hold particular beliefs, perceptions, opinions, and attitudes about science that are often absent in first-year undergraduate students. Shifts toward more expert-like attitudes and views have been linked to improved student engagement, critical-thinking ability, conceptual understanding, and academic performance. In this study, we investigate shifts in attitudes and views toward science by students in four biology classes with differences in student enrollment, academic support, and instruction. We observe significant, positive effects of enrollment in a guided-inquiry lab course and academic performance on the percentage of expert-like student attitudes and views at the end of term. We also identify variation in two aspects of student attitudes and views: 1) confidence and interest and 2) understanding and acceptance. In particular, enrollment in the lab course boosts student confidence and interest in scientific inquiry in the short term, even for students with low academic performance or little English-language experience. Our results suggest that low-performing students in particular may require additional opportunities for experiential learning or greater academic support to develop expert-like perceptions of biology as a science. © 2016 E. Jeffery et al. CBE—Life Sciences Education © 2016 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).

Interpolated testing influences focused attention and improves integration of information during a video-recorded lecture.

PubMed

Jing, Helen G; Szpunar, Karl K; Schacter, Daniel L

2016-09-01

Although learning through a computer interface has become increasingly common, little is known about how to best structure video-recorded lectures to optimize learning. In 2 experiments, we examine changes in focused attention and the ability for students to integrate knowledge learned during a 40-min video-recorded lecture. In Experiment 1, we demonstrate that interpolating a lecture with memory tests (tested group), compared to studying the lecture material for the same amount of time (restudy group), improves overall learning and boosts integration of related information learned both within individual lecture segments and across the entire lecture. Although mind wandering rates between the tested and restudy groups did not differ, mind wandering was more detrimental for final test performance in the restudy group than in the tested group. In Experiment 2, we replicate the findings of Experiment 1, and additionally show that interpolated tests influence the types of thoughts that participants report during the lecture. While the tested group reported more lecture-related thoughts, the restudy group reported more lecture-unrelated thoughts; furthermore, lecture-related thoughts were positively related to final test performance, whereas lecture-unrelated thoughts were negatively related to final test performance. Implications for the use of interpolated testing in video-recorded lectures are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Leading with the Heart.

ERIC Educational Resources Information Center

Linik, Joyce Riha

1998-01-01

Describes techniques used in a multi-age class at Coupeville Elementary School, Washington, to boost reading comprehension and inspire students' love of books: access to an abundance of books, challenges to students, skills reinforcement, combined phonics and whole-language instruction, running-record assessment, paired reading, independent…

Modeling Learning and Memory Using Verbal Learning Tests: Results From ACTIVE

PubMed Central

Gross, Alden L.

2013-01-01

Objective. To investigate the influence of memory training on initial recall and learning. Method. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Results. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen’s d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p < .001). Findings were replicated using the HVLT (decline in initial recall, d = 0.60, p = .01; pre- and posttraining acceleration in learning, d = 3.10, p < .001). Because of the immediate training boost, the memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. Discussion. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning. PMID:22929389

Modeling learning and memory using verbal learning tests: results from ACTIVE.

PubMed

Gross, Alden L; Rebok, George W; Brandt, Jason; Tommet, Doug; Marsiske, Michael; Jones, Richard N

2013-03-01

To investigate the influence of memory training on initial recall and learning. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen's d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p < .001). Findings were replicated using the HVLT (decline in initial recall, d = 0.60, p = .01; pre- and posttraining acceleration in learning, d = 3.10, p < .001). Because of the immediate training boost, the memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning.

Imputing data that are missing at high rates using a boosting algorithm

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

Cauthen, Katherine Regina; Lambert, Gregory; Ray, Jaideep

Traditional multiple imputation approaches may perform poorly for datasets with high rates of missingness unless many m imputations are used. This paper implements an alternative machine learning-based approach to imputing data that are missing at high rates. Here, we use boosting to create a strong learner from a weak learner fitted to a dataset missing many observations. This approach may be applied to a variety of types of learners (models). The approach is demonstrated by application to a spatiotemporal dataset for predicting dengue outbreaks in India from meteorological covariates. A Bayesian spatiotemporal CAR model is boosted to produce imputations, andmore » the overall RMSE from a k-fold cross-validation is used to assess imputation accuracy.« less

Optical diagnosis of cervical cancer by higher order spectra and boosting

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Barman, Ritwik; Pratiher, Souvik; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-03-01

In this contribution, we report the application of higher order statistical moments using decision tree and ensemble based learning methodology for the development of diagnostic algorithms for optical diagnosis of cancer. The classification results were compared to those obtained with an independent feature extractors like linear discriminant analysis (LDA). The performance and efficacy of these methodology using higher order statistics as a classifier using boosting has higher specificity and sensitivity while being much faster as compared to other time-frequency domain based methods.

Reducing "Math Anxiety" in College Algebra Courses Including Comparisons with Elementary Statistics Courses.

ERIC Educational Resources Information Center

Bankhead, Mike

The high levels of anxiety, apprehension, and apathy of students in college algebra courses caused the instructor to create and test a variety of math teaching techniques designed to boost student confidence and enthusiasm in the subject. Overall, this proposal covers several different techniques, which have been evaluated by both students and the…

Every Moment Counts: Five Principles for Boosting the Achievement of Struggling Students

ERIC Educational Resources Information Center

Gerzon-Kessler, Ari

2006-01-01

In this article, the author relates her difficult experiences as a novice teacher when she started teaching bilingual third-graders in Spanish at Spangler Elementary School in 2002. She relates that her teaching strategy of balancing rigor and sweetness had its rewards as her students' rate of reading proficiency on the Colorado Student Assessment…

Repetition across Successive Sentences Facilitates Young Children's Word Learning

ERIC Educational Resources Information Center

Schwab, Jessica F.; Lew-Williams, Casey

2016-01-01

Young children who hear more child-directed speech (CDS) tend to have larger vocabularies later in childhood, but the specific characteristics of CDS underlying this link are currently underspecified. The present study sought to elucidate how the structure of language input boosts learning by investigating whether repetition of object labels in…

Retrieval Practice Makes Procedure from Remembering: An Automatization Account of the Testing Effect

ERIC Educational Resources Information Center

Racsmány, Mihály; Szollosi, Ágnes; Bencze, Dorottya

2018-01-01

The "testing effect" refers to the striking phenomenon that repeated retrieval practice is one of the most effective learning strategies, and certainly more advantageous for long-term learning, than additional restudying of the same information. How retrieval can boost the retention of memories is still without unanimous explanation. In…

Professionalising Physics Teachers in Doing Experimental Work

ERIC Educational Resources Information Center

Haagen-Schutzenhofer, Claudia; Joham, Birgit

2018-01-01

It is commonly agreed that experiments play a central role in teaching and learning physics. Recently, Inquiry-Based Learning (IBL) has been introduced into science teaching in many countries, thus giving another boost for experiments. From a didactical point of view, experiments can serve a number of different goals in teaching and learning…

Helping Adults Learn To Deliver Value in a Global Society.

ERIC Educational Resources Information Center

Montgomery, Joel R.

Andersen Consulting is a global management and technology consulting organization whose mission is to boost clients' success by teaching them to link strategy, people, processes, and technology. Andersen's professional development program for its own 41,000-person global work force is designed to help adults learn to deliver value to global…

Federal Grant Boosts Educational Television, Faces Fresh Scrutiny

ERIC Educational Resources Information Center

Honawar, Vaishali

2005-01-01

This article reports how the Ready to Learn program, which has helped transform children's educational television over the past decade, faced scrutiny after it aired a controversial topic. The Ready to Learn program attracted unusual attention when one of the shows it helped get on the air, "Postcards from Buster," drew criticism from…

An Alternative Educational Method in Early Childhood: Museum Education

ERIC Educational Resources Information Center

Akamca, Güzin Özyilmaz; Yildirim, R. Gunseli; Ellez, A. Murat

2017-01-01

According to the preschool education program that came into effect by Turkish Ministry of Education in Turkey in 2013, teaching should be offered not only in classrooms but also in places outside classrooms likely to boost learning. The program required utilizing learning techniques, and environments different from conventional ones. The aim of…

Lessons Learned in Starting and Running a Neighborhood Networks Center.

ERIC Educational Resources Information Center

Department of Housing and Urban Development, Washington, DC.

This guide shares information about setting up and operating Neighborhood Networks centers. (These centers operate in Department of Housing and Urban Development-assisted or -insured housing nationwide to help low-income people boost their basic skills and find good jobs, learn to use computers and the Internet, run businesses, improve their…

Older adults get episodic memory boosting from noninvasive stimulation of prefrontal cortex during learning

PubMed Central

Brambilla, Michela; Cobelli, Chiara; Cohen, Leonardo G.; Cotelli, Maria

2016-01-01

Episodic memory displays the largest degree of age-related decline, a process that is accelerated in pathological conditions such as amnestic mild cognitive impairment and Alzheimer's disease. Previous studies have shown that the left lateral prefrontal cortex (PFC) contributes to the encoding of episodic memories along the life span. The aim of this randomized, double-blind, placebo-controlled study was to test the hypothesis that anodal trascranial direct current stimulation (tDCS) over the left lateral PFC during the learning phase would enhance delayed recall of verbal episodic memories in elderly individuals. Older adults learned a list of words while receiving anodal or placebo (sham) tDCS. Memory recall was tested 48 hours and 1 month later. The results showed that anodal tDCS strengthened episodic memories, an effect indicated by enhanced delayed recall (48 hours) compared to placebo stimulation (Cohen's d effect size = 1.01). The observation that PFC-tDCS during learning can boost verbal episodic memory in the elderly opens up the possibility to design-specific neurorehabilitation protocols targeted to conditions that affect episodic memory such as mild cognitive impairment. PMID:26923418

Peptide Seems to Boost Human Memory.

ERIC Educational Resources Information Center

Chemical and Engineering News, 1981

1981-01-01

This article discusses recent studies which have shown that the peptide hormone vasopressin apparently can stimulate memory and learning in healthy human volunteers and in certain mentally disturbed patients. (ECO)

BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

PubMed

Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

2018-04-11

The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes by using deep learning on high-dimensional and small-scale biology data.

Comparison of composite prostate radiotherapy plan doses with dependent and independent boost phases.

PubMed

Narayanasamy, Ganesh; Avila, Gabrielle; Mavroidis, Panayiotis; Papanikolaou, Niko; Gutierrez, Alonso; Baacke, Diana; Shi, Zheng; Stathakis, Sotirios

2016-09-01

Prostate cases commonly consist of dual phase planning with a primary plan followed by a boost. Traditionally, the boost phase is planned independently from the primary plan with the risk of generating hot or cold spots in the composite plan. Alternatively, boost phase can be planned taking into account the primary dose. The aim of this study was to compare the composite plans from independently and dependently planned boosts using dosimetric and radiobiological metrics. Ten consecutive prostate patients previously treated at our institution were used to conduct this study on the Raystation™ 4.0 treatment planning system. For each patient, two composite plans were developed: a primary plan with an independently planned boost and a primary plan with a dependently planned boost phase. The primary plan was prescribed to 54 Gy in 30 fractions to the primary planning target volume (PTV1) which includes prostate and seminal vesicles, while the boost phases were prescribed to 24 Gy in 12 fractions to the boost planning target volume (PTV2) that targets only the prostate. PTV coverage, max dose, median dose, target conformity, dose homogeneity, dose to OARs, and probabilities of benefit, injury, and complication-free tumor control (P+) were compared. Statistical significance was tested using either a 2-tailed Student's t-test or Wilcoxon signed-rank test. Dosimetrically, the composite plan with dependent boost phase exhibited smaller hotspots, lower maximum dose to the target without any significant change to normal tissue dose. Radiobiologically, for all but one patient, the percent difference in the P+ values between the two methods was not significant. A large percent difference in P+ value could be attributed to an inferior primary plan. The benefits of considering the dose in primary plan while planning the boost is not significant unless a poor primary plan was achieved.

Rebooting Computers as Learning Machines

DOE PAGES

DeBenedictis, Erik P.

2016-06-13

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

Rebooting Computers as Learning Machines

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

DeBenedictis, Erik P.

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

Dual Enrollment Programs. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2017

2017-01-01

"Dual enrollment" programs allow high school students to take college courses and earn college credits while still attending high school. Such programs, also referred to as "dual credit" or early college programs, are designed to boost college access and degree attainment, especially for students typically underrepresented in…

Teachers' Pedagogical Resistance to Prescribed Curriculum

ERIC Educational Resources Information Center

Owens, Darya

2017-01-01

Research indicates that teachers feel intimidated into fully implementing prescribed literacy curriculum at the expense of their own praxis which may indeed be effective in boosting student literacy achievement. This perceived intimidation may serve to compromise students' literacy outcomes. The objective of the study was to recognize the…

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

Gradient boosting machine for modeling the energy consumption of commercial buildings

DOE PAGES

Touzani, Samir; Granderson, Jessica; Fernandes, Samuel

2017-11-26

Accurate savings estimations are important to promote energy efficiency projects and demonstrate their cost-effectiveness. The increasing presence of advanced metering infrastructure (AMI) in commercial buildings has resulted in a rising availability of high frequency interval data. These data can be used for a variety of energy efficiency applications such as demand response, fault detection and diagnosis, and heating, ventilation, and air conditioning (HVAC) optimization. This large amount of data has also opened the door to the use of advanced statistical learning models, which hold promise for providing accurate building baseline energy consumption predictions, and thus accurate saving estimations. The gradientmore » boosting machine is a powerful machine learning algorithm that is gaining considerable traction in a wide range of data driven applications, such as ecology, computer vision, and biology. In the present work an energy consumption baseline modeling method based on a gradient boosting machine was proposed. To assess the performance of this method, a recently published testing procedure was used on a large dataset of 410 commercial buildings. The model training periods were varied and several prediction accuracy metrics were used to evaluate the model's performance. The results show that using the gradient boosting machine model improved the R-squared prediction accuracy and the CV(RMSE) in more than 80 percent of the cases, when compared to an industry best practice model that is based on piecewise linear regression, and to a random forest algorithm.« less

Gradient boosting machine for modeling the energy consumption of commercial buildings

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

Touzani, Samir; Granderson, Jessica; Fernandes, Samuel

Accurate savings estimations are important to promote energy efficiency projects and demonstrate their cost-effectiveness. The increasing presence of advanced metering infrastructure (AMI) in commercial buildings has resulted in a rising availability of high frequency interval data. These data can be used for a variety of energy efficiency applications such as demand response, fault detection and diagnosis, and heating, ventilation, and air conditioning (HVAC) optimization. This large amount of data has also opened the door to the use of advanced statistical learning models, which hold promise for providing accurate building baseline energy consumption predictions, and thus accurate saving estimations. The gradientmore » boosting machine is a powerful machine learning algorithm that is gaining considerable traction in a wide range of data driven applications, such as ecology, computer vision, and biology. In the present work an energy consumption baseline modeling method based on a gradient boosting machine was proposed. To assess the performance of this method, a recently published testing procedure was used on a large dataset of 410 commercial buildings. The model training periods were varied and several prediction accuracy metrics were used to evaluate the model's performance. The results show that using the gradient boosting machine model improved the R-squared prediction accuracy and the CV(RMSE) in more than 80 percent of the cases, when compared to an industry best practice model that is based on piecewise linear regression, and to a random forest algorithm.« less

School Improvement Should Rely on Reliable, Scientific Evidence. Why Did "No Child Left Behind" Leave Class Size Behind?

ERIC Educational Resources Information Center

Achilles, C. M.; Krieger, Jean D.; Finn, J. D.; Sharp, Mark

Small classes in grades K-3 boost student academic performance in all subjects and in prosocial behavior. Results are both short- and long-term. One study explored the theory that a major cause behind improved academic achievement involves improved student behavior, which increases student engagement in the classroom. Two other studies provide…

The San Diego Blueprint for Student Success: A Retrospective Overview and Commentary

ERIC Educational Resources Information Center

Betts, Julian R.

2009-01-01

In a series of reforms started in 1998 and formalized with the 2000 introduction of the Blueprint for Student Success, the San Diego Unified School District (SDUSD) implemented a wide-ranging series of reforms designed to boost the literacy skills of students. This article provides an overview of the reforms, assesses the contributions made by the…

Boosting Student Comprehension of Informational Materials at the Secondary Level at Benjamin Holt College Preparatory Academy

ERIC Educational Resources Information Center

Sampley, Jolyne K.

2008-01-01

Without proficiency in content reading skills, seventh grade students were at risk of not being able to achieve understanding of what they read in non-fiction texts, a skill that is absolutely necessary for college-bound students. The purpose of this action research study was to investigate whether an approach that involved specific and focused…

The Determinants of International Student Mobility Flows: An Empirical Study on the Erasmus Programme

ERIC Educational Resources Information Center

Rodriguez Gonzalez, Carlos; Bustillo Mesanza, Ricardo; Mariel, Petr

2011-01-01

The Erasmus Programme for higher education students is supposed to play an important socio-economic role within Europe. Erasmus student mobility flows have reached a relevant level of two million since 1987, boosted in recent years by the enlargement of the programme to eastern countries. Thereafter, it seems that flows have staggered. In this…

Rural Student Entrepreneurs: Linking Commerce and Community. (Benefits)[Squared]: The Exponential Results of Linking School Improvement and Community Development, Issue Number Three.

ERIC Educational Resources Information Center

Boethel, Martha

In many rural areas, both communities and schools are threatened by decreasing population and changing economic conditions. To boost both the local economy and student achievement, a growing number of rural schools are turning to entrepreneurial education. In school entrepreneurship programs, students create small businesses under the guidance of…

Dopaminergic Modulation of Decision Making and Subjective Well-Being.

PubMed

Rutledge, Robb B; Skandali, Nikolina; Dayan, Peter; Dolan, Raymond J

2015-07-08

The neuromodulator dopamine has a well established role in reporting appetitive prediction errors that are widely considered in terms of learning. However, across a wide variety of contexts, both phasic and tonic aspects of dopamine are likely to exert more immediate effects that have been less well characterized. Of particular interest is dopamine's influence on economic risk taking and on subjective well-being, a quantity known to be substantially affected by prediction errors resulting from the outcomes of risky choices. By boosting dopamine levels using levodopa (l-DOPA) as human subjects made economic decisions and repeatedly reported their momentary happiness, we show here an effect on both choices and happiness. Boosting dopamine levels increased the number of risky options chosen in trials involving potential gains but not trials involving potential losses. This effect could be better captured as increased Pavlovian approach in an approach-avoidance decision model than as a change in risk preferences within an established prospect theory model. Boosting dopamine also increased happiness resulting from some rewards. Our findings thus identify specific novel influences of dopamine on decision making and emotion that are distinct from its established role in learning. Copyright © 2015 Rutledge et al.

Dopaminergic Modulation of Decision Making and Subjective Well-Being

PubMed Central

Skandali, Nikolina; Dayan, Peter; Dolan, Raymond J.

2015-01-01

The neuromodulator dopamine has a well established role in reporting appetitive prediction errors that are widely considered in terms of learning. However, across a wide variety of contexts, both phasic and tonic aspects of dopamine are likely to exert more immediate effects that have been less well characterized. Of particular interest is dopamine's influence on economic risk taking and on subjective well-being, a quantity known to be substantially affected by prediction errors resulting from the outcomes of risky choices. By boosting dopamine levels using levodopa (l-DOPA) as human subjects made economic decisions and repeatedly reported their momentary happiness, we show here an effect on both choices and happiness. Boosting dopamine levels increased the number of risky options chosen in trials involving potential gains but not trials involving potential losses. This effect could be better captured as increased Pavlovian approach in an approach–avoidance decision model than as a change in risk preferences within an established prospect theory model. Boosting dopamine also increased happiness resulting from some rewards. Our findings thus identify specific novel influences of dopamine on decision making and emotion that are distinct from its established role in learning. PMID:26156984

Orthographic Facilitation of First Graders' Vocabulary Learning: Does Directing Attention to Print Enhance the Effect?

ERIC Educational Resources Information Center

Chambré, Susan J.; Ehri, Linnea C.; Ness, Molly

2017-01-01

Orthographic facilitation refers to the boost in vocabulary learning that is provided when spellings are shown during study periods, but not during testing. The current study examined orthographic facilitation in beginning readers and whether directing their attention to print enhances the effect. In an experiment, first graders (N = 45) were…

A Hierarchical and Contextual Model for Learning and Recognizing Highly Variant Visual Categories

DTIC Science & Technology

2010-01-01

neighboring pattern primitives, to create our model. We also present a minimax entropy framework for automatically learning which contextual constraints are...Grammars . . . . . . . . . . . . . . . . . . 19 3.2 Markov Random Fields . . . . . . . . . . . . . . . . . . . . . . . . 23 3.3 Creating a Contextual...Compositional Boosting. . . . . 119 7.8 Top-down hallucinations of missing objects. . . . . . . . . . . . . . . 121 7.9 The bottom-up to top-down

The Recruitment Agent in Internationalized Higher Education: Commercial Broker and Cultural Mediator

ERIC Educational Resources Information Center

Robinson-Pant, Anna; Magyar, Anna

2018-01-01

The internationalization and marketization of higher education has resulted in U.K. universities' increasing reliance on recruitment agents to boost international student numbers. This places agents and agencies in a position of considerable influence with regard to the educational choices that students make. These institutional and individual…

Teaching Smarter: An Unconventional Guide to Boosting Student Success

ERIC Educational Resources Information Center

Kelley, Patrick

2015-01-01

This refreshingly frank handbook shows teachers how to close the achievement gap in their classrooms by teaching students innovative paths to academic success. Drawing on over 20 years' experience, Kelley presents straightforward strategies for helping learners improve their grades and test scores and experience greater school engagement--all…

Enhancing Students' Employability through Business Simulation

ERIC Educational Resources Information Center

Avramenko, Alex

2012-01-01

Purpose: The purpose of this paper is to introduce an approach to business simulation with less dependence on business simulation software to provide innovative work experience within a programme of study, to boost students' confidence and employability. Design/methodology/approach: The paper is based on analysis of existing business simulation…

Classroom Management Strategies for Difficult Students: Promoting Change through Relationships

ERIC Educational Resources Information Center

Beaty-O'Ferrall, Mary Ellen; Green, Alan; Hanna, Fred

2010-01-01

Teachers in middle level schools face overwhelming demands and challenges in their classrooms. They are expected to know content and pedagogy, develop engaging lessons that meet the needs of diverse learners, and use a variety of instructional strategies that will boost student achievement while they simultaneously develop positive relationships…

Predicting Kindergarteners' Achievement and Motivation from Observational Measures of Teaching Effectiveness

ERIC Educational Resources Information Center

Mantzicopoulos, Panayota; Patrick, Helen; Strati, Anna; Watson, Jesse S.

2018-01-01

We investigated the premise that observation measures of instruction are indicators of effective teaching, using the definition of effectiveness articulated by departments of education: teaching that boosts student achievement. We argued that student motivation is equally as important as achievement in the evaluation of teaching effectiveness…

Ban or Boost Student-Owned Technology?

ERIC Educational Resources Information Center

Johnson, Doug

2004-01-01

We've experienced Generation X and Generation Y. Now Generation Wi-Fi is making its presence known in many schools. Today's students are connected with each other and the world, increasingly through personally owned communication technologies. Cell phones that send text messages and photographs, handheld personal digital assistants that can beam…

A Tale of Unintended Consequences

ERIC Educational Resources Information Center

Corn, Jennifer

2006-01-01

A teacher of Limited English Proficient elementary students in California describes how she put her students through daily timed read-aloud drills to boost their scores on a benchmark assessment of reading rate that her school district required. Corn briefly reviews the rationale behind measuring reading rate as an indicator of fluency. The reason…

Can Interdistrict Choice Boost Student Achievement? The Case of Connecticut's Interdistrict Magnet School Program

ERIC Educational Resources Information Center

Bifulco, Robert; Cobb, Casey D.; Bell, Courtney

2009-01-01

Connecticut's interdistrict magnet schools offer a model of choice-based desegregation that appears to satisfy current legal constraints. This study presents evidence that interdistrict magnet schools have provided students from Connecticut's central cities access to less racially and economically isolated educational environments and estimates…

Does Student Attrition Explain KIPP's Success?

ERIC Educational Resources Information Center

Nichols-Barrer, Ira; Gill, Brian P.; Gleason, Philip; Tuttle, Christina Clark

2014-01-01

The Knowledge Is Power Program (KIPP) is a network of charter schools designed to improve the educational opportunities available to low-income families. KIPP schools seek to boost their students' academic achievement and ultimately prepare them to enroll and succeed in college. To achieve these objectives, KIPP schools leverage strong…

When Tests Make You Nervous

MedlinePlus

... you figure out some solutions. For instance, learning study skills can boost your test-day confidence. Be prepared. Pay attention in class. Do your homework. Study for the test. On test day, you're ...

A study of a science-based peer reading assignment and its effects on first grade student understanding and use of describing words in science

NASA Astrophysics Data System (ADS)

Pearson, Meghan Jeanne

The first grade curriculum for science in Colorado requires students be able to use describing words to depict and compare objects and people; however, first graders struggle with using specific enough language to create strong descriptions. With science education research encouraging teachers to use alternative teaching methods to approach these challenging topics, it is important to provide teachers with resources appropriate to their students. One such alternative learning method is a reading partner. Reading partners have been shown to increase vocabulary, boost school performance, and improve self-esteem in children. This study analyzed the effectiveness of using a science-based peer reading assignment about describing words on increasing a first grader's understanding of the topic. The book required the class to work together to help the characters describe different images and characters in the book with the intent that students were engaged during the reading. In pre-interview and post-interview, students described pictures, and their responses were analyzed for quality of the describing words provided and the number of strong (specific and not opinion) describing words provided. In the post-interview, students had an overall increase in the number of strong describing words provided. The quantitative data was analyzed by comparing strong describing words used pre-reading and post-reading, and the effect size was very large. The results indicate reading the book explaining describing words that asked for student participation did increase students understanding and use of describing words.

Whole System Thinking: Working with K-12 and Four-Year Partners to Boost Student Success

ERIC Educational Resources Information Center

Collett, Stacy

2013-01-01

As they closed the books on the 2012-2013 school year, Long Beach City College continued the task of pouring over years of student enrollment data. They found that after years of offering remedial courses for students who entered unprepared for the rigors of higher education, the college reported and astonishing 500 percent increase in the number…

Comparisons between physics-based, engineering, and statistical learning models for outdoor sound propagation.

PubMed

Hart, Carl R; Reznicek, Nathan J; Wilson, D Keith; Pettit, Chris L; Nykaza, Edward T

2016-05-01

Many outdoor sound propagation models exist, ranging from highly complex physics-based simulations to simplified engineering calculations, and more recently, highly flexible statistical learning methods. Several engineering and statistical learning models are evaluated by using a particular physics-based model, namely, a Crank-Nicholson parabolic equation (CNPE), as a benchmark. Narrowband transmission loss values predicted with the CNPE, based upon a simulated data set of meteorological, boundary, and source conditions, act as simulated observations. In the simulated data set sound propagation conditions span from downward refracting to upward refracting, for acoustically hard and soft boundaries, and low frequencies. Engineering models used in the comparisons include the ISO 9613-2 method, Harmonoise, and Nord2000 propagation models. Statistical learning methods used in the comparisons include bagged decision tree regression, random forest regression, boosting regression, and artificial neural network models. Computed skill scores are relative to sound propagation in a homogeneous atmosphere over a rigid ground. Overall skill scores for the engineering noise models are 0.6%, -7.1%, and 83.8% for the ISO 9613-2, Harmonoise, and Nord2000 models, respectively. Overall skill scores for the statistical learning models are 99.5%, 99.5%, 99.6%, and 99.6% for bagged decision tree, random forest, boosting, and artificial neural network regression models, respectively.

A hypothesis on a role of oxytocin in the social mechanisms of speech and vocal learning.

PubMed

Theofanopoulou, Constantina; Boeckx, Cedric; Jarvis, Erich D

2017-08-30

Language acquisition in humans and song learning in songbirds naturally happen as a social learning experience, providing an excellent opportunity to reveal social motivation and reward mechanisms that boost sensorimotor learning. Our knowledge about the molecules and circuits that control these social mechanisms for vocal learning and language is limited. Here we propose a hypothesis of a role for oxytocin (OT) in the social motivation and evolution of vocal learning and language. Building upon existing evidence, we suggest specific neural pathways and mechanisms through which OT might modulate vocal learning circuits in specific developmental stages. © 2017 The Authors.

A hypothesis on a role of oxytocin in the social mechanisms of speech and vocal learning

PubMed Central

Jarvis, Erich D.

2017-01-01

Language acquisition in humans and song learning in songbirds naturally happen as a social learning experience, providing an excellent opportunity to reveal social motivation and reward mechanisms that boost sensorimotor learning. Our knowledge about the molecules and circuits that control these social mechanisms for vocal learning and language is limited. Here we propose a hypothesis of a role for oxytocin (OT) in the social motivation and evolution of vocal learning and language. Building upon existing evidence, we suggest specific neural pathways and mechanisms through which OT might modulate vocal learning circuits in specific developmental stages. PMID:28835557

The Effect of Stimulating Immigrant and National Pupils' Helping Behaviour during Cooperative Learning in Classrooms on Their Maths-Related Talk

ERIC Educational Resources Information Center

Oortwijn, Michiel Bastiaan; Boekaerts, Monique; Vedder, Paul

2008-01-01

This study examined whether stimulation of immigrant and national pupils' use of high-quality helping behaviour (experimental condition) during cooperative learning (CL) in classrooms boosts their maths-related talk more than in an educational situation in which such stimulation is largely absent (control condition). A total of 59 elementary-age…

Preparing Pupils to Cooperate during Cooperative Controversy in Grade 6: A Way to Increase Positive Interactions and Learning?

ERIC Educational Resources Information Center

Golub, Mijal; Buchs, Céline

2014-01-01

Research has underlined the necessity to prepare pupils to cooperate in order to boost cooperative learning benefits. However, this kind of training may appear very demanding. The present study aims to demonstrate that a short preparation related to social support and targeted cooperative rules relevant for the task increases constructive…

Minimal Groups Increase Young Children's Motivation and Learning on Group-Relevant Tasks

ERIC Educational Resources Information Center

Master, Allison; Walton, Gregory M.

2013-01-01

Three experiments ("N" = 130) used a minimal group manipulation to show that just perceived membership in a social group boosts young children's motivation for and learning from group-relevant tasks. In Experiment 1, 4-year-old children assigned to a minimal "puzzles group" persisted longer on a challenging puzzle than children identified as the…

The Link between Foreign Language Classroom Anxiety, Second Language Tolerance of Ambiguity and Self-Rated English Proficiency among Chinese Learners

ERIC Educational Resources Information Center

Dewaele, Jean-Marc; Ip, Tsui Shan

2013-01-01

Previous research has suggested that high levels of Foreign Language Classroom Anxiety (FLCA) have a negative effect on foreign language learning (Horwitz, 2001; Lu & Liu, 2011) while moderate levels of Second Language Tolerance of Ambiguity (SLTA) are believed to boost foreign language learning (Ely, 1995). There is prima facie evidence that…

Spaced Learning: The Design, Feasibility and Optimisation of SMART Spaces. Evaluation Report and Executive Summary

ERIC Educational Resources Information Center

O'Hare, Liam; Stark, Patrick; McGuinness, Carol; Biggart, Andy; Thurston, Allen

2017-01-01

This report describes the development and pilot evaluation of SMART Spaces. This programme aims to boost GCSE science outcomes by applying the principle that information is more easily learnt when it is repeated multiple times, with time passing between the repetitions. This approach is known as "spaced learning" and is contrasted with a…

Older adults get episodic memory boosting from noninvasive stimulation of prefrontal cortex during learning.

PubMed

Sandrini, Marco; Manenti, Rosa; Brambilla, Michela; Cobelli, Chiara; Cohen, Leonardo G; Cotelli, Maria

2016-03-01

Episodic memory displays the largest degree of age-related decline, a process that is accelerated in pathological conditions such as amnestic mild cognitive impairment and Alzheimer's disease. Previous studies have shown that the left lateral prefrontal cortex (PFC) contributes to the encoding of episodic memories along the life span. The aim of this randomized, double-blind, placebo-controlled study was to test the hypothesis that anodal trascranial direct current stimulation (tDCS) over the left lateral PFC during the learning phase would enhance delayed recall of verbal episodic memories in elderly individuals. Older adults learned a list of words while receiving anodal or placebo (sham) tDCS. Memory recall was tested 48 hours and 1 month later. The results showed that anodal tDCS strengthened episodic memories, an effect indicated by enhanced delayed recall (48 hours) compared to placebo stimulation (Cohen's d effect size = 1.01). The observation that PFC-tDCS during learning can boost verbal episodic memory in the elderly opens up the possibility to design-specific neurorehabilitation protocols targeted to conditions that affect episodic memory such as mild cognitive impairment. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiple-choice tests stabilize access to marginal knowledge.

PubMed

Cantor, Allison D; Eslick, Andrea N; Marsh, Elizabeth J; Bjork, Robert A; Bjork, Elizabeth Ligon

2015-02-01

Marginal knowledge refers to knowledge that is stored in memory, but is not accessible at a given moment. For example, one might struggle to remember who wrote The Call of the Wild, even if that knowledge is stored in memory. Knowing how best to stabilize access to marginal knowledge is important, given that new learning often requires accessing and building on prior knowledge. While even a single opportunity to restudy marginal knowledge boosts its later accessibility (Berger, Hall, & Bahrick, 1999), in many situations explicit relearning opportunities are not available. Our question is whether multiple-choice tests (which by definition expose the learner to the correct answers) can also serve this function and, if so, how testing compares to restudying given that tests can be particularly powerful learning devices (Roediger & Karpicke, 2006). In four experiments, we found that multiple-choice testing had the power to stabilize access to marginal knowledge, and to do so for at least up to a week. Importantly, such tests did not need to be paired with feedback, although testing was no more powerful than studying. Overall, the results support the idea that one's knowledge base is unstable, with individual pieces of information coming in and out of reach. The present findings have implications for a key educational challenge: ensuring that students have continuing access to information they have learned.

The Use of Inflight Online Distance Education for Mission Support and Psychological Support.

NASA Astrophysics Data System (ADS)

Mardon, Austin; Nichol, Kenneth; Mardon, Catherine

Time, too much of and the resulting boredom is a major psychological barrier to multi year inner solar system space missions. Cross training which could be facilitated by online in flight educational programs might serve mission purposes and distract astronauts from the natural multiyear boredom to and from Mars. The personnel selected will be motivated well educated and likely very intelligent. They might have even experience some educational online and computer based education during their educational history. Distance learning is become more and more common in the educational landscape in the world. The mission doctor might learn geology. The geologist might learn ship systems. The pilot might learn basic medical treatment. The advantage of having planned out learning schemes might have major morale boosting factors by giving the self motivated high achieving crew something to direct their energies toward. The time lag could be compensated for by AI spacecraft educational software. Also for recreational purposes archeology or cultural studies could be taught to give greater breadth of interest. Online educational institutions might even do curriculum for free if they could be used afterward and before. Many high achievers have diverse interests and this might boost morale by allowing them to learn about a field of study that they had always had an interest in but their career took them in a different direction

Citation as a Stimulus to Boost Students' Communication Skills at the English Lessons

ERIC Educational Resources Information Center

Sadykova, Aida G.; Yashina, Marianna E.; Sharafieva, Alina D.

2014-01-01

The study contemplates significance of using citation at the English lessons by exposing its advantages. Quotations represent the enormous linguistic variety, which discloses the modern language that unambiguously assists students to develop skills of oral speech. Special attention is paid to the experiment conducted at the series of lessons in…

College Challenge to Ensure "Timely Graduation": Understanding College Students' Mindsets during the Financial Crisis

ERIC Educational Resources Information Center

Chen, Xiaoying; Yur-Austin, Jasmine

2016-01-01

Since mid-2007, the United States has experienced the direst economic recession since the Great Depression. While considerable institutional resources have been spent on boosting 4-year graduation rates, many college students purposefully delayed graduation, waiting to enter the labor market until the overall economic situation had improved. The…

High Schools Try out RTI

ERIC Educational Resources Information Center

Samuels, Christina A.

2009-01-01

"Response to intervention" (RTI) as a model for boosting student achievement has taken off like wildfire. When it comes to research on how best to implement the process for students in middle and high school, though, the flame abruptly fizzles out. There's little RTI research that is specific to secondary schools, although it has been…

Virginia's College and Career Ready Initiative Grade 12 English Capstone Course Content and Performance Expectations

ERIC Educational Resources Information Center

Virginia Department of Education, 2011

2011-01-01

Virginia's "College and Career Ready English Performance Expectations" grade 12 capstone course contains high-interest contextualized content designed to give certain students an additional boost for competent and successful entry into college and careers. The course will add to students' preparation for critical reading, college and…

Seeing the Wood for the Trees

ERIC Educational Resources Information Center

Ritchie, Meabh

2010-01-01

This article is an informal description of a forest school outdoor programme designed to boost emotional literacy, inclusion and attainment of secondary school pupils with a range of learning and behavioural difficulties. (Contains 2 online resources.)

Learning "Math on the Move": Effectiveness of a Combined Numeracy and Physical Activity Program for Primary School Children.

PubMed

Vetter, Melanie; O'Connor, Helen; O'Dwyer, Nicholas; Orr, Rhonda

2018-03-27

Physically active learning that combines physical activity with core curriculum areas is emerging in school-based health interventions. This study investigates the effectiveness of learning an important numeracy skill of times tables (TT) while concurrently engaging in aerobic activity compared with a seated classroom approach. Grade-4 primary school students were randomly allocated to physical activity (P) or classroom (C) groups and received the alternate condition in the following term. P group received moderate to vigorous exercise (20 min, 3 times per week, 6 wk) while simultaneously learning selected TT. C group received similar learning, but seated. Changes in TT accuracy, general numeracy, aerobic fitness, and body mass index were assessed. Data were expressed as mean (SEM) and between-condition effect size (ES; 95% confidence interval). Participants [N = 85; 55% male, 9.8 (0.3) y, 36.4% overweight/obese] improved similarly on TT in both conditions [C group: 2.2% (1.1%); P group: 2.5% (1.3%); ES = 0.03; -0.30 to 0.36; P = .86]. Improvement in general numeracy was significantly greater for P group than C group [C group: 0.7% (1.2%); P group: 5.3% (1.4%); ES = 0.42; 0.08 to 0.75; P < .03]. An improvement in aerobic fitness for P group (P < .01) was not significantly greater than C group [C group: 0.8 (0.6); P group: 2.2 (0.5) mL·kg·min -1 ; ES = 0.32; -0.01 to 0.66; P = .06]. Body mass index was unchanged. Combined movement with learning TT was effective. Physically active learning paradigms may contribute to meeting daily physical activity guidelines while supporting or even boosting learning.

An AdaBoost Based Approach to Automatic Classification and Detection of Buildings Footprints, Vegetation Areas and Roads from Satellite Images

NASA Astrophysics Data System (ADS)

Gonulalan, Cansu

In recent years, there has been an increasing demand for applications to monitor the targets related to land-use, using remote sensing images. Advances in remote sensing satellites give rise to the research in this area. Many applications ranging from urban growth planning to homeland security have already used the algorithms for automated object recognition from remote sensing imagery. However, they have still problems such as low accuracy on detection of targets, specific algorithms for a specific area etc. In this thesis, we focus on an automatic approach to classify and detect building foot-prints, road networks and vegetation areas. The automatic interpretation of visual data is a comprehensive task in computer vision field. The machine learning approaches improve the capability of classification in an intelligent way. We propose a method, which has high accuracy on detection and classification. The multi class classification is developed for detecting multiple objects. We present an AdaBoost-based approach along with the supervised learning algorithm. The combi- nation of AdaBoost with "Attentional Cascade" is adopted from Viola and Jones [1]. This combination decreases the computation time and gives opportunity to real time applications. For the feature extraction step, our contribution is to combine Haar-like features that include corner, rectangle and Gabor. Among all features, AdaBoost selects only critical features and generates in extremely efficient cascade structured classifier. Finally, we present and evaluate our experimental results. The overall system is tested and high performance of detection is achieved. The precision rate of the final multi-class classifier is over 98%.

Quantum neuromorphic hardware for quantum artificial intelligence

NASA Astrophysics Data System (ADS)

Prati, Enrico

2017-08-01

The development of machine learning methods based on deep learning boosted the field of artificial intelligence towards unprecedented achievements and application in several fields. Such prominent results were made in parallel with the first successful demonstrations of fault tolerant hardware for quantum information processing. To which extent deep learning can take advantage of the existence of a hardware based on qubits behaving as a universal quantum computer is an open question under investigation. Here I review the convergence between the two fields towards implementation of advanced quantum algorithms, including quantum deep learning.

Effects of a Research-Infused Botanical Curriculum on Undergraduates’ Content Knowledge, STEM Competencies, and Attitudes toward Plant Sciences

PubMed Central

Clarke, H. David; Horton, Jonathan L.

2014-01-01

In response to the American Association for the Advancement of Science's Vision and Change in Undergraduate Biology Education initiative, we infused authentic, plant-based research into majors’ courses at a public liberal arts university. Faculty members designed a financially sustainable pedagogical approach, utilizing vertically integrated curricular modules based on undergraduate researchers’ field and laboratory projects. Our goals were to 1) teach botanical concepts, from cells to ecosystems; 2) strengthen competencies in statistical analysis and scientific writing; 3) pique plant science interest; and 4) allow all undergraduates to contribute to genuine research. Our series of inquiry-centered exercises mitigated potential faculty barriers to adopting research-rich curricula, facilitating teaching/research balance by gathering publishable scholarly data during laboratory class periods. Student competencies were assessed with pre- and postcourse quizzes and rubric-graded papers, and attitudes were evaluated with pre- and postcourse surveys. Our revised curriculum increased students’ knowledge and awareness of plant science topics, improved scientific writing, enhanced statistical knowledge, and boosted interest in conducting research. More than 300 classroom students have participated in our program, and data generated from these modules’ assessment allowed faculty and students to present 28 contributed talks or posters and publish three papers in 4 yr. Future steps include analyzing the effects of repeated module exposure on student learning and creating a regional consortium to increase our project's pedagogical impact. PMID:25185223

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

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

2008-03-01

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

Learning optimal embedded cascades.

PubMed

Saberian, Mohammad Javad; Vasconcelos, Nuno

2012-10-01

The problem of automatic and optimal design of embedded object detector cascades is considered. Two main challenges are identified: optimization of the cascade configuration and optimization of individual cascade stages, so as to achieve the best tradeoff between classification accuracy and speed, under a detection rate constraint. Two novel boosting algorithms are proposed to address these problems. The first, RCBoost, formulates boosting as a constrained optimization problem which is solved with a barrier penalty method. The constraint is the target detection rate, which is met at all iterations of the boosting process. This enables the design of embedded cascades of known configuration without extensive cross validation or heuristics. The second, ECBoost, searches over cascade configurations to achieve the optimal tradeoff between classification risk and speed. The two algorithms are combined into an overall boosting procedure, RCECBoost, which optimizes both the cascade configuration and its stages under a detection rate constraint, in a fully automated manner. Extensive experiments in face, car, pedestrian, and panda detection show that the resulting detectors achieve an accuracy versus speed tradeoff superior to those of previous methods.

Boosted Multivariate Trees for Longitudinal Data

PubMed Central

Pande, Amol; Li, Liang; Rajeswaran, Jeevanantham; Ehrlinger, John; Kogalur, Udaya B.; Blackstone, Eugene H.; Ishwaran, Hemant

2017-01-01

Machine learning methods provide a powerful approach for analyzing longitudinal data in which repeated measurements are observed for a subject over time. We boost multivariate trees to fit a novel flexible semi-nonparametric marginal model for longitudinal data. In this model, features are assumed to be nonparametric, while feature-time interactions are modeled semi-nonparametrically utilizing P-splines with estimated smoothing parameter. In order to avoid overfitting, we describe a relatively simple in sample cross-validation method which can be used to estimate the optimal boosting iteration and which has the surprising added benefit of stabilizing certain parameter estimates. Our new multivariate tree boosting method is shown to be highly flexible, robust to covariance misspecification and unbalanced designs, and resistant to overfitting in high dimensions. Feature selection can be used to identify important features and feature-time interactions. An application to longitudinal data of forced 1-second lung expiratory volume (FEV1) for lung transplant patients identifies an important feature-time interaction and illustrates the ease with which our method can find complex relationships in longitudinal data. PMID:29249866

Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

PubMed

Pashaei, Elnaz; Ozen, Mustafa; Aydin, Nizamettin

2015-08-01

Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

New York City Goes to College: A First Look at Patterns of College Enrollment, Persistence, and Degree Attainment for NYC High School Students. Brief

ERIC Educational Resources Information Center

Coca, Vanessa

2014-01-01

Over the past 15 years, in New York City and across the country, expectations for high schools--and high school students--have changed dramatically. Increasingly, high schools are being asked not only to reduce dropout rates and boost graduation rates, but also to impart knowledge, skills, and experiences that will prepare students to succeed in…

Improved semi-supervised online boosting for object tracking

NASA Astrophysics Data System (ADS)

Li, Yicui; Qi, Lin; Tan, Shukun

2016-10-01

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.

Comparing ensemble learning methods based on decision tree classifiers for protein fold recognition.

PubMed

Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi

2014-01-01

In this paper, some methods for ensemble learning of protein fold recognition based on a decision tree (DT) are compared and contrasted against each other over three datasets taken from the literature. According to previously reported studies, the features of the datasets are divided into some groups. Then, for each of these groups, three ensemble classifiers, namely, random forest, rotation forest and AdaBoost.M1 are employed. Also, some fusion methods are introduced for combining the ensemble classifiers obtained in the previous step. After this step, three classifiers are produced based on the combination of classifiers of types random forest, rotation forest and AdaBoost.M1. Finally, the three different classifiers achieved are combined to make an overall classifier. Experimental results show that the overall classifier obtained by the genetic algorithm (GA) weighting fusion method, is the best one in comparison to previously applied methods in terms of classification accuracy.

Designing boosting ensemble of relational fuzzy systems.

PubMed

Scherer, Rafał

2010-10-01

A method frequently used in classification systems for improving classification accuracy is to combine outputs of several classifiers. Among various types of classifiers, fuzzy ones are tempting because of using intelligible fuzzy if-then rules. In the paper we build an AdaBoost ensemble of relational neuro-fuzzy classifiers. Relational fuzzy systems bond input and output fuzzy linguistic values by a binary relation; thus, fuzzy rules have additional, comparing to traditional fuzzy systems, weights - elements of a fuzzy relation matrix. Thanks to this the system is better adjustable to data during learning. In the paper an ensemble of relational fuzzy systems is proposed. The problem is that such an ensemble contains separate rule bases which cannot be directly merged. As systems are separate, we cannot treat fuzzy rules coming from different systems as rules from the same (single) system. In the paper, the problem is addressed by a novel design of fuzzy systems constituting the ensemble, resulting in normalization of individual rule bases during learning. The method described in the paper is tested on several known benchmarks and compared with other machine learning solutions from the literature.

Application of adaptive boosting to EP-derived multilayer feed-forward neural networks (MLFN) to improve benign/malignant breast cancer classification

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Masters, Timothy D.; Lo, Joseph Y.; McKee, Dan

2001-07-01

A new neural network technology was developed for improving the benign/malignant diagnosis of breast cancer using mammogram findings. A new paradigm, Adaptive Boosting (AB), uses a markedly different theory in solutioning Computational Intelligence (CI) problems. AB, a new machine learning paradigm, focuses on finding weak learning algorithm(s) that initially need to provide slightly better than random performance (i.e., approximately 55%) when processing a mammogram training set. Then, by successive development of additional architectures (using the mammogram training set), the adaptive boosting process improves the performance of the basic Evolutionary Programming derived neural network architectures. The results of these several EP-derived hybrid architectures are then intelligently combined and tested using a similar validation mammogram data set. Optimization focused on improving specificity and positive predictive value at very high sensitivities, where an analysis of the performance of the hybrid would be most meaningful. Using the DUKE mammogram database of 500 biopsy proven samples, on average this hybrid was able to achieve (under statistical 5-fold cross-validation) a specificity of 48.3% and a positive predictive value (PPV) of 51.8% while maintaining 100% sensitivity. At 97% sensitivity, a specificity of 56.6% and a PPV of 55.8% were obtained.

The Lightbulb Moment - the importance of fieldwork as a link between the classroom and the real world

NASA Astrophysics Data System (ADS)

Bambridge, Helen; Barraclough, Alison

2016-04-01

All teachers love the light bulb moment; that moment when a student says, "Ah ha, I get it!" and makes the move from remembering to understanding. This boosts their confidence, leading to increased engagement with the subject and, in turn, increased progress and enjoyment. For many young geologists such moments occur outside the classroom when they are given the opportunity to carry out fieldwork. Understanding involves making links and investigations within the field allow students to make these essential links between actual observations and theory. All A-Level geologists at Sir William Borlase's Grammar School are given the opportunity to take part in a five day fieldtrip. This poster celebrates key 'lightbulb moments' that occurred during fieldwork to the famous Jurassic Coast, England. Students investigated the geological setting at Kimmeridge Bay where the cyclic sedimentation in the Lias helped their understanding of orbital obliquity and precession. The processes of fossilisation and preservation were examined at West Bay and in the upper Jurassic at Bowleaze Cove, which also enabled students to appreciate the incompleteness of the fossil record. Modern day processes and coastal management at Swanage allowed sixth formers to understand the non-permanent nature of landscapes and the difficulties encountered when attempting to conserve eroding areas. Therefore, the chance to get outside the classroom and study in the field is an invaluable opportunity for students to make those all important links through investigative learning and to develop a deeper understanding of the world around them.

California Community Colleges: Vital to the Economy

ERIC Educational Resources Information Center

California Community Colleges, Chancellor's Office, 2014

2014-01-01

The California Community Colleges play an important role in boosting the state's economy by serving more than 2.3 million students a year. In fact, one out of three community college students in the U.S. is enrolled in a California community college, making it the nation's largest system of higher education. Their 112 colleges provide students…

Making the Familiar Strange: How a Culture Audit Can Boost Your Advising Impact

ERIC Educational Resources Information Center

Ahren, Chad; Ryan, Helen-Grace; Niskode-Dossett, Amanda Suniti

2009-01-01

Student organizations enhance college students' experiences and contribute to the vitality of campus life. As staff and faculty, the authors are regularly called on to advise these groups. Good advising can help an organization stay connected with its true mission. One tool that can help advisors navigate and grasp the culture of student…

A Randomized Experiment Using Absenteeism Information to "Nudge" Attendance. REL 2017-252

ERIC Educational Resources Information Center

Rogers, Todd; Duncan, Teresa; Wolford, Tonya; Ternovski, John; Subramanyam, Shruthi; Reitano, Adrienne

2017-01-01

Reducing student absenteeism is a key part of the School District of Philadelphia's plan to boost graduation rates. One of the district's goals is to increase guardians' awareness of absenteeism, with the hope that greater awareness will lead to guardians' taking a more active role in improving their student's attendance and academic performance.…

Advanced Math: Closing the Equity Gap. Math Works

ERIC Educational Resources Information Center

Achieve, Inc., 2013

2013-01-01

Minority and low-income students are less likely to have access to, enroll in and succeed in higher-level math courses in high school than their more advantaged peers. Under these circumstances, higher-level math courses function not as the intellectual and practical boost they should be, but as a filter that screens students out of the pathway to…

Early College Can Boost College Success Rates for Low-Income, First-Generation Students

ERIC Educational Resources Information Center

Ndiaye, Mamadou; Wolfe, Rebecca E.

2016-01-01

Early college high school models are designed to encourage and assist traditionally underrepresented groups of students- low income, Latino, and African-American- to persist in and graduate from high school while earning college credit. Some of the models target high school dropouts, with the aim of helping them acquire the education and training…

Framework Fuels the Need to Read: Strategies Boost Literacy of Students in Content-Area Classes

ERIC Educational Resources Information Center

Schoenbach, Ruth; Greenleaf, Cynthia L.; Hale, Gina

2010-01-01

Middle and high school teachers across academic disciplines face increased pressure to address the Common Core State Standards (CCSS) for English language arts and for literacy in history/social studies, science, and technical subjects. This means that the responsibility of preparing students to read, write, talk, and think critically about…

Boosting Student Achievement: The Effect of Comprehensive School Reform on Student Achievement

ERIC Educational Resources Information Center

Gross, Betheny; Booker, T. Kevin; Goldhaber, Dan

2009-01-01

Between the late 1980s and early 2000s, schools, districts, states, and the federal government devoted enormous resources to the implementation of Comprehensive School Reform (CSR) models. With more than 1.6 billion federal dollars distributed through the Comprehensive School Reform Demonstration (CSRD) project and its successor, the CSR project,…

Big6 Turbotools and Synthesis

ERIC Educational Resources Information Center

Tooley, Melinda

2005-01-01

The different tools that are helpful during the Synthesis stage, their role in boosting students abilities in Synthesis and the way in which it can be customized to meet the needs of each group of students are discussed. Big6 TurboTools offers several tools to help complete the task. In Synthesis stage, these same tools along with Turbo Report and…

Summer Boost: Challenges and Opportunities in Summer Programs for Rising Kindergarten Students

ERIC Educational Resources Information Center

Condliffe, Barbara; Foster, Anna; Jacob, Robin

2017-01-01

There is a growing belief that access to academic opportunities during the summer can help close the achievement gap between low-income students and their higher-income peers. But while significant research is emerging on summer programs for school-age children, information on the preschool period is limited. The Expanding Children's Early…

Seven Strategies of Highly Effective Readers: Using Cognitive Research to Boost K-8 Achievement

ERIC Educational Resources Information Center

McEwan, Elaine K.

2004-01-01

How do some students extract complex information from advanced reading materials while others struggle to find the meaning of even simple passages? What characteristics do strategic readers exhibit that others don't possess? Unlocking the cognitive strategies of exceptional readers means finding ways to teach every student to read strategically,…

Evaluation of machine learning algorithms for classification of primary biological aerosol using a new UV-LIF spectrometer

NASA Astrophysics Data System (ADS)

Ruske, Simon; Topping, David O.; Foot, Virginia E.; Kaye, Paul H.; Stanley, Warren R.; Crawford, Ian; Morse, Andrew P.; Gallagher, Martin W.

2017-03-01

Characterisation of bioaerosols has important implications within environment and public health sectors. Recent developments in ultraviolet light-induced fluorescence (UV-LIF) detectors such as the Wideband Integrated Bioaerosol Spectrometer (WIBS) and the newly introduced Multiparameter Bioaerosol Spectrometer (MBS) have allowed for the real-time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal spores and pollen.This new generation of instruments has enabled ever larger data sets to be compiled with the aim of studying more complex environments. In real world data sets, particularly those from an urban environment, the population may be dominated by non-biological fluorescent interferents, bringing into question the accuracy of measurements of quantities such as concentrations. It is therefore imperative that we validate the performance of different algorithms which can be used for the task of classification.For unsupervised learning we tested hierarchical agglomerative clustering with various different linkages. For supervised learning, 11 methods were tested, including decision trees, ensemble methods (random forests, gradient boosting and AdaBoost), two implementations for support vector machines (libsvm and liblinear) and Gaussian methods (Gaussian naïve Bayesian, quadratic and linear discriminant analysis, the k-nearest neighbours algorithm and artificial neural networks).The methods were applied to two different data sets produced using the new MBS, which provides multichannel UV-LIF fluorescence signatures for single airborne biological particles. The first data set contained mixed PSLs and the second contained a variety of laboratory-generated aerosol.Clustering in general performs slightly worse than the supervised learning methods, correctly classifying, at best, only 67. 6 and 91. 1 % for the two data sets respectively. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 82. 8 and 98. 27 % of the testing data, respectively, across the two data sets.A possible alternative to gradient boosting is neural networks. We do however note that this method requires much more user input than the other methods, and we suggest that further research should be conducted using this method, especially using parallelised hardware such as the GPU, which would allow for larger networks to be trained, which could possibly yield better results.We also saw that some methods, such as clustering, failed to utilise the additional shape information provided by the instrument, whilst for others, such as the decision trees, ensemble methods and neural networks, improved performance could be attained with the inclusion of such information.

Recent Flight Results of the TRMM Kalman Filter

NASA Technical Reports Server (NTRS)

Andrews, Stephen F.; Bilanow, Stephen; Bauer, Frank (Technical Monitor)

2002-01-01

The Tropical Rainfall Measuring Mission (TRMM) spacecraft is a nadir pointing spacecraft that nominally controls the roll and pitch attitude based on the Earth Sensor Assembly (ESA) output. TRMM's nominal orbit altitude was 350 km, until raised to 402 km to prolong mission life. During the boost, the ESA experienced a decreasing signal to noise ratio, until sun interference at 393 km altitude made the ESA data unreliable for attitude determination. At that point, the backup attitude determination algorithm, an extended Kalman filter, was enabled. After the boost finished, TRMM reacquired its nadir-pointing attitude, and continued its mission. This paper will briefly discuss the boost and the decision to turn on the backup attitude determination algorithm. A description of the extended Kalman filter algorithm will be given. In addition, flight results from analyzing attitude data and the results of software changes made onboard TRMM will be discussed. Some lessons learned are presented.

Integrating Enhanced STEM Themes in the UTEP CAREERS Weather Camp for Youth

NASA Astrophysics Data System (ADS)

Güereque, M.; Olgin, J. G.; Kier, M. W.; Winston, C. E.; Fitzgerald, R. M.; Morris, V. R.

2014-12-01

The NOAA Center for Atmospheric Science (NCAS) sponsors a network of high school and middle school summer camps entitled "Channeling Atmospheric Research into Educational Experiences Reaching Students program, CAREERS". These camps are conducted nationwide at NCAS academic partners; the University of Texas at El Paso (UTEP), Howard University (HU), University of Puerto Rico at Mayagüez (UPRM), and Jackson State University (JSU). The goals of these camps are to increase the interest of secondary school (HS) students in atmospheric and weather related sciences, target under-represented students, and to ultimately boost their college enrollment in STEM related fields. For 2014 at UTEP, the annual student-outreach weather camp program underwent a thematic overhaul that sought to incorporate more of the geological and environmental context of the region. Doctoral students were allowed to assume greater responsibility for the design, development and implementation of the camp activities. The prevailing assumption was that these Ph.D. students were better suited for peer mentoring, bridging the age and interest gap, and delivering the material through the modern technologies and modes of communication. The redesigned approach focused on the identification of climate drivers within the region and this concept formed a thread throughout the planning and design of the camp modules. The outcome resulted in the incorporation of project based learning (PBL) activities, field excursions, and deployment of weather instrumentation, for explaining regional climate processes and events. Standardized surveys were administered to camp participants to evaluate the efficacy, as well as student perceptions of the camp and its activities. Results will be presented that are based on qualitative and quantitative analysis of student responses.

Effects of Mobile Augmented Reality Learning Compared to Textbook Learning on Medical Students: Randomized Controlled Pilot Study

PubMed Central

2013-01-01

Background By adding new levels of experience, mobile Augmented Reality (mAR) can significantly increase the attractiveness of mobile learning applications in medical education. Objective To compare the impact of the heightened realism of a self-developed mAR blended learning environment (mARble) on learners to textbook material, especially for ethically sensitive subjects such as forensic medicine, while taking into account basic psychological aspects (usability and higher level of emotional involvement) as well as learning outcomes (increased learning efficiency). Methods A prestudy was conducted based on a convenience sample of 10 third-year medical students. The initial emotional status was captured using the “Profile of Mood States” questionnaire (POMS, German variation); previous knowledge about forensic medicine was determined using a 10-item single-choice (SC) test. During the 30-minute learning period, the students were randomized into two groups: the first group consisted of pairs of students, each equipped with one iPhone with a preinstalled copy of mARble, while the second group was provided with textbook material. Subsequently, both groups were asked to once again complete the POMS questionnaire and SC test to measure changes in emotional state and knowledge gain. Usability as well as pragmatic and hedonic qualities of the learning material was captured using AttrakDiff2 questionnaires. Data evaluation was conducted anonymously. Descriptive statistics for the score in total and the subgroups were calculated before and after the intervention. The scores of both groups were tested against each other using paired and unpaired signed-rank tests. An item analysis was performed for the SC test to objectify difficulty and selectivity. Results Statistically significant, the mARble group (6/10) showed greater knowledge gain than the control group (4/10) (Wilcoxon z=2.232, P=.03). The item analysis of the SC test showed a difficulty of P=0.768 (s=0.09) and a selectivity of RPB=0.2. For mARble, fatigue (z=2.214, P=.03) and numbness (z=2.07, P=.04) decreased with statistical significance when comparing pre- and post-tests. Vigor rose slightly, while irritability did not increase significantly. Changes in the control group were insignificant. Regarding hedonic quality (identification, stimulation, attractiveness), there were significant differences between mARble (mean 1.179, CI −0.440 to 0.440) and the book chapter (mean −0.982, CI −0.959 to 0.959); the pragmatic quality mean only differed slightly. Conclusions The mARble group performed considerably better regarding learning efficiency; there are hints for activating components of the mAR concept that may serve to fascinate the participants and possibly boost interest in the topic for the remainder of the class. While the small sample size reduces our study’s conclusiveness, its design seems appropriate for determining the effects of interactive eLearning material with respect to emotions, learning efficiency, and hedonic and pragmatic qualities using a larger group. Trial Registration German Clinical Trial Register (DRKS), DRKS-ID: DRKS00004685; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00004685. PMID:23963306

Effects of mobile augmented reality learning compared to textbook learning on medical students: randomized controlled pilot study.

PubMed

Albrecht, Urs-Vito; Folta-Schoofs, Kristian; Behrends, Marianne; von Jan, Ute

2013-08-20

By adding new levels of experience, mobile Augmented Reality (mAR) can significantly increase the attractiveness of mobile learning applications in medical education. To compare the impact of the heightened realism of a self-developed mAR blended learning environment (mARble) on learners to textbook material, especially for ethically sensitive subjects such as forensic medicine, while taking into account basic psychological aspects (usability and higher level of emotional involvement) as well as learning outcomes (increased learning efficiency). A prestudy was conducted based on a convenience sample of 10 third-year medical students. The initial emotional status was captured using the "Profile of Mood States" questionnaire (POMS, German variation); previous knowledge about forensic medicine was determined using a 10-item single-choice (SC) test. During the 30-minute learning period, the students were randomized into two groups: the first group consisted of pairs of students, each equipped with one iPhone with a preinstalled copy of mARble, while the second group was provided with textbook material. Subsequently, both groups were asked to once again complete the POMS questionnaire and SC test to measure changes in emotional state and knowledge gain. Usability as well as pragmatic and hedonic qualities of the learning material was captured using AttrakDiff2 questionnaires. Data evaluation was conducted anonymously. Descriptive statistics for the score in total and the subgroups were calculated before and after the intervention. The scores of both groups were tested against each other using paired and unpaired signed-rank tests. An item analysis was performed for the SC test to objectify difficulty and selectivity. Statistically significant, the mARble group (6/10) showed greater knowledge gain than the control group (4/10) (Wilcoxon z=2.232, P=.03). The item analysis of the SC test showed a difficulty of P=0.768 (s=0.09) and a selectivity of RPB=0.2. For mARble, fatigue (z=2.214, P=.03) and numbness (z=2.07, P=.04) decreased with statistical significance when comparing pre- and post-tests. Vigor rose slightly, while irritability did not increase significantly. Changes in the control group were insignificant. Regarding hedonic quality (identification, stimulation, attractiveness), there were significant differences between mARble (mean 1.179, CI -0.440 to 0.440) and the book chapter (mean -0.982, CI -0.959 to 0.959); the pragmatic quality mean only differed slightly. The mARble group performed considerably better regarding learning efficiency; there are hints for activating components of the mAR concept that may serve to fascinate the participants and possibly boost interest in the topic for the remainder of the class. While the small sample size reduces our study's conclusiveness, its design seems appropriate for determining the effects of interactive eLearning material with respect to emotions, learning efficiency, and hedonic and pragmatic qualities using a larger group. German Clinical Trial Register (DRKS), DRKS-ID: DRKS00004685; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00004685.

New York City Goes to College: A First Look at Patterns of College Enrollment, Persistence, and Degree Attainment for New York City High School Students. Report

ERIC Educational Resources Information Center

Coca, Vanessa

2014-01-01

Over the past 15 years, in New York City and across the country, expectations for high schools--and high school students--have changed dramatically. Increasingly, high schools are being asked not only to reduce dropout rates and boost graduation rates, but also to impart knowledge, skills, and experiences that will prepare students to succeed in…

New York City Goes to College: A First Look at Patterns of College Enrollment, Persistence, and Degree Attainment for NYC High School Students. Technical Appendices

ERIC Educational Resources Information Center

Coca, Vanessa

2014-01-01

Over the past 15 years, in New York City and across the country, expectations for high schools--and high school students--have changed dramatically. Increasingly, high schools are being asked not only to reduce dropout rates and boost graduation rates, but also to impart knowledge, skills, and experiences that will prepare students to succeed in…

Biology Question Generation from a Semantic Network

NASA Astrophysics Data System (ADS)

Zhang, Lishan

Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions. To boost students' learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student's current competence so that a suitable question could be selected based on the student's previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group. To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators. A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from Amazon Mechanical Turk, it turned out that the two types of questions performed very closely on all the three measures.

The application of online transcranial random noise stimulation and perceptual learning in the improvement of visual functions in mild myopia.

PubMed

Camilleri, Rebecca; Pavan, Andrea; Campana, Gianluca

2016-08-01

It has recently been demonstrated how perceptual learning, that is an improvement in a sensory/perceptual task upon practice, can be boosted by concurrent high-frequency transcranial random noise stimulation (tRNS). It has also been shown that perceptual learning can generalize and produce an improvement of visual functions in participants with mild refractive defects. By using three different groups of participants (single-blind study), we tested the efficacy of a short training (8 sessions) using a single Gabor contrast-detection task with concurrent hf-tRNS in comparison with the same training with sham stimulation or hf-tRNS with no concurrent training, in improving visual acuity (VA) and contrast sensitivity (CS) of individuals with uncorrected mild myopia. A short training with a contrast detection task is able to improve VA and CS only if coupled with hf-tRNS, whereas no effect on VA and marginal effects on CS are seen with the sole administration of hf-tRNS. Our results support the idea that, by boosting the rate of perceptual learning via the modulation of neuronal plasticity, hf-tRNS can be successfully used to reduce the duration of the perceptual training and/or to increase its efficacy in producing perceptual learning and generalization to improved VA and CS in individuals with uncorrected mild myopia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Long- and short-term retention of traditional instruction vs. previously tested tactual vs. innovative tactual resources on the achievement and attitudes of second-grade students in science

NASA Astrophysics Data System (ADS)

Mitchell, Sherese A.

This researcher investigated the long- and short-term retention of information using traditional instruction versus previously tested tactual resources versus innovative tactual resources on the achievement and attitudes of second-grade students in science. The processing of new and difficult knowledge has challenged many young children who tend to be kinesthetic or tactual learners. In compliance with the National Science Education Standards, students should be actively engaged in their own learning. Therefore, to boost student achievement in science, the use of tactual materials was implemented. The sample included 67 second-grade students drawn from three heterogeneously grouped classes in a low socio-economic neighborhood. It consisted of 30 females and 37 males of which 97 percent were African American, 2 percent were Hispanic, and 1 percent Other. Students were unaware of their diagnosed learning-style preference(s) during the instruction and assessment phases of the study. Therefore, students' knowledge of their learning-style preferences could not have had any impact on their achievement or attitudes. A counterbalanced research design was employed. During the first session, Group 1 was taught with previously tested tactual resources (Electroboards, Flip Chutes, Fact Wheels, and Fact Fans), and Group 3 was taught traditionally. During the second session of instruction, Group 1 received instruction with innovative tactual resources, Group 2 received traditional instruction, Group 3 received instruction with previously tested tactual resources. During the final session of instruction, Group 1 received traditional instruction, Group 2 received instruction with previously tested tactual resources, and Group 3 received instruction with innovative tactual resources. The results indicated that the use of tactual materials, regardless of whether they were previously tested or innovative, produced higher achievement gains and more positive attitudes than traditional instruction. The lowest gains in the General Linear Model procedure were in the traditional condition. An omnibus ANOVA revealed that the three conditions yielded significantly different results (F(2,65) = 4.66, p = .013). Pairwise analyses of mean differences indicated that the means of both the innovative tactual resources and previously tested tactual resources were significantly different from the means of the traditional condition, but were not significantly different from each other. A series of single factor t-tests was performed on the items of the attitude scale. Most ratings differed from 3.0. The single-sample t-tests indicated that all the ratings were significantly higher than 3.0. This result revealed that the traditional instruction was statistically less effective than the other two tactual treatments.

1998 News Releases | NREL

Science.gov Websites

Community - (5/4/98) High School Students Compete in Solar-Powered Bike Race - (4/23/98) New Battery Testing Facility Could Boost Future of Electric Vehicles - (4/21/98) NREL Publications Win Awards - (4/17/98) Local Students Celebrate Earth Day at NREL - (4/17/98) One-Step Device Converts Water, Sunlight Into Fuel of the

Lightening the Load: A Look at Four Ways that Community Schools Can Support Effective Teaching

ERIC Educational Resources Information Center

Chang, Theodora

2012-01-01

The job of a teacher these days seems to stretch beyond the walls of a classroom, especially in primary and secondary schools in high-poverty communities. There are stories of teachers purchasing food for hungry students, going door to door in neighborhoods to boost parent involvement in school, and referring students and families to health…

Boosting Completion at Community Colleges: Time, Choice, Structure and the Significant Role of States. Policy Brief

ERIC Educational Resources Information Center

Complete College America, 2010

2010-01-01

A new American majority of students is emerging on campuses, especially at community colleges. These students must delicately balance long hours at jobs they must have with the higher education they desire. Even though this emerging majority has fundamentally different needs, American higher education in general has been slow to change, continuing…

Moving the Needle: Exploring Key Levers to Boost College Readiness Among Black and Latino Males in NYC

ERIC Educational Resources Information Center

Villavicencio, Adriana; Bhattacharya, Dyuti; Guidry, Brandon

2013-01-01

Increasingly, school districts are recognizing that high school graduation rates may not be the ultimate measure of success, as evidence accumulates that students who obtain a college degree do markedly better than students who only graduate from high school. In New York City, while graduation rates have increased dramatically over the last…

Motivation Matters: How New Research Can Help Teachers Boost Student Engagement

ERIC Educational Resources Information Center

Headden, Susan; McKay, Susan

2015-01-01

Quitting in the face of hard work is never the response a teacher wants to see, but it's one that threatens to become more common as academic pressures rise. The new Common Core State Standards, the latest in a decades-long effort to drive educational improvement, soon will be setting unprecedented expectations for the performance of students,…

Achievement Emotions as Predictors of High School Science Success Among African-American and European American Students

NASA Astrophysics Data System (ADS)

Bowe, Marilyn Louise Simmons

The literature includes few studies of the interrelations of achievement goals and achievement emotions with respect to minority students and science achievement. The objective of this study was to test the control-value theory (CVT) of achievement emotions to determine if the eight discrete achievement emotions would be predictive of test scores on the High School Graduation Test (GHSGT)-Science for African-American compared to European-American science students. Convenience cluster sampling was employed to select 160 students who were all juniors in the same public high school at the time that they took the GHSGT-Science. The central research question for this study aimed to uncover whether any of the eight achievement emotions identified in CVT would contribute significantly to the predictability of science achievement as measured by GHSGT-Science scores. Data were collected using a nonexperimental, cross sectional design survey. Data were analyzed using a hierarchal, forced entry, multiple regression analysis. Key results indicated that the eight achievement emotions were predictive of GHSGT-Science score outcomes. Positive social change at the individual level could reflect a boost in confidence for African American science students and help decrease the achievement gap in science, technology, engineering, and mathematics (STEM) endeavors between European Americans and African-American students. Educators may consider the importance of achievement emotions in science outcomes by including social emotional learning (SEL) as a part of the regular science curriculum. Future researchers should repeat the study in a school district where the population is available to support the desired cluster sample of equal parts European Americans to African Americans and male to female students.

Thermal Management and Packaging Reliability (Text Version) |

Science.gov Websites

Transportation Research | NREL Thermal Management and Packaging Reliability (Text Version ) Thermal Management and Packaging Reliability (Text Version) Learn how NREL's thermal management and ;Boosting Thermal Management & Reliability of Vehicle Power Electronics." Better power electronics

Lime, Fertilizer Cottonwood Tests

Treesearch

B. G. Blackmon; W. M. Broadfoot

1969-01-01

As eastern cottonwood is cut increasingly for pulp and other wood products, efforts to boost its production in Mississippi are growing. To learn more about fertilizer requirements of the species, the Southern Hardwoods Laboratory at Stoneville recently tested four common bottomland soils in which cottonwood grows.

An ensemble boosting model for predicting transfer to the pediatric intensive care unit.

PubMed

Rubin, Jonathan; Potes, Cristhian; Xu-Wilson, Minnan; Dong, Junzi; Rahman, Asif; Nguyen, Hiep; Moromisato, David

2018-04-01

Early deterioration indicators have the potential to alert hospital care staff in advance of adverse events, such as patients requiring an increased level of care, or the need for rapid response teams to be called. Our work focuses on the problem of predicting the transfer of pediatric patients from the general ward of a hospital to the pediatric intensive care unit. The development of a data-driven pediatric early deterioration indicator for use by clinicians with the purpose of predicting encounters where transfer from the general ward to the PICU is likely. Using data collected over 5.5 years from the electronic health records of two medical facilities, we develop machine learning classifiers based on adaptive boosting and gradient tree boosting. We further combine these learned classifiers into an ensemble model and compare its performance to a modified pediatric early warning score (PEWS) baseline that relies on expert defined guidelines. To gauge model generalizability, we perform an inter-facility evaluation where we train our algorithm on data from one facility and perform evaluation on a hidden test dataset from a separate facility. We show that improvements are witnessed over the modified PEWS baseline in accuracy (0.77 vs. 0.69), sensitivity (0.80 vs. 0.68), specificity (0.74 vs. 0.70) and AUROC (0.85 vs. 0.73). Data-driven, machine learning algorithms can improve PICU transfer prediction accuracy compared to expertly defined systems, such as a modified PEWS, but care must be taken in the training of such approaches to avoid inadvertently introducing bias into the outcomes of these systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Exogenous Attention Enables Perceptual Learning

PubMed Central

Szpiro, Sarit F. A.; Carrasco, Marisa

2015-01-01

Practice can improve visual perception, and these improvements are considered to be a form of brain plasticity. Training-induced learning is time-consuming and requires hundreds of trials across multiple days. The process of learning acquisition is understudied. Can learning acquisition be potentiated by manipulating visual attentional cues? We developed a protocol in which we used task-irrelevant cues for between-groups manipulation of attention during training. We found that training with exogenous attention can enable the acquisition of learning. Remarkably, this learning was maintained even when observers were subsequently tested under neutral conditions, which indicates that a change in perception was involved. Our study is the first to isolate the effects of exogenous attention and to demonstrate its efficacy to enable learning. We propose that exogenous attention boosts perceptual learning by enhancing stimulus encoding. PMID:26502745

"Moving the Needle": Exploring Key Levers to Boost College Readiness among Black and Latino Males in New York City. Report

ERIC Educational Resources Information Center

Villavicencio, Adriana; Bhattacharya, Dyuti; Guidry, Brandon

2013-01-01

College readiness is becoming an increasingly important standard by which to measure school success and student achievement. While high school graduation and dropout prevention remain critical issues for educators, there is a substantial gap in outcomes between students who only earn a high school diploma and those who go on to obtain a college…

Ensuring that No Child is Left Behind. How are Student Health Risks & Resilience Related to the Academic Progress of Schools?

ERIC Educational Resources Information Center

Hanson, Thomas L.; Austin, Gregory; Lee-Bayha, June

2004-01-01

Public schools have come under enormous pressure in recent years to demonstrate academic gains and to address deeply rooted disparities among students of different races, ethnic groups, and income levels. Clearly, boosting academic achievement should be a top priority. Less evident, however, is the long-term effect of supporting this goal by…

Senior Adults and Computers in the 1990s.

ERIC Educational Resources Information Center

Lawhon, Tommie; And Others

1996-01-01

Older adults use computers for entertainment, education, and creative and business endeavors. Computer training helps them increase productivity, learn skills, and boost short-term memory. Electronic mail, online services, and the Internet encourage socialization. Adapted technology helps disabled and ill elders use computers. (SK)

Application of LogitBoost Classifier for Traceability Using SNP Chip Data

PubMed Central

Kang, Hyunsung; Cho, Seoae; Kim, Heebal; Seo, Kang-Seok

2015-01-01

Consumer attention to food safety has increased rapidly due to animal-related diseases; therefore, it is important to identify their places of origin (POO) for safety purposes. However, only a few studies have addressed this issue and focused on machine learning-based approaches. In the present study, classification analyses were performed using a customized SNP chip for POO prediction. To accomplish this, 4,122 pigs originating from 104 farms were genotyped using the SNP chip. Several factors were considered to establish the best prediction model based on these data. We also assessed the applicability of the suggested model using a kinship coefficient-filtering approach. Our results showed that the LogitBoost-based prediction model outperformed other classifiers in terms of classification performance under most conditions. Specifically, a greater level of accuracy was observed when a higher kinship-based cutoff was employed. These results demonstrated the applicability of a machine learning-based approach using SNP chip data for practical traceability. PMID:26436917

Application of LogitBoost Classifier for Traceability Using SNP Chip Data.

PubMed

Kim, Kwondo; Seo, Minseok; Kang, Hyunsung; Cho, Seoae; Kim, Heebal; Seo, Kang-Seok

2015-01-01

Consumer attention to food safety has increased rapidly due to animal-related diseases; therefore, it is important to identify their places of origin (POO) for safety purposes. However, only a few studies have addressed this issue and focused on machine learning-based approaches. In the present study, classification analyses were performed using a customized SNP chip for POO prediction. To accomplish this, 4,122 pigs originating from 104 farms were genotyped using the SNP chip. Several factors were considered to establish the best prediction model based on these data. We also assessed the applicability of the suggested model using a kinship coefficient-filtering approach. Our results showed that the LogitBoost-based prediction model outperformed other classifiers in terms of classification performance under most conditions. Specifically, a greater level of accuracy was observed when a higher kinship-based cutoff was employed. These results demonstrated the applicability of a machine learning-based approach using SNP chip data for practical traceability.

A comparison of machine learning and Bayesian modelling for molecular serotyping.

PubMed

Newton, Richard; Wernisch, Lorenz

2017-08-11

Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological insights, which we illustrate with an example.

A boosted optimal linear learner for retinal vessel segmentation

NASA Astrophysics Data System (ADS)

Poletti, E.; Grisan, E.

2014-03-01

Ocular fundus images provide important information about retinal degeneration, which may be related to acute pathologies or to early signs of systemic diseases. An automatic and quantitative assessment of vessel morphological features, such as diameters and tortuosity, can improve clinical diagnosis and evaluation of retinopathy. At variance with available methods, we propose a data-driven approach, in which the system learns a set of optimal discriminative convolution kernels (linear learner). The set is progressively built based on an ADA-boost sample weighting scheme, providing seamless integration between linear learner estimation and classification. In order to capture the vessel appearance changes at different scales, the kernels are estimated on a pyramidal decomposition of the training samples. The set is employed as a rotating bank of matched filters, whose response is used by the boosted linear classifier to provide a classification of each image pixel into the two classes of interest (vessel/background). We tested the approach fundus images available from the DRIVE dataset. We show that the segmentation performance yields an accuracy of 0.94.

That Entrepreneurial Spirit

ERIC Educational Resources Information Center

Lum, Lydia

2012-01-01

When Tim Clevenger became executive director of the University of Oregon Alumni Association in 2011, he was dismayed to learn that revenue, including paid memberships, was steadily declining. The association staff and board of directors considered multiple strategies to boost earnings, with stabilizing and growing dues revenue high on the list.…

Learning and Parallelization Boost Constraint Search

ERIC Educational Resources Information Center

Yun, Xi

2013-01-01

Constraint satisfaction problems are a powerful way to abstract and represent academic and real-world problems from both artificial intelligence and operations research. A constraint satisfaction problem is typically addressed by a sequential constraint solver running on a single processor. Rather than construct a new, parallel solver, this work…

Videogames: Multisensory Incentives Boosting Multiple Intelligences in Primary Education

ERIC Educational Resources Information Center

del Moral-Pérez, Mª Esther; Fernández-García, Laura Carlota; Guzmán-Duque, Alba Patricia

2015-01-01

Introduction: Our research focused on studying the extent to which the planned, systematic use of educational videogames can result in the generation of learning contexts conducive to developing Multiple Intelligences (MIs) amongst schoolchildren. Methodology: A twofold methodological approach was adopted: a) qualitative: previous assessment and…

Cortical rewiring and information storage

NASA Astrophysics Data System (ADS)

Chklovskii, D. B.; Mel, B. W.; Svoboda, K.

2004-10-01

Current thinking about long-term memory in the cortex is focused on changes in the strengths of connections between neurons. But ongoing structural plasticity in the adult brain, including synapse formation/elimination and remodelling of axons and dendrites, suggests that memory could also depend on learning-induced changes in the cortical `wiring diagram'. Given that the cortex is sparsely connected, wiring plasticity could provide a substantial boost in storage capacity, although at a cost of more elaborate biological machinery and slower learning.

Shopping for Dollars? Try This List!

ERIC Educational Resources Information Center

DiGeronimo, Joseph

1991-01-01

A California school superintendent presents clever savings tips, including boosting average daily attendance, sparing new hires, bird dogging insurance interest, disposing of surplus school property, recruiting students attending nonpublic schools, creating more classroom space, contracting for part-time help, reducing vandalism, marketing staff…

Lavosier Measures with Polymers.

ERIC Educational Resources Information Center

Goates, Wayne

2000-01-01

Presents a creative, hands-on activity for teaching measurement skills inspired by Antoine Laurent Lavosier and a product called polyacrylamide spikes for students to develop their metric measurement skills and boost their math proficiency as they interpret data and results from their investigations. (ASK)

Education Matters, June 2010

ERIC Educational Resources Information Center

Beckner, Gary, Ed.

2010-01-01

"Education Matters" is the monthly newsletter of the Association of American Educators (AAE), an organization dedicated to advancing the American teaching profession through personal growth, professional development, teacher advocacy and protection. This issue of the newsletter includes: (1) Coaching Teachers Boosts Student Reading:…

Post-boosting of classification boundary for imbalanced data using geometric mean.

PubMed

Du, Jie; Vong, Chi-Man; Pun, Chi-Man; Wong, Pak-Kin; Ip, Weng-Fai

2017-12-01

In this paper, a novel imbalance learning method for binary classes is proposed, named as Post-Boosting of classification boundary for Imbalanced data (PBI), which can significantly improve the performance of any trained neural networks (NN) classification boundary. The procedure of PBI simply consists of two steps: an (imbalanced) NN learning method is first applied to produce a classification boundary, which is then adjusted by PBI under the geometric mean (G-mean). For data imbalance, the geometric mean of the accuracies of both minority and majority classes is considered, that is statistically more suitable than the common metric accuracy. PBI also has the following advantages over traditional imbalance methods: (i) PBI can significantly improve the classification accuracy on minority class while improving or keeping that on majority class as well; (ii) PBI is suitable for large data even with high imbalance ratio (up to 0.001). For evaluation of (i), a new metric called Majority loss/Minority advance ratio (MMR) is proposed that evaluates the loss ratio of majority class to minority class. Experiments have been conducted for PBI and several imbalance learning methods over benchmark datasets of different sizes, different imbalance ratios, and different dimensionalities. By analyzing the experimental results, PBI is shown to outperform other imbalance learning methods on almost all datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploring Opportunities to Boost Adult Students' Graduation--The Reasons behind the Delays and Drop-Outs of Graduation

ERIC Educational Resources Information Center

Aarreniemi-Jokipelto, Päivi; Bäck, Asta

2014-01-01

Drop-outs and delays of graduation is currently a huge problem in adult education. The main reason for the drop-outs and delays is usually stated to be the difficulty of combining studies with family and work. This study was based on interviews where students studying in the bachelor's or master's degree programme were interviewed to find out the…

Nonmonetary Decision-Making Indices Discriminate Between Different Behavioral Components of Gambling.

PubMed

Navas, Juan F; Torres, Ana; Vilar, Raquel; Verdejo-García, Antonio; Catena, Andrés; Perales, José C

2015-12-01

Recent research has proposed that altered reward and punishment sensitivity, heightened impulsivity, and faulty dynamic decision-making are at the core of disordered gambling. However, each of these traits and cognitive aspects dimensionally vary in the normal population, such that the link between individual differences in these dimensions and gambling use can be ultimately informative to explain disordered gambling. The main aim of the present study was to investigate the contribution of such decision-making-related indices to gambling use parameters in a community sample of college students. Assessment included punishment and reward sensitivity (as measured by the shortened Sensitivity to Punishment and Sensitivity to Reward Questionnaire), impulsivity (as measured by the UPPS-P model and a motor inhibition Go/No-go task), and dynamic decision-making [as measured by the probabilistic reversal learning task (PRLT)]. A structured interview was conducted to explore quantitative aspects of the participants gambling habits (gambling presence, gambling frequency, and average amount of money spent in gambling per unit of time). Our results showed the existence of a decision-making profile of gambling, as it naturally occurs in college students, in which sensation seeking is directly and specifically related to gambling presence (gambling, or not gambling at all), punishment sensitivity is inversely related to gambling frequency, and inflexibility in the PRLT specifically predicts the losses accrued because of gambling. These results are compatible with the idea that sensation seeking and punishment insensitivity could increase exposure to gambling activities, whereas reversal learning inflexibility, in people who already gamble, could boost the risk to accumulate losses.

Starting Up in a Down Market, with a Boost From Entrepreneurship Graduate Programs

NASA Astrophysics Data System (ADS)

Taylor, Cyrus

2003-03-01

In the late 1990's, it seemed that any two graduate students and their dog could start and grow a high-tech company. With the collapse of, first, the internet sector, and, more recently, the telecommunications sector, there has been a traumatic shake-out among high tech firms, and the challenges facing new firms appear to have greatly increased. This talk will highlight the keys for physics entrepreneurs to survive and even thrive in this environment, with a special initial boost from new graduate programs combining business school and physics training. The infrastructure needed by educational programs designed to empower physicists as entrepreneurs is discussed.

Exogenous Attention Enables Perceptual Learning.

PubMed

Szpiro, Sarit F A; Carrasco, Marisa

2015-12-01

Practice can improve visual perception, and these improvements are considered to be a form of brain plasticity. Training-induced learning is time-consuming and requires hundreds of trials across multiple days. The process of learning acquisition is understudied. Can learning acquisition be potentiated by manipulating visual attentional cues? We developed a protocol in which we used task-irrelevant cues for between-groups manipulation of attention during training. We found that training with exogenous attention can enable the acquisition of learning. Remarkably, this learning was maintained even when observers were subsequently tested under neutral conditions, which indicates that a change in perception was involved. Our study is the first to isolate the effects of exogenous attention and to demonstrate its efficacy to enable learning. We propose that exogenous attention boosts perceptual learning by enhancing stimulus encoding. © The Author(s) 2015.

Boosting Adult Learning. Working Brief.

ERIC Educational Resources Information Center

Boyer, David

Too many of Britain's workforce lack the skills needed for a knowledge-based economy. To remedy this will require the commitment, in time and resources, of individuals, employers, the education and training infrastructure and the state. Adults with the lowest qualifications have the least access to employer-funded training, especially in small…

MOOCs as Change Agents to Boost Innovation in Higher Education Learning Arenas

ERIC Educational Resources Information Center

Ossiannilsson, Ebba; Altinay, Fahriye; Altinay, Zehra

2016-01-01

Massive open online courses (MOOCs) provide opportunities for learners to benefit from initiatives that are promoted by prestigious universities worldwide. The introduction of MOOCs in 2008 has since then transformed education globally. Consequently, MOOCs should be acknowledged as a pedagogical innovation and recognized as change agents and…

Machine Translation for Academic Purposes

ERIC Educational Resources Information Center

Lin, Grace Hui-chin; Chien, Paul Shih Chieh

2009-01-01

Due to the globalization trend and knowledge boost in the second millennium, multi-lingual translation has become a noteworthy issue. For the purposes of learning knowledge in academic fields, Machine Translation (MT) should be noticed not only academically but also practically. MT should be informed to the translating learners because it is a…

Sound-Symbolism Boosts Novel Word Learning

ERIC Educational Resources Information Center

Lockwood, Gwilym; Dingemanse, Mark; Hagoort, Peter

2016-01-01

The existence of sound-symbolism (or a non-arbitrary link between form and meaning) is well-attested. However, sound-symbolism has mostly been investigated with nonwords in forced choice tasks, neither of which are representative of natural language. This study uses ideophones, which are naturally occurring sound-symbolic words that depict sensory…

Learning across Lines. The Secret to More Efficient Factories.

ERIC Educational Resources Information Center

Lapre, Michael A.; Van Wassenhove, Luk N.

2002-01-01

Manufacturers' attempts to boost operating productivity rarely pay off and some do more harm than good. A study of a Belgian manufacturer illustrates characteristics that enhance productivity improvement: (1) production of process knowledge that is well understood and relevant and (2) transfer by combining conceptual and operational knowledge.…

Flexible model of work-based learning boosts development.

PubMed

Clark, Elisabeth

2011-01-19

I was interested to read your news story, 'Nurses miss out on essential training due to staff shortages' (January 5). As director of the Open University-RCN strategic alliance I would emphasise the importance of investing in continuing professional development (CPD), particularly in times of change and service redesign.

Online English-English Learner Dictionaries Boost Word Learning

ERIC Educational Resources Information Center

Nurmukhamedov, Ulugbek

2012-01-01

Learners of English might be familiar with several online monolingual dictionaries that are not necessarily the best choices for the English as Second/Foreign Language (ESL/EFL) context. Although these monolingual online dictionaries contain definitions, pronunciation guides, and other elements normally found in general-use dictionaries, they are…

Start Smart! Building Brain Power in the Early Years.

ERIC Educational Resources Information Center

Schiller, Pam

Noting current brain development research, this book offers simple, straightforward ways to boost children's brain power with active exploration, repetition, sensory exploration, laughter, and more. The chapters describe how and why the brain develops and explain how parents can give their children the best foundation for future learning.…

Curriculum Connection: Create a Classroom Community.

ERIC Educational Resources Information Center

Donlan, Leni

1991-01-01

One elementary teacher runs her classroom as a technology-based token economy. Students hold classroom jobs and use software to track money earned, manage checking accounts, and disburse classroom cash. The strategy boosts math and technology skills. A list of software programs is included. (SM)

Adiabatic Quantum Anomaly Detection and Machine Learning

NASA Astrophysics Data System (ADS)

Pudenz, Kristen; Lidar, Daniel

2012-02-01

We present methods of anomaly detection and machine learning using adiabatic quantum computing. The machine learning algorithm is a boosting approach which seeks to optimally combine somewhat accurate classification functions to create a unified classifier which is much more accurate than its components. This algorithm then becomes the first part of the larger anomaly detection algorithm. In the anomaly detection routine, we first use adiabatic quantum computing to train two classifiers which detect two sets, the overlap of which forms the anomaly class. We call this the learning phase. Then, in the testing phase, the two learned classification functions are combined to form the final Hamiltonian for an adiabatic quantum computation, the low energy states of which represent the anomalies in a binary vector space.

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

Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records

PubMed Central

Weiss, Jeremy C; Page, David; Peissig, Peggy L; Natarajan, Sriraam; McCarty, Catherine

2013-01-01

Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically-relevant high recall region. We observe that both SRL algorithms predict outcomes better than their propositional analogs and suggest how our methods can augment current epidemiological practices. PMID:25360347

A Qualitative Study Examining the Exclusive Use of Primary Literature in a Special Topics Biology Course: Improving Conceptions about the Nature of Science and Boosting Confidence in Approaching Original Scientific Research

ERIC Educational Resources Information Center

Carter, B. Elijah; Wiles, Jason R.

2017-01-01

This qualitative study explores the experiences of six students enrolled in a special topics biology class that exclusively used primary literature as course material. Nature of science (NOS) conceptions have been linked to students' attitudes toward scientific subjects, but there has been little research specifically exploring the effects of…

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

PubMed Central

Kai, Joe; Garibaldi, Jonathan M.; Qureshi, Nadeem

2017-01-01

Background Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiting complex interactions between risk factors. We assessed whether machine-learning can improve cardiovascular risk prediction. Methods Prospective cohort study using routine clinical data of 378,256 patients from UK family practices, free from cardiovascular disease at outset. Four machine-learning algorithms (random forest, logistic regression, gradient boosting machines, neural networks) were compared to an established algorithm (American College of Cardiology guidelines) to predict first cardiovascular event over 10-years. Predictive accuracy was assessed by area under the ‘receiver operating curve’ (AUC); and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) to predict 7.5% cardiovascular risk (threshold for initiating statins). Findings 24,970 incident cardiovascular events (6.6%) occurred. Compared to the established risk prediction algorithm (AUC 0.728, 95% CI 0.723–0.735), machine-learning algorithms improved prediction: random forest +1.7% (AUC 0.745, 95% CI 0.739–0.750), logistic regression +3.2% (AUC 0.760, 95% CI 0.755–0.766), gradient boosting +3.3% (AUC 0.761, 95% CI 0.755–0.766), neural networks +3.6% (AUC 0.764, 95% CI 0.759–0.769). The highest achieving (neural networks) algorithm predicted 4,998/7,404 cases (sensitivity 67.5%, PPV 18.4%) and 53,458/75,585 non-cases (specificity 70.7%, NPV 95.7%), correctly predicting 355 (+7.6%) more patients who developed cardiovascular disease compared to the established algorithm. Conclusions Machine-learning significantly improves accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment, while avoiding unnecessary treatment of others. PMID:28376093

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

PubMed

Weng, Stephen F; Reps, Jenna; Kai, Joe; Garibaldi, Jonathan M; Qureshi, Nadeem

2017-01-01

Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiting complex interactions between risk factors. We assessed whether machine-learning can improve cardiovascular risk prediction. Prospective cohort study using routine clinical data of 378,256 patients from UK family practices, free from cardiovascular disease at outset. Four machine-learning algorithms (random forest, logistic regression, gradient boosting machines, neural networks) were compared to an established algorithm (American College of Cardiology guidelines) to predict first cardiovascular event over 10-years. Predictive accuracy was assessed by area under the 'receiver operating curve' (AUC); and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) to predict 7.5% cardiovascular risk (threshold for initiating statins). 24,970 incident cardiovascular events (6.6%) occurred. Compared to the established risk prediction algorithm (AUC 0.728, 95% CI 0.723-0.735), machine-learning algorithms improved prediction: random forest +1.7% (AUC 0.745, 95% CI 0.739-0.750), logistic regression +3.2% (AUC 0.760, 95% CI 0.755-0.766), gradient boosting +3.3% (AUC 0.761, 95% CI 0.755-0.766), neural networks +3.6% (AUC 0.764, 95% CI 0.759-0.769). The highest achieving (neural networks) algorithm predicted 4,998/7,404 cases (sensitivity 67.5%, PPV 18.4%) and 53,458/75,585 non-cases (specificity 70.7%, NPV 95.7%), correctly predicting 355 (+7.6%) more patients who developed cardiovascular disease compared to the established algorithm. Machine-learning significantly improves accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment, while avoiding unnecessary treatment of others.

Engaging Parents through Better Communication Systems

ERIC Educational Resources Information Center

Kraft, Matthew A.

2017-01-01

Matthew A. Kraft, an assistant professor of education and economics at Brown University, highlights new research showing that frequent, personalized outreach to parents can boost parent engagement and student achievement. He offers tips on how schools can create infrastructures, including digital technology tools, to better support such…

An Introductory Research Experience in Mathematics for Undergraduates

ERIC Educational Resources Information Center

Johnston, William W.; Webster, Jonathan E.; Wilson, Christopher James

2017-01-01

This paper offers a strategic initiative designed to boost the level of collaborative mathematical research involving undergraduate mathematics students at Butler University. It describes goals, program design, logistics, and outcomes for an 8-day intensive summer experience in which undergraduate mathematics majors engaged in original…

The Trade-off

ERIC Educational Resources Information Center

Stuart, Reginald

2009-01-01

When Lincoln University opened its state-of-the art $23 million International Cultural Center in November, the small liberal arts college reached another milestone in its sweeping modernization program aimed at boosting its appeal to students in an increasingly competitive higher education environment. To say Lincoln, a small, quasi-private…

Sweets, Sex, or Self-Esteem? Comparing the Value of Self-Esteem Boosts with Other Pleasant Rewards

PubMed Central

Bushman, Brad J.; Moeller, Scott J.; Crocker, Jennifer

2011-01-01

Many people ascribe great value to self-esteem, but how much value? Do people value self-esteem more than other pleasant activities, such as eating sweets and having sex? Two studies of college students (Study 1: N=130; Study 2: N=152) showed that people valued boosts to their self-esteem more than they valued eating a favorite food and engaging in a favorite sexual activity. Study 2 also showed that people valued self-esteem more than they valued drinking alcohol, receiving a paycheck, and seeing a best friend. Both studies found that people who highly valued self-esteem engaged in laboratory tasks to boost their self-esteem. Finally, personality variables interacted with these value ratings. Entitled people thought they were more deserving of all pleasant rewards, even though they did not like them all that much (both studies); and people who highly value self-esteem pursue potentially maladaptive self-image goals, presumably to elevate their self-esteem (Study 2). PMID:21950264

Analysis of Machine Learning Techniques for Heart Failure Readmissions.

PubMed

Mortazavi, Bobak J; Downing, Nicholas S; Bucholz, Emily M; Dharmarajan, Kumar; Manhapra, Ajay; Li, Shu-Xia; Negahban, Sahand N; Krumholz, Harlan M

2016-11-01

The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates. © 2016 American Heart Association, Inc.

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

Effects of a research-infused botanical curriculum on undergraduates' content knowledge, STEM competencies, and attitudes toward plant sciences.

PubMed

Ward, Jennifer Rhode; Clarke, H David; Horton, Jonathan L

2014-01-01

In response to the American Association for the Advancement of Science's Vision and Change in Undergraduate Biology Education initiative, we infused authentic, plant-based research into majors' courses at a public liberal arts university. Faculty members designed a financially sustainable pedagogical approach, utilizing vertically integrated curricular modules based on undergraduate researchers' field and laboratory projects. Our goals were to 1) teach botanical concepts, from cells to ecosystems; 2) strengthen competencies in statistical analysis and scientific writing; 3) pique plant science interest; and 4) allow all undergraduates to contribute to genuine research. Our series of inquiry-centered exercises mitigated potential faculty barriers to adopting research-rich curricula, facilitating teaching/research balance by gathering publishable scholarly data during laboratory class periods. Student competencies were assessed with pre- and postcourse quizzes and rubric-graded papers, and attitudes were evaluated with pre- and postcourse surveys. Our revised curriculum increased students' knowledge and awareness of plant science topics, improved scientific writing, enhanced statistical knowledge, and boosted interest in conducting research. More than 300 classroom students have participated in our program, and data generated from these modules' assessment allowed faculty and students to present 28 contributed talks or posters and publish three papers in 4 yr. Future steps include analyzing the effects of repeated module exposure on student learning and creating a regional consortium to increase our project's pedagogical impact. © 2014 J. R. Ward et al. CBE—Life Sciences Education © 2014 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).

Software Acquisition Program Dynamics

DTIC Science & Technology

2011-10-24

greatest capability, which requires latest technologies • Contractors prefer using latest technologies to boost staff competency for future bids Risk...mistakes Build foundation to test future mitigation/solution approaches to assess value • Qualitatively validate new approaches before applying them to...classroom training, eLearning , certification, and more—to serve the needs of customers and partners worldwide.

Genetics and Education.

ERIC Educational Resources Information Center

Jensen, Arthur R.

This book is organized in nine parts, as follows. Part I, "Preface," includes an account of how the author went from the rather esoteric research on theoretical problems in serial rote learning to research on the inheritance of mental abilities and its implications for education. Part II, "How Much Can We Boost IQ and Scholastic Achievement?," is…

Boosting the Supply and Effectiveness of Washington's STEM Teachers. Executive Summary

ERIC Educational Resources Information Center

New Teacher Project, 2010

2010-01-01

In the spring of 2009, the Partnership for Learning (PFL) asked The New Teacher Project (TNTP) to analyze challenges Washington faces in science, technology, engineering and mathematics (STEM) instruction and to make recommendations to overcome these challenges as part of a new STEM initiative. This initiative aims to dramatically raise student…

Beyond Functionality and Technocracy: Creating Human Involvement with Educational Technology

ERIC Educational Resources Information Center

Westera, Wim

2005-01-01

Innovation of education is highly topical. It is obviously boosted by a range of new technologies, which enable new modes of learning that, are independent of time and place through Web-based delivery and computer-mediated communication. However, innovators in education often encounter intrinsic conservatism or even deliberate obstructions. For…

Multisensory Information Boosts Numerical Matching Abilities in Young Children

ERIC Educational Resources Information Center

Jordan, Kerry E.; Baker, Joseph

2011-01-01

This study presents the first evidence that preschool children perform more accurately in a numerical matching task when given multisensory rather than unisensory information about number. Three- to 5-year-old children learned to play a numerical matching game on a touchscreen computer, which asked them to match a sample numerosity with a…

Social-Emotional Assessment, Performance, and Standards

ERIC Educational Resources Information Center

McKown, Clark

2017-01-01

In the push to boost young people's social and emotional learning (SEL), assessment has lagged behind policy and practice. We have few usable, feasible, and scalable tools to assess children's SEL. And without good assessments, teachers, administrators, parents, and policymakers can't get the data they need to make informed decisions about SEL.…

Boosting Your Baby's Brain Power

ERIC Educational Resources Information Center

Engel-Smothers, Holly; Heim, Susan M.

2009-01-01

With more than 100 billion neurons that would stretch more than 60,000 miles, a newborn baby's brain is quite phenomenal! These neurons must generally form connections within the first eight months of a baby's life to foster optimal brain growth and lifelong learning. Mommies, daddies, and caregivers are extremely vital to ensuring babies reach…

Morpho-Phonemic Analysis Boosts Word Reading for Adult Struggling Readers

ERIC Educational Resources Information Center

Gray, Susan H.; Ehri, Linnea C.; Locke, John L.

2018-01-01

A randomized control trial compared the effects of two kinds of vocabulary instruction on component reading skills of adult struggling readers. Participants seeking alternative high school diplomas received 8 h of scripted tutoring to learn forty academic vocabulary words embedded within a civics curriculum. They were matched for language…

The View from the Principal's Office: An Observation Protocol Boosts Literacy :eadership

ERIC Educational Resources Information Center

Novak, Sandi; Houck, Bonnie

2016-01-01

The Minnesota Elementary School Principals' Association offered Minnesota principals professional learning that placed a high priority on literacy instruction and developing a collegial culture. A key component is the literacy classroom visit, an observation protocol used to gather data to determine the status of literacy teaching and student…

Foreign Language Methodology Conference Workshop Reports, 1976.

ERIC Educational Resources Information Center

Carranza, Jose M., Ed.; Whitmer, Robert L., Ed.

This collection resulting from a workshop on language teaching methodology contains the following papers: (1) "The Role of Culture in Foreign Language Learning," by N. Brooks; (2) "Guidelines and Ideas to Boost the Enrollment in Foreign Language Courses," by L.F. Gonzalez-Cruz; "Cooking in the Classroom," by K. Boykin; (4) "Performance Based…

Propensity score estimation: machine learning and classification methods as alternatives to logistic regression

PubMed Central

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-01-01

Summary Objective Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this Review was to assess machine learning alternatives to logistic regression which may accomplish the same goals but with fewer assumptions or greater accuracy. Study Design and Setting We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. Results We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (CART), and meta-classifiers (in particular, boosting). Conclusion While the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and to a lesser extent decision trees (particularly CART) appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. PMID:20630332

Using "The Giving Tree" To Teach Literary Criticism.

ERIC Educational Resources Information Center

Remler, Nancy Lawson

2000-01-01

Argues that introducing students to literary criticism while introducing them to literature boosts their confidence and abilities to analyze literature, and increases their interest in discussing it. Describes how the author, in her college-level introductory literature course, used Shel Silverstein's "The Giving Tree" (a children's…

Education by Robot!

ERIC Educational Resources Information Center

Cobb, Cheryl

2004-01-01

This article describes BEST (Boosting Engineering, Science, and Technology), a hands-on robotics program founded by Texas Instruments engineers Ted Mahler and Steve Marum. BEST links educators with industry to provide middle and high school students with a peek into the exciting world of robotics, with the goal of inspiring and interesting…

PubMed

1988-06-04

Fourth year student nurse tmma Moore accepts a high-powered boost to the Great Ormond Street Wishing Well Appeal. The new Escort donated by Ford Motor Company Limited will be raffled by the Hospital's nurses during their rag week in August. Proceeds from the raffle will be added to the £25 million appeal fund.

Teaching a Machine to Feel Postoperative Pain: Combining High-Dimensional Clinical Data with Machine Learning Algorithms to Forecast Acute Postoperative Pain

PubMed Central

Tighe, Patrick J.; Harle, Christopher A.; Hurley, Robert W.; Aytug, Haldun; Boezaart, Andre P.; Fillingim, Roger B.

2015-01-01

Background Given their ability to process highly dimensional datasets with hundreds of variables, machine learning algorithms may offer one solution to the vexing challenge of predicting postoperative pain. Methods Here, we report on the application of machine learning algorithms to predict postoperative pain outcomes in a retrospective cohort of 8071 surgical patients using 796 clinical variables. Five algorithms were compared in terms of their ability to forecast moderate to severe postoperative pain: Least Absolute Shrinkage and Selection Operator (LASSO), gradient-boosted decision tree, support vector machine, neural network, and k-nearest neighbor, with logistic regression included for baseline comparison. Results In forecasting moderate to severe postoperative pain for postoperative day (POD) 1, the LASSO algorithm, using all 796 variables, had the highest accuracy with an area under the receiver-operating curve (ROC) of 0.704. Next, the gradient-boosted decision tree had an ROC of 0.665 and the k-nearest neighbor algorithm had an ROC of 0.643. For POD 3, the LASSO algorithm, using all variables, again had the highest accuracy, with an ROC of 0.727. Logistic regression had a lower ROC of 0.5 for predicting pain outcomes on POD 1 and 3. Conclusions Machine learning algorithms, when combined with complex and heterogeneous data from electronic medical record systems, can forecast acute postoperative pain outcomes with accuracies similar to methods that rely only on variables specifically collected for pain outcome prediction. PMID:26031220

A phenomenological research study: Perspectives of student learning through small group work between undergraduate nursing students and educators.

PubMed

Wong, Florence Mei Fung

2018-06-18

Small group work is an effective teaching-learning approach in nursing education to enhance students' learning in theoretical knowledge and skill development. Despite its potential advantageous effects on learning, little is known about its actual effects on students' learning from students' and educators' perspectives. To understand students' learning through small group work from the perspectives of students and educators. A qualitative study with focus group interviews was carried out. Semi-structured interviews with open-ended questions were performed with 13 undergraduate nursing students and 10 educators. Four main themes, "initiative learning", "empowerment of interactive group dynamics", "factors for creating effective learning environment", and "barriers influencing students' learning", were derived regarding students' learning in small group work based on the perspectives of the participants. The results showed the importance of learning attitudes of students in individual and group learning. Factors for creating an effective learning environment, including preference for forming groups, effective group size, and adequacy of discussion, facilitate students' learning with the enhancement of learning engagement in small group work. The identified barriers, such as "excessive group work", "conflicts", and "passive team members" can reduce students' motivation and enjoyment of learning. Small group work is recognized as an effective teaching method for knowledge enhancement and skill development in nursing education. All identified themes are important to understand the initiatives of students and group learning, factors influencing an effective learning environment, and barriers hindering students' learning. Nurse educators should pay more attention to the factors that influence an effective learning environment and reduce students' commitment and group dynamics. Moreover, students may need further support to reduce barriers that impede students' learning motivation and enjoyment. Copyright © 2018 Elsevier Ltd. All rights reserved.

STEM Outreach to the African Canadian Community - The Imhotep Legacy Academy

NASA Astrophysics Data System (ADS)

Hewitt, Kevin

2012-02-01

Like the African American community in the US, the African Canadian community is underrepresented in the Science Technology Engineering and Mathematics (STEM) fields. To serve these communities two outreach organizations emerged in Canadian cities where there is a critical mass of learners of African Descent - Toronto and Halifax. I will describe the Imhotep's Legacy Academy, which began in the Physics labs of Dalhousie University in Halifax, Nova Scotia and has grown to a province-wide program serving three-quarters of the school boards in the province with an annual budget that has grown to 400,000 in 2011-12. It follows the learner from the time they enter grade 7 to the time they graduate from university, through three programs: (a) Weekly After-School science enrichment for junior high learners, (b) Virtual High school tutoring program and (c) Summer student internships and research scholarships for post-secondary students. This year, the program was the beneficiary of funding from TD Bank to establish scholarships for program participants to enter Dalhousie university. Modeled on the Meyerhoff scholarships the program participants are identified at an early stage and are promised a subset of funding as they meet selected criteria during participation in the program. The program enjoys support from the Department of Education and the highest levels of government. A tri-mentoring system exists where faculty of African descent train mentors, who are science students of African descent at associated universities, to deliver hands-on enrichment activities to learners of African Descent. Evidence supporting the success of the program will be highlighted. Project outcomes measured include (i) recruitment; (ii) attendance; (iii) stakeholder relationships; (iv) programming; (v) staff training; (vi) perception of ILASP's value; (vii) academic performance. The end results are new lessons and best practices that are incorporated into a strategic plan for the new project year. Teachers perceived that ILASP had a positive ripple effect on the entire academic and non-academic educational experience of the learners, crediting the project with (i) encouraging self-learning; (ii) assisting in honing learners' science and math skills; (iii) developing core skills that were applicable in learners' schoolwork; (iv) boosting learners' self-esteem; (v) improving school attendance; (vi) boosting learners' motivation to be engaged participants in all other classes.

Time Is Money...and the Enemy of College Completion: Transform American Higher Education to Boost Completion and Reduce Costs. Testimony before the United States House of Representatives Subcommittee on Higher Education and Workforce Training

ERIC Educational Resources Information Center

Jones, Stan

2012-01-01

This paper presents Stan Jones' testimony before the United States House of Representatives Subcommittee on Higher Education and Workforce Training. In his testimony, he talks about a new American majority of students that is emerging on campuses, especially at community colleges. These students must delicately balance long hours at jobs they must…

Using Boosting Decision Trees in Gravitational Wave Searches triggered by Gamma-ray Bursts

NASA Astrophysics Data System (ADS)

Zuraw, Sarah; LIGO Collaboration

2015-04-01

The search for gravitational wave bursts requires the ability to distinguish weak signals from background detector noise. Gravitational wave bursts are characterized by their transient nature, making them particularly difficult to detect as they are similar to non-Gaussian noise fluctuations in the detector. The Boosted Decision Tree method is a powerful machine learning algorithm which uses Multivariate Analysis techniques to explore high-dimensional data sets in order to distinguish between gravitational wave signal and background detector noise. It does so by training with known noise events and simulated gravitational wave events. The method is tested using waveform models and compared with the performance of the standard gravitational wave burst search pipeline for Gamma-ray Bursts. It is shown that the method is able to effectively distinguish between signal and background events under a variety of conditions and over multiple Gamma-ray Burst events. This example demonstrates the usefulness and robustness of the Boosted Decision Tree and Multivariate Analysis techniques as a detection method for gravitational wave bursts. LIGO, UMass, PREP, NEGAP.

Shrinkage Degree in $L_{2}$ -Rescale Boosting for Regression.

PubMed

Xu, Lin; Lin, Shaobo; Wang, Yao; Xu, Zongben

2017-08-01

L 2 -rescale boosting ( L 2 -RBoosting) is a variant of L 2 -Boosting, which can essentially improve the generalization performance of L 2 -Boosting. The key feature of L 2 -RBoosting lies in introducing a shrinkage degree to rescale the ensemble estimate in each iteration. Thus, the shrinkage degree determines the performance of L 2 -RBoosting. The aim of this paper is to develop a concrete analysis concerning how to determine the shrinkage degree in L 2 -RBoosting. We propose two feasible ways to select the shrinkage degree. The first one is to parameterize the shrinkage degree and the other one is to develop a data-driven approach. After rigorously analyzing the importance of the shrinkage degree in L 2 -RBoosting, we compare the pros and cons of the proposed methods. We find that although these approaches can reach the same learning rates, the structure of the final estimator of the parameterized approach is better, which sometimes yields a better generalization capability when the number of sample is finite. With this, we recommend to parameterize the shrinkage degree of L 2 -RBoosting. We also present an adaptive parameter-selection strategy for shrinkage degree and verify its feasibility through both theoretical analysis and numerical verification. The obtained results enhance the understanding of L 2 -RBoosting and give guidance on how to use it for regression tasks.

Comparative Study of Learning Using E-Learning and Printed Materials on Independent Learning and Creativity

NASA Astrophysics Data System (ADS)

Wahyu Utami, Niken; Aziz Saefudin, Abdul

2018-01-01

This study aims to determine: 1) differences in students taking independent learning by using e-learning and the students who attend the learning by using the print instructional materials ; 2) differences in the creativity of students who follow learning with e-learning and the students who attend the learning by using the print instructional materials ; 3) differences in learning independence and creativity of students attend learning with e-learning and the students who attend lessons using printed teaching materials in the subject of Mathematics Instructional Media Development. This study was a quasi-experimental research design using only posttest control design. The study population was all students who take courses in Learning Mathematics Media Development, Academic Year 2014/2015 100 students and used a random sample (random sampling) is 60 students. To test the hypothesis used multivariate analysis of variance or multivariable analysis of variance (MANOVA) of the track. The results of this study indicate that 1) There is a difference in student learning independence following study using the e-learning and the students who attend lessons using printed teaching materials in the lecture PMPM ( F = 4.177, p = 0.046 < 0.05 ) ; 2 ) There is no difference in the creativity of the students who complete the learning by using e -learning and students to follow the learning using printed teaching materials in the lecture PMPM ( F = 0.470, p = 0.496 > 0.05) ; No difference learning independence and creativity of students attend learning by using e-learning and the students who attend the learning using printed teaching materials in the lecture PMPM (F = 2.452, p = 0.095 > 0.05). Based on these studies suggested that the learning using e -learning can be used to develop student creativity, while learning to use e -learning and teaching materials can be printed to use to develop students’ independence.

STEM Gets a Boost from Business

ERIC Educational Resources Information Center

Rosen, Linda

2012-01-01

STEM--science, technology, engineering, and mathematics--has become a fixture of the education debate, and much effort already has been put toward improving student performance. Yet troubling statistics persist: On the latest round of testing for the National Assessment of Educational Progress (NAEP), only 40 percent of fourth graders nationwide…

The Million-Dollar Question: Can Internships Boost Employment?

ERIC Educational Resources Information Center

Silva, Patrícia; Lopes, Betina; Costa, Marco; Melo, Ana I.; Dias, Gonçalo Paiva; Brito, Elisabeth; Seabra, Dina

2018-01-01

Higher education institutions are increasingly concerned with the professional insertion of graduates in the labour market and with the design of institutional mechanisms to facilitate students' transition from higher education to work, particularly given the context of scarcity of financial resources and the rise of graduate unemployment. This…

Fiscal Stress: Worldwide Trends in Higher Education Finance

ERIC Educational Resources Information Center

Vossensteyn, Hans

2004-01-01

While higher education is generally a high priority in boosting economic development, public budgets to sustain expansion of higher education systems remain limited around the globe. This fiscal stress creates an impetus for governments to develop various strategies to meet the growing demand--from both students and society--for higher education…

Loss of Veterans Doesn't Hurt Scores

ERIC Educational Resources Information Center

Sparks, Sarah D.

2013-01-01

Boosting early retirement in cash-strapped districts does not hurt students' math and reading scores, according to new studies released at the American Economic Association meeting, but pension-incentive programs may cost schools some of their most effective teachers. Separate studies of teachers in California, Illinois, and North Carolina paint a…

Longitudinal Comparative Study: Females' vs. Males' Graduation Outcomes in Undergraduate Engineering

ERIC Educational Resources Information Center

Madara, Diana Starovoytova; Namango, Saul Sitati

2016-01-01

Increasing postsecondary enrolments, reducing university drop-outs, while, simultaneously, boosting graduation rates, is a worldwide dilemma, currently challenging any university and any educational system. One of the most pressing issues facing universities, however, is the number of students, who fail to graduate. The literature survey on gender…

How Can Schools Boost Students' Self-Regulation?

ERIC Educational Resources Information Center

Le, Cecilia; Wolfe, Rebecca E.

2013-01-01

A striking convergence of research, documentation, commentary, and policy in the past five years strongly suggests that an almost exclusive focus on academic knowledge and skills is an incomplete solution. Additional behaviors, skills, and mindsets--sometimes called metacognitive skills or 21st-century skills--are just as necessary for academic…

A Clearer View of Vista Features

ERIC Educational Resources Information Center

Descy, Don E.

2008-01-01

In this article, the author discusses some features of Windows Vista that may be of interest to teachers and/or their students. These are: (1) User Account Control; (2) Windows Firewall; (3) Windows Backup; (4) Parental Controls; (5) Windows Sidebar and Gadgets; (6) Instant Search; and (7) Windows ReadyBoost.

Why Save a Can?

ERIC Educational Resources Information Center

Gutierrez, Melida; Johnson, Cheryl

2009-01-01

This activity ties together the recycling of aluminum and the protection of rain forests. Students use critical thinking to study the effects of open pit mining of bauxite in rain forests and then draw their own conclusions about how to minimize the impact of bauxite mining and boost recycling efforts within their communities. Drawing conclusions…

Leagues Revive Debate in City Schools

ERIC Educational Resources Information Center

Keller, Bess

2008-01-01

This article describes how the National Association for Urban Debate Leagues is reviving debate competitions among high school students in city schools. Starting in Atlanta in 1985 and boosted by seed money from the billionaire George Soros' Open Society Institute, urban educators and their supporters in 2002 formed the National Association for…

Completion Day

ERIC Educational Resources Information Center

Hilliard, Tom; Spaic, Tina

2013-01-01

As New York State transitions from a manufacturing economy to a knowledge economy, few institutions are playing a more important role than the state's 35 community colleges. With more than 328,000 students enrolled statewide, community colleges are boosting New York's economic competitiveness by upgrading the skills of a large chunk of the state's…

Human resource recommendation algorithm based on ensemble learning and Spark

NASA Astrophysics Data System (ADS)

Cong, Zihan; Zhang, Xingming; Wang, Haoxiang; Xu, Hongjie

2017-08-01

Aiming at the problem of “information overload” in the human resources industry, this paper proposes a human resource recommendation algorithm based on Ensemble Learning. The algorithm considers the characteristics and behaviours of both job seeker and job features in the real business circumstance. Firstly, the algorithm uses two ensemble learning methods-Bagging and Boosting. The outputs from both learning methods are then merged to form user interest model. Based on user interest model, job recommendation can be extracted for users. The algorithm is implemented as a parallelized recommendation system on Spark. A set of experiments have been done and analysed. The proposed algorithm achieves significant improvement in accuracy, recall rate and coverage, compared with recommendation algorithms such as UserCF and ItemCF.

Developpement et evaluation d'un environnement informatise d'apprentissage pour faciliter l'integration des sciences et de la technologie

NASA Astrophysics Data System (ADS)

Saliba, Marie-Therese

2011-12-01

Through this research we will fully assess the benefits brought by the ExAO (Computer Assisted Experimentation) in school laboratories of science and technology in Lebanon. We would also like to mention its contribution in a tangible way in laboratory research of Pedagogic Robotic from Montreal University, particularly in the development of ExAO mulaboratory. We wanted to test the capabilities of the ExAO, its use in the classroom such as: 1. A replacement of a traditional laboratory in the use of the experimental method. 2. A scientific investigation tool. 3. An integration tool of experimental sciences and mathematics. 4. An integration tool of experimental sciences, mathematics and technology in the technoscientific learning. To do so, we have mobilized 13 group classes, designated teachers to experiment themselves along with their students in order to assess, in a more realistic way, the benefits of implementing this micro computer laboratory at school. Different testing, evaluated using the results of learning activities undertaken by students, their responses to a questionnaire and feedback from teachers, show that: 1. The replacement of a traditional laboratory with an ExAO mulaboratory does not seem to pose problem, expected that students have adapted to it in only ten minutes, indicating that the speed with which data were graphed was more productive. 2. In order to investigate a physical phenomenon, the usability of the tutorial associated with the ability to amplify the phenomenon before its graph representation, has allowed students to design and implement quickly and independently an experiment to verify their prediction. 3. The integration of mathematics into an experimental approach can quickly grasp the phenomenon. In addition, it gives more autonomy and a meaning to the graphs and algebraic representations allowing to use them as a cognitive tool to interpret this phenomenon. 4. The approach made by the students to design and construct a technological object, showed that this activity was easily carried out by the use of universal sensors, amplifiers to offset the graphical modeling tool, and the tutorial ability to transform any measured variable by another variable (for instance, the resistance variation in temperature change, ...). This educational activity shows that students had no difficulty integrating in a single learning activity the mathematics, experimental sciences and technology, in order to design and implement a functional piece of technology. The ExAO mulaboratory, by offering new educational opportunities, such as the ability to design, produce and validate a technological object, in order to do so, new capacities to boost measures, modeling physical phenomena, developing new sensors, is an important addition to the experiments being conducted in ExAO. Keywords: ExAO, teaching, integration, Lebanese schools.

Learning Science and the Science of Learning. Science Educators' Essay Collection.

ERIC Educational Resources Information Center

Bybee, Rodger W., Ed.

This yearbook addresses critical issues in science learning and teaching. Contents are divided into four sections: (1) "How Do Students Learn Science?"; (2) "Designing Curriculum for Student Learning"; (3) "Teaching That Enhances Student Learning"; and (4) "Assessing Student Learning." Papers include: (1) "How Students Learn and How Teachers…

Integration of Engineering Education by High School Teachers to Meet Standards in the Physics Classroom

NASA Astrophysics Data System (ADS)

Kersten, Jennifer Anna

In recent years there has been increasing interest in engineering education at the K-12 level, which has resulted in states adopting engineering standards as a part of their academic science standards. From a national perspective, the basis for research into engineering education at the K-12 level is the belief that it is of benefit to student learning, including to "improve student learning and achievement in science and mathematics; increase awareness of engineering and the work of engineers; boost youth interest in pursuing engineering as a career; and increase the technological literacy of all students" (National Research Council, 2009a, p. 1). The above has led to a need to understand how teachers are currently implementing engineering education in their classrooms. High school physics teachers have a history of implementing engineering design projects in their classrooms, thus providing an appropriate setting to look for evidence of quality engineering education at the high school level. Understanding the characteristics of quality engineering integration can inform curricular and professional development efforts for teachers asked to implement engineering in their classrooms. Thus, the question that guided this study is: How, and to what extent, do physics teachers represent quality engineering in a physics unit focused on engineering? A case study research design was implemented for this project. Three high school physics teachers were participants in this study focused on the integration of engineering education into the physics classroom. The data collected included observations, interviews, and classroom documents that were analyzed using the Framework for Quality K-12 Engineering Education (Moore, Glancy et al., 2013). The results provided information about the areas of the K-12 engineering framework addressed during these engineering design projects, and detailed the quality of these lesson components. The results indicate that all of the design projects contained components of the indicators central to engineering education, although with varied degrees of success. In addition, each design project contained aspects important to the development of students' understanding of engineering and that promote important professional skills used by engineers. The implications of this work are discussed at the teacher, school, professional development, and policy levels.

The effect of discovery learning and problem-based learning on middle school students’ self-regulated learning

NASA Astrophysics Data System (ADS)

Miatun, A.; Muntazhimah

2018-01-01

The aim of this research was to determine the effect of learning models on mathematics achievement viewed from student’s self-regulated learning. The learning model compared were discovery learning and problem-based learning. The population was all students at the grade VIII of Junior High School in Boyolali regency. The samples were students of SMPN 4 Boyolali, SMPN 6 Boyolali, and SMPN 4 Mojosongo. The instruments used were mathematics achievement tests and self-regulated learning questionnaire. The data were analyzed using unbalanced two-ways Anova. The conclusion was as follows: (1) discovery learning gives better achievement than problem-based learning. (2) Achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. (3) For discovery learning, achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. For problem-based learning, students who have high and medium self-regulated learning have the same achievement. (4) For students who have high self-regulated learning, discovery learning gives better achievement than problem-based learning. Students who have medium and low self-regulated learning, both learning models give the same achievement.

Medical student use of digital learning resources.

PubMed

Scott, Karen; Morris, Anne; Marais, Ben

2018-02-01

University students expect to use technology as part of their studies, yet health professional teachers can struggle with the change in student learning habits fuelled by technology. Our research aimed to document the learning habits of contemporary medical students during a clinical rotation by exploring the use of locally and externally developed digital and print self-directed learning resources, and study groups. We investigated the learning habits of final-stage medical students during their clinical paediatric rotation using mixed methods, involving learning analytics and a student questionnaire. Learning analytics tracked aggregate student usage statistics of locally produced e-learning resources on two learning management systems and mobile learning resources. The questionnaire recorded student-reported use of digital and print learning resources and study groups. The students made extensive use of digital self-directed learning resources, especially in the 2 weeks before the examination, which peaked the day before the written examination. All students used locally produced digital formative assessment, and most (74/98; 76%) also used digital resources developed by other institutions. Most reported finding locally produced e-learning resources beneficial for learning. In terms of traditional forms of self-directed learning, one-third (28/94; 30%) indicated that they never read the course textbook, and few students used face-to-face 39/98 (40%) or online 6/98 (6%) study groups. Learning analytics and student questionnaire data confirmed the extensive use of digital resources for self-directed learning. Through clarification of learning habits and experiences, we think teachers can help students to optimise effective learning strategies; however, the impact of contemporary learning habits on learning efficacy requires further evaluation. Health professional teachers can struggle with the change in student learning habits fuelled by technology. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

The Role of Single Talker Acoustic Variation in Early Word Learning

ERIC Educational Resources Information Center

Galle, Marcus E.; Apfelbaum, Keith S.; McMurray, Bob

2015-01-01

Recent work has demonstrated that the addition of multiple talkers during habituation improves 14-month-olds' performance in the switch task (Rost & McMurray, 2009). While the authors suggest that this boost in performance is due to the increase in acoustic variability (Rost & McMurray, 2010), it is also possible that there is…

Rhythmic Rhymes for Boosting Phonological Awareness in Socially Disadvantaged Children

ERIC Educational Resources Information Center

Kuppen, Sarah E. A.; Bourke, Emilie

2017-01-01

This study evaluated the ability for two rhythmic rhyming programs to raise phonological awareness in the early literacy classroom. Year 1 (5-6-year-olds) from low socioeconomic status schools in Bedfordshire, learned a program of sung or spoken rhythmic rhymes, or acted as controls. The project ran with two independent cohorts (Cohort 1 N = 98,…

Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction

ERIC Educational Resources Information Center

Trivedi, Shubhendu; Pardos, Zachary A.; Sarkozy, Gabor N.; Heffernan, Neil T.

2012-01-01

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…

Using LEGO Blocks for Technology-Mediated Task-Based English Language Learning

ERIC Educational Resources Information Center

Gadomska, Agnieszka

2015-01-01

LEGO blocks have been played with by generations of children worldwide since the 1950s. It is undeniable that they boost creativity, eye-hand coordination, focus, planning, problem solving and many other skills. LEGO bricks have been also used by educators across the curricula as they are extremely motivating and engaging and, in effect, make…

The State of Play: Gallup Survey of Principals on School Recess

ERIC Educational Resources Information Center

Robert Wood Johnson Foundation, 2010

2010-01-01

When most people talk about how to improve education, they tend to focus only on what happens in the classroom. But the most unexpected opportunity to boost learning lies outside the classroom: on the playground at recess. A new, first-of-its-kind Gallup poll reveals that elementary school principals overwhelmingly believe recess has a positive…

An Agile Framework for Real-Time Visual Tracking in Videos

DTIC Science & Technology

2012-09-05

multiplied by the structure tensor , for which there are two eigenvalues λ1 and λ2; if either or both is large and positive, an edge or corner is found...cannot learn to an accuracy better than 1/2. This holds even if the boosting algorithm stops early or the voting weights are bounded. Consider two sets

Factors Influencing the Acceptance of E-Learning Adoption in Libya's Higher Education Institutions

ERIC Educational Resources Information Center

Benghet, Mahfoud; Helfert, Markus

2014-01-01

The growing influence of technologies on all aspects of life, including the education sector, requires developing countries to follow the example of the developed countries and adopt technology in their education systems. Libya has been able to boost its economic and educational position over the years, and this brings it to the concern of…

High-Quality School-Based Pre-K Can Boost Early Learning for Children with Special Needs

ERIC Educational Resources Information Center

Phillips, Deborah A.; Meloy, Mary E.

2012-01-01

This article assesses the effects of Tulsa, Oklahoma's school-based prekindergarten program on the school readiness of children with special needs using a regression discontinuity design. Participation in the pre-K program was associated with significant gains for children with special needs in early literacy scores, but not in math scores. These…

The Influence of Bilingualism on the Preference for the Mouth Region of Dynamic Faces

ERIC Educational Resources Information Center

Ayneto, Alba; Sebastian-Galles, Nuria

2017-01-01

Bilingual infants show an extended period of looking at the mouth of talking faces, which provides them with additional articulatory cues that can be used to boost the challenging situation of learning two languages (Pons, Bosch & Lewkowicz, 2015). However, the eye region also provides fundamental cues for emotion perception and recognition,…

Issues of ICT Usage among Malaysian Secondary School English Teachers

ERIC Educational Resources Information Center

Raman, Arumugam; Mohamed, Abdul Halim

2013-01-01

This study explored on perception, usage and obstacles of using ICT in teaching English Language among secondary school English teachers. The advancement of technology has given a space for teachers to boost teaching and learning of English language in secondary schools. It is believed that integration of ICT could enhance quality of teaching and…

Semantics Boosts Syntax in Artificial Grammar Learning Tasks with Recursion

ERIC Educational Resources Information Center

Fedor, Anna; Varga, Mate; Szathmary, Eors

2012-01-01

Center-embedded recursion (CER) in natural language is exemplified by sentences such as "The malt that the rat ate lay in the house." Parsing center-embedded structures is in the focus of attention because this could be one of the cognitive capacities that make humans distinct from all other animals. The ability to parse CER is usually…

The Learning of Chinese Idioms through Multimedia Storytelling Prototype

ERIC Educational Resources Information Center

Li, Ee Hui; Hew, Soon Hin; Choo, Siew Hwa

2016-01-01

In recent years, the growth of China has successfully boosted the Chinese language to be studied by people from different language-speaking societies. The Chinese language has become the most preferred second or third language among non-Chinese native novices due to the great development of China and global economic change. The Chinese idiom is…

"Districts Matter": Cultivating the Principals Urban Schools Need. Perspective

ERIC Educational Resources Information Center

Mitgang, Lee

2013-01-01

An effective school requires an effective leader, but great principals rarely just happen. They are cultivated. This Wallace Perspective draws on a decade of foundation research and work in school leadership to show how urban school districts can play a major role in ensuring they have principals who can boost teaching and learning in troubled…

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

PubMed Central

Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms—including the model tuning and predictor selection—were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models’ predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction. PMID:27128736

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.

PubMed

Ließ, Mareike; Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms-including the model tuning and predictor selection-were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models' predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.

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.

A Tribute to Charlie Chaplin: Induced Positive Affect Improves Reward-Based Decision-Learning in Parkinson’s Disease

PubMed Central

Ridderinkhof, K. Richard; van Wouwe, Nelleke C.; Band, Guido P. H.; Wylie, Scott A.; Van der Stigchel, Stefan; van Hees, Pieter; Buitenweg, Jessika; van de Vijver, Irene; van den Wildenberg, Wery P. M.

2012-01-01

Reward-based decision-learning refers to the process of learning to select those actions that lead to rewards while avoiding actions that lead to punishments. This process, known to rely on dopaminergic activity in striatal brain regions, is compromised in Parkinson’s disease (PD). We hypothesized that such decision-learning deficits are alleviated by induced positive affect, which is thought to incur transient boosts in midbrain and striatal dopaminergic activity. Computational measures of probabilistic reward-based decision-learning were determined for 51 patients diagnosed with PD. Previous work has shown these measures to rely on the nucleus caudatus (outcome evaluation during the early phases of learning) and the putamen (reward prediction during later phases of learning). We observed that induced positive affect facilitated learning, through its effects on reward prediction rather than outcome evaluation. Viewing a few minutes of comedy clips served to remedy dopamine-related problems associated with frontostriatal circuitry and, consequently, learning to predict which actions will yield reward. PMID:22707944

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

Eads, Damian Ryan; Rosten, Edward; Helmbold, David

The authors present BEAMER: a new spatially exploitative approach to learning object detectors which shows excellent results when applied to the task of detecting objects in greyscale aerial imagery in the presence of ambiguous and noisy data. There are four main contributions used to produce these results. First, they introduce a grammar-guided feature extraction system, enabling the exploration of a richer feature space while constraining the features to a useful subset. This is specified with a rule-based generative grammer crafted by a human expert. Second, they learn a classifier on this data using a newly proposed variant of AdaBoost whichmore » takes into account the spatially correlated nature of the data. Third, they perform another round of training to optimize the method of converting the pixel classifications generated by boosting into a high quality set of (x,y) locations. lastly, they carefully define three common problems in object detection and define two evaluation criteria that are tightly matched to these problems. Major strengths of this approach are: (1) a way of randomly searching a broad feature space, (2) its performance when evaluated on well-matched evaluation criteria, and (3) its use of the location prediction domain to learn object detectors as well as to generate detections that perform well on several tasks: object counting, tracking, and target detection. They demonstrate the efficacy of BEAMER with a comprehensive experimental evaluation on a challenging data set.« less

Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma.

PubMed

Zhang, Bin; He, Xin; Ouyang, Fusheng; Gu, Dongsheng; Dong, Yuhao; Zhang, Lu; Mo, Xiaokai; Huang, Wenhui; Tian, Jie; Zhang, Shuixing

2017-09-10

We aimed to identify optimal machine-learning methods for radiomics-based prediction of local failure and distant failure in advanced nasopharyngeal carcinoma (NPC). We enrolled 110 patients with advanced NPC. A total of 970 radiomic features were extracted from MRI images for each patient. Six feature selection methods and nine classification methods were evaluated in terms of their performance. We applied the 10-fold cross-validation as the criterion for feature selection and classification. We repeated each combination for 50 times to obtain the mean area under the curve (AUC) and test error. We observed that the combination methods Random Forest (RF) + RF (AUC, 0.8464 ± 0.0069; test error, 0.3135 ± 0.0088) had the highest prognostic performance, followed by RF + Adaptive Boosting (AdaBoost) (AUC, 0.8204 ± 0.0095; test error, 0.3384 ± 0.0097), and Sure Independence Screening (SIS) + Linear Support Vector Machines (LSVM) (AUC, 0.7883 ± 0.0096; test error, 0.3985 ± 0.0100). Our radiomics study identified optimal machine-learning methods for the radiomics-based prediction of local failure and distant failure in advanced NPC, which could enhance the applications of radiomics in precision oncology and clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.

Random Bits Forest: a Strong Classifier/Regressor for Big Data

NASA Astrophysics Data System (ADS)

Wang, Yi; Li, Yi; Pu, Weilin; Wen, Kathryn; Shugart, Yin Yao; Xiong, Momiao; Jin, Li

2016-07-01

Efficiency, memory consumption, and robustness are common problems with many popular methods for data analysis. As a solution, we present Random Bits Forest (RBF), a classification and regression algorithm that integrates neural networks (for depth), boosting (for width), and random forests (for prediction accuracy). Through a gradient boosting scheme, it first generates and selects ~10,000 small, 3-layer random neural networks. These networks are then fed into a modified random forest algorithm to obtain predictions. Testing with datasets from the UCI (University of California, Irvine) Machine Learning Repository shows that RBF outperforms other popular methods in both accuracy and robustness, especially with large datasets (N > 1000). The algorithm also performed highly in testing with an independent data set, a real psoriasis genome-wide association study (GWAS).

Double-charming Higgs boson identification using machine-learning assisted jet shapes

NASA Astrophysics Data System (ADS)

Lenz, Alexander; Spannowsky, Michael; Tetlalmatzi-Xolocotzi, Gilberto

2018-01-01

We study the possibility of identifying a boosted resonance that decays into a charm pair against different sources of background using QCD event shapes, which are promoted to jet shapes. Using a set of jet shapes as input to a boosted decision tree, we find that observables utilizing the simultaneous presence of two charm quarks can access complementary information compared to approaches relying on two independent charm tags. Focusing on Higgs associated production with subsequent H →c c ¯ decay and on a C P -odd scalar A with mA≤10 GeV we obtain the limits B r (H →c c ¯ )≤6.48 % and B r (H →A (→c c ¯ )Z )≤0.01 % at 95% C.L.

How Memory Replay in Sleep Boosts Creative Problem-Solving.

PubMed

Lewis, Penelope A; Knoblich, Günther; Poe, Gina

2018-06-01

Creative thought relies on the reorganisation of existing knowledge. Sleep is known to be important for creative thinking, but there is a debate about which sleep stage is most relevant, and why. We address this issue by proposing that rapid eye movement sleep, or 'REM', and non-REM sleep facilitate creativity in different ways. Memory replay mechanisms in non-REM can abstract rules from corpuses of learned information, while replay in REM may promote novel associations. We propose that the iterative interleaving of REM and non-REM across a night boosts the formation of complex knowledge frameworks, and allows these frameworks to be restructured, thus facilitating creative thought. We outline a hypothetical computational model which will allow explicit testing of these hypotheses. Copyright © 2018. Published by Elsevier Ltd.

Visualising the invisible: a network approach to reveal the informal social side of student learning.

PubMed

Hommes, J; Rienties, B; de Grave, W; Bos, G; Schuwirth, L; Scherpbier, A

2012-12-01

World-wide, universities in health sciences have transformed their curriculum to include collaborative learning and facilitate the students' learning process. Interaction has been acknowledged to be the synergistic element in this learning context. However, students spend the majority of their time outside their classroom and interaction does not stop outside the classroom. Therefore we studied how informal social interaction influences student learning. Moreover, to explore what really matters in the students learning process, a model was tested how the generally known important constructs-prior performance, motivation and social integration-relate to informal social interaction and student learning. 301 undergraduate medical students participated in this cross-sectional quantitative study. Informal social interaction was assessed using self-reported surveys following the network approach. Students' individual motivation, social integration and prior performance were assessed by the Academic Motivation Scale, the College Adaption Questionnaire and students' GPA respectively. A factual knowledge test represented student' learning. All social networks were positively associated with student learning significantly: friendships (β = 0.11), providing information to other students (β = 0.16), receiving information from other students (β = 0.25). Structural equation modelling revealed a model in which social networks increased student learning (r = 0.43), followed by prior performance (r = 0.31). In contrast to prior literature, students' academic motivation and social integration were not associated with students' learning. Students' informal social interaction is strongly associated with students' learning. These findings underline the need to change our focus from the formal context (classroom) to the informal context to optimize student learning and deliver modern medics.

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…

Sweets, sex, or self-esteem? Comparing the value of self-esteem boosts with other pleasant rewards.

PubMed

Bushman, Brad J; Moeller, Scott J; Crocker, Jennifer

2011-10-01

Many people ascribe great value to self-esteem, but how much value? Do people value self-esteem more than other pleasant activities, such as eating sweets and having sex? Two studies of college students (Study 1: N=130; Study 2: N=152) showed that people valued boosts to their self-esteem more than they valued eating a favorite food and engaging in a favorite sexual activity. Study 2 also showed that people valued self-esteem more than they valued drinking alcohol, receiving a paycheck, and seeing a best friend. Both studies found that people who highly valued self-esteem engaged in laboratory tasks to boost their self-esteem. Finally, personality variables interacted with these value ratings. Entitled people thought they were more deserving of all pleasant rewards, even though they did not like them all that much (both studies), and people who highly value self-esteem pursued potentially maladaptive self-image goals, presumably to elevate their self-esteem (Study 2). © 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.

Student views on the role of self-regulated learning in a surgery clerkship.

PubMed

Lyons-Warren, Ariel M; Kirby, John P; Larsen, Douglas P

2016-12-01

Self-regulated learning, including student-generated learning goals and flexibility in the learning structure are increasingly being used to enhance medical education. The role of these practices in surgical education of medical students has not been studied. We administered an 18-question electronic survey to all third-year medical students at Washington University in St. Louis School of Medicine. Of the 126 students invited, 64 responded and 56 were included in the analysis. We found that third-year medical students develop learning goals at the beginning of the surgery clerkship. Although these learning goals theoretically can be a mechanism for enhanced student-faculty engagement, students are not aware of formal mechanisms for sharing these goals with faculty members. Furthermore, students report a lack of flexibility within the surgery clerkship and discomfort with requesting specific learning opportunities. Finally, students report that they believe increased flexibility could improve student engagement, learning, and the overall clerkship experience. We therefore propose that a mechanism for students to share their learning goals with faculty and an infrastructure in which student learning experiences can be tailored to fit with these individualized goals would enhance student surgical learning. Copyright © 2016 Elsevier Inc. All rights reserved.

Proposed learning strategies of medical students in a clinical rotation in obstetrics and gynecology: a descriptive study.

PubMed

Deane, Richard P; Murphy, Deirdre J

2016-01-01

Medical students face many challenges when learning within clinical environments. How students plan to use their time and engage with learning opportunities is therefore critical, as it may be possible to highlight strategies that optimize the learning experience at an early stage in the rotation. The aim of the study was to describe the learning drivers and proposed learning strategies of medical students for a clinical rotation in obstetrics and gynecology. A descriptive study of personal learning plans completed by students at the start of their clinical rotation in obstetrics and gynecology was undertaken. Data relating to students' learning strategies were obtained from the personal learning plans completed by students. Quantitative and qualitative analyses were used. The desire to obtain a good examination result was the most significant reason why the rotation was important to students (n=67/71, 94%). Students struggled to create a specific and practical learning outcome relevant to their career interest. Target scores of students were significantly higher than their reported typical scores (P<0.01). Textbooks were rated as likely to be the most helpful learning resource during the rotation. Bedside tutorials were rated as likely to be the most useful learning activity and small group learning activities were rated as likely to be more useful than lectures. Most students intended to study the course material linked to their clinical program rather than the classroom-based tutorial program. The main learning driver for medical students was academic achievement, and the proposed learning strategy favored by medical students was linking their study plans to clinical activities. Medical educators should consider strategies that foster more intrinsic drivers of student learning and more student-oriented learning resources and activities.

Boosting Social and Emotional Competence

ERIC Educational Resources Information Center

Beland, Kathy

2007-01-01

Beland maintains that high school students will need a high level of skill in the social and emotional arena to be ready for competitive employment in the 21st century. In a 2006 survey, human resource professionals said five skills were most crucial to high school graduates' success: professionalism/work ethic; teamwork; oral communications;…

Don't Leave Accountability behind: A Call for ESEA Reauthorization

ERIC Educational Resources Information Center

Alliance for Excellent Education, 2010

2010-01-01

As 2010 unfolds, Americans should feel encouraged by federal, state, and local efforts to transform education policies that boost student performance. In the midst of a recession, rather than merely allocating billions of American Recovery and Reinvestment Act (ARRA) dollars by formula to the states with no strings attached, the Obama…

The Sixth Bracey Report on the Condition of Public Education.

ERIC Educational Resources Information Center

Bracey, Gerald W.

1996-01-01

American youngsters could beat the socks off Asian kids if they too, studied constantly. Charter schools' ability to boost student achievement is unproven, and choice programs benefit some clients at others' expense. Schools should stress civic responsibility, not vocational training and the work ethic. Scholastic Aptitude Test scores rose in…

Collaborating with Parents for Early School Success: The Achieving-Behaving-Caring Program

ERIC Educational Resources Information Center

McConaughy, Stephanie H.; Kay, Pam; Welkowitz, Julie A.; Hewitt, Kim; Fitzgerald, Martha D.

2007-01-01

The Achieving-Behaving-Caring (ABC) Program is an evidence-based approach to addressing the needs of elementary students at risk for emotional and behavioral difficulties and promoting successful home-school collaboration. This practical guide demonstrates how classroom teachers and parents can work together to boost individual children's…

The Principal as Instructional Leader: A Practical Handbook. 3rd Edition

ERIC Educational Resources Information Center

Zepeda, Sally J.

2013-01-01

In the updated third edition of this highly successful book, leadership expert, Sally Zepeda offers savvy advice to both new and seasoned principals and assistant principals. You get practical tools and strategies, along with real-world examples to help you improve teacher effectiveness and boost student achievement. This edition features valuable…

Free Student Breakfasts: Surest Way to Raise Performance

ERIC Educational Resources Information Center

Chmelynski, Carol

2007-01-01

According to James Weill, president of the Food Research and Action Center (FRAC), breakfast is not the solution to the problems in America's schools, but it is the fastest, easiest, cheapest way of boosting school performance. According to FRAC, the federal breakfast program run by the Agricultural Department reached a record 7.7 million…

From the Inner City to the Elite

ERIC Educational Resources Information Center

Farmer, Ann

2005-01-01

Vassar College in Poughkeepsie, New York, offers to a select group of community college students from around the U.S., an intensive summer program called Exploring Transfer. Exploring Transfer, which recently completed its 21st summer season, is hailed as an affirmative-action program that provides a much-needed educational boost to its diverse,…

Tangled up in Blue: Boosting Mental Health Services at Community Colleges

ERIC Educational Resources Information Center

Finkel, Ed

2016-01-01

In a recent survey of 4,000 community college students, half reported experiencing a mental health condition. American College Counseling Association's (ACCA) fifth annual survey of personal and mental health counseling at community colleges provides some data from 159 professionals at two-year colleges in 41 states and Puerto Rico. Among the…

Parents, Are You Aware of the Commercial Activity in Your School? You Should Be.

ERIC Educational Resources Information Center

Molnar, Alex

2003-01-01

Explains that financially strapped and resource-poor schools often accept corporate-sponsored educational materials and ads, especially when they come with free computers or other resources, discussing how corporations use schools to boost brand loyalty; how commercialism undermines the health of students (e.g., soda machines in schools, which…

The Changing Face of the College Store

ERIC Educational Resources Information Center

Halligan, Tom

2008-01-01

Increased competition from Internet merchants, coupled with the swelling popularity of electronic books and skyrocketing textbook prices, is forcing the nation's college stores to get creative, find new ways to boost revenues, and drive sales of books and other merchandise to students and faculty. To make up for lost revenue as a result of…

Goal Complexity in Financial Aid and the Contingency of Organizational Sector

ERIC Educational Resources Information Center

Rutherford, Amanda

2016-01-01

Expectations of public institutions of higher education now include a growing number of competing goals. Financial assistance policies are expected to reward student talent, expand access to education, boost retention and graduation rates, and more. Yet research has not generally provided an empirical assessment of whether and how higher levels of…

Ticket to Work: Why Certificates Build Careers and Boost Economic Success

ERIC Educational Resources Information Center

Woods, Bob

2012-01-01

As community colleges cement their role as catalysts for the nation's economic recovery, administrators struggle to set the record straight about one long-standing misconception: that a large number of community college students leave without achieving their professional or academic goals. Now, a new policy brief from the American Association of…

Boosting Female Ambition: How College Diversity Impacts Graduate Degree Aspirations of Women. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Tsui, Lisa

In seeking to expand research on the actual effects of diversity on college students, this study investigated whether various multi-cultural and feminism-related variables at the individual, peer, and institutional levels significantly influenced educational degree ambitions among women. The study used data from the Cooperative Institutional…

Fluency Idol: Using Pop Culture to Engage Students and Boost Fluency Skills

ERIC Educational Resources Information Center

Calo, Kristine M.; Woolard-Ferguson, Taylor; Koitz, Ellen

2013-01-01

This article shares an oral reading practice that develops children's fluency skills, with a particular emphasis on performance reading and prosody. The authors share their experiences with Fluency Idol! as a way to engage young children by tapping into pop culture. The practice emphasizes repeated readings, feedback, practice, and…

More than Prize Lists: Head Teachers, Student Prize Winners, School Ceremonies and Educational Promotion in Colonial South Australia

ERIC Educational Resources Information Center

Young, Marisa

2007-01-01

Australian educators now operate in environments that frequently stress marketing activities. This article highlights the ways that colonial school prize ceremonies were deliberately developed to promote teaching activities. These ceremonies were part of carefully considered strategies that helped to boost the status of entrepreneurial teachers…

The Early Career Paths of UK-Educated Intra-European Mobile Graduates

ERIC Educational Resources Information Center

Behle, Heike

2017-01-01

Students and graduates alike are encouraged to enhance their skills and knowledge by moving to a different European country as both national governments and European institutions anticipate individual skill gains, closer European networks and a boost to national economies as a result. Using data from a longitudinal survey, this paper follows…

NAEP Test-Taking Pool Grows More Inclusive

ERIC Educational Resources Information Center

Maxwell, Lesli A.; Shah, Nirvi

2011-01-01

Following a push to make "the nation's report card" better reflect the academic performance of all children in America's schools, most states boosted the numbers of students with disabilities and English-language learners who participated in the 2011 reading and math tests that are part of the National Assessment of Educational Progress (NAEP).…

More High School Graduates: How Schools Can Save Students from Dropping Out

ERIC Educational Resources Information Center

Levin, Ben

2012-01-01

"More High School Graduates" is a comprehensive guide for school leaders and government policymakers committed to boosting high school graduation rates. Drawing from his knowledge as an education official and professor, author Ben Levin presents a system to turn around secondary schools that is adaptable for local-, district-, and state-level…

Sacred Heart University's Online Emergency Plan Boosts Interagency Cooperation

ERIC Educational Resources Information Center

Healy, Paul J.

2010-01-01

Taking its responsibility to students, faculty, and staff seriously, Sacred Heart University wanted a highly effective emergency response plan, one that could be updated at any time, with information always available to first responders and other authorized users. For this lifesaving function, the university built a Web site based on Microsoft[R]…

Improved Saturated Hydraulic Conductivity Pedotransfer Functions Using Machine Learning Methods

NASA Astrophysics Data System (ADS)

Araya, S. N.; Ghezzehei, T. A.

2017-12-01

Saturated hydraulic conductivity (Ks) is one of the fundamental hydraulic properties of soils. Its measurement, however, is cumbersome and instead pedotransfer functions (PTFs) are often used to estimate it. Despite a lot of progress over the years, generic PTFs that estimate hydraulic conductivity generally don't have a good performance. We develop significantly improved PTFs by applying state of the art machine learning techniques coupled with high-performance computing on a large database of over 20,000 soils—USKSAT and the Florida Soil Characterization databases. We compared the performance of four machine learning algorithms (k-nearest neighbors, gradient boosted model, support vector machine, and relevance vector machine) and evaluated the relative importance of several soil properties in explaining Ks. An attempt is also made to better account for soil structural properties; we evaluated the importance of variables derived from transformations of soil water retention characteristics and other soil properties. The gradient boosted models gave the best performance with root mean square errors less than 0.7 and mean errors in the order of 0.01 on a log scale of Ks [cm/h]. The effective particle size, D10, was found to be the single most important predictor. Other important predictors included percent clay, bulk density, organic carbon percent, coefficient of uniformity and values derived from water retention characteristics. Model performances were consistently better for Ks values greater than 10 cm/h. This study maximizes the extraction of information from a large database to develop generic machine learning based PTFs to estimate Ks. The study also evaluates the importance of various soil properties and their transformations in explaining Ks.

The Future of Personalized Learning for Students with Disabilities

ERIC Educational Resources Information Center

Worthen, Maria

2016-01-01

Personalized learning models can give each student differentiated learning experiences based on their needs, interests, and strengths, including students with disabilities. Personalized learning can pinpoint specific gaps in student learning, identify where a student is on his or her learning pathway, and provide the appropriate interventions to…

The Professor-Student Learning Relationship in Higher Education: Wisdom from Students with Learning Disabilities

ERIC Educational Resources Information Center

Fox, Laurie; McNally, Jennifer Ceven

2018-01-01

This mixed-methods study addressed the professor-student learning relationship in higher education and perception of its helpfulness in learning among college students with diagnosed learning disabilities. The Relationship and Learning Questionnaire drew items from four previously researched instruments. Results identify students' preference for…

Do dental hygiene students fit the learning profile of the millennial student?

PubMed

Blue, Christine M

2009-12-01

Differences in learning and the cultural context of our students' life experiences are important variables that faculty members need to understand in order to be effective in the classroom. Faculty members are finding that millennial students' approaches to learning are often vastly different from their own and as a result feel frustrated in their ability to help these students with their learning needs. Cultivating awareness of how today's dental hygiene student learns as well as the millennial learner profile can help faculty members address this educational challenge. The purpose of this study was to identify the learning styles of three groups of dental hygiene students and determine if they fit the learning profile of the millennial student as measured by the Learning Type Measure. Given this new generation of learners, it was hypothesized that dental hygiene students' learning style preferences would fit the learning profile of the millennial student. The Learning Type Measure was administered to 101 dental hygiene students at the University of Minnesota, University of Arizona, and Virginia Commonwealth University. The results from the study revealed that dental hygiene students do exhibit learning style preferences consistent with the millennial learner profile.

Complexity, Training Paradigm Design, and the Contribution of Memory Subsystems to Grammar Learning

PubMed Central

Ettlinger, Marc; Wong, Patrick C. M.

2016-01-01

Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative, procedural, and working memory subsystems. Experiment 1 demonstrated that passive, exposure-based training boosted learning of both simple and complex grammatical rules, relative to no training. Additionally, procedural memory correlated with simple rule learning, whereas declarative memory correlated with complex rule learning. Experiment 2 showed that presenting corrective feedback during the test phase did not improve learning. Experiment 3 revealed that structuring the order of training so that subjects are first exposed to the simple rule and then the complex improved learning. The cumulative findings shed light on the contributions of grammatical complexity, training paradigm design, and domain-general memory subsystems in determining grammar learning success. PMID:27391085

Approach to Learning of Sub-Degree Students in Hong Kong

ERIC Educational Resources Information Center

Chan, Yiu Man; Chan, Christine Mei Sheung

2010-01-01

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

Are students' impressions of improved learning through active learning methods reflected by improved test scores?

PubMed

Everly, Marcee C

2013-02-01

To report the transformation from lecture to more active learning methods in a maternity nursing course and to evaluate whether student perception of improved learning through active-learning methods is supported by improved test scores. The process of transforming a course into an active-learning model of teaching is described. A voluntary mid-semester survey for student acceptance of the new teaching method was conducted. Course examination results, from both a standardized exam and a cumulative final exam, among students who received lecture in the classroom and students who had active learning activities in the classroom were compared. Active learning activities were very acceptable to students. The majority of students reported learning more from having active-learning activities in the classroom rather than lecture-only and this belief was supported by improved test scores. Students who had active learning activities in the classroom scored significantly higher on a standardized assessment test than students who received lecture only. The findings support the use of student reflection to evaluate the effectiveness of active-learning methods and help validate the use of student reflection of improved learning in other research projects. Copyright © 2011 Elsevier Ltd. All rights reserved.

The influence of tutor training for peer tutors in the dissection course on the learning behavior of students.

PubMed

Shiozawa, T; Hirt, B; Lammerding-Koeppel, M

2016-11-01

Student tutors in the dissection course are expected to meet high demands in their job, to fulfill these expectations they receive training. Combined tutor training is well accepted by tutors and tutees, however, it is not known how tutor training influences student learning. Deduced from the learning goals of the tutor training, a randomized, controlled, single-blinded study was set up with a quantitative cross-sectional analysis to compare student learning behavior. A total of 197 medical students, coached either by ten trained or ten untrained tutors, were enlisted in the study. To assess the students' learning behavior we employed the LIST questionnaire. A common factor analysis was calculated to extract dimensions. Factor scores of the extracted dimensions were calculated for both groups to estimate differences in learning behavior. Factor analysis of the LIST questionnaire revealed eight factors explaining 47.57% of the overall variance. The eight factors comprise: deep learning, attention, learning organization, cooperative learning, time management, learning effort, superficial learning and learning environment. Comparing the factor scores of the extracted dimensions, students coached by trained tutors learned significantly more with their fellow students (factor score in cooperative learning 0.194 vs. -0.205, p<0.05), than students trained by untrained tutors. Students coached by trained tutors also tend to be better organized in their learning (factor score in learning organization 0.115 vs. -0.122, p=0.16). The learning behavior of students coached by trained tutors differs from the learning behavior of students coached by untrained tutors. Students coached by trained tutors learn significantly more often in teams than their colleagues and are better organized. Copyright © 2016 Elsevier GmbH. All rights reserved.

The diversity of Iranian nursing students' clinical learning styles: a qualitative study.

PubMed

Baraz, Shahram; Memarian, Robabeh; Vanaki, Zohreh

2014-09-01

Numerous factors, including learning styles, affect the learning process of nursing students. Having insights about students' learning styles helps promoting the quality of education. The aim of this study was to explore the Iranian baccalaureate nursing students' learning styles in clinical settings. A qualitative design using a content analysis approach was used to collect and analyze data. Semi-structured interviews were conducted with fifteen Iranian baccalaureate nursing students selected using a purposive sample method. During data analysis, it was found that nursing students employed different clinical learning styles such as 'thoughtful observation,' 'learning by thinking,' and 'learning by doing'. Students adopt different learning strategies in clinical practice. Designing teaching strategies based on students' learning styles can promote students' learning and maximize their academic and clinical practice success. Nursing educators, curriculum designers, and students can use the findings of this study to improve the quality of nursing education in both the classroom and clinical settings. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Internship Preparation Camp at the University of Maryland.

PubMed

Bontempo, Laura J; Frayha, Neda; Dittmar, Philip C

2017-01-01

Specialty-specific 'boot camps' boost the competence and confidence of medical school graduates as they prepare to enter a residency programme. We sought to evaluate the efficacy of a specialty-neutral Internship Preparation Camp (IPC) that we developed and made available to senior medical students at our medical school. The primary goal of the IPC is to educate students in the cognitive and procedural skills that are applicable to postgraduate year 1 trainees in all fields of specialisation. The curriculum was developed through input from senior medical students and faculty from multiple specialties. The course used small-group sessions and skills labs led by distinguished speakers from various professions (medicine, nursing and pharmacy) to teach senior medical students the information and skills common to the needs of all new physicians, regardless of the specialty they have chosen. The course was presented across 3 half-days and was offered just prior to graduation. Of 166 possible participants, 65 attended the course; 39 (60%) of them completed evaluations immediately following the course and 29 (45%) of participants completed a follow-up evaluation 3 months later. All respondents reported increased confidence in caring for patients in all subject areas taught. In the follow-up survey, 82% of respondents reported using information learned during the course on an hourly, daily or weekly basis in their care of patients. A specialty-neutral IPC is of benefit to its attendees, regardless of the medical specialty in which they train. 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/.

MC-1 Engine Valves, Lessons Learned

NASA Technical Reports Server (NTRS)

Laszar, John

2003-01-01

Many lessons were learned during the development of the valves for the MC-1 engine. The purpose of this report is to focus on a variety of issues related to the engine valves and convey the lessons learned. This paper will not delve into detailed technical analysis of the components. None of the lessons learned are new or surprising, but simply reinforce the importance of addressing the details of the design early, at the component level. The Marshall Space Flight Center (MSFC), Huntsville, Alabama developed the MC-1 engine, a LOX / FW-1, 60,000 pound thrust engine. This engine was developed under the Low Cost Boost Technology office at MSFC and proved to be a very successful project for the MSFC Propulsion team and the various subcontractors working the development of the engine and its components.

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed Central

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F.

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students. PMID:28559866

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students.

Mobile Learning in Nursing Undergraduates in China: Current Status, Attitudes and Barriers.

PubMed

Xiao, Qian; Zhang, Qiannan; Wang, Lanlan; Wang, Yanling; Sun, Liu; Wu, Ying

2017-01-01

To explore the current status, attitudes and barriers of nursing undergraduates toward mobile learning, 157 nursing students were investigated. more than half of them used mobile learning frequently in past half year. The mean score of students' intention towards mobile learning was 10.5 (ranged from 6 to 15), and it related to students' gender, expected effect, ease of operation, influence of other students, self-learning management and perceived interest. Some barriers affected students' mobile learning. Therefore, students had positive attitude and perception toward mobile learning, then we should create enough conditions to promote students' mobile learning.

Effectiveness of students worksheet based on mastery learning in genetics subject

NASA Astrophysics Data System (ADS)

Megahati, R. R. P.; Yanti, F.; Susanti, D.

2018-05-01

Genetics is one of the subjects that must be followed by students in Biology education department. Generally, students do not like the genetics subject because of genetics concepts difficult to understand and the unavailability of a practical students worksheet. Consequently, the complete learning process (mastery learning) is not fulfilled and low students learning outcomes. The aim of this study develops student worksheet based on mastery learning that practical in genetics subject. This research is a research and development using 4-D models. The data analysis technique used is the descriptive analysis that describes the results of the practicalities of students worksheets based on mastery learning by students and lecturer of the genetic subject. The result is the student worksheet based on mastery learning on genetics subject are to the criteria of 80,33% and 80,14%, which means that the students worksheet practical used by lecturer and students. Student’s worksheet based on mastery learning effective because it can increase the activity and student learning outcomes.

From Desktop to Teraflop: Exploiting the U.S. Lead in High Performance Computing. NSF Blue Ribbon Panel on High Performance Computing.

ERIC Educational Resources Information Center

National Science Foundation, Washington, DC.

This report addresses an opportunity to accelerate progress in virtually every branch of science and engineering concurrently, while also boosting the American economy as business firms also learn to exploit these new capabilities. The successful rapid advancement in both science and technology creates its own challenges, four of which are…

The Use of ICT in the Assessment of Modern Languages: The English Context and European Viewpoints

ERIC Educational Resources Information Center

Hunt, Marilyn; Neill, Sean; Barnes, Ann

2007-01-01

The ever increasing explosion of highly attractive multimedia resources on offer has boosted the use of information and communication technology (ICT) in the teaching and learning of modern languages. The use of ICT to assess languages is less frequent, however, although online testing is starting to develop. This paper examines the national…

INL Director Discusses Lessons Learned from TMI, Fukushima

ScienceCinema

Grossenbacher, John

2017-12-22

Idaho National Laboratory's Director John Grossenbacher explains how the U.S. nuclear industry has boosted its safety procedures as a result of the Three Mile Island (TMI) accident in 1979 and how the industry plans to use current events at Japan's Fukushima nuclear plants to further enhance safety. For more information about INL's nuclear energy research, visit http://www.facebook.com/idahonationallaboratory.

Improving Access to Prekindergarten for Children of Immigrants: "Building Relationships." Fact Sheet No. 3

ERIC Educational Resources Information Center

Lei, Serena

2014-01-01

Pre-K has been shown to strongly boost children's learning trajectories. This is as true, or even truer, for children of immigrants and English language learners (ELLs) as for children overall. Children of immigrants, who make up about a quarter of children in the United States, have significantly lower rates of pre-K enrollment, on average, than…

Improving Access to Prekindergarten for Children of Immigrants: "Enrollment Strategies." Fact Sheet No. 2

ERIC Educational Resources Information Center

Lei, Serena

2014-01-01

Pre-K has been shown to strongly boost children's learning trajectories. This is as true, or even truer, for children of immigrants and English language learners (ELLs) as for children overall. Children of immigrants, who make up about a quarter of children in the United States, have significantly lower rates of pre-K enrollment, on average, than…

Learning to Eat: Who Knew the Ivory Tower Had a Kitchen?

ERIC Educational Resources Information Center

Cardone, Kenneth

2009-01-01

Beating the competition with restaurant-style dining, wood-fired pizza ovens, espresso machines and organic vegetables is one of many ways for colleges to attract and hold the best and brightest. It also seems that fond food memories fuel alumni associations, which increase attendance at reunions and boost giving. But is it just an arms race with…

Improving Access to Prekindergarten for Children of Immigrants: "Outreach." Fact Sheet No. 1

ERIC Educational Resources Information Center

Lei, Serena

2014-01-01

Pre-K has been shown to strongly boost children's learning trajectories. This is as true, or even truer, for children of immigrants and English language learners (ELLs) as for children overall. Children of immigrants, who make up about a quarter of children in the United States, have significantly lower rates of pre-K enrollment, on average, than…

The Effect of Google Earth and Wiki Models on Oral Presentation Skills of University EFL Learners

ERIC Educational Resources Information Center

Awada, Ghada; Diab, Hassan B.

2018-01-01

This article reports the results of an experimental study that investigated the effectiveness of Google Earth and Wiki tools in improving the oral presentation skills of English as a Foreign Language (EFL) learners and boosting their motivation for learning. The participants (n =81) are enrolled in writing classes at two English-medium…

Increasing Student Metacognition and Learning through Classroom-Based Learning Communities and Self-Assessment †

PubMed Central

Siegesmund, Amy

2016-01-01

Student overconfidence challenges success in introductory biology. This study examined the impact of classroom learning communities and self-assessment on student metacognition and subsequent impact on student epistemological beliefs, behaviors, and learning. Students wrote weekly self-assessments reflecting on the process of learning and received individual feedback. Students completed a learning strategies inventory focused on metacognition and study behaviors at the beginning and end of the semester and a Student Assessment of their Learning Gains (SALG) at the end of the semester. Results indicated significant changes in both metacognition and study behaviors over the course of the semester, with a positive impact on learning as determined by broad and singular measures. Self-assessments and SALG data demonstrated a change in student beliefs and behaviors. Taken together, these findings argue that classroom learning communities and self-assessment can increase student metacognition and change student epistemological beliefs and behaviors. PMID:27158301

Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning

PubMed Central

2017-01-01

This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image of Liverpool (UK) to evaluate their potential to predict Living Environment Deprivation at a small statistical area level. We also contribute to the methodological literature on the estimation of socioeconomic indices with remote-sensing data by introducing elements from modern machine learning. In addition to classical approaches such as Ordinary Least Squares (OLS) regression and a spatial lag model, we explore the potential of the Gradient Boost Regressor and Random Forests to improve predictive performance and accuracy. In addition to novel predicting methods, we also introduce tools for model interpretation and evaluation such as feature importance and partial dependence plots, or cross-validation. Our results show that Random Forest proved to be the best model with an R2 of around 0.54, followed by Gradient Boost Regressor with 0.5. Both the spatial lag model and the OLS fall behind with significantly lower performances of 0.43 and 0.3, respectively. PMID:28464010

Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning.

PubMed

Arribas-Bel, Daniel; Patino, Jorge E; Duque, Juan C

2017-01-01

This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image of Liverpool (UK) to evaluate their potential to predict Living Environment Deprivation at a small statistical area level. We also contribute to the methodological literature on the estimation of socioeconomic indices with remote-sensing data by introducing elements from modern machine learning. In addition to classical approaches such as Ordinary Least Squares (OLS) regression and a spatial lag model, we explore the potential of the Gradient Boost Regressor and Random Forests to improve predictive performance and accuracy. In addition to novel predicting methods, we also introduce tools for model interpretation and evaluation such as feature importance and partial dependence plots, or cross-validation. Our results show that Random Forest proved to be the best model with an R2 of around 0.54, followed by Gradient Boost Regressor with 0.5. Both the spatial lag model and the OLS fall behind with significantly lower performances of 0.43 and 0.3, respectively.

'Simulation-based learning in psychiatry for undergraduates at the University of Zimbabwe medical school'.

PubMed

Piette, Angharad; Muchirahondo, Florence; Mangezi, Walter; Iversen, Amy; Cowan, Frances; Dube, Michelle; Peterkin, Hugh Grant-; Araya, Ricardo; Abas, Melanie

2015-02-21

The use of simulated patients to teach in psychiatry has not been reported from low-income countries. This is the first study using simulation teaching in psychiatry in Africa. The aim of this study was to introduce a novel method of psychiatric teaching to medical students at the University of Zimbabwe and assess its feasibility and preliminary effectiveness. We selected depression to simulate because students in Zimbabwe are most likely to see cases of psychoses during their ward-based clinical exposure. Zimbabwean psychiatrists adapted scenarios on depression and suicide based on ones used in London. Zimbabwean post-graduate trainee psychiatrists were invited to carry out the teaching and psychiatric nursing staff were recruited and trained in one hour to play the simulated patients (SPs). All students undertaking their psychiatry placement (n = 30) were allocated into groups for a short didactic lecture on assessing for clinical depression and then rotated around 3 scenarios in groups of 4-5 and asked to interview a simulated patient with signs of depression. Students received feedback from peers, SPs and facilitators. Students completed the Confidence in Assessing and Managing Depression (CAM-D) questionnaire before and after the simulation session and provided written free-text feedback. Post-graduate trainers, together with one consultant, facilitated the simulated teaching after three hours training. Student confidence scores increased from mean 15.90 to 20.05 (95% CI = 2.58- 5.71) t (20) = 5.52, (p > 0.0001) following the simulation teaching session. Free-text feedback was positive overall with students commenting that it was "helpful", "enjoyable" and "boosted confidence". In Zimbabwe, simulation teaching was acceptable and could be adapted with minimal effort by local psychiatrists and implemented by post-graduate trainees and one consultant, Students found it helpful and enjoyable and their confidence increased after the teaching. It offers students a broader exposure to psychiatric conditions than they receive during clinical attachment to the inpatient wards. Involving psychiatry trainees and nursing staff may be a sustainable approach in a setting with small number of consultants and limited funds to pay for professional actors.

An e-learning course in medical immunology: does it improve learning outcome?

PubMed

Boye, Sondre; Moen, Torolf; Vik, Torstein

2012-01-01

E-learning is used by most medical students almost daily and several studies have shown e-learning to improve learning outcome in small-scale interventions. However, few studies have explored the effects of e-learning in immunology. To study the effect of an e-learning package in immunology on learning outcomes in a written integrated examination and to examine student satisfaction with the e-learning package. All second-year students at a Norwegian medical school were offered an animated e-learning package in basic immunology as a supplement to the regular teaching. Each student's log-on-time was recorded and linked with the student's score on multiple choice questions included in an integrated end-of-the-year written examination. Student satisfaction was assessed through a questionnaire. The intermediate-range students (interquartile range) on average scored 3.6% better on the immunology part of the examination per hour they had used the e-learning package (p = 0.0046) and log-on-time explained 17% of the variance in immunology score. The best and the less skilled students' examination outcomes were not affected by the e-learning. The e-learning was well appreciated among the students. Use of an e-learning package in immunology in addition to regular teaching improved learning outcomes for intermediate-range students.

Self-directed learning readiness of Asian students: students perspective on a hybrid problem based learning curriculum.

PubMed

Leatemia, Lukas D; Susilo, Astrid P; van Berkel, Henk

2016-12-03

To identify the student's readiness to perform self-directed learning and the underlying factors influencing it on the hybrid problem based learning curriculum. A combination of quantitative and qualitative studies was conducted in five medical schools in Indonesia. In the quantitative study, the Self Directed Learning Readiness Scale was distributed to all students in all batches, who had experience with the hybrid problem based curriculum. They were categorized into low- and high -level based on the score of the questionnaire. Three focus group discussions (low-, high-, and mixed level) were conducted in the qualitative study with six to twelve students chosen randomly from each group to find the factors influencing their self-directed learning readiness. Two researchers analysed the qualitative data as a measure of triangulation. The quantitative study showed only half of the students had a high-level of self-directed learning readiness, and a similar trend also occurred in each batch. The proportion of students with a high level of self-directed learning readiness was lower in the senior students compared to more junior students. The qualitative study showed that problem based learning processes, assessments, learning environment, students' life styles, students' perceptions of the topics, and mood, were factors influencing their self-directed learning. A hybrid problem based curriculum may not fully affect the students' self-directed learning. The curriculum system, teacher's experiences, student's background and cultural factors might contribute to the difficulties for the student's in conducting self-directed learning.

Ideal versus School Learning: Analyzing Israeli Secondary School Students' Conceptions of Learning

ERIC Educational Resources Information Center

Hadar, Linor

2009-01-01

This study explored 130 secondary school students' conceptions of learning using an open-ended task, analyzed both qualitatively and quantitatively. Students' reality of learning comprised two separate spheres, ideal learning and school learning, which rarely interacted. Generally, students commented more about school than ideal learning. Factor…

Distance Learning Students' Evaluation of E-Learning System in University of Tabuk, Saudi Arabia

ERIC Educational Resources Information Center

Al-Juda, Mefleh Qublan B.

2017-01-01

This study evaluates the experiences and perceptions of students regarding e-learning systems and their preparedness for e-learning. It also investigates the overall perceptions of students regarding e-learning and the factors influencing students' attitudes towards e-learning. The study uses convenience sampling in which students of the Education…

Student Achievement in Basic College Mathematics: Its Relationship to Learning Style and Learning Method

ERIC Educational Resources Information Center

Gunthorpe, Sydney

2006-01-01

From the assumption that matching a student's learning style with the learning method best suited for the student, it follows that developing courses that correlate learning method with learning style would be more successful for students. Albuquerque Technical Vocational Institute (TVI) in New Mexico has attempted to provide students with more…

Higher Learning: Developing Students' Powers of Learning in Higher Education

ERIC Educational Resources Information Center

Bourner, Tom

2009-01-01

This article is about student learning, specifically the problem of what a university can do to develop its students' powers of learning. The broad approach is to discover what we can learn from the university's long experience with developing students' critical faculties and then apply the lessons to developing students' powers of learning. The…

Combining Active Learning with Service Learning: A Student-Driven Demonstration Project.

ERIC Educational Resources Information Center

Hatcher-Skeers, Mary; Aragon, Ellen

2002-01-01

Describes a project that integrates active learning into service learning targeting both college students and middle schools students wherein college students perform chemical demonstrations for middle school students. (YDS)

Towards Automatically Detecting Whether Student Learning Is Shallow

ERIC Educational Resources Information Center

Gowda, Sujith M.; Baker, Ryan S.; Corbett, Albert T.; Rossi, Lisa M.

2013-01-01

Recent research has extended student modeling to infer not just whether a student knows a skill or set of skills, but also whether the student has achieved robust learning--learning that enables the student to transfer their knowledge and prepares them for future learning (PFL). However, a student may fail to have robust learning in two fashions:…

An Examination through Conjoint Analysis of the Preferences of Students Concerning Online Learning Environments According to Their Learning Styles

ERIC Educational Resources Information Center

Daghan, Gökhan; Akkoyunlu, Buket

2012-01-01

This study examines learning styles of students receiving education via online learning environments, and their preferences concerning the online learning environment. Maggie McVay Lynch Learning Style Inventory was used to determine learning styles of the students. The preferences of students concerning online learning environments were detected…

Using appreciative inquiry to help students identify strategies to overcome handicaps of their learning styles.

PubMed

Kumar, Latha Rajendra; Chacko, Thomas Vengail

2012-01-01

In India, as in some other neighboring Asian countries, students and teachers are generally unaware of the differences in the learning styles among learners, which can handicap students with learning styles alien to the common teaching/learning modality within the institution. This study aims to find out whether making students aware of their learning styles and then using the Appreciative Inquiry approach to help them discover learning strategies that worked for them and others with similar learning styles within the institution made them perceive that this experience improved their learning and performance in exams. The visual, auditory, read-write, and kinesthetic (VARK) inventory of learning styles questionnaire was administered to all 100 first-year medical students of the Father Muller's Medical College in Mangalore India to make them aware of their individual learning styles. An Appreciate Inquiry intervention was administered to 62 student volunteers who were counseled about the different learning styles and their adaptive strategies. Pre and post intervention change in student's perception about usefulness of knowing learning styles on their learning, learning behavior, and performance in examinations was collected from the students using a prevalidated questionnaire. Post intervention mean scores showed a significant change (P < 0.0001) in student's self-perceptions about usefulness of knowing one's learning style and discovering strategies that worked within the institutional environment. There was agreement among students that the intervention helped them become more confident in learning (84%), facilitating learning in general (100%), and in understanding concepts (100%). However, only 29% of the students agreed that the intervention has brought about their capability improvement in application of learning and 31% felt it improved their performance in exams. Appreciate Inquiry was perceived as useful in helping students discover learning strategies that work for different individual learning styles and sharing them within the group helped students choose strategies to help overcome the handicap presented by the school's teaching methods.

Peer learning a pedagogical approach to enhance online learning: A qualitative exploration.

PubMed

Raymond, Anita; Jacob, Elisabeth; Jacob, Darren; Lyons, Judith

2016-09-01

Flexible online programs are becoming increasingly popular method of education for students, allowing them to complete programs in their own time and cater for lifestyle differences. A mixture of delivery modes is one way which allows for enhanced learning. Peer learning is another method of learning which is shown to foster collaboration and prepare healthcare students for their future careers. This paper reports on a project to combine peer and online learning to teach pharmacology to nursing students. To explore undergraduate nursing student opinions of working in peer groups for online learning sessions in a pharmacology course. A qualitative study utilising a self-reported questionnaire. A rural campus of an Australian university. Second year nursing students enrolled in a Bachelor of Nursing Program. A hard copy questionnaire was distributed to all students who attended the final semester lecture for the course. Content analysis of open-ended survey questions was used to identify themes in the written data. Of the 61 students enrolled in the nursing subject, 35 students chose to complete the survey (57%). Students reported a mixed view of the benefits and disadvantages of peer online learning. Sixty 6% (66%) of students liked peer online learning, whilst 29% disliked it and 6% were undecided. Convenience and ease of completion were reported as the most common reason to like peer online learning, whilst Information Technology issues, communication and non-preferred learning method were reasons for not liking peer online learning. Peer online learning groups' acted as one further method to facilitate student learning experiences. Blending peer online learning with traditional face-to-face learning increases the variety of learning methods available to students to enhance their overall learning experience. Copyright © 2016 Elsevier Ltd. All rights reserved.

A National Study Assessing the Teaching and Learning of Introductory Astronomy; Part II: Analysis of Student Demographics

NASA Astrophysics Data System (ADS)

Prather, E. E.; Consiglio, D.; Rudolph, A. L.; Brissenden, G.

2011-09-01

This is the second in a series of reports on a national study of the teaching and learning of astronomy in general education, non-science major, introductory astronomy courses (Astro 101). We report here on the analysis of how individual student characteristics affect student learning in these classes, and whether the demonstrated positive effect of interactive learning strategies on student learning differs based on these characteristics. This analysis was conducted using data from nearly 2000 students enrolled in 69 Astro 101 classes taught across the country. These students completed a 15-question demographic survey, in addition to completing the 26-question Light and Spectroscopy Concept Inventory (LSCI) pre- and post-instruction. The LSCI was used to determine student learning via a normalized gain calculated for each student. A multivariate regression analysis was conducted to determine how ascribed characteristics (personal demographic and family characteristics), obtained characteristics (academic achievement and student major), and the use of interactive learning strategies predict student learning in these classes. The results show dramatic improvement in student learning with increased use of interactive learning strategies even after controlling for individual characteristics. In addition, we find that the positive effects of interactive learning strategies are the same for strong and weak students, men and women, across ethnicities, and regardless of primary language. The research strongly suggests all students benefit from interactive learning strategies.

Collaborative, case-based learning: how do students actually learn from each other?

PubMed

Thurman, Joanne; Volet, Simone E; Bolton, John R

2009-01-01

The value of collaborative, case-based, and problem-based learning has received increased attention in recent years. Several studies have documented veterinary staff and students' generally positive feedback on group learning activities, but one largely unaddressed question is how students actually learn from each other. This study examined how second-year veterinary students learned from each other during a collaborative, case-based learning project. Data were students' written reflections on their learning in the veterinary course and the specific learning experience, and a matched pre- and post-task questionnaire. Consistent with prior research describing veterinary students as individualistic learners, only a third of students spontaneously mentioned learning from each other as one of their most effective strategies. However, when prompted to describe a time when they felt that group members were really learning from each other, students reported highly valuable collaborative learning processes, which they explicitly linked to learning and understanding benefits. Questionnaire data were consistent, showing that students became more positive toward several aspects of the activity as well as toward group work in general. One unexpected finding was the lack of a relationship between students' self-evaluation of their learning and how well group members knew each other. These findings provide strong support for the educational value of collaborative, case-based learning. In light of other research evidence (using observation data) that the amount of time students actually engage in high-level collaborative processes may be rather limited, this article points to the need for veterinary teachers to better prepare students for group learning activities.

Exam Success at Undergraduate and Graduate-Entry Medical Schools: Is Learning Style or Learning Approach More Important? A Critical Review Exploring Links Between Academic Success, Learning Styles, and Learning Approaches Among School-Leaver Entry ("Traditional") and Graduate-Entry ("Nontraditional") Medical Students.

PubMed

Feeley, Anne-Marie; Biggerstaff, Deborah L

2015-01-01

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

A Turkish study of medical student learning styles.

PubMed

Kalaca, S; Gulpinar, M

2011-12-01

A good understanding of the learning styles of students is necessary for optimizing the quality of the learning process. There are few studies in Turkey on the subject of the learning characteristics of medical students. The aim of this study was to define the learning patterns of Turkish medical students based on the Turkish version of Vermunts Inventory of Learning Styles (ILS). The Turkish version of the ILS was developed and administered to 532 medical students. Learning patterns were investigated using factor analysis. Internal consistencies of scales ranged from 0.43 to 0.80. The Turkish version of the ILS identified four learning styles among medical students. In comparing the pre-clinical and clinical phases of medical students related to mental models of learning, statistically significant differences (p < .01) were found between the two groups for the learning characteristics: lack of regulation; certificate; self-test and ambivalent orientation; intake of knowledge; and use of knowledge. The Turkish version of the ILS can be used to identify learning styles of medical students. Our findings indicate an intermediate position for our students on a teacher-regulated to student-regulated learning continuum. A variety of teaching methods and learning activities should be provided in medical schools in order to address the range of learning styles.

Shaping a valued learning journey: Student satisfaction with learning in undergraduate nursing programs, a grounded theory study.

PubMed

Smith, Morgan R; Grealish, Laurie; Henderson, Saras

2018-05-01

Student satisfaction is a quality measure of increasing importance in undergraduate programs, including nursing programs. To date theories of student satisfaction have focused primarily on students' perceptions of the educational environment rather than their perceptions of learning. Understanding how students determine satisfaction with learning is necessary to facilitate student learning across a range of educational contexts and meet the expectations of diverse stakeholders. To understand undergraduate nursing students' satisfaction with learning. Constructivist grounded theory methodology was used to identify how nursing students determined satisfaction with learning. Two large, multi-campus, nursing schools in Australia. Seventeen demographically diverse undergraduate nursing students studying different stages of a three year program participated in the study. Twenty nine semi-structured interviews were conducted. Students were invited to describe situations where they had been satisfied or dissatisfied with their learning. A constructivist grounded theory approach was used to analyse the data. Students are satisfied with learning when they shape a valued learning journey that accommodates social contexts of self, university and nursing workplace. The theory has three phases. Phase 1 - orienting self to valued learning in the pedagogical landscape; phase 2 - engaging with valued learning experiences across diverse pedagogical terrain; and phase 3 - recognising valued achievement along the way. When students experience a valued learning journey they are satisfied with their learning. Student satisfaction with learning is unique to the individual, changes over time and maybe transient or sustained, mild or intense. Finding from the research indicate areas where nurse academics may facilitate satisfaction with learning in undergraduate nursing programs while mindful of the expectations of other stakeholders such as the university, nurse registering authorities, employers and the receivers of nursing care. Copyright © 2018 Elsevier Ltd. All rights reserved.

Non-parametric adaptative JPEG fragments carving

NASA Astrophysics Data System (ADS)

Amrouche, Sabrina Cherifa; Salamani, Dalila

2018-04-01

The most challenging JPEG recovery tasks arise when the file header is missing. In this paper we propose to use a two layer machine learning model to restore headerless JPEG images. We first build a classifier able to identify the structural properties of the images/fragments and then use an AutoEncoder (AE) to learn the fragment features for the header prediction. We define a JPEG universal header and the remaining free image parameters (Height, Width) are predicted with a Gradient Boosting Classifier. Our approach resulted in 90% accuracy using the manually defined features and 78% accuracy using the AE features.