Arizona State's retention rate rose to 84 percent from 77 percent in recent years, a change that the provost credits largely to eAdvisor.
Open Research Online - Learning dispositions and transferable competencies: pedagogy, m... - 0 views
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Theoretical and empirical evidence in the learning sciences substantiates the view that deep engagement in learning is a function of a complex combination of learners' identities, dispositions, values, attitudes and skills. When these are fragile, learners struggle to achieve their potential in conventional assessments, and critically, are not prepared for the novelty and complexity of the challenges they will meet in the workplace, and the many other spheres of life which require personal qualities such as resilience, critical thinking and collaboration skills. To date, the learning analytics research and development communities have not addressed how these complex concepts can be modelled and analysed, and how more traditional social science data analysis can support and be enhanced by learning analytics. We report progress in the design and implementation of learning analytics based on a research validated multidimensional construct termed "learning power". We describe, for the first time, a learning analytics infrastructure for gathering data at scale, managing stakeholder permissions, the range of analytics that it supports from real time summaries to exploratory research, and a particular visual analytic which has been shown to have demonstrable impact on learners. We conclude by summarising the ongoing research and development programme and identifying the challenges of integrating traditional social science research, with learning analytics and modelling.
Learning Dispositions and Transferable Competencies: Pedagogy, Modelling, and Learning ... - 0 views
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Simon Buckingham Shum Ruth Deakin Crick 2012 (In review) Theoretical and empirical evidence in the learning sciences substantiates the view that deep engagement in learning is a function of a combination of learners' dispositions, values, attitudes and skills. When these are fragile, learners struggle to achieve their potential in conventional assessments, and critically, are not prepared for the novelty and complexity of the challenges they will meet in the workplace, and the many other spheres of life which require personal qualities such as resilience, critical thinking and collaboration skills. To date, the learning analytics research and development communities have not addressed how these complex concepts can be modelled and analysed. We report progress in the design and implementation of learning analytics based on an empirically validated multidimensional construct termed "learning power". We describe a learning analytics infrastructure for gathering data at scale, managing stakeholder permissions, the range of analytics that it supports from real time summaries to exploratory research, and a particular visual analytic which has been shown to have demonstrable impact on learners. We conclude by summarising the ongoing research and development programme.
Submissions for the Awards for Excellence in Learning Analytics « ascilite - 0 views
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"Awards for Excellence in Learning Analytics: Submissions The LA SIG operates an Awards program recognising excellence in the practical application of LA to enhance learning and teaching. A key driver for the Awards program is to create and share resources about effective LA practices. We want to give a voice to all who are working with LA to improve learning and teaching - whatever the scale of their endeavours. To this end, all presentations from Award applicants are available below for viewing. (Submissions closed on 11 September). We believe these presentations will form an important resource library around the use of LA in tertiary education across Australasia and New Zealand. You may view the awards submission criteria and other background information on the awards in the SIG Awards Program Information (PDF) and to find out more about LA-SIG activities, go here."
College Degrees, Designed by the Numbers - Technology - The Chronicle of Higher Education - 0 views
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Mr. Lange and his colleagues had found that by the eighth day of class, they could predict, with 70-percent accuracy, whether a student would score a C or better. Mr. Lange built a system, rolled out in 2009, that sent professors frequently updated alerts about how well each student was predicted to do, based on course performance and online behavior.
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Rio Salado knows from its database that students who hand in late assignments and don't log in frequently often fail or withdraw from a course. So the software is more likely to throw up a red flag for current students with those characteristics.
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July 18, 2012 College Degrees, Designed by the Numbers By Marc Parry Illustration by Randy Lyhus for The Chronicle Campuses are places of intuition and serendipity: A professor senses confusion on a student's face and repeats his point; a student majors in psychology after a roommate takes a course; two freshmen meet on the quad and eventually become husband and wife. Now imagine hard data substituting for happenstance. As Katye Allisone, a freshman at Arizona State University, hunkers down in a computer lab for an 8:35 a.m. math class, the Web-based course watches her back. Answers, scores, pace, click paths-it hoovers up information, like Google. But rather than personalizing search results, data shape Ms. Allisone's class according to her understanding of the material.
AUSSE | ACER - 0 views
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Australasian Survey of Student Engagement (AUSSE) Areas measured by the AUSSE The survey instruments used in the AUSSE collect information on around 100 specific learning activities and conditions along with information on individual demographics and educational contexts.The instruments contain items that map onto six student engagement scales: Academic Challenge - the extent to which expectations and assessments challenge students to learn; Active Learning - students' efforts to actively construct knowledge; Student and Staff Interactions - the level and nature of students' contact and interaction with teaching staff; Enriching Educational Experiences - students' participation in broadening educational activities; Supportive Learning Environment - students' feelings of support within the university community; and Work Integrated Learning - integration of employment-focused work experiences into study. The instruments also contain items that map onto seven outcome measures. Average overall grade is captured in a single item, and the other six are composite measures which reflect responses to several items: Higher-Order Thinking - participation in higher-order forms of thinking; General Learning Outcomes - development of general competencies; General Development Outcomes - development of general forms of individual and social development; Career Readiness - preparation for participation in the professional workforce; Average Overall Grade - average overall grade so far in course; Departure Intention - non-graduating students' intentions on not returning to study in the following year; and Overall Satisfaction - students' overall satisfaction with their educational experience.
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