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Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – Grantee Submission, 2016
How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…
Descriptors: Sequential Learning, Data Collection, Information Retrieval, Evaluation Methods
Huang, Yong-Ming – Australasian Journal of Educational Technology, 2015
The use of collaborative technologies in learning has received considerable attention in recent years, but few studies to date have examined the factors that affect sequential and global learners' intention to use such technologies. Previous studies have shown that the learners of different learning styles have different needs for educational…
Descriptors: Technology Uses in Education, Intention, Performance Factors, Sequential Learning
Diket, Read M.; Xu, Lihua; Brewer, Thomas M. – Studies in Art Education: A Journal of Issues and Research in Art Education, 2014
The aspirational model resulted from the authors' secondary analysis of the Mother/Child (M/C) test block from the 2008 National Assessment of Educational Progress restricted data that examined the responses of the national sample of 8th-grade students (n = 1648). This test block presented no artmaking task and consisted of the same 13 questions…
Descriptors: Group Testing, Art Education, Grade 8, National Surveys

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