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Volume 119, Number 3 (2017)

by Philip H. Winne
This article argues that today’s gold standard for identifying what works, the randomized controlled trial, poorly serves each and any individual learner. Elements of this argument provide grounds for proposed remedies in cases where software can log extensive data about the operations that each learner applies to learning and about each bit of information to which a learner applies those operations.
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by Susanne P. Lajoie & Eric Poitras
This article reviews recent advances in research by members of the Learning Environments Across Disciplines partnership on the design of adaptive technology-rich learning environments as cognitive, metacognitive, and affective tools. In particular, we examine the use of convergent methodologies and how the design guidelines of the learning environments are grounded in instructional theories and empirical evidence.
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by Victoria Q. Almeda, Ryan S. J. D. Baker & Albert Corbett
This article investigates whether there is an optimal point for determining whether a student needs help. Findings reveal that it is better for students within intelligent learning systems to seek help early in the learning process.
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by Herbert P. Ginsburg
This article discusses how high quality software can both promote children’s math learning and also provide analytic tools for studying its development over time. Macrogenetic research on digital learning can contribute to the further development of effective math education software, shed light on children’s math learning, and also largely eliminate the need for high-stakes testing and traditional achievement tests.
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by Korinn S. Ostrow, Neil T. Heffernan & Joseph Jay Williams
This article defines how educational technologies can be leveraged for use in collaborative research environments by highlighting the research revolution of ASSISTments, a popular online learning platform, and by outlining the many benefits made possible through educational research at scale.
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by Gary Natriello & Hui Soo Chae
An introduction to the special issue.
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by Gary Natriello
This article specifies a model to organize both historical and contemporary work to create adaptive learning opportunities and applies it to identify active lines of relevant research as well as areas for additional development.
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by I-Han Hsiao & Peter Brusilovsky
This paper attempts to integrate the ideas of adaptive navigation support and open student modeling, two prominent technologies in the field of personalized learning with social visualization.
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by Arthur C. Graesser, Carol M. Forsyth & Blair A. Lehman
Pedagogical agents are computerized talking heads or avatars that help students learn by performing actions and holding conversations with the students in natural language. This paper explores several designs of trialogues (two agents interacting with a human student) that have been productively implemented for particular students, subject matters, and depths of learning.
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