Personalized learning in iSTART: Past modifications and future design |
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| Authors: | Kathryn S McCarthy Micah Watanabe Jianmin Dai Danielle S McNamara |
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| Institution: | 1. Department of Learning Sciences, Georgia State University, Atlanta, Georgia, USA;2. Kmccarthy12@gsu.edu;4. Department of Psychology, Arizona State University, Tempe, Arizona, USA |
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| Abstract: | AbstractComputer-based learning environments (CBLEs) provide unprecedented opportunities for personalized learning at scale. One such system, iSTART (Interactive Strategy Training for Active Reading and Thinking) is an adaptive, game-based tutoring system for reading comprehension. This paper describes how efforts to increase personalized learning have improved the system. It also provides results of a recent implementation of an adaptive logic that increases or decreases text difficulty based on students’ performance rather than presenting texts randomly. High school students who received adaptive text selection showed increased sense of learning. Adaptive text selection also resulted in greater pre-training to post-training comprehension test gains, especially for less-skilled readers. The findings demonstrate that system-driven, just-in-time support consistent with the goals of personalized learning benefit the efficacy of computer-based learning environments. |
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| Keywords: | Personalized learning reading comprehension text difficulty adaptive text selection |
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