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Sao Pedro, Michael A.; Baker, Ryan S. J. d.; Gobert, Janice D.; Montalvo, Orlando; Nakama, Adam – Grantee Submission, 2013
We present work toward automatically assessing and estimating science inquiry skills as middle school students engage in inquiry within a physical science microworld. Towards accomplishing this goal, we generated machine-learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in…
Descriptors: Artificial Intelligence, Inquiry, Middle School Students, Physical Sciences
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Lai, Yen-Shou; Tsai, Hung-Hsu; Yu, Pao-Ta – Educational Technology & Society, 2009
This paper proposes a multimedia English learning (MEL) system, based on Hidden Markov Models (HMMs) and mastery theory strategy, for teaching students with the aim of enhancing their English phonetic awareness and pronunciation. It can analyze phonetic structures, identify and capture pronunciation errors to provide students with targeted advice…
Descriptors: Experimental Groups, Control Groups, Quasiexperimental Design, Phonemic Awareness