James P Bywater

James P Bywater
James Madison University | JMU · College of Education

Doctor of Philosophy

About

9
Publications
626
Reads
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20
Citations

Publications

Publications (9)
Conference Paper
Researchers from around the world have shaped knowledge integration (KI), a framework that captures the processes learners use to build on their multiple ideas and refine their understanding. KI emerged 25 years ago from syntheses of experimental, longitudinal, and meta-analytic studies of learning and instruction. Advances in KI have resulted from...
Article
Research in teacher education highlights the importance of responding to student ideas. However, effectively noticing, interpreting, and then responding to students' mathematical ideas can be quite challenging for teachers as they try to balance multiple, competing goals in an authentic classroom setting. This study introduces the Teacher Respondin...
Article
This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the same learning design and adapted it to three different populations, settings, and classroom contexts: at the middle-scho...
Chapter
Open-ended learning environments afford students opportunities to explore, manipulate, and test concepts, and have the potential to provide students with feedback and support by leveraging the log data generated by them. However, within open-ended contexts, student log data is often noisy and identifying periods of meaningful activity is difficult....
Article
Computer‐aided design (CAD) simulation environments offer opportunities for students to evaluate, redesign, and visualize engineering design solutions quickly and get feedback. However, the use of CAD simulation tools in precollege settings is relatively rare. This study explores design strategies used by experienced designers in Energy3D, a CAD si...
Preprint
Full-text available
A large body of research demonstrates how teachers' questioning strategies can improve student learning outcomes. However, developing new scenarios is challenging because of the lack of training data for a specific scenario and the costs associated with labeling. This paper presents a high-fidelity, AI-based classroom simulator to help teachers reh...
Preprint
Full-text available
High-fidelity, AI-based simulated classroom systems enable teachers to rehearse effective teaching strategies. However, dialogue-oriented open-ended conversations such as teaching a student about scale factor can be difficult to model. This paper presents a high-fidelity, AI-based classroom simulator to help teachers rehearse research-based mathema...
Preprint
Full-text available
Machine learning techniques applied to the Natural Language Processing (NLP) component of conversational agent development show promising results for improved accuracy and quality of feedback that a conversational agent can provide. The effort required to develop an educational scenario specific conversational agent is time consuming as it requires...

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