James P Bywater

James Madison University | JMU · College of Education

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...

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...

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...

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....

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...

This paper examines whether natural language processing technologies can provide teachers with high-quality formative feedback about questioning practices that promote rich inclusive mathematical discourse within classrooms. This paper describes how a training dataset was collected and labeled using teacher questioning classifications that are grou...

This study examines technology-enhanced teacher responses and students’ written mathematical explanations to understand how to support effective teacher responding and the centering of students’ mathematical ideas. Although prior research has focused on teacher noticing and responding to students’ mathematical ideas, few studies have explored the r...

The nature and quality of classroom instruction is highly correlated to teachers’ ability to rehearse effective teaching strategies. Utilizing research-based teaching practices increases teacher effectiveness, confidence, and retention along with improving student achievements. High-fidelity, AI-based simulated classroom systems enable teachers to...

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...

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...

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...