Improving the Generalizability of Models of Collaborative Discourse Abstract We investigated methods to enhance the generalizability of large language models (LLMs) designed to classify dimensions of collaborative discourse during small group work.Our research utilized five diverse datasets that spanned various grade levels, demographic groups, collaboration settings, and curriculum units. We explored different model train-ing techniques with RoBERTa […]
Sense-Making with an AI-Enhanced Coaching Tool: A Think-Aloud Study
Sense-Making with an AI-Enhanced Coaching Tool: A Think-Aloud Study Abstract We investigate the sense-making processes of instructional coaches who engage with an AI feedback tool, Hybrid Human-Agent Tutoring (HAT)platform, in the context of a high-dosage human tutoring program. HAT providesautomatic feedback on the discourse practices of tutors embedded in a coached-tutor model. This study describes the […]
An Evaluation of Perceptions Regarding Mentor Competencies for Technology-based Personalized Learning
This study discusses the development of Personalized Learning 2 (PL2), an online human mentoring system. PL2 uses student math learning data and mentor input to write custom feedback. This particular research is focused on finding a more efficient and research-based way to organize resources for PL2. 18 PL2 partner members completed a survey that revealed that Engaging and Motivating Students was the most important skill and Underingstanding Educational Norms and Policies was the least important. Reorganization will optimize mentor training and their ability to help students overcome barriers.
Development of Scenario-Based Mentor Lessons
This demonstration shows the recent advancement of scenario based tutor training and its focus on using the learn-by-doing approach. The 15 minute lessons outlined in this study use the predict-observe-explain inquiry method to develop tutor skills in helping student motivation. These methods are being developed within the Personalized Learning2 (PL2) program. PL2 is an app that combines student software with human tutors to improve mentoring ability. Enhancing mentor training will help to increase student ability while also maintaining low costs. This form of training works best when tutors have scenario based practice with response specific feedback.