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Tsubasa Minematsu; Atsushi Shimada – International Association for Development of the Information Society, 2024
In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…
Descriptors: Educational Technology, Technology Uses in Education, Error Patterns, Sentences
Rohani, Narjes; Gal, Kobi; Gallagher, Michael; Manataki, Areti – International Educational Data Mining Society, 2023
Massive Open Online Courses (MOOCs) make high-quality learning accessible to students from all over the world. On the other hand, they are known to exhibit low student performance and high dropout rates. Early prediction of student performance in MOOCs can help teachers intervene in time in order to improve learners' future performance. This is…
Descriptors: Prediction, Academic Achievement, Health Education, Data Science
Hollylynne S. Lee; Emily P. Thrasher; Matt Grossman; Gemma F. Mojica; Bruce Graham; Adrian Kuhlman – Grantee Submission, 2023
This paper presents the design of an innovative platform to support teachers' personalized learning related to teaching statistics and data science in grades 6-12 (http://instepwithdata.org). Through a study of 32 pilot users, the authors describe how teachers utilized supports such as personalization surveys, tracking of progress on a dashboard,…
Descriptors: Secondary School Teachers, Faculty Development, Statistics Education, Data Science
Whitacre, Paula – National Academies Press, 2023
Domestic and international competition for STEM talent is driving institutions across the research and innovation landscape to consider new policies and partnerships for building and managing STEM knowledge and skills. New levels of investment in human capital to increase U.S. innovation capacity and competitiveness will require coordination and…
Descriptors: Capacity Building, Human Capital, STEM Education, Innovation
Gemma F. Mojica; Emily Thrasher; Adrian Kuhlman; Bruce Graham; Hollylynne S. Lee; Michelle Pace – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
In this study, 82 middle and high school teachers engaged with the InSTEP online professional learning platform to develop their expertise in teaching data science and statistics. We investigated teachers' engagement within the platform, aspects of the platform that were most and least effective in building teachers' expertise, and the extent to…
Descriptors: Middle School Teachers, High School Teachers, Faculty Development, Data Science
Rethlefsen, Melissa L.; Norton, Hannah F.; Meyer, Sarah L.; MacWilkinson, Katherine A.; Smith, Plato L.; Ye, Hao – Journal of Statistics and Data Science Education, 2022
Research Reproducibility: Educating for Reproducibility, Pathways to Research Integrity was an interdisciplinary, conference hosted virtually by the University of Florida in December 2020. This event brought together educators, researchers, students, policy makers, and industry representatives from across the globe to explore best practices,…
Descriptors: Interdisciplinary Approach, Educational Research, Replication (Evaluation), Integrity