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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
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Christopher J. Casement; Laura A. McSweeney – Journal of Statistics and Data Science Education, 2024
As the use of data in courses that incorporate statistical methods has become more prevalent, so has the need for tools for working with such data, including those for data creation and adjustment. While numerous tools exist that support faculty who teach statistical methods, many are focused on data analysis or theoretical concepts, and there…
Descriptors: Statistics Education, Data Science, Educational Technology, Computer Software
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Andrew A. Tawfik; Linda Payne; Andrew M. Olney – Technology, Knowledge and Learning, 2024
Theorists and educators increasingly highlight the importance of computational thinking in STEM education. While various scaffolding strategies describe how to best support this skillset (i.e., paired programming, worked examples), less research has focused on the design and development of these digital tools. One way to support computational…
Descriptors: Thinking Skills, Computation, STEM Education, Scaffolding (Teaching Technique)
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Tiffany Tseng; Matt J. Davidson; Luis Morales-Navarro; Jennifer King Chen; Victoria Delaney; Mark Leibowitz; Jazbo Beason; R. Benjamin Shapiro – ACM Transactions on Computing Education, 2024
Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data diversity and inspect…
Descriptors: Artificial Intelligence, Models, Data Processing, Design
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Alina Hase; Poldi Kuhl – Educational Technology Research and Development, 2024
Data-based decision-making is a well-established field of research in education. In particular, the potential of data use for addressing heterogeneous learning needs is emphasized. With data collected during the learning process of students, teachers gain insight into the performance, strengths, and weaknesses of their students and are potentially…
Descriptors: Instructional Design, Technology Uses in Education, Journal Articles, Decision Making
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Shesen Guo; Ganzhou Zhang – Education and Information Technologies, 2024
This study looked at titles of research papers on educational technology that were published between 1927 and 2023 using computational text analysis. To map research trends, metrics for technology terminology use, network complexity, and knowledge updating rates were used. The findings showed that, despite some fluctuations, titles have become…
Descriptors: Educational Research, Educational Technology, Journal Articles, Content Analysis
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Susie Gronseth; Amani Itani; Kathryn Seastrand; Bettina Beech; Marino Bruce; Thamar Solorio; Ioannis Kakadiaris – Journal of Interactive Learning Research, 2025
This study examines the design, implementation, and evaluation of a Digital Educational Escape Room (DEER) titled "Escape from the Doctor's Office," developed to enhance artificial intelligence/machine learning (AI/ML) literacy. Grounded in constructivist pedagogy and behaviorist principles, the DEER was designed using the ADDIE…
Descriptors: Educational Games, Artificial Intelligence, Technological Literacy, Teamwork