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…

This scoping review explores the intersection of climate change education and technology usage in the classroom. We conducted a scoping review of 93 articles to ascertain what, if any, trends exist across this body of scholarship. Findings indicate that technology serves to provide learners with refutation experiences for accepting and making…

This dissertation explores technological affordances in blended learning, their influence on the flexibility of statistics and data science curricula, and students' satisfaction with learning. While blended learning is often perceived as a flexible learning approach, its correlation with flexibility lacks substantial evidence in existing…

Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying…

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…

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…

As initiatives on AI education in K-12 learning contexts continues to evolve, researchers have developed curricula among other resources to promote AI across grade levels. Yet, there is a need for more effort regarding curriculum, tools, and pedagogy, as well as assessment techniques to popularize AI at the middle school level. Drawing on prior…

Debates surrounding the use of data science in educational AI are frequently rather entrenched, revolving around commercial models and talk of teacher replacement. This article explores the potential for digital textual analysis within humanities and social science education, advocating for a sociologically-driven approach that complements, rather…

"Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines" is a resource for researchers and practitioners in a field where the mainstreaming of AI technologies, and their increased capacities for deception, have produced confusion and fear. Identifying theoretical frameworks and practices in teaching…