What’s the Eberly Center reading and thinking about this month?

The Research and Scholarship Digest, published the first Monday of each month, consists of short summaries of recently peer-reviewed studies on teaching and learning topics. This digest offers a view into what we are reading and thinking about at the Eberly Center that:

• adds to our understanding of how students learn
• is potentially generalizable across teaching contexts in higher education
• provokes reflection on implications for our teaching and educational development practices.

We hope the readers of this digest will find it a useful resource for staying in-tune with the rapidly expanding education research literature.

Beardsley, M., Santos, P., Amarasinghe, I., Theophilou, E., Vujovic, M., & Hernández-Leo, D. (2025). A learning agreement for generative AI use in university courses: A pilot study. Innovations in Education and Teaching International, 1-19. 

In this study, researchers piloted the use of learning agreements to guide responsible student use and disclosure of use of generative AI tools on their assignments for a first-year engineering course at a university in Spain. The 82 participants completed pre- and post-surveys focused on their awareness, use, and beliefs about genAI tools and learning agreements, attended a plenary session on academic integrity and responsible genAI use and a seminar that modeled genAI tools that students might use or find helpful, completed a learning agreement via an online form, and were required to disclose and reflect on their use of genAI tools for a group research assignment. The study found that although students accepted the use of learning agreements to guide genAI use, they did not necessarily then adhere to the agreement in their submitted course work, with few groups completely following the learning agreement stipulations in citing, describing, and reflecting on their use of genAI tools for their final assignment. However, the study did find that students perceive learning agreements as beneficial and supportive of their learning when there is adequate reflection and discussion of the agreements.

https://doi.org/10.1080/14703297.2025.2535444

Noroozi, O., Khalil, M., & Banihashem, S. K. (2025). Artificial intelligence in higher education: Impact depends on support, pedagogy, human agency, and purpose. Innovations in Education and Teaching International, 1-6.

This editorial introduces a special journal issue exploring how Artificial Intelligence (AI) is reshaping higher education, drawing on seventeen different studies. It summarizes the key topics that educators and institutions need to pay attention to when using AI in the classroom, covering dimensions like learning, teaching, assessment, feedback, and academic integrity. The central and most important message is that the impact of AI is not determined by the technology itself but rather by "supported, pedagogically driven, human-centred, and purpose-driven approaches to AI adoption". While AI tools can enhance student motivation, learning, and feedback, the studies highlight significant risks such as over-reliance, bias, and the potential to undermine critical thinking skills. Therefore, effective integration requires careful pedagogical design, institutional support and training for educators, and a strong focus on ethical and responsible use to ensure AI supports, rather than supplants, the human elements of teaching and learning.

https://doi.org/10.1080/14703297.2025.2539579