Learning Environment
This week I would like to share recent research on the effects of the learning environment on learning. The paper is entitled, “Dynamic Interaction between Student Learning Behaviour and Learning Environment: Meta-Analysis of Student Engagement and Its Influencing Factors” by Li and Xue (2023). The meta-analysis revealed 14 factors affecting students’ learning participation. The results indicated that factors influencing student engagement include:
Promoting
students’ positive emotion, positive learning behavior, positive teacher behavior, teacher-student relationship, students’ thinking ability, learning resources, students’ individual and personality characteristics, and teaching factors; and
Hindering
lack of environmental support, negative student and teacher behavior.
Student engagement involves three main factors:
Behavioral
effort, persistence, concentration, asking questions and class communication
Emotional
students’ affective communication and practices on campus
Cognitive.
psychological involvement through learning, applying and mastering the knowledge, skills and disposition.
The most influential factor for participation in learning activities is individual positive emotion. The second and third most important factors were the teacher-student relationship and positive teacher behavior. The reasons for low student engagement include poverty, lack of purpose, poor physical and mental health, environmental and community factors.
As a follow up from the SoTL article shared two weeks ago on AI Assistants (AIA), a colleague shared an AIA that they found useful for summarizing academic papers. The name of the program is called Elicit. Elicit is an AI research assistant which uses generative AI (GenAI) and language models to automate research tasks. Currently, they are focused on finding and analyzing academic papers. To get started, simply ask a research question in the find papers workflow. The program will search through 125 million papers across 380,000 journals to find ones that are relevant to the query. I asked the AIA to summarize recent academic articles on integrating GenAI into higher ed teaching and learning:
“Generative AI is being integrated into higher education teaching methods in various ways. It can enhance personalized learning, automate assessments, provide virtual assistance, and aid in content creation (Nikolopoulou, 2024). Tools like ChatGPT, Claude, Gemini, Perplexity, Pi, OpenAI Codex, and Cognii are being used to create personalized learning materials and improve assessment strategies (Faccia et al., 2023). Strategies for responsible integration include raising awareness, training faculty, changing teaching practices, and imparting AI literacy (Kurtz et al., 2024). Specific AI tools like "Coursera Coach" and "AI-assisted course building" are being implemented to revolutionize teaching, learning, and assessment practices (Gupta et al., 2024). These tools can enhance student engagement, personalize learning experiences, and optimize assessment processes. However, ethical considerations such as data privacy, transparency, and cultural sensitivity must be addressed when implementing AI in higher education (Nikolopoulou, 2024).”
References
Li, J., & Xue, E. (2023). Dynamic Interaction between Student Learning Behaviour and Learning Environment: Meta-Analysis of Student Engagement and Its Influencing Factors. Behav Science, 13(1):59. doi: 10.3390/bs13010059
Nikolopoulou, K. (2024). Generative Artificial Intelligence in Higher Education: Exploring Ways of Harnessing Pedagogical Practices with the Assistance of ChatGPT. International Journal of Changes in Education, 1, 103-111. https://doi.org/10.47852/bonviewIJCE42022489
Kurtz, G., Amzalag, M., Shaked, N., Zaguri, Y., Kohen-Vacs, D., Gal, E., Zailer, G., & Barak-Medina, E. (2024). Strategies for Integrating Generative AI into Higher Education: Navigating Challenges and Leveraging Opportunities. Education Sciences, 14(5), Article 503. https://doi.org/10.3390/educsci14050503
Gupta, R., Nair, K., Mishra, M., Ibrahim, B., & Bhardwaj, S. (2024). Adoption and impacts of generative artificial intelligence: Theoretical underpinnings and research agenda,International Journal of Information Management Data Insights, 4(1). https://doi.org/10.1016/j.jjimei.2024.100232
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