Abstract:

Generative AI (GenAI) has introduced new trends in higher education due to its capacity to provide personalized learning instructions, generate new learning content, and support students’ assignments in new ways. Due to GenAI’s enhanced capacity to support students and teachers, some educational stakeholders believe that it may replace human tutors in the education domain in the future. Student learning is a complex process and is supported by factors of pedagogy (PED), motivation (MOT), and cognition (COG). In literature, there is evidence that GenAI supports pedagogic frameworks like Bloom’s taxonomy (BT) at various levels of student learning. Regarding student motivation, literature studies relate GenAI features positively with well-known motivational theories like Self-Determination Theory (SDT). Although GenAI shows potential in student learning, it has several drawbacks. GenAI lacks advanced emotional capabilities like empathy, which are essential for efficient student learning. GenAI’s regular usage can adversely impact critical thinking and build cognitive load among students. Also, GenAI faces issues related to the credibility of data sources for new content generation and plagiarism in student assignments.

The paper conducts design science research in the area of GenAI in higher education to answer “What are the strengths, weaknesses, opportunities, and threats (SWOT) of the features of GenAI in the PED, MOT, and COG contexts of student learning in higher education ?” This analysis is done through the lens of well-established theories, namely BT for PED, SDT for MOT, and cognitive load theory (CLT) for the COG context. The paper focuses on features of the design and the behavioral aspects of GenAI. The output of the research is a condensed SWOT analysis of GenAI features categorized by PED, MOT, and COG learning contexts. This artifact provides a basis for a SWOT framework for educational stakeholders and policymakers to analyze GenAI for its successful adoption in their learning environments. The paper positions GenAI as a human tutor supportive rather than a complete replacement tool for the human tutor within the tutoring process.

Keywords:

Gen AI, pedagogy, motivation, cognitive, Bloom's taxonomy, Self-Determination theory, Cognitive Load Theory, Gen AI-mediated learning, SWOT analysis.