4 papers
Why Machines Misread Pedagogical Quality: Human-Machine Alignment in LLM-Based Pretest Question Evaluation
Pei-Yu Tseng, Mahir Akgun, Peng Liu
Designing effective pretest questions is challenging at scale: high-quality questions require careful calibration of openness, cognitive depth, and alignment with learning objectiv…
Do Gains from Generative AI-Enabled Adaptive Pretesting Persist? Evidence from a Retention Study
Mahir Akgun, Sacip Toker
Pretesting - attempting problems before instruction - supports learning by activating prior knowledge and sharpening attention to subsequent instruction. Recent work suggests that…
Shaping Credibility Judgments in Human-GenAI Partnership via Weaker LLMs: A Transactive Memory Perspective on AI Literacy
Md Touhidul Islam, Mahir Akgun, Syed Billah
Generative AI (GenAI) is increasingly used as a knowledge partner in higher education, raising the need for instructional designs that emphasize AI literacy practices such as evalu…
Short-Term Gains, Long-Term Gaps: The Impact of GenAI and Search Technologies on Retention
Mahir Akgun, Sacip Toker
The rise of Generative AI (GenAI) tools, such as ChatGPT, has transformed how students access and engage with information, raising questions about their impact on learning outcomes…