In this research-to-practice full paper, we explored the perceptions of AI-enabled microlearning as an instructional approach in a second-year introduction to database design and programming course for new technology primary students at an urban Midwestern university. This pilot study was built upon our prior work, where we identified the microlearning instructional design practices to maximize student learning outcomes ([1]–[3]). Our analysis of this study was based on the students' perceptions survey (n=23) and twelve semi-structured interviews. The following research questions guided this study: 1)What are students' overall perceptions of the effectiveness of the AI-enabled microlearning approach? 2What are the perceived benefits and challenges of using an AI chatbot in microlearning modules? Using a single case study design, we collected student perceptions through a survey and semi -structured interviews with novice data science students. The results revealed mixed opinions about the effectiveness of the AI-enabled microlearning approach. Although students initially approached the tool with curiosity and interest, they encountered challenges due to its inconsistent and sometimes inaccurate responses. Nevertheless, participants recognized the potential of the AI tool in simplifying concepts and delivering prompt feedback, particularly for basic database queries. However, the AI tool's limitations in handling complex queries and technical errors affected its reliability. This pilot study emphasizes the need to refine AI tools to improve accuracy, consistency, and contextual understanding while incorporating interactive features and human support. Addressing these challenges would allow educators to harness AI tools more effectively for personalized, technology-enhanced learning in database management and other technical courses. Overall, the findings highlight the potential of AI-enabled microlearning as a valuable instructional approach for teaching introductory programming concepts, with key implications outlined in the study.
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Sankaranarayanan et al. (2024) studied this question.
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