STUDENTS’ EVALUATION OF AI-GENERATED INSTRUCTIONAL MATERIALS ON COMPARING PLANT AND ANIMAL CONTROL SYSTEM: BASIS FOR AI-ENHANCED BIOLOGY MODULE
Keywords:
AI-generated instructional materials, student perceptions, Biology education, plant and animal control systems, AI-enhanced module, Senior High School STEM, descriptive mixed-methods researchAbstract
Artificial intelligence (AI) is increasingly used to generate instructional materials, yet little is known about how students evaluate such materials in specialized science subjects. This study evaluated Grade 11 Science, Technology, Engineering, and Mathematics (STEM) students’ perceptions of AI-generated instructional materials on comparing plant and animal control systems as a basis for developing an AI-enhanced Biology module. Specifically, it determined students’ evaluation in terms of (a) content, accuracy, and clarity; (b) organization and presentation; (c) relevance to the lesson; and (d) engagement and usefulness. It also identified the perceived strengths and areas for improvement of the materials and proposed an enhanced instructional module based on the findings. The study employed a descriptive research design using a mixed-methods approach. A total of 33 Grade 11 STEM students from Guinaoang National High School in the Mankayan District, Benguet Division, were purposively selected. Quantitative data were collected through a researcher-developed, expert-validated Likert-scale questionnaire and analyzed using weighted mean and standard deviation, while responses to open-ended questions were examined using thematic analysis. Students generally agreed on the effectiveness of the AI-generated materials, with a grand mean of 4.08 and a standard deviation of 0.67, indicating consistent responses. Relevance to the lesson obtained the highest mean (4.18), while engagement and usefulness received the lowest (3.81), though still within the “Agree” range. The most frequently cited strengths were the use of visuals and diagrams (60.61%) and clarity (54.55%), followed by organization, examples and summaries, and lesson relevance. The most cited areas for improvement were simplifying content (42.42%) and providing more examples and explanations (36.36%), followed by enhancing visuals and layout, increasing interactivity, and adding motivational elements. Based on these results, an AI-enhanced Biology module was developed incorporating simplified explanations, enhanced visuals, additional examples, interactive activities, and real-life applications. The study concludes that AI-generated materials are perceived as effective for delivering accurate, relevant, and organized content but require improved engagement and instructional design for optimal use.
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