Development of AI-Enhanced Learning Environment to Reduce Cognitive Load and Strengthen Mental Resilience in Biotechnology Learning

Mimi Halimah; Cartono Cartono; Cita Tresnawati

doi:10.61142/esj.v4i2.367

Authors

Mimi Halimah Universitas Pasundan
Cartono Cartono Universitas Pasundan
Cita Tresnawati Universitas Pasundan

DOI:

https://doi.org/10.61142/esj.v4i2.367

Keywords:

AI-enhanced learning, Biotechnology learning, Cognitive load, Mental resilience, The 21st-century skills

Abstract

Biology learning in higher education, particularly in biotechnology, faces complex challenges due to excessive cognitive load experienced by Generation Z and Alpha students. This study aimed to develop and validate an AI-enhanced learning environment (AI-ELE) prototype specifically designed for biotechnology courses to reduce cognitive load, strengthen mental resilience, and foster 21st-century skills. Using a Research and Development (R&D) design, this study proceeded through two phases: Phase 1 (needs analysis) and Phase 2 (prototype development), which is the focus of this article. Needs analysis was conducted through surveys and focus group discussions with 100 students to identify sources of cognitive load in biotechnology learning. The prototype integrates an AI-assisted personalized learning system, an adaptive scaffolding mechanism, and an intelligent feedback module built upon Cognitive Load Theory and Self-Determination Theory. Expert validation was carried out by five specialists in instructional design, educational technology, and biology. Validation results showed an average expert score of 4.2/5.0, and the System Usability Scale (SUS) score reached 72.4, indicating an acceptable level of usability. The developed instruments—Cognitive Load Scale (CLS), Mental Resilience Inventory (MRI), and 21st Century Skills Assessment (21CSA)—demonstrated high reliability (Cronbach's alpha > 0.80). The findings confirm that the AI-ELE prototype is valid and ready for pilot implementation. This study contributes to the growing body of knowledge on technology-enhanced biology education and provides a practical framework for integrating AI tools into university-level biotechnology courses.

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