THE DEVELOPMENT OF AI-BLENDED LEARNING ENVIRONMENT BASE ON CONSTRUCTIVIST APPROACH TO ENHANCE ANALYTICAL THINKING IN GENETICS FOR GRADE 11 STUDENTS: PHASE 1-THEORETICAL ANALYSIS AND FRAMEWORK DESIGN

Abstract

Phase 1 of this research aims to analyze theoretical foundations and synthesize a conceptual framework for developing an AI-blended learning environment based on the constructivist approach to enhance analytical thinking in genetics for Grade 11 students. The study examines the curriculum requirements, learner context, and instructional approaches aligned with the Core Education Curriculum B.E. 2551 (Revised 2017), together with an analysis of constructivist theories—both cognitive and social—and major cognitivist learning theories, including Information Processing Theory, Meaningful Learning Theory, and Metacognition Theory. The study also incorporates three components of analytical thinking: identifying elements, determining causal relationships, and categorizing information. In addition, the research reviews constructivist learning environment models such as Constructivist Learning Environment (CLEs), Open Learning Environments (OLEs), and Cognitive Apprenticeship, as well as concepts related to media, network-based learning, and the potential of artificial intelligence in supporting active learning, social interaction, and self-regulated learning. The synthesis results in six key components of the learning environment: 1) problem situations, 2) learning resource room,
3) analytical thinking room, 4) knowledge-exchange room, 5) scaffolding room, and 6) consulting room, all systematically linked to relevant theoretical foundations. The outcome of this phase provides a theoretically grounded conceptual framework that is suitable for subsequent prototype development in the next stage of the research.

Keywords: AI-Blended Learning, Analytical Thinking, Constructivist