Schema and emotion in memory retrieval following video-based learning: An artificial intelligence study

Abstract

Adapting innovative educational technologies to bolster students’ academic learning is increasing rapidly. This study explored schema congruent and incongruent participants behaviour when experiencing video-based materials as the medium of learning within the frame of a flipped learning environment. The participants watched an educational learning video on a given topic and completed memory retention tests in different time variations: immediate and delayed. Additionally, an artificial intelligence-based emotion analysis examined the emotional valency of participants during two phases: study phase and test phase. The experiment comprised 16 healthy young adult volunteers (8 schema congruent, 8 schema incongruent; 9 males [56.25%], 7 females [43.75%]; age range 20–34 years, mean age 27.31 years, SD = 2.87 years). A combination of statistics-based and AI-based analysis evaluated the effectiveness of video-based learning in terms of retrieval accuracy, response time and emotional valence. The findings indicate that retrieval accuracy for the schema incongruent group was better than schema congruent. Response time for schema congruent group was quicker than schema incongruent. Both groups exhibited more negative emotions during the study phase but more positive emotions during the test phase.

Implications for practice or policy:

• Acceptance testing of video-based learning in tertiary education for different schema groups of students by assessing their emotional state helps educators to enhance pedagogy.
• Nourishing positive learning experiences from videos and questionnaires should be the goal, considered at the design stage for courses that rely on video-based materials.
• Adaptation of video-based learning strategy is more instructionally efficient and scalable for academic institutions and educators during a pandemic situation.