Artificial Intelligence–Supported Concept-Based Activities and Self-Concept Development in Learning General Science at the Elementary Level
Abstract
Self-concept is a crucial psychological construct that significantly influence the psychological academic performance, motivation and engagement, particularly at elementary level, In science education many young learners develop negative self-perceptions due to abstract self-concept, lack of individualized self-instructions and traditional teachers self-centered pedagogies. with the rapid advancement pf educational technologies, artificial intelligence supported concept-based activities of learning experience. This study investigates the effect of artificial intelligence supported concept-based activities on self-concept development of elementary school students in learning general science. The experimental group received the instructions using concept-based activities (CBA), while the control group received the instructions using traditional lecture methods (TLM). The study found that both boys and girls in the experimental group improved significantly in achievement and self-concept development scale scores. After twelve weeks of teaching to both groups the researcher administered posttest to both groups The analysis of collected data was done by using mean scores, standard deviation and paired sample t-test, with Cohens D for effect of size to compare student’s self-concept in both groups. The results showed a significant difference between scores in two groups. The (CBA) Concept-Based Activities as independent variable is effective practice for experiment. The Piers Harris children’s Self-concept development scale was used before and after treatment. Statistical Analysis revealed a significant improvement in the self-concept of students. Statistical analysis revealed a significant improvement in the self-concept development of students exposed to AI supported concept-based learning compared to those taught thought traditional lecture methods. The findings suggest that integrating AI in to elementary science education not only enhance conceptual understanding but also influences students’ academic self-concept, confidence and engagement. This study highlights the pedagogical value of AI driven learning environments in fostering both cognitive and effective development among young learners at elementary level.
Keywords: Artificial Intelligence (AI), Concept-Based Activities (CBA), Self-Concept Development (SCD), General Science (GS), Elementary Education (E- E), Pieris-Harris Scale (PHS), Experimental group (EG), Control Group (GP).
