Аnalyzing socio-emotional states and utilizing ai capabilities in chemistry teaching

Abstract

Artificial intelligence (AI) research is the product of many years of continuous efforts by scientists and engineers. Primarily focused on expanding the capabilities of information systems and databases, the AI field has evolved to address the incorporation of human-like emotional and cognitive abilities, becoming relevant in modern studies. This paper aimed to enhance the quality of the educational process in chemistry by analyzing and predicting students’ socio-emotional states through an AI application. This investigation is particularly useful for teachers and researchers interested in addressing social-emotional states in the context of teaching natural sciences. The research employed a descriptive research methodology and was conducted in two directions. In the first phase, the capabilities of AI in education were studied, revealing their types and applications. This phase comprised reviewing prior research conducted by other scholars. In the second phase, a questionnaire (through Google Forms) was conducted to collect students’ perspectives and attitudes toward the topic. The questionnaire focused on eighth-grade students from 5 schools in Shymkent, with 96 of 97 respondents. The responses were analyzed to assess the reliability of the questionnaire items, using Cronbach’s alpha coefficient. The findings indicated that a significant part of students expected emotional support from their teachers during instruction, struggled to express their emotional states, and sometimes experienced feelings of inauthenticity. Moreover, the students demonstrated an interest in AI and its contribution to research conducted during their classes. Researchers can expand the scope of the study for further development, taking into account the questionnaire results, i.e., strengths and limitations.