An exploration of secondary students' mental states when learning about acids and bases

This study explored factors of students’ mental states, including emotion, intention, internal mental representation, and external mental representation, which can affect their learning performance. In evaluating students’ mental states during the science learning process and the relationship between mental states and learning achievement, valid, reliable, and scalable measures of students’ mental states and learning achievement are needed. This paper presents the development of the Mental State Conceptual Learning Inventory (MSCLI) to identify students’ mental states before and after learning about acids and bases. This instrument is time efficient and convenient and can be administered to large student samples so that teachers and researchers can gain profound insights into their students’ learning of acids and bases in science class. The results of this study indicate that students’ mental states are highly correlated with their achievement. As a whole, low-achieving students tended to have negative emotions and low intentions, were not good at internal visualization, and were unable to interpret graphics and draw pictures. In contrast, high-achieving students had positive emotions and intentions when learning life-related topics about acids and bases, and were good at internal visualization and drawing and interpreting graphics

Multimodal Affect Recognition in Intelligent Tutoring Systems

Abstract. This paper concerns the multimodal inference of complex mental states in the intelligent tutoring domain. The research aim is to provide intervention strategies in response to a detected mental state, with the goal being to keep the student in a positive affect realm to maximize learning potential. The research follows an ethnographic approach in the determination of affective states that naturally occur between students and computers. The multimodal inference component will be evaluated from video and audio recordings taken during classroom sessions. Further experiments will be conducted to evaluate the affect component and educational impact of the intelligent tutor