Identifying Emotional Expressions During Family Science Engagement at Home—A Case Study From a Parent's Perspective

Abstract

Families play a pivotal role in fostering children's science literacy, interests, and identities through everyday interactions and informal learning contexts, with parents as main facilitators. An essential, yet often underexplored, aspect of this process is the role of emotions in shaping science learning experiences. Emotions serve as powerful mediators of engagement, influencing key learning outcomes such as interest, motivation, achievement, and persistence. Despite the recognized importance of family engagement in science learning and the emotional dimensions associated with it, there is a significant gap in research specifically examining how families engage with science at home and the role emotions play in these settings. In this case study, we employed a mixed methods approach consisting of electro-dermal activity (physiological) and recorded observations (behavioral) to identify the emotional expressions of a mother as she engaged in five science activities with her children (ages 13, 11, 7, and 4) at home. All five activities were analyzed utilizing the following procedures: 1. Peak analysis, 2. Structural breaks, and 3. Microanalysis. We complemented our interpretation of the data with reflective notes and a reflective interview (self-reports) with the participant. The study reveals that mediated activities elicit more positive emotional expressions; the interrelationship between emotions and cognitive, social, and cultural domains needs to be accounted for while analyzing emotions, and highlights the methodological challenges of measuring emotions. By focusing on how a parent guides home science activities, it fills critical gaps in understanding family-based science engagement and sheds light on the affective dimensions of informal science learning. Employing a mixed methods approach provides a comprehensive understanding of emotional expressions during home science activities, which enhances the validity of the findings and captures the dynamic nature of emotions, offering a robust approach for analyzing the interplay between physiological, behavioral, and interpretive emotional expressions in real-world contexts.