Using intensive longitudinal methods to quantify the sources of variability for situational engagement in science learning environments

• Main Authors: Joshua M. Rosenberg (Author), Patrick N. Beymer (Author), Vicky Phun (Author), Jennifer A. Schmidt (Author)
• Format: Book
• Published: SpringerOpen, 2023-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s40594-023-00449-0; 2196-7822
• Keywords: Intensive longitudinal methods; Engagement; Science education; Multivariate models; Mixed effects models; Education; L; Education (General); L7-991; Special aspects of education; LC8-6691; Theory and practice of education; LB5-3640
• Source: International Journal of STEM Education, Vol 10, Iss 1, Pp 1-14 (2023)

Abstract Background Situational engagement in science is often described as context-sensitive and varying over time due to the impact of situational factors. But this type of engagement is often studied using data that are collected and analyzed in ways that do not readily permit an understanding of the situational nature of engagement. The purpose of this study is to understand-and quantify-the sources of variability for learners' situational engagement in science, to better set the stage for future work that measures situational factors and accounts for these factors in models. Results We examined how learners' situational cognitive, behavioral, and affective engagement varies at the situational, individual learner, and classroom levels in three science learning environments (classrooms and an out-of-school program). Through the analysis of 12,244 self-reports of engagement collected using intensive longitudinal methods from 1173 youths, we found that the greatest source of variation in situational engagement was attributable to individual learners, with less being attributable to-in order-situational and classroom sources. Cognitive engagement varied relatively more between individuals, and affective engagement varied more between situations. Conclusions Given the observed variability of situational engagement across learners and contexts, it is vital for studies targeting dynamic psychological and social constructs in science learning settings to appropriately account for situational fluctuations when collecting and analyzing data.