Reading texts can prompt intense emotions, and these emotions profoundly influence learning from texts. I first discuss the findings from the eight studies reported in this special issue. The studies represent pivotal advances in research on reading. Focusing on learning from science texts, they show that different emotions and different types of text influence reading in different ways. Furthermore, they document how the interplay of emotions, text features, and reading processes impacts knowledge acquisition, conceptual change, and attitude change. I then outline core directions for future research. We need to (a) expand current theories to adequately explain the multiple links between emotions, cognitive processes, and motivational processes during reading; (b) use causal designs to disentangle the cause-effect relations linking these processes to antecedents and outcomes, including reciprocal causation; (c) complement between-person designs with intraindividual analysis; (d) use dynamic measurement and multichannel indicators to capture emotional processes; and (e) investigate the generalizability of current findings across diverse groups of learners and sociocultural contexts.

This study was conducted using Facial Expression Analysis (FEA), which is fully integrated into the iMotions Software Suite. To learn more about how FEA can benefit your research, see the dedicated product page, or download our comprehensive pocket guide on Facial Expression Analysis below.  

iMotions booklet for facial expression analysis