Emotion Regulation in Achievement Situations: An Integrated Model

Abstract

Achievement emotions are critical because of their impact on success and failure in important domains such as learning. These emotions may be modified via emotion regulation (ER). The dominant process model of ER (PMER;Gross, 1998Gross, , 2015, however, provides a domain-general account of ER strategies and has not had substantial contact with theories of achievement emotions such as Pekrun's ( 2006) control-value theory (CVT) and the academic achievement literature. Moreover, ER has not been a focal point of major theories related to achievement emotions, such as CVT. We propose an integrated model of ER in achievement situations (ERAS) that integrates propositions about the generation of emotions from CVT with propositions about how emotions are regulated and types of ER strategies from PMER. The ERAS model also offers new propositions regarding how different achievement situations, object foci, and time frames, as well as discrete emotions with different appraisal patterns, impact ER strategies.

Effects of Levels of Self-Regulation and Regulatory Teaching on Strategies for Coping With Academic Stress in Undergraduate Students

“…The study of students' emotional experiences in the teaching and learning context has yielded much research on aspects previously unconsidered by the cognitivist paradigm (Linnenbrink-Garcia and Pekrun, 2011;Goetz et al, 2014;Lüftenegger et al, 2016;Murayama et al, 2017;Duffy et al, 2018;Gentsch et al, 2018;Loderer et al, 2018;Collie et al, 2019;Harley et al, 2019;Hirvonena et al, 2019). In the present study, our effort has focused on explaining the degree to which emotional…”

A Structural Equation Model of Achievement Emotions, Coping Strategies and Engagement-Burnout in Undergraduate Students: A Possible Underlying Mechanism in Facets of Perfectionism

“…The study of students' emotional experiences in the teaching-learning context has produced a great deal of research on aspects not previously considered under the cognitivist paradigm. Such research seeks to explain to what degree emotional processes facilitate or interfere in learning processes [1][2][3][4][5][6][7]. Specifically, the level of stress experienced by students who try to meet the demands and requirements of university study has captured the interest of researchers [8,9].…”

Facial expressions when learning with a Queer History App: Application of the Control Value Theory of Achievement Emotions

“…Cronbach’s Alpha score accounting for the entire questionnaire (28 items) was reported as 0.55 from our previous study (Harley, Liu, et al ., 2019). The Alpha score for this study ( α = .40, α based on standardized items = .45 for version A; α = .64 for version B) also indicated low internal reliability as expected when targeting many different topics with relatively few items (Harley, Liu, et al ., 2019; Rowe et al ., 2017; van Griethuijsen et al ., 2015). The topics and difficulty of the 22 test items were divided and balanced using Papenberg’s (2018) minDiff R‐package.…”

“…Further, affect was found to be influenced by the activity, location and source of the measurements: Engagement/flow was associated with advanced learning technologies (eg, serious games), authentic learning contexts and observer reports; frustration and boredom was associated with laboratory studies, more basic technologies (eg, simple web interface) and self‐reports. We note that while the studies featured in the meta‐analysis focused on non‐basic emotions, such emotions can be inferred from basic emotion as explained in our methods section (eg, emotions such as enjoyment, hope and pride being able to be viewed as happy, since all belong to the positive‐valenced high‐activation category; Harley et al ., 2013; Harley, Pekrun, Taxer, & Gross, 2019).…”

“…Previous findings with the Queer History App used in this study as well as other similarly designed apps for learning history (Harley et al ., 2016, 2018; Harley, Liu, et al ., 2019; Poitras et al ., 2019) indicate that high mean levels of emotions, such as enjoyment, and low mean levels of negative emotions, such as frustration and boredom, are experienced with such apps. Based on these reports, we have hypothesized that learners would tend to express happiness (positive‐activating), and tend to express little sadness (negative‐deactivating), or anger (negative‐activating) for RQ1b and RQ2b.…”