Emotions in Advanced Learning Technologies

A multi-componential analysis of emotions during complex learning with an intelligent multi-agent system

“…Accordingly, there is growing recognition among researchers of emotions that there is a need to move beyond experiential, self-report measures to inform our theoretical and empirical understanding of emotions in the context of learning Graesser, D'Mello, & Strain, 2014;Harley, in press;Pekrun, 2006;Pekrun & Linnenbrink-Garcia, 2014). One of the caveats in this area of research is disagreement between theories of emotion regarding whether different components of emotions should provide similar or dissimilar emotional information; in other words, whether different components of emotions should provide a coherent (i.e., coordinated) response (Ekman, 1992;Pekrun, 2011).…”

“…Emotions are a critical component of effective learning and problem solving, especially when it comes to interacting with computer-based learning environments (CBLEs; multi-agent systems, intelligent tutoring systems, serious games; Azevedo & Aleven, 2013;Baker et al, 2012;Graesser, D'Mello, & Strain, 2014;Grafsgaard, Wiggins, Boyer, Wiebe, & Lester, 2014;Pekrun, 2011;Sabourin & Lester, 2014). In recent years there has been a surge in interdisciplinary research leading to a plethora of new approaches (including tools/devices and analytical techniques) to measure emotions (e.g., physiological sensors, automatic facial expression analysis software, concurrent state self-report measures; Alzoubi, Hussain, D'Mello, & Calvo, 2011;Baker et al, 2012;Grafsgaard et al, 2014;Harley et al, 2013).…”

High school students' perceptions of affect and collaboration during virtual science inquiry learning

“…The prevalence of positive or negative affect is rather unstudied, but a study by Muños, Kevitt, Lunney, Noguez, and Neri () on individual students' online learning revealed more positive achievement emotions than negative emotions (see Tomas et al, ). Graesser, D'Mello, and Strain () reviewed the research of learning‐centred emotions that occur in advanced learning technologies in STEM fields, such as computer science, mathematics, physics, and biology. Emotions of frustration , boredom , confusion , and engagement or flow were frequently reported and, although to a lesser degree, moments of happiness , sadness , curiosity , surprise , delight , and anxiety .…”

“…Therefore, it is plausible to claim that more research of affect in contexts that incorporate collaborative inquiry and computer‐supported learning in science, such as inquiry in a virtual science laboratory, are needed. The present study aims to contribute to this scarce literature through students' self‐evaluation, which is viewed as a useful method of collecting information about affective processes (Graesser et al, ) and provides an opportunity to explore the affective experiences of a student individually and part of a group. Further, this study was conducted as part of the science classroom work following Kim and Pekrun's () argument that the influence of affect on learning and performance should be studied in a classroom or a context where it actually occurs.…”

Students' level of boredom, boredom coping strategies, epistemic curiosity, and graded performance

“…Nonetheless, boredom is a selfdisruptive emotion (Eren & Coskun, 2015) that negatively influences student achievement and learning (Maroldo, 1986;Pekrun et al, 2002). This is particularly true when students are assigned difficult material to learn or problems to solve (Graesser & D'Mello, 2012) and when they have maladaptive motivation and little or lack of interest in the learning material (Graesser, D'Mello, & Strain, 2014). However, this does not mean that boredom is equal to lack of interest or motivation (Pekrun, Goetz, Daniels, Stupnisky, & Perry, 2010).…”