Should I grade or should I comment: Links among feedback, emotions, and performance

The Ungrading Learning Theory We Have Is Not the Ungrading Learning Theory We Need

Ungrading is an emancipatory pedagogy that focuses on evaluative assessment of learning. Self-regulated learning (SRL) has consistently been referred to as the learning theory that undergirds ungrading, but SRL-with its deficit frame in the literature and in practice-fails to uphold ungrading's emancipatory aims. An asset-framed learning theory-one that combines the cultural orientation of funds of knowledge with the power dynamics of community cultural wealth-is proposed as an alternative to SRL. The proposed learning theory aligns ungrading to its emancipatory aims and may provide an opportunity to better understand the learning that occurs in ungraded classrooms. Scholarly and practical impacts for Science, Technology, Engineering, and Mathematics (STEM), and specifically biology, educational research and practice include investigating the plausibility of mixing learning theories, aligning learning theory to emancipatory aims and researching how faculty activate funds of knowledge and community cultural wealth, both individually and collectively, in ungraded STEM classrooms.

Multimodal measurements enhance insights into emotional responses to immediate feedback

Adaptive learning technologies often provide students with immediate feedback on task performance. This feedback can elicit various emotional responses, which, in turn, influence learning. Most recent studies capture these emotions by single data streams, contradicting the multi-componential nature of emotion. Therefore, this study investigated 32 university students solving mathematical problems using an adaptive learning technology. Students received immediate feedback on every step in the solution process, after which their physiological, experiential and behavioral responses to this feedback were recorded. Physiological arousal was measured by electrodermal activity, valence was measured by self-reports (experiential), and emotion types were measured by observations of facial expressions (behavioral). Results showed more peaks in electrodermal activity after feedback than was expected based on chance. These responses were comparable in strength after feedback on failure and success. Students' experiential responses conveyed mostly positive valence after feedback on success and mostly negative valence after feedback on failure. Behavioral observations showed more negative than positive emotion types after feedback on failure and more positive than negative emotion types after feedback on success. These results show that physiological arousal is a valuable objective indicator of emotional responses after immediate feedback but should be accompanied by other data streams in order to understand students' emotional responses. Both valence and emotion types can be used for this purpose. These outcomes pave the way for designing adaptive learning technologies that take students' emotions into account.

Feelings on feedback: Children's emotional responses during mathematics problem solving

Theories of learning emphasize the importance of both the cognitive and affective state of the learner. The current study focused on children's affective reactions to corrective feedback during mathematics problem solving. Eighty-seven elementary school children (M age = 7.6 years, 41% female, 68% White) solved mathematical equivalence problems during an online video call and received trial-by-trial feedback on their answers. Trained researchers used children's facial expressions, tone of voice, and verbal statements to quantify their positive and negative affect on each trial. Overall, children tended to express more positive affect than negative affect. However, negative affect was more prominent when the child was incorrect and received negative feedback, and higher negative affect was associated with lower accuracy and lower persistence on the task. These results provide novel empirical evidence for the role of emotions during children's STEM learning in a non-evaluative context.

The Role of Self-Efficacy, Task Value, and Intrinsic and Extrinsic Motivations in Students' Feedback Engagement in English Learning

Drawing on Wigfield and Eccles's motivational theory, which is acclaimed for explaining individual behavioral intentions, this study investigated the extent to which different forms of motivation (i.e., self-efficacy, task value, and intrinsic and extrinsic motivations) predicted student behavioral feedback engagement (i.e., action on teacher feedback and feedback seeking) in English learning. The participants were 276 male and female students who were enrolled in a second-year full-time English language and literature program at two Chinese universities. Multiple regression analyses showed that task value emerged as the only motivational variable that significantly predicted both students' action on teacher feedback and feedback seeking. Intrinsic motivation significantly predicted action on teacher feedback, whereas extrinsic motivation and self-efficacy significantly predicted feedback seeking. Pedagogical implications for endeavors to support students in their engagement with feedback in learning English as a foreign language in China are discussed.

The Influence of Feedback Content and Feedback Time on Multimedia Learning Achievement of College Students and Its Mechanism

This study investigated the content of feedback (adaptive, elaborated, and knowledge of correct response, KCR) and time (Immediate and Delayed) influences on multimedia learning of college students. Students from the Northeast Normal University (N = 157) were randomly assigned to one of the six experimental conditions. We tried to explain the influence mechanisms of different feedback effects through subjectively reported motivation, cognitive load, and eye movement trajectory during the feedback period. The results showed that (1) different feedback methods in terms of feedback time and feedback content have significantly different effects on scores. Among them, scores of the immediate feedback group were significantly higher than those of the delayed feedback group, and the scores of the adaptive feedback (AF) group were significantly higher than those of the elaborated feedback (EF) group and the knowledge of the correct response feedback group. (2) Different types of feedback contents have significantly different effects on motivation. The motivation scores reported by the AF group and EF group were significantly higher than those reported by the knowledge of the correct response feedback group. (3) Different feedback methods in terms of feedback time and feedback content had significantly different effects on subjective germane cognitive load reports. Among them, the germane cognitive load score of the immediate feedback group was significantly higher than that of the delayed feedback group. The germane cognitive load scores reported by the AF group were significantly higher than those reported by the EF group and knowledge of the correct response feedback group. (4) The germane cognitive load plays a partial mediating role between the AF and post-test scores. (5) Different feedback methods in feedback time have different effects on eye movement fixation trajectory, which shows that the subjects in the immediate feedback group were significantly less than those in the delayed feedback group in fixation count and fixation time in the interest area of the stem. (6) Consistent with our hypothesis, different feedback methods in feedback content have different effects on eye movement trajectory. In summary, the results show that the AF initiated in this study has a positive effect on multimedia learning of college students; it not only provides empirical evidence for cognitive load theory but also helps educators design adaptive learning feedback according to responses of students.