Mental Model Development in Multimedia Learning: Interrelated Effects of Emotions and Self-Monitoring

Time-dependent relations between emotion regulation, frustration, and metacognitive strategy use in technology-mediated learning

Understanding how learners regulate their emotions and engage in metacognitive strategies is crucial for fostering self-regulated learning, particularly in technology-mediated learning. This study examines the temporal relationships between two emotion regulation (ER) strategies, reappraisal and suppression, frustration, and use of progress monitoring as metacognitive strategy, within the context of an educational game on financial literacy. The study involved 82 undergraduate students whose levels of frustration, progress monitoring behaviour, ER strategies were assessed at various points during the learning task. Findings revealed that the use of both reappraisal and suppression decreased during the learning task. Additionally, both ER strategies were negatively associated with frustration, although the relationship between reappraisal and frustration diminished over time. Frustration was negatively related to progress monitoring, indicating that effective emotion regulation can help maintain engagement in metacognitive strategies by keeping cognitive resources available. Notably, suppression and progress monitoring showed a positive relation that increased over time, highlighting the potential usefulness of suppression in extended learning tasks, despite its generally lower effectiveness compared to reappraisal. The results highlight the importance of considering temporal dynamics in the application of ER strategies during extended learning. Practical implications for the design of technology-mediated learning environments and educational interventions are proposed.

Lower grade students tend to give up early in multimedia learning

This study examined the relationship between grade and the ability of text-picture integration in terms of task completion and the pattern of using textual and pictorial information. Children (N = 144) from secondary schools were recruited from grade 5 and grade 8. Analyzing the time spent with the multimedia unit prior to an incorrect response, this study suggests that 5th graders tend to give up relatively early compared to 8th graders. Furthermore, early incorrect responses were more prevalent among students of the non-academic track and were predicted by a low proportion of fixations on the text in mental model construction and on the picture in adaptive mental model specification. An inappropriate approach of integrating text and picture can thus be the reason for giving up early. The work provides a basis for (1) automated feedback during the course of working on a multimedia unit. (2) Instructional design should be adapted to the characteristics of student groups to support text-picture integration and to avoid giving up early.

Investigating the Usability of a Head-Mounted Display Augmented Reality Device in Elementary School Children

Augmenting reality via head-mounted displays (HMD-AR) is an emerging technology in education. The interactivity provided by HMD-AR devices is particularly promising for learning, but presents a challenge to human activity recognition, especially with children. Recent technological advances regarding speech and gesture recognition concerning Microsoft’s HoloLens 2 may address this prevailing issue. In a within-subjects study with 47 elementary school children (2nd to 6th grade), we examined the usability of the HoloLens 2 using a standardized tutorial on multimodal interaction in AR. The overall system usability was rated “good”. However, several behavioral metrics indicated that specific interaction modes differed in their efficiency. The results are of major importance for the development of learning applications in HMD-AR as they partially deviate from previous findings. In particular, the well-functioning recognition of children’s voice commands that we observed represents a novelty. Furthermore, we found different interaction preferences in HMD-AR among the children. We also found the use of HMD-AR to have a positive effect on children’s activity-related achievement emotions. Overall, our findings can serve as a basis for determining general requirements, possibilities, and limitations of the implementation of educational HMD-AR environments in elementary school classrooms.

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

Achievement emotions that the university student experiences in the learning process can be significant in facilitating or interfering with learning. The present research looked for linear and predictive relations between university students' achievement emotions, coping strategies, and engagement-burnout, in three different learning situations (classroom, study time, and testing). Hypotheses were identified for a possible model that would analyze the two facets of perfectionism based on these relations. In the case of perfectionistic strivings, the test hypothesis was that positive emotions would predispose the use of problem-focused coping strategies and an emotional state of engagement; in the case of perfectionistic concerns, however, negative emotions would predispose the use of emotion-focused strategies and a state of burnout. A total of 654 university students participated in the study, using an online tool to complete validated questionnaires on the three study variables. All students provided informed consent and corresponding permissions. Given the ex-post facto linear design, the predictions could be verified for each situation by means of logistic regression analyses and Structural Equations Models (SEM). Empirical results lent support, in varying degree, to the proposed theoretical relations. The testing situation was of particular interest. We discuss implications for perfectionism research and for the practice of prevention, education and health care in the university setting.

Multiple Negative Emotions During Learning With Digital Learning Environments - Evidence on Their Detrimental Effect on Learning From Two Methodological Approaches

Emotions are a core factor of learning. Studies have shown that multiple emotions are co-experienced during learning and have a significant impact on learning outcomes. The present study investigated the importance of multiple, co-occurring emotions during learning about human biology with MetaTutor, a hypermedia-based tutoring system. Person-centered as well as variable-centered approaches of cluster analyses were used to identify emotion clusters. The person-centered clustering analyses indicated three emotion profiles: a positive, negative and neutral profile. Students with a negative profile learned less than those with other profiles and also reported less usage of emotion regulation strategies. Emotion patterns identified through spectral co-clustering confirmed these results. Throughout the learning activity, emotions built a stable correlational structure of a positive, a negative, a neutral and a boredom emotion pattern. Positive emotion pattern scores before the learning activity and negative emotion pattern scores during the learning activity predicted learning, but not consistently. These results reveal the importance of negative emotions during learning with MetaTutor. Potential moderating factors and implications for the design and development of educational interventions that target emotions and emotion regulation with digital learning environments are discussed.