Best possible self (BPS) is a positive psychological intervention shown to enhance well-being which involves writing a description of an ideal future scenario. This paper presents a comparison of psychophysiological effects of a BPS activity that has been adapted for classroom settings and a time-matched control activity (NA). Thirty-three undergraduate students participated in the study that assessed state anxiety (State-Trait Anxiety Inventory, STAI), affect (Affective Slider, AS), and cardiac vagal activity (heart-rate variability, HRV) as an indicator of self-regulatory resource usage, at three time periods (PRE, DURING, POST). Results show that BPS led to a significantly greater increase in positive valence (DURING) and overall higher levels of cardiac vagal activity (HRV) compared to NA. These findings suggest that BPS has promising characteristics as a self-regulatory technique aimed at fostering positive affect and positively impacting self-regulatory resources. As BPS does not require expert knowledge nor specialized technology to administer, it may be a suitable activity for educators to use when teaching and having students practice self-regulation. This study presents evidence collected in a replicable multimodal approach of the self-regulatory effects of a brief BPS activity on undergraduate students.

In this paper, we present findings from the evaluation of compulsory lessons on stress management at an engineering school in Spain. Both a face-to-face and an online lesson were integrated into a credit-bearing course for first-year university students. A pre-post survey study was conducted (n = 54). Results indicate that the lessons fostered more positive stress mindsets among students. Findings also suggest that students increased their proficiency in contemplating the topic of academic stress and in understanding the active role they can play in managing stress.

Researchers have demonstrated the effectiveness of self-explanations (SE) as an instructional practice and study strategy. However, there is a lack of work studying the characteristics of SE responses prompted by collaborative activities. In this paper, we use writing analytics to investigate differences between SE text responses resulting from individual versus collaborative learning activities. A Coh-Metrix analysis suggests that students in the collaborative SE activity demonstrated a higher level of comprehension. Future research should explore how writing analytics can be incorporated into CSCL systems to support student performance of SE activities.

Learning to learn has been identified as an underdeveloped yet critical skill for learners. However, interventions often struggle to alter learner behavior in a lasting manner. We conducted a quasi-experimental study, guided by the Fogg Behavior Model, that involved 83 first-year university students in a computer engineering degree program. Our study examined learner levels of motivation, self-assessments of their abilities, and preferences for future interventions related to learning to learn. Our results suggest that student learning to learn skills are underdeveloped, not all students are motivated to improve their learning skills, and ICT-based solutions are preferred to more traditional educational approaches.

Whether deciding to participate in a study or gain access to online applications, research suggests that individuals often fail to understand the conditions they agree to when giving consent. Limited comprehension related to the risks of big data and habituation may contribute to consent being given in a manner that counters the best interests of individuals (i.e. a privacy paradox). Who is responsible for helping students learn to make informed decisions regarding the sharing of their data? We conducted a quasi-experimental study involving 127 undergraduate students. We explored the effects on study enrolment of supporting students in making informed data sharing decisions. Prior to reading the consent form for a study involving the evaluation of a collaborative learning application, one group of participants was primed to think about data sharing risks and evaluate their participation in terms of a harm-benefit decision whereas the other group was not. The primed group scored lower on a consent form comprehension quiz yet had higher enrolment rates and were more likely to cite trust as reasoning for enrolling in the study.

Self-reports of affective states are increasingly being collected in educational settings. However, individual definitions and usage of emotion and mood terms are often subjective despite objective definitions becoming more widely accepted. We explore whether the variation among individual learners in how mood terms are defined presents an obstacle to using self-reported mood data for group comparison studies. Following a design-based research methodology, we ran two case studies to explore the use of ClassMood App in a multimodal learning study and the validity of the self-reported mood data it collected. During the first case, 24 primary school students experienced difficulty understanding the words used to describe the moods in ClassMood App. In the second case, involving 77 university students, we explored whether the misunderstanding of mood words persisted with older students. Participants were asked to rate their familiarity with and match definitions to a set of 8 mood words. We found that levels of familiarity with the mood words varied greatly and 17.9% of all definition matching attempts were incorrect. The results suggest that the variation in subjective definitions of mood terms is likely to affect the validity of the data collected by the ClassMood App for group comparison studies.