This pilot study investigates the relationship between self-regulated learning (SRL) strategies and early dropout in a largely underexplored professional online learning context. Forty-two professionals (N = 42) enrolled in a four-week course delivered via a workplace Learning Experience Platform (LXP) supporting self-directed, adaptive learning pathways. SRL was measured using self-reports and behavioural trace data collected during the first week. A dual-method analytic approach was employed: top-down models (logistic regression and decision trees) tested predefined SRL predictors, while bottom-up methods (hierarchical clustering and process mining) uncovered emergent learner profiles without prior assumptions. Trace-based SRL indicators, particularly the number of unique actions on the platform, time spent during week one, participation in the forum, and completion of an action plan, were significantly stronger predictors of dropout (p < .05) than self-reports, where only the goal-setting subscale was significant. Despite the small sample size limiting generalisability, the study demonstrates that early behavioural engagement patterns can reliably predict learner persistence, often outperforming self-reported SRL measures. These findings advance our understanding of SRL in professional online learning environments and provide a replicable analytic framework for integrating trace data and surveys. By identifying actionable SRL behaviours linked to course completion, this study contributes toward the development of adaptive workplace learning systems capable of detecting and mitigating early disengagement in real time.
There are empirical studies on both the cognitive and performative outcomes of learning via VR and the affective aspects of the use of VR in learning. Studies on affective outcomes in relation to the learning object, such as the attitude towards it or the atmospheric effect of a visited environment on the students, are still pending. This desideratum of educational research is addressed in this paper by comparing the auratic experience elicited by physical church visits with that elicited by virtual church visits via Head Monted Displays (HDMs). Therefore, the study applied an experimental design with two points of measurement and two treatments. Auratic experience was operationalized as both mystical experience and flow, while flow was structured according to the two dimensions of control and concentration. The participants were students of religious education (N = 52). In both virtual and physical exploration, there is hardly any mystical experience to be measured. However, it is the physical visit that stimulates a more pronounced experience than the virtual visit. However, the auratic experience in the given experiment is sensitive to the time of measurement: switching from virtual to physical exploration seems to stimulate an increase in the mystical experience, while switching from physical to virtual exploration somehow attenuates this experience. This result and the limitations of the study are discussed.
Classrooms are becoming increasingly digital. One novel digital technology that might enter classrooms soon is eye tracking. This is a method to estimate a person’s gaze direction and infer the point of visual attention. This technology has already provided insights into how students process computer-based instructional material. Moreover, it has been used to enhance pre-recorded video instruction, by showing learners where the teacher is looking, which made it easier for learners to follow and learn from the teacher (i.e., eye movement modeling examples). Thus far, this was only implemented in pre-recorded videos. In the current paper, we present a proof-of-concept, with a focus on the technical set-up, that shows how this approach can also be used in real time, during teaching. We recorded the eye movements of a teacher giving a PowerPoint presentation and displayed his eye-movements in real-time to students who were present in the same classroom. Students saw one of three different versions of the presentation: The PowerPoint only (1), the PowerPoint with an overlay of the teacher’s eye movements as a circle (2) or as an inversed blurring of the material (3). Eye movement displays significantly affected how closely students followed the teacher’s gaze, but had no impact on learning. We discuss open research questions and possible future applications in educational practice.
The present study addresses a critical and underexplored area in learning research: how learners conceptualize scientists beyond the natural sciences. While previous studies have extensively examined learners' perceptions of natural scientists, little is known about their understanding of social and educational scientists – fields often overlooked as scientific domains and not associated with competence. Given the potential influence of such conceptions on learners’ academic engagement, study choices, and career aspirations, the present interview study provides an in-depth exploration of learners’ conceptions of the work and personal characteristics of educational scientists. The results of a qualitative content analysis show that the predominant image of the educational scientist among learners refers to a pedagogical practitioner who needs interpersonal skills to help children and families in educational and social service institutions. An additional typological content analysis reveals that learners who associate educational scientists with scientific activities and tasks tend to have uncertain, diffuse, and inaccurate ideas about the actual nature of this scientific work, putting into question whether this work can really be called research and imagining that educational scientists just sit together and think. Our findings also suggest that such misconceptions are rooted in learners’ school experiences. These findings point to a significant gap in the understanding of educational scientists and its potential consequences for engagement with the social sciences. This study emphasizes the need for targeted interventions to foster accurate conceptions about educational scientists, which ultimately could enhance learners’ appreciation of the social sciences and support more informed academic and career choices.
This study explored how learners engage in shared control in math in Adaptive Learning Technologies (ALT). In shared control, learners adjust task difficulty (easy, medium, or hard), while the ALT selects tasks based on performance. These adjustments to task difficulty influence the probability of solving the next task correctly. This study aimed to understand (1) differences in how learners use shared control and (2) how this relates to general math ability, regulation of practice behaviour (number of finished problems and accuracy), and learning outcomes. In this exploratory study, 98 grade 5 learners practiced three math topics using an ALT combined with an app, including personalised visualisations of learners’ real-time progress on the math topics and shared control selection options. Results showed four clusters reflecting differences in learners’ use of shared control in quantity and direction of task difficulty changes: learners making no changes (cluster 1), learners making some changes preferring hard difficulty (cluster 2) or easy difficulty (cluster 3), and learners who frequently changed across all task difficulties (cluster 4). Shared control was related to general math ability and influenced learners’ regulation of practice behaviour. Although a comparison with the ALT control was absent, learners seem to choose task difficulties in line with their needs and benefit from these choices, resulting in learning gain. From a self-regulated learning perspective, this indicated how learners engaged in regulation and were aware of their needs.
