Self-Regulated Learning (SRL) plays a crucial role in student success, particularly in blended learning (BL) environments where learners must take greater ownership of their educational journey. Whilst prior research has extensively examined SRL, there remains a gap in understanding how students' SRL profiles evolve over time and how motivation and learning strategies dynamically interact within these profiles.
This study investigates the dynamic nature of SRL by identifying distinct learner profiles and tracking their evolution throughout a semester in a BL setting. By adopting a person-centred clustering approach, the research provides insights into how students' motivation and strategy use shift over time.
Data were collected from 314 tertiary-level students enrolled in two BL courses, with responses from the Motivated Strategies for Learning Questionnaire (MSLQ) captured at three time points. K-Means clustering was used to classify students into SRL profiles, and longitudinal analysis was conducted to track transitions between profiles over time.
The findings revealed three distinct SRL profiles—highly self-regulated, moderately self-regulated, and minimally self-regulated learners—suggesting that students adapt their motivation and strategies in response to course feedback and assessments. The study highlights the fluid and iterative nature of SRL development.
This research enhances the theoretical understanding of SRL by empirically illustrating how students' motivation and learning strategies evolve within a semester. Additionally, it offers practical insights for designing interventions to support students with varying levels of SRL, ultimately contributing to more adaptive and effective BL environments.
This research significantly advances SRL theory by exploring how students' SRL profiles adapt and evolve over time, shedding light on the cyclical and dynamic nature of self-regulated learning. Additionally, it makes a critical contribution to the field of Learning Analytics (LA) by incorporating motivational constructs–an ar
High fidelity simulations can be an effective tool for anti-harassment education. While emotions have been identified as crucial in simulation-based education, their role in anti-harassment education within medical training remains underexplored.
We aimed to investigate emotional profiles of medical residents during harassment bystander simulation training via hierarchical clustering based on multimodal emotions data.
Twenty seven internal medicine residents with complete data sets that were part of a larger study were recruited. Emotions were captured through self-report surveys, an electronic bracelet that records electrodermal activity, and speech content analysis based on the residents' simulation debriefing. The study involved residents performing a simulated central line insertion while a simulated harassment took place that they could use to practice intervening in harassment.
Our cluster analysis revealed three equal-sized groups: ‘Emotionally Balanced, Minimal Arousal’, ‘Positive, Spiked Arousal’ and ‘Negative High Arousal’. The clusters had distinct levels of self-report emotions and electrodermal activity. Content analysis revealed distinct emotions, and sources of emotions between the clusters. Post hoc analysis revealed that the ‘Emotionally Balanced, Minimal Arousal’ group showed a higher propensity for directly confronting the harasser, indicating a composed emotional state conducive to focusing on simulation objectives.
Our findings reveal the varied emotional profiles that can be expected in simulation-based medical education and underscore the value of a multimodal approach to understanding these dynamics. Furthermore, the study highlights the criticality of recognising the sources of emotions and promoting effective emotion regulation strategies, especially in authentic learning environments where emotional responses are complex and impactful.
Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT skills.
This study aimed to investigate the effects of self-explanation on students' CT skills and programming behaviours.
Using a quasi-experimental design, 60 7th-grade students were recruited to participate in a 5-week programme. They were randomly assigned to one of three conditions: a group that received scaffolded self-explanation prompts (n = 20), a group that received open-ended self-explanation prompts (n = 20) or a control group that received no self-explanation prompts (n = 20). A series of analyses of covariance (ANCOVAs) were conducted to explore the effects of self-explanation on learning CT skills, and lag sequential analysis (LSA) was used to examine the behavioural patterns and traits exhibited by participants in these three groups throughout the programming learning process.
The results revealed that the students in the experimental groups (i.e., both the scaffolded and the open-ended self-explanation groups) exhibited significantly better CT skills than did those in the control group. Additionally, the students in the experimental groups exhibited more logical and systematic thinking behaviours (e.g., explanations, conclusions, operational simulations and predictions) than did those in the control group. Overall, our findings provide valuable insights that can support the design of instructional strategies to promote students' CT through programming.
With the rapid transition to remote learning necessitated by the closure of traditional educational infrastructures globally, the arena of informal digital learning of English (IDLE) has received much attention, particularly among English as a Foreign Language (EFL) learners in China.
This study explores how demographic variables (gender, age, grade, major, and background) along with confidence, desire, online self-efficacy, attitudinal belief, and intention to learn English predict IDLE behaviours among EFL learners in IDLE contexts.
Utilising a comprehensive dataset, the research incorporates machine learning algorithms (e.g., Random Forest, Support Vector Machine, Logistic Regression, Decision Tree, Gradient Boosting Decision Tree and Adaptive Boosting (AdaBoost)) to analyse psychological, behavioural and demographic predictors of IDLE behaviours. Participants included 2, 055 EFL learners in China.
The study finds that EFL learners' confidence, desire, online self-efficacy, attitudinal belief, intention to learn English and IDLE behaviours display a moderate level. Moreover, confidence and desire act as the strongest predictors of IDLE behaviours, whereas demographic variables (gender, age, grade, major and background) predict the minimum of IDLE behaviours.
By understanding these predictors, educational strategies can be better tailored to enhance digital education outcomes.
Gamification has been used in recent years to enhance the student experience in educational environments and to help students achieve an optimal experience. However, there is limited empirical evidence of the effects of gamification on specific psychological experiences, such as the students' flow experience, which is a highly motivating state associated with the learning process.
To address this gap, we examined the impact of gamification on students' flow experience within a learning management system.
We conducted a controlled between-subjects experiment (N = 65) in which participants in the experimental group interacted with a gamified version of the system, which incorporated a typical gamification design consisting of a collection of various game elements that constituted a form of meta-game interaction around the learning activity (as opposed to, for example, serious games or game-based learning). In contrast, the participants in the control group used the same system with the same educational tasks but without gamification. We used descriptive and inferential statistical methods (i.e., Mann–Whitney U test) to compare the students' flow experience between the groups.
The results reveal that the influence of gamification on students' flow experience was not statistically significant. These findings suggest that current gamification designs may not effectively facilitate flow in educational contexts, highlighting the need for further research and development to align gamification with desired educational outcomes.
While a substantial number of studies have investigated English-as-a-foreign-language (EFL/L2 English) anxiety, they predominantly examined it from a unidimensional perspective, overlooking the potential insights offered by examining language-skill-specific L2 anxiety from a multidimensional lens. Moreover, prior research has overlooked the influence of shifts in learning environments on L2 anxiety, particularly the transition from traditional face-to-face classroom instruction to technology-mediated synchronous online language learning.
Against this background, this study, drawing on the tripartite model of L2 anxiety, examined the differences in EFL college students' self-perceived L2 speaking anxiety across the cognitive, somatic and behavioural dimensions under both traditional classroom-based learning and synchronous online learning conditions.
A total of 153 Chinese EFL learners from two universities voluntarily participated in the study. Data were collected using an adapted L2 speaking anxiety scale (22 items). Confirmatory factor analysis and Cronbach's alpha test were conducted to confirm the construct validity and reliability of the scale. Subsequently, linear mixed-effects modelling (LMM) was performed to examine the influence of fixed (traditional classroom vs. synchronous online learning) and random effects (individual differences) on L2 speaking anxiety.
The results revealed that learners' L2 speaking anxiety was significantly lower in the synchronous online learning context than in the traditional classroom setting. Specifically, students experienced less cognitive and somatic anxiety when speaking English in the synchronous online learning environment. However, no significant difference was observed in the behavioural dimension of their L2 speaking anxiety across the two learning conditions. Overall, synchronous online learning appears to offer potential benefits in alleviating learners' L2 speaking anxiety. The study concludes with pedagogical implications for teachers in terms of how to design learning environments to effectively mitigate learners' L2 speaking anxiety.
Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its potential application as a diagnostic instrument for reflection remains insufficiently explored within programming education.
This study aims to develop and evaluate a CT-based diagnostic reflective report system as a technological intervention to facilitate structured reflective learning in programming education. Furthermore, it investigates the impact of this system on knowledge construction, higher-order thinking skills (HOTS), and project performance within an introductory Python programming course.
The study employed a quasi-experimental design spanning two academic semesters, involving 82 undergraduate students randomly assigned to experimental (n = 42) and control (n = 40) groups. The experimental group utilised weekly CT-based diagnostic reflective reports, whilst the control group engaged in traditional reflective practises. The curriculum integrated Python programming with Raspberry Pi embedded systems. Assessment measures included pre- and post-tests for knowledge construction, a validated questionnaire for HOTS evaluation, and the Creative Product Analysis Matrix (CPAM) for project performance assessment.
Implementation of the CT-based diagnostic reflective report system demonstrated statistically significant improvements in knowledge construction, critical thinking, and problem-solving skills compared to traditional approaches. Project performance metrics, including valuable, logical, useful, understandable, and well-crafted, showed marked enhancement. However, no significant impact was observed regarding creativity. These findings substantiate the efficacy of integrating CT diagnostic mechanisms with reflective learning practises.
Situated simulation is a pedagogical method used for on-the-job training in many occupations. Establishing a framework that uses mobile devices to provide both simulation elements and incorporates instant feedback as reasoning scaffolding is a promising and relatively unexplored research topic.
In this study, we designed a simulation game framework with mobile instant feedback to help learners develop high-risk emergency decision-making skills. According to the learners' different emergency decision-making, the mobile game provides instant feedback on the subsequent development of different medical conditions and provides the guidance of an instant reasoning scaffolding to help learners immediate correction strategies. In this study, we analysed the learners' learning effectiveness and psychological responses to the instant reasoning scaffolding-based game-based training, including flow, motivation and activity anxiety, as well as analysing the fidelity of the game.
A quasi-experimental design study with a total of 96 volunteers participated was grouped into Experimental group 1 (game with instant reasoning scaffolding), Experimental group 2 (game with document scaffolding) and a Control group (general case study with document scaffolding).
The results showed that participants who participated in instant reasoning scaffolding-based game-based training had better learning effectiveness than those who participated in document scaffolding game training and general case study. Participants in the instant reasoning scaffolding-based game-based training were able to achieve high flow, high motivation and low anxiety, and this scaffolding-based game framework has the potential to be extended to various emergency decision-making training areas.
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