Integrating information from multiple sources is a common yet challenging learning task for secondary school students. Many underuse metacognitive skills, such as monitoring and control, which are essential for promoting engagement and effective learning outcomes.
This study aims to examine the relationship between metacognitive processes and the quality of writing from multiple sources with diverse language backgrounds.
To understand these processes, we conducted a laboratory study with 162 secondary students from diverse language backgrounds (English, German and Finnish). We collected trace data about metacognition while students were reading and writing in a digital learning platform. These data, along with the language used by students to produce their writing, were analysed to determine the association of metacognition with essay scores obtained using both automated and human evaluations.
Our findings indicate that students from different language backgrounds exhibit varying performance levels detectable by automated scoring. Secondary school students showed limited metacognitive processes in multi-source writing; this contrasts with findings from previous studies conducted in higher education. These findings can inform the development of analytics-based tools to support secondary students' writing through trace data and automated essay scoring, and provide evidence of the need for targeted interventions to assist and support secondary school students in improving their writing from multiple sources.
The potential of adaptive feedback in digital educational games remains largely unexplored. Fractions are a suitable topic for investigating the effectiveness of adaptive feedback, as the complexity of this domain highlights the need for adequate feedback.
This study examines the effectiveness of explanatory adaptive feedback in a digital educational game to address two particular misconceptions regarding fractions (i.e., Natural Number Bias and Unit of Reference).
A total of 197 4th graders were randomly assigned to two different conditions, each playing a different version of a digital educational game: one with corrective feedback and one with explanatory adaptive feedback. During gameplay, we collected log data of students' item-wise correctness and misconception errors.
Explanatory item response analyses indicated that correctness improved in both game versions, with a more pronounced increase for the game with explanatory adaptive feedback compared to the game with corrective feedback. However, no decrease in misconception errors was observed in either game version. Moreover, neither the type of misconception nor students' prior fraction knowledge were moderating factors. These results suggest that adaptive feedback can support students in learning fractions; however, to reduce misconception errors concrete feedback should be optimised.
The integration of pedagogical agents (PAs) into educational settings has become widespread, yet the impact of humorous versus non-humorous PAs on student academic performance and engagement remains underexplored. Although research highlights the benefits of PAs, the specific role of humour in enhancing educational outcomes is not well studied.
This study evaluates the effectiveness of humorous PAs compared to non-humorous PAs in improving academic performance and student engagement among fifth-grade students in science education.
A quasi-experimental design with pre-test and post-test measures was used. A sample of 78 fifth-grade students from District 4 of Tehran during the 2022–2023 academic year participated in the study. Three classes, balanced by the school based on academic performance, were randomly selected, and each was assigned to one of three groups: humorous PA (n = 28), non-humorous PA (n = 25) and no PA (n = 25). Data were collected using a researcher-developed learning test and the Reeve Student Engagement Questionnaire (2013), and analysed using ANCOVA.
The humorous PA group showed higher levels of student academic performance and engagement outcomes compared to the non-humorous PA and no PA groups. The ‘humorous PA’ group achieved the highest scores in both engagement and academic performance.
These findings suggest that incorporating humour into PAs can significantly enhance educational experiences and effectiveness. The study highlights the importance of considering the personality and style of PAs to optimise student engagement and academic performance.
This study explored the factors that influence the balance between academic integrity and the effective use of GenAI tools in higher education. It focused on the role of institutional guidelines in enhancing the responsible use of GenAI technologies to enhance academic integrity.
The study was theoretically grounded in the Technology Acceptance Model and the Theory of Planned Behaviour to investigate the factors that promote academic integrity in using GenAI tools (RQ1), their impact and institutional strategies to effectively mitigate ethical risks (RQ2) and the model practices to support the ethical and effective use in higher education (RQ3).
The PRISMA framework was used to systematically review and thematically synthesise the results of 213 peer-reviewed articles published between January 2021 and May 2025.
Finding indicates that academic support, defined by structured training, technical scaffolding, and perceived usefulness, is critical to enabling ethical GenAI use. Additionally, student self-regulation, as influenced by behavioural control and goal setting, was associated with greater academic integrity in GenAI-mediated learning. Whereas institutional policies varied widely, those with transparent, adaptive and discipline-responsive governance frameworks more effectively mitigated academic misconduct. Indeed, the model practices included GenAI ethics committees, interactive GenAI literacy modules, and the developer-educator collaborations to promote algorithmic transparency.
A comprehensive systems-based approach that encompasses academic support, self-regulation and ethical guidelines is critical for the responsible use of GenAI tools in education. Hence, to preserve academic integrity while nurturing innovation, institutions should integrate GenAI ethics into curricular design, faculty development and cross-sectoral policy frameworks. Future research may expand into multilingual and longitudinal analyses to support equitable and sustainable GenAI integration across diverse educational settings.
Computer-assisted educational technologies that integrate affective supports into math practices could be particularly beneficial for addressing troubling declines in middle grade students' math achievement, affect, and motivation. MathSpring is a web-based intelligent tutor that offers personalised content, remedial tutoring, and affective support for students and diagnostic reports on students' progress and effort for teachers.
This preregistered randomised control trial experiment sought to experimentally test the efficacy of the MathSpring platform in improving students' math achievement and dispositions towards math.
The final sample included 53 teachers and their 2003 10–12-year-old students from one U.S. state. Teachers were randomly assigned to either use MathSpring with their students (treatment condition) or continue business-as-usual math instruction (control condition) for one school year. Before and after the intervention, students' math achievement was measured with standardised math assessments and their dispositions towards math were measured with standardised surveys. Teachers completed logs, surveys, and interviews about their implementation.
The results indicated that students in the treatment group did not show evidence of improved achievement, affect, or dispositions towards math compared with students who received business-as-usual math instruction. Still, exploratory analyses indicated that students with high usage demonstrated greater achievement than those in the business-as-usual group. Though no overall effects of this intervention were detected, educational technology interventions with affective supports still hold potential for improving students' academic and dispositional outcomes.
Computational thinking (CT) is a fundamental ability required of individuals in the 21st-century digital world. Past studies show that generative artificial intelligence (GenAI) can enhance students' CT skills. However, GenAI may produce inaccurate output, and students who rely too much on AI may learn little and be unable to think independently. Besides, most research on CT mainly focused on Scratch or programming classes, but incorporating it into the K-12 science curriculum is better for students' deep learning and CT core skills development.
This study proposed a causal explanation and reflection (CER) model-based GenAI learning system in science courses to cultivate students' CT core skills.
One hundred and eighteen elementary school students in three different classes participated in this study.
A quasi-experiment was conducted in Fujian, China. Students in the experimental group learned with the CER model-based GenAI learning system; students learned with the CER model-based learning system in control group 1; students in control group 2 used the causal-explanation-based GenAI learning system. Students' learning achievement and CT core skills were examined.
The results showed that the CER model-based GenAI learning system significantly improved students' science learning and CT core skills. Interview results further showed some students complained that GenAI only provided answers without encouraging them to comprehend the material.
CT should not exist only in computer courses. Instead, it is an approach to problem-solving that applies to all disciplines. Also, over-reliance on GenAI may hinder learning ability. The effectiveness of GenAI-based learning depends on its judicious use.
Online collaborative learning has been broadly applied in the field of higher education. Nevertheless, not all types of collaborative learning can produce the desired learning results.
To facilitate online collaborative learning, the present study proposed an innovative artificial intelligence-enabled group cognitive diagnosis approach with the goal of improving online collaborative learning.
A total of 135 college students was included in the current study and divided into 45 groups. A total of 15 groups consisting of 45 students used the group cognitive diagnosis approach. An additional 15 groups were assigned to the group knowledge graph approach, while the remaining 15 groups were assigned to the traditional online collaborative learning approach.
The findings of this research indicated that the group cognitive diagnosis approach had more significant and positive impacts on collaborative learning performance, knowledge elaboration, and higher-order cognitive engagement than did the group knowledge graph and traditional online collaborative learning approaches.
The current study deepens our understanding of group cognition and the corresponding complex interactions and provides a new method for improving online collaborative learning.
Despite the recognised potential of Virtual Reality (VR) in education, the role of VR in enhancing presentation skills remains uncertain. Mixed findings, coupled with low adoption rates in educational settings, highlight the need to investigate how current VR applications are designed to facilitate effective learning outcomes for students.
Grounded in constructivist and situated learning theories, which emphasise learning through active engagement and real-world contexts, this study examines how specific VR design features, namely, feedback mechanisms (feedback awareness and feedback usefulness) and presence types (social and spatial presence), relate to student motivation and performance in presentations.
In a one-group pre-test-post-test field study, 285 university students participated in 30-min individual VR training sessions focused on presentation skills refinement. Using structural equation modelling, this study assessed the relationships between feedback and presence elements with student motivation and performance outcomes.
Analysis revealed that feedback awareness and social presence were positively associated with students' motivation to refine their presentation skills. Effective feedback mechanisms, particularly those that enhance feedback awareness and usefulness, were crucial for skill transfer, while increased social presence was associated with improved academic performance in the classroom. Conversely, spatial presence was unexpectedly negatively related to both motivation and performance, suggesting that how VR creates spatial elements may influence learning outcomes. By examining the nuances of these VR features, this study offers valuable insights for software developers and educators aiming to improve university students' presentation skills through VR training applications.
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