Learning Context Research Articles

Applying social cognition to feedback chatbots: Enhancing trustworthiness through politeness

AbstractGenerative AI systems like chatbots are increasingly being introduced into learning, teaching and assessment scenarios at universities. While previous research suggests that users treat chatbots like humans, computer systems are still often perceived as less trustworthy, potentially impairing their usefulness in learning contexts. How are processes of social cognition applied to chatbots compared to humans? Our study focuses on the role of politeness in communication. We hypothesise that polite communication improves the perception of trustworthiness of chatbots. University students read a feedback dialogue between a student and a feedback provider. In a 2 × 2 between‐subjects experimental design, we manipulated the feedback's author (chatbot vs. human teacher) and the feedback formulation (polite vs. direct). Participants evaluated the feedback giver on measures of epistemic trustworthiness (expertise, benevolence and integrity) and on two basic dimensions of social cognition, namely agency and communion. Results showed that a polite feedback giver was rated higher on benevolence and communion, whereas a direct feedback giver was rated higher on agency. Unexpectedly, the chatbot was rated lower on benevolence than the human. This suggests that social cognition does apply to interactions with chatbots, with caveats. We discuss the findings regarding the design of feedback chatbots and their use in higher education. Practitioner notesWhat is already known about this topic Technology users tend to treat computer systems like humans, but computers are usually trusted less. Polite communication, that is mitigation of face threats is expected to enhance the evaluation of a chatbot as trustworthy. The research is relevant for the use and acceptance of chatbots as feedback providers in educational contexts. What this paper adds We test the assumption that polite language reduces the gap in epistemic trustworthiness between chatbots and human teachers as feedback givers. We describe an empirical study with 284 university student participants who report their perceptions of a feedback dialogue between a student and either a human teacher or a chatbot. We analyse the impact of feedback source as well as politeness on trustworthiness perceptions and social cognition. Implications for practice and/or policy The study confirms that users are receptive to politeness in communication. They treat chatbots in a similar manner to human interaction partners. The results highlight the significance of politeness of chatbots' language in learning contexts. Feedback chatbots need to be equipped with suitable linguistic strategies, such as politeness, for communicating in a socially appropriate manner at critical points in the instructional dialogue.

Implementasi Pembelajaran Outing Class dalam Menstimulasi Motivasi Belajar Siswa

This study aims to determine the implementation of outing class learning in stimulating students' learning motivation, which is expected to be a reference for contextual learning innovation. This study uses a qualitative descriptive method with data collection techniques through direct observation and interviews with teachers, school administrators, and students at Jogja Green School. The data obtained were analyzed using content analysis techniques to identify the main themes related to the impact of outing class learning on students' learning motivation. The results of the study showed that the implementation of the outing class method significantly increased students' learning motivation. Learning that involves direct experience in nature as a learning medium creates higher involvement, provides freedom to choose activities that suit students' interests, and improves character development and environmental awareness. This learning not only improves students' academic knowledge, but also life skills that can be applied in everyday life. These findings indicate that a more personal and contextual learning approach can be effective in increasing students' learning motivation.

Do generative artificial intelligence related competencies, attitudes and experiences affect employee outcomes? An intellectual capital perspective

PurposeThe research on intellectual capital focuses on the role of innovative technologies in organizational systems, particularly in knowledge generation and learning processes. This study addresses the third stage of intellectual capital research, emphasizing how innovative technologies like generative AI (Gen AI) applications can enhance learning experiences, individual talents and personalized learning. Based on the WEST model, this study examines the relationship between attitude, competency, experience, Gen AI integration and managers’ creative involvement. Additionally, it investigates the direct and mediating roles of Gen AI integration and managers’ creative involvement in improving learning effectiveness.Design/methodology/approachA cross-sectional survey of managers from organizations operating in diverse sectors of Saudi Arabia was conducted using a web-administered structured questionnaire. PLS-based structural equation modeling was employed to assess the hypothesized relationships.FindingsThe results revealed that the manager’s Gen AI experience, competency, attitude and access positively affect its integration. However, only Gen AI competence and attitudes demonstrated the same positive impact on managers’ creative involvement. Furthermore, Gen AI integration and creative involvement positively and significantly impact learning effectiveness. The study also uncovered the positive mediation of Gen AI integration in enabling all four antecedents to enhance learning effectiveness. However, the mediation of creative involvement was corroborated only for the Gen AI attitudes and competence.Originality/valueThis study examines how integrating innovative technologies, such as generative AI, enhances the learning experience, develops individual talents and personalizes learning in workplace contexts at the managerial level. By providing new insights into the dynamics of generative AI integration in workplace settings, it significantly contributes to the generative AI literature.

The relationship between trait- and state-math anxiety and math engagement: The role of math learning context and task difficulty.

Various findings regarding the relationship between math anxiety and engagement have been identified in the literature, with many focusing on general math anxiety and overall math engagement. Based on the control-value theory, this study examined the relationships between trait- and state-math anxiety and behavioural and cognitive engagement in math under daily practice and exam preparation conditions across math tasks of varying difficulty levels. A survey study with 449 high school students and an experimental study with 33 freshmen were conducted. Students' trait- and state-math anxiety, as well as behavioural and cognitive engagement in math, were measured under daily practice and exam preparation conditions across easy and difficult math tasks. A two-level latent variable model was built in the survey study, and two-way ANOVAs and regressions were used in the experimental study. Students exhibited greater state anxiety under exam preparation conditions in the survey study and showed differences in state-math anxiety and engagement across learning contexts and math tasks in the experimental study. Students with higher trait-math anxiety displayed less engagement in both studies, while those with higher state-math anxiety when facing difficult tasks tended to engage more cognitively in the experiment. These findings demonstrated discrepancies in the relationships between trait- and state-math anxiety and math engagement, while accounting for learning context and task difficulty.

Evolusi Pendidikan Klasik dan Modern Serta Kajian Terhadap Faktor-Faktor Pendidikan

The Educational theories are fundamental in developing effective teaching methods and strategies. They serve as a guide for educators to understand various aspects of the teaching-learning process, including student motivation, cognitive development, and social interactions. Key educational theories offer unique perspectives on how education should be conducted. Jean Piaget's theory of cognitive development emphasizes that children undergo four distinct stages of cognitive growth, each with unique characteristics and abilities. This theory significantly influences curriculum design and teaching methods appropriate for different cognitive levels. Albert Bandura's social learning theory highlights the importance of observation and imitation in learning. He argues that people learn many behaviors by observing others and the consequences of those behaviors, underscoring the role of social environments and peer interactions in education. Constructivism, popularized by Lev Vygotsky and Piaget, posits that learners actively construct their knowledge through interaction with their environment. This approach stresses the importance of hands-on experiences and contextual learning in developing student understanding. B.F. Skinner's behaviorism theory focuses on the role of reinforcement and punishment in shaping student behavior. According to this theory, behavior can be systematically shaped and controlled through positive and negative reinforcement. These theories, along with others such as humanism and cognitive theory, provide valuable frameworks for educators to design and implement effective teaching strategies. Understanding and applying various educational theories can create a better learning environment that supports students' holistic development.

Exploring Honai construction as a resource for mathematics learning

Cultural heritage plays a critical role in providing context for mathematical learning, offering opportunities to enhance both academic understanding and cultural appreciation. However, there is a gap in integrating ethnomathematical knowledge into formal education, particularly in connecting local cultural practices with abstract mathematical concepts. This study addresses this gap by examining the ethnomathematics of the Dani community, focusing on the construction of the Honai, a traditional structure that reflects the community's indigenous knowledge and craftsmanship. The research aims to identify and analyze the mathematical concepts embedded in the Honai's construction, thereby demonstrating how these principles can inform culturally responsive mathematics education. Using a qualitative ethnographic methodology, data were collected through participant observation, in-depth interviews with traditional builders and community elders, and document analysis. The findings reveal that the Honai incorporates various mathematical principles, including circular geometry in its base, conical or paraboloid shapes in its roof, and non-standard measurement techniques based on body spans and visual alignment. These results highlight the rich geometric, proportional, and spatial reasoning inherent in the Honai's design and construction. The study demonstrates that incorporating the Honai's construction principles into mathematics instruction can enhance student engagement and deepen conceptual understanding by linking abstract concepts to culturally significant practices. This culturally responsive approach not only bridges traditional knowledge with academic content but also fosters pride in cultural identity. By leveraging cultural artifacts like the Honai, this research contributes to the development of inclusive and effective educational strategies that enrich mathematics teaching and learning.

Meningkatkan Prestasi Belajar Matematika Materi Pengukuran Menggunakan Metode Problem Based Learning di MI Muhammadiyah Wonoanti I

Mathematical ability is a crucial aspect of education as it contributes to developing students' logical, critical, and analytical thinking skills. However, mathematics learning is often perceived as difficult and monotonous by students, especially in measurement topics. This perception negatively impacts students' academic performance. This study aims to improve the mathematics achievement of fourth-grade students at MI Muhammadiyah Wonoanti 1 through the application of the Problem-Based Learning (PBL) method. PBL was chosen because it provides more contextual and challenging learning experiences, encouraging students to think independently in solving problems. This study employed a classroom action research (CAR) approach conducted in two cycles, including planning, implementation, observation, and reflection stages. The results indicate a significant improvement in students' academic performance, demonstrated by an increase in the class average score and active student participation during the learning process. Many changes and improvements were observed in the students. The students' average learning scores increased from 42.86% to 57.14% in the first cycle and rose further to 85.71% in the second cycle. Additionally, the learning environment became more interactive and enjoyable. Thus, the implementation of the Problem-Based Learning method proved effective in enhancing mathematics learning outcomes, particularly in measurement topics.

Leadership for Educational Inclusion: Design and Validation of a Measurement Instrument

This article addresses the validation of an instrument designed to measure organizational leadership practices for inclusion and evaluates the said instrument’s factorial structure and convergent validity. This work responds to the need for quantitative tools to assess how school principals promote inclusion, in recognition of its importance for guaranteeing student access to an equitable quality education at all levels, from early childhood education through high school. The above-referenced instrument was developed based on a comprehensive literature review and consultations with experts, resulting in a 36-item scale structured in six key dimensions: D1: Professional Development; D2: Inclusive Vision; D3: Support for the Teaching–Learning Process; D4: Building Networks; D5: Participation and Dialog, and D6: Resource Management. The validation process included a confirmatory factor analysis that supported the existence of a hierarchical structure of a general factor of leadership for inclusion that determines the aforementioned key dimensions, with adequate fit indices (χ2(588) = 1694.624, p < 0.001, CFI = 0.945, TLI = 0.941, RMSEA = 0.060, SRMR = 0.034) and high internal consistency in the general scale (α = 0.98, Ω = 0.96). In terms of convergent validity, the instrument showed significant and consistent correlations with related constructs such as teacher self-efficacy and pedagogical leadership. This study highlights the importance of leadership for inclusion as a central element of fostering participation and learning in diverse school contexts, by providing a reliable tool for continuous improvement of the school management team’s performance of its functions. Also, it is important input for education policymakers charged with formulating student equity, who recognize the enhanced well-being and active participation in the social environment that result from the greater inclusion of students in their educational communities.

Word Learning in L1 and L2 Acquisition: A Comparative Analysis through the Emergentist Coalition Model (ECM)

This qualitative study compared the word learning strategies of children acquiring their first language (L1) and adults acquiring a second language (L2) using the Emergentist Coalition Model (ECM) as a framework. Children (aged 4-7) and adults (aged 18-65) participated in semi-structured interviews. Thematic analysis revealed that children relied more on implicit learning through social cues and phonological awareness, while adults adopted a more explicit and strategic approach, emphasizing semantic knowledge. These findings highlighted the influence of developmental stage and learning context on word learning strategies. By demonstrating the importance of both implicit and explicit learning for L1 and L2 learners, this study contributed to a more holistic understanding of word acquisition.

Associations of Postencephalitic Epilepsy Using Multi-Contrast Whole Brain MRI: A Large Self-Supervised Vision Foundation Model Strategy.

Postencephalitic epilepsy (PEE) is a severe neurological complication following encephalitis. Early identification of individuals at high risk for PEE is important for timely intervention. To develop a large self-supervised vision foundation model using a big dataset of multi-contrast head MRI scans, followed by fine-tuning with MRI data and follow-up outcomes from patients with PEE to develop a PEE association model. Retrospective. Fifty-seven thousand six hundred twenty-one contrast-enhanced head MRI scans from 34,871 patients for foundation model construction, and head MRI scans from 144 patients with encephalitis (64 PEE, 80 N-PEE) for the PEE association model. 1.5-T, 3-T, T1-weighted imaging, T2-weighted imaging, fluid attenuated inversion recovery, T1-weighted contrast-enhanced imaging. The foundation model was developed using self-supervised learning and cross-contrast context recovery. Patients with encephalitis were monitored for a median of 3.7 years (range 0.7-7.5 years), with epilepsy diagnosed according to International League Against Epilepsy. Occlusion sensitivity mapping highlighted brain regions involved in PEE classifications. Model performance was compared with DenseNet without pre-trained weights. Performance was assessed via confusion matrices, accuracy, sensitivity, specificity, precision, F1 score, and area under the receiver operating characteristic curve (AUC). The DeLong test evaluated AUC between the two models (P < 0.05 for statistical significance). The PEE association model achieved accuracy, sensitivity, specificity, precision, F1 score, and AUC of 79.3% (95% CI: 0.71-0.92), 92.3% (95% CI: 0.80-1.00), 68.8% (95% CI: 0.55-0.87), 70.6% (95% CI: 0.61-0.90), 80.0% (95% CI: 0.71-0.93), and 81.0% (95% CI: 0.68-0.92), respectively. A significant AUC improvement was found compared to DenseNet (Delong test, P = 0.03). The association model focused on brain regions affected by encephalitis. Using extensive unlabeled data via self-supervised learning addressed the limitations of supervised tasks with limited data. The fine-tuned foundation model outperformed DenseNet, which was trained exclusively on task data. This research develops a model to assess the occurrence epilepsy after encephalitis, a severe brain inflammation condition. By using over 57,000 brain scans, the study trains a computer program to recognize patterns in brain images. The model analyzes whole-brain scans to identify areas commonly affected by the disease, such as the temporal and frontal lobes. It was tested on data from patients with encephalitis and showed better performance than older methods. The model can assess the risk of secondary epilepsy in patients with encephalitis, allowing doctors to intervene early and improve treatment outcomes for those affected by this condition. 4 TECHNICAL EFFICACY: Stage 1.

The Effect of Body Expressions on the Learning Process and Facial Recognition among Healthy Participants and Individuals with Traumatic Brain Injury: Examination Using Eye Movements.

Context-dependent effect (CDE) is a process by which reinstating at test the original learning context enhances the recall ability of the material being studied. Although recognition by people with traumatic brain injury (TBI) is poorer than that of healthy controls, both groups show CDE equally. In the current study, we seek to test the effect of body emotional expressions as contextual information, on facial recognition, and eye movements. Twenty-four healthy individuals and 27 patients with moderate-to-severe TBI participated in the study. Participants were exposed to photos of people with neutral facial and body expressions and were asked to remember the people for a subsequent memory test. In the testing session, they were asked to determine whether the person presented to them had appeared before, under two conditions: (1) where the context remains constant (facial and body expressions remained neutral-Repeat condition) and (2) where the context changes (facial expression remained neutral but the body expression changed to angry or happy-Re-pair condition). While the memory of the individuals with TBI was poorer than that of the controls, both groups exhibited equal CDE. We found that both groups, controls more than TBI, spent most of their time looking at the head. Furthermore, longer dwell time was associated with better recognition in the study phase. These findings are consistent with previous studies showing that despite impaired memory following TBI compared to a control group, CDE was preserved. The current study extends the context effect to body postures that express emotion.

Modeling the relationship between online L2 motivational self-system and EFL learners’ virtual exchange self-regulations: the mediator and moderator roles of L2 grit

Abstract While previous studies in computer-assisted language learning have extensively explored sociolinguistic factors, such as cultural competence, important psycholinguistic factors such as online L2 motivational self-system, L2 grit, and online self-regulation in relation to virtual exchange (VE) have remained widely unexplored. To address this gap, a study was conducted with 92 Spanish English as a foreign language learners who exchanged language and culture with Cypriot and Irish students and responded to questionnaires adapted for the study context, as part of the SOCIEMOVE (Socioemotional Skills Through Virtual Exchange) Project. The partial least squares structural equation modeling approach showed that language learners who set positive personal goals for the future and evaluate their current learning progress in VE can regulate their learning in it. Interestingly, the sign of authenticity gap was found in the study context, since learners’ motivation to learn in VE was higher compared to their previous language learning contexts, resulting in more effort and consistency of interest in setting their goals, evaluating their progress, and asking for help from others. Furthermore, learners’ L2 grit moderated and mediated the correlation between learners’ online motivation and online self-regulation, indicating that VE success requires long-term perseverance of effort and consistency of interest. Accordingly, a new conceptual framework for VE was developed. In addition, one of the main implications is that teachers who employ VE should focus more on learners’ current needs and the goals they wish to achieve when exchanging information rather than only focusing on their accomplishments based on the course syllabus.

Vocabulary learning in EFL context: do primary school English Subject textbooks provide structured support?

Vocabulary learning in EFL context: do primary school English Subject textbooks provide structured support?

Learning to fear novel stimuli by observing others in the social affordance framework.

Fear responses to novel stimuli can be learned directly, through personal experiences (Fear Conditioning, FC), or indirectly, by observing conspecific reactions to a stimulus (Social Fear Learning, SFL). Although substantial knowledge exists about FC and SFL in humans and other species, they are typically conceived as mechanisms that engage separate neural networks and operate at different levels of complexity. Here, we propose a broader framework that links these two fear learning modes by supporting the view that social signals may act as unconditioned stimuli during SFL. In this context, we highlight the potential role of subcortical structures of ancient evolutionary origin in encoding social signals and argue that they play a pivotal function in transforming observed emotional expressions into adaptive behavioural responses. This perspective extends the social affordance hypothesis to subcortical circuits underlying vicarious learning in social contexts. Recognising the interplay between these two modes of fear learning paves the way for new empirical studies focusing on interspecies comparisons and broadens the boundaries of our knowledge of fear acquisition.

AI and Uncertain Motivation: Hidden allies that impact EFL argumentative essays using the Toulmin Model.

This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Motivation (UM) strategies on the argumentative writing performance of Saudi EFL learners, using the Toulmin Model. Sixty Saudi EFL students participated in four writing tasks, with results demonstrating significant improvements in essay quality, particularly in clarity, structure, and depth. AI tools provided real-time feedback, enhancing students' ability to refine claims, data, backing, and counterarguments. UM strategies, employing varied and unpredictable rewards, effectively sustained student motivation and engagement. However, a temporary decline was noted early in the study, attributed to the learning curve associated with both AI and the Toulmin model. Writing argumentative essays poses significant linguistic and cognitive challenges for EFL learners. By addressing these barriers, the study highlights the potential of AI to enhance EFL writing proficiency and underscores the motivational role of UM in maintaining student engagement. The findings emphasize the importance of integrating AI and UM thoughtfully into educational practices to maximize their effectiveness. Future research is encouraged to explore AI's long-term effects, address ethical considerations, and refine the integration of AI and UM strategies across diverse learning contexts.

The synergy of immersion and basic psychological needs satisfaction: Exploring gamification's impact on student engagement and learning outcomes.

The integration of gamification into educational institutions has recently attracted considerable interest, owing to the digital era and emerging learning contexts. This study examined how immersion, an essential feature of games, affects various dimensions of education, including satisfaction of basic psychological needs (BPNS), academic engagement, perceived learning effectiveness, and perceived academic performance. Based on Self-determination Theory and the Theory of Gamified Learning, this study investigated how immersion influences autonomy, competence, and relatedness among learners, which could directly affect their engagement and outcomes. Quantitative findings derived from 568 respondent datasheets collected from university and postgraduate students in Vietnam indicate that immersion significantly influences BPNS. However, among the BPNS, only autonomy and competence affected engagement and learning outcomes. Using empirical research within the context of the post-COVID-19 Vietnamese education system, this study intends to provide useful insights for policymakers and researchers seeking to improve teaching performance by applying gamification in schools.

Vision-based displacement measurement method of large-scale bridges using tilt shift camera and fast spatio-temporal context learning

Tracking vibration displacement across multiple points on large-scale bridges in the field poses significant challenges due to perspective distortion by camera tilting, interference from adverse environmental factors and low-resolution images by long distance measurement. To address these issues, this study proposed a novel vision-based displacement measurement framework that combined the Fast Spatio-Temporal Context Learning algorithm (FSTC) with tilt shift cameras to enhance visual tracking accuracy. A procedure was introduced to select suitable tilt shift cameras to eliminate the adverse effects of potential lens distortion. The FSTC algorithm, which integrated the Spatio-Temporal Context Learning algorithm (STC) and FastFlownet, was employed to improve the displacement tracking accuracy of the target object under fog occlusion and during long-distance measurements. Experimental results from slider and shaking table tests demonstrated that the FSTC algorithm outperformed the existing vision-based methods such as STC, Digital Image Correlation (DIC), and Kanade-Lucas-Tomasi (KLT) algorithms in tracking the displacement of the target object, effectively controlling the displacement error (e.g., RMSE and peak error) to below 3 mm. The FSTC algorithm was less sensitive to fog occlusion and exhibited enhanced efficiency in object tracking. Furthermore, the FSTC algorithm, in combination with image resolution reconstruction, enabled subpixel accuracy in tracking the displacement of the target object. A preliminary field application was conducted to track the vibration displacement of the Sanchaji Bridge under wind load, validating the feasibility and applicability of the proposed framework.

Edukasi Fisika: Pembuatan Es Krim Menggunakan Metode Contextual Teaching and Learning

The low level of scientific literacy in society and the perception of physics as a difficult subject to understand pose significant challenges in enhancing public comprehension and engagement with science. Addressing these challenges requires a contextual learning approach that links physics concepts to everyday activities, enabling the community to better understand and apply scientific knowledge. This program aimed to improve public understanding of physics concepts through a contextual approach applied to ice cream-making activities, while also equipping participants with practical skills that are both educationally and economically beneficial. The activity was attended by 11 participants, mostly housewives from Mekar Sari Housing Complex, Sekupang District, Batam City. Conducted at the Posyandu facility, the program utilized the Contextual Teaching and Learning (CTL) approach, incorporating education sessions, demonstrations, hands-on ice cream making, and reflective discussions. Data collection was carried out through direct observations and Likert-scale-based pre-test and post-test questionnaires to measure participants’ understanding, skills, motivation, and creativity. The results indicated an increase in participants' understanding of physics concepts, with the average pre-test score of 58% rising to 93% in the post-test. The program also successfully enhanced participants’ motivation and creativity in applying physics concepts to everyday life. Positive feedback from participants suggested the sustainable application of the knowledge gained, particularly in home-based ice cream-making activities. This activity effectively improved participants' understanding of physics concepts, motivation, and creativity through a contextual approach based on ice cream-making, providing sustainable educational and practical benefits.

EXPRESS: Eye on Context: Individual Differences Reveal the Mechanisms of Statistical Learning.

If a searched-for target object is consistently encountered within repeating spatial distractor arrangements, target detection becomes more efficient relative to non-repeated, i.e., random arrangements (contextual-cueing effect). On the other hand, target location changes within otherwise unchanged distractor arrays substantially weaken the cueing effect. Previous studies reported substantial variations in individual participants' abilities to learn and relearn invariant contexts. Therefore, the current study examined how individual differences in attentional control and focus, as indexed by the well-established Stroop and Navon tasks, respectively, relate to contextual cueing (CC) in a learning phase/relocation phase design. During the visual search, we recorded behavioral reaction times (RTs) and fixation locations, the latter permitting us to decompose search RTs into search- and motor-related substages. We could thus evaluate the processes responsible for CC and the lack thereof after target relocation while also testing whether search and motor components of CC are different for individuals depending on their Stroop/ Navon scores. Repeated contexts yielded faster RTs (and reduced fixation numbers), though there was a substantial decrease in cueing from learning to adaptation, consistent with previous studies. Critically, contextual learning, but not relearning, varied across individuals: participants with high-Stroop interference displayed overall larger CC during early target search, while a more local Navon task bias was associated with increased CC during later processes of target response decisions. Our results demonstrate that analyzing individual differences can help validate the processes responsible for CC in search tasks, particularly distinguishing between early search and later response-related mechanisms.

FROM DIGITAL GAMES TO COMPUTATIONAL THINKING: A META-ANALYTIC REVIEW IN MATHEMATICS EDUCATION

In the last ten years, there has been considerable growth in empirical studies examining the effects of digital games on mathematics learning and computational thinking (CT). However, a review of the existing literature indicates that the outcomes of digital game-enhanced math instruction on students' CT skills have yielded inconsistent results. This research intends to evaluate how effective digital game-supported mathematics education is in developing students' CT abilities, while taking into account various factors such as educational level, duration of the intervention, learning context, game developer, and type of game. A meta-analytic review was conducted, analyzing 15 pertinent studies published between 2011 and 2023, which produced 21 effect sizes and included a total of 8,911 students. Statistical analyses, including the Q Cochrane test, publication bias assessment, Z test, and sensitivity analyses, were performed using CMA software to scrutinize the data. The results indicated a statistically significant but modest positive effect (g = 0.344; p &lt; 0.05) of digital game-supported math education on students' CT skills. Several factors, including the length of the intervention, the software developer, and the type of game, significantly impacted CT outcomes, whereas other factors, such as educational level and learning environment, did not show a significant influence. These findings suggest that digital game-supported mathematics instruction can be an effective technological approach to enhance students' computational thinking abilities.