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    Effects of cooperative learning on students' learning outcomes in physical education: a meta-analysis
    (Frontiers Media Sa, 2025) Boke, Hulusi; Aygun, Yalin; Tufekci, Sakir; Yagin, Fatma Hilal; Canpolat, Burak; Norman, Goktug; Prieto-Gonzalez, Pablo
    This meta-analysis examines the effect of Cooperative Learning (CL) interventions, compared to traditional instructional methods, on students' learning outcomes across affective, cognitive, physical, and social domains in physical education (PE). The review involved a comprehensive search of 12 databases in English, Spanish, and Turkish, with the last search conducted on June 2nd, 2024. Studies included were true experimental or quasi-experimental designs featuring direct CL interventions in PE, covering students of both genders from primary school to university levels. The standardized Cochrane methods were used to identify eligible records, collect and combine data, and assess the risk of bias. Comprehensive Meta-Analysis (CMA) v4 software package was used to yield a summary of quantitative results. Hedges's g was used as the effect size (ES) measure, calculated from pre- and post-tests in both experimental and control groups. Forty-three studies (comprising 60 reports) were initially included, but three studies were excluded as outliers, leaving 40 studies (56 reports) with a total of 3.985 participants for analysis. The random effects model revealed a moderate positive overall effect of CL interventions (ES = 0.459, 95% CI = [0.324, 0.592], p < 0.001), indicating that CL enhances PE students' learning across four domains. Subgroup analyses showed small to moderate ESs for affective (ES = 0.304), physical (ES = 0.471), cognitive (ES = 0.589), and social learning (ES = 0.612). Risk of bias was evaluated using Begg and Mazumdar's rank correlation, the classic fail-safe number, and a funnel plot, all indicating a low risk of bias. Methodological quality was assessed using the Medical Education Research Study Quality Instrument (MERSQI). The study was registered on PROSPERO (ID: CRD42024532607). This meta-analysis underscores the effectiveness of CL as a student-centered pedagogical model in PE, demonstrating its positive effect on various learning outcomes in the affective, cognitive, physical, and social domains. The findings provide instructive data and strategies for researchers, practitioners, and policymakers aiming to integrate, implement, or make context-specific adaptations of CL into educational processes, while ESs in the affective, physical, cognitive, and social learning domains provide domain-based implementation guidance for these stakeholders.
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    Emotional and Social Outcomes of the Teaching Personal and Social Responsibility Model in Physical Education: A Systematic Review and Meta-Analysis
    (Mdpi, 2024) Aygun, Yalin; Boke, Hulusi; Yagin, Fatma Hilal; Tufekci, Sakir; Murathan, Talha; Gencay, Ertugrul; Prieto-Gonzalez, Pablo
    Context: In today's ever-changing world, fostering personal and social responsibility is essential for building strong and compassionate communities. This study aimed to provide a quantitative synthesis focusing on the emotional and social outcomes of Teaching Personal and Social Responsibility (TPSR) model-based Physical Education (PE) programs. Methods: A comprehensive literature review covering the period from November 2022 to September 2023 identified 637 articles published between 2005 and 2023. Of these, 20 met the inclusion criteria. Data from these articles were coded, and a comprehensive meta-analysis was conducted, incorporating 28 effect sizes. Methodological quality was assessed using the Medical Education Research Study Quality Instrument. Hedge's g served as the effect size measure and emotional and social outcomes subgroups were consolidated. Heterogeneity was evaluated with Cochran's Q and I2. Meta-regression and ANOVA-like models addressed categorical moderators, whereas publication bias was assessed through funnel plot, failsafe number, and Egger's linear regression. Results: A significant and positive effect of the TPSR model on product outcomes (Hedge's g = 0.337, 95% CI = 0.199 to 0.476) was found. Despite considerable heterogeneity (I2 = 83.830), a random effects model was justified. Assessment of publication bias indicated a low likelihood. Moderator analyses revealed that publication countries significantly influenced the effect, with stronger effects in Turkey. Publication type (article vs. thesis) also played roles in moderation. The meta-regression analyses did not reveal significant effects for the grade level, duration of intervention, publication year or sample size on the TPSR model's impact on product outcomes. The TPSR model positively impacts emotional and social outcomes in PE, enhancing children' skills and behaviour. However, variations across cultures highlight the need for further research, considering limitations like language constraints and potential biases in study selection and data extraction.
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    Examination of nutritional knowledge levels of physical education and sports stakeholders in gender variable: A systematic review and meta-analysis
    (Iermakov S S, 2021) Tufekci, Sakir; Boke, Hulusi; Altungul, Oguzhan
    Background and Study Aim Nutrition knowledge is related to dietary behavior in athletes. Therefore, it may also have an impact on performance. Athletes with better nutrition knowledge have more healthy dietary habits. This metaanalysis study focused on the impact of gender on the nutrition knowledge levels of physical education and sports stakeholders. Material and Methods This study adopted a meta-analysis research design, which is used to analyze, synthesize, and interpret quantitative findings from an array of studies through advanced statistical techniques. A meta-analysis involves combining the findings of studies carried out in different places and at different times on the same topic and obtaining a quantitatively accurate result based on a large sample. This study employed the Comprehensive Meta-Analysis (CMA, v. 2.0) to determine effect sizes and the variance of each study and to compare groups. Cohen's kappa intercoder reliability and outlier tests were performed using the Statistical Package for Social Sciences (SPSS). Results: We focused on 31 studies with a total sample size of 4575. We calculated the effect size of each study. We found a statistically significant effect size in favor of female stakeholders (d = 0.15; 95% CI -0.22 -0.09) in the fixed effects model, which was a weak result according to Cohen's classification. We determined a statistically significant effect size in favor of female stakeholders (d = 0.15; 95% CI -0.29-0.01) in the randomeffects model. These results suggest a slight difference in nutrition knowledge levels between male and female physical education and sports stakeholders. This result can pave the way for further research. Conclusions It is understood from the physical education and sports stakeholders that there is a weak difference in the nutritional knowledge levels of women compared to men. It is thought that people who study on sports nutrition and nutrition programs will benefit from the present finding. In addition, it is estimated that the researches to be carried out on the relevant subject will take the current study as a reference.
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    Examination of sports science faculty students' attitudes towards online learning by different variables
    (Iermakov S S, 2021) Boke, Hulusi; Tufekci, Sakir
    Background and Study Aim In distance education, students' attitudes towards this method gain importance in the process. The aim of this research is to examine the impact of coronavirus anxiety, academic self-sufficiency and life satisfaction levels of students in the faculty of sports sciences over their attitudes towards online learning. Material and Methods A total of 379 sports science faculty students voluntarily participated for the cross-sectional data collection. A simple random sampling method was used in the selection of students from four universities in the Eastern Anatolian region, which make up the universe of the study. Data were collected electronically and analysed by IBM SPSS and AMOS statistical package program. Results: The structural equity model results revealed that academic self-sufficiency and life satisfaction are positive predictors of online learning attitudes and negative predictors of coronavirus anxiety. Online learning attitude was found to be positively correlated with other variables other than coronavirus anxiety. In addition, it has been determined that the scale total scores are slightly above average, except for coronavirus anxiety. Conclusions: The results have been discussed in terms of their meaning for the environment of physical education. In this research, which created a model for understanding online learning attitudes in students of the faculty of sports sciences, it was understood that coronavirus anxiety has a statistically significant effect on online learning attitudes while academic self-sufficiency and life satisfaction do not have a statistically significant effect. Students' positive attitude towards online learning and understanding the predictors of this attitude will be a development to be appreciated by all stakeholders of the subject.
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    Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence
    (Frontiers Media Sa, 2025) Gormez, Yasin; Yagin, Fatma Hilal; Yagin, Burak; Aygun, Yalin; Boke, Hulusi; Badicu, Georgian; De Sousa Fernandes, Matheus Santos
    Objectives This study aims to build a machine learning (ML) prediction model integrated with explainable artificial intelligence (XAI) to categorize obesity levels from physical activity and dietary patterns. The inclusion of XAI methodologies facilitates a comprehensive understanding of the risk factors influencing the model predictions and thus increases transparency in the identification of obesity risk factors.Methods Six ML models were used: Bernoulli Naive Bayes, CatBoost, Decision Tree, Extra Trees Classifier, Histogram-based Gradient Boosting and Support Vector Machine. For each model, hyperparameters were tuned by random search methodology and model effectiveness was evaluated by repeated holdout testing. SHAP (SHapley Additive Annotations) and LIME (Local Interpretable Model Independent Annotations) interpretability methods were used to generate local and global feature importance measures.Results The CatBoost model exhibited the highest overall performance and achieved superior results in accuracy, precision, F1 score and AUC metrics. Nonetheless, other models such as Decision Tree and Histogram-based Gradient Boosting also yielded strong and competitive results. The results also highlighted age, weight, height and specific food patterns as key predictors of obesity. In terms of interpretability, LIME showed superior in fidelity, whereas SHAP showed improved sparsity and consistency across models, facilitating a comprehensive understanding of trait importance.Conclusion This research demonstrates that ML algorithms, when integrated with XAI technologies, can accurately predict obesity levels and explain important contributing risk factors. The use of SHAP and LIME increases model transparency, facilitating the identification of specific lifestyle patterns linked to obesity risk. These findings help to formulate more precise intervention techniques guided by a reliable and understandable predictive framework.