Spyridon Plakias
Department of Physical Education and Sport Science, University of Thessaly

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Reclaiming the value of qualitative analysis in sports performance research Spyridon Plakias
Physical Education and Sports: Studies and Research Vol. 5 No. 1 (2026): Physical Education and Sports: Studies and Research
Publisher : CV Rezki Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56003/pessr.v5i1.672

Abstract

Quantitative metrics and technology-driven approaches have reshaped sports performance analysis (SPA), yet they risk overshadowing the equally vital contribution of qualitative methods. This opinion paper highlights the value of qualitative analysis in capturing the complexity, context, and meaning of player and team behaviors, elements that numbers alone cannot explain. Drawing on video-based evaluations, case studies, and narrative reconstructions, qualitative approaches provide insights into tactical, psychological, and interactional dimensions of performance that are indispensable for bridging the science–practice gap. By integrating qualitative and quantitative perspectives, SPA can achieve a more balanced and applicable paradigm, ensuring that scientific research remains relevant to real-world coaching and athlete development. This paper calls for a renewed recognition of qualitative methods as a central pillar of SPA and invites further scholarly contributions to this evolving discussion.
Artificial intelligence-supported motor skill performance in physical education and sport: A systematic review and meta-analysis informed by motor learning theory Yulingga Nanda Hanief; Vera Septi Sistiasih; Ferdinando Cereda; Spyridon Plakias
Journal of Artificial Intelligence in Education & Learning Innovation Vol. 2 No. 1 (2026): Journal of Artificial Intelligence in Education & Learning Innovation
Publisher : CV Rezki Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56003/jaieli.v2i1.753

Abstract

Background: Artificial Intelligence (AI) has increasingly been integrated into physical education (PE) to support motor learning through technologies such as computer vision, motion tracking, intelligent tutoring systems, virtual reality, and generative AI. However, evidence regarding its effectiveness remains fragmented across different intervention types and learning contexts. Objectives: This study aimed to evaluate the effects of AI-supported interventions on motor skill performance in physical education and sport settings and to synthesize complementary learning-related outcomes. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA 2020. Scopus, PubMed, and ProQuest were searched through 22 June 2026. Eligible studies evaluated AI-supported, adaptive, or intelligent interventions in physical education, sport, or motor skill-learning contexts and reported learner-level motor performance; complementary learning-related outcomes were synthesized narratively. Risk of bias was assessed using RoB 2 and ROBINS-I, and standardized mean differences (SMDs) with 95% confidence intervals (CIs) were synthesized using a random-effects model. Results: Fifteen studies were included in the qualitative synthesis; six contributed to the meta-analysis and nine were synthesized narratively. The pooled estimate favored the designated AI-supported experimental conditions over their comparators (SMD = 3.15, 95% CI 1.86–4.44; p < .001; I² = 98%). Given the small evidence base, very high heterogeneity, and variable risk of bias, the magnitude of this pooled effect is uncertain. Qualitative findings concerned short-term motor skill performance and complementary outcomes such as engagement, motivation, learning interest, and self-directed learning. Conclusions: AI-supported interventions may improve short-term motor skill performance in some physical education and sport contexts and may support complementary learning-related outcomes. However, the evidence is preliminary and highly heterogeneous, and immediate post-intervention performance should not be interpreted as definitive evidence of durable motor learning, retention, or transfer. AI should be considered a complementary pedagogical tool rather than a replacement for teacher or coach expertise.