The Impact of Real-Time Pose Recognition Technology on Tennis Learning in Individuals With Intellectual Disabilities: A Comparative Study With Traditional Methods
The Impact of Real-Time Pose Recognition Technology on Tennis Learning in Individuals With Intellectual Disabilities: A Comparative Study With Traditional Methods
This study investigates the effect of real-time pose recognition technology on learning tennis skills in individuals with mild to moderate intellectual disabilities. The study compares two training methods: traditional face-to-face tennis instruction and training supported by Real-Time Pose Recognition System (RPRS). Thirty participants aged 12-18 from special education institutions in Burdur, Turkey, were randomly assigned to either the experimental group using the technology or a control group receiving traditional instruction. The study aims to determine whether the use of real-time pose recognition improves tennis skill accuracy, learning speed, attention, and motivation compared to traditional methods.
This study was conducted over 14 weeks with 30 participants aged 12-18 years, diagnosed with mild to moderate intellectual disabilities, recruited from special education institutions in Burdur, Turkey. Participants were randomly assigned to two groups: an experimental group receiving tennis training supported by RPRT and a control group receiving traditional face-to-face instruction.
The intervention consisted of three 45-minute sessions per week, with participants practicing forehand, backhand, and serve skills. The experimental group used a MediaPipe-based system that provided real-time visual feedback on movement accuracy, including body pose, hand gestures, and eye tracking (FaceMesh and Iris modules). The control group received conventional instruction with in-person guidance and manual correction from instructors.
Weekly interim assessments monitored skill accuracy, frequency and type of errors, reaction time, attention, and motivation. Primary outcomes included skill performance metrics and reaction times, while motivation and attention were assessed using semi-structured interviews. Data were collected via structured observation forms, video recordings, and interviews, and analyzed using SPSS software with repeated measures ANOVA and paired/independent t-tests.
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