EVALUATING THE PEDAGOGICAL EFFICACY OF AI INTEGRATED LEARNING VERSUS TRADITIONAL DIDACTICS: A STRATIFIED CROSS-SECTIONAL STUDY OF DENTAL STUDENTS.

Abstract

Background Cerebral Palsy is one of the most common causes of physical disability in children. Children with spastic diplegic cerebral palsy commonly present with impairments in balance, sensory processing, and gross motor function, which affect their functional independence and quality of life. Balance and sensory impairments may significantly influence postural control, gait, and motor performance in these children. Aim To determine the prevalence of balance and sensory impairments and their correlation with gross motor function in children with spastic diplegic cerebral palsy. Objectives 1. To assess balance impairments using the Pediatric Berg Balance Scale. 2. To evaluate sensory impairments using the Sensory Profile. 3. To assess gross motor function using the Gross Motor Function Measure and Gross Motor Function Classification System. 4. To analyze the correlation between balance, sensory impairments, and gross motor function. Methodology A cross-sectional study was conducted among 109 children diagnosed with spastic diplegic cerebral palsy aged between 5–12 years. Participants were selected based on inclusion and exclusion criteria. Balance was assessed using the Pediatric Berg Balance Scale, sensory impairments were evaluated using the Sensory Profile, and gross motor function was assessed using the GMFM and GMFCS. The collected data were statistically analyzed using Pearson’s and Spearman’s correlation tests. Results The study demonstrated a strong positive correlation between Pediatric Berg Balance Scale scores and GMFM scores (Pearson r = 0.828, p < 0.001; Spearman rho = 0.854, p < 0.001). A very strong positive correlation was observed between Pediatric Berg Balance Scale scores and Sensory Profile scores (Pearson r = 0.955, p < 0.001; Spearman rho = 0.953, p < 0.001). Similarly, GMFM scores showed a very strong positive correlation with Sensory Profile scores (Pearson r = 0.946, p < 0.001; Spearman rho = 0.948, p < 0.001). Conclusion The study concluded that balance and sensory impairments are highly prevalent in children with spastic diplegic cerebral palsy and are significantly correlated with gross motor function. Better balance and sensory processing abilities were associated with improved gross motor performance. Early assessment and targeted rehabilitation focusing on balance and sensory integration may help improve functional outcomes in children with spastic diplegic cerebral palsy.Background: Artificial intelligence (AI) technologies, including large language models (LLMs) and computer aided diagnostic platforms, are increasingly integrated into higher education. However, empirical comparative evaluations regarding their pedagogical efficacy in dental clinical training remain limited. Building upon the foundational survey framework of Slimi et al. (2025), this study scaled and adapted the thematic constructs to a target population of dental students to evaluate the perceived impact of AI-assisted learning tools compared to conventional educational methods. Methods: A stratified cross-sectional comparative study was conducted among ???? = 250 dental students spanning preclinical (BDS Years 2–3) and clinical (BDS Year 4 and Interns) training levels across three dental academic institutions. Participants completed a validated 5-point Likert scale instrument assessing primary AI usage patterns, core competency improvements, cognitive engagement, and perceptions of academic integrity. Parametric and non-parametric statistical analyses—including Chi-square tests of independence and independent samples ????-tests—were utilized to compare outcomes between AI-integrated and conventional pedagogical approaches. Results: Overall, 86.4% (???? = 216) of participants reported utilizing generative AI or automated diagnostic tools for academic or clinical case analysis. ChatGPT (74.4%, ???? = 186) and automated writing/feedback platforms (62.8%, ???? = 157) were the dominant tools utilized. Paired metric evaluations demonstrated that AI-assisted learning yielded significantly higher perceived efficacy in clinical case diagnostic interpretation (???? = 4.12,???????? = 0.78) compared to conventional seminar instruction (???? = 3.34,???????? = 0.89; ????(249) = 11.24,???? < 0.001). Furthermore, AI integration significantly accelerated perceived concept comprehension speed (???? < 0.001) and self-assessment capability (???? < 0.001). However, 47.2% (???? = 118) expressed concerns that over-reliance on AI could impair independent diagnostic reasoning skills. Conclusion: AI tools substantially enhance student self-efficacy, rapid conceptual understanding, and diagnostic case analysis compared to traditional didactic modalities. Nevertheless, curriculum integration must be accompanied by explicit ethical guidelines and balanced pedagogical frameworks to prevent cognitive atrophy in clinical judgment.