AI-Assisted Teaching Model for Personalized Computer Education Based on Deep Learning
Year: 2025
Type: article
Study design: Clinical Trial
Abstract: This study investigates an AI-assisted, deep learning–based personalized teaching model for computer education. With the rapid expansion of artificial intelligence in the education sector, personalized learning has become increasingly important for improving instructional effectiveness. Sixty computer science students were selected and randomly assigned to an experimental group—receiving AI-assisted personalized instruction—and a control group using traditional teaching methods. Data were collected through a learning management system, a programming practice platform, and a structured questionnaire. Descriptive statistics, independent-sample difference tests, and correlation analyses were employed to evaluate outcomes. The findings indicate that the experimental group outperformed the control group across key indicators, including learning-path adaptability, learning-effect improvement rate, and satisfaction with learning feedback. These results demonstrate that the AI-assisted teaching model significantly enhances learning effectiveness and learner engagement. The study contributes a practical and data-driven framework for integrating AI into personalized computer education. However, limitations related to sample size, single-discipline focus, and short intervention duration suggest the need for broader, longitudinal, and cross-disciplinary future research.
Institution: Bansomdejchaopraya Rajabhat University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7219987978