Integrating Artificial Intelligence into Educational Technology: Theoretical Foundations and Educational Practices

This study aimed to investigate the effect of integrating artificial intelligence (AI) into educational technology on certain learning outcomes among university students. It examined the role of AI-based personalization, AI-supported feedback, and learner autonomy in explaining academic performance, student engagement, and perceived learning efficiency. The study adopted a quantitative descriptive correlational predictive approach and was conducted on a sample of 80 students from Al al-Bayt University. Data were collected using a structured questionnaire based on a five-point Likert scale and analyzed through descriptive statistics, simple linear regression, and multiple regression. The findings revealed high levels of AI-based personalization and perceived academic performance, with a statistically significant positive effect of personalization on academic performance. The results also showed high levels of AI-supported feedback, student engagement, and learner autonomy, with a significant positive effect of feedback on student engagement. Furthermore, multiple regression analysis indicated that AI integration features collectively predicted perceived learning efficiency, with learner autonomy contributing the most, followed by personalization and feedback. The study emphasized the importance of integrating AI into higher education within clear pedagogical frameworks. Keywords: artificial intelligence in education, educational technology, educational personalization, AI-supported feedback, learner autonomy, academic performance, higher education