The development of artificial intelligence (AI) has significantly impacted the learning process in higher education. This study aims to analyze the use of artificial intelligence to support the learning process in higher education, including the forms of use, benefits, and challenges it poses. The study used a qualitative descriptive approach with a literature review method. Data were obtained from various scientific journal articles, books, research reports, and institutional documents relevant to the use of AI in higher education. Data analysis was conducted using content analysis by identifying, classifying, comparing, and synthesizing various previous research findings. The results show that AI can be utilized as a learning assistant, a supporter of personalized learning, a developer of teaching materials, a provider of feedback, an assessment supporter, and a tool to enhance student self-directed learning and creativity. The use of AI can also help lecturers increase efficiency in planning and implementing learning. However, the use of AI presents challenges such as information inaccuracy, technology dependency, violations of academic integrity, data privacy, bias, and the potential for a decline in students' critical thinking skills. Therefore, the use of AI in higher education must be carried out ethically, critically, responsibly, and human-centeredly through strengthening AI literacy, improving lecturer competency, institutional policies, and adjusting assessment systems. AI should be positioned as a tool to enhance the learning process, not as a substitute for lecturers or students' thinking processes.
Heppy Sapulete, Lia Khalisa, Afifah Qurrota A'yun et al.· International Journal of Edu...· 0 citations
The integration of digital technology into elementary education has accelerated the implementation of blended learning, requiring students to develop stronger self-regulated learning skills to achieve optimal academic outcomes. Although previous studies have examined these variables independently, limited research has investigated their combined contribution to academic achievement among elementary school students. This study aims to examine the effects of blended learning and self-regulated learning on students' academic achievement in elementary education, both individually and simultaneously.This research employed a quantitative explanatory design using a survey approach. The study involved elementary school students selected through proportionate random sampling. Data on blended learning and self-regulated learning were collected using validated and reliable questionnaires, while academic achievement was measured through students' academic performance records. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the measurement model and structural relationships among the variables. The findings indicate that blended learning has a positive and significant effect on academic achievement, demonstrating that the integration of face-to-face and digital learning environments enhances students' learning outcomes. Self-regulated learning also exerts a positive and significant influence, indicating that students with stronger abilities in goal setting, self-monitoring, learning strategy management, and self-evaluation tend to achieve higher academic performance. Furthermore, the structural model reveals that blended learning and self-regulated learning jointly explain a substantial proportion of the variance in academic achievement, confirming their complementary roles in improving educational outcomes.
Nurlaiha Ibrahim, T. Santosa, Sahwan Sahwan et al.· Education and Learning Journ...· 0 citations
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