Factors influencing the effective use of AI in higher education student learning
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Key Factors Influencing Effective Use of AI in Higher Education Student Learning
Perceived Usefulness, Benefits, and Attitudes Toward AI
A major factor influencing the effective use of AI in higher education is students’ perception of its usefulness and the expected benefits it brings to their learning. Studies consistently show that when students believe AI tools will improve their academic performance, engagement, or learning experience, they are more likely to adopt and use these technologies effectively 15910. Positive attitudes toward technology and a clear understanding of AI’s potential also play a significant role in driving adoption and effective use 1410.
Ease of Use, Technical Competency, and Human-Computer Interaction
Perceived ease of use and students’ technical competency are important, but their influence can be complex. While some research finds that easier-to-use AI tools encourage adoption, others note that if a tool is too intuitive, students may undervalue its usefulness for deeper learning 15. Technical competency—students’ confidence in using digital tools—directly impacts their ability to benefit from AI applications 35. Additionally, the quality of human-computer interaction, such as how engaging or supportive the AI interface is, mediates the effectiveness of AI in learning .
Institutional Support, Training, and Ethical Guidelines
Universities play a critical role by fostering a supportive environment for AI integration. This includes providing training for both students and faculty, encouraging experimentation, and developing clear ethical guidelines for responsible AI use 1247810. Formal AI education and training help bridge the gap between students’ enthusiasm and their practical knowledge, ensuring more effective and ethical use 410.
Personalization, Collaboration, and Learning Environment
AI tools are most effective when they support personalized learning, self-assessment, and collaborative environments. They can help students identify their learning needs, provide tailored feedback, and facilitate meaningful peer interactions, all of which enhance motivation, engagement, and academic performance 2678. Creating a balance between AI-mediated and human interaction is also important for maintaining a supportive and ethical learning environment .
Performance Expectancy, Pedagogical Fit, and Information Accuracy
Students are more likely to use AI tools when they expect these tools to improve their academic performance and when the tools fit well with their learning needs and course requirements. The accuracy of information provided by AI and its alignment with pedagogical goals are also crucial for effective use 9610.
Barriers: Language, Access, and Trust
Barriers such as language difficulties, especially for non-native English speakers, can hinder effective AI use . Other challenges include unequal access to technology, lack of trust in AI systems, and insufficient knowledge or training 410. Addressing these barriers is essential for equitable and effective AI integration.
Moderating and Mediating Factors
Factors such as prior experience with technology, digital self-efficacy, and the specific context (e.g., STEM vs. non-STEM disciplines, public vs. private institutions) can moderate or mediate the effectiveness of AI in student learning 3710. Facilitating conditions, such as institutional resources and support, further influence how well students can leverage AI tools 57.
Conclusion
The effective use of AI in higher education student learning depends on a combination of perceived usefulness, technical competency, supportive institutional environments, personalized and collaborative learning opportunities, and the removal of barriers such as language and access. Ethical guidelines, ongoing training, and context-specific strategies are essential to maximize the benefits of AI while ensuring responsible and equitable use 12345678+2 MORE.
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