Integrating AI Into Instructional Design: A Case Study on Digital Photography Education in Higher Education

Abstract

This study investigates the impact of artificial intelligence (AI)-supported education in higher education, specifically examining its integration into a digital photography course and its effects on both students and instructors. A qualitative research methodology was employed, and participants were selected through purposive sampling. The study involved one instructor and 38 students, with data collected through semi-structured interviews and analyzed using content analysis within a qualitative case study design. The findings indicate that AI enhances educational processes by facilitating individualized learning, improving instructional effectiveness, supporting digital content development, and advancing academic language proficiency. Students demonstrated improvements in critical evaluation and technological adaptability. Additionally, the study revealed that AI-supported tools contributed to the development of students' technical skills and promoted active engagement in learning processes. The immediate feedback provided by AI tools aided students' understanding of fundamental photography principles. However, some students expressed concerns about potential risks associated with AI, including decreased engagement, learner passivity, and exposure to misinformation or contradictory content. The study highlights the importance of integrating AI within a sound pedagogical framework to ensure its effective application in educational contexts. Drawing on the experiences of both students and the instructor, the findings suggest that AI-supported educational models can enhance learning efficiency, while also emphasizing the need to bolster information reliability and foster critical thinking skills.