Adoption of AI by PhD Students at Ibn Tofail University: A Qualitative Study
The adoption of Artificial Intelligence (AI) by PhD students is an emerging area of academic inquiry, intersecting fields such as education, technology, and research methodology. Despite its growing prevalence, limited knowledge exists regarding how PhD students understand, use, and perceive AI in...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Moroccan Association for Applied Science and Innovation
2025-04-01
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| Series: | Moroccan Journal of Quantitative and Qualitative Research |
| Subjects: | |
| Online Access: | https://revues.imist.ma/index.php/MJQR/article/view/54346 |
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| Summary: | The adoption of Artificial Intelligence (AI) by PhD students is an emerging
area of academic inquiry, intersecting fields such as education, technology, and research
methodology. Despite its growing prevalence, limited knowledge exists regarding how
PhD students understand, use, and perceive AI in their academic practices. This study
addresses these gaps by exploring the opportunities and challenges faced by doctoral
researchers in integrating AI tools into their work. Using a qualitative approach, we
conducted semi-structured interviews with PhD students from diverse academic
disciplines at Ibn Tofail University, Morocco. The analysis focused on six key themes:
awareness and understanding of AI, usage of AI tools, perceived benefits, challenges to
adoption, institutional support, and the future role of AI.
The findings reveal that while AI enhances efficiency, productivity, and innovation in
academic research, barriers such as technical complexity, ethical concerns, and limited
institutional support hinder its broader adoption. Participants also highlighted the
transformative potential of AI in reshaping research methodologies and fostering global
collaboration. This study underscores the need for targeted interventions, including
tailored training, resource accessibility, and ethical oversight, to empower PhD students
in leveraging AI effectively.
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| ISSN: | 2665-8623 |