supervisor: reza farrokhnia
The rapid integration of AI tools like ChatGPT and Gemini in education is transforming how students learn, write, and engage with academic tasks. However, over-reliance on these tools poses risks to critical thinking, self-regulation, and ethical considerations. AI literacy, encompassing knowledge of AI, its mechanisms, and ethical use, is vital to ensure students critically and effectively engage with AI while fostering lifelong learning skills. It manifests as a particular kind of intellectual agility: the ability to see and critically evaluate multiple potential pathways through AI interaction, all while navigating uncertainty with nuanced judgment. Despite growing research, there is a gap in student-centered studies focusing on practical and theory-driven approaches to enhance AI literacy. The following topics could be chosen by a master student to advance understanding and application of AI literacy in higher education, addressing critical gaps in measurement, pedagogy, and its impact on student learning and engagement.
PROPOSED TOPICS RELATED TO THE THEME
1. | Generative AI sensitivity to text quality in automated feedback |
2. | Developing and validating an AI literacy scale
Purpose: To create a reliable, multidimensional measurement tool for AI literacy (knowledge, skills, attitudes) and address gaps in student-centered research.
Method: Literature review, expert feedback via the Delphi method, pilot study for scale validation using factor analysis, and correlational analysis with academic outcomes. |
3. | Exploring the impact of pedagogical interventions on students’ AI literacy
Purpose: To assess how instructional strategies (e.g., workshops, guided practice) enhance critical and ethical use of AI tools and their impact on engagement and critical thinking.
Method: Quasi-experimental study with pre- and post-tests, comparing intervention and control groups, combined with focus groups for qualitative insights. |
4. | Developing a comprehensive model of AI literacy
Purpose: To refine the conceptual framework of AI literacy by identifying its dimensions (e.g., knowledge, skills, ethics) and their interrelations.
Method: Delphi study with experts to define dimensions, followed by confirmatory factor analysis of a student survey to validate the model. |
5. | The role of AI literacy in reducing over-reliance on AI tools
Purpose: To explore how AI literacy influences students’ dependency on AI tools and promote strategies for independent, critical learning.
Method: Mixed methods using surveys to measure AI literacy and reliance on AI tools, alongside interviews to uncover students’ perceptions and barriers. |
6. | The relationship between AI literacy and academic integrity
Purpose: To examine how AI literacy affects students’ adherence to academic integrity when using AI tools for academic tasks.
Method: Mixed methods study combining surveys measuring AI literacy and integrity behaviors with focus groups exploring students’ attitudes and challenges. |
7. | AI Literacy and digital equity: Barriers among underrepresented students
Purpose: To understand how digital equity factors influence AI literacy and engagement with AI tools in higher education.
Method: Mixed methods study using surveys to measure AI literacy and digital equity, complemented by interviews exploring challenges faced by marginalized students. |
