Conference Program
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Daily Overview |
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1.2.2: Decolonization & Knowledge
Session Topics: Decolonization & Knowledge
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Probing perspectives on artificial intelligence and development: The process and results of student projects in an international development qualitative research methods course What are the experiences of development studies students and alumni, and of faculty, in bringing artificial intelligence (AI) into course content and the development studies program? What are their views on the future of AI and development studies? What insights do campus specialists in teaching and learning, in academic accommodation services, in library services, in career services, and in information technology services offer into the use of and role for AI on campus? These are some of the questions tackled by undergraduate students in an international development qualitative research methods class in which student groups were tasked with designing, conducting and writing up semester-long projects. Each study focused on one type of actor, and used one method – interviews, surveys, participant observation, photovoice, focus group discussion, journaling – to explore their perspectives on AI and development. In this round table discussion, undergraduate students, graduate student teaching assistant, graduate student mentor and course instructor discuss their processes, their study findings and surprises, and their reflections on the future of AI in development research and development work. By critically engaging with qualitative research methodologies and reflecting on their own positionalities and biases, students discuss how they became aware of the power dynamics at play within knowledge production processes, and how AI may and does disrupt these processes. This roundtable aims to start a conversation among students and instructors about AI in and beyond the development studies classroom. Audience participation will be encouraged. Presentations of the Symposium Undergraduate student insights Undergraduate students in the course will contribute their insights conducting the research. For many students, this was their first time designing and conducting empirical research. Teaching assistant insights The course teaching assistant will share her experiences supporting student learning through her involvement supporting student projects throughout the semester. Course instructor insights The course instructor will share her experiences setting up and running the course to scaffold student learning of qualitative research methods and about AI and development. Graduate student mentor insights Graduate student mentors will share their experiences supporting student learning through their mentorship of student projects throughout the semester. | ||