Ibrahim Oluwajoba Adisa
Postdoctoral Scholar, Education
Web page: https://profiles.stanford.edu/jobaa
Bio
Ibrahim ('Joba) Adisa is a Human-Centered AI (HAI) Postdoctoral Fellow at Stanford's Graduate School of Education, collaborating with Dr. Victor Lee on advancing research to promote AI literacy in K-12 education. His research lies at the intersection of learning sciences, computing education, data science, and AI literacy. He focuses on developing tools and curricula resources that enhance data literacy and promote creativity, computational thinking, and collaborative problem-solving with AI in K-12 education. His research is often conducted through co-designs and partnerships in formal and informal learning environments. He uses qualitative and statistical machine learning methods to model learners' interactions in these environments.
'Joba completed his undergraduate studies at the Federal University of Technology Minna with an emphasis on cognitive science, physics, and mathematics. He earned a master's in educational technology from the University of Ibadan and obtained his doctorate in Learning Sciences from Clemson University, where he supported several NSF-funded projects in STEM, data science, and AI education. Before graduate school, he worked as a Digital Learning Specialist at Tek Experts, a global digital tech talent corporation. His diverse academic background underpins his innovative approach to educational research and instructional design. 'Joba has received numerous awards and honors throughout his academic career, including the Outstanding Graduate Researcher Award and fellowships from MTN Foundation, Caroline Odunola Foundation, Clemson University, and Stanford PRISM Baker. His publications span various high-impact journals and conferences, contributing to the fields of AI literacy, data science and computing education.
Honors & Awards
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PRISM Baker Fellowship, Stanford University (2024)
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Graduate Student Award of Excellence in Research, Clemson University (2024)
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RC Edward Graduate Fellowship, Clemson University (2020-2022)
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Best Poster Paper, International Conference on Quantitative Ethnography (2021)
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Caroline Odunola Memorial Fellowship, Caroline Odunola Foundation (2019)
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MTN Foundation Scholar, MTN Foundation (2012-2015)
Boards, Advisory Committees, Professional Organizations
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Member, Association for Computing Machinery's Special Interest Group on Computer Science Education (SIGCSE) (2024 - Present)
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Member, ACM Special Interest Group on Computer-Human Interaction (SIGCHI) (2023 - Present)
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Member, International Society of the Learning Sciences (ISLS) (2022 - Present)
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Member, American Educational Research Association (AERA) (2022 - Present)
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Member, International Society for Quantitative Ethnography (ISQE) (2021 - Present)
Professional Education
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Ph.D., Clemson University, Learning Sciences (2024)
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M.Ed., University of Ibadan, Educational Technology (2018)
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B.Tech., Federal University of Technology Minna, Physics Education (2015)
Research Interests
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Collaborative Learning
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Data Sciences
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Professional Development
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Science Education
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Technology and Education
Projects
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CRAFT, Stanford University
Classroom-Ready Resources About AI For Teaching (CRAFT) is a collaboration between the Graduate School of Education and the Institute for Human-Centered AI. It offers co-designed, free AI literacy resources for high school teachers to help students explore, understand, and critique AI.
Location
Stanford, California 94305
Collaborators
- Victor Lee, Associate Professor of Education, Stanford University
- Vanessa Parli, Director of Research Programs, Institute for Human-Centered Artificial Intelligence (HAI), Institute for Human-Centered Artificial Intelligence (HAI)
All Publications
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"What Makes ChatGPT Dangerous is Also What Makes It Special": High-School Student Perspectives on the Integration or Ban of Artificial Intelligence in Educational Contexts
INTERNATIONAL JOURNAL OF TECHNOLOGY IN EDUCATION
2024; 7 (2): 174-199
View details for DOI 10.46328/ijte.651
View details for Web of Science ID 001209255000001
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Engaging elementary students in data science practices
INFORMATION AND LEARNING SCIENCES
2024; 125 (7/8): 513-544
View details for DOI 10.1108/ILS-06-2023-0062
View details for Web of Science ID 001131155700001
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Bop or Flop?: Integrating Music and Data Science in an Elementary Classroom
JOURNAL OF EXPERIMENTAL EDUCATION
2024; 92 (2): 262-286
View details for DOI 10.1080/00220973.2023.2201570
View details for Web of Science ID 000971599400001
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SPOT: A Game-Based Application for Fostering Critical Machine Learning Literacy Among Children
ASSOC COMPUTING MACHINERY. 2023: 507-511
View details for DOI 10.1145/3585088.3593884
View details for Web of Science ID 001103422700051
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Characterizing children’s conceptual knowledge and computational practices in a critical machine learning educational program
International Journal of Child-Computer Interaction
2022
View details for DOI 10.1016/j.ijcci.2022.100541
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Shifting roles and slow research: children's roles in participatory co-design of critical machine learning activities and technologies
BEHAVIOUR & INFORMATION TECHNOLOGY
2024
View details for DOI 10.1080/0144929X.2024.2313147
View details for Web of Science ID 001157649200001
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Supporting Theory Building in Design-Based Research through Large Scale Data-Based Models
17th International Conference on Educational Data Mining
2024: 296-303
View details for DOI 10.5281/zenodo.12729819
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Developing Machine Learning Agency Among Youth: Investigating Youth Critical Use, Examination, and Production of Machine Learning Applications
ASSOC COMPUTING MACHINERY. 2023: 781-784
View details for DOI 10.1145/3585088.3593929
View details for Web of Science ID 001103422700109
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The Design of a Critical Machine Learning Program for Young Learners
ISLS Annual Meeting 2023
2023: 1174-1177
View details for DOI 10.22318/icls2023.684080
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To Ban or Embrace: Students’ Perceptions Towards Adopting Advanced AI Chatbots in Schools
International Conference on Quantitative Ethnography 23
2023: 140-154
View details for DOI 10.1007/978-3-031-47014-1_10
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Connect: A Tool for Collaborative Interview Data Analysis
ISLS Annual Meeting 2023
2023: 2033-2034
View details for DOI 10.22318/icls2023.660710
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Designing with and for Youth: A Participatory Design Research Approach for Critical Machine Learning Education
EDUCATIONAL TECHNOLOGY & SOCIETY
2022; 25 (4): 126-141
View details for Web of Science ID 000886441700010
- Exploring Elementary Teachers' Perceptions of Data Science and Curriculum Design through Professional Development Journal of Technology and Teacher Education 2022; 30: 493-525
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Cognitive, Affective, and Politicized Trust in a Community Youth Program: A Participatory Design Research Project
IEEE. 2021: 269-270
View details for DOI 10.1109/RESPECT51740.2021.9620658
View details for Web of Science ID 000869715300053