Ibrahim Oluwajoba Adisa
Biographic Data
| ID | 9510413 |
|---|---|
| NAME | Ibrahim Oluwajoba Adisa |
| GIVEN NAMES | Ibrahim Oluwajoba |
| FAMILY NAME | Adisa |
| SIGNATURE | ADISA I O |
| AFFILIATIONS | Stanford University |
| ORCID | 0000-0003-1657-2030 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
“It can not only just predict your future; it can also change it”
Background While children interact with AI applications, they are not often given opportunities to develop a sociotechnical understanding of machine learning systems. Research is needed to understand how children make sense of AI, including algorithmic bias. We draw on sociocultural perspectives to examine how two children, aged 10 and 11, used symbolic and material tools to critique issues of bias and create personally valuable machine learning …
Investigating elementary students’ experiences and perspectives with data science education
This study investigates how elementary students experience and perceive data science instruction in interest-driven and contextually relevant learning environments. We focused on fourth- and fifth-grade students (ages 8–11) who participated in data science units co-developed by educators and researchers over two years. Drawing on qualitative data from 214 students in a rural STEM-focused elementary school, we examined how students engaged with da…
Shifting roles and slow research
Including children’s voices in the design of learning activities and technologies has increasingly become a subject of conversation among researchers and learning designers. Research suggests children have lived experiences that position them as useful contributors in co-designing curricula activities or technologies they will use. However, one significant challenge in participatory co-design is engaging children in the co-design of curricula whe…
Middle school students’ perspectives on adopting generative AI in K-12 education
This qualitative study explores middle school students’ perspectives on the adoption of GenAI for learning. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) and competence and control beliefs framework, we explored how contextual and psychological factors influence students’ perspectives on AI use for schoolwork. Participants included 13 middle school students who participated in a 10-week AI literacy program. Using quali…
Teaching high school students about generative AI
Teachers who wish to enact lessons about generative AI are required to simultaneously learn about it and develop curricula with activities that align with their discipline. We present two cases of high school teachers, June and Margot, who had different prior experiences, resources, and learning goals related to GenAI instruction. We found that they designed lessons that positioned GenAI as an object-of-study or subject-specific, but neither less…
Opening the ‘Can of Worms’
Educators hold diverse beliefs and attitudes about generative artificial intelligence (AI). Irrespective of their stance, many acknowledge AI's growing influence and the pressing need for greater AI literacy. In this case study, we draw on Davis's (1989) technology acceptance model (TAM) to examine how two English teachers, Fiona and Margot, arrived at different enactments of AI literacy. Using qualitative methods, we found that Fiona was primari…
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Shifting roles and slow research
Including children’s voices in the design of learning activities and technologies has increasingly become a subject of conversation among researchers and learning designers. Research suggests children have lived experiences that position them as useful contributors in co-designing curricula activities or technologies they will use. However, one significant challenge in participatory co-design is engaging children in the co-design of curricula whe…
Middle school students’ perspectives on adopting generative AI in K-12 education
This qualitative study explores middle school students’ perspectives on the adoption of GenAI for learning. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) and competence and control beliefs framework, we explored how contextual and psychological factors influence students’ perspectives on AI use for schoolwork. Participants included 13 middle school students who participated in a 10-week AI literacy program. Using quali…
Teaching high school students about generative AI
Teachers who wish to enact lessons about generative AI are required to simultaneously learn about it and develop curricula with activities that align with their discipline. We present two cases of high school teachers, June and Margot, who had different prior experiences, resources, and learning goals related to GenAI instruction. We found that they designed lessons that positioned GenAI as an object-of-study or subject-specific, but neither less…
Opening the ‘Can of Worms’
Educators hold diverse beliefs and attitudes about generative artificial intelligence (AI). Irrespective of their stance, many acknowledge AI's growing influence and the pressing need for greater AI literacy. In this case study, we draw on Davis's (1989) technology acceptance model (TAM) to examine how two English teachers, Fiona and Margot, arrived at different enactments of AI literacy. Using qualitative methods, we found that Fiona was primari…
“It can not only just predict your future; it can also change it”
Background While children interact with AI applications, they are not often given opportunities to develop a sociotechnical understanding of machine learning systems. Research is needed to understand how children make sense of AI, including algorithmic bias. We draw on sociocultural perspectives to examine how two children, aged 10 and 11, used symbolic and material tools to critique issues of bias and create personally valuable machine learning …
Investigating elementary students’ experiences and perspectives with data science education
This study investigates how elementary students experience and perceive data science instruction in interest-driven and contextually relevant learning environments. We focused on fourth- and fifth-grade students (ages 8–11) who participated in data science units co-developed by educators and researchers over two years. Drawing on qualitative data from 214 students in a rural STEM-focused elementary school, we examined how students engaged with da…
Pedagogy (4 works) · Psychology (4 works) · Teaching and Learning Programming (4 works) · Artificial Intelligence (3 works) · Artificial Intelligence (3 works) · Computer Science (3 works) · Educational Games and Gamification (3 works) · Mathematics education (3 works) · Online Learning and Analytics (3 works) · Curriculum (2 works)