Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubbles
The nascent digital footprints of adolescents make them particularly susceptible to being misrepresented by AI systems. We design, implement, and evaluate two educational modules on the causes and consequences of two particularly salient types of AI misrepresentation: algorithmic biases and filter b...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Computers and Education: Artificial Intelligence |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666920X25000657 |
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| author | Mehtab Iqbal Khushbu Singh Sushmita Khan Oluwafemi Osho Emily Sidnam-Mauch Nicole Bannister Kelly Caine Bart Knijnenburg |
| author_facet | Mehtab Iqbal Khushbu Singh Sushmita Khan Oluwafemi Osho Emily Sidnam-Mauch Nicole Bannister Kelly Caine Bart Knijnenburg |
| author_sort | Mehtab Iqbal |
| collection | DOAJ |
| description | The nascent digital footprints of adolescents make them particularly susceptible to being misrepresented by AI systems. We design, implement, and evaluate two educational modules on the causes and consequences of two particularly salient types of AI misrepresentation: algorithmic biases and filter bubbles. We implement these modules in middle school math and computer science classrooms by integrating our materials with the existing curricula and curricular requirements of the partner school. This integration, as well as the many confounding factors of the classroom, are nontrivial problems that have heretofore not been considered in privacy education research and required us to adopt methodologies from learning sciences, particularly design-based research and backward design. Quantitative results of the pre-/post-test and qualitative assessments of open-ended questions find that students were engaged with the materials and exhibited substantial learning gains. The findings emphasize the need for tailored educational interventions and avenues for future research to address AI-related challenges. |
| format | Article |
| id | doaj-art-5ddf7d26948949e491bbb464734839a2 |
| institution | OA Journals |
| issn | 2666-920X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computers and Education: Artificial Intelligence |
| spelling | doaj-art-5ddf7d26948949e491bbb464734839a22025-08-20T02:06:00ZengElsevierComputers and Education: Artificial Intelligence2666-920X2025-06-01810042510.1016/j.caeai.2025.100425Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubblesMehtab Iqbal0Khushbu Singh1Sushmita Khan2Oluwafemi Osho3Emily Sidnam-Mauch4Nicole Bannister5Kelly Caine6Bart Knijnenburg7School of Computing, Clemson University, Clemson, SC, USA; Corresponding author.College of Education, Clemson University, Clemson, SC, USASchool of Computing, Clemson University, Clemson, SC, USASchool of Computing, Clemson University, Clemson, SC, USASchool of Computing, Clemson University, Clemson, SC, USACollege of Education, Clemson University, Clemson, SC, USASchool of Computing, Clemson University, Clemson, SC, USASchool of Computing, Clemson University, Clemson, SC, USAThe nascent digital footprints of adolescents make them particularly susceptible to being misrepresented by AI systems. We design, implement, and evaluate two educational modules on the causes and consequences of two particularly salient types of AI misrepresentation: algorithmic biases and filter bubbles. We implement these modules in middle school math and computer science classrooms by integrating our materials with the existing curricula and curricular requirements of the partner school. This integration, as well as the many confounding factors of the classroom, are nontrivial problems that have heretofore not been considered in privacy education research and required us to adopt methodologies from learning sciences, particularly design-based research and backward design. Quantitative results of the pre-/post-test and qualitative assessments of open-ended questions find that students were engaged with the materials and exhibited substantial learning gains. The findings emphasize the need for tailored educational interventions and avenues for future research to address AI-related challenges.http://www.sciencedirect.com/science/article/pii/S2666920X25000657 |
| spellingShingle | Mehtab Iqbal Khushbu Singh Sushmita Khan Oluwafemi Osho Emily Sidnam-Mauch Nicole Bannister Kelly Caine Bart Knijnenburg Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubbles Computers and Education: Artificial Intelligence |
| title | Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubbles |
| title_full | Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubbles |
| title_fullStr | Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubbles |
| title_full_unstemmed | Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubbles |
| title_short | Teaching AI awareness in middle school classrooms: Design, implementation and evaluation of two education modules on algorithmic bias and filter bubbles |
| title_sort | teaching ai awareness in middle school classrooms design implementation and evaluation of two education modules on algorithmic bias and filter bubbles |
| url | http://www.sciencedirect.com/science/article/pii/S2666920X25000657 |
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