Supporting AI Literacy Teaching Through the Development of Assessments for Classroom Use
John Masla, Christina Bosch, Prerna Ravi, Lydia Guterman, Sarah Wharton, Mary Cate Gustafson-Quiett, Samar Abu Hegly, Calvin Macatantan
Abstract
Initial discussion of AI literacy assessment has focused on competency frameworks and learning standards rather than materials for classroom use. Responsible AI for Computational Action (RAICA), a constructionist AI curriculum for middle and high school students, includes assessment materials to support teachers with the evaluation of student AI literacy competencies in their classrooms. These materials include exit tickets used as formative assessments at the end of each lesson and both teacher and student-facing rubrics. After beta-testing a module of the curriculum with nine teachers and 282 students, we reviewed teacher usage data and feedback as well as student responses. The review process surfaced a number of improvements to the materials to better align them with classroom teaching practice. These included clarifying language and adding visual scaffolds. We present the assessment materials and iterative design process used to bridge the gap between the theoretical AI literacy competencies and their practical implementation in classrooms.
BibTeX
@article{Masla_Bosch_Ravi_Guterman_Wharton_Gustafson-Quiett_Abu Hegly_Macatantan_Klopfer_Breazeal_Abelson_2025, title={Supporting AI Literacy Teaching Through the Development of Assessments for Classroom Use}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/35191}, DOI={10.1609/aaai.v39i28.35191}, abstractNote={Initial discussion of AI literacy assessment has focused on competency frameworks and learning standards rather than materials for classroom use. Responsible AI for Computational Action (RAICA), a constructionist AI curriculum for middle and high school students, includes assessment materials to support teachers with the evaluation of student AI literacy competencies in their classrooms. These materials include exit tickets used as formative assessments at the end of each lesson and both teacher and student-facing rubrics. After beta-testing a module of the curriculum with nine teachers and 282 students, we reviewed teacher usage data and feedback as well as student responses. The review process surfaced a number of improvements to the materials to better align them with classroom teaching practice. These included clarifying language and adding visual scaffolds. We present the assessment materials and iterative design process used to bridge the gap between the theoretical AI literacy competencies and their practical implementation in classrooms.}, number={28}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Masla, John and Bosch, Christina and Ravi, Prerna and Guterman, Lydia and Wharton, Sarah and Gustafson-Quiett, Mary Cate and Abu Hegly, Samar and Macatantan, Calvin and Klopfer, Eric and Breazeal, Cynthia and Abelson, Hal}, year={2025}, month={Apr.}, pages={29178-29185} }