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arxiv logo>cs> arXiv:2312.04839
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Computer Science > Human-Computer Interaction

arXiv:2312.04839 (cs)
[Submitted on 8 Dec 2023]

Title:Understanding Teacher Perspectives and Experiences after Deployment of AI Literacy Curriculum in Middle-school Classrooms

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Abstract:Artificial Intelligence (AI) and its associated applications are ubiquitous in today's world, making it imperative that students and their teachers understand how it works and the ramifications arising from its usage. In this study, we investigate the experiences of seven teachers following their implementation of modules from the MIT RAICA (Responsible AI for Computational Action) curriculum. Through semi-structured interviews, we investigated their instructional strategies as they engaged with the AI curriculum in their classroom, how their teaching and learning beliefs about AI evolved with the curriculum as well as how those beliefs impacted their implementation of the curriculum. Our analysis suggests that the AI modules not only expanded our teachers' knowledge in the field, but also prompted them to recognize its daily applications and their ethical and societal implications, so that they could better engage with the content they deliver to students. Teachers were able to leverage their own interdisciplinary backgrounds to creatively introduce foundational AI topics to students to maximize engagement and playful learning. Our teachers advocated their need for better external support when navigating technological resources, additional time for preparation given the novelty of the curriculum, more flexibility within curriculum timelines, and additional accommodations for students of determination. Our findings provide valuable insights for enhancing future iterations of AI literacy curricula and teacher professional development (PD) resources.
Comments:Published at 16th annual International Conference of Education, Research and Innovation (ICERI) 2023
Subjects:Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
Cite as:arXiv:2312.04839 [cs.HC]
 (orarXiv:2312.04839v1 [cs.HC] for this version)
 https://doi.org/10.48550/arXiv.2312.04839
arXiv-issued DOI via DataCite
Journal reference:ICERI2023 Proceedings, pp. 6875-6884
Related DOI:https://doi.org/10.21125/iceri.2023.1716
DOI(s) linking to related resources

Submission history

From: Prerna Ravi [view email]
[v1] Fri, 8 Dec 2023 05:36:16 UTC (178 KB)
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