Reflections of a Diversity, Equity, and Inclusion Working Group based on Data from a National CS Education Program

Ibe, Nwannediya Ada; Howsmon, Rebecca A.; Penney, Lauren; Granor, Nathaniel; DeLyser, Leigh Ann; Wang, Kevin

doi:10.1145/3159450.3159594

Cited by 27 publications

(12 citation statements)

References 12 publications

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“…Third, this article did not consider how teachers select learning resources in the curriculum, and longitudinal research design is suggested to track teaching and learning activities will capture valuable data to support learning analytics and inform future pedagogical development. Finally, diversity and inclusion are important to ensure the success of AI Education [46], [47], further studies should investigate how the curriculum addresses the needs of varied academic abilities and gender differences.…”

Section: Limitations and Future Studiesmentioning

confidence: 99%

Creation and Evaluation of a Pretertiary Artificial Intelligence (AI) Curriculum

et al. 2022

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Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created the first pretertiary AI curriculum at the secondary school level for Hong Kong and evaluated its efficacy. This study added to the AI education community by introducing a new AI curriculum framework. The preposttest multifactors evaluation about students' perceptions of AI learning confirmed that the curriculum is effective in promoting AI learning. The teachers also confirmed the co-creation process enhanced their capacity to implement AI education.Background: AI4Future is a cross-sector project that engages five major partners-CUHK's Faculty of Engineering and Faculty of Education, secondary schools, Hong Kong government, and AI industry. A team of 14 professors collaborated with 17 principals and teachers from six secondary schools to co-create the curriculum.Research Questions: Would the curriculum significantly improve the student perceived competence, attitude, and motivation toward AI learning? How does the co-creation process benefit the implementation of the curriculum?Methodology: The participants were 335 students and eight teachers from the secondary schools. This study adopted a mix-method with quantitative data measures at pre-and postquestionnaires and qualitative data emphasizes teachers' perspectives on the co-creation process. Paired t-tests and ANCOVAs, and thematic analysis were used to analyze the data.Findings: 1) students perceived greater competence and developed a more positive attitude to learn AI and 2) the cocreation process enhanced teachers' knowledge in AI, as well as fostered teachers' autonomy in bringing the subject matter into their classrooms.

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Section: Limitations and Future Studiesmentioning

confidence: 99%

Creation and Evaluation of a Pretertiary Artificial Intelligence (AI) Curriculum

et al. 2022

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“…As the population of the United States continues to diversify, our school systems have been charged with how we can also diversify the pathways and pipelines leading toward STEM and Computer Science (CS) careers. While early equity analyses have focused primarily on gender representation in CS and programming [9,17,27], more recent calls for equity in CS challenge the field to recognize the importance of the intersections between gender and race representations [23,30]. Additionally, there has been a strong push to leverage the cultural affordances of diverse students' positional identities that could plausibly lead to ways of developing transformative and innovative initiatives to broaden participation and success in CS by drawing from social justice paradigms to think about the future of the field at K-12 grade levels [7,37,41].…”

Section: Introductionmentioning

confidence: 99%

Broadening Participation and Success in AP CSA: Predictive Modeling from Three Years of Data

Boda

McGee

2021

Proceedings of the 52nd ACM Technical Symposium on Computer Science Education

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The AP Computer Science A course and exam continually exhibit inequity among over-and under-represented populations. This paper explored three years of AP CS A data in the Chicago Public School district (CPS) from 2016-2019 (N = 561). We analyzed the impact of teacher and student-level variables to determine the extent AP CS A course taking and exam passing differences existed between over-and under-represented populations. Our analyses suggest four prominent findings: (1) CPS, in collaboration with their Research-Practice Partnership (Chicago Alliance for Equity in Computer Science; CAFÉCS), is broadening participation for students taking the AP CS A course; (2) Overand under-represented students took the AP CS A exam at statistically comparable rates, suggesting differential encouragement to take or not take the AP CS A exam was not prevalent among these demographics; (3) After adjusting for teacher and student-level prior experience, there were no significant differences among over-and under-represented racial categorizations in their likelihoods to pass the AP CS A exam, albeit Female students were 3.3 times less likely to pass the exam than Males overall; (4) Taking the Exploring Computer Science course before AP CS A predicted students being 3.5 times more likely to pass the AP CS A exam than students that did not take ECS before AP CS A. Implications are discussed around secondary computer science course sequencing and lines of inquiry to encourage even greater broadening of participation in the AP CS A course and passing of the AP CS A exam.

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“…Therefore, the vast differences between identities, languages, backgrounds, experiences, communities and families, as well as their complex entanglements, should be embraced and shared between students and teachers as they constitute foundational literacies and ways of being (Häggström & Schmidt, 2020). In addition, a focus on literacies makes possible the centring of community members' voices (Cooper, 2020;Ishimaru et al, 2015) and family involvement-central dimensions for students' educational success and well-being (Ireland et al, 2018).…”

Section: Inclusive Learning Environmentsmentioning

confidence: 99%

Working towards more socially just futures: five areas for transdisciplinary literacies research

et al. 2023

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Policy-makers and provincial governments have a responsibility to prioritise equity, diversity, inclusion and accessibility (EDIA) with approaches that leverage both intersectionality and transdisciplinarity, especially when looking at literacies research. Supported by a federally funded knowledge synthesis grant that surveyed the scope of EDIA in Canadian schools, this article focuses on youth marginalisation to address literacies learning. The authors address five concepts from a three-phase literature review to examine inclusive practices that respect, acknowledge and address EDIA in K-12 education. Across reviewed studies, there is an underlying trajectory outlining methodological challenges in implementing EDIA practices. We advance anti-racist and abolitionist approaches by addressing five areas: (1) making learning more accessible by adopting culturally responsive pedagogy informed by local cultures, languages and values; (2) pursuing sustainable professional development in culturally inclusive teaching practices; (3) creating safer school environments that nurture community-driven relationships between parents, students and their teachers; (4) reforming educational policies to concretely address structural racism, discrimination and misrepresentation of socially marginalised students by disrupting what is conceptualised and accepted as ideal culturally responsive pedagogy; and (5) prioritising community perspectives and input curriculum decisions to support underrepresented students. Ultimately, this article echoes this issue's orientations as it explores transdisciplinary practices composing an evolving understanding of literacies.

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Reflections of a Diversity, Equity, and Inclusion Working Group based on Data from a National CS Education Program

Cited by 27 publications

References 12 publications

Creation and Evaluation of a Pretertiary Artificial Intelligence (AI) Curriculum

Creation and Evaluation of a Pretertiary Artificial Intelligence (AI) Curriculum

Broadening Participation and Success in AP CSA: Predictive Modeling from Three Years of Data

Working towards more socially just futures: five areas for transdisciplinary literacies research

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