This study aims to understand the perceptions, attitudes, and preparedness of pre-service teachers towards the use of generative AI technologies in educational settings. This research investigates how future educators view the potential benefits, challenges, and ethical considerations associated with AI-driven tools in their teaching practice. The study employs a mixed-methods approach, combining semi-structured interviews, attitudes surveys, and video recordings of lesson design challenges from pre-service teachers enrolled in a teacher preparation program at a large public midwestern university in the US. Data is collected through detailed interviews and thematic analysis is conducted to identify common themes and insights. Additionally, surveys were administered to capture their general perspective to incorporate AI in their future classrooms. And, analysis of video logs from the pre-service teachers’ AI assisted lesson design provides insights into their skill levels and creativity with generative AI tools. The findings aim to inform teacher education programs and policymakers on how to better prepare educators for the evolving landscape of AI in education.

While computer science is widely recognized as crucial for all U.S. high school students, challenges persist for teachers’ pedagogical content and culturally responsive-sustaining knowledge. In this paper we explore how a co-teaching method shaped three teachers’ understandings of their knowledge while implementing Advanced Placement Computer Science Principle courses. Using a multi-case study methodology, we analyzed semi-structured interviews, pre- and post-surveys for content knowledge, and teachers created artifacts from the three co-teachers to compare their knowledge and experiences. We found that the teachers perceived the co-teaching model as valuable professional development, used pedagogical strategies to fill in content knowledge gaps, and struggled with culturally responsive education. We discuss the implications of these findings for supporting novice CS teachers.

Background: While advocates for integrating Computational Thinking (CT) into existing K12 classrooms have acknowledged and aimed to address various barriers to implementation, we contend that a more foundational issue—tensions between the epistemology of computing and those of existing disciplines—has largely been overlooked. Studies of contact between heterogeneous disciplinary perspectives in both pedagogical and real world professional settings point to other risks, and harms, that educators may need to consider as they attempt to integrate CT into their teaching. As such, designing for integrated CT pedagogies does not simply require addressing functional problems such as teacher professional learning and limited classroom time, but rather implicates complex epistemological navigations.
Objective: This manuscript explores potential epistemic tensions between Computational Thinking (CT) and K12 humanities and arts disciplines and possibilities for their resolution.
Method: Based on a Delphi study with 43 experts from three disciplines—language arts, social studies, and arts—as they engaged in 20 hours of focus group conversations exploring potential approaches to integrating CT these disciplines, analysis focused on identifying potential epistemic tensions that can arise in the context of instruction and directions for their resolution.
Findings: We found 5 epistemic tensions that are explored in detail: contextual reductionism, procedural reductionism, epistemic chauvinism, threats to epistemic identities, and epistemic convergence, as well as a number of potential directions for navigating them.
Implications: The study’s findings provide insights that bear on both scholarship and pedagogical design aimed at promoting substantive interdisciplinary learning with CT, and, critically, navigating potential tensions that can arise within it.

Opinion piece in CACM about equity in CS education influenced by social studies education

Part of my undergrad research in Amy Ko’s Lab

I worked on this project as an undergrad, applying skills from compilers in a computational biology context.

As demand for K-12 computer science (CS) education grows, we argue that most students would be best served by CS classes that not only teach computational thinking/programming, but also chal- lenge them to critically analyze the role of technology in society. One of the main barriers to implementing this in K-12 classrooms is a lack of research on how in-service CS teachers can integrate critical pedagogy into their school context and existing curricula. This poster presents results from a study to co-design lessons with current K-12 CS teachers to integrate critical perspectives into their classrooms. Teacher participants participated in a synchronous pro- fessional learning series in which we taught them critical computing content drawn from relevant books and frameworks. Following this, we collaborated with the teacher participants to design or modify lessons that engage their students in critical analysis, which the participants then implemented in their classrooms. Teachers were encouraged to include content relevant to their students and the communities they are a part of. We conducted thematic analysis of transcripts from the interviews, professional learning series, and co-design sessions. The resulting eight (8) themes demonstrate the challenges and opportunities inherent in integrating critical per- spectives into K-12 computing education. In the long term, results from this work will inform future sociocultural content integration into K-12 CS courses (e.g. “ethics content”).

Why does education need artificial intelligence (AI), and what does AI mean for educational justice? While optimism surrounds the growing use of AI in education, we challenge this uncritical embrace. As yet, education researchers have not fully examined the potential and documented harms AI poses—particularly to minoritized students, their schools, and communities. This presidential session aims to open a research-based dialogue on the risks and potential benefits of AI in education, given what our limited evidence tells us thus far. Framed through a lens of rigorous skepticism, we question whether AI is truly necessary for advancing education or educational justice. We will explore both the well-documented harms from interdisciplinary research and engage in thoughtful speculation about future risks.

With the rise of generative AI tools like chatGPT, the implications for education and the need to prepare teachers for its use have become paramount. This exploratory study delves into teacher education faculty’s perspectives on AI’s role in education, its potential to support teaching and learning, and the importance of fostering critical perspectives and ethical awareness among future educators. The findings underscore the belief among faculty that AI education should be integrated into teacher training that could enhance teaching and learning process. The faculty also believe the importance of equipping teachers to think critically and understand the ethical dimensions of AI.

As demand for K-12 computer science (CS) education grows, we argue that most students would be best served by CS classes that not only teach computational thinking/programming, but also challenge them to critically analyze the role of technology in society. One of the main barriers to implementing this into K-12 classrooms is a lack of research on how in-service CS teachers can integrate critical pedagogy into their school context and existing curricula. This lightning talk presents a proposed method to co-design lessons with current K-12 CS teachers to integrate critical perspectives into their classrooms. Teacher participants will join a synchronous summer professional development where we will teach them critical computing content drawn from relevant books and frameworks, and collaborate with them to design or modify lessons that will engage their students in critical analysis. Teachers will be encouraged to include content relevant to their communities. For example, a teacher in Detroit might teach facial recognition in the context of continued use of the technology by police, despite wrongful arrests. Results from this work will inform future sociocultural content integration into K-12 CS courses (e.g. “ethics content”). Feedback from the audience will be used to improve the methods and literature review of the study.

Archive of a SIGCSE poster about the iCT project. You can see some examples of computational thinking integration in ELA, Arts, and Social Studies.