As efforts to broaden participation in computing continue to grow, culturally responsive pedagogy (CRP) has become an increasingly important framework for promoting access and inclusion in computer science (CS) and computational thinking (CT) education.While CRP has been extensively theorized in general education [1], its application in computing education is still evolving [2,3].However, no comprehensive synthesis currently exists that maps how CRP has been conceptualized, implemented, and studied across CS and CT educational contexts.This poster presents an innovative methodological approach that uses natural language processing (NLP) and topic modeling to systematically synthesize the scholarly landscape of culturally responsive pedagogy in computing education.We assembled a corpus of 109 peer-reviewed articles published between 2010 and 2024, including empirical studies, theoretical papers, and curricular reports addressing CRP-related issues in K-12 and undergraduate computing education.Using a multi-step preprocessing pipeline with SpaCy [4], we tokenized, lemmatized, and cleaned the text to prepare it for analysis.We then applied two complementary topic modeling techniques: BERTopic [5], an embedding-based model that identifies semantically coherent topic clusters, and windowed Latent Dirichlet Allocation (LDA) [6], applied separately across publication years to track thematic shifts over time.We chose to utilize both models to assess their efficacy in identifying nuanced thematic patterns and temporal dynamics.Our analysis revealed several key themes in the literature, including equity and inclusion, culturally responsive pedagogy, teacher identity development, technological tools, and implementation challenges.Both the BERTopic and LDA model results highlighted an increase in research attention to equity and identity-related topics after 2020, aligning with broader societal calls for justice-centered computing education [3].However, notable gaps remain: relatively few studies address CRP in K-8 or rural computing education, and

Self-efficacy is important for success in computing courses, but best practices for how computing instructors can support students' self-efficacy development are still a matter of ongoing development. CS students' judgments about their own abilities are often very self-critical and disagree with the ways that experts in CS would measure competency. Self-assessment scaffolding has been observed to improve learning outcomes and self-efficacy in various domains. However, these practices are not well known in CS education research, and there is a lack of empirically-based guidance about how to implement them. This project is devoted to developing a self-assessment scaffolding intervention for CS1 that is effective, efficient to implement, and usable for students. Improving pedagogical practices in introductory courses (CS1) will help improve the outcomes for everyone, but approaches targeting self-efficacy may particularly benefit students from minoritized groups in CS, such as women and students of color.

Educational stakeholders want to understand and overcome the well-documented racial and gender disparities within computer science education. There are many factors that influence students’ participation, performance, and persistence in CS courses, including motivational and affective factors. Prior research in CS education has documented the influence of these factors on students’ CS outcomes generally, and on URM students in particular. What has been less investigated, is how students’ motivational and affective experiences in CS develop and evolve from moment to moment, particularly for URM students. To better understand how these experiences develop, this paper presents the results of a study using intensive longitudinal methods which examined the differences in momentary experiences between racially underrepresented students and their represented peers in undergraduate introductory computer science courses. Using the Experience Sampling Method (ESM), we solicited responses on students’ momentary self-efficacy, interest, and affective experiences 8-18 times in each of two semesters from a total of 110 CS students, of which 19 identified as racially underrepresented.

There are significant participation gaps in computing, and the way to address these participation gaps lies not simply in getting students from underrepresented groups into a CS1 classroom, but supporting students to pursue their interest in computing further beyond CS1. There are many factors that may influence students’ pursuit of computing beyond introductory courses, including their sense that they can do what CS courses require of them (their self-efficacy) and positive emotional experiences in CS courses. When interest has been addressed in computing education, research has treated it mostly as an outcome of particular pedagogical approaches or curricula; what has not been studied is how students’ longer-term interest develops through more granular experiences that students have as they begin to engage with computing. In this paper, we present the results of a study designed to investigate how students’ interest in computing develops as a product of their momentary self-efficacy and affective experiences. Using a methodology that is relatively uncommon to computer science education—the experience sampling method, which involves frequently asking students brief, unobtrusive questions about their experiences—we surveyed CS1 students every week over the course of a semester to capture the nuances of their experiences. 74 CS1 students responded 14-18 times over the course of a semester about their self-efficacy, frustration, and situational interest. With this data, we used a multivariate, multi-level statistical model that allowed us to estimate how students’ granular, momentary experiences (measured through the experience sampling method surveys) and initial interest, self-efficacy, and self-reported gender (measured through traditional surveys) relate to their longer-term interest and achievement in the course. We found that students’ momentary experiences have a significant impact on their interest in computing and course outcomes, even controlling for the self-efficacy and interest students reported at the beginning of the semester. We also found significant gender differences in students’ momentary experiences, however, these were reduced substantially when students’ self-efficacy was added to the model, suggesting that gender gaps could instead be self-efficacy gaps. These results suggest that students’ momentary experiences in CS1, how they experience the course week to week, have an impact on their longer-term interest and learning outcomes. Furthermore, we found that male and female students reported different experiences, suggesting that improving the CS1 experiences that students have could help to close gender-related participation gaps. In all, this study shows that the granular experiences students have in CS1 matter for key outcomes of interest to computing education researchers and educators and that the experience sampling method, more common in fields adjacent to computer science education, provides one way for researchers to integrate the experiences students have into our accounts of why students become interested in computing.

While computer science (CS) education researchers have frequently examined what happens in courses, programs of study, or occupations in general, they have less frequently addressed finer-grained experiences that spark students' interest in CS. One excellent way to study these types of student experiences is the Experience Sampling Method (ESM). ESM involves collecting data on individuals' experiences at much more frequent intervals than traditional survey research. This aspect of ESM makes it well-suited to examine time-specific aspects of students' experiences, as well as changes due to the disruptive effects of COVID-19.

Around the United States, educators are teaching new computer science (CS) education standards, including in Tennessee, which announced its first K-8 CS standards in 2018. In Tennessee, the standards are now the official guidelines for CS education at the K-8 level, what barriers prevent CS teaching and learning to become a reality, especially for elementary and middle grades teachers, are unknown. We developed and administered a needs survey for K-8 teachers regarding CS education as a part of a broader community-engaged project. From 251 K-8 teachers' responses, we found that CS is important to them, but there are barriers to meeting the standards. Qualitative items about needs and barriers related to CS education teachers revealed a demand for professional development and training opportunities for teachers to learn about both the technical aspects of computing education and embedding computing ideas across the K-8 curriculum. We will discuss the implications of these findings and will describe how these results will enable our efforts to provide professional learning opportunities for educators.

This lightning talk describes a new grant-funded research project investigating how undergraduate computer science students' interest in CS develops. The goal of this project is to investigate how sustained, individual interest develops from finer-grained experiences of situational interest that students have in introductory CS courses. This project will accomplish this goal using the experience sampling method (Hektner, Schmidt, & Csikszentmihalyi, 2007), which is a longitudinal research method that asks participants to report on their immediate experiences at many occasions. Prior research has not adequately investigated what drives individual differences in CS interest at the level at which policymakers and educators can most effectively act, namely, at a situation-to-situation level, rather than in terms of what happens in courses, programs of study, or occupations in general and overall. Moreover, research has shown that some overall factors, such as competence-related beliefs and co-curricular supports, might be related to the development of sustained interest in CS (e.g., Lishinski, Yadav, Good, & Enbody, 2016). Thus, we will explore how students' initial interest, as well as their individual motivational characteristics, such as CS self-concept, and CS self-efficacy, relate to interest at a situation-to-situation level. Furthermore, we will also explore how contextual factors - those internal to students, such as how challenging they found the activities, as well as those external to students, such as the focus of each class - relate to students' situational interest. Overall, we hope to better understand how students' situational interest relates to changes in their longer-term, individual interest.

The entire enterprise of computer science education is predicated on the ability to develop and sustain students' interest in the subject. Given how fundamental this aspect of the educational process is, our understanding of what experiences are actually driving the development of interest in computer science remains far from complete. This BOF session seeks to inform the direction of a new research project dedicated to investigating this question, by eliciting a discussion from expert practitioners about what they know from their experiences about how interest in CS develops.