Culturally Relevant Computing (CRC) has been shown to have positive effects on students, including increased classroom engagement, increased computing interest, and increased math performance. However, the vast majority of CRC studies take place in primary and secondary education, with little known about its efficacy in higher education. Despite the lack of literature on CRC in higher education, we believe that there may be CRC techniques presently being implemented in this context---yet not published in the research community. To investigate, we interviewed 21 professors from Hispanic Serving Institutions within the Computing Alliance for Hispanic Serving Institutions to document their implementation (if any) of CRC in the higher education context. Professors reported several CRC implementations including, but not limited to, culture in course materials, language-based approaches, providing opportunities outside the classroom, cultural sharing, and professional development. We conclude by discussing how these results may contribute to the promotion of leveraging students' cultures in higher education to serve students---particularly of minoritized backgrounds in computing.

Undergraduate teaching assistants (tutors) are commonly employed in computing courses to help students with programming assignments. Prior research in computing education has reported the benefits of tutoring both for students and for the tutors' own learning. In contrast, recent research that examined actual tutoring sessions has reported that these sessions may be less productive than one might hope, with tutors often just giving students the answers to their problems without trying to teach the underlying concepts. To better understand why tutors may be employing these suboptimal practices, we interviewed ten tutors across early computing courses in higher education to identify their perceived role in these sessions, what stressors and factors influence their ability to perform their job effectively, and what kinds of best practices they learned in their tutor training course. Tutors reported their roles around student learning, gauging student understanding, identifying or providing solutions to students, and providing socioemotional support. They reported their stressors around environmental factors (e.g., number of students waiting to be helped, preparation time, peer-tutor frustrations), internal influences, student behavior, student skill levels, and feeling the need to ''read a student's mind.'' Regarding their tutor training course, Tutors reported learning about interaction guidelines and procedures and question-based problem solving. We conclude by discussing how these results may contribute to the less-effective behaviors seen in prior research and potential ways to improve tutoring in computing courses.

In the United States, culturally relevant computing (CRC) is one of the most popular pedagogical implementations for Latin American (Latine) students. Culturally-relevant learning resources are a valuable tool for implementing CRC. However, the traditional method of creation and maintenance of textbooks takes a significant amount of time and effort. Given the duration required for textbook production, the development of culturally-relevant learning resources may become lengthened, as it requires close attention both on the material and the incorporation of cultural referents. In order to accelerate the process, we used the advancement of large language models (LLMs) to our advantage. Through prompt engineering, we created a series of prompts to produce a textbook for an introductory computer science course (CS1) that incorporates Latine culture. This textbook was evaluated on metrics regarding sensibility, correctness, readability, linguistic approachability, appropriateness of examples, and cultural relevance. Overall, the generated textbook was mainly sensible, correct, readable, and linguistically approachable. Code examples were not always appropriate due to the usage of libraries that are not typically used in a CS1 course. The cultural relevance was apparent, but it often included surface-level cultural referents. The main incorporation of culture was through geographical locations and people's names. This suggests that the use of LLMs to generate textbooks may serve as a valuable first step for writing culturally-relevant learning resources. Though this study focuses on Latines, our results and prompts may be applicable for generating culturally-relevant CS1 textbooks for other cultures.

Though there is a known issue with enrollment disparities across race/ethnicity in computing, U.S. Latin American (Latine) students have remained chronically underrepresented for decades. In order to actively support the recruitment, retention, performance, and experiences of U.S. Latines, we must make sure that we are carrying out studies with this population across outreach practices, interventions, student outcomes, and testimonies. To offer a more comprehensive understanding of the existing body of work on U.S. Latines in computing, we reviewed computing education papers that either fully center around or dedicate specific analyses to U.S. Latines. We analyzed 53 papers and found the following results: most research focuses on Student Experiences and Institutional Perspectives with very few studies on Research Opportunities; the educational setting tended to be K-12 with a severe lack of community college studies; there is a low number of popular pedagogical practices studied with U.S. Latines; research has mainly focused on students, but seldom focused families despite strong Latine connections to family; there was a strong spike in studies in 2021; and the U.S. location of the studies tended to line up with the U.S. Hispanic populations, but many states are under-performing. We discuss the implications of our findings and suggest future research directions to better understand, recruit, and support Latines in computing.

Over the past decades, computer science education (CSEd) research has studied the multitude of factors that may impact student success in introductory programming courses (CS0/CS1). The lack of foundational structure behind how these factors interrelate has made it difficult to gain a thorough understanding of this area of CSEd literature. Gaining a deeper understanding and applying structure to these factors would allow CSEd to adopt better teaching practices, study habits, learning environments, course materials, etc. and to better understand the student experience to better foster success among a broader population of students. Our systematic literature review used search criteria for factors that predicted student success in CS0/CS1, which yielded 311 research articles. We then mapped this body of work under the Biggs' 3P (Presage, Process, Product) educational model, which provides a comprehensive framework for how students engage with learning opportunities. We discovered that although many studies focused on the Presage and Product phases of the model, fewer studies mapped to the Process phase, which describes the students' active learning processes. Our study shows there is a potential gap in the literature and future studies should focus more specifically on how students choose to engage with learning opportunities and what factors may be hindering that engagement throughout a learning period.

Online discussion boards, designed to facilitate learning from peers and instructors in an accessible space, are a vital part of course design, especially in large scale computer science classes. Previous work has shown that women in computer science tend to use anonymity more often than men on these boards, a trend not found in humanities, social science or business courses. In this work, we build on these findings using an intersectional lens, analyzing both gender and race/ethnicity. We find this combined analysis reveals differences in anonymity that are not apparent when examining gender alone. For example, we find a significantly greater difference in anonymity use between Hispanic men and women than would be expected from analyzing race/ethnicity and gender independently. We additionally analyze type of content (e.g., questions, answers), course, platform, and data source to characterize the many factors at play in measuring students’ choice to participate anonymously. In doing so, we show that different approaches used in prior work for eliciting information on gender — whether using registrar data, a survey, or imputing gender based on name — changes how over of students are classified, particularly affecting nonbinary students and Asian students. Understanding when students participate anonymously can help educators and platform designers to make students’ experience of online discussion boards more welcoming.

Prior studies in multilingual computing education have shown that many non-native English speakers (NNES) in India struggle with introductory programming courses as they learn both a programming language (e.g., Java) and a natural language (e.g., English) concurrently. Although multiple studies have been conducted with NNES in India whose first language is Hindi or Tamil, we do not yet know the influence a students' native language may have among Spanish speaking students in the United States. This replication study investigates the effects of an instructional design integrating the students' native language along with English on high school students' learning and engagement in a two week CS0 course using the block-based programming language, Scratch. We designed an experiment to teach introductory computing topics (e.g., algorithms, variables, loops, conditionals) to two groups of students from a rural area spanning multiple institutions in the US. The experimental group was taught using English and Spanish (students' native language) and the control section was taught using only English. A pre-test and post-test was conducted to test students' programming knowledge before and after the course. We also recorded all the questions students asked during the course to measure student engagement. We found that teaching Scratch programming using Spanish and English is no different than teaching Scratch programming using only English to high school students whose native language is Spanish. We also found that the students in the experimental group asked more questions when compared to the control group.

Many institutions use undergraduate teaching assistants (tutors) in their computing courses to help provide more resources to students. Because of the role tutors play in students' learning experiences, recent work in computing education has begun to explore student-tutor interactions through the tutor's perspective and through direct observation of the interactions. The results suggest that these interactions are cognitively challenging for tutors and may not be as beneficial for students' learning as one might hope. Given that many of these interactions may be unproductive, this work seeks to understand how student expectations of these sessions might be impacting the interactions' effectiveness. We interviewed 15 students in a CS2 course to learn about the expectations and desires that students have when they attend tutoring sessions. Our findings indicate that there is variation in what students consider a desired result from the interaction, that assignment deadlines affect students' expectations and desires for interactions, and that students do not always want what they believe is beneficial for their learning. We discuss implications for instructors and potential guidance for students and tutors to make tutoring sessions more effective.

As enrollments in computing courses have surged, the ratio of students to faculty has risen at many institutions. Along with many other large undergraduate programs, our institution has adapted to this challenge by hiring increasing numbers of undergraduate tutors to help students. In early computing courses, their role at our institution is primarily to help students with their programming assignments. Despite our institution offering a training course for tutors, we are concerned about the quality and nature of these student-tutor interactions. As instruction moved online due to COVID-19, this provided the unique opportunity to record all student-tutor interactions (among consenting participants) for research. In order to gain an understanding of the behaviors common in these interactions, we conducted an initial qualitative analysis using open coding followed by a quantitative analysis on those codes. Overall, we found that students are not generally receiving the instruction we might hope or expect from these sessions. Notably, tutors often simply give students the solution to the problem in their code without teaching them about the process of finding and correcting their own errors. These findings highlight the importance of tutoring sessions for learning in introductory courses and motivate remediation to make these sessions more productive.