With growing enrollment in computing, undergraduate teaching assistants (UTAs) play a key role in managing large courses and supporting student learning. Yet, little is known about how UTAs actually teach students. To address this gap, we conducted an ethnographically informed study of seven UTAs at a large public university, observing 37.5 hours of office-hour interactions and conducting three hours of interviews. Our analysis identified six core pedagogical practices: asking open-ended questions, hands-on demonstrating, prompting, referencing resources, explaining, and expressing affect. We use these practices to build a pedagogical model, showing how UTAs adapt in real time to balance efficiency and student independence. Our work can inform UTA training and advance CSEd research by providing a framework for pedagogical decision-making.

Background and Context: While ample research has examined undergraduate students’ participation in Computer Science I (CS1), far less attention has been paid to Computer Science II (CS2) outcomes. Inspired by self-efficacy, Object-Oriented Programming (OOP) and CS2, we expand our understanding of the traditional computer programming curriculum sequence in CS curricula guidelines (CS1, CS2, and data structures and algorithms).

Employers in the tech industry have expectations for students' involvement outside of the classroom. One avenue where students engage with computing communities of practice is student organizations or clubs. Given the lack of empirical studies on students' involvement in clubs in computing, we designed a study that aims to understand computing undergraduate students' participation in clubs and to explore what students get out of their participation in these informal learning environments. We report findings from a multi-institutional survey-based study consisting of 673 undergraduate computing students from three universities in the United States. We found that 41% of the computing students across all years participate in at least one club related to their major. Forty-seven percent of female students participated in a club compared with thirty-eight percent of male students. Through inductive content analysis, we found that students participated in six types of clubs: computing areas, professional societies, affinity groups for underrepresented students, project-based development, Greek organizations, and other types of clubs. Overall, clubs allow students to explore computing areas, develop technical and professional skills, network with industry professionals, prepare for jobs, build a community, meet and socialize with like-minded peers, and gain motivation to sustain in computing. Our work provides empirical insights into computing students' club participation and insights to our community on the importance of types of clubs that can complement students' experiences in formal education supporting students' professional development.

This experience report describes and evaluates the introduction of Hire Thy Gator technical interview preparation activities in a Data Structures and Algorithms (DSA) course. Our intervention included a panel on internship experiences, a role-play interview demonstration, two participatory mock interview preparation exercises where students interviewed each other first using self-selected peers and second through random pair-ups, and graded short programming problems. We (1) explain the logistics and rationale for embedding these activities, (2) describe the lessons learned and evolution of the activities beyond the intervention semester, and (3) evaluate the impact of these activities on students. We report data from 257 students who participated in our intervention and 106 students who were a part of a control group. Students found that our activities promoted awareness of the recruitment process, allowed them to self-evaluate their strengths and weaknesses, and prepared them for technical interviews. Quantitatively, the intervention cohort reported a higher average normalized confidence gain (0.42) than the control group (0.36) indicating that our activities can aid in building students' confidence.

Computing students are expected to contribute to large unfamiliar codebases as they transition from university to industry settings. While computing courses provide students ample opportunities to write code independently or utilize abstract functionalities from standard libraries, students have fewer opportunities to read or extend codebases written by other programmers. This paper presents the logistics, affordances, and empirical evaluation of a novel instructional strategy, Build Programming, which is designed to promote code reading and extension in CS courses. In this strategy, a student (1) solves a programming problem, (2) is assigned a new codebase from a peer who solved the same problem, and (3) is asked to extend the assigned codebase to solve another problem. This allows a student to understand and extend an authentic codebase that is situated in a familiar context. In this paper, we shed light on the logistics of operationalizing this strategy in the context of an undergraduate Data Structures and Algorithms course (N=206). We also describe the affordances of this strategy through student experiences and evaluate the efficacy of one of these affordances, improving code quality through source code analysis. Most students (91%) proposed continuing Build Programming and students' code quality significantly improved after our strategy. Our findings underscore the benefits of Build Programming, and we hope that more instructors incorporate it in CS courses.

Internships provide opportunities for computing students to self-evaluate their interests and develop authentic technical and professional skills that are critical to a career in computing-related industries. However, it is a cause for concern that only 60% of computing students participate in an internship before graduation. Our work aims to identify the factors which are associated with the likelihood of a student's participation in an internship. To identify these factors, we designed a cross-sectional study at a large public university in the United States. 518 computing undergraduate students completed our survey, and we used a quantitative approach to model a student's ability to secure internships. Using a logistic regression model, we found that (1) year in school, (2) household income (a proxy for socioeconomic status), (3) involvement in activities outside the curriculum, and (4) lower identity diffusion scores (i.e., low exploration and low commitment) are significantly associated with a student's participation in an internship. Our findings confirm prior work which showed that factors outside the curriculum are at play for students' internship participation. Further, we add to the computing education research literature the unexplored relationship between computing students' identity formation and participation in internships.

In this paper, we present a bug bounty program that can aid instructors in systematically gathering formative feedback for iterative refinement of their course content. We describe the logistics of implementing the program, explain the types of content in which bugs are reported, elaborate on how students received the program, and evaluate if the program can be effective in improving the course quality. We present data from a large undergraduate Data Structures and Algorithms (DSA) course that was offered consecutively for four semesters. In total, 898 students enrolled in our course, 200 students reported at least one bug, and 373 bugs were reported in total related to incorrect or ambiguous content in instructional material, logistical errors such as broken links, and bugs in short programming problems such as less exhaustive testing. We found that a majority of the students who participated reported a single bug. We also found that the normalized number of bugs reported per student gradually decreased across semesters to almost one-half after two iterations (0.53 bugs reported/student in the first two semesters vs 0.28 bugs reported/student in the last two). This suggests that the program can be effectively used to iteratively refine the course content and improve the learner experience. Students received the program enthusiastically with 97% showing positive or neutral valence on the continuation of the program in future course offerings.

Technical interviews have predominantly been used by companies to recruit students for software-related and other computing jobs. Since the content of the interviews has an overlap with Data Structures and Algorithms (DSA), we introduced a mock interview activity to promote students' awareness of the technical interview process and build students' confidence in problem-solving in a DSA course. In this short paper, we (1) describe the logistics for embedding such an intervention, and (2) explain the affordances and opportunities for improvement of the activity through student perspectives. Students were explained the technical interview process and asked to interview each other twice during the semester on coding problems. Students received the intervention positively describing that the activity helped them to understand the technical interview process, prepared them for future interviews, built their confidence to secure a job, and supported them in knowing their strengths and weaknesses. Opportunities for improving the activity include providing interview questions explicitly, offering an alternate activity for students who are not interested in computing careers, and reducing the length requirement for interviews. Given students' positive reception of the intervention, we recommend that instructors adopt these mock interview exercises in computing courses to improve students' access to professional development opportunities.

Industry internships offer CS students an opportunity to gain authentic disciplinary experiences, evaluate self-interests, and secure future employment. However, little is empirically known about CS students' participation in industry internships and the preparation process used to successfully securing an internship. This paper presents findings from our multi-institutional study aimed at understanding the participation of CS students in industry internships as well as analyzing the differences between students who intern and those who do not. We surveyed 536 CS undergraduate students across three universities in the United States and analyzed the quantitative data using descriptive and inferential statistical methods. We used thematic analysis on the open-ended survey responses. Overall, we found that 40% of students participate in at least one internship. Demographically, equal proportions of males and females interned. However, we observed that students who have higher socioeconomic status were more likely to intern. Academically, there were no significant differences between students who intern and those who do not. However, through thematic analysis, we found differences regarding students' preparation process. Interns explicitly prepared to secure internship positions by practicing interview questions and dedicating time to career preparation. Students who do not intern were less involved in the application process or relied on coursework for securing internships. Quantitative results from the survey corroborated our qualitative findings that factors outside of coursework are influencing students' ability to secure industry internships.

Computing professional identity formation is critical for curriculum decision-making, workforce development, and retaining students in computing degree programs. However, we have limited knowledge of how computing professional identity develops. My research focuses on filling this gap by empirically understanding how undergraduate computing students form their professional identity through their negotiations in formal and informal learning environments. The end goal is to generate and test a theory, grounded in data, which can help Computer Science departments to design interventions for fostering computing professional identity formation.

Academic institutions play a crucial role in the development of students' professional identities. However, we have limited knowledge of how computing professional identity develops. This paper aims to understand how CS undergraduate students develop their professional identity through analyzing students' reflection on their career goals, experiences in CS degree programs, and engagement in professional development. We present findings from qualitative analysis of 14 semi-structured interviews with CS undergraduate students in the United States. We found that CS undergraduates form their computing professional identity typically between Years 2-3 of their degree programs. We identified several reasons students are committed to a computing profession: intrinsic factors (e.g., interest and perception of ability), and discipline-specific factors (e.g. utility and growth). We also found several factors that shape their professional identity: coursework, informal activities like hackathons, and professional development activities including internships and conferences. These findings suggest that the development of computing professional identity is not limited to students' involvement in the academic degree programs but the engagement they have with the broader computing community.

Internships play a crucial role in helping CS undergraduate students to commit to CS degrees and computing careers. Internships also promote students' personal and professional growth. Studies have also shown that pursuing an internship is positively correlated with an improved chance of getting a full-time job offer and a higher starting salary. However, previous research has shown that only 52.1% of undergraduate students pursue an internship before they graduate. In this poster, we present findings from a cross-sectional study focused on understanding the characteristics of CS undergraduate students who have interned at one or more companies and those who have not interned. We surveyed 97 and interviewed 14 CS undergraduates. We found that 41.2% of 97 students participated in one or more internships. The key characteristics that distinguish students who successfully interned and those who did not were: 1) 95% students who interned had career goals - either to join industry or pursue graduate school after they graduate. In contrast, 21% of the students who did not intern were unsure or confused about their career goals; 2) students who interned were more likely to have participated in an undergraduate research experience or a student organization; 3) students who interned intentionally prepared for interviews, while those who did not intern were not actively preparing, not confident enough to apply, or were unsuccessful in the interview process because of lack of preparation. This poster provides insight into CS students' competitiveness for securing internships and for developing programs to support professional development.

Professional development is critical for preparing undergraduate CS students for their future careers. Industry internships offer students pathways for professional development. However, little is empirically known about the impact industry-based internships have on CS students' career paths as well as the effectiveness of CS degree programs in preparing students for these professional development opportunities. In this paper, we present a thematic analysis of open-ended survey responses of 40 CS undergraduate students in the US who participated in an internship. This study aimed to understand the impact that professional internships have on: CS students' career goals, students' perceptions of the gaps between academia and industry, and students' strategies for professional success. We found four themes that describe the impact of internships on CS students. Internships (1) strengthened students' commitment to CS degrees and careers; (2) encouraged exploration of CS careers and industries; (3) promoted personal/professional growth; and (4) developed awareness of professional expectations. We also analyzed students' perception of the curriculum's effectiveness and found that students were strategically working to improve their technical skills outside of coursework to secure employment. These findings have the potential to retain students in computing and reduce the gaps between academia and industry, thereby increasing CS students' competitiveness in the workforce.

This working group contributes to formulating a framework for modeling competencies in the current and future disciplines that comprise computing education. We draw upon the innovative approach taken in the curricular document for information technology (IT2017), curricular competency frameworks, other related documents such as the software engineering competency model (SWECOM), the Skills Framework for the Information Age (SFIA), current research in competency models, and elicitation workshop results from other computing conferences. The outcomes contribute to the Computing Curricula 2020 (CC2020) project, and include the formulation and review of sets of disciplinary-relevant competencies for use in computing education. This work directly informs the CC2020 project sponsored by the Association for Computing Machinery (ACM) and the IEEE Computer Society.

Understanding undergraduate students’ academic, professional and social experiences in computer science (CS) degree programs is critical to retaining students in these programs. This paper presents findings from an exploratory study aimed at empirically investigating the academic, social, and professional experiences that influence CS students to consider switching out of their major. We surveyed 96 CS undergraduate students at the University of Florida and examined their experiences during their degree program. The data were categorically analyzed to identify factors that influenced students to consider switching out of a CS major. We found that students who considered switching out of a CS major experienced gender biases in the classroom, had negative or neutral satisfaction with computing courses, and felt that the assignments and projects were not relevant to the coursework. We also found that females were twice as likely to consider leaving a CS major as compared to males. Several factors significantly affected female students: perception of the presence of gender biases in the classroom, not receiving timely feedback, negative satisfaction in coursework, and negative team experiences. We conclude by discussing these findings in light of retention theories and literature.

Virtual humans are used to facilitate interactions in sensitive contexts such as healthcare. In such contexts, trust in the information source plays an important role in reception of the information. Prior work has shown that physical appearance affects trustworthiness in human-human interactions; therefore, we examined the effect of virtual human's appearance on users' trust. We ran a between-users study with 12 adult participants, who watched a video of a virtual human with professional attire (e.g., lab coat) or with general attire (e.g., button-down shirt). We examined the duration of eye fixation on the virtual human's face along with participants' self-reported trust levels. We found that there was no statistical difference in eye contact or trust between the two test conditions.

Understanding the development of professional identity in Computer Science (CS) undergraduate students can help better evaluate CS degree program's effectiveness in preparing students for their career goals. This poster presents findings from a study where we surveyed 105 CS undergraduate students about their self-perceptions of technical competencies in their chosen CS professions, the mechanisms to develop their competencies, as well as their motivations behind attaining these skill sets. Preliminary analysis of this data indicates that most CS students (93.3%), identified themselves into 7 different computing professions including Software Engineering (81.0%), Web Development (37.1%), User Experience (19.0%), and Computer Security (12.4%). They indicated using multiple mechanisms to develop their technical competencies including coursework, internship/professional experience, and research. Motivations behind their learning included self-interest as well as industry demands. We analyzed the relationships between students' skill proficiencies, motivations, and mechanisms for learning and found differences between novice, intermediate, and advanced learners. We found that students who self-assessed their proficiencies as novices in their chosen professional identity had a single mechanism for learning, most commonly coursework preparation. On the other hand, students who rated themselves as intermediate or advanced learners had multiple mechanisms and motivational factors behind attaining their skill set. These findings are important for better understanding students' learning needs and career aspirations. CS departments can use this information for better aligning their degree programs to student goals and creating pathways that ensure the development of CS students professional identity.

Understanding professional goals and identities of undergraduate Computer Science (CS) students is critical for curriculum decisions, workforce development, and retention programs. This paper aims to explore the ways in which undergraduate CS students describe their professional goals and identities, and gauge how these goals and identities vary across gender and academic standing. This paper is part of a larger study aimed at understanding how students form their professional goals and identities. In the study presented in this paper, we surveyed 109 CS undergraduate students and interviewed 14 CS undergraduate students across gender and academic standing. The data were qualitatively analyzed using inductive coding and thematic analysis. Our findings indicate that most students identify themselves professionally as software development professionals, various specialized CS professionals, and by their majors. We also found that both male and female students were interested in becoming entrepreneurs, and females were more likely to have professional goals to move into management. This paper contributes to the fields' growing knowledge of undergraduate students' professional goals and professional identities. This knowledge can help CS departments to better align their degree programs, curriculum, and specialization tracks with student goals. Such an alignment has the potential to increase retention in the major as well as prepare students to be competitive in the workforce.

Block-based programming environments have increased students' interest in computer science (CS). Research suggests that block-based programming environments have positively impacted students' retention, effectiveness, efficiency, engagement, attitudes, and perceptions towards computing. We know that when novice programmers are learning to program in block-based programming environments, they need to understand the components of these environments, how to apply programming concepts, and how to create artifacts. However, few studies have been done to understand the impacts that usability of block-based programming environments may have on students' programming. In this poster, we present results from a two-part study designed to understand the impact that usability of the programming environment has on novice programmers when learning to program in Scratch. Our findings indicate that usability challenges may affect students' ability to navigate and create programs within block-based programming environments.