Hidden curriculum plays a significant, yet often overlooked, role in shaping students' experiences, expectations, identities, and professional development (PD) in computing education. As computing programs continue to evolve in response to emerging technologies--i.e., artificial intelligence (AI), and changing industry expectations, understanding the implicit structures that influence student success becomes increasingly important. Students are increasingly expected to navigate collaboration, communication, co-curricular experiences (e.g., internships, research, etc.), and the use of technological tools. These expectations are rarely uncovered and made explicit within formal curricula.

As computing cohorts grow in scale, designing assessments that foster communication, collaboration, and meaningful learning becomes increasingly challenging. This lightning talk shares a pedagogical strategy implemented in a large-scale (over 300 students) software design and engineering course at a Southeastern university in the United States. In this iteration, teams of computer science (CS) students created two video-recorded podcast chapters, each 30 to 60 minutes long, as part of a conceptual assessment. Each chapter focused on a key topic in software design and engineering, one on three design patterns (e.g., the Factory Method Pattern) and another on code smells, refactoring, and test-driven development. Podcasts, now widely popular across streaming platforms, offered students an accessible and creative medium to communicate technical concepts while practicing professional collaboration. The team-based format aimed to promote interaction, reinforce conceptual understanding, and develop communication skills as all members planned, scripted, and discussed each episode together. Rather than focusing only on outcomes, this activity emphasized process and reflection as students explained, questioned, and built on one another's ideas. This lightning talk is presented to gather feedback from the computing education community on this instructional strategy and possibly collaborate on further extensive research on student-created artifacts in large-scale CS courses.

As artificial intelligence (AI) tools like ChatGPT become more common, their role in computer science (CS) education continues to evolve, especially in large courses with time-limited assessments. This lightning talk presents an observation from a large-scale (over 300 students) introductory software design and engineering course at a university in the Southeastern United States. During a 30-minute, open-notes assessment where students were allowed to use generative AI, they were asked to extend one user story in an existing codebase they had previously built for the course. The task followed an all-or-nothing grading approach that required a fully functional user story implementation for credit. Although students often support using AI for learning, their reactions revealed a gap between what they expected AI to do and the actual thinking required to solve real problems quickly: Some students even expressed frustration, noting that AI tools offered little help under time pressure. To close the experience, we held a reflection lecture where students analyzed the role of AI as a tool and discussed its purpose in supporting augmented intelligence rather than replacing human reasoning. This case illustrates how assessment design can expose the limits of generative AI as a learning aid and highlights the importance of helping students build awareness of time, effort, and reflection when using these tools. The goal of this talk is to share these insights, invite discussion on AI use under time constraints, and explore how students adapt or resist adapting when AI cannot ''think fast enough'' for them.

Active learning has been found to increase student performance, particularly in science, technology, engineering, and mathematics (STEM) disciplines [2].However, adopting active learning in large courses is challenging, especially in scenarios involving hundreds of students in the same classroom.The larger the class, the more challenging it is to navigate and support students' critical thinking skills and study habits.This limits effective follow-ups on students' learning processes and forces instruction to rely heavily on automated methods based on standardized summative assessments and strategies that focus arguably more on grading than learning [1,3].Due to the current scale of large courses in computer science and the ease of access required, instructors are asked to rely on methods that are easy to design and implement, one being the use of study sheets to support student preparation for tests.This poster reports preliminary findings from a strategy that required students to create study sheets for an in-class test in an introductory software engineering course.A total of 372 students from four separate large sections (70+ students) voluntarily reported on their work for this strategy.Two sections were asked to submit two study sheets in two separate assignments that counted as half of their evaluation grade, both submitted within a week of each other.The remaining sections worked on study cheats (encouraged but ungraded) without required submission.We report preliminary findings that suggest significant differences between both modalities when gender is considered concerning students' perceived performance and dedication to the study sheet creation.We report on students' perceived performance and self-reported dedication, considering 368 responses: our analysis considered a gendered classification between male and female students.Four students were not considered due to the small subgroup sample.We found no significant differences between the two groups when analyzing them as a whole.Nonetheless, we observed significant differences in students' perceived performance and selfreported dedication regarding the first and second cheat sheets when comparing students' genders.Particularly, female students who were not asked to submit their study sheets reported the highest rates of perceived performance

Virtual humans (i.e., embodied conversational agents) have the potential to support college students’ mental health, particularly in Science, Technology, Engineering, and Mathematics (STEM) fields where students are at a heightened risk of mental disorders such as anxiety and depression. A comprehensive understanding of students, considering their cultural characteristics, experiences, and expectations, is crucial for creating timely and effective virtual human interventions. To this end, we conducted a user study with 481 computer science students from a major university in North America, exploring how they co-designed virtual humans to support mental health conversations for students similar to them . Our findings suggest that computer science students who engage in co-design processes of virtual humans tend to create agents that closely resemble them demographically—agent-designer demographic similarity. Key factors influencing virtual human design included age, gender, ethnicity, and the matching between appearance and voice. We also observed that the demographic characteristics of virtual human designers, especially ethnicity and gender, tend to be associated with those of the virtual humans they designed. Finally, we provide insights concerning the impact of user-designer demographic similarity in virtual humans’ effectiveness in promoting mental health conversations when designers’ characteristics are shared explicitly or implicitly. Understanding how virtual humans’ characteristics serve users’ experiences in mental wellness conversations and the similarity-attraction effects between agents, users, and designers may help tailor virtual humans’ design to enhance their acceptance and increase their counseling effectiveness.

This research paper explores the prevalence of the Impostor Phenomenon (IP) among undergraduate college students in computer science (CS) courses, addressing its variations concerning different student demographics such as gender, ethnicity, and institutional background. We surveyed 502 students from two Southeastern U.S. institutions-one in Georgia and one in Florida-using the Clance Impostor Phenomenon Scale (CIPS). We found that 63% of our participants reported experiencing IP, with higher rates among female students (68%) compared to males (62 %) and those of other gender identities (46 %). Our findings also suggest that IP experiences are significantly influenced by the interplay of students' gender and their institutional context. At the first institution (Georgia Institute of Technology), IP was found in 58% of female students and 65% of male students, compared to 29% among students with other gender identities. At the second institution (University of Florida), these figures were 80% for females, 57% for males, and 67% for students with other gender identities. Our study underscores the importance of developing targeted support strategies within the CS education community to address the high prevalence of IP, particularly considering its varying impact across different demographics and institutional contexts.

Designing virtual humans to support mental health scenarios is challenging, as it requires designers to think of characteristics and strategies to promote rapport, increase trust, and favor the agents’ effectiveness during the intended interactions. This paper explores the impact of featuring the designer as a product cue in virtual human interactions, with a particular focus on how gender synchrony among users, virtual humans, and their designers influences trust and intentions towards well-being practices like gratitude journaling. We conducted an online, asynchronous, between-subjects user study and analyzed responses from 159 adult participants from the United States: Participants were female (n=80) or male (n=79). We assessed how gender synchrony could affect users’ intentions and the perceived trustworthiness of the virtual agents. Our findings suggest that gender synchrony does not significantly impact users’ intentions towards gratitude journaling. However, significant differences were observed concerning source credibility linked to agent trustworthiness when there was an age gap of less than ten years between users and virtual humans. These findings underscore the importance of considering both gender and age when designing virtual humans, as these factors can significantly enhance user acceptance and could foster the overall effectiveness of virtual human interactions in sensitive contexts such as mental health. Our study contributes to understanding how demographic characteristics and the use of the designer as a product cue can be strategically adapted to improve user experience in mental health scenarios.

Promoting active learning is challenging in large computing courses, often with hundreds of students. We present insights from a pedagogical strategy we designed to foster college Computer Science (CS) students' learning in a large introductory course on software design and engineering (SWE). Students first created an instructional video explaining SWE concepts. Next, they peer-reviewed their classmates' explanations. Our findings suggest that using student-created instructional videos can support students' learning processes and help promote active learning in large computing courses.

In an era where digital platforms like TikTok and Instagram redefine interaction, integrating active learning in large-scale computer science (CS) courses presents both a unique challenge and opportunity. This lightning talk intends to discuss a two-step strategy piloted within a second-year large-scale (i.e., over 500 students) introductory course to software engineering at a Southeast North American university. First, we tasked CS students to create a video tutorial as their midterm exam deliverable. The exam consisted of four questions: three open-ended questions for concepts on software engineering and one diagramming question that had them transform a descriptive context into a UML domain model diagram. Next, students took part in a double-masked peer review process that had them evaluate their peers' deliverables and explanations. Overall, we intended to assess students' understanding of software engineering concepts while enabling them to reflect upon their learning processes as they taught what they learned. Also, by having them peer-review among themselves, we aimed to foster an experience to enrich students' engagement and develop feedback skills. This lightning talk is to gather feedback from the CS Education community on this instructional strategy and possibly collaborate for a more extensive study on student-created artifacts in large-scale CS courses.

Virtual humans (VHs) have the potential to support mental wellness among college computer science (CS) students. However, designing effective VHs for counseling purposes requires a clear understanding of students’ demographics, backgrounds, and expectations. To this end, we conducted two user studies with 216 CS students from a major university in North America. In the first study, we explored how students co-designed VHs to support mental wellness conversations and found that the VHs’ demographics, appearance, and voice closely resembled the characteristics of their designers. In the second study, we investigated how the interplay between the VH’s appearance and voice impacted the agent’s effectiveness in promoting CS students’ intentions toward gratitude journaling. Our findings suggest that the active participation of CS students in VH design leads to the creation of agents that closely resemble their designers. Moreover, we found that the interplay between the VH’s appearance and voice impacts the agent’s effectiveness in promoting CS students’ intentions toward mental wellness techniques.

Counseling requires intimacy between a counselor and a patient to reach healing and growth. However, building rapport between virtual human counselors and computing college students is a complex problem. It requires understanding students' experiences and goals, as also the effects the characteristics of a virtual human counselor, like the spoken accent, have in the interaction with a patient in regards to messenger credibility and self-disclosure. This paper reports findings of how virtual human counselors' spoken accents impact computing undergraduate students' mental wellness conversations in regard to students' self-reported multilingual skills: monolingual or multilingual. We developed two English-speaking rapport-building virtual humans, each with a different spoken English accent-American or German, to interview 62 North American undergraduate computing students from a North American campus. Our findings suggest that virtual humans' spoken accents impacted students' perceptions of the virtual humans' speaking skills. Additionally, we found a similarity-attraction effect between monolingual English speakers and the American-English-accented virtual human counselor concerning participants' engagement and perceptions of the virtual human's speaking skills.

Learning how to program is perceived by many college students as difficult. Factors that influence novices’ success in computer programming learning include the student’s mental model of programming, computer playfulness during training, and programming anxiety. Programming anxiety (PA) is a psychological state engendered when a student experiences or expects to lose self-esteem in confronting a programming task. Students’ achievements have been seen to be negatively affected by programming anxiety. Others have investigated storytelling and tangible block programming to facilitate learning programming skills, but such efforts did not focus on analyzing their effects on users’ anxiety toward programming. In this work, we present fableBlocks, a tangible block-based programming (BBP) environment that relies on storytelling to mitigate programming anxiety. We adapted an existing BBP environment to incorporate storytelling. In a comparative pilot study, fableBlocks outdid a conventional GUI-based environment in usability and user-experience scores. Although not statistically significant, participants demonstrated lower levels of PA with fableBlocks.

In the context of mental wellness support, trust and intimacy between a counselor and a patient are necessary to converge healing processes positively. However, convincing students to trust a virtual human for topics regarding mental wellness is a complex problem that requires understanding students' experiences. Based on research that discusses mental health as a concerning topic regarding Computer Science (CS) students, this paper investigates how undergraduate computing-related students perceive virtual humans' expertise on mental wellness support based on demographic resemblance on spoken accent and gender. Four virtual human counselors were developed to conduct the study, as 58 undergraduate computing-related students from two North American universities were recruited and assessed. Our findings suggest that students were less inclined to interact with a male virtual human than a female one. Also, that spoken accents can impact students' perceptions of expertise under students' multilingualism.

Block-based programming is typically based solely on graphical user interfaces (GUIs). Some approaches, however, provide tangible interaction. They usually allow users to create block programs with GUIs to control physical robots or use physical blocks to create programs displayed on a vertical display. With these systems, users split their attention between the GUI and the physical objects. Split-attention effects have been shown to increase task completion time and hinder learning. BlockXR applies projected augmented reality and computer vision to provide users with tangible interaction for programming and feedback in the same plane. A comparative study with a GUI-based system determined that BlockXR scored significantly higher in the user experience scores of Attractiveness, Stimulation, and Novelty. We found no significant differences between usability scores. In this work, we describe the system and the quantitative and qualitative feedback from an user study.

In this paper we present findings on a pedagogical approach we designed to enhance students' understanding of Functional Programming, in which they were required to create two video-tutorials. The first video-tutorial assignment asked the students to develop explanations of Functional Programming concepts. The second video-tutorial required them to explain their solutions while completing coding exercises using Haskell. We present a detailed description of the activities, their evaluation, and their impact on students' learning, motivation, and performance. Our findings suggest that the use of a student-created video-tutorial approach can be effective for increasing students' understanding, performance, and engagement on Functional Programming assessments. This suggests that using student-created video tutorials may be a promising strategy to implement in other computing courses.

This poster presents findings on a pedagogical approach we designed to enhance undergraduate computing students' understanding of functional programming (FP) through student-created video-tutorials. Students created two video tutorials. The first video-tutorial assignment asked the students to develop explanations of FP concepts (theoretical understanding of FP). The second video-tutorial required students to explain their solutions to programming exercises using Haskell (application of FP). Our findings suggest that the use of student-created video-tutorial can be effective for increasing students' understanding and application of functional programming.

This paper presents the design of Blocks4DS, a block-based environment for students to learn data structures. As a proof-of-concept, we designed custom blocks to allow students to build and visualize Binary Search Trees (BST). Blocks4DS is built on Blockly and uses vis.js to provide visualizations of the binary search tree and its operations. This paper describes the results from an initial evaluation of usability and student learning.

Uno de los principales desafíos relacionados con la enseñanza algorítmica y de programación con estudiantes novatos, es enfocar su proceso en la adquisición de conceptos y el desarrollo de habilidades de resolución de problemas en programación, sin perder tiempo superando curvas de aprendizaje orientadas a la sintaxis de lenguajes específicos. La aplicación aquí explicada se propone como una tecnología instruccional que, aprovechando las ventajas de la Programación Visual Blocks, a través de escenarios de robótica móvil virtual y remota, busca dar mecanismos lúdicos y amigables para la programación y el autoaprendizaje algorítmico. Este artículo presenta el diseño y enfoque pedagógico de la herramienta, evaluado a través de un enfoque de Experiencia de Usuario con estudiantes de secundaria en el contexto educativo colombiano.

One of the major challenges related to teaching programming and algorithms to novice students is the time spent on the language's syntax and how their attention is incorrectly focused on the syntax rather than the acquisition of concepts and the development of problem-solving and programming skills. This study focuses on the design and evaluation of a Web App (RoBlock) designed for autodidactic learning. It uses Visual Blocks Programming, and contains six interactive modules that cover programming concepts. The solution is presented as virtual scenarios for Mobile Robotics.