The widespread adoption of Generative AI (GenAI) tools by students across different educational levels highlights the need for them to develop robust GenAI literacy, including a working understanding of these systems' fundamental concepts, their limitations, and implications for responsible use. However, misconceptions about GenAI, such as perceiving these systems as mere search engines or database lookup systems, are commonly observed among students, while the availability of teaching resources remains fragmented, and learning objectives lack alignment. This Working Group aims to design pedagogical resources for computing science instructors, enabling them to develop students' GenAI literacy. To achieve this, the Working Group will first identify a concise set of GenAI literacy learning objectives informed by instructor experience, research literature, and community input, and subsequently design pedagogical resources aligned with these objectives.

Recent research has shown the great potential of automatic feedback in education. This paper presents SOBO, a bot we designed to automatically provide feedback on code quality to undergraduate students. SOBO has been deployed in a course at the KTH Royal Institute of Technology in Sweden with 130+ students. Overall, SOBO has analyzed 1687 GitHub repositories and produced 8443 tailored code quality feedback messages to students. Unlike traditional tools embedded in CI pipelines, SOBO is designed to interact with students in a way that promotes personalized learning without imposing additional teaching burdens. The quantitative and qualitative results indicate that SOBO effectively nudges students into adopting code quality best practices, without interfering with pedagogical objectives. From this experience, we provide guidelines on how to design and deploy teaching bots in programming courses.

GenAI is playing an increasingly important role in computing courses at all levels, offering new opportunities to support teaching and learning. However, using GenAI effectively raises important concerns regarding trust, academic integrity, and broader social and ethical dimensions. This Working Group was formed to report on the current state of the art in using GenAI in upper-level computing courses to aid educators. The working group will undertake a methodological review of published work and solicit input from the computing educational community as part of the report.

We present a system that enables students to generate their own programming assignments that are both personalized to their interests and aligned with the course objectives. A group of twelve undergraduate students randomly selected from an introductory programming course (~200) received training and access to the system for six weeks. Students were free to use the system to generate assignments or take regular assignments instead. Weekly student feedback was used to refine the system through three iterations, and a focus group with three students was held after the course to gather opinions on the experience. Our findings are complicated and cautionary: students appreciated generating their own personalized assignments with feedback on demand. However, the cognitive load of having to generate and decide which assignment to complete, along with the variation of difficulty and alignment with learning objectives were noted as problematic and discouraging. Perhaps the most negative but heartwarming result is that students missed the community aspect of independently solving and collectively discussing solutions to a common assignment.

The aim of this work is to describe a simple and cost effective way to integrate generative AI into GitHub to support course specific scenarios. We are motivated by helping teachers realise their creative AI use cases in spite of technical barriers and also to ensure that students have a blessed and fair way to access AI services without needing to sign-up, prompt or pay. First we will describe a scenario that we have implemented for our own CS1 course, then we will describe the technical requirements for implementation. We finish off with our early thoughts on where these types of scenarios might be heading in terms of supporting computing education.

Characterising code quality is a challenge that was addressed by Börstler et al. 's working group in 2017. As emerged from their study, educators, developers and students have different perceptions of the manifold aspects involved, and a major conclusion of that WG was that "code quality should be discussed more thoroughly in educational programs" [2, p. 70]. However, the lack of materials and the time constraints have slowed down progress in that regard.

Low code quality incurs a significant cost upon the software industry. Despite this, little serious effort has been devoted to the topic at the most basic levels of computing science education. Where studies have been conducted, the results are disappointing in terms of code quality. In this work, four iterations of a medium to large CS1 and CS2 course (n=200 students) were analyzed through the lens of code violations to better understand (1) what code violations occur most frequently, (2) how does their occurrence vary throughout the course, and (3) to what extent do teaching assistants have an effect upon code quality. Results showed a statistically significant improvement in code quality over 19 assignments in all four course iterations. In particular, when a single violation was the focus of a learning outcome, the effects were both a dramatic fall and sustained low occurrence. However, this improvement was mostly focused on the three most frequently occurring violations (> 70%), which masked an increase in lesser occurring violations throughout the course. Finally, the effects from different teaching assistants were found to be random at best, contradicting expectations that their influence would be easily detected. Given that explicit learning outcomes targeted at code quality had an effect and teaching assistant influence had no effect, a path forward to improving code quality might combine these forces without creating too many additional demands upon the already stretched teaching resources with CS1 and CS2 courses.

Historically, computing instructors and researchers have developed a wide variety of tools to support teaching and educational research, including exam and code testing suites and data collection solutions. Many are then community or individually maintained. However, these tools often find limited adoption beyond their creators. As a result, it is common for many of the same functionalities to be re-implemented by different instructional groups within the CS Education community. We hypothesize that this is due in part to accessibility, discoverability, and adaptability challenges, among others. Further, instructors often face institutional barriers to deployment, which can include hesitance of institutions to utilize community developed solutions that often lack a centralized authority. This working group will explore what solutions are currently available, what instructors need, and reasons behind the above-mentioned phenomenon. This will be accomplished via a literature review and survey to identify the tools that have been developed by the community; the solutions that are currently available and in use by instructors; what features are needed moving forward for classroom and research use; what support for extensions is needed to support further CS Education research; and what institutional challenges instructors and researchers are currently facing or have faced in the past in developing, deploying or otherwise using community software solutions. Finally, the working group will identify factors that limit adoption of solutions and ways to integrate and improve the accessibility, discoverability, and dissemination of existing community projects, as well as manage and overcome institutional challenges.

Developing good version control skills is important for students to master. This work focuses on helping students integrate good commit behaviour using a scaffolding process that happens with their regular assignments. A test group of students (n=30) was required to make a minimum of three commits in the first week. In the second week, students were trained to write better commit messages and worked together on a commit plan. In the final week, students worked alone on their commit plan. Commit behaviour was analysed for assignments occurring before, during and after the process. Results showed that students improved their commit behaviour in terms of number of commits, starting earlier with their assignments and writing more meaningful commit messages when compared to the rest of their cohort and the previous year's cohort (m=350). Qualitative results showed that students were mostly positive towards developing better commit behaviour and felt that the extra effort to think in commits delivered proportionally more benefits for their work.

The shift to meeting students online has made traditional forms of interaction difficult or impossible to replicate. In response, we suggest that teachers become co-pilots for each other: joining lectures and extending the abilities of a solo teacher. By doing so, there are clear and distinct benefits for students, the teacher, and the co-pilot, with almost no barrier to entry and very little preparation required. Whilst there is a time cost, we feel this is well spent and acts as a gateway to more established pedagogical practices, such as peer observation and cooperative teaching.

This paper presents Sanitizer, a tool for maintaining a student assignment and its reference solution in a single Git repository. The solution to the assignment is kept on its own branch, and is annotated with a simple inline markup. Based on this markup, Sanitizer removes files or parts of them, and commits the result to the student branch that can then be safely distributed to students. This provides a consistent workflow for developing assignments and their solutions together, avoiding the problem of drift between assignment and solutions over time, and simplifying the sharing of solutions with other teachers.

Peer review is an important component of student development. As such, systems have been developed to support teachers in facilitating peer review. A key feature is double-blind review, were the reviewer and reviewee remain anonymous to each other. As more courses adopt Git along with a platform like GitHub, an interesting challenge emerges - all changes are tracked along with the identity of the student and it is not obvious how to conduct double-blind peer review. While external systems can be used, we believe it is more authentic for students to conduct their peer review within the environment provided by platforms such as GitHub, and less of an administrative burden for teachers. This paper presents our extension to RepoBee that facilitates double-blind peer review with minimal effort on the GitHub, GitLab and Gitea platforms, as well as the results of an informal study of teachers using it in their practice.

The coronavirus (COVID-19) pandemic has forced an unprecedented global shift within higher education in the ways that we communicate with and educate students. This necessary paradigm shift has compelled educators to take a critical look at their teaching styles and use of technology. Computing education traditionally focuses on experiential, in-person activities. The pandemic has mandated that educators reconsider their use of student time and has catalysed overnight innovations in the educational setting. Even in the unlikely event that we return entirely to pre-COVID-19 norms, many new practices have emerged that offer valuable lessons to be carried forward into our post-COVID-19 teaching. This working group will explore what the post-COVID-19 academic landscape might look like, and how we can use lessons learned during this educational shift to improve our subsequent practice. The exploration will strive to identify practices within computing that appear to have been improved through exposure to online tools and technologies, and that should therefore continue to be used in the online space. In the broadest sense, our motivation is to explore what the post-COVID-19 educational landscape will look like for computing education.

Many online learning initiatives have failed to reach beyond the environments in which they were first developed. One exception is the Open Learning Initiative (OLI) at Carnegie Mellon University (CMU). In an attempt to validate the question-based learning methodology implemented in OLI, we developed online material for an introductory course in object-oriented programming, and tested it on two course offerings with a total of 70 students. As our course has been given in the same format for several years, we also had comparable assessment data for two classes prior to our intervention in order to determine that we did not introduce any obvious harm with this methodology. Findings show a reduced teaching and learning time by 25%. No statistically significant differences could be found in the results of the assessment quizzes nor confidence surveys completed by the students. The two teachers (the same who handled the classes before the intervention) took different paths to teaching preparations with this new methodology. One teacher increased preparations, whilst the other reduced them, but both teachers were convinced that using online question-based learning was superior to the previous lecture and textbook-based approach, both for the students and themselves in terms of overall satisfaction. We also gathered time logs from the development to estimate return on investment.

To make effective use of version control systems like Git in teaching, teachers require tool support to manage student repositories. RepoBee (https://repobee.org) is a command line tool that assists teachers in creating repositories for students, batch cloning of student repositories, facilitating industry-inspired peer review, and much more. A powerful plugin system makes RepoBee flexible, allowing it to execute workflow-specific tasks such as running JUnit test cases on cloned student repositories, managing repositories created by GitHub Classroom, and extracting grades from grading issues on issue trackers. Also by way of the plugin system, RepoBee uniquely supports both the GitHub and GitLab platforms. In this demo, we shall demonstrate how teachers can apply RepoBee to manage student repositories. We shall first show the core features of student repository creation and cloning, and then how workflows can be customized with the plugin system. To cultivate interaction, participants will be able to suggest desirable features, which we then attempt to start developing plugins for. Finally, we shall conclude with an open discussion on tool support for version control in education and attempt to identify future directions.

As students transition into higher education, their experience can be quite new and foreign to them - at times acting as a barrier into higher education. This experience, while an individual one, consists of many concerns that are shared amongst these transitioning students. Partly as a result of these concerns, retention rates of first year Computer Science students suffer. These topics were discussed and analysed at length in various studies, panels and working groups to create an initial body of understanding, influenced by a number of institutions across the world. However, the recent and unprecedented COVID-19 pandemic has caused further disruption: it is likely that students transitioning into higher education during the pandemic were faced with unparalleled concerns, anxieties and stresses.

Feedback has been long understood to be a vital component of learning. This is even more important in an online environment, where access to teachers is limited or unavailable. When online learning material is interspersed with opportunities for students to test their knowledge, there is a golden opportunity to give feedback and fix misconceptions immediately. All too often this opportunity is missed or mishandled in online learning platforms - either providing no feedback, or providing it at a coarse level of granularity. Furthermore, generating constructive feedback at a fine level of granularity is so time consuming as to be prohibitive. In this work, we build upon literature that has established students can be recruited to generate quality multiple choice questions, by exploring if students can also generate quality feedback to compliment the questions they generate. In the first iteration of an introductory programming course, we tasked 35 students to generate six questions each over three weeks, and analysed this dataset to generate principles of creating good multiple choice questions with constructive feedback. In the second iteration of the course, we repeated the same task, but provided students with the principles. The results showed an increased occurrence of good feedback when compared to the previous iteration with minimal need for additional intervention by teachers.

RepoBee is an open source tool that helps teachers to use Git effectively in teaching. Use of version control systems has been growing in popularity, with more teachers adopting the technology, or planning to in the future. However, systems like Git are challenging to use and were not designed with teaching in mind. In response, tools have emerged that attempt to reduce the complexity of this task for teachers, whilst providing students with an authentic experience of using a version control system. We have developed RepoBee to provide common features a teacher might need: the ability to distribute assignments to students; gather their efforts for grading; run grading tasks and other analytics; as well enabling support for peer review. In sharing our solution with other academics, it has become clear that there is a wide range of needs. This in turn has influenced our design philosophy for RepoBee such that it should be flexible and extensible, in order to be used in a broad range of teaching contexts and can be extended to accommodate course specific needs. This paper aims to draw attention to three particular aspects that distinguish RepoBee: support for different course models; support for course specific features; and support for multiple repository hosting platforms.

The use of version control systems within computing education is growing in popularity. However, this is challenging because such systems are not particularly well designed to support educational situations, nor are they easy to use with confidence in teaching, as specialist knowledge and experience is required. This experience paper reports the development of the open source tool RepoBee, which assists in the use of Git/GitHub in an educational context. The tool provides a straightforward interface for managing batch tasks such as repository generation and cloning for setting and gathering assignments, opening and closing of issues to communicate with students, as well as facilitating peer reviews. Parts of RepoBee are open to integration with third party tools for additional tasks, such as running unit tests or static analysis on student repositories. We also include the perspectives of both teachers and teaching assistants who have been using the tool as part of a first year course for computer scientists.

As students transition into higher education, their experience can be quite new and foreign to them. This experience, while an individual one, consists of many concerns that are shared amongst these transitioning students. Partly as a result of these concerns, retention rates of first year Computer Science students suffer. Members of this panel have been involved in multi-year studies across Scotland [2, 5] as well as an international study [3] looking at the student experience as they transition into undergraduate Computer Science. This panel hopes to discuss the transition into CS1 and implications for Computer Science retention rates from varied international perspectives as well as through the lens of online learning. It further hopes to discuss new ways that we might be able to better support first year CS student retention in light of collected transition data, as well as the current state of any implemented recommendations in previous work (you may want to rephrase this).

This poster provides insight into the use of an issue tracker for the management of assignment feedback within an introductory course in computer science (CS). Students have made use of Github for three successive years, and the issue tracker has become one of the key mechanisms for managing formative feedback. This approach has yielded three key benefits: increased student engagement in their own feedback; provided an early experience of an authentic and industry desirable communication skill; and created a means to oversee and learn from feedback discussions for the teaching team.

The experience of transitioning into and starting higher education is a very individual one, with some applicants viewing the prospect of higher education as an unknown entity; for those who are first in their family or community to consider higher education, this can seem an "alien environment". These are just some of the issues that lead to applicants experiencing levels of concern when considering a transition into higher education. This international working group proposes to consider concerns across a wide range of participants: namely students who are in the process of transitioning into a higher education environment, and students who have recently completed this transition.

How to provide users a positive experience during interaction with information (i.e., the “Information eXperience” (IX)) is still an open question. As a starting point, this work investigates how the emotion of interest can be influenced by modifying the complexity of the information presented to users. The appraisal theory of interest suggests a “sweet spot” where interest will be at its peak: information that is novel and complex yet still comprehensible. This “sweet spot” is approximated using two studies. Study One develops a computational model of textual complexity founded on psycholinguistic theory on processing difficulty. The model was trained and tested on 12,420 articles, achieving a classification performance of 90.87% on two classes of complexity. Study Two puts the model to its ultimate test: Its application to change the user's IX. Using 18 news articles the influence of complexity on interest and its appraisals is unveiled. A structural equation model shows a positive influence of complexity on interest, yet a negative influence of comprehensibility, confirming a seemingly paradoxical relationship between complexity and interest. By showing when complexity becomes interesting, this paper shows how information systems can use the model of textual complexity to construct an interesting IX.

This demonstration paper introduces ALF which provides a light-weight client side logging application and a server for collecting user interaction data. ALF has been designed as a loosely coupled independent service that runs in parallel with the IR web application that requires logging

MaSe provides a sandbox environment for high school students to create their own personalised search interface. It has been designed with two major goals in mind: (1) as a hands-on tutorial for school children, to excite them about programming and computing science through the development of a practical application, and (2) to enable children to design and create their own search interface without extensive programming knowledge or prior experience. Consequently, MaSe provides a way to ascertain what children would like from a search engine interface in an exploratory and creative way as they can create a working prototype. This approach contrasts with previous work on exploring children's requirements of IR systems which attempts to directly elicit user needs through more traditional methods (i.e. surveys, interviews, focus groups, etc). However, we have attempted to incorporate the design guidelines for children as identified by Large (2006) into MaSe, where: we make use of bright colours, large text fonts, spell checking and the use of icons to represent search services, as well as including a thematic experience as suggested by Large (2006), with the use of a puppy avatar and puppy dog footprints.

Children often struggle with information retrieval tasks as searching for information often requires a developed vocabulary and strong categorisation skills; neither of which are particularly developed in children under the age of 12. In a study conducted by Druin et al, it was found that in an experimental setting many children are often uninterested in searching for information online or are only interested in searching for information that is relevant to their personal interests. Consequently, children who were unmotivated were the least successful in completing information retrieval tasks in their study. It was suggested that a more effective means of engaging child participants in search studies must be developed in order to gain further insights into the searching behaviours of children. To this end we have developed a game called PageFetch which aims to engage children (aged 8 to 80) in completing search tasks through a fun and interactive search-like interface.

As adults we take for granted our capacity to express our information needs verbally and textually. However, young children also have preferences and information needs, but are just learning to be able to express themselves effectively. Consequently they encounter many barriers when trying to spell, type, and communicate their needs to a 'faceless' search engine text box.

Children face several challenges when using information access systems. These include formulating queries, judging the relevance of documents, and focusing attention on interface cues, such as query suggestions, while typing queries. It has also been shown that children want a personalised Web experience and prefer content presented to them that matches their long-term entertainment and education needs. To this end, we have developed an interaction-based information filtering system to address these challenges.