Allocating students to projects is a commonplace task in computing education. These decisions underpin student-supervisor allocation, the formation of tutee and capstone groups, and pair programming. These allocations play a critical role for individual learner outcomes and the success of collaborative interventions. For example, imbalance in either gender, ethnicity, or nationality can negatively impact learner outcomes. Despite the critical importance of these allocation choices, we see little consensus on how these are implemented. The allocation task can be challenging and time-consuming for instructors of even moderately-sized classes, and the fairness implications can be difficult to assess. Inadvertently, an instructor may allocate in a way that amplifies existing biases or disproportionately harms those from disadvantaged or protected groups. From students' perspectives, a lack of transparency on the allocation process may also lead to issues of trust. The Working Group will undertake a study of allocation practices by bringing together educational and ML literature to develop and evaluate the fairness of allocation methods, and develop educator guidelines to promote pedagogically grounded allocation practices.

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.

This paper describes a study in which a computer terminology translation activity was implemented in a CS1 class using a specially designed web application. Students translated an English technical term into their native language and wrote an accompanying definition of the term. These completed translations were then reviewed anonymously by their peers. Finally, students voted on the most highly rated translations to compose a glossary of translations.

What do students perceive as helpful when they learn to program? This paper presents the results of this question from a survey conducted with 125 students enrolled in two online introductory programming courses. The question asked students to rank a number of resources and activities that they used or completed in their course. The results show that students perceive lecture videos as the most helpful resource while syntax exercises were seen as the most helpful activity. The spread of the student responses would seem to indicate that a more thorough and widely completed investigation of student perceptions of resources and activities would be beneficial to the field of computer science education.

This paper describes a tool for managing peer-reviewed translation activities within CS1 classes. The tool is designed to help students develop a better understanding of terms within class by writing and reviewing translations of those terms and their descriptions in their native language. The peer-review of the translations means that lecturers do not need to share the language of their students.

When seeking to maximise the authenticity of assessment in programming courses it makes sense to provide students with practical programming problems to solve in an environment that is close to real software development practice, i.e., online, open book, and using their typical development environment. This creates an assessment environment that should afford students sufficient opportunities to evidence what they have learned, but also creates practical challenges in terms of academic integrity, flexibility in the automated grading process, and assumptions surrounding how the student may attempt to solve the problems both in terms of correct and incorrect solutions. In this experience report, we outline two independently observed cohorts of students sitting the same Java programming exam, with different weights, over three years. This is undertaken as a reflective exercise in order to derive a series of recommendations and retrospectively obvious pitfalls to act as guidance for educators considering online programming exams for large (i.e. n > 150) introductory programming courses. After discussing our assessment methodology, we provide 4 high-level observations and centre a set of recommendations around these to aid practitioners in their assessment design.

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.

In this paper, we analyze 32,000 Java programming assessments submitted to the CodeRunner platform by introductory programming students. We identify common sequences of errors and link these patterns with observations of code that compiles but still contains logical errors. We establish reoccurring errors and common error pathways through a Markov chain analysis of attempts and use Association Rule Mining to link common error patterns with logical errors that occur later in the attempts. As a result, we provide a number of suggestions for instructors of introductory Java courses regarding how to potentially navigate these issues in their teaching practice and discuss possible pedagogical interventions on the basis of our observations.

Code comprehension is an important skill to develop when learning to program. However, it can be hard to emphasise this to students when they are assessed with problems that overtly challenge their knowledge of syntax or their problem solving skills. This poster presents a prototype for developing automatically graded quizzes on program tracing for basic programs in both C and Python. Questions can be generated for each individual line of code, focusing in higher detail, or about a whole file. Feedback explaining the execution is automatically generated including a diagram showing the code represented as a tree and accompanied with a text explanation.

This study describes the development of a word list for CS1 and the creation of a Computer Terminology Test. The CS1 word list contains 123 most frequent words compiled from CS1 textbooks and lecture notes. This list is beneficial for students, teachers, and curriculum designers to use it in studying, teaching, and setting learning goals especially for non-native English speakers. The Computer Terminology Test was built based on words perceived to be most important from the CS1 word list. This test is designed to help in identifying students who may need extra support in English computer terminology to improve their performance in introductory programming classes.