Our working group aims to better understand teamwork in undergraduate computing education through a systematic literature review and focus groups with instructors. Based on the strategies suggested and needs identified, we will also co-design instructional resources with the community to cultivate the skills, values, and virtues pertinent to teamwork. Through planned research and collaboration, we seek to inform and establish practical materials that can enhance teaming pedagogy and prepare graduates for the evolution of technology and the workforce.

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.

Students entering Computer Science (CS) programs are arriving at college with a varying knowledge of coding and CS. The rigid structure suggested to all, does not fit everybody. But finding the correct starting course in CS at college level is not simple, since students may not understand that CS is not only coding. The failure of a good selection on where to start the CS program can be a hindrance to students, since they may perceive that CS is not for them because it appears to be too hard, or they may perceive it as too easy and lose their interest. The General Concept Inventory for Introductory Computer Science (GCSCI) was created to tackle this problem, it can be roughly divided in two parts. In previous research authors have presented the validation of the first part, that can assess concepts that are usually taught in CS0 and CS1. This work presents the second part of GCSCI, the topics covered and its validity assessment. This part of the assessment contains 42 questions that assess topics from object orientation to data structures and sorting. All students doing CS2 in Fall 2023 were invited to participate, from the 42 questions being evaluated; 20 had a good coverage and were validated in terms of discrimination and difficulty level.

In higher education, introductory Computer Science (CS) programs offer a range of foundational courses. These encompass not only the standard CS1 and CS2 courses but may also include more specialized options like CS0 and CS1.5. In order to appropriately assign students to the suitable introductory courses, many institutions utilize placement tests, which assess students' pre-existing knowledge and skills. While most institutions rely on accuracy alone to make these determinations, there is often additional information concealed within the completed tests. This paper delves into the potential of Large Language Models (LLMs) to uncover this hidden information, particularly in gaining insights into how students perform in different concepts. Moreover, our framework has the flexibility to accommodate variations in curricula across different institutions, providing additional analytical perspectives. Initially, we built a concept inventory (CI) using the concepts covered in an institution's CS0, CS1, and CS2 curricula. Next, an LLM, specifically GPT 3.5, was applied to associate each question in the placement test with one or more concepts in the CI. Finally, the results of the placement tests were scrutinized, allowing the calculation of mastery levels in each concept for individual students. These mastery levels enable institutions to gauge a student's prior knowledge across various concepts simply by using a CS placement test. Additionally, we presented a case study demonstrating the application of this framework to 267 existing placement test results at Boston College.

In project-based software engineering courses, the collaboration among participants is usually the cornerstone that makes these experiences successful and allows reaching the courses’ instructional goals. Prescribing a collaboration process for these courses is not appropriate, since their workflows are ad hoc framed; i.e., most of their activities are defined on-the-fly by the participants, according to their current context and needs. Therefore, only coordination and awareness mechanisms can be defined at the course design time, in order to support and promote collaboration among participants during these courses. This article presents a qualitative study that identifies and relates these coordination and awareness mechanisms, and embeds them in a set of software ceremonies. Course instructors and instructional designers can take advantage of these results, not only to identify design decision points, but also coordination and awareness mechanisms to promote collaboration in this type of courses.

Although it is already established that computing education (CEd) is an emergent interdisciplinary field with scholars around the globe contributing to research in this area, it is less clear how and where this research occurs. To better understand the current state of computing education research (CEdR) and opportunities for those engaged in the field, we employed a data collection process involving training, information gathering, and reporting with institutional representatives. We sought to develop an overview of: 1) affiliations of graduate students and faculty conducting CEdR; 2) funding for graduate students and faculty conducting CEdR; 3) the academic degree options and the credit, coursework, and publication requirements for graduate students; and 4) institutions' current and future plans for CEd. Partnerships with contacts spanning 30 institutions spread across five continents provided insight into the pathways and possibilities that presently exist for researchers in the field, as well as a glimpse into future plans for expansion (or the lack thereof). The findings from this investigation offer valuable information for students and faculty seeking potential collaborations, thinking about their career trajectories, or when planning CEd initiatives; for educators trying to develop courses; and for administrators considering creating more formal tracks for those focused on CEd.

In the last couple years, the interest in computer science programs has significantly increased both within the academic realm and the general population. Currently, students entering computer science programs possess very diverse computing experience; some have never coded before, some have a little code experience, and others have years worth of experience. Because of this, the fixed-structured program style, where students follow a predetermined, specific course path does not work very well; students are often left feeling frustrated and discouraged because the courses they have to do are either too easy or too hard. This deters many students from pursuing careers or majors in computer science. To solve this issue, a standardized assessment that will measure students' knowledge independently of any previously learned programming languages is necessary. This paper presents the idea and a partial validation of a General Computer Science Concept Inventory (GCSCI). The goal is to have a language independent assessment that can measure students' knowledge of the concepts contained within the introductory CS courses (CS0, CS1, CS2). Here we present the topics covered in the first part of the GCSCI and its validity assessment. Students doing an Intro to CS course were invited to participate in the validation of the first part of the GCSCI. Of the 25 questions generated, which have a good coverage of the concepts being evaluated, 14 were validated.

Despite the expansion and development of the field of computing education (CEd), a lack of formal programs means that researchers often exist as islands across and within a diverse range of departments. Given the broad nature of the discipline, trying to build a community typically occurs through more formal conferences. Another way to expand engagement with the field is through Research Experiences for Undergraduates (REU), programs that offer students the chance to get involved with research. REUs have been shown to strengthen disciplinary identity and encourage the pursuit of graduate degrees. However, such opportunities are not usually available at the graduate level. To address this gap, we present an experience report that describes our approach, Research Experiences for Graduate Students (REGS). In the work that follows, we detail our implementation and the partnerships created that allowed (n = 10) internationally dispersed graduate students from different institutions the chance to build connections, conduct CEd research, and develop a graduate-centric community. Leadership researchers, faculty, and staff supported the efforts, offering guidance and critical examination of the work to establish rigor over the course of the projects. Publications and presentations contributed to the CEd knowledge base, and interviews with the students upon completion of the experience illustrated the value of participation in the REGS.

This Research Full Paper presents a literature review on introductory CS assessments. As Computer Science (CS) becomes increasingly popular in the world of big data, more college students are taking introductory CS courses to follow the trend. However, students have different levels of exposure to CS when they start CS in college, varying from no experience to years of coding experience. This disparity in the amount of exposure can pose many problems. In the same intro-level class, some students may think they do not learn anything new, while others believe the professor goes through concepts so fast that they cannot follow the pace. CS professors may also feel confused about how to control the pace and content of introductory courses. Therefore, CS departments need an assessment to measure students’ CS knowledge and then assign them to the appropriate CS introductory courses. Though a vast number of research papers discuss CS introductory courses, few of them focus on developing and validating assessments that evaluate students’ background knowledge (i.e., concept inventory). This paper aims to conduct a systematic literature review to gain an overview of the most important introductory CS contents that need to be assessed, the methods to evaluate students’ understanding of introductory CS concepts, and some existing assessments/concept inventories. By reviewing relevant papers over the last 15 years, we selected 48 papers that are related to assessments and corresponding introductory courses. We collected assessment information and made tables of contents, question types, programming languages, and origins to analyze data. We found that iterations, conditionals, and variables are the most popular assessment contents. Multiple-Choice and Code Writing questions, which are more popular than Code Explaining questions, are the preferred ways of assessing students’ knowledge. Scratch is commonly used as a CS0 assessment language, while Python, Java, C, and Pseudo-codes are employed in CS1 assessments. FCS1, SCS1, and BDSI are existing assessments/concept inventories for CS1 or CS2, but there is not yet a validated assessment or concept inventory that encompasses introductory concepts of CS0 (computational thinking), CS1 (fundamentals), and CS2 (data structure). Designing a comprehensive CS0/CS1/CS2 assessment by using the information collected from our systematic literature review would help students choose the right course and benefit educators and researchers for general use.

Professional accreditation in medicine and religious organizations started in the 1800s; business and engineering followed in the early 1900s. Program accreditation in computing commenced in the 1980s after computer science, informatics, and information systems programs had become widespread. In 2008, accrediting bodies in eight countries signed the Seoul Accord to set up mutual recognition of professional computing degrees. Although competency-based learning has existed for centuries, it has only made headway in computing in the last dozen years. Computing Curricula 2020 defined competency as the amalgamation of knowledge, skills, and dispositions. This working group report examines professional accreditation in computing, exploring aspects of professional accreditation criteria that support competency-based learning. The report will help educators understand professional accreditation and competency-based learning worldwide. Finally, it will also guide future efforts contributing to competency-based accreditation.

Computer science education (CSEd) is a growing interdisciplinary area that continues to gain momentum from students, researchers, and educators. Yet, there are few formal programs or degree options for students interested in pursuing graduate work in CSEd. This article explores the existing state of CSEd in the United States (U.S.) through semi-structured interviews with ( n = 15) faculty engaged in CSEd research. Thematic coding of the transcripts revealed the complexities involved in the development of formal programs, the distinct considerations for faculty, and the value of having strong ties to both computer science and education. The themes described positive aspects of support and cohesion within the larger community and opportunities to expand knowledge across fields. Applying Cornell and Parker’s principles of interdisciplinary science to the field of CSEd, we provide recommendations for ways forward and discuss the potential impact on institutional structures, research capacity, individual and group identities, and teaching and learning. The findings from this investigation not only inform on the present state of CSEd in the U.S., but also offer guidance for CSEd-focused graduate programs.

Although computer science education (CSEd) is growing rapidly as a discipline, presently there are a limited number of formal programs available for students to pursue graduate degrees. To explore what options exist, we sought to develop a better understanding of the researchers and institutions currently working in CSEd. We collected publication data between 2015 and 2020 from the Innovation and Technology in Computer Science Education (ITiCSE) and ACM International Computing Education Research (ICER) conferences, and from the ACM Transactions on Computing Education (TOCE) journal. Using a total of 1,099 publications, we analyzed the authorship blocks and their affiliations. We created a comprehensive database, used for analysis on recent contributions to CSEd research. Among other findings, we observed that 2,068 distinct authors contributed, spanning 578 global institutions. From these, 963 of the authors came from 236 distinct universities in the United States. Moreover, we found that most often, new growth from international contributions resulted from the participation of additional universities, whereas in the United States most growth was the result of new contributors from the same universities. The results of this research are intended to encourage global collaborations, to provide an informative guide about recent publications in the field, and also to serve as a guidepost for graduate recruitment and further exploration into CSEd research and programs.

The structure and the way in which organizations manage their projects have evolved. Agile software development has emerged as an alternative to manage projects management processes more efficiently. Process mining allows the analysis of project historical information and proposing improvements for agile processes. A systematic mapping study (SMS) was conducted to classify the proposed approaches in agile development methodologies that uses process mining. A total of 502 studies were identified, and finally 6 studies were selected and analyzed according to distinct aspects. Conference proceedings is the most common venue. There is a concentration of approaches published that comes from Asia and Europe. Disco tool is the most frequently used tool. Meanwhile, the process discovery being the most relevant process mining type used by researchers in this research area. There are two evaluation methods reported as being used: case study and running example, where Scrum is the most frequently methodology used. To the best of our knowledge, this is the first research that has been conducted to generate a SMS in this research area.

This research presents that teaching software engineering can be a demanding challenge for instructors, considering that the software industry grows rapidly and there are new development technologies being released constantly. Some of the methodologies being used in industry with time are converted in “best practices”. This systematic literature review (SLR) focuses on finding what are the software engineering best practices being taught to students in academia. It is expected to show with this SLR what are the best practices being taught and how, so other instructors and the teaching staff can evaluate what to choose and level up their courses to the extent of what is being used and is already tested. To perform this SLR, a well-known protocol was used with the search string: “software engineering education” and “best practices” (variations and synonyms of the words were also used), the search was performed in six well-known databases. It is surprising that the amount of primary studies found in this SLR was not what was expected, seventeen primary studies were identified. These studies mentioned a total of seventy best practices that are being used in academia to teach software engineering, some of them are mentioned in more than one paper. But the granularity of the primary studies was quite different some of the best practices are really software engineering best practices and others are instructional best practices. It was also evaluated how the use of these practices was validated and reported, and the results are very diverse, some of them did not have a validation, others have qualitative data, and a few qualitative and quantitative data.

Although most computer science graduates develop their professional careers as software engineers, there are no academic program with a specific focus on software engineering in Chile. Considering ACM/IEEE Software Engineering 2014 Curriculum Guidelines as a starting point, we analyzed the curricula of the CS Engineering and CS Technology programs offered by the most traditional Chilean universities, in order to establish to what extent they address the knowledge areas included in that recommendation. We also gathered information about theoretical and/or practical approaches of their courses, their types of evaluations and temporality. The results of this status report indicate that most knowledge areas of the ACM/IEEE curricula are covered but not all with the same emphasis. Programs count on three or four mandatory software engineering courses, most of them have a practical approach, are evaluated through exams and projects and start between the seventh and eight semesters. These results let us learn that some knowledge areas are not emphasized as they deserve. For example, Software Quality or Software Process are skills that industry often requires but academia does not seem to take into account. Similarly, it might be necessary to have students learn about software engineering earlier during their career. Knowing the actual status, actions can be taken.

Software engineering education is currently being taught in many universities with a hands-on approach, where students have to learn to develop software in teams, intending to simulate industry, to minimize the gap between what universities teach and what industry needs. The industry "simulation" that a university performs in software engineering courses is a good approach but it is normally undermined by student bad behaviors (free-riding, social loafing and student syndrome), which leads to lower team performance and lower team motivation. In this work I propose the use of reflexive weekly monitoring (RWM) to mitigate these students' bad behaviors that can disrupt team results. The use of the RWM in the past two semesters in a software engineering course, has improved teams' results in terms of both, project and final grades.

Teaching software engineering in a practical course in academia is considered one of the best strategies to help students understand what they will face in industry. Teamwork, coordination, communication are soft skills that are demanded in real life, but how to improve these courses to be more effective and yield better results is not clear. Software engineering - as with most computer careers - is known to be short on women, but the participation of women improves diversity to student teams. Women may have personal characteristics that are different from the ones we normally see among male software engineering students. Do, mixed gender software teams have better project results than one-gender teams? After assisting software engineering courses for four years, I observed mixed gender teams to be better. With this idea in mind I performed a case study where I analyzed the behavior and the results of software projects over nine semesters. The obtained results show that mixed gender teams were more effective and coordinated.

Software engineering has been taught over the years using expositive classes, but learning this discipline requires more than just theory. Lately, universities started teaching software engineering in a theoretical-practical way. Typically, these experiences involve the development of software projects in the academia, using industry-oriented or ad hoc processes. However, most of them are not fully formalized, therefore it is not possible to repeat, measure or improve them. Moreover, it is not clear which project contexts are proper for each ad hoc process. This thesis work proposes to define and formalize a prescriptive software development process for use in undergraduate software engineering courses. We hypothesize that this process can make these experiences repeatable investing an affordable effort and will help produce positive results in student projects. This software process will be evaluated in the context of a second software engineering undergraduate course at the University of Chile, and it will address specific project contexts. This software process could be used in any university that has a similar course context. The proposed process can also be adapted to fit with new contexts.

The software industry and the academia have recognized the importance of teamwork as a driver to succeed in software projects. Therefore, the industry expects that new engineers are able to work in teams. Unfortunately, teamwork is a skill that cannot be transferred in a simple way, and there is not a clear recipe for doing that. This paper proposes the use of particular ThinkLets (a process pattern to address collaboration recurrent problems) to help overcome particular problems that jeopardize teamwork. This proposal has been evaluated through software developments in the academia involving computer science undergraduate students.

Background: Software engineering is a core subject in computing education. Today, there seems to be a consensus that teaching software engineering requires students to perform practical experiences that simulate the work in the software industry. This represents a challenge for universities and instructors, because these experiences are complex to setup and involve considerable time and effort. Although there are several experiences and proposals reported in the literature, there is no clear solution to address this challenge. Aim: Being knowledgeable about the several approaches reported in the literature for dealing with this challenge is the first step to proposing a new solution. Counting on this knowledge allows instructors to reuse lessons learned from other universities. In order to address this challenge, we conducted a systematic mapping study that intends to answer the following questions: What are the main approaches used to address the practical experiences in software engineering education? Is there an emerging tendency to address this challenge? Which software process models are used to support the practical experiences in software engineering courses? Have the universities changed the way of conducting these experiences over the years? What are the main forums to seek information on practical approaches for teaching software engineering? Method: We used a systematic mapping study to identify and classify available research papers that report the use of practical experiences in software engineering education. Results: There were 173 papers selected, analyzed and classified. The results indicate that universities have realized the value of including practical experiences as part of the software engineering teaching process. However, few proposals indicate how to address that challenge. The practical approaches identified in this study were game learning, case studies, simulation, inverted classrooms, maintenance projects, service learning, and open source development. Only one recent report on the use of traditional approaches (i.e., teaching using expositive lectures) was found. The use of a development process to support these practical experiences seems not to be a concern for software engineering instructors. Only 40% of these studies report the use of a development process to guide the process experience. The reported processes are mainly agile methods. Conferences are the most used forum to publish studies in this area (72%). One third of these studies have been published over the last five years. Conclusion: There is a clear concern for teaching software engineering involving practical experiences, and there are several initiatives exploring how to do it. The map gives us an overview of the different proposals to address this challenge, and also allows us to make some preliminary conclusions about the preferred approaches.

The software industry has recognized the importance of teamwork as a driver for good projects results. However teamwork is not an easy goal to reach, because there is a large list of variables affecting the process. Each project probably will require a particular recipe to promote and perform real teamwork. Therefore a one-size fits-all approach does not work to promote teamwork in the software development scenarios. This article presents an influence model that helps the development teams to find a strategy that allow them to carry out teamwork. This model is the result of an analysis conducted by the authors on 27 software projects performed in a controlled setting in an academic environment.