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2024 Working Group Proposals

Below are descriptions of the 10 Working Groups (WG) open for membership applications. Please read the descriptions below, and if you find one, or more, WG you are interested in, use the link (below) to apply to participate. You can apply for one, or two, WGs in one application and you are limited to one application.

Groups that attract a sufficient number of members to create a viable group will proceed and work on their project from late March to the end of the year to produce their research report. Pending satisfactory reviews of the report, it will be published in the Conference Proceedings. 

As a reminder, all members are expected to (a) participate in WG activities from March to November, as needed by your WG, (b) register for the conference (including the WG fee), and (c) be present at the 2024 ITiCSE Conference in Milan. Also, there is a separate WG Conference fee that provides the work space (not lodging) for WGs in Milan as well as lunch and morning and afternoon breaks.

Applying to join a working group

Application Form link: https://forms.gle/qPtEMsjpGZREQ57H6

Application Deadline: 11 March

Membership Decisions expected by: 25 March

Please email (potential) WG Leaders to ask questions about a specific WG (as listed below).

Please email WG Co-Chairs with any/all questions about the process: iticse2024wg@easychair.org 

The proposed working groups:

  1. Computing Education in Africa
  2. A Multi-Institutional-Multi-National Study into the Impacts of AI on Work Practices of IT Professionals and Implications for Computing Students
  3. Experiences of Instructors Who Teach Capstone Courses in the Computing and Information Technology Fields
  4. Curriculum Analysis for Data Systems Education
  5. All for One and One for All – Collaboration in Computing Education: Policy, Practice, and Professional Dispositions
  6. Equity-Minded Computer Science Undergraduate Curriculum
  7. What We Talk About When We Talk About K-12 Computing Education
  8.  Designing a Pedagogical Framework for Developing Abstraction Skills
  9. How Are Instructors Incorporating Generative AI into Teaching Computing?
  10. Improving Code Quality at CS1 Level: Structure, Style and Good Practices

WG 1: Computing Education in Africa

WG Leaders:

  • Sally Hamouda (shamouda@vt.edu)
  • Linda Marshall (lmarshall@cs.up.ac.za)
  • Kate Sanders (ksanders@ric.edu)
  • Ethel Tshukudu (tshukudue@ub.ac.bw)

Motivation and Goals: To increase the visibility of African computing education in the larger ACM community and strengthen connections between researchers inside and outside of Africa, this Working Group (WG) will focus on two tasks: first, writing a literature review of publications related to computing education in Africa, and second, developing sample introductory programming materials designed to connect with and motivate African students at university level. Preference will be given to applicants who have a background related to computing education in Africa, but other interested applicants are also welcome to apply.

Expectations of WG members: As soon as we are notified that the WG will run (in late March), we will schedule an initial meeting for all accepted participants (two, if needed to accommodate different time zones). At the initial meeting(s), after introductions and conversation, we will discuss the WG goals and the work to be done.

Between the initial meeting and the conference in Milan, most of the work will be done online in two subgroups: one focused on a literature review of computing education in Africa and one on developing indigenous course materials for CS1/CS2 (introductory programming and data structures). Each participant will work within one of these subgroups, and each subgroup will include at least one of the organisers. In forming the subgroups, we will attempt to accommodate the participants’ topic preferences, to ensure that neither subgroup spans more than 6-7 time zones, and also to make each subgroup a diverse mix of junior and senior CER researchers. Our goal is for these small, focused subgroups to enable and support engaged participation by all WG members.

The subgroups will each determine how often they need to meet synchronously to meet the milestones for their group, but will be expected to communicate asynchronously (through email and the documents they create online) several times a week. In addition, we plan on one full-group meeting per month of approximately an hour, for conversation and brief progress updates from the subgroups. We have found that a combination of Zoom, Google Drive, Overleaf, and email works well for multi-national groups, but we will adapt this plan as needed.

In Milan, participants will work together face-to-face from July 5-7 to combine the two subgroups’ work into a single draft ready for submission.

Methodology and milestones.

The literature-review subgroup’s milestones are:

  1. agree on one or more queries
  2. divide the work of searching the ACM Digital Library, IEEE XPlore, Scopus, and Google Scholar
  3. compile an initial bib file of potential papers
  4. decide on inclusion/exclusion criteria
  5. review the abstracts, and reduce the set of papers to those which satisfy the inclusion criteria
  6. read the papers closely, looking for themes, patterns, areas of focus, and open questions for future work
  7. write draft sections describing methodology, results, and suggestions for future work, plus an extensive bibliography.

The indigenous-materials subgroup’s milestones are:

  1. identify a short list of introductory programming topics to be covered
  2. select current textbook(s) to be used as context
  3. research the use of indigenous materials in other contexts and the importance of relevant materials generally in motivating students
  4. determine what materials to develop
  5. design and polish them to the point that they are ready for testing in a classroom
  6. write rough drafts of an introduction and related-work section to motivate and provide context for the materials

Our three in-person days in Milan will focus on two main goals: strengthening connections within and across subgroups and pulling the pieces of the report together into a single rough draft. We will also set aside time to discuss future collaborations.

After the conference, the organisers will give interested participants the opportunity for input into the final report, but will take responsibility for ensuring the report is completed and submitted by the appropriate deadlines.

WG 2: A Multi-Institutional-Multi-National Study into the Impacts of AI on Work Practices of IT Professionals and Implications for Computing Students

WG Leaders:

·        Tony Clear (Tony.clear@aut.ac.nz)

·        Åsa Cajander (asa.cajander@it.uu.se)

·        Roger McDermott (roger.mcdermott@rgu.ac.uk)

·        Alison Clear (aclear@eit.ac.nz)

Motivation and Goals: As the pervasive influence of Artificial Intelligence (AI) extends across various industries, its significance in shaping Information Technology (IT) work practices and computing education continues to grow. This coordinated, multinational working group is dedicated to examining the ramifications of AI integration within the IT sector. Employing qualitative research methods and conducting thematic analysis on interview data gathered from IT professionals [i.e. industry practitioners such as software developers] representing diverse contexts, the working group endeavours to uncover profound insights into how AI impacts work engagement, socio-technical dynamics, and the cultivation of professional competencies.

It is anticipated that the outcomes of this collaborative endeavour will serve as valuable guidance for policymaking and curriculum development.

Invitation: We invite experts in thematic analysis, qualitative research methods, and competency-based curricula to join our collaborative research effort to investigate AI’s impact on IT work practices and computing education.  We aim for additional members, some bringing expertise in [generative] artificial intelligence, to benefit from being in the WG and also for them to contribute perhaps by anchoring/contrasting their experience with other countries. Emerging researchers are particularly encouraged to contribute, enriching the diversity of perspectives within the working group.

Methodology: The study has been informed by the literature on work engagement in the context of automation and motivation for IT professionals. 

The working group sits in the context of an overall international study, which has employed an extensive interview study, with an aim of interviewing a total of 20 participants within each country sub-study.  Participants have been identified based on their grouped or specific IT professional roles as classified within the Skills Framework for the Information Age [11] and in addition based on their appropriateness, such as people who have used AI in their work.

These interview transcripts will be available for analysis by working group members for cross function, cross site, cross-country and cross-sector analysis. This data pool will comprise sets of de-identified and unidentifiable transcripts. A common protocol for cross site data sharing will be adhered to, to ensure that any access and analysis adheres to the ethical requirements of each institution involved.

Thematic analysis and synthesis will be used to analyse the collected data, where qualitative content analysis will use a deductive approach, with related work engagement and motivational theories as a foundation.  The theoretical frameworks from the CC2020 report will be adopted to evaluate competencies demanded as a deductive frame.  Each respondent interviewed will constitute a case for analysis.  Cross case comparison will be employed to analyse the commonality of experiences of IT Professionals in similar roles, and to draw contrasts between roles.  While the WG Leaders will lead this process, the WG Members as co-researchers will assist in validating the derivation and allocation of codes and themes.  These strategies will be used to analyse the collected data, understand the experiences of IT Professionals working within a typical set of roles, and to evaluate the impact of AI on the work of IT professionals.

The literature on professional competencies in computing will be drawn upon to analyse and characterise the new needs identified in this analysis.  Further implications for computing curricula design and assessment will be developed from this analysis.

In the event of delays in conducting interviews or making transcriptions available to the team, a strategy for an accompanying literature review (probably multivocal) will be developed.

Proposed work-plan: It is proposed that the WG will work using collaboration technologies such as Zoom or MS-Teams for conducting full team or smaller team meetings, complemented by email, and secure shared repositories for transcripts [e.g. One Drive, MS-Teams or Google Drive]. Working repositories with shared spreadsheets, papers and documents will also be secured for the WG team members. Overleaf or MS-Word [dependent on team preference] may be used for report writing.

Team members will need to sign the common data access protocol to participate.

A schedule for the WG is given below:

        Interviews conducted [ongoing]

•         Set up secure repository structure

•         Members gain access approvals

•         Take stock of Interviews and relevant literature

•         Review and confirm approach to literature review

•         Allocate groupings and sets of interviews to WG members

•         Theme development

•         Themes validated – end April

•         Cross case analysis – cross roles, cross sector, cross site, cross country – end May

•         Develop implications, and conclusions – June – July

•         Meet on site 4 Jul. and work on site 5 July – 7 July

•         Review and confirm implications and conclusions, produce first draft report 7 July.

•         Receive feedback after conference

•         Revise and prepare for review and submit – Aug -Sept

•         Reviews received – Sept/Oct

•         Final revisions and submissions – Nov/Dec

A schedule of expected meetings prior to the conference and milestones or other progress points: It is proposed that the WG will meet regularly [weekly at an agreed time] via Zoom or MS-Teams for conducting full team or [as required at key milestones] and for smaller team meetings.

WG 3: Experiences of Instructors Who Teach Capstone Courses in the Computing and Information Technology Fields

WG Leaders:

  • Sara Hooshangi (shoosh@vt.edu)
  • Asma Shakil (asma.shakil@auckland.ac.nz)
  • Subhasish Dasgupta (dasgupta@gwu.edu)

Abstract: Capstone courses are an integral part of undergraduate and postgraduate degrees in

Computer Science (CS), Information Systems (IS), and Information Technology (IT).

They are designed to help students gain hands-on experience and develop

professional dispositions such as communication skills, teamwork ability, and

self-reflection as they transition into the real world. Prior research on capstone

courses has primarily focused on the students’ experience in these courses. The

experience of instructors who teach CS/IT capstone classes has not been explored

much. However, instructor motivation and expectancy can have a significant effect

on the capstone course quality. In this working group, we plan to use a mixed

method approach to understand the experience of instructors who teach capstone.

Goals

Our working group has three main goals. First, we aim to collect instructor feedback

on the design and delivery of CS/IT capstone courses through a mixed method

research strategy. Next, we aim to develop a framework that applies

expectancy-value theory to CS capstone courses with a view to identify motivational

constructs that influence faculty decisions and pedagogical approaches in capstone

courses. Finally, we aim to provide recommendations for university administrators

and policymakers on supporting and enhancing faculty motivation in teaching

capstone courses. As a member of our working group, you’ll have the chance to

delve into:

  • Reviewing the design and delivery models of CS/IT/IS capstone courses from around the globe.
  • Sharing your insights and experiences to improve capstone course delivery.
  • Conducting surveys, interviews, and case studies with faculty members to identify motivational factors that influence pedagogical approaches in capstone courses.
  • Contributing to recommendations for university administrators and policymakers on supporting faculty teaching capstone courses.

Who Are We Looking For?

  • Academics and educators who have an interest in this topic and have taught capstone courses in IT and CS in the past, are currently teaching, or are interested in teaching in the future.
  • Academics who are able to get data from instructors who are currently teaching or have taught CS/IT-based capstone courses.
  • Researchers with interests in curriculum design, pedagogy, and student engagement.
  • Professionals willing to contribute their expertise and insights into a collective effort.

Working Group Activities:

  • Obtain IRB or ethics approval to conduct qualitative research.
  • Regular virtual meetings to discuss progress and share findings.
  • Collaborative research and analysis on capstone course strategies and outcomes.
  • Development of a report/paper summarizing our insights and recommendations for publication.
  • Members of the working group are expected to attend the conference in-person.

Methodology: A mixed methods study will be used to collect data for this WG.Our work will be

guided by a sequential explanatory approach to study the lived experiences of

instructors and teaching staff who coordinate and run capstone courses at various

institution types and student levels. Using the result of that analysis, we will design

an in-depth qualitative study. We will then develop a framework based on

expectancy-value theory to understand the attainment values, intrinsic factors, and

utility values that collectively influence the pedagogical approaches and motivations

of CS and IT faculty in designing and teaching capstone courses. This would include

practical guidelines and recommendations for support systems to motivate

capstone instructors through different pedagogical approaches.

Meeting frequency: We will meet online twice a month from March to July to discuss logistics, research, and progress on data collection and writing. We will discuss the timeline and set

deadlines for completion of individually assigned work. Our ultimate goal is to have a

comprehensive report of the collected data from the interviews, including qualitative

analysis of faculty perspectives on motivation, challenges, and their approaches to

designing and improving capstone course, ready before the in-person work at ITiCSE

2024 in Milan, Italy.

WG 4: Curriculum Analysis for Data Systems Education

Working group leaders:

Motivation: The field of data systems has seen quick advances due to the popularization of data science, machine learning, and real-time analytics with recommendation systems, chatbots and reverse image search, all of which require efficient infrastructure and data management solutions. This poses new requirements on data science teachers and students. However, it remains unclear (i) which topics are recommended to be included in data systems studies in higher education, (ii) which topics are a part of data systems courses and how they are taught, and (iii) which data-related skills are valued for roles such as software developers, data engineers, and data scientists.

Goals: This working group aims to answer these points to explain the state of data systems education today, and to uncover knowledge gaps and possible discrepancies between recommendations, course implementations, and industry needs. We expect the results to be applicable in tailoring various data systems courses to better cater for the needs of industry, and for teachers to share best practices.

Methodology: The goals of the working group are expected to be achieved in three phases. First, the members will analyze curriculum recommendations related to data systems in higher education. Second, the members will collect data on data systems education course syllabi from various higher education institutions via an online survey. Based on the results of the first two phases, we will design an interview or survey setup to gather the opinions of industry professionals on this topic too. Finally, the members will compare the possible agreements and disagreements between curriculum recommendations, course topics, and the opinions of industry professionals.

Expectations for group members: We estimate contributions of three to four hours per week from mid-March to early July, including weekly online meetings for pre-conference work. We expect to have completed the data collection and analysis and discussion of the first two phases prior to the conference. We expect all members to attend the pre-conference working days on-site (July 5th to July 7th). Similarly to pre-conference work, we expect all members to work three to four hours per week from August to October in analyzing the data for phase three and writing the working group report.

All members are expected to contribute to data collection and acquire ethics approvals from their institutions. We welcome group members with various backgrounds, and researchers, educators, junior and senior academics alike. We hope that members bring their expertise, enthusiasm, and commitment to data systems so that we can achieve meaningful results together.

WG 5: All for One and One for All – Collaboration in Computing Education: Policy, Practice, and Professional Dispositions

WG Leaders:

  • Rita Garcia (rita.garcia@vuw.ac.nz)
  • Andrew Csizmadia (a.p.csizmadia@newman.ac.uk)
  • Jan Pearce (jan_pearce@berea.edu)

Motivation: The ITiCSE ’23 final keynote raised teaching soft skills, or professional dispositions, to help students face challenges in modern programming approaches. This ITiCSE ’24 working group is focused on helping computing students develop professional dispositions through collaborative learning (CL). From some members of the industry’s perspective, recent graduates frequently struggle in the workplace due to their fragile professional dispositions. We are motivated to understand professional expectations from recent graduates and present the academia-industry gap to promote a positive influence of change in CL practice and policy. 

Approach and Expected Outcomes: The project will conduct two literature reviews. The first identifies CL practices that support professional dispositions in Computing Education, as well as those that consider aspects of Diversity, Equity, Inclusion, and Accessibility (DEIA). The second determines the high-tech industry’s expectations regarding professional dispositions from recent graduates to determine how these expectations align with academia’s CL practices and policy. We will also conduct a multi-national survey with high-tech industry organisations, giving a contemporary, global perspective to their expectations of professional dispositions from recent graduates. 

Contributions: Our contributions support practitioners and researchers in advancing CL in Computing Education, encouraging positive curricula and policy changes that support aspects of DEIA. To assist practitioners in adoption, we will present CL practices with the professional dispositions they help to develop. We will present the academia-industry gap in CL for future research opportunities, helping researchers advance CL practices to integrate professional dispositions the industry expects from recent graduates.

Expectations of Members: We seek individuals interested in researching collaboration from an academic or an industry perspective. We also welcome researchers with industry connections to invite them to participate in the survey. In this project, members will perform literature reviews and/or conduct the project’s survey, which includes analysing survey data and using cluster analysis on the literature reviews. Members will use mixed methods research to analyse the collected data. We have already received ethics (IRB) approval to survey high-tech industry organisations.

The Working Group (WG) will have members in three subgroups:

  1. Academia Literature Review – Identify and examine literature on CL approaches and strategies applied in learning environments.
  2. Industry Literature Review – Identify and examine the literature on the industry’s expectations on professional dispositions from recent graduates.
  3. Industry Survey – Conduct and analyse a survey involving high-tech organisations to get their perspectives on professional dispositions from recent graduates.

Our goal is equal coverage across the subgroups, but members can work across them.

The WG will use video conferencing software for asynchronous communication to address the members’ different time zones. We will meet weekly, offering two virtual meetings to accommodate the globally distributed group.

In your application, please explain your interest in this WG and the subgroup(s) of interest to you. Please include your experience and/or background in the application and how it relates to this Working Group’s goals.  

WG 6:  Equity-Minded Computer Science Undergraduate Curriculum

WG Leaders: 

  • Alice Gao, University of Toronto (ax.gao@utoronto.ca)
  • Giulia Toti, University of British Columbia (giulia.toti@ubc.ca)
  • Peggy Lindner, University of Houston (plindner@central.uh.edu)
  • Ouldooz Baghban Karimi, Simon Fraser University (ouldooz@sfu.ca)

Motivation: One of the less explored approaches to equity, diversity, and inclusion (EDI) in computer science is through changes to the curriculum. Despite sporadic work on adopting Culturally Responsive Computing (CRC), the inclusion of equity-minded courses, or modifications on specific elements of the curriculum, such as introductory programming courses, there has never been wide exploration or adoption of a successful equity-minded computer science curriculum.

In this work, we will divide the undergraduate Computer Science (CS) curriculum into upper division (UD), lower division (LD), and service courses (SC). We will explore the design and adoption of successful equity-minded approaches for each level, focusing on their motivation, cultural relevance, and rigour.

Objectives and Methodology: We aim to investigate existing efforts on equity-minded curriculum design in undergraduate computer science programs and examine their effectiveness. We ask:

(1) What are examples of equity-minded curriculum design efforts in undergraduate computer science programs?

(2) What are the outcomes of these equity-minded curriculum design efforts?

(3) What are possible ways in which undergraduate computer science programs can adopt equity-minded curricula?

To answer these questions, we intend to explore undergraduate curricula in computer science programs worldwide, emphasizing North America, that have shown relative success in attracting and retaining women and historically marginalized groups. This will be performed through a literature review of experience reports, scientific published work on the topic reported by these institutions, and public resource data, such as publicly available information on degree requirements, offered courses, course information, and syllabi in relevant programs. We will formulate the factors impacting the effectiveness of these programs for achieving equity, diversity, and inclusion and their student populations.

We will then integrate the knowledge from the literature through surveys, interviews, and case studies to better understand the students’ perspectives. By surveying students, we hope to gather examples of efforts that helped to raise their interest, engage them in their program, or motivate them to pursue CS studies. The students’ responses will be paired with the information provided by the literature to identify and propose recommendations for best practices in equity-minded curriculum design based on our findings.

Group Plan and Members: We are planning for 3-4 hours of work per week from April to July. This includes a one-hour online meeting. We expect all members to attend the pre-conference intensive working days in person. We also expect 3-4 hours per week from July to November for addressing the review comments.

All members are expected to be involved in data collection and analysis and receive the required unified ethics approval and/or those from their host institutions.

We seek collaborators with experience or interest in curriculum design, EDI initiatives, computer science research, and data-driven research. We welcome collaborators motivated to perform high-quality research who bring their experience, expertise, enthusiasm and commitment to achieve meaningful results, take and own a part of the work they are passionate about, and contribute to our group research and learning together.

WG 7: What We Talk About When We Talk About K-12 Computing Education

WG Leaders:

  • Carsten Schulte (carsten.schulte@uni-paderborn.de)
  • Sue Sentance (ss2600@cam.ac.uk)
  • Sören Sparmann (soeren.sparmann@uni-paderborn.de)

Motivation and Goals

K-12 computing education research is a rapidly growing field of research, both driven by and driving the implementation of computing as a school and extra-curricular subject globally. In the context of discipline-based education research, it is a new and emerging field, drawing on fields such as mathematics and science education research for inspiration and theoretical bases. The urgency around investigating effective teaching and learning in computing in school alongside broadening participation has led to much of the field being focused on empirical research. Less attention has been paid to the underlying philosophical assumptions informing the discipline, which might include a critical examination of the rationale for K-12 computing education, its goals and perspectives, and associated inherent values and beliefs. In this working group, we will conduct an analysis of the implicit and hidden values, perspectives and goals underpinning computing education at school in order to shed light on the question of what we are talking about when we talk about K-12 computing education.

The overarching goals are to:

  • Identify, characterise and label different philosophies of computing education
  • Develop a framework to express an underlying philosophy, with examples
  • Propose a further research agenda that considers the practical applicability of the framework in schools

Methodology

The general approach by the WG will be to use an analysis of existing research literature to achieve the goals set out above. To increase the efficiency and depth of our literature analysis, we plan to use natural language processing (NLP) techniques. 

The work will take place in four stages:

Literature search: we will conduct a broad search to identify relevant papers with an explication of computing education philosophy, underlying values or beliefs.
Analysis: having identified a set of papers, we will analyse them to identify themes aligned to the goals of the project.
Build framework: we will build a framework that represents the findings of the analysis, to be presented in a diagrammatic form (see this previous ITiCSE working group report as an example).
Develop use cases: a follow-up analysis of the literature together with current curricula and resource frameworks in K-12 will lead to a set of use cases for the framework, illustrating how different values and beliefs are evident in research and practice. 

Potential WG members

We are looking for researchers with some of the following skills or interests:

  • Experience of different local contexts (we are hoping for a geographically diverse group)
  • K-12 computing education research experience
  • Experience of literature synthesis
  • Innovative approaches to literature searches and analysis, particularly drawing on NLP
  • Theoretical or philosophical perspectives on computing education

WG activities

We will hold monthly online 2-hour meetings focused on specific aspects of the work and anticipate that WG participants can set aside time to work on tasks in between meetings. 

Before the conference: The work to be undertaken in this period will include collecting papers from a wide-ranging search. We anticipate using NLP methods including word embedding, vector representations and topic modelling to search through a large number of papers using education databases and examine sentiment, value-laden terms and justification-related vocabulary within the papers. Also within the pre-ITiCSE period, we intend to start to create a draft framework to represent the findings to date. 

During the conference: we will meet in-person to further develop the draft framework and identify use cases and examples to make it less abstract. Different members of the WG will be able to focus on data analysis, presenting the framework visually, writing up our findings, and developing use cases. 

After the conference: the WG will continue to meet online to finalise the outputs and plan and write the full WG report. 

Expectations of WG members

We expect that WG members will be able to attend monthly online meetings, with additional meetings for sub-groups, and to be able to set aside time for the pre and post-ITiCSE tasks. 

WG8: Designing a Pedagogical Framework for Developing Abstraction Skills

Working Group Leaders

•    Marjahan Begum, marjahan.begum@city.ac.uk

•    Julia Crossley, julia.crossley.2@city.ac.uk

•    Filip Stromback, filip.stromback@liu.se

 Motivation and goals

The purpose of this working group is to apply current research findings in abstraction to the development of a pedagogical framework underpinned by constructivism. This working group is motivated by the fact it is difficult to teach and difficult to understand and apply in problem solving scenarios in CS1, CS2 and CS3. Our current definition of define pedagogical framework involves:

  •  instructional design and practices (e.g. creation activities, comprehension, debugging and testing, pair- programming);
  •  learning and conceptualized models of abstraction (such as the Block model, Sfard’s model and Fyfe’s CRA framework);
  •  tools and problems that are suitable for developing and assessing abstraction skills.

We will explore the broad question of how to encourage the transfer of abstraction skills in a practical setting and how to assess whether thresholds in competency have been met. We will meet regularly 1.5 hours a week from April to July. We will repeat this meeting once so members in different zones can contribute. All members will be expected to take on specific tasks to work on, whether individually or in pairs. Specific tasks would be:

  • agreeing on the key literature we have found;
  • discussing, identifying and analyzing models that aligns with members’ perspectives
  • focusing on identifying pedagogical tools.

The 1.5 hours will serve three purposes:

1. giving updates on what has been done and discuss the out- come of those tasks;

2.   giving feedback to other members on outcome of tasks;

3.   deciding on subsequent steps to maintain progress.

Given the possible time differences, communication may need to be asynchronous, through minuted meetings.

Inclusion criteria for members

Selection of members will take into account the holistic needs of the group. We will expect members to fit both essential requirements and at least one desirable requirement.

Selection criteria Member type Role within the Working Group 
Interests in working with theoretical models of computational abstraction within an educational context. All members of the WG. To demonstrate an active and clear interest in improving the academic experience of computing students. Essential. 
Willingness to collect and share relevant empirical data, whether in situ or within the time frame of the working group. All members of the WG. To bring student responses to exercises in various formats that can be analyzed within the models of abstraction; if the member is not currently doing any teaching the data could be through past exams scripts, coursework or from a large set of data. Essential. 
Experience of research into abstraction in computer science education.  These are members who are familiar with the literature in CS education. CER researchers. To contribute relevant and exhaustive literature. Desirable. 
Experience of teaching  modules/courses that requires the development of abstraction skills (algorithm and data structures and/or algorithm design, programming). Educators. To give experiential advice based on their teaching. Desirable. 
Research expertise in theoretical areas of Computer Science. CS researchers. To give advice on the suitability of models, tools and data for the teaching and learning of computational skills. Desirable. 

  Requirements of the Working Group

  • Attending one of the two weekly 60-90 minute meetings.
  • Collecting, sharing and discussing empirical data that will be analyzed qualitatively.
  • Registration at the ITiCSE ’24 conference.
  • Attendance to the working group at ITiCSE ’24 in Milan; the format will be hybrid and will take place from the 5th to 7th of July.

How to apply 

Please use the standard application form on the conference website to apply, specifying how you will meet the essential requirements and how you meet one of the desirables.

WG9: How Are Instructors Incorporating Generative AI into Teaching Computing?

WG Leaders:

  • James Prather (james.prather@acu.edu)
  • Juho Leinonen (juho.2.leinonen@aalto.fi)
  • Natalie Kiesler (kiesler@dipf.de)

Generative AI (GenAI) has seen great advancements in the past two years and the conversation around adoption is increasing. Widely available GenAI tools that could impact that classroom can write and explain code based on minimal student prompting. While most acknowledge that there is no way to stop students from using such tools, a consensus has yet to form on how students should use them if they choose to do so. At the same time, researchers have begun to introduce a slate of new pedagogical tools that integrate GenAI into computing curricula. These new teaching-focused tools offer students help like a TA or attempt to teach them prompting skills without undercutting code comprehension. This working group aims to detail the current landscape of education-focused GenAI tools, present gaps where new tools could appear, and provide a guide for instructors to utilize as they continue to adapt to the era of generative AI.

Expectations from members: 

Before the conference: We expect members to attend regular meetings before the conference (twice a month), and to work on data collection (conduct interviews, literature review, and identity gaps in current approaches). We also expect everyone to contribute to writing a first draft. We intend to work in subgroups, thereby trying to accommodate members in different time zones.

During the conference: All members are expected to physically attend the conference during the intensive working group time. During this time, all members are expected to contribute to writing the draft. Our goal is to have a complete draft by the end of the working group time.

After the conference: We expect members to help polish the draft to submit for the final deadline in September, and attend individually agreed meetings if any are needed. Finally, if the working group paper is accepted, we expect members to help address the feedback from reviewers in October/November for the final camera-ready submission.

WG10: Improving Code Quality at CS1 Level: Structure, Style and Good Practices

WG Leaders

Cruz Izu  ( cruz.izu@adelaide.edu.au )

Claudio Mirolo ( claudio.mirolo@uniud.it )

Rodrigo Duran ( rodrigo.duran@ifms.edu.br )

Motivation & Goals

Education research has covered in depth novices’ misconceptions that cause incorrect code. On the other hand, characterizing the quality of correct solutions is still a challenge since educators, developers and students give different emphasis to different aspects such as coding style, naming, documentation, comprehensibility, structure, modularity, robustness, performance, testability, maintainability, etc. Although attention to this topic appears to be growing, up to now limited research has focused on the quality of novice code.

Recently, a number of educators have urged to address code quality earlier and more thoroughly in the CS curricula. However, the lack of materials and the time constraints to cover programming topics have slowed down progress in that regard.

Thus, a major goal of this working group is to identify manageable ways to discuss code quality in the CS1 classroom, with particular focus on activities that help students to become aware of and improve the quality of their code.

Methodology & Expected outcomes

The WG would direct their collaborative effort towards three main tasks:

(1) A literature review of reported quality issues/defects at introductory level, as well as related instructional strategies and resources.

(2) The design and submission of a survey addressed to CS1 instructors in order to explore their views about code quality issues and if/how they deal with them.

(3) Development of a taxonomy of code quality issues and a small set of associated teaching materials appropriate for CS1 level.

The main expected outcomes are:

– An extended bibliography relative to the topic;

– A taxonomy of code quality issues;

– A sample list of materials intended to improve the quality of code design (planning), code structure (refactoring) and code style (good practices).

Proposed working plan 

1. The literature review is a key element of the pre-conference work, to be commenced as soon as feasible. The implied subtasks include: choosing the source libraries, selecting appropriate search keys, filtering the resulting dataset (by reading titles and abstracts), reviewing the relevant references, snowballing. Conceivably, the preparatory decisions are to be made collectively, whereas the workload of reviewing the bib items should be subdivided among individual participants, but with a second researcher checking the outcome of the filtering step.

2. The instructor survey would be meant to reveal the extent to which they actually address this topic in their classes, their approach to code quality instruction and assessment.

To this aim, all participants in the WG should discuss the appropriate structure and questions of the survey, as well as identify the channels to circulate the instrument. We would aim to circulate the survey in May/June, so that data can be pre-processed for group analysis and discussion on-site.

3. The quality issues emerging from the previous tasks will then be classified in terms of involved programming aspects, relevance/severity and potential strategies to remedy them.

Since the assessment of code quality is subjective, depending on the instructor’s goals, prior experience, and context, we expect this task will generate a level of discussion within the WG.

Conceivably, this and the analysis of the surveys will constitute the bulk of the on-site work, while the results of the on-site discussion will be polished as part of the post-conference work.

Meeting frequency: possibly a general meeting once a month and subgroups meetings every second week/according to the needs.

Membership recruitment

We hope to attract a diverse range of researchers, from different locations and at different career stages, who will help the WG to capture worldwide perspectives and practices of teaching code quality.

If you consider applying, your education research should somehow be linked in a broad sense to the topic at hand; for instance, you may have thought about how to address code quality at some point at CS1 or CS2 level, or you may have experimented with assessing a code quality component, or your research has found good or poor examples of student code that you would like to share and discuss further.

Please use the standard application form on the conference website to apply. In your application, please explain your interest in the Working Group goals; you may describe any code quality issues that are of particular interest to you. You should also include a brief summary of your teaching and/or research experience and how it relates to this Working Group’s goals.