Working groups are formed by participants with a common interest in a topic related to the subject matter of the conference. The groups of 5 to about 10 participants work together electronically before the start of the conference. Working groups convene on the Friday evening before the conference, and start face-to-face work in their sessions the following day, Saturday, at 9am. Group members are expected to work together for the whole of Saturday and Sunday, and continue their work throughout the conference, which runs from Monday to Wednesday. However, members are able to attend some conference sessions and the Tuesday afternoon excursion if they wish.
Every working group member must register for and be present at the conference in order to be considered a contributor to the final report. Participants present their preliminary results to conference attendees at a special working group presentation session, and submit a final report after the conference concludes. Final reports are refereed and, if accepted, are published in the ACM Digital Library.
Researchers interested in joining a Working Group must apply for membership up to March 31 . Please see the Working Group general page for details on how to apply.
Working groups have been formed! All 10 of the proposed working groups (listed below) have the requisite number of members to proceed.
Climate change is the defining environmental challenge now facing our planet. Babies born today will be 22 when global warming reaches 1.5 C, according to the latest IPCC report and forecasts. What will life be like in 2040? How do we as educators respond today, to the challenges that lie ahead for the next generation?
How do our practices evolve to take global climate change into account?How do we as educators respond when we see the impact our products have on climate change and the environment? Is it enough to relegate sustainability and climate change to a required course or can we begin to imagine sustainability as a conversation across the entire curriculum?
In this working group, we will collaboratively review the literature, and gather, assemble and compile sample syllabi, case studies, and assignments that address climate change in the context of computer science education. We will work together to think through how best to equip our students with the tools needed to adapt to a world shaped by climate change.
This working group asserts that Program Comprehension (PC) plays a critical part in the writing process. For example, this abstract is written from a basic draft that we have edited and revised until it clearly presents our idea. Similarly, a program is written in an incremental manner, with each step being tested, debugged and extended until the program achieves its goal. Novice programmers should develop their program comprehension as they learn to code, so that they are able to read and reason about code while they are writing it. To foster such competencies our group has identified two main goals: (1) to collect and define learning activities that explicitly cover key components of program comprehension and (2) to define possible learning trajectories that will guide teachers using those learning activities in their CS0/CS1courses.
We plan to achieve these goals as follows:
Step 1 – Review of the current state of research and development by analysing literature on classroom activities that improve program comprehension.
Step 2 – Concurrently, survey CS1 lecturers at various institutions on their use of workshop activities to foster PC.
Step 3 – Use the outputs from both activities to define and conceptualise what is meant by PC in the context of novice programmers.
Step 4 – Catalogue of learning activities with regard to their prerequisites, intended learning outcomes and additional special characteristics.
Step 5 – Develop a map of learning activities and thereby also models of probable learning trajectories.
Vast numbers of publications in computing education begin with the premise that programming is hard to learn and hard to teach. Many papers note that failure rates in computing courses, and particularly in introductory programming courses, are higher than their institutions would like. Two highly distinct research projects have established that average success rates in introductory programming courses world-wide are in the region of 67%.
However, there is little published work comparing pass rates in computing courses with those in other STEM disciplines. As some institutions continually ask computing educators to justify the atypical failure rates in their courses, a thoroughly researched comparison of this sort could prove useful in demonstrating whether the phenomenon is real, and, if so, whether it extends somewhat beyond the boundaries of individual institutions.
This working group will gather information on pass rates in computing courses, particularly introductory programming courses, and in courses at comparable levels in other STEM disciplines. Members of the group will be required to gather the information from their own institutions, and further data will be gathered by way of a broad survey. The data will be analysed to see whether global patterns can be established, and the group will survey the literature to gather and summarise postulated explanations for any difference between pass rates in computing and in other STEM disciplines.
Applicants to join the working group should describe how they will gather the five years of data from their own institution, and what other STEM courses will be included.
Over the past two decades, data science or data analytics degree programs have begun to emerge, reflecting the world’s demand for data specialists to make sense of the vast amounts of data being collected in the sciences, business, engineering and other domains. As degree creation has occurred mainly due to demand, ACM and other professional bodies have recently stepped in to begin the process of providing curricular guidance to this field. However, no shared global framework for data science as an academic discipline exists, making growth unfocused and driven by employer demands. Because of the lack of a globally accepted reference model, new data science programs have been on their own to conceptualize, design, package and market their programs. Due to overlaps between artificial intelligence and data science, joint degrees in the two have also begun to be developed. This working group will build on prior efforts and participant experiences to develop a taxonomy of approaches to data science education, outline its dimensions, and develop a corresponding global reference model.
Computer Science Education research is built on the use of suitable methods within appropriate theoretical frameworks to provide guidance and solutions for our discipline, in a way that is rigorous and repeatable. However, the scale of theory covered is well beyond the CS discipline and includes educational theory, behavioural psychology, statistics, economics, and game theory, among others. A CS Ed researcher’s journey to relevant and discipline relevant theory can be challenging and, when a researcher has learned one area of theory, it can be easy to return to familiar theory, as it may not be clear what a next step could be. The Periodic Table is a visual arrangement of the elements to group like with like and provide insight into how families of elements will react. Could we do the same with learning theories located in the domain of computer science education and would it be useful?
The working group will (1) identify and survey existing literature on relationships between key areas of theory in CS Education, (2) identify ways of organising these research areas to show how knowledge of one could assist another, (3) use existing research in visualisation and data organisation to consider whether these can be represented graphically, and (4) produce initial graphical representations of theory and their relationship groupings. The outcome of this working group will be a report.
There has been a growing interest and increase in the body of work being shared about national K-12 Computer Science Education (CSED) curriculum and implementation efforts to support the introduction of CSED curriculum into formal primary and secondary (K-12) schooling around the world. Much of this work focuses on curriculum analysis, country reports, experience reports and case studies.
The K-12 CSED community would benefit from an international strategic effort to compare, contrast and monitor K-12 CSED over time, across multiple countries and regions, to understand pedagogy, practice, resources, experiences and equity from the perspective of teachers working in classrooms. This calls for an international research effort to develop validated instruments and a robust strategy that can guide comparable investigations into the current state of K-12 CSED in schools, establishing opportunities for longitudinal and international research collaboration.
This Working Group aims to establish a consistent and collective effort to collect data about CSED implementation and practice in K-12 schools. Prior to the conference, the Group will collaborate on the development of a standardised template for presenting “country reports” and an international teacher survey instrument for collecting data about K-12 CSED in schools. A pilot of the survey will be administered to K-12 teacher cohorts by authors for their respective country. The Working Group will analyse, compare and contrast survey findings across countries. In the report, we will summarise our findings and make the instruments available as open-source.
Cloud computing continues to be important in higher education, as it is becoming the common infrastructure for advanced technology. However, finding high-quality materials to teach cloud concepts is an ongoing challenge.
A 2018 Working Group created a report that among other things described fourteen Knowledge Areas (KAs) for teaching cloud concepts. Each of these KAs had numerous Learning Objectives (LOs) included. But that report is only the beginning of creating a framework that can both adapt to changes in the field and provide faculty with current resources.
The next working group will respond to both of these issues by expanding on the KAs. In particular, it will:
We envision this will ultimately provide a framework similar to either NICE, TCPP Curriculum, or CSinParallel.
We will also entertain the possibility of having a community website for hands-on modules that can be integrated into curricula, and building a repository of assignments following the recent nifty/peachy assignments model.
Recent global demand for cybersecurity professionals is promising, with the U.S. job growth rate of 28%, three times the national average . Lacking qualified applicants, many organizations struggle to fill open positions . In a global survey of 2,300 security managers, 59% of their security positions were unfilled despite 82% anticipating cyberattacks to their systems . Cybersecurity fields are broadening not only in technical concepts, but human factors, business processes, and international law. However, security positions have not become culturally diversified, with only 24.9% women, 12.3% African American, and 6.8% of Latino professionals hired in 2018 . An opportunity arises in higher education: to diversify the profession while increasing the numbers of skilled computer scientists. New and integrated methods of attracting student populations in the field of cybersecurity are needed. The working group goal is to evaluate the effectiveness of methodologies that international higher education use to diversify the field of cybersecurity. This group will build upon past ITiCSE cybersecurity endeavors by expanding cybersecurity development to engage a diverse undergraduate program and interests.
The primary goals of this working group are to complete:
We propose a working group to investigate methods of proper placement of university entrance-level students into introductory computer science courses. The main issues are the following.
We perceive the current advanced placement exams offered by organizations such as The College Board to be inadequate for our purposes because they are language specific and they test the results of taking a standardized course. Their exams are not intended to determine whether or not a student who has not been exposed to computing or has been exposed to a different computing paradigm or language would be able to grasp completely new concepts quickly.
Members of the group will collect evidence-based research on freshman college student readiness, the utility of so-called “placement” and “entrance” exams, and actual exams employed by universities. Admission to the group will be determined largely by the documented ability of the applicant to collect such information and/or to be able to contribute to the anticipated intense debates that will be part of the work.
Compiler error messages have been researched for over 40 years with one obvious consensus: they present substantial difficulty and could be more effective, particularly for novices. They are often vague, imprecise, confusing and at times seemingly incorrect. Unfortunately, drawing any other conclusion from this history of research is difficult. Various studies have analyzed the types and frequency of Compiler Error Messages (CEMs) that students generate; others have explored how `standard’ error messages can be enhanced to make them more usable; and others have sought to determine how the effectiveness of CEMs can be measured.
Despite increased interest in the area in recent years, this literature is quite scattered and has not been brought together in any digestible form. For instance, the difficulties CEMs present have not been comprehensively analyzed. Additionally, many sets of CEM design guidelines (explicit and implicit) exist but they span several decades and many of them are conflicting, leaving the way forward unclear. Also, many works have presented evidence on CEM effectiveness (or lack thereof), and this too is often conflicting. We argue that before the community proceeds with more work on CEMs, these guidelines and this evidence need to be presented in a state-of-the-art report. This work can serve as a starting point for those who wish to design better Compiler Error Messages or measure their effectiveness, more effectively.