CLOSED: Call for Papers: Special Issue on AI in SEE&T
IEEE Software seeks submissions for this upcoming special issue.
Share this on:
Submissions Due: 30 August 2023
Abstract Submission: 30 August 2023
Submission Deadline: 30 August 2023
Final Decisions: 17 November 2023
Camera-Ready: 1 December 2023
Publication: March/April 2024 (tentative)
The demands placed on software engineers have increased dramatically in recent years. This is because the systems they develop increased in complexity, size, and criticality. Novel system types like adaptive systems or cyber physical systems and new technologies, in particular Artificial Intelligence change the technology landscape. Professionals creating such systems hence need to stay on the cutting edge to face the challenges of the future. We need to enable future generations and current software engineers not only to meet contemporary demands, but also prepare them for challenges and competencies that are unforeseen today. This is the mission of Software Engineering Education and Training (SEE&T) research. For more than 30 years, SEE&T efforts at the undergraduate, graduate, postgraduate, and professional level have explored challenges, shared experiences, and generated new impulses for educators. While in early work, emphasis was placed on the role of software engineers and the question of how SEE&T fits into a larger engineering or computer science curriculum, lately special emphasis is on knowledge transfer and pedagogical paradigms between educators, experiential instruction, and sensitizing the learner for industrial challenges.
The aim of this IEEE Software Special Issue is to solicit, review, and publish original high-quality research, tutorial, and survey articles in SE Education at the undergraduate, graduate, and postgraduate level, as well as SE Training in industrial or post-academic settings. Contributions of all areas of SEE&T with a focus on Artificial Intelligence are desired. Submissions pertaining to SEE&T at large, particularly programming instruction will be considered if they have a clear focus on instructional methods. Tool proposals will be considered as well, however papers with a focus on approaches and techniques presenting data and/or experiences will be preferentially accepted. Priority will be given to high-impact papers with a strong focus on industry training, university cooperation with industry, or research in practical and industrial contexts. The list below indicates areas of SEE&T in the focus of the Special Issue. Submissions on additional topics consistent with the central theme of the Special Issue are also welcome.
Leveraging Artificial Intelligence to teach SE
Project-based Learning with AI / for AI
Cooperation Between Industry and Academia
Degree Specializations for AI
AI-based improvement of pedagogyInstructing students in AI technologies
Software Engineering Education Methodology
Open Source AI tools in Education
Innovative CS and SE Education: Perspectives, Progress, and Industry Perspectives
Vision For SEE&T in the Future
Novel Delivery Methods
Interdisciplinary Education and Training Programs
Cooperative Education and Networks of Training among Universities and Industry
Teaching formal methods
Teaching “real world” SE and AI practices
This special issue will be the second in a series of IEEE Software SIs on SEE&T. Given the prevalence of AI technologies and their applicability in pedagogy are the driving motivators for this special issue.
Manuscripts must not exceed 4,200 words, including figures and tables, which count for 250 words each. Submissions in excess of these limits may be rejected without refereeing. The articles we deem within the theme and scope will be peer reviewed and are subject to editing for magazine style, clarity, organization, and space. Be sure to include the name of the theme you’re submitting for. Articles should have a practical orientation and be written in a style accessible to practitioners. Overly complex, purely research-oriented, or highly theoretical aren’t appropriate, however articles providing scientific evidence are welcome if they focus on practical and industrial contexts. IEEE Software doesn’t republish material published previously in other venues, including other periodicals and formal conference or workshop proceedings, whether previous publication was in print or electronic form. See the link below for submission instructions and the link to the submission system.