Call for Papers – Education Track

Paper Categories

• Research Papers - A research paper must address a topic related to software engineering and education using appropriate research techniques and proper scholarly writing. Within the context of the topics of interest for this call for papers, papers in this category must follow rigorous standards, describing research questions, hypotheses, methods, results, and limitations, as is typical and expected of research studies. Therefore, papers such as controlled experiments, surveys, qualitative studies, case studies are expected. Negative and mixed findings are acceptable.
• Experience Reports - Papers must describe the use of an intervention, course or education/training experience in Software Engineering, detailing the theoretical bases of the approach, the context of use and providing a rich reflection on what worked or did not work and why what, but the paper does not need to evaluate the experience or use rigorous research methods to support its claims. It is essential that papers in this category bring enough detail to allow the approach presented to be replicated by other professors. Negative and mixed findings are acceptable provided they can support advice or lessons learned.
• Replication Paper - A replication paper describes the repetition of an existing and already published pedagogical intervention (e.g. course, approach, study, education, training experience) in new contexts. The goal is to determine if the basic findings related to the original pedagogical intervention can be applied to other circumstances. Negative and mixed findings are acceptable provided they can support advice or lessons learned.

Evaluation Criteria

• Research Papers will be evaluated against these criteria: Relevance, Significance, Soundness, Verifiability, Presentation
• Experience Reports will be evaluated against these criteria: Relevance, Significance, Actionability, Lessons, Presentation
• Replication Papers will be evaluated against these criteria: Relevance, Significance, Soundness, Presentation

• Relevance: The extent to which the paper is relevant to SBES Education track to enhance the body of knowledge on challenges, good practices, experiences, and innovations in Software Engineering education and training.
• Significance: The extent to which the paper is well-motivated and its contributions are original or important, with respect to the existing literature on software engineering education and training.
• Soundness: The extent to which the paper’s contributions are supported by rigorous application of appropriate research methods and whether the paper discusses meaningfully the research methods’ limitations and threats to the validity of the findings.
• Verifiability: The extent to which the paper includes sufficient information to support independent verification or replication of the paper’s claimed contributions. This includes public availability of research data or an explicit statement why such data cannot be made publicly available.
• Actionability: The extent to which the paper provides actionable advice with clear take-away messages.
• Lessons: The extent to which the paper meaningfully discusses lessons learned in terms of what went right, what went wrong, and what could be improved if the experience is repeated.
• Presentation: The extent to which the paper’s organization and quality of writing is up to the standard: the paper is well-structured, employs clear and correct scholarly language, avoids ambiguity, includes clearly readable figures and tables, and is appropriately formatted.

Important Dates

Topics of Interest

• On-site, Hybrid, or Remote education and training of Software Engineering after the COVID-19 pandemic, highlighting changes in the teaching-learning process;
• Education and Training Software Engineering through active learning methodologies: Problem-based Learning, Project-based Learning, Challenge-based Learning, Flipped Classroom, among others;
• Good practices and innovative practices for education and training Software Engineering;
• Curriculum or innovative course projects;
• Education and training Software Engineering in the context of different undergraduate and graduate courses;
• Education and training methods, techniques, and tools for software development;
• Education and training Software Engineering in informal environments, such as hackathons and Stack overflow;
• Emerging educational environments for Software Engineering, such as online learning;
• Teaching/learning experiences using approaches in practical Software Engineering scenarios, such as: agile methods, open source, distributed software development, cloud computing, big data, mobile devices, embedded systems, robotics, machine learning and others;
• Tools and methods for evaluating Software Engineering learning;
• Teaching/learning of human, political, ethical, legal, professional, and social aspects in Software Engineering;
• Integration of practical experiences in Software Engineering education and training;
• Integration between research and education of Software Engineering;
• Interdisciplinarity in Software Engineering Education and Training;
• Innovative methods that promote study and encourage instructors´' learning, keeping them updated for education and training Software Engineering;
• Education and training in Software Engineering that encourages entrepreneurship, especially the creation of startups;
• Research on equality, diversity, and inclusion in Software Engineering education and training;
• Open source in Software Engineering education and training;
• Education and training of emerging topics in Software Engineering.

Open Science Policies

About the use of AI (Artificial Intelligence) or AI-assisted technologies in submitted work

• List Generative AI tools and technologies, such as ChatGPT, as paper authors.
• Use texts or sections entirely produced by generative AI tools.

• Use generative AI tools to create parts of the content, with mention in the paper acknowledgments indicating what was generated and which tool was used. It is essential to check the terms of use of the tool, which is the responsibility of the paper's authors. For example, in the acknowledgments: ChatGPT was used to generate the first paragraph of Section 3 and Table 3.2.

• Use AI or AI-assisted technologies to improve the quality of images in terms of contrast and clarity;
• Utilize generative AI tools to edit and improve the quality of your existing text (similar to an assistant like Grammarly to improve spelling, grammar, punctuation, clarity, and engagement).

Paper Preparation and Submission

• Paper registration: The title, authors, abstract, topics of interest, and language of the paper must be informed.
• Submission of the complete paper: You must submit the file in PDF format containing the paper.

Optional Anonymization

• Citations to related work by the authors themselves must be written in the third person. For example, you should write "the previous work by Silva et al." instead of "our earlier work". As a heuristic, look for occurrences of identifiers such as: "we", "our", "GitHub", "funding", "University", etc., in the paper and modify these words before submitting it.
• The submitted paper must not mention artifacts in repositories or websites that allow the identification of authors. The availability of artifacts related to the paper must be made anonymously;
• If the submitted paper presents an evolution of a previous work, the reference to this work can be anonymized. For example, "based on work by Silva et al." can be replaced with "based on our previous work [Ref]" and the reference can be presented as "[Ref] reference omitted due to double-anonymous review" in the bibliographic references section;
• Reviewers will not be encouraged to look for references identifying authors in other sources. Searches of existing digital libraries or artifacts do not break the double-anonymous rules.

Desk Reject

Paper Review

NEW FOR 2024: Early Decisions

Authors' Response (Rebuttal)

Best Paper Award

Outstanding Reviewer Award

Organization