4th International Workshop on evaLuation and assEssment in softwARe eNgineers’ Education and tRaining (LEARNER 2026)

The LEARNER (evaLuation and assEssment in softwARe eNgineers’ Education and tRaining) workshop aims to bring together researchers, educators, and trainers from both academia and industry to discuss and advance the state-of-the-art on the evaluation and assessment of education and training of present and future software engineers. In other words, the goal of LEARNER is to assess and evaluate educational and training approaches to enable software engineers to acquire the required soft and hard skills, as well as to experiment novel educational and training means, including the use of any resource or technology (e.g., gamification, chatbots, and LLMs) for educational and training purposes of software engineers.

LEARNER 2026 is also interested in methods and solutions for evaluating and assessing both soft and hard skills required for software engineers, as well as engagement and retention (e.g., diversity and gender balance) in the education and training of software engineers.

Any questions about submissions can be emailed to the organizing committee (learner2026@easychair.org).

Call for Papers

Software engineers need to acquire a rich set of soft (e.g., problem-solving) and hard skills (e.g., software testing) in order to be able to deliver high-quality software systems that meet stakeholders’ needs. Such a skill set can be acquired through different educational and training approaches: from formal education in schools and universities to workplace training and capstone projects, from offline classes to those online, from coding clubs to boot camps and contests, up to the use of any resource or technology for the education and training of present and future software engineers. These educational and training approaches need to be assessed by educators or trainers.

LEARNER 2026 is a workshop interested in any aspect concerning the evaluation and assessment of educational and training means for present and future software engineers. Contributions aiming to evaluate and assess the skills above mentioned, as well as engagement and retention (e.g., diversity and gender balance) in the education and training of software engineers, are also of interest to the workshop.

The workshop will expect a mixed audience of researchers and educators from both academia and industry worldwide to share and discuss findings resulting from the evaluation and assessment in the context of education and training of present and future software engineers within schools, universities, workplaces, etc.

Special Theme: Software engineering education in the AI era

Software engineering education in the AI era is more important than ever, as artificial intelligence is reshaping how software is designed, developed, and maintained. Future engineers must not only master traditional programming and software design principles but also understand how to integrate AI models, data pipelines, and intelligent systems into complex applications. This requires a multidisciplinary skill set combining software engineering foundations with data science, ethics, and human-centered design to ensure that AI-enabled systems are both technically sound and socially responsible. Educational programs must therefore evolve to prepare students for a landscape where automation, adaptive systems, and continuous learning are central to the development process.

On the other hand, the rise of AI-based solutions is transforming software engineering education itself by enabling more personalized, efficient, and engaging learning experiences. Intelligent tutoring systems, automated code review tools, and adaptive learning platforms can provide real-time feedback, helping students identify and correct errors, improve code quality, and develop problem-solving skills more effectively. These technologies also allow educators to tailor learning paths to individual students’ needs, monitor progress with greater accuracy, and focus their efforts on higher level mentorship rather than routine assessment. As a result, AI-driven teaching tools have the potential to enhance both the quality and accessibility of software engineering education, fostering deeper learning and broader participation.

(Note that we still welcome submissions outside of this theme - we simply choose to highlight this area as a particular focus of this year’s workshop.)

Topics of Interest

LEARNER 2026 encourages contributions covering any topic related to (quantitative, qualitative, and mixed) research in the context of software engineers’ education and training. The topics of interest include, but are not limited to:

• Educational and training methods for acquiring hard skills and soft skills required to software engineers;
• Role of soft skills and human factors in the education and training of software engineers;
• Measurement of hard skills, as well as soft skills required to software engineers;
• Pedagogical approaches supporting software engineers’ education and training in distributed and remote settings;
• Education and training of software engineers in university and workplace settings;
• Online platforms and software tools specially designed or just used for education and training purposes of software engineers;
• Lifelong learning and continuing training of software engineers;
• Engagement and retention (e.g., diversity and gender balance) in software engineers’ education and training.

As for the special theme, the topics of interest include, but are not limited to:

• Educational and training methods to include AI in software engineering education;
• Models, methods, and techniques for evaluating the effectiveness of using AI software engineering education;
• Evaluation on innovative software engineering teaching processes;
• Role of soft skills and human factors in the education and training of software engineering;
• Metrics, measures and assessment techniques to evaluate knowledge in testing engineering courses;
• Tools specifically designed for education and training of software engineering.

Submission Guidelines

Papers must be written in English, contain original unpublished work, and follow official ACM Primary Article Template (https://www.acm.org/publications/proceedings-template). Papers must be submitted in PDF format through EasyChair https://easychair.org/conferences/?conf=learner2026

Accepted papers will be published in the joint workshop proceedings in the ACM Digital Library. The authors have the following options for submitting their papers:

• Full research papers (max 10 pages) describing original and completed research (i.e quantitative, qualitative, and mixed research) on topics related to software engineers’ education and training. Negative results papers are welcome as long as they can support advice or lessons learned. Papers reporting replications of empirical studies are welcome as well.
• Experience reports (max 5 pages) describe an experience on topics related to software engineers’ education and training. Unlike research papers, experience-report ones do not leverage empirical research (i.e., quantitative, qualitative, and mixed research) to distill findings. Experience-report papers are of interest as long as they provide an interpretation of the experience in terms of lessons learned and actionable tips.
• Ongoing-research papers (max 5 pages) describing novel, interesting, and high potential work in progress, but not necessarily reaching their full completion; or position papers that analyze trends or issues of importance. An ongoing-research paper must describe the idea as well as the proposed evaluation and assessment strategy possibly (but not necessarily) with some preliminary results.
• Educational and training artifacts and materials (around 6 to max 10 pages) describing artifacts and teaching modules that can be adopted and integrated as part of courses. The aim with this category of submissions is to contribute to Education and Training of Software Engineering Body of Knowledge (ETSEBoK) as a community-wide effort to provide a unique and comprehensive description of teaching concepts, best practices, tools, methods, and materials developed by the community. These papers may focus on, but are not limited to, methods, techniques, best practices and pedagogical approaches by describing how the proposed educational artifacts and materials have been used and can be adopted by others in the community. It is important to include some evidence and evaluations that demonstrate the benefits and unique features of the proposed teaching modules and materials.

Any questions about submissions should be emailed to the organizing committee (learner2026@easychair.org).

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