The Journal of Information Systems Education (JISE) invites submissions for a Special Issue titled "Reframing IS Education for the Era of Generative AI: Competencies, Assessment, and Curriculum When Artifacts No Longer Signal Learning," expected to be published in the second half of 2028. JISE is a peer-reviewed, diamond open access journal. There are no fees to submit or to publish.
Information systems (IS) education has long judged learning by the work students submit. The IS2020 model defines competency as knowledge, skills, and dispositions applied in a task (Leidig & Salmela, 2022). JISE's 2008 special issue on assessment described grading an assignment against criteria as probably the most common assessment tool in IS programs (White et al., 2008). Generative AI now performs many of those tasks: the code, the data model, the requirements specification, the analytics report, and the project plan. Studies show that generative AI can produce assessment artifacts that are difficult to distinguish from human work and can perform strongly on open-ended assessment tasks (Kofinas et al., 2025; Rodrigues et al., 2024). When the work can be produced without the learning, the work stops being dependable evidence of the learning.
The first responses treated this as a problem of academic integrity and detection. Recent assessment scholarship treats it as one of validity: whether our assessments still support the claims we make about what graduates can do (Dawson et al., 2024). One line of response is to assess both how students worked and what they produced, to secure assessment at key points, and to judge progress across a program instead of one assignment at a time (Lodge et al., 2023). Other recent work has proposed responses ranging from supervised processes and oral defenses to broader curricular and institutional frameworks (Chan, 2023; Fajardo-Ramos et al., 2025; Gimpel et al., 2025; Van Slyke et al., 2023). Further research is needed on what student work in IS demonstrates about learning when generative and agentic AI can participate in complex, multi-step work, and on how assessment, curriculum, and competency models should respond as AI capabilities evolve. This special issue invites that research.
We welcome articles (empirical, conceptual, design science, and review papers), teaching tips, and teaching cases. Teaching tips and teaching cases must follow the JISE guidelines for those types (https://jise.org/submissions.html), and teaching cases need separate teaching notes. Reflective position pieces are welcome as articles if they advance an argument that the field can test. We prefer pieces by several authors that include dissenting views. We welcome authors from assessment research, computing education, and the learning sciences as well as IS. Submissions should be set in, or be directly relevant to, information systems and related programs such as business analytics and information technology.
Studies of how students use generative AI, of learning outcomes, and of faculty development are in scope when they address one of two questions. What does student work now show about learning? What should change in assessment, curriculum, competency models, or program-level educational practice in IS? Surveys of adoption or attitudes toward AI tools, and evaluations of AI-detection tools, are better suited to a regular issue.
We want the issue to reflect IS education as it is practiced worldwide. We particularly welcome submissions from Africa, Asia, Oceania, and Latin America, and from early-career researchers. Because the issue will appear about two years after this call, we ask authors to address questions that will still matter after today's tools have changed, including shifts in AI autonomy, agency, modality, and integration into professional IS work, and to report tool names, versions, dates of data collection, and the prompts or interaction protocol used.
Topics of interest include, but are not limited to:
Competencies
Assessment
Curriculum
AI in the IS classroom
Faculty development and governance
Papers for the Special Issue are due on June 1, 2027. Any author may ask for an extension of up to June 30, 2027.
Prospective authors are welcome to submit an abstract of up to 500 words to the Guest Editors for preliminary feedback on the appropriateness of their planned manuscript. Abstracts may be sent at any time, and preferably by March 1, 2027. We aim to reply within 10 working days. Feedback is advisory and is limited to fit and paper type. It is neither a prerequisite for submission nor an indication of the editorial decision. Please send abstracts in Microsoft Word format by email to the corresponding Guest Editor, Tim C. Smith, smith515@usf.edu, with the subject "JISE Special Issue."
Full papers are submitted in Microsoft Word format by email to the corresponding Guest Editor at the same address, with the subject "JISE Special Issue." Please state the submission type (article, teaching tip, or teaching case).
Papers should not exceed 8,000 words, including all sections, figures, tables, and references, and must follow the JISE submission guidelines at https://jise.org/submissions.html. Papers that extend work presented at a conference are welcome, as JISE encourages, provided they are revised and have a modified title. The submission must declare the earlier version and explain how the paper differs.
This is an open call. All papers that pass initial editorial screening will be double-anonymized peer reviewed by at least three reviewers, and accepted papers are subject to editing for journal style, clarity, organization, and space. The Guest Editors will not author or co-author any paper in the Special Issue other than the editorial introduction.
Use of generative AI. Authors may use generative AI tools in their research and writing, provided the submission reflects their own intellectual contribution. AI tools may not be listed as authors. Authors are fully responsible for the accuracy, integrity, and originality of the work, including every reference cited. Authors must declare any use of generative AI beyond basic spelling and grammar checking. The declaration names the tool and what it was used for. It appears in the cover note sent with the submission and in a short statement in the manuscript. The statement must be worded so that it does not identify the authors. Where AI is part of the research itself, describe it in the Methods section. Using AI for language editing or translation is welcome, needs only a one-line declaration, and will not lower a paper's evaluation. No submission will be rejected because AI use is declared, and the Guest Editors will not use AI-detection software. Fabricated or unverifiable references, or substantial undeclared AI-generated content, will be handled under JISE's Guidelines for Ethical Behavior in Publishing in consultation with the Editor-in-Chief.