2026 Pre-ICIS SIGDSA Symposium

Teaching and Prototype Track - Call for Papers

The Association for Information Systems‘ Special Interest Group on Decision Support and Analytics (SIGDSA) is seeking submissions related to teaching decision support and data analytics concepts, tools, and technologies in the age of AI.

SIGDSA provides a forum for facilitating constructive discussions for researchers, instructors, and practitioners who are engaged in exploring topics and issues in AI, Business Analytics, and Data Science. The pre-ICIS SIGDSA 2026 Symposium theme is “Analytics and AI-Based Decision Support for Digital Collaboration and Coexistence.” This theme highlights the growing importance of analytics, artificial intelligence, and decision support systems in enabling collaboration across digital, organizational, and societal contexts while addressing the opportunities and challenges of coexistence in an increasingly connected world.

Digital transformation is reshaping how people, organizations, and communities communicate, collaborate, and make decisions through data, intelligent algorithms, and autonomous technologies. Meanwhile, challenges such as sustainability, economic uncertainty, cybersecurity, inequality, public health, and governance continue to intensify. These changes create both opportunities and responsibilities for analytics, AI, and decision support researchers and practitioners. As humans and AI increasingly work together across unequal digital environments, differences in access, data availability, digital literacy, and infrastructure remain critical. A key challenge for the information systems discipline is designing analytics and AI-based decision support that enables more inclusive and effective collaboration.

Aligning with the ICIS 2026 conference theme of "Analytics and AI for Digital Collaboration and Coexistence", we seek submissions focused on teaching. Submissions should address the innovation and challenges related to education, pedagogy, curriculum design & implementation, outcomes assessment, distance education challenges, capstone learning projects, technology selection & impact, especially focused on the age of AI. The submission can relate to teaching business intelligence, big data analytics, cognitive analytics, social media analytics, machine learning, IoT analytics, data science, visualization, generative AI, or other emerging analytic technologies.

We also seek prototype demonstrations or design research idea papers showcasing/discussing innovative analytics methodologies and applications.

Authors of accepted papers will have the option of publishing: (a) the complete manuscript OR (b) an extended abstract (single-spaced 2-3 pages) as part of the symposium proceedings on AIS eLibrary. If authors choose to publish only the extended abstract, authors will retain the copyright of the original manuscript submitted for review and feedback. Please see the details below.

Submission Categories: Teaching and Prototype Track

Teaching sub-track

Contributions can be of varied types, including: teaching cases, tutorials, curriculum innovations, pedagogical studies, or infrastructure for teaching analytics and AI. Topics may include but are not limited to:

• Newly developed Business Analytics (BA) programs, curriculum, and assessment methods incorporating AI and generative AI components
• Bodies of Knowledge (BOK) for Business Intelligence, Analytics, Machine Learning, Data Science, and AI integration
• Pedagogical frameworks for teaching Agentic AI and its role in shaping autonomous, goal-driven analytics systems for future organizations
• Curriculum integration of Model Context Protocol (MCP) to teach students how to contextualize, document, and communicate AI model behavior, ethics, and applicability across industries
• Developing an interdisciplinary focus on teaching analytics courses with an emphasis on digital platforms, AI tools, and their impact on emerging societies
• Differentiating business analytics curricula for Undergraduate, MBA, Master of Science, and Executive Education, and tailoring curricula to generalists and specialists
• Integration of IT, analytics, and AI skills for digitally connected learning
• Pedagogical innovations in business analytics, including the use of AI and generative AI for instruction and engagement
• Innovative pedagogical approaches to teaching ethics in business analytics design, development, and implementation in the age of AI
• Innovations in the delivery of analytics courses (online, hybrid, student interaction, etc.) in the AI era
• Challenges and solutions related to the construction and maintenance of classrooms and labs in support of business analytics education and AI
• Organizational case studies (preferably with teaching notes) that provide rich stories of management, analytics, and AI initiatives and address issues such as management sponsorship, strategic priorities, AI adoption, digital integration, implementation of analytics, technical challenges, collaboration, communication, and actionable business outcomes
• Tutorial exercises and simulations that provide a business scenario, data sets, and a step-by-step introduction to the latest business analytics tools
• Data sets that can be used by other faculty members to augment their pedagogy
• Integrating generative AI tools in the classroom to enhance learning and engagement while addressing ethical considerations and biases
• Developing assessment methods that effectively measure student understanding and use of AI tools and generative systems without encouraging over-reliance on such technologies

Submissions for the teaching sub-track must not exceed ten (10) single-spaced pages and must conform to the paper submission template. The page limit covers everything in the submission, including the title, text, tables, figures, appendices, and references. Submissions that exceed this limit will be automatically rejected. Based on the type of submission (e.g., teaching case, tutorial, etc.), the correct submission type should be specified in the submission.

Prototype Sub-track

This sub-track showcases innovative methodological developments or applications of artificial intelligence, generative technologies, machine learning, deep learning, reinforcement learning, text mining, or other data analytics/decision support techniques. Prototypes should highlight aspects such as novelty, architecture, functioning, and ongoing/future work. This high-visibility category is different from the research paper presentation category and provides an opportunity to display a working artifact to an audience in an interactive manner. Prototype demonstrations will involve a poster display (printed or electronic) and a live demonstration of a prototype to the attendees.

The prototype submission must be five to seven (5-7) single-spaced pages and must conform to the paper submission template. The page limit covers everything in the submission, including title, text, tables, figures, appendices, and references. In addition to the Title, Abstract, and Keywords, a prototype proposal should contain only one or two sections describing the prototype or core research idea to be showcased, highlighting the key features and novelty. The submission type should be mentioned in the submission as Prototype Track.

Important Dates, Submission Guidelines, Publication Opportunities, and Awards

Please see the important relevant dates below:

• July 13, 2026 (Mon): Manuscript submissions open
• August 31, 2026 (Mon): Manuscript submission deadline (11:59 pm EDT)
• October 12, 2026 (Mon): Acceptance decisions communicated to authors on a rolling basis, but no later than October 12, 2026
• November 16, 2026 (Mon): Regular registration deadline; at least one author must be registered for the Symposium
• November 16, 2026 (Mon): Camera-ready submissions due
• December 12–13, 2026 (Sat/Sun): 2026 Pre-ICIS SIGDSA Symposium

      Note:

• For submission guidelines, template, and submission instructions please click here.
• For publication opportunities and awards, please click here.
• Important dates can be found by visiting this link.

Teaching and Prototype Track Co-Chairs

For questions regarding the submissions to the Teaching and Prototype Track, please contact:

• Jongsawas Chongwatpol, jongsawas.c@nida.ac.th, NIDA Business School, National Institute of Development Administration, Thailand
• Rupesh Agrawal, agrawalr1@nku.edu, Northern Kentucky University, USA
• Rachel Chung, rachel.chung@mason.wm.edu, William & Mary, USA

We recommend including the 'Pre-ICIS SIGDSA 2026 Teaching & Prototype Track Question' as the email subject line.