Call for Papers—Special Issue on Empirical Pedagogical Research in Analytics

INFORMS is the prominent organization of analytics professionals and academics and publisher of multiple highly rated journals. INFORMS Transactions on Education (ITED) is the INFORMS journal focused on advancing and disseminating approaches, cases, and research that lead to instructional success. ITED’s mission is to become the flagship journal of education science related to the core domains of INFORMS: management science, operations research, operations management, and analytics.

The rapid adoption of digital transformation and data-driven decision-making processes has led to a rapid, dramatic increase of analytics knowledge and skills that industry requires of new hires (Zheng et al. 2021). Many colleges and universities were not initially equipped to address this shift because few analytics programs existed. For example, fewer than 10% of U.S. colleges and universities offered undergraduate analytics degree programs in 2016 (Clayton and Clopton 2019). Over the past decade, academic institutions have integrated analytics content into existing degree programs and have created hundreds of new, focused analytics degree programs (Zhang et al. 2025).

In that time, academic journals have published dozens of articles related to issues of curricular design for analytics content (e.g., Hartzel and Ozturk 2022, Brattin 2025) and innovative methods for teaching analytics tools and methods (e.g., Isken 2024, Roshanaei et al. 2024, Snyder et al. 2026).

The literature related to the effectiveness of these methods and the required antecedent knowledge and attitudes for learning analytics content, however, has been somewhat less developed. This lack of rigorous assessment of the efficacy of analytics pedagogy is even more pronounced when considering the use of artificial intelligence tools.

The main goal of this special issue is to contribute to the body of knowledge related to the improved understanding of effective teaching and learning methods for analytics concepts through studies grounded in empirical results. The papers published in this special issue will help analytics educators identify approaches that help their students learn these essential tools more effectively.

Example topics for potential submissions include, but are not limited to, the following:

  • Empirical assessment of pedagogical approaches for teaching analytics content at different levels (e.g., undergraduate or graduate courses), in different programs (e.g., core analytics courses in broader degree programs, courses in dedicated analytics programs, etc.), and across different delivery modalities (e.g., in-person, hybrid, or online formats).

  • Empirically supported approaches for effectively integrating analytics content into courses in other academic domains such as accounting, engineering, finance, law, marketing, nursing, and supply chain management.

  • Empirical analysis of the effectiveness of different approaches for using AI tools to perform, summarize, or communicate data analysis and to support decision making.

  • Cross-cultural studies of the differences in the effectiveness of analytics pedagogy and/or in the attitudes of students toward learning analytics content.

  • Comparative studies of outcomes from using different software tools and applications to teach analytics content.

  • Empirical investigation of approaches for assessing analytics competencies, including the design and validation of instruments that measure student learning outcomes in analytics courses and programs.

Authors should review the INFORMS Transactions on Education instructions on preparing a paper at https://pubsonline.informs.org/page/ited/submission-guidelines.

Papers must be submitted online at https://mc.manuscriptcentral.com/ite.

Anticipated Editorial Timeline

  • December 31, 2026: Target deadline for first round of submissions. Papers submitted earlier than this deadline will be reviewed and accepted on a rolling basis.

  • March 2027: First round of reviews completed with decisions (and requests for revision, if appropriate) delivered to authors.

  • July 2027: Second round of reviews completed with decisions delivered to authors.

  • October 2027: Final versions of accepted papers to be submitted.

  • January 2028: Target ITED issue publication date.

We look forward to your contributions to this exciting and timely topic! We invite potential authors to reach out to the guest editors with any questions they have about the special issue or their manuscripts.

References

  • Brattin RL (2025) The process deficit in data analytics education: Addressing workforce readiness gaps. Higher Ed. Skills Work-Based Learn. 15(5):1129–1145.CrossrefGoogle Scholar
  • Clayton PR, Clopton J (2019) Business curriculum redesign: Integrating data analytics. J. Ed. Bus. 94(1):57–63.CrossrefGoogle Scholar
  • Hartzel KS, Ozturk P (2022) Analytics in the business school: Insights from the literature. J. Inform. Systems Ed. 33(2):169–181.Google Scholar
  • Isken MW (2024) Spreadsheet modeling and wrangling with Python. INFORMS Trans. Ed. 25(2):152–168.LinkGoogle Scholar
  • Roshanaei V, Naderi B, Baron O, Krass D (2024) An interactive spreadsheet model for teaching classification using logistic regression. INFORMS Trans. Ed. 25(1):55–80.LinkGoogle Scholar
  • Snyder LV, Shehadeh KS, Novoa LJ (2026) The burrito optimization game: An educational resource for optimization in operations research, business analytics, and supply chain management. Decision Sci. J. Innovative Ed. 24(1–2):e70018.CrossrefGoogle Scholar
  • Zhang H, Mohd Thas Thaker MA, Hamid Z, Mohd Thas Thaker H (2025) Current status and future research directions of business intelligence and analytics education: A bibliometric analysis. Internat. J. Evaluation Res. Ed. 14(5):3502–3514.Google Scholar
  • Zheng Y, Hameed T, Lavoie R, Sendall P (2021) An overview of current business analytics programs across US AACSB schools. Issues Inform. Systems 22(2):306–317.Google Scholar