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Data-driven decision-making in instructional design: instructional designers’ practices and strategies

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Date

2025

Author

Caskurlu, Secil
Yalçın, Yasin
Hur, Jaesung
Shi, Hui
Klein, James D.

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Citation

Caskurlu, S., Yalçın, Y., Hur, J., Shi, H., & Klein, J. D. (2025). Data-Driven Decision-Making in Instructional Design: Instructional Designers’ Practices and Strategies. TechTrends, 69(4), 737-748. https://doi.org/10.1007/s11528-025-01077-x

Abstract

This exploratory qualitative study examined how instructional designers use data to make decisions during the instructional design process. Participants included full-time instructional designers (n = 9) who were involved in one or more phases of the ADDIE (Analysis, Design, Development, Implementation, Evaluation) across different job sectors, including health, corporate, higher education, and non-profit. Data sources included pre-interview surveys and semi-structured interviews. We analyzed the data using thematic analysis (Braun & Clarke, 2006). The results indicated that instructional designers use data in diverse ways, depending on project scope, resources, team structures, and personal preferences. Data was often gathered through interactions with target audiences, clients, and subject matter experts, and reflected the project’s context, scope, resource availability, and the instructional designer’s individual approach. Log data and user experience data emerged as critical sources in the analysis, design, and evaluation phases. Implications for practice and research are discussed.

Source

TechTrends

Volume

69

Issue

4

URI

https://doi.org/10.1007/s11528-025-01077-x
https://hdl.handle.net/11436/10942

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  • Bilgisayar Mühendisliği Bölümü Koleksiyonu [50]
  • Scopus İndeksli Yayınlar Koleksiyonu [6292]



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