, Volume 61, Issue 4, pp 393–403 | Cite as

Tech Select Decision Aide: A Mobile Application to Facilitate Just-In-Time Decision Support for Instructional Designers

  • Nada DabbaghEmail author
  • Helen Fake
Original Paper


With the ubiquitous use of mobile technologies and the increasing demand for just-in-time training, there is a need to prepare and support instructional designers and educators to meet the pedagogical and technological development requirements of their target audience in the most effective and efficient way. This paper reviews the iterative design, development and testing of the Tech Select Decision Aide, a mobile recommender system designed to align instructional strategies with learning technologies based on the pedagogical affordances of the learning technology and the cognitive level of the learning objective. Focus group and survey results show that the Tech Select Decision Aide is a useful and usable mobile app that provides just-in-time performance support to assist instructional designers and faculty in the development and creation of pedagogically sound instructional and training materials using technology. Future areas of mobile development are discussed.


Decision support Design thinking Instructional design User experience design Agile development Mobile learning Recommender systems Mobile app Technological affordances Pedagogical affordances 


  1. App Annie (2016). App Annie mobile app forecast: The path to $100 billion [PDF document]. Retrieved from
  2. Association for Talent Development (2013, October). A Byte of Instructional Design. T+D Magazine. Retrieved from
  3. Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., & Grenning, J. (2001). Manifesto for Agile Software Development. Retrieved from
  4. Bosman, L., & Zagenczyk, T. (2011). Revitalize your teaching: Creative approaches to applying social media in the classroom. In B. White, K. King, & P. Tsang (Eds.), Social media and platforms in learning environments (pp. 3–15). Heidelberg: Springer.CrossRefGoogle Scholar
  5. Business Wire (2011). Allen Communications releases DesignJot, the first iPad app for instructional designers [Press release]. Retrieved from
  6. Churches, A. (2009). Bloom’s digital taxonomy. Retrieved from
  7. Cresswell, J. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Upper Saddle River: Pearson Education.Google Scholar
  8. Dabbagh, N. (2004). Emerging pedagogical issues and learning designs. Quarterly Review of Distance Education, 5(1)Google Scholar
  9. Dabbagh, N., Clark, K., Dass, S., Al Waaili, S., Byrd, S., Conrad, S., et al. (2011). LATIST: a performance support tool for integrating technologies into DAU learning assets. Defense Acquisition Research Journal, 18(3), 313–334. Available from Scholar
  10. Donne, V., & Lin, F. (2013). Special education teacher induction: the wiki way. The Clearing House: A Journal of Educational Strategies, Issues, & Ideas, 86(2), 1–5. doi: 10.1080/00098655.2012.735279.CrossRefGoogle Scholar
  11. Ericsson (2015, November). Ericsson mobility report: On the pulse of the networked society [PDF document]. Retrieved from
  12. Farwell, T. M., & Kruger-Ross, M. (2013). Is there (still) a place for blogging in the classroom? In K. K. Seo (Ed.), Using social media effectively in the classroom: Blogs, wikis, twitter, and more (pp. 207–223). New York: Routledge.Google Scholar
  13. Gee, J. P. (2007). What video games have to teach about learning and literacy. New York: MacMillion.Google Scholar
  14. Gillen, J., Ferguson, R., Peachey, A., & Twining, P. (2012). Distributed cognition in a virtual world. Language and Education, 26(2), 151–167. doi: 10.1080/09500782.2011.642881.CrossRefGoogle Scholar
  15. Glesne, C. (2011). Becoming qualitative researchers: An introduction. Boston: Pearson Education.Google Scholar
  16. Hartson, R., & Pyla, P. (2012). The UX Book: Process and guidelines for ensuring a quality user experience. Waltham: Morgan Kaurmann/Elsevier.Google Scholar
  17. Hashemi, M., Azizinezhad, M., Najafi, V., & Nesari, A. J. (2011). What is mobile learning? challenges and capabilities. Procedia - Social and Behavioral Sciences, 30, 2477–2481.CrossRefGoogle Scholar
  18. Houser, R., Thoma, S., Coppock, A., Mazer, M., Midkiff, L., Younanian, M., et al. (2011). Learning ethics through virtual fieldtrips. International Journal of Teaching and Learning in Higher Education, 23(2), 260–268.Google Scholar
  19. Hu, Q., & Johnston, E. (2012). Using a wiki-based course design to create a student centered learning environment: strategies and lessons. Journal of Public Affairs Education, 18(3), 493–512.Google Scholar
  20. Lightle, K. (2011). More than just the technology. Science Scope, 34(9), 6–9.Google Scholar
  21. Lund, A.M. (2001). Measuring Usability with the USE Questionnaire. STC Usability SIG Newsletter, 8(2). Google Scholar
  22. Nerur, S., & Balijepally, V. (2007). Theoretical reflections on agile development methodologies: the traditional goal of optimization and control is making way for learning and innovation. Communications of the AMC, 50(3), 79–83.Google Scholar
  23. Quinn, C. (2001). Get ready for m-learning. Training and Development, 20(2), 20–21.Google Scholar
  24. Rogers, Y., Connelly, K., Hazlewood, W., & Tedesco, L. (2010). Enhancing learning: a study of how mobile devices can facilitate sensemaking. Personal Ubiquitous Computing, 14, 111–124.CrossRefGoogle Scholar
  25. Sharples, M. (2000). The design of personal mobile technologies for lifelong learning. Computers and Education, 34, 177–193.CrossRefGoogle Scholar
  26. Shipee, M., & Keengwe, J. (2014). mLearning: anytime, anywhere learning transcending the boundaries of the educational box. Educational Information Technology, 19(1), 103–113. doi: 10.1007/s10639-012-9211-2.CrossRefGoogle Scholar
  27. Statista (2016). Number of apps available in leading app stores as of June 2016. Retrieved from
  28. Wu, W. H., Wu, Y. C., Chen, C. Y., Kao, H. Y., Lin, C. H., & Huang, S. H. (2012). Review of trends from mobile learning studies: a meta-analysis. Computers & Education, 59(2), 817–827.doi: 10.1016/j.compedu.2012.03.016.CrossRefGoogle Scholar
  29. Yang, C., & Chang, Y. S. (2012). Assessing the effects of interactive blogging on student attitudes towards peer interaction, learning motivation, and academic achievement. Journal of Computer Assisted Learning, 28(2), 126–135.CrossRefGoogle Scholar

Copyright information

© Association for Educational Communications & Technology 2016

Authors and Affiliations

  1. 1.Division of Learning TechnologiesGeorge Mason UniversityFairfaxUSA
  2. 2.Learning Technologies Design Research ProgramGeorge Mason UniversityFairfaxUSA

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