Advertisement

Journal of Computing in Higher Education

, Volume 31, Issue 3, pp 472–494 | Cite as

Preparing today’s educational software developers: voices from the field

  • Marisa E. ExterEmail author
  • Iryna Ashby
Article

Abstract

Educational software is a growing industry, creating demand for professionals with the skills and knowledge necessary to develop high-quality learning software. This paper explores the perceptions and experiences of professionals who have made a career of developing educational software and suggests educational paths useful for professionals in the field. In-depth interviews (n = 9) and surveys (n = 92) were incorporated in this mixed-methods study. Topics addressed include developers’ backgrounds, perceptions of working in this field, roles played, alignment between educational background and roles, and suggestions for an ideal undergraduate degree for a career in educational software development. Participants’ formal education paths included computing, instructional design, and other backgrounds. Roles played varied based on those backgrounds. When asked for recommendations for an ideal educational program, the most frequent response was a hybrid/dual major. However, those with degrees in computing or instructional design were most likely to recommend a similar degree, and use of on-the-job self-study for other topics. Those without a computing degree frequently indicated that formal education in programming and technology was important, but less so than the ability to think critically. Those with a computing background indicated that a background in education was not necessary, although ideally computing students should gain experience delving into at least one industry so that they would be prepared to interact with specialists and stakeholders in any specialty area in the future. Throughout, participants noted the importance of professional skills, critical thinking, and life-long learning. Implications for educators and researchers are discussed.

Keywords

Educational technology Development Software development Computing education Instructional design education 

Notes

Acknowledgements

Hidden for blind review.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.” Data collected as part of this study was overseen by the Institutional Review Board of Indiana University, protocol # 0813604.

References

  1. ACM/IEEE-CS Joint Task Force on Computing Curricula. (2013). Computer science curricula 2013. New York: ACM Press and IEEE Computer Society Press.  https://doi.org/10.1145/2534860.CrossRefGoogle Scholar
  2. Adnan, N. H., & Ritzhaupt, A. D. (2018). Software engineering design principles applied to instructional design: What can we learn from our sister discipline? TechTrends, 62(1), 77–94.  https://doi.org/10.1007/s11528-017-0238-5.CrossRefGoogle Scholar
  3. Allen Interactions. (2018). Interactive eLearning development with SAM. Retrieved October 15, 2018 from http://www.alleninteractions.com/sam-process.
  4. Andriole, S., & Roberts, E. (2008). Technology curriculum for the early 21st century. Communications of the ACM, 51(7), 27–30.  https://doi.org/10.1145/1364782.1364792.CrossRefGoogle Scholar
  5. Ardis, M., Chenoweth, S., & Young, F. (2008). The “soft” topics in Software Engineering education. In 38th ASEE/IEEE frontiers in education conference. http://dx.doi.org/10.1109/FIE.2008.4720272.
  6. Ashby, I., & Exter. M. (in press). Designing for interdisciplinarity in higher education: Considerations for instructional designers. TechTrends.Google Scholar
  7. Berry, D. (1995). The importance of ignorance in requirements engineering. Journal of Systems and Software, 28(2), 179–184.  https://doi.org/10.1016/0164-1212(94)00054-q.CrossRefGoogle Scholar
  8. Biernacki, P., & Waldorf, D. (1981). Snowball sampling: Problems and techniques of chain referral sampling. Sociological Methods & Research, 10(2), 141–163.CrossRefGoogle Scholar
  9. Chamorro-Premuzic, T., Arteche, A., Bremner, A. J., Greven, C., & Furnham, A. (2010). Soft skills in higher education: Importance and improvement ratings as a function of individual differences and academic performance. Educational Psychology, 30(2), 221–241.CrossRefGoogle Scholar
  10. Creswell, J., & Clark, V. (2007). Designing and conducting mixed methods research. Thousand Oaks, CA: Sage.Google Scholar
  11. Dieste, O., Juristo, N., & Shull, F. (2008). Understanding the customer: What do we know about requirements elicitation? IEEE Software, 25(2), 11–13.CrossRefGoogle Scholar
  12. Driscoll, M. (2000). Motivation and self-regulation in learning. In M. P. Dricoll (Ed.), Psychology of learning for instruction. Needham Heights, MA: Allyn and Bacon.Google Scholar
  13. Ertmer, P., York, C., & Gedic, N. (2009). Learning from the Pros: How experienced designers translate instructional design models into practice. Educational Technology, 41(1), 19–27.Google Scholar
  14. Exter, M. (2014). Comparing educational experiences and on-the-job needs of educational software designers. In Proceedings of the 45th ACM Technical Symposium on Computer Science Education - SIGCSE ’14 (pp. 355–360).  https://doi.org/10.1145/2538862.2538970.
  15. Exter, M. (2018). Developing multi-disciplinary skills through a course in educational software design. International Journal of Designs for Learning, 9(1), 49–79.  https://doi.org/10.14434/ijdl.v9i1.23413.CrossRefGoogle Scholar
  16. Exter, M., & Turnage, N. (2012). Exploring experienced professionals’ reflections on computing education. ACM Transactions on Computing Education.  https://doi.org/10.1145/2275597.2275601.CrossRefGoogle Scholar
  17. Harlin, N. M., Exter, M., & Boling, E. (2009). Software designers’ use of precedent. Annual Meeting of the Association for Educational Communications and Technologies. Lousville, KY.Google Scholar
  18. Gibbons, A. S., & Brewer, E. K. (2005). Elementary principles of design languages and design notation systems for instructional design. In Innovations in instructional technology: Essays in honor of M. David Merrill (pp. 111–130). Mahwah, NJ: Taylor & Francis.Google Scholar
  19. Gibbons, A. S., Nelson, J. & Richards, R. (2000). The nature and origin of instructional objects. In D. A. Wiley (Ed.), The instructional use of learning objects: Online version. Retrieved October 15, 2018 from http://reusability.org/read/chapters/gibbons.doc.
  20. Gorla, N., & Lin, S.-C. (2010). Determinants of software quality: A survey of information systems project managers. Information and Software Technology, 52(6), 602–610.  https://doi.org/10.1016/j.infsof.2009.11.012.CrossRefGoogle Scholar
  21. Hart Research Associates. (2013). It takes more than a major: Employer priorities for college learning and student success. An online survey among employers conducted on behalf of the Association of American Colleges and Universities. Retrieved October 15, 2018 from http://www.aacu.org/sites/default/files/files/LEAP/2013_EmployerSurvey.pdf.
  22. Hart Research Associates. (2015). Falling short? College learning and career success. Washington, DC: Association of American Colleges and Universities. Retrieved October 15, 2018 from https://www.aacu.org/sites/default/files/files/LEAP/2015employerstudentsurvey.pdf.
  23. Hofmann, H., & Lehner, F. (2001). Requirements engineering as a success factor in software projects. IEEE Software, 18(4), 58–66.  https://doi.org/10.1109/ms.2001.936219.CrossRefGoogle Scholar
  24. Holley, K. (2017). Interdisciplinary curriculum and learning in higher education. In Oxford research encyclopedia of education. Retrieved October 15, 2018 from http://education.oxfordre.com/view/10.1093/acrefore/9780190264093.001.0001/acrefore-9780190264093-e-138.
  25. Hooper, S., Rook, M., & Choi, K. (2015). Reconsidering the design of a learning design studio. In B. Hokanson, G. Clinton, & M. Tracey (Eds.), The design of learning experience: Creating the future of educational technology. New York, NY: Springer.Google Scholar
  26. Jaccheri, L., & Sindre, G. (2007). Software engineering meet interdisciplinary project work and art. In Conference proceedings from the 11th international conference information visualization (IV ‘07).  https://doi.org/10.1109/iv.2007.102.
  27. Kang, U., & Ritzhaupt, A. (2015). A job announcement analysis of educational technology professional positions: Knowledge, skills, and abilities. Journal of Educational Technology, 43(3), 231–256.CrossRefGoogle Scholar
  28. Kenny, R., Zhang, Z., Schwier, R., & Campbell, K. (2005). A review of what instructional designers do: Questions answered and questions not asked. Canadian Journal Of Learning And Technology/La Revue Canadienne De L’Apprentissage Et De La Technologie. Retrieved October 15, 2018 from  https://doi.org/10.21432/T2JW2P.CrossRefGoogle Scholar
  29. Klein, J., & Jun, S. (2014). Skills for instructional design professionals. Performance Improvement, 53(2), 41–46.  https://doi.org/10.1002/pfi.21397.CrossRefGoogle Scholar
  30. Knox, A. (2000). The continuum of professional education and practice. New Directions for Adult and Continuing Education, 86, 13–22.CrossRefGoogle Scholar
  31. Koszalka, T., Russ-Eft, D., Reiser, R., Canela, F., Grabowski, B., & Wallington, C. (2013). Instructional designer competencies: The standards (4th ed.). Charlotte, NC: Information Age Publishing.Google Scholar
  32. Larson, M. (2005). Suvey of the alignment of prepration and practice. Techtrends, 49(6), 22–32.CrossRefGoogle Scholar
  33. Lattuca, L. (2001). Creating interdisciplinarity: Interdisciplinary research and teaching among college and university faculty. Nashville, TN: Vanderbilt University Press.Google Scholar
  34. Lincoln, Y., & Guba, E. (1984). Processing the naturalistically obtained data. Naturalistic Inquiry (pp. 256–332). Beverly Hills, CA: Sage.Google Scholar
  35. Mall, R. (2014). Fundamentals of software engineering (4th ed.). New Delhi: PHI Learning.Google Scholar
  36. McConnel, S. (1996). Lifecycle planning. Rapid development: Taming wild software schedules (pp. 133–181). Redmond, WA: Microsoft Press.Google Scholar
  37. Molnar, M. (2016). Investors see promise in Ed-Tech sector despite challenges. Retrieved October 15, 2018 from https://marketbrief.edweek.org/marketplace-k-12/investors-see-promise-ed-tech-sector-despite-challenges.
  38. Neill, C., & LaPlante, P. (2003). Requirements engineering: The state of the practice. IEEE Software, 20(6), 40–45.CrossRefGoogle Scholar
  39. Newman, D., Jaciw, A., & Larazarev, V. (2017). Guidelines for conducting and reporting EdTech impact research in U.S. K-12 schools. Retrieved October 15, 2018 from https://www.empiricaleducation.com/pdfs/guidelines.pdf.
  40. Niknafs, A., & Berry, D. (2012). The impact of domain knowledge on the effectiveness of requirements engineering activities. In 20th IEEE international on requirements engineering conference (RE) (pp. 181–190). IEEE Press.Google Scholar
  41. Patton, M. (2015). Qualitative research and evaluation (4th ed.). Thousand Oaks, CA: SAGE.Google Scholar
  42. Radermacher, A., & Walia, G. (2013). Gaps between industry expectations and the abilities of graduates. In SIGCSE’13. Denver, CO: ACM. http://dx.doi.org/10.1145/2445196.2445351.
  43. Richards, J. & Stebbins, L. (2015). 2014 U.S. Education Technology Market: PreK-12. Retrieved October 15, 2018 from http://www.siia.net/Portals/0/pdf/Education/SIIA2014Report_PreK12_FINAL%201%2031%202015_Exec%20Summ.pdf.
  44. Ritzhaupt, A., Martin, F., & Daniels, K. (2010). Multimedia competencies for an educational technologist: A survey of professionals and job announcement analysis. Journal of Educational Multimedia and Hypermedia, 19(4), 421–449.Google Scholar
  45. Roytek, M. (2010). Enhancing instructional design efficiency: Methodologies employed by instructional designers. British Journal of Educational Technology, 41(2), 170–180.CrossRefGoogle Scholar
  46. Sahmi, M., Cuadros-Vargas, E., Roach, S., & Reed, D. (2012). Computer science curriculum 2013: Reviewing the strawman report from the ACM/IEEE Task Force. In SIGCSE’12. Raleigh, North Carolina.Google Scholar
  47. Schach, S. R. (2011). Software life-cycle models. In M. Hill (Ed.), Object-oriented and classical software engineering (pp. 37–73). New York: McGraw-Hill.Google Scholar
  48. Schwier, R., & Wilson, J. (2010). Unconventional roles and activities identified by Instructional Designers. Contemporary Educational Technology, 1(2), 134–147.Google Scholar
  49. Smith, B. (2006). Design and computational flexibility. Digital Creativity, 17(2), 65–72.  https://doi.org/10.1080/14626260600787589.CrossRefGoogle Scholar
  50. Styron, R. (2013). Interdisciplinary education: A reflection of the real world. Systems, Cybernetics, and Informatics, 11(9), 47–52.Google Scholar
  51. Sugar, W. (2014). Studies of ID practices (pp. 47–100). Cham: Springer International Publishing.  https://doi.org/10.1007/978-3-319-03605-2.CrossRefGoogle Scholar
  52. Sugar, W., Hoard, B., Brown, A., & Daniels, L. (2012). Identifying multimedia production competencies and skills of instructional design and technology professionals: An analysis of recent job postings. Journal of Educational Technology Systems, 40(3), 227–249.CrossRefGoogle Scholar
  53. Tafa, Z., Rakocevic, G., Mihailovic, D., & Milutinovic, V. (2011). Effects of interdisciplinary education on technology-driven application design. IEEE Transactions on Education, 54(3), 462–470.CrossRefGoogle Scholar
  54. Tripp, S., & Bichelmeyer, B. (1990). Rapid prototyping: An alternative instructional design strategy. Educational Technology Research and Development, 38(1), 31–44.CrossRefGoogle Scholar
  55. van Vliet, H. (2006). Reflections on software engineering education. IEEE Software, 23(2), 55–61.Google Scholar
  56. Zohrabi, M. (2013). Mixed methods research: Instruments, validity, reliability and reporting findings. Theory and Practice in Language Studies, 3(2), 254–262.  https://doi.org/10.4304/tpls.3.2.254-262.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Purdue UniversityWest LafayetteUSA

Personalised recommendations