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Concurrent Design: Instructional and Motivational Strategy Planning

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Abstract

Once the objectives are clustered, the next set of essential design tasks in the concurrent design stage is to determine the instructional and motivational strategies for online instruction. Formative evaluation continues as the instructional strategies take form. To promote a sense of continuity, the designer uses a conceptual framework for describing these instructional and motivational strategies. The WBID Model uses the WBI Strategy Worksheet as the means to frame and document such strategies. While creating these strategies, the designer must bear in mind other factors that impact online delivery: class size, navigation and learner control, feedback, and interactivity. The designer also determines the types of media to incorporate into the online instruction, if it has not already been predetermined.

This chapter begins with an overview of the main features in an LMS that influence the types of instructional and motivational strategies selected. A discussion of the conceptual framework that guides the design plan follows. We next describe the WBI Strategy Worksheet, which outlines the framework, and provide examples of how to use it. We then present two different motivational models and describe basic motivational strategies. In the last section of this chapter, several factors that affect the design are explored. Development tasks, the last part of the concurrent design stage, are the subject of Chap.  8.

Keywords

Web instructional strategy worksheet Instructional strategies Motivation Motivational strategies Learning management systems Intrinsic motivation Extrinsic motivation Navigation Learner control Class size Learning management system (LMS) Feedback Interactivity 

References

  1. Abrami, P. C., Bernard, R. M., Bures, E. M., Borokhovski, E., & Tamim, R. M. (2011). Interaction in distance education and online learning: Using evidence and theory to improve practice. Journal of Computing In Higher Education, 23(2-3), 82.CrossRefGoogle Scholar
  2. Airasian, P. W., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., Raths, J., & Wittrock, M. C. (2001). In L. W. Anderson & D. R. Krathwohl (Eds.), A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives (Complete edition). New York, NY: Longman.Google Scholar
  3. Alderman, M. K. (2008). Motivation for achievement: Possibilities for teaching and learning (3rd ed.). New York, NY: Routledge.Google Scholar
  4. Alomyan, H. (2004). Individual differences: Implications for Web-based learning design. International Education Journal, 4(4), 188–196.Google Scholar
  5. Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289. https://doi.org/10.3102/0034654309333844 CrossRefGoogle Scholar
  6. Clayton, K., Blumberg, F., & Auld, D. P. (2010). The relationship between motivation, learning strategies and choice of environment whether traditional or including an online component. British Journal of Educational Technology, 41(3), 349–364.CrossRefGoogle Scholar
  7. Davidson-Shivers, G. V., & Reese, R. M. (2014). Are online assessments measuring student learning or something else? In P. Lowenthal, C. York, & J. Richardson (Eds.), Online learning: Common misconceptions, benefits, and challenges (pp. 137–152). Hauppauge, NY: Nova Science Publishers.Google Scholar
  8. Dennen, V. P., Darabi, A. A., & Smith, L. J. (2007). Instructor-learner interaction in online courses: The relative perceived importance of particular instructor actions on performance and satisfaction. Distance Education, 28(1), 65–79. https://doi.org/10.1080/01587910701305319 CrossRefGoogle Scholar
  9. Denzine, G., & Brown, R. (2014). Motivation to learn and achievement. In R. Papa (Ed.), Media rich instruction: Connecting curriculum to all learners (pp. 19–34). New York, NY: Springer International Publishing. https://doi.org/10.1007/978-3-319-00152-4_2 Google Scholar
  10. Dick, W., Carey, L., & Carey, J. O. (2015). The systematic design of instruction (8th ed.). New York, NY: Pearson Education, Limited.Google Scholar
  11. Dodge, B. (2017). Webquest.org. Retrieved from http://webquest.org.
  12. Driscoll, M. (2005). Psychology of learning for instruction (3rd ed.). Boston, MA: Pearson.Google Scholar
  13. Faculty eCommons. (2017). Exam proctoring: Review of the top five tools. Retrieved from http://facultyecommons.com/exam-proctoring-a-review-of-the-top-five-tools/.
  14. Fisher, J. J. (2000). Implementation considerations for instructional design of Web-based learning environments. In B. Abbey (Ed.), Instructional and cognitive impacts of Web-based education (pp. 78–101). Hershey, PA: Idea Group.CrossRefGoogle Scholar
  15. Fisher, S., Howardson, G., Wasserman, M. E., & Orvis, K. (2017). How do learners interact with e-learning? Examining patterns of learner control behaviors. IAS Transactions on Human-Computer Interaction, 9(2), 75–98.Google Scholar
  16. Gagné, R. M. (1985). The conditions of learning and theory of instruction. New York, NY: Holt, Rinehart & Winston.Google Scholar
  17. Garrison, D., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education, 15(1), 1–23. Retrieved from www.tandfonine.com/toc/hadjd20/current#.Uxne6z9WSo CrossRefGoogle Scholar
  18. Ginsberg, M. B., & Wlodkowski, R. J. (2009). Diversity and motivation: Culturally responsive teaching in college (2nd ed.). San Francisco, CA: Jossey Bass: A Wiley Imprint.Google Scholar
  19. Hannafin, M. J., & Peck, K. L. (1988). The design development and evaluation of instructional software. New York, NY: Macmillan Publishing Company.Google Scholar
  20. Hanover Research Council. (2009). Best practices in online teaching strategies. Washington, DC: Author.Google Scholar
  21. Hart, C. (2012). Factors associated with student persistence in an online program of study: A review of the literature. Journal of Interactive Online Learning, 11(1), 19–39.Google Scholar
  22. Hill, P. (2015). State of the US higher education LMS market: 2015 Edition. E-Literate. Retrieved from http://mfeldstein.com/state-of-the-us-higher-education-lms-market-2015-edition/.
  23. Ingwersen, H. (2016). The top 8 free/open source LMSs. Capterra Training Technology Blog. Retrieved from http://blog.capterra.com/top-8-freeopen-source-lmss/.
  24. Johnson, D. W., & Johnson, R. T. (2002). Meaningful assessment: A manageable and cooperative process. Boston, MA: Allyn & Bacon.Google Scholar
  25. Jonassen, D. H., & Grabowksi, B. L. (1993). Handbook of individual differences, learning, and instruction. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  26. Keller, J. M. (1987). The systematic process of motivational design. Performance and Instruction, 26(9-10), 1–8.CrossRefGoogle Scholar
  27. Keller, J. M. (1999). Motivational systems. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology: Improving individual and organizational performance worldwide (2nd ed., pp. 373–394). San Francisco, CA: Jossey-Bass.Google Scholar
  28. Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach. Boston, MA: Springer USA.CrossRefGoogle Scholar
  29. Ko, S., & Rossen, S. (2010). Teaching online: A practical guide (3rd ed.). New York, NY: Routledge.Google Scholar
  30. Kozulin, A. (2003). Psychological tools and mediated learning. In A. Kozulin, B. Gindis, V. Ageyev, & S. M. Miller (Eds.), Vygotsky’s educational theory in cultural context (pp. 15-38). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
  31. Kraiger, K., & Jerden, E. (2007). A meta-analytic investigation of learner control: Old findings and new directions. In S. M. Fiore & E. Salas (Eds.), Toward a science of distributed learning (pp. 65–90). Washington DC: APA Books.CrossRefGoogle Scholar
  32. Larson, M. B., & Lockee, B. B. (2014). Streamlined ID: A practical guide to instructional design. New York, NY: Routledge.Google Scholar
  33. Leung, A. (2003). Providing navigation aids and online learning helps to support user control: A conceptual model on computer-based learning. Journal of Computer Information Systems, 43(3), 10–17.Google Scholar
  34. Linn, R. O., & Gronlund, N. E. (2002). Measurement and assessment in teaching (8th ed.). Englewood Cliffs, NJ: Merrill/Prentice Hall.Google Scholar
  35. Mager, R. F. (1997). Preparing objectives for effective instruction (3rd ed.). Atlanta, GA: CEP.Google Scholar
  36. Markets and Markets. (2016). Learning management system market by application, delivery mode (distance learning and instructor-led training), deployment (on-premises and cloud), user type (academic and corporate), vertical and region – Global forecast to 2021. Retrieved from http://www.marketsandmarkets.com/Market-Reports/learning-management-systems-market-1266.html.
  37. Maslow, A. H. (1987). Motivation and personality (3rd ed.). New York, NY: Harper & Row.Google Scholar
  38. Mayer, R. E. (2014). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 42–71). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
  39. Moore, M. G. (1989). Three types of transactions. In M. G. Moore & C. G. Clark (Eds.), Readings in principles of distance education (pp. 100–105). University Park, PA: Pennsylvania State University.Google Scholar
  40. Nagel, L., & Kotze, T. G. (2010). Supersizing e-learning: What a COI survey reveals about teaching presence in a large online class. Internet and Higher Education, 13, 45–51. https://doi.org/10.1016/j.iheduc.2009.12.001 CrossRefGoogle Scholar
  41. Nenniger, P. (2011). Autonomy in Learning and Instruction: Roots, Frames, and Concepts of a Basic Issue. In P. R. Martin, F. M. Cheung, M. C. Knowles, M. Kyrios, L. Littlefield, J. B. Overmier, & J. M. Prieto (Eds.), IAAP handbook of applied psychology. Wiley-Blackwell: Chichester.Google Scholar
  42. Olgun, O. S., & Adali, B. (2008). Teaching grade 5 life science with a case study approach. Journal of Elementary Science Education, 20(1), 29–44.CrossRefGoogle Scholar
  43. Ormrod, J. E. (2016). Human learning (7th ed.). Boston, MA: Pearson Education.Google Scholar
  44. Palloff, R. M., & Pratt, K. (2007). Building learning communities: Effective strategies for the virtual classroom (2nd ed.). San Francisco, CA: Jossey-Bass.Google Scholar
  45. Pappas, C. (2013). Learning management systems comparison checklist of features. eLearning Industry. Retrieved from https://elearningindustry.com/learning-management-systems-comparison-checklist-of-features.
  46. Park, J., & Choi, H. J. (2009). Factors influencing adult learners’ decision to drop out or persist in online learning. Educational Technology & Society, 12(4), 207.Google Scholar
  47. Persichitte, K. A. (2000). A case study of lessons learned for the web-based educator. In B. Abbey (Ed.), Instructional and cognitive impacts of Web-based instruction (pp. 192–199). Hershey, PA: Idea Group.CrossRefGoogle Scholar
  48. Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications (2nd ed.). Upper Saddle River, NJ: Merrill/Prentice Hall.Google Scholar
  49. Rasmussen, K., & Northrup, P. T. (2000). Interactivity. Presentation at the Annual Meeting of AECT, Long Beach, CA.Google Scholar
  50. Reigeluth, C., Watson, W. R., Watson, S. L., Dutta, P., Chen, Z., & Powell, N. D. P. (2008). Roles for technology in the information-age paradigm of education: Learning management systems. Educational Technology, 48(6), 32–39.Google Scholar
  51. Richey, R., Klein, J. D., & Tracey, M. (2011). The instructional design knowledge base: Theory, research and practice. New York, NY: Routledge.Google Scholar
  52. Schwier, R. A., & Misanchuk, E. R. (1993). Interactive multimedia instruction. Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  53. Smith, P. L., & Regan, T. J. (2005). Instructional design (3rd ed.). Hoboken, NJ: John Wiley & Sons.Google Scholar
  54. Sriwongkol, T. (2002). Online learning: A model of factors predictive of course completion rate as viewed by online instructors. Unpublished dissertation, University of South Alabama, Mobile, AL.Google Scholar
  55. Stavredes, T. (2011). Effective online teaching: Foundations and strategies for student success. San Francisco, CA: Jossey-Bass: A Wiley Imprint.Google Scholar
  56. Stiggins, R. J. (2002). Assessment crisis: The absence of assessment for learning. The Phi Delta Kappan, 83(10), 758–765.CrossRefGoogle Scholar
  57. Van Merriënboer, J. J. G., & Kester, L. (2014). The four-component instructional design model: Multimedia principles in environments for complex learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 104–150). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
  58. Weiner, B. (1992). Human motivation: Metaphors, theories, and research. Newbury Park, CA: Sage.Google Scholar
  59. Wlodkowski, R. J. (2008). Enhancing adult motivation to learn: A comprehensive guide for teaching all adults (3rd ed.). San Francisco, CA: Jossey-Bass: A Wiley Imprint.Google Scholar
  60. Wlodkowski, R. J., & Ginsberg, M. B. (1995). Diversity and motivation: Culturally responsive teaching. San Francisco, CA: Jossey-Bass Publishers.Google Scholar
  61. Wlodkowski, R. J., & Ginsberg, M. B. (2010). Teaching intensive and accelerated courses: Instruction that motivates learning. San Francisco, CA: Jossey-Bass.Google Scholar

Copyright information

©  Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Counseling and Instructional ScienceUniversity of South AlabamaMobileUSA
  2. 2.Division of Research and Strategic InnovationUniversity of West FloridaPensacolaUSA
  3. 3.Department of Educational TechnologyBoise State UniversityBoiseUSA

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