instructional design

Title:

Instructional Design Heuristics (Rules of Thumb)
Short Description:

This study was designed to explore the heuristics (rules of thumb) experienced instructional designers use when engaged in the instructional design process. Qualitative methods were used to capture and describe individual and shared heuristics. A short video will demonstrate rules of thumb as expressed by the participants themselves.
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Background Solving problems is key to the practice of instructional design (Muraida & Spector, 1993; Perez & Emery, 1995; Rowland, 1991; Seel, Eichenwald, & Penterman, 1995). Johnson (1988) stated, “… no single correct procedure exists, and there is no definitive way of assessing the correctness of a rule based upon the outcome of a single case. There is no optimally correct rule… only rules which are relatively more accurate” (p. 212). This study is about expert use of heuristics in instructional design. Heuristics are “simple decision rules through which individuals make judgments” (Dudczak, 1995, p. 4). For purposes of this presentation, ‘heuristics’ and ‘rules of thumb’ will be used interchangeably (Abel, 2003). Purpose This study was designed to explore the heuristics experienced instructional designers use when engaged in the instructional design process. A phenomenological framework (Patton, 2002) was used to develop a deep understanding of instructional design heuristics from the perspective of 16 instructional designers. In order to achieve this, we interviewed people who have been directly involved in instructional design. Specifically, the research question was: What heuristics do experienced instructional designers use to solve instructional design problems? Methodology A purposeful sampling technique (Creswell, 2007) was used to select participants. A semi-structured interview was used to elicit a story about a complex or challenging instructional design problem on which the instructional designer had worked. In-depth information was obtained from each participant in the form of personal narratives (Kvale, 1996). Each interview lasted between 30 and 90 minutes, was audio/video-taped, and transcribed verbatim. Data Analysis In order to answer the research question, What rules of thumb do experienced instructional designers use when solving ID problems? transcripts were qualitatively coded, beginning with a search for evidence that related to the research question. Rules of thumb were extracted from participants’ responses and categorized according to common themes. Systematic steps (i.e., open coding, axial coding, and selective coding) were used to generate categories of rules of thumb (Creswell, 2007). Results Analyses of interview transcripts have identified ten categories of heuristics. Categories included: communication, management, learner/audience, pedagogy, solutions/deliverables/outcomes, process, team/people, problem/situation, client, and technology.. Within these categories, there are multiple heuristics identified. Due to limited space in this proposal, all results cannot be discussed. Some examples of results that emerged from the category Communication are the following: • When communicating with the client, listen more than you talk. (Go to the meeting and keep your ears open. They are going to say things there that you are going to need to know about later. [E.B.] I want the client to lead the conversation at this point, because they are the ones with the situation that they want to have resolved in some way. And the more that they get into talking about it, the more they begin to reveal things. [J.Q.] I let people describe the problem. And again, even though it can be difficult for me, I will not ask any questions, what so ever, until they are completely finished. [J.Q.] I very much stay quiet. I listen a lot more than I usually would. [M.G.] As a designer, you need to listen more than you talk. [R.B.]) • Verify things you’ve heard. (The first thing I want to do is I verify things that I’ve heard. Just literally, honestly, and completely verify the things that I’ve heard. Not to ask a leading question, but just simply for me to verify that what I think I’ve heard is what the client is trying to say. [J.Q.] I put things in writing and I say “do you agree with this? Is this accurate? Let’s change this until it’s accurate.” [S.P.] The confirmation message is worth gold. After a meeting, very soon after a meeting, same day if possible, “thank you for the meeting, I look forward to taking care of these things/items that we discussed at the meeting which were these things and here’s the action item list I am drawing from that.” 1 out of every 2 messages comes back with, “whoa… we really meant this,” and you have an exchange of email to clarify. [R.B.]) • Utilize visuals and tangible documents when communicating with the client. (It is always more successful for me to show people what I am thinking, than it is to tell them about it. [E.B.] People can almost never tell you what they want until you show them something they don’t want. [E.B.] Visually portray whatever process model you will be using and consider sharing that with the client or the primary stakeholder group early on in the process to help make sure the lines of communication are clear. [R.B.] When you actually create the task analysis diagram and use that in your meetings it tends to facilitate a quicker and deeper level of conversation. [R.B.]) Future efforts will be devoted to validating these heuristics as well as determining the best methods by which to share the resulting rules of thumb with novice designers Conclusion “Procedures for intelligently applying past knowledge to new experience often seem to require common sense and practical rules of thumb in addition to, or instead of, formal analysis” (Schank & Abelson, 1977, p. 3). This study elicited these rules of thumb from experienced instructional designers as a way of expanding our understanding of what practicing instructional designers utilize during their design process. This knowledge of instructional design heuristics should be imparted on novice instructional designers while they are learning the intricacies of becoming an instructional designer as a way of providing them some wisdom from more experienced designers. References Abel, C. F. (2003). Heuristics and problem solving. New Directions for Teaching and Learning, 95, 53-58. Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five approaches (2nd ed.). Thousand Oaks, CA: Sage. Dudczak, C. A. (1995). Heuristic elements of plausible reasoning. Paper presented at the Annual Meeting of the Speech Communication Association. San Antonio, TX. Ingram, A. L. (1988). Instructional design for heuristic-based problem solving. Educational Communications and Technology Journal, 36, 211-230. Johnson, E. J. (1988). Expertise and decision under uncertainty: Performance and process. In M. T. H. Chi, R. Glaser, & M. J. Farr (Eds.), The nature of expertise (pp. 209 - 228). Hillsdale, NJ: Lawrence Erlbaum. Kvale, S. (1996). InterViews: An introduction to qualitative research interviewing. Thousand Oaks, CA: Sage. Muraida, D. J., & Spector, J. M. (1993). The advanced instructional design advisor. Instructional Science, 21, 239-253. Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks, CA: Sage. Perez, R. S., & Emery, C. D. (1995). Designer thinking: How novices and experts think about instructional design. Performance Improvement Quarterly, 8(3), 80-95. Rowland, G. (1991). Problem solving in instructional design. Unpublished doctoral dissertation, Indiana University, Bloomington, IN. Schank, R. C., & Abelson, R. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. Hillsdale, NJ: Lawrence Erlbaum. Seel, N. M., Eichenwald, L. D., & Penterman, N. F. N. (1995). Automating decision support in instructional system development: The case of delivery systems. In R. D. Tennyson & A. E. Barron (Eds.), Automating instructional design: Computer-based development and delivery tools (pp. 177-216). Germany: Springer-Verlag.