Expert conceptualizations of the domain of instructional design: An investigative study on the deep assessment methodology for complex problem-solving outcomes

Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Instructional Design, Development and Evaluation


Philip Doughty


Expert conceptualizations, Instructional design, Deep assessment, Complex problem-solving

Subject Categories

Educational Assessment, Evaluation, and Research


In simple, well-structured problem solving, assessment is straight-forward since there is usually a single correct answer to such problems. In the case of complex, ill-structured problems, such as instructional design problems, typically, performance on actual problems, while generally desirable for determining actual level of expertise, is less appropriate since these often require teams of experts and specialists interacting over a period of months to develop an actual solution. Furthermore, it is hard to evaluate individual students on the basis of their actual performances since such problems do not have standard 'correct' responses.

Given this situation, the motivation underlying this study was the lack of a reliable assessment method to determine progress in higher-order learning in situations involving complex and ill-structured problems. One may argue that differences in performance-outcomes imply domain experts conceptualize ill-structured problems differently. Another alternative explanation may be that experts do conceptualize a given problem similarly but there are other factors that lead to different performance-outcomes of experts. In this case, expert problem conceptualizations could be used as a basis for assessment.

In this direction, this study aimed at (1) exploring the processes underlying complex, ill-structured problem solving of instructional design experts to investigate whether expert instructional designers exhibit recognizable patterns in their conceptualizations of a given instructional design problem; and (2) investigating the utility of annotated causal representations for eliciting problem conceptualizations of experts in a complex, ill-structured problem domain such as instructional design.

The results of this study suggested that annotated causal representations are useful in eliciting problem conceptualizations of individuals and identifying their relative levels of expertise. In addition, expert instructional designers exhibited recognizable patterns in their conceptualizations of the given instructional design problem. Despite these similarities, however, each expert offered different solution approaches for the given problem. This was explained by the differences in the processes underlying well-structured and complex, ill-structured problem solving. Unlike in well-structured problem solving, problem conceptualization and problem solution are not two separate activities in ill-structured problem solving. Rather, they are intimately connected; they complete each other, and develop in parallel.


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