Students As Sequential Decision-Makers: Quantifying the Impact of Problem Knowledge and Process Deviation on the Achievement of Their Design Problem Objective

Factors such as a student’s knowledge of the design problem and their deviation from a design process impact the achievement of their design problem objective. Typically, an instructor provides students with qualitative assessments of such factors. To provide accurate assessments, there is a need to quantify the impact of such factors in a design process. Moreover, design processes are iterative in nature. Therefore, the research question addressed in this study is, How can we quantify the impact of a student’s problem knowledge and their deviation from a design process, on the achievement of their design problem objective, in successive design iterations? We illustrate an approach in the context of a decision-making scenario. In the scenario, a student makes sequential decisions to optimize a mathematically unknown design objective with given constraints. Consequently, we utilize a decision-making model to abstract their design process. Their problem knowledge is quantified as their belief about the feasibility of the design space via a probability distribution. Their deviation from the decision-making model is quantified by introducing uncertainty in the model. We simulate cases where they have a combination of high (or low) knowledge of the design problem and high (or low) deviation in their design process. The results of our simulation study indicate that if students have a high (low) deviation from the modeled design process then we cannot (can) infer their knowledge of the design problem based on their problem objective achievement.