Performance Criteria For Quality In Problem Solving: Engineering Analysis

Many educators believe that our educational system teaches students to solve problems using cook-book procedures, instead of teaching students how to solve problems in an effective way. In trying to raise issues of teaching and learning of problem solving, we have encountered significant resistance from both teachers (“I need to cover content”) and students (“just tell me how to get the right answer”). To address these problems, it is important to have a clear understanding of what quality looks like. Thus, we developed criteria for performance (see Appendix A), that are a set of 30 specific objectives that can be observed and measured as students engage in relevant tasks. Our work is limited in scope to problem solving that involves engineering calculations that are based on mathematical representations of scientific concepts. Our context is those engineering classes that involve significant amounts of engineering analysis. To understand present conditions, we designed a pilot (first iteration) survey to assess student and faculty beliefs about 8 of the 30 objectives. The survey provided a concrete example (scenario) of each specific objective (or performance) considered. Each scenario was assessed by asking a set of four focus questions. In simple terms, these focus questions are (a) Is this objective emphasized in engineering science courses? (b) Is this objective important? (c) Can students realistically develop this performance? and (d) What is the present level of student performance? Reliability of the survey was estimated by using statistical analysis with the Cronbach-Alpha metric. Logical validity was established through the use of expert analysis of questions relative to the theoretical construct. The survey was completed by 66 students and 15 faculty members at our institution. For each objective measured, the survey data showed similar trends that may be summarized as follows. On average, student and faculty believe (a) the objective is emphasized in engineering science courses, (b) the objective is important, (c) students can develop the requisite performance in the context of an engineering science course, and (d) present performance levels are satisfactory. These results provide evidence that performance criteria developed in this study are aligned with professor and student perceptions of quality. These results also provide a plausible explanation for the resistance that we have encountered when we have raised issues associated with teaching and learning of problem solving. Both professors and students (on average) believe that present educational practices are producing satisfactory outcomes—thus, there is no compelling need for change and efforts to promote change prompt opposition. We hypothesize that the root cause of the problem is related to assessment practices. Because most professors have had little opportunity to learn effective assessment methodologies, they tend to reach invalid conclusions about students’ abilities.