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This research paper elaborates on the process used by a team of researchers to create a codebook from interviews of Civil Engineers who included students, professors, and professionals, solving ill-structured problems. The participants solved two ill-structured problems while speaking aloud their thought process. In addition to recording the participant verbalization, the solution to their problems were also collected with the use of a smart pen. Creating a codebook from interviews is a key element of qualitative analysis forming the basis for coding. While individuals can create codebooks for analysis, a team-based approach is advantageous especially when dealing with large amounts of data. A team-based approach involves an iterative process of inter-rater reliability essential to the trustworthiness of the data obtained by coding. In addition to coding the transcripts as a team, which consisted of novice, intermediate, and experts in the engineering education field, the audio and written solution to the problems were also coded. The use of multiple data sources to obtain data, and not just the verbatim transcripts, is lesser studied in engineering education literature and provides opportunities for a more detailed qualitative analysis. Initial codes were created from existing literature, which were refined through an iterative process. This process consisted of coding data, team consensus on coded data, codebook refinement, and recoding data with the refined codes. Results show that coding verbatim transcripts might not provide an accurate representation of the problem-solving processes participants used to solve the ill-structured problem. Benefits, challenges and recommendations regarding the use of multiple sources to obtain data are discussed while considering the amount of time required to conduct such analysis. 

One of the main skills of engineers is to be able to solve problems. It is generally recognized that real-world engineering problems are inherently ill structured in that they are complex, defined by non-engineering constraints, are missing information, and contain conflicting information. Therefore, it is very important to prepare future engineering students to be able to anticipate the occurrence of such problems, and to be prepared to solve them. However, most courses are taught by academic professors and lecturers whose focus is on didactic teaching of fundamental principles and code-based design approaches leading to predetermined “right” answers. Most classroom taught methods to solve well-structured problems and the methods needed to solve ill-structured problems are strikingly different. The focus of our current effort is to compare and contrast the problem solving approaches employed by students, academics and practicing professionals in an attempt to determine if students are developing the necessary skills to tackle ill-structured problems. To accomplish this, an ill-structured problem is developed, which will later be used to determine, based on analysis of oral and written responses of participants in semi-structured interviews, attributes of the gap between student, faculty, and professional approaches to ill-structured problem solving. Based on the results of this analysis, we will identify what pedagogical approaches may limit and help students’ abilities to develop fully-formed solutions to ill-structured problems.