Connecting Dots: Coding Multiple Data Sources to Enhance Qualitative Analysis

Bir, Devayan Debashis; Ahn, Benjamin; Çetin, Bora; Akinci-Ceylan, Cecil; Cetin, Kristen; Surovek, Andrea; Lerdal, Kristin; Anton, Mary M.; Thompson, Kyle R

doi:10.18260/1-2--32536

Cited by 1 publication

(1 citation statement)

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“…Table 3 shows a few of the codes utilized in this paper associated with the broader research study, along with some examples of quotes representing what is included in each type of code. For a full set of codes developed, please see [26][27][28]. The codes/subcodes shown in Table 3 are included in this paper because they were found to most strongly correlate with participants' learning styles.…”

Section: Discussionmentioning

confidence: 99%

Learning Styles Impact on Ill-Structured Problem Solving Processes of Engineering Students, Faculty and Professionals

Kelly,

Akinci-Ceylan,

Zhang

et al.

2023 ASEE Annual Conference &Amp; Exposition Proceedings

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Ill-structured problems are problems that are complex and open-ended in their design and as such they do not have a prescribed solution. They are generally more representative of the situations engineers face post-degree, in the "real world". As these types of problems are integrated into college engineering classrooms, it is important to consider how the learning styles of the faculty and students involved may impact this problem solving process, and if this is similar or different to that of engineering professionals. Specifically, for faculty, their personal learning basis may impact the implementation and design of such problems within the curricula. Similarly, engineering students' range of learning styles may influence how they solve or learn to solve design problems. Finally, engineering professionals' learning styles may relate to the problem solving processes and external constraints seen in their professions, but may be different from those seen in the classroom. This research thus seeks to better understand variations in students, faculty and professionals' learning styles, and how their learning styles relate to the steps and time taken to solve various steps of the problem solving process when presented with an ill-structured engineering problem.As part of a larger study, 60 undergraduate students, academic faculty, and practicing engineers within Civil Engineering were asked to solve an ill-structured problem during which they were required to verbalize what they were doing. Prior to doing this, participants were asked to complete an Index of Learning Style (ILS) survey. Recordings of their verbalization were then transcribed and coded to divide the problem solving process into steps. Analysis of this data suggests there are some differences in learning styles between undergraduate students, academic faculty, and practicing engineers. Moreover, trends suggest that certain components of a participant's preferred learning styles are predictors of the relative amount of time a participant will take to complete different steps of the problem solving process. This has implications for the teaching of such problems, since learning styles are likely to affect how a faculty teaches. This also has implications for how students learn the problem solving process. More research is needed to understand what factors and experiences may result in these differences. This includes how illstructured problems and the process used to solve them in the classroom may or may not accurately represent professional engineering problem solving processes.

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Section: Discussionmentioning

confidence: 99%