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We all have moments when we are struck by a “gut feeling” or a “sixth sense” about something. It could pertain to a relationship or task at work. That sense can be broadly termed intuition. Intuitive decisionmaking is an essential characteristic of individuals who have attained a certain level of expertise. The development of expertise and intuition are heavily influenced by experience. Engineering intuition is defined as an experience-informed skill subconsciously leveraged in problem solving by engineering practitioners when under pressure from constraints such as lack of time. Practicing engineers use and develop intuition regularly on-the-job, but the use of intuition is often discouraged in undergraduate education. The disconnect between intuition’s use in engineering practice and in education, coupled with our limited knowledge of the relationship between intuition, expertise, and experience, presents an important gap in our existing understanding of engineering problem solving and future workforce preparation. Through this Research in the Formation of Engineers (RFE) grant, we seek to address this gap by examining the application of intuition by engineering practitioners to generate knowledge that promotes professional formation and development of a stronger engineering workforce. 

This work-in-progress research paper describes the pilot work in a study seeking to gain further insight on the relationships between intuition, expertise, and experience through a better understanding of how intuition is applied in engineering problem solving. Individuals who have attained a high level of expertise, exhibit characteristics of intuitive decision making (Dreyfus & Dreyfus, 1980). The development of expertise (Dreyfus &; Dreyfus, 1980; Seifert et al., 1997) and intuition (Authors, 2019; Authors, 2023) are heavily influenced by experience. Engineering intuition can be summarized as a subconscious problem-solving skill that is based on previous experience (Authors, 2023). In this work, we will be using Cognitive Task Analysis (CTA) to examine the use of intuition in engineering problem solving. CTA is a class of observational protocols that surface tacit knowledge through engaging experts with a task (Crandall, 2006). The purpose of CTA is to capture how the mind works through three primary aspects: knowledge elicitation, data analysis, and knowledge representation. As best CTA practices use multiple methods, we will use three methods for this analysis, 1) Simulation Interviews where participants are given a simulated engineering problem and asked to speak out loud to describe their process in approaching the problem, 2) Critical Decision Method (Klein, 1989) where a retrospective interview probes the decisions made during the simulation interview, and 3) Knowledge Audit Method (Taheri et al., 2014) which further guides our probing questions to identify types of knowledge used, or not used, during the simulated problem solving experience. These three techniques are applied to collect data on participants' problem solving. To develop the problems for the Simulation Interviews, we have first conducted pilot work using just the Critical Decision Method and Knowledge Audit Method. As part of the Critical Decision Method, participants will select a non routine problem-solving incident, construct an incident timeline, identify decision points for future probing, and then probe these decisions using the Knowledge Audit Method. This method allows us to determine realistic, practice-based problems for the Simulation Interview, why the participant makes certain decisions, and how their educational background and on the job training influenced their decision making process. The anticipated outcomes of this research are to expand engineering education through a better understanding of engineering intuition and to provide a foundation for the explicit application of intuition in engineering problem solving. These insights can be beneficial for creating educational interventions that promote intuition development and introduce real-world engineering practices in the classroom. This in turn can promote metacognition in engineering students by creating pathways to expertise development, as well as boost confidence and support retention (Metcalfe & Wiebe, 1987; Bolton, 2022; Authors, 2021; Authors, 2023). Additionally, insights into intuition can be beneficial in onboarding new hires who may have more expertise development, agility, and adaptability to the technical landscape in the engineering workforce. References: Authors. (2021). Authors. (2019). Authors. (2023). Bolton, C. S. (2022). What Makes an Expert? Characterizing Perceptions of Expertise and Intuition Among Early-Career Engineers [Undergraduate Honors Thesis, Bucknell University]. Lewisburg, PA. Crandall, B., Klein, G. A., &; Hoffman, R. R. (2006). Working minds: A practitioner's guide to cognitive task analysis. MIT Press. Dreyfus, S. E., & Dreyfus, H. L. (1980). A Five-Stage Model of the Mental Activities Involved in Directed Skill Acquisition. Klein, G. A, Calderwood, R., and Macgregor, D. (1989). Critical decision method for eliciting knowledge, IEEE Transactions on systems, man, and cybernetics, 19(3), 462-472. https://doi.org/10.1109/21.31053 Metcalfe, J., & Wiebe, D. (1987). Intuition in Insight and Noninsight Problem Solving. Memory & Cognition, 15(3), 238-246. https://doi.org/10.3758/BF03197722. Seifert, C. M., Patalano, A. L., Hammond, K. J., & Converse, T. M. (1997). Experience and expertise: The role of memory in planning for opportunities. In P. J. Feltovich, K. M. Ford, & R. R. Hoffmanm (Eds.), Expertise in Context (pp. 101-123). AAAI Press/ MIT Press. Taheri, L., Che Pa, N., Abdullah, R., & Abdullah, S. (2014). Knowledge audit model for requirement elicitation process. International Scholarly and Scientific Research & Innovation, 8(2), 452-456. 

Engineering problem solving has become more complex and reliant on technology making engineering judgement an increasingly important and essential skill for engineers. Educators need to ensure that students do not become rote learners with little ability to critically analyze the result of solutions. This suggests that greater focus should be placed on developing engineering judgement, specifically engineering intuition, in our students who will be the future engineering workforce. This project is focused on the following four research questions: 1) What are practicing professional engineers’ perceptions of discipline specific intuition and its use in the workplace? 2) Where does intuition manifest in expert engineer decision-making and problem-solving processes? 3) How does the motivation and identity of practicing professional engineers relate to discipline-specific intuition? 4) What would an instrument designed to validly and reliably measure engineering intuition look like? Literature from the fields of nursing (Smith), management (Simon), and expertise development (Dreyfus) suggest intuition plays a role in both decision making and becoming an expert. This literature is used to support our definition of engineering intuition which is defined as the ability to: 1) assess the feasibility of a solution or response, and 2) predict outcomes and/or options within an engineering scenario (Authors). This paper serves as an update on the progress of our work to date. The first three research questions have been addressed through interviews with engineering practitioners at various stages in their careers, from early career to retired. Emergent findings have allowed us to construct a modified definition of engineering intuition, while also identifying related constructs. In Spring 2021, we created and tested an instrument to measure intuition. This instrument was re-deployed in Fall 2021. Preliminary results from the project’s qualitative and quantitative efforts will be presented. Our ultimate aim of this project is to inform the creation of classroom practices that improve students’ ability to develop, recognize, and improve their own engineering intuition. Select References: Authors (2020). Dreyfus, Stuart E., and Hubert L. Dreyfus. A five-stage model of the mental activities involved in directed skill acquisition. No. ORC-80-2. California Univ Berkeley Operations Research Center, 1980. Smith, Anita. "Exploring the legitimacy of intuition as a form of nursing knowledge." Nursing Standard (through 2013) 23.40 (2009): 35. Simon, Herbert A. "Making management decisions: The role of intuition and emotion." Academy of Management Perspectives 1.1 (1987): 57-64. 

CONTEXT - Judging the feasibility of solutions has become an increasingly important engineering skill as engineering problem solving has become more complex and technology-dependent. Engineering education must take care to foster engineering judgement in our students to produce robust problem solvers primed to critically evaluate and interpret output. Our work uses expertise development and dual-cognition processing theories (Dreyfus & Dreyfus, 1980; Smith, 2009; Simon, 1987) to frame such engineering judgement as engineering intuition or the ability to assess the outcome of an engineering solution and predict outcomes within an engineering scenario (Miskioğlu and Martin, 2019). PURPOSE OR GOAL - Our overarching goal is to create classroom interventions that explicitly recognize and enhance the development of engineering intuition. Accomplishing this goal requires a means of measuring engineering intuition before and after such interventions. This paper discusses our process to develop the Predicting and Evaluating Engineering Problem Solving (PEEPS) tool for measuring engineering intuition. APPROACH OR METHODOLOGY/METHODS - PEEPS is built directly on our prior qualitative work with practicing engineers, which revealed the construct of engineering intuition (Aaron et al., 2020). The emergent findings were combined with questions adapted from the Concept Assessment Tool for Statics (Steif & Dantzler, 2005) to create a preliminary survey assessing intuition. Additional items asked participants to assess their level of confidence in their answers. The survey was designed such that the statics problems could be switched out for other forms of engineering problems. Think-aloud sessions were used to check face validity and usability prior to full deployment in Spring 2021. ACTUAL OR ANTICIPATED OUTCOMES - This study details the process used to create PEEPS. Modifications were made following 19 think aloud sessions. The initial deployment in Spring 2021 resulted in 88 completed responses with responses primarily coming from white, male, aerospace engineering students who had previously performed well in their statics courses. CONCLUSIONS/RECOMMENDATIONS/SUMMARY - This work showcases a new survey designed to assess the engineering intuition of engineering students. Next steps include expanding the work to a more diverse sample of engineering students, further validity checks of the instrument, and pairing the instrument with newly created educational interventions designed to better foster engineering intuition development in students. KEYWORDS - engineering judgement, problem solving, survey development 

CONTEXT - Judging the feasibility of solutions has become an increasingly important engineering skill as engineering problem solving has become more complex and technology-dependent. Engineering education must take care to foster engineering judgement in our students to produce robust problem solvers primed to critically evaluate and interpret output. Our work uses expertise development and dual-cognition processing theories (Dreyfus & Dreyfus, 1980; Smith, 2009; Simon, 1987) to frame such engineering judgement as engineering intuition or the ability to assess the outcome of an engineering solution and predict outcomes within an engineering scenario (Miskioğlu and Martin, 2019). PURPOSE OR GOAL - Our overarching goal is to create classroom interventions that explicitly recognize and enhance the development of engineering intuition. Accomplishing this goal requires a means of measuring engineering intuition before and after such interventions. This paper discusses our process to develop the Predicting and Evaluating Engineering Problem Solving (PEEPS) tool for measuring engineering intuition. APPROACH OR METHODOLOGY/METHODS - PEEPS is built directly on our prior qualitative work with practicing engineers, which revealed the construct of engineering intuition (Aaron et al., 2020). The emergent findings were combined with questions adapted from the Concept Assessment Tool for Statics (Steif & Dantzler, 2005) to create a preliminary survey assessing intuition. Additional items asked participants to assess their level of confidence in their answers. The survey was designed such that the statics problems could be switched out for other forms of engineering problems. Think-aloud sessions were used to check face validity and usability prior to full deployment in Spring 2021. ACTUAL OR ANTICIPATED OUTCOMES - This study details the process used to create PEEPS. Modifications were made following 19 think aloud sessions. The initial deployment in Spring 2021 resulted in 88 completed responses with responses primarily coming from white, male, aerospace engineering students who had previously performed well in their statics courses. CONCLUSIONS/RECOMMENDATIONS/SUMMARY - This work showcases a new survey designed to assess the engineering intuition of engineering students. Next steps include expanding the work to a more diverse sample of engineering students, further validity checks of the instrument, and pairing the instrument with newly created educational interventions designed to better foster engineering intuition development in students. KEYWORDS - engineering judgement, problem solving, survey development 

This work in progress paper describes preliminary findings from interviews intending to develop a definition of and method for measuring “engineering intuition.” Engineers are asked regularly in their profession to judge situations and predict or estimate results in order to minimize the potential for error. The need for this ability has been amplified with the pervasiveness of computer-aided problem solving in engineering. It is now mandatory for practicing engineers to quickly and accurately evaluate software results as part of the problem-solving process. We hypothesize that the ability to undertake such actions is heavily influenced by discipline-specific intuition, which has been previously explored in the disciplines of nursing and business management. The following study presents preliminary results attempting to define the construct of “engineering intuition.” Semi-structured interviews with practicing nurses, business managers, and engineers were conducted using: 1) implicit discussion around intuition informed by literature, and 2) critical incident technique, i.e., explicit discussion around the concept of intuition. Each interview sought to identify practitioner decision-making and problem-solving processes on the job. The combined dataset and supporting literature are planned to be used as the basis of our future work, which ultimately aims to develop a psychometrically tested instrument capable of accurately measuring engineering intuition. Dissemination of these preliminary results are intended to elicit feedback on our methodologies and findings before moving to the second phase of our research study. 

This Research Category - Full Paper presents initial emergent themes from our quest to understand the construct of intuition. Our work uses theories of expertise development and dual-cognitive processing frameworks to provide a theoretical grounding to define discipline-specific intuition. We hypothesize that intuition can be observed in disciplinary experts through discussions of experience and decision-making processes. Interviews were conducted with professionals in three fields - engineering, nursing, and business management - that engage intuition in decision-making. A comparative analysis of emergent themes is presented to understand similarities and differences in use and definition across these disciplines. Parallel grounded theory and critical incident technique approaches were used to identify perceptions and incidents of intuition. Results suggest that intuition can be defined as a "sense of knowing" that is context specific and at least partly attributable to experience. Inclusion of multiple fields and comparisons across disciplines form the foundation for our future work focusing solely on engineering intuition.