Assessing Intuition Used Among Undergraduate Engineering Technology and Engineering Students

Melissa Cai Shi; Therese M. Azevedo; Anne M. Lucietto

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Conference: 2021 ASEE Virtual Annual Conference Content Access
Location: Virtual Conference
Publication Date: July 26, 2021
Start Date: July 26, 2021
End Date: July 19, 2022
Conference Session: Focus on ETAC Accreditation
Tagged Division: Engineering Technology
Page Count: 14
DOI: 10.18260/1-2--36708
Permanent URL: https://peer.asee.org/36708
Download Count: 397

Paper Authors

biography

Melissa Cai Shi Purdue University at West Lafayette

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Melissa Cai Shi is an Undergraduate Researcher working under Dr. Lucietto. She is a student at Purdue University, pursuing a Bachelor of Science in Actuarial Science and Applied Statistics with minors in Management and Chinese. She began working under Dr. Lucietto in the Summer of 2019 as an undergraduate researcher and has thus far continued her work. She is currently working on her Honors Scholarly Project. In addition to her Actuarial coursework, Melissa serves as a leadership team leader for both the Women in Science Programs and Global Science Partners.

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Therese M. Azevedo Sonoma State University

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Therese Azevedo is a fourth year student at Sonoma State University pursuing a Bachelor of Science in Statistics. Over the Summer of 2019, she had the opportunity to work with Dr. Anne Lucietto at Purdue University on a project related to math anxiety and continued that work to present.

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Anne M. Lucietto Purdue University at West Lafayette orcid.org/0000-0003-0053-753X

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Dr. Lucietto has focused her research in engineering technology education and the understanding of engineering technology students. She teaches in an active learning style which engages and develops practical skills in the students. Currently she is exploring the performance and attributes of engineering technology students and using that knowledge to engage them in their studies while mentoring undergraduate and graduate researchers to do the same.

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Abstract

Intuition plays an essential role in decision-making and is independent of an analytical way of thinking that is considered a gut feeling. Individuals can shape their intuition, and each field of study develops a variety of skills and trains students for a way of thinking needed for that specific area. A focus on undergraduate engineering technology students and comparing them to undergraduate engineering students allows this study to examine the types of intuition used by these two groups.

The Types of Intuition Scale (TIntS), an established, validated instrument, which categorizes intuition into inferential, affective, holistic abstract, and holistic big picture intuition, was used to assess and understand the intuition types used by both engineering technology and engineering undergraduate students. Additionally, ANOVA and t-tests are used to provide deeper analysis for comparison purposes.

This study employs inferential statistics to compare engineering technology and engineering undergraduate students in their use of intuition. Anecdotal evidence shows that these students often utilize intuition to solve problems, suggesting that they use past knowledge to guide their intuition. This study's findings provide evidence that these students use intuition, and engineering technology and engineering students report using intuition in similar ways.

Citation
Format

Cai Shi, M., & Azevedo, T. M., & Lucietto, A. M. (2021, July), Assessing Intuition Used Among Undergraduate Engineering Technology and Engineering Students Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36708