Computational Thinking in the Formation of Engineers (Year 1)

Diaz, Noemi V. Mendoza; Meier, Russ; Trytten, Deborah A.; Yoon, So Yoon; Moore, Janie McClurkin; Ogilvie, Andrea M.; Weichold, M.H.

doi:10.18260/1-2--36826

Cited by 3 publications

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The research goals of the multi-institutional project include answering multiple research questions regarding computational thinking and how it impacts the enculturation of students into the engineering profession. Outputs of the project that have been documented previously include a computational thinking framework for engineering education, the multiple-choice questions that form the ECTD, and the continuous improvement process used to refine the diagnostic questions [8]- [10], [72], [73] . This continuous improvement process is diagrammed in Figure 1.…”

Section: A Diagnostic Developmentmentioning

confidence: 99%

Development and Validation of the Engineering Computational Thinking Diagnostic for Undergraduate Students

Mendoza Diaz,

Yoon,

Trytten

et al. 2023

IEEE Access

Self Cite

View full text Add to dashboard Cite

Computational thinking is one barrier to enculturating as a professional engineer. We created the Engineering Computational Thinking Diagnostic (ECTD) as an instructional tool that can identify at-risk first-year engineering students. The purpose of this study is to provide construct validity, internal consistency reliability, item characteristics, and criterion validity evidence for this diagnostic. From fall 2020 to fall 2021, 469 students from three institutions in the United States took the diagnostic. The data from 152 students at one institution was used to provide evidence of predictive validity. Exploratory and confirmatory factor analyses resulted in 20 items loading onto one factor in a good model fit range, with the internal consistency reliability coefficient, Cronbach α of 0.86. From item analyses based on classical test theory, the diagnostic items on average tended to be slightly easy but had sufficient discrimination power. The correlation matrix for criterion validity evidence indicated that the diagnostic functions well to differentiate students' computational thinking ability by prior computer science course experience as well as by first-generation status. Predictive validity evidence from regression analyses revealed the statistically significant effect of students' diagnostic scores assessed at the beginning of the first semester on predicting their end of semester course grades. The ECTD can have a broad impact because it provides a tool to gauge the entry-level skills of students, enabling early curriculum interventions to help retention and persistence to graduation. We make the case that the ECTD could contribute to the development of a more diverse workforce in engineering.

show abstract

Section: A Diagnostic Developmentmentioning

confidence: 99%

Development and Validation of the Engineering Computational Thinking Diagnostic for Undergraduate Students

Mendoza Diaz,

Yoon,

Trytten

et al. 2023

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…Exploratory factor analysis was again conducted by the statistical consultant. All eigenvalues and correlations between items confirmed the instrument validated against a single factor called computational thinking [11].…”

Section: Instrument Validationmentioning

confidence: 64%

Computational Thinking in the Formation of Engineers: Year 2

Mendoza Diaz,

Meier,

Trytten

et al.

2022 ASEE Annual Conference &Amp; Exposition Proceedings

View full text Add to dashboard Cite

Dr. Mendoza is a faculty member of Technology Management in the College of Education-Engineering at Texas A&M University. She has worked as electrical engineering professor in Mexico. She recently obtained funds from NSF to investigate enculturation to engineering and computational thinking in engineering students. She is the co-advisor of the Society for Hispanic Professional Engineers at TAMU and is interested in computing engineering education and Latinx engineering entrepreneurship.

show abstract

“…We then transcribed the interviews, coded the interview transcripts, and performed a qualitative thematic analysis of the data. We found many forms of academic and socioeconomic privilege that ease student transitions into engineering, usually by hearing from students who lacked the privilege [24], [25]. Examples of academic privileges we found include the availability of AP courses in high school, prior computer programming experience through structured high school classes, and prior programming experience through extracurricular activities.…”

Section: Second Major Resultsmentioning

confidence: 96%

Board 240: Computational Thinking in the Formation of Engineers: Year 3

Mendoza Diaz,

Meier,

Trytten

et al.

2023 ASEE Annual Conference &Amp; Exposition Proceedings

View full text Add to dashboard Cite

where she received a B.S. in Bio Environmental Engineering in 2006. She then began pursuing her graduate education at Purdue University in the Agricultural and Biological Engineering Department, completing her Ph.D. in 2015. Her primary research areas include 1) mycotoxin risk assessment and treatment in stored grains and 2) innovate instructional strategies for Biological and Agricultural Engineering students. She is also a Member of the Engineering Education Faculty, In-

show abstract

Computational Thinking in the Formation of Engineers (Year 1)

Cited by 3 publications

References 7 publications

Development and Validation of the Engineering Computational Thinking Diagnostic for Undergraduate Students

Development and Validation of the Engineering Computational Thinking Diagnostic for Undergraduate Students

Computational Thinking in the Formation of Engineers: Year 2

Board 240: Computational Thinking in the Formation of Engineers: Year 3

Contact Info

Product

Resources

About