- Conference Session
- Ocean and Marine Division (OMED) Technical Session 1
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
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Robert Kidd, State University of New York, Maritime College; Martin S. Lawless, State University of New York, Maritime College; Kathryn R. Gosselin, State University of New York, Maritime College
- Tagged Divisions
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Ocean and Marine Division (OMED)
engineering courses and found that first-time freshmen performed betterthan transfer students, and additionally, that this trend persisted across multiple instructors andsemesters of the same course [5]. A number of possible causes for this have been examined;Laanan et al. found in a survey of transfer students that many felt less comfortable interactingwith faculty at their new institution, and some felt increased stress and received lower grades [3].Concannon and Barrow found that engineering transfer students have lower self-efficacy thanfirst-time freshman, which was theorized to be due to transfer shock [4].A systematic literature review [6] was unable to locate research on transfer students after theirfirst post-transfer year, although the same
- Conference Session
- Ocean and Marine Division (OMED) Poster Session
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
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Gregory Murad Reis, Florida International University; Luana Okino Sawada, Florida International University; Paulo Padrao, Florida International University; Jose Fuentes, Florida International University
- Tagged Divisions
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Ocean and Marine Division (OMED)
modest, implying that encountering and overcoming real-data challengesreinforces students’ self-efficacy. In our course, even when some project results were imperfect,students gained assurance that they could approach complex, messy problems – an outcome alsoemphasized by educators advocating for realism in data science education. Addressing real-worldcomplexity (e.g. missing data, noisy measurements) in a supportive classroom setting helpsvalidate students’ abilities; acknowledging and working through data challenges can help renew astudent’s confidence in applying their knowledge 23 . By the end of the term, open-ended feedbackfrom our participants frequently mentioned confidence –“I feel more prepared to analyze realdatasets on my own