A Statistical Evaluation of the Value of Pre-Engineering Curricula on First-Year Civil Engineering Student Performance

AEI 2017 ◽  
2017 ◽  
Author(s):  
Christopher H. Raebel ◽  
Blake Wentz ◽  
Frank Mahuta
Author(s):  
Lauren Dent ◽  
Patricia Maloney ◽  
Tanja Karp

Service-learning presents exciting new ways for students to enhance their learning.  Educators and scholars agree that service-learning is connected to self-efficacy, which affects student performance.  This research tests the development of self-efficacy in students enrolled in service-learning and traditional sections of a first-year engineering course. Using a previously developed metric, the Engineering Skills Assessment (ESA), students enrolled in service-learning (SL) and “traditional” (non-SL) sections quantified self-efficacy on 11 skills previously deemed important for engineering.  Student responses were compared between SL and non-SL students at the beginning and end of the semester.  Analysis of the collected data using exploratory factor analysis (EFA) grouped self-efficacy ratings for the 11 skills into three meaningful constructs: (1) Job-related skills (2) Interpersonal skills and (3) Life skills.  Mean self-efficacy scores were significantly better at the end of the course for non-SL students in all areas and for SL students in four of the 11 skills and two of the three constructs.  Self-efficacy growth was significantly higher for non-SL students, which may be due to the Dunning-Kruger effect.  However, similar percentages of both populations self-reported that their skills were improved at the end of the semester due to the class.  This research also supports the use of the ESA as a reliable psychometric tool to evaluate student self-efficacy and its relationship to service-learning.


Author(s):  
Nachirat Rachburee ◽  
Wattana Punlumjeak

<span>The first year of an engineering student was important to take proper academic planning. All subjects in the first year were essential for an engineering basis. Student performance prediction helped academics improve their performance better. Students checked performance by themselves. If they were aware that their performance are low, then they could make some improvement for their better performance. This research focused on combining the oversampling minority class data with various kinds of classifier models. Oversampling techniques were SMOTE, Borderline-SMOTE, SVMSMOTE, and ADASYN and four classifiers were applied using MLP, gradient boosting, AdaBoost and random forest in this research. The results represented that Borderline-SMOTE gave the best result for minority class prediction with several classifiers.</span>


1996 ◽  
Vol 5 (1) ◽  
pp. 47-57
Author(s):  
J. A. Cilliers ◽  
P. Kruger ◽  
I. Basson ◽  
P. A. Kirschner

2006 ◽  
Vol 15 (3) ◽  
pp. 234-256 ◽  
Author(s):  
Mick Short

This article reports on research conducted in the department of Linguistics and English Language at Lancaster University from 2002 to 2005 on first-year undergraduate student performance in, and reaction to, a web-based introductory course in stylistic analysis. The main focus of this report is a comparison of student responses to the varying ways in which the web-based course was used from year to year. The description of student responses is based on an analysis of end-of-course questionnaires and a comparison of exit grades. In 2002–3, students accessed the first two-thirds of the course in web-based form and the last third through more traditional teaching. In 2003–4 the entire course was accessed in web-based form, and in 2004–5 web-based course workshops were used as part of a combined package which also involved weekly lectures and seminars. Some comparison is also made with student performance in, and responses to, the traditional lecture + seminar form of the course, as typified in the 2001–2 version of the course.


2016 ◽  
Vol 7 (2) ◽  
Author(s):  
Shannon Reidt ◽  
Keri Hager ◽  
James Beattie ◽  
Amy Pittenger ◽  
Maureen Smith ◽  
...  

This case study describes a longitudinal curricular sequence implemented to teach evidence-based medicine (EBM) skills. The longitudinal sequence is innovative in its approach, design, and assessment of EBM. This approach moves away from the conventional strategy of teaching drug information and drug literature evaluation as stand-alone courses and instead embraces the EBM Framework and its use in the context of authentic problem solving. The EBM Framework—Ask, Acquire, Appraise, and Apply—was used as the basis for defining seven EBM skills. These skills were targeted in the evidence-based, integrated design of 17 learning episodes delivered with eight faculty members through six courses in the first year. Student perceptions of relevance of EBM and performance on assessments and learning activities throughout the sequence suggest that integrating EBM across the first year of the curriculum is an effective strategy for teaching EBM skills. Three themes emerged from analysis of the data and experience, including the need for: a strong teaching team, a whole task approach with a focus on solving authentic problems, and care in interpreting the progression of assessments and patterns of student performance. Through instructor observations and peer review, the longitudinal sequence has been refined and has had an impact on the rest of the curriculum.   Type: Case Study


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248629
Author(s):  
Johan Coenen ◽  
Bart H. H. Golsteyn ◽  
Tom Stolp ◽  
Dirk Tempelaar

In this study, we investigate whether Conscientiousness, Emotional Stability and Risk Preference relate to student performance in higher education. We employ anchoring vignettes to correct for heterogeneous scale use in these non-cognitive skills. Our data are gathered among first-year students at a Dutch university. The results show that Conscientiousness is positively related to student performance, but the estimates are strongly biased upward if we use the uncorrected variables. We do not find significant relationships for Emotional Stability but find that the point estimates are larger when using the uncorrected variables. Measured Risk Preference is negatively related to student performance, yet this is fully explained by heterogeneous scale use. These results indicate the importance of using more objective measurements of personality traits.


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