scholarly journals A Pilot Validation Study Of The Epistemological Beliefs Assessment For Engineering (Ebae): First Year Engineering Student Beliefs

2020 ◽  
Author(s):  
Adam Carberry ◽  
Matthew Ohland ◽  
Chris Swan
2016 ◽  
Vol 175 (6) ◽  
pp. 633-643 ◽  
Author(s):  
Adam Stevens ◽  
Philip Murray ◽  
Jerome Wojcik ◽  
John Raelson ◽  
Ekaterina Koledova ◽  
...  

Objective Single-nucleotide polymorphisms (SNPs) associated with the response to recombinant human growth hormone (r-hGH) have previously been identified in growth hormone deficiency (GHD) and Turner syndrome (TS) children in the PREDICT long-term follow-up (LTFU) study (Nbib699855). Here, we describe the PREDICT validation (VAL) study (Nbib1419249), which aimed to confirm these genetic associations. Design and methods Children with GHD (n = 293) or TS (n = 132) were recruited retrospectively from 29 sites in nine countries. All children had completed 1 year of r-hGH therapy. 48 SNPs previously identified as associated with first year growth response to r-hGH were genotyped. Regression analysis was used to assess the association between genotype and growth response using clinical/auxological variables as covariates. Further analysis was undertaken using random forest classification. Results The children were younger, and the growth response was higher in VAL study. Direct genotype analysis did not replicate what was found in the LTFU study. However, using exploratory regression models with covariates, a consistent relationship with growth response in both VAL and LTFU was shown for four genes – SOS1 and INPPL1 in GHD and ESR1 and PTPN1 in TS. The random forest analysis demonstrated that only clinical covariates were important in the prediction of growth response in mild GHD (>4 to <10 μg/L on GH stimulation test), however, in severe GHD (≤4 μg/L) several SNPs contributed (in IGF2, GRB10, FOS, IGFBP3 and GHRHR). Conclusions The PREDICT validation study supports, in an independent cohort, the association of four of 48 genetic markers with growth response to r-hGH treatment in both pre-pubertal GHD and TS children after controlling for clinical/auxological covariates. However, the contribution of these SNPs in a prediction model of first-year response is not sufficient for routine clinical use.


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.


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