Effect of Technology on Student Class Performance and Class Absence

2012 ◽  
Vol 102 (6) ◽  
pp. 471-476
Author(s):  
Sanjay Sesodia ◽  
David Molnar
Keyword(s):  
Instructional Technology ◽  
Grade Point Average ◽  
Test Performance ◽  
Test Score ◽  
Linear Regression Analysis ◽  
College Admission ◽  
Medical College Admission Test ◽  
Grade Point ◽  
Medical College ◽  
Admission Test

Background: This study examined the effect of instructional technology availability on the performance of students enrolled in a medical physiology course at a podiatric medical school. Methods: Multiple linear regression analysis was used to predict student overall test performance based on instructional technology, Medical College Admission Test score, undergraduate grade point average, and class absence. Results: The availability of instructional technology was associated with a small decline in mean test performance and a small increase in class absence. Class absence had a negative effect on test performance only when the technology was available. Total Medical College Admission Test score and grade point average were positively correlated with performance. Conclusions: Instructional technology did not enhance absentee student course performance and, indeed, hurt it. Its use as a means of providing access to additional lecture material needs to be reevaluated. (J Am Podiatr Med Assoc 102(6): 471–476, 2012)

Can We Predict Podiatric Medical School Grade Point Average Using an Admission Screen?

2012 ◽  
Vol 102 (6) ◽  
pp. 499-504 ◽  
Author(s):  
Graham P. Shaw ◽  
Evelio Velis ◽  
David Molnar
Keyword(s):  
Medical School ◽  
Grade Point Average ◽  
Test Score ◽  
College Admission ◽  
Medical College Admission Test ◽  
Data Set ◽  
Grade Point ◽  
First Semester ◽  
Medical College ◽  
Admission Test

Background: Most medical school admission committees use cognitive and noncognitive measures to inform their final admission decisions. We evaluated using admission data to predict academic success for podiatric medical students using first-semester grade point average (GPA) and cumulative GPA at graduation as outcome measures. Methods: In this study, we used linear multiple regression to examine the predictive power of an admission screen. A cross-validation technique was used to assess how the results of the regression model would generalize to an independent data set. Results: Undergraduate GPA and Medical College Admission Test score accounted for only 22% of the variance in cumulative GPA at graduation. Undergraduate GPA, Medical College Admission Test score, and a time trend variable accounted for only 24% of the variance in first-semester GPA. Conclusions: Seventy-five percent of the individual variation in cumulative GPA at graduation and first-semester GPA remains unaccounted for by admission screens that rely on only cognitive measures, such as undergraduate GPA and Medical College Admission Test score. A reevaluation of admission screens is warranted, and medical educators should consider broadening the criteria used to select the podiatric physicians of the future. (J Am Podiatr Med Assoc 102(6): 499–504, 2012)

scholarly journals Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores

2016 ◽  
Vol 7 (1) ◽  
pp. e47-e56 ◽  
Author(s):  
Banibrata Roy ◽  
Kyle Perry ◽  
Ira Ripstein ◽  
Barry Cohen
Keyword(s):  
Linear Regression ◽  
Grade Point Average ◽  
College Admission ◽  
Medical College Admission Test ◽  
Medical Council ◽  
Grade Point ◽  
National Board ◽  
Medical College ◽  
Admission Test ◽  
Medical Examiners

Background: To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores.Methods: Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson’s correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed.Results: Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT.Conclusions: Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

Undergraduate GPAs, MCAT Scores, and Academic Performance the First 2 Years in Podiatric Medical School at Des Moines University

2012 ◽  
Vol 102 (6) ◽  
pp. 446-450
Author(s):  
Robert M. Yoho ◽  
Kosta Antonopoulos ◽  
Vassilios Vardaxis
Keyword(s):  
Academic Performance ◽  
Medical School ◽  
Test Score ◽  
College Admission ◽  
Medical College Admission Test ◽  
Grade Point ◽  
Medical College ◽  
Pooled Data ◽  
Des Moines ◽  
Admission Test

Background: This study was performed to determine the relationship between undergraduate academic performance and total Medical College Admission Test score and academic performance in the podiatric medical program at Des Moines University. The allopathic and osteopathic medical professions have published educational research examining this relationship. To our knowledge, no such educational research has been published for podiatric medical education. Methods: The undergraduate cumulative and science grade point averages and total Medical College Admission Test scores of four podiatric medical classes (2007–2010, N = 169) were compared with their academic performance in the first 2 years of podiatric medical school using pairwise Pearson product moment correlations and multiple regression analysis. Results: Significant low to moderate positive correlations were identified between undergraduate cumulative and science grade point averages and student academic performance in years 1 and 2 of podiatric medical school for each of the four classes (except one) and the pooled data. There was no significant correlation between Medical College Admission Test score and academic performance in years 1 and 2 (except one) and the pooled data. Conclusions: These results identify undergraduate cumulative grade point average as the strongest cognitive admissions variable in predicting academic performance in the podiatric medicine program at Des Moines University, followed by undergraduate science grade point average. These results also suggest limitations of the total Medical College Admission Test score in predicting academic performance. Information from this study can be used in the admissions process and to monitor student progress. (J Am Podiatr Med Assoc 102(6): 446–450, 2012)

Can We Predict First-time Failure on the Podiatric Boards Using an Admission Screen?

2012 ◽  
Vol 102 (6) ◽  
pp. 485-490
Author(s):  
David Molnar ◽  
Jeffrey Jensen ◽  
Larissa Rolim
Keyword(s):  
Grade Point Average ◽  
Logistic Regression Model ◽  
College Admission ◽  
The Other ◽  
Medical College Admission Test ◽  
True Positive ◽  
Grade Point ◽  
Medical College ◽  
Admission Test ◽  
First Time

Background: This study examined the success of an admission screen in identifying applicants who will fail Part I or Part II of the Podiatric Boards on the first attempt. Methods: A logistic regression model was used to predict failure on the Podiatric Boards. Results: The biology Medical College Admission Test (MCAT) score predicted failure on Part I and Part II. Adding undergraduate grade point average and the other MCAT subscores did not significantly improve the prediction. Although a screen based on the biology MCAT score can identify nearly 90% of those who fail, there are six false-positives for every true-positive. Conclusions: First-time Board failure can be predicted, but Board failure must be primarily addressed by interventions after matriculation rather than by an admission screen. (J Am Podiatr Med Assoc 102(6): 485–490, 2012)

Can We Predict 4-year Graduation in Podiatric Medical School Using Admission Data?

2012 ◽  
Vol 102 (6) ◽  
pp. 463-470 ◽  
Author(s):  
Sanjay Sesodia ◽  
David Molnar ◽  
Graham P. Shaw
Keyword(s):  
Medical School ◽  
Test Score ◽  
At Risk Students ◽  
Predictive Ability ◽  
College Admission ◽  
Educational Background ◽  
High Rate ◽  
Medical College Admission Test ◽  
Medical College ◽  
Admission Test

Background: This study examined the predictive ability of educational background and demographic variables, available at the admission stage, to identify applicants who will graduate in 4 years from podiatric medical school. Methods: A logistic regression model was used to identify two predictors of 4-year graduation: age at matriculation and total Medical College Admission Test score. The model was cross-validated using a second independent sample from the same population. Cross-validation gives greater confidence that the results could be more generally applied. Results: Total Medical College Admission Test score was the strongest predictor of 4-year graduation, with age at matriculation being a statistically significant but weaker predictor. Conclusions: Despite the model’s capacity to predict 4-year graduation better than random assignment, a sufficient amount of error in prediction remained, suggesting that important predictors are missing from the model. Furthermore, the high rate of false-positives makes it inappropriate to use age and Medical College Admission Test score as admission screens in an attempt to eliminate attrition by not accepting at-risk students. (J Am Podiatr Med Assoc 102(6): 463–470, 2012)

scholarly journals What Influences the Decision to Interview a Candidate for Medical School?

2020 ◽  
Vol 185 (11-12) ◽  
pp. e1999-e2003
Author(s):  
Ting Dong ◽  
Jeffrey Hutchinson ◽  
Dario Torre ◽  
Steven J Durning ◽  
Anthony R Artino ◽  
...  
Keyword(s):  
Health Service ◽  
Medical School ◽  
College Admission ◽  
Medical College Admission Test ◽  
Military Experience ◽  
Military Health ◽  
Grade Point ◽  
Medical College ◽  
Holistic Review ◽  
Admission Test

ABSTRACT Introduction Holistic review, in which medical schools seek to balance applicant attributes and experiences alongside traditional academic metrics in making admissions decisions, has been in place for over a decade. Medical school applicants and the admissions’ community are still trying to understand the impact of holistic review on the composition of those medical schools choose to interview and accept. Materials and Method The study cohort included all candidates who applied to Uniformed Services University of the Health Sciences (USU) in 2014, 2015, and 2016 (N = 8,920). We conducted logistic regression analysis to examine the associations between the sociodemographic, academic, and military service variables of applicants applying to the School of Medicine and offers for interview. Results Medical College Admission Test scores and undergraduate grade point averages were important in predicting who would receive an interview. Having military experience, being a woman, and being self-reported African American race also predicted a higher likelihood of receiving an interview invitation. For example, controlling for all other variables in the model, if an applicant had previous military experience, the odds of being invited for interview was about 4 times that of an applicant who had no previous military experience. Leave this for the text and discussion. The resulting pool of interviewed and accepted students more increasingly represented the Military Health Service population served. Conclusions The use of holistic review generated a class with a composition different from that which would be predicted by Medical College Admission Test and grade point average alone. Further, holistic review produced an interview pool and class more representative of the wider Military Health Service beneficiary population. In the case of USU, holistic review allowed the school to better meet its mission to create a representative class able to “care for those in harm’s way.”

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