Dataset Information

Semantic fluency including task switching predicts academic success in medical school.

ABSTRACT:

Objectives

The future state treaty on the admission of students to German medical schools calls for a variety of selection criteria among which at least two are required to be independent of school leaving grades. Against this background, the present study investigated achievement motivation and executive functions as predictors of academic success in medical school.

Material and methods

Second year medical students were assessed for executive functioning by using the Tower of London Test (ToL), a German version of the Controlled Oral Word Association Test (COWAT), the Trail Making Test (TMT-A) and for motivation by using the Achievement Motivation Inventory (AMI). Academic success was evaluated twofold, i) whether the first state exam (M1) was passed at the earliest possible, after completion of the second year and ii) via the grades obtained.

Results

81 out of 226 students enrolled participated in our study. Passing the M1 was best explained by semantic fluency including task switching. Moreover, academically successful students achieved significantly higher levels in the AMI-facets "compensatory effort" and "engagement". All students scored above average in the TMT-A and average in the ToL.

Conclusion

Alternating semantic fluency-requiring simultaneously inhibition, updating and task shifting-turned out highly predictive of academic success in medical school. Moreover, higher levels in "compensatory effort" and "engagement" suggested that both, increased energy expenditure as response to fear of failure and elevated readiness to exert effort also impacted positively on success.

SUBMITTER: Kaufmann S

PROVIDER: S-EPMC7771681 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Semantic fluency including task switching predicts academic success in medical school.

Kaufmann Sabrina S Glass Änne Ä Kropp Peter P Müller-Hilke Brigitte B

PloS one 20201229 12

<h4>Objectives</h4>The future state treaty on the admission of students to German medical schools calls for a variety of selection criteria among which at least two are required to be independent of school leaving grades. Against this background, the present study investigated achievement motivation and executive functions as predictors of academic success in medical school.<h4>Material and methods</h4>Second year medical students were assessed for executive functioning by using the Tower of Lon ...[more]

PMID: 33373421

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Project description:The acceptance of students to a medical school places a considerable emphasis on performance in standardized tests and undergraduate grade point average (uGPA). Traditionally, applicants may be judged as a homogeneous population according to simple quantitative thresholds that implicitly assume a linear relationship between scores and academic success. This 'one-size-fits-all' approach ignores the notion that individuals may show distinct patterns of achievement and follow diverse paths to success. In this study, we examined a dataset composed of 53 variables extracted from the admissions application records of 1,088 students matriculating to NYU School of Medicine between the years 2006-2014. We defined training and test groups and applied K-means clustering to search for distinct groups of applicants. Building an optimized logistic regression model, we then tested the predictive value of this clustering for estimating the success of applicants in medical school, aggregating eight performance measures during the subsequent medical school training as a success factor. We found evidence for four distinct clusters of students-we termed 'signatures'-which differ most substantially according to the absolute level of the applicant's uGPA and its trajectory over the course of undergraduate education. The 'risers' signature showed a relatively higher uGPA and also steeper trajectory; the other signatures showed each remaining combination of these two main factors: 'improvers' relatively lower uGPA, steeper trajectory; 'solids' higher uGPA, flatter trajectory; 'statics' both lower uGPA and flatter trajectory. Examining the success index across signatures, we found that the risers and the statics have significantly higher and lower likelihood of quantifiable success in medical school, respectively. We also found that each signature has a unique set of features that correlate with its success in medical school. The big data approach presented here can more sensitively uncover success potential since it takes into account the inherent heterogeneity within the student population.

Project description:OBJECTIVES:The UK Clinical Aptitude Test (UKCAT) previously piloted an assessment of 'online confidence', where candidates were asked to indicate how confident they were with their answers. This study examines the relationship between these ratings, the odds of receiving an offer to study medicine and subsequent undergraduate academic performance. DESIGN:National cohort study. SETTING:UK undergraduate medical selection. PARTICIPANTS:56?785 UKCAT candidates who sat the test between 2013 and 2016 and provided valid responses to the online confidence pilot study. PRIMARY OUTCOME MEASURES:Two measures of 'online confidence' were derived: the well-established 'confidence bias', and; a novel 'confidence judgement' measure, developed using Item Response Theory in order to derive a more sophisticated metric of the ability to evaluate one's own performance on a task. Regression models investigated the relationships between these confidence measures, application success and academic performance. RESULTS:Online confidence was inversely related to cognitive performance. Relative underconfidence was associated with increased odds of receiving an offer to study medicine. For 'confidence bias' this effect was independent of potential confounders (OR 1.48, 1.15 to 1.91, p=0.002). While 'confidence judgement' was also a univariable predictor of application success (OR 1.22, 1.01 to 1.47, p=0.04), it was not an independent predictor. 'Confidence bias', but not 'confidence judgement', predicted the odds of passing the first year of university at the first attempt, independently of cognitive performance, with relative underconfidence positively related to academic success (OR 3.24, 1.08 to 9.72, p=0.04). No non-linear effects were observed, suggesting no 'sweet spot' exists in relation to online confidence and the outcomes studied. CONCLUSIONS:Applicants who either appear underconfident, or are better at judging their own performance on a task, are more likely to receive an offer to study medicine. However, online confidence estimates had limited ability to predict subsequent academic achievement. Moreover, there are practical challenges to evaluating online confidence in high-stakes selection.

Dataset Information

Semantic fluency including task switching predicts academic success in medical school.

Objectives

Material and methods

Results

Conclusion

Publications

Semantic fluency including task switching predicts academic success in medical school.

Similar Datasets

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