Article
Computer Science, Artificial Intelligence
Yadi Wang, Jun Wang
Summary: Feature selection plays a crucial role in machine learning and pattern recognition by selecting informative features from the original dataset. Supervised feature selection outperforms unsupervised feature selection in the presence of label information. However, it is challenging for supervised feature selection methods to select relevant features when there is a small number of labeled data and a large number of unlabeled data.
Article
Education, Scientific Disciplines
Kathryn Robinett, Raushanah Kareem, Kristin Reavis, Sandra Quezada
Summary: This study demonstrates that implementing multiple interventions to mitigate bias in the admissions process can increase the number of medical students who identify as underrepresented minorities. Specific interventions such as interviewer training, recruitment strategies, holistic screening, increasing diversity on the admissions committee, and blinding interviewers to MCAT scores and GPA have been successful in increasing underrepresented minority representation among medical school matriculants at the University of Maryland School of Medicine.
Article
Education, Scientific Disciplines
Hak Yung Ng, Jane Anderson, Lorna Marson, David Hope
Summary: Non-cognitive traits should be considered in the selection of medical students. The study examined whether measuring undesirable non-cognitive behavior ('Red Flags') added value to the admissions process. Red Flags included rudeness, ignoring contributions, disrespect, or poor communication.
Article
Education, Scientific Disciplines
Philip Chan, Anna Anthony, Kathleen Quinlan, Sharon Smith, Chris Holland
Summary: The outcomes of widening participation in admissions to UK medical schools have remained unchanged from 2007 to 2018, partly due to inequity in the selection process. This study introduces a novel method of contextualizing applicants to model the effects of changing selection on widening participation. The results indicate that by ranking applicants based on their GCSE grades in comparison to their schools' average performance, a higher level of widening participation can be achieved, thus promoting equity.
Review
Education, Scientific Disciplines
Leila E. Harrison, Laura Fletcher, Dana Dunleavy, Tanisha Price-Johnson, Roopal Vashi Kundu, Glen T. Fogerty, Linda Berardi-Demo
Summary: This study examined how applicants interpret the self-reported disadvantaged (SRD) question in the American Medical College Application Service (AMCAS) application. The results showed significant differences between SRD and non-SRD applicants in terms of background, financial status, educational environment, and personal experiences. The interviews also revealed applicants' concerns about the lack of transparency in how the SRD question is used in admissions.
Article
Multidisciplinary Sciences
Chelsea M. Gustafson, Crystal R. Johnson, Gary L. Beck Dallaghan, O'Rese J. Knight, Kimberly Malloy, Kimberley Nichols, Lisa Rahangdale
Summary: This study evaluated the relationship between Computer-based Assessment for Sampling Personal Characteristics (CASPer) scores and admissions interview evaluations. The results showed that there were differences in CASPer scores among applicants of different races and ethnicities, indicating that CASPer may not contribute to reducing bias in medical school admissions.
Review
Education, Scientific Disciplines
Sunny Nakae, Erik J. Porfeli, Dwight Davis, Christina J. Grabowski, Leila E. Harrison, Leila Amiri, Will Ross
Summary: This article introduces a theory of holistic enrollment management, combining holistic review with enrollment management principles in medical school admissions. It discusses the complex marketplace and competing forces in medical school admissions and suggests that a clear, compelling, and focused mission can help attract applicants who are better prepared to enact the mission. Institutions that strategically mobilize resources in this dynamic marketplace can engage, admit, and matriculate the most suiting applicants over time.
Article
Green & Sustainable Science & Technology
Oskar Seuntjens, Matthias Buyle, Bert Belmans, Amaryllis Audenaert
Summary: This study explores the efficient utilization of school buildings in the future by involving the local community in their usage. The findings suggest that extensive building usage can bring positive social, environmental, educational, and economic benefits. Educational experts emphasize the adoption of more innovative and flexible teaching methods, while technical directors express concerns about safety issues. The analysis concludes that a school building with a high degree of short-term flexibility is the preferred option to reconcile societal and educational needs.
Editorial Material
Education, Scientific Disciplines
Charles G. Prober, Sanjay V. Desai
Summary: To address the physician shortage, the selection process for medical students needs to be transformed. Academic medicine should focus on nurturing a diverse pool of applicants, aligning admission criteria with expected competencies, and leveraging innovations in data science and artificial intelligence.
Review
Audiology & Speech-Language Pathology
Aileen A. Wong, Nicole L. Marrone, Leah Fabiano-Smith, Pelagie M. Beeson, Marla A. Franco, Vignesh Subbian, Guadalupe Lozano
Summary: This tutorial shares the experience of a university's speech, language, and hearing sciences department in revising the graduate admissions review process and discussing equity, providing useful guiding questions for other organizations. The adaptive case study approach was used to support students at Hispanic-serving institutions, with structured collaborative reflection and engagement of stakeholders at multiple levels. Key motivations, barriers, facilitators, and phases in moving towards holistic evaluation for graduate admissions, as well as areas for continued improvement related to diversity, equity, and inclusion, are outlined in the tutorial.
AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY
(2021)
Article
Health Care Sciences & Services
Parisa Moll-Khosrawi, Wolfgang Hampe, Leonie Schulte-Uentrop, Christian Zoellner, Stefan Zimmermann, Thorben Huelmann
Summary: Non-technical skills (NTS) play a crucial role in ensuring patient safety in medical care. Focusing on assessing applicants' NTS during medical school admission may be a promising approach to ensure that future physicians possess high-level NTS. This study investigated the predictive validity of various selection tests and admission criteria for NTS performance in clinical emergency medicine training among medical students.
Article
Economics
Somouaoga Bonkoungou, Alexander Nesterov
Summary: The reformed rules are less prone to gaming and each reform expands the set of schools wherein each student can never get admission by manipulation.
THEORETICAL ECONOMICS
(2021)
Article
Education & Educational Research
Michael N. Bastedo, Mark Umbricht, Emma Bausch, Bo-Kyung Byun, Yiping Bai
Summary: This study, based on data from 2.3 million students in a Midwestern state, finds a strong association between contextualized high school grades and standardized test scores with college success. Contextualized grades have a stronger correlation than contextualized test scores, making them particularly helpful for colleges that have not adopted holistic admissions practices.
Article
Education & Educational Research
A. L. Atkinson, L. J. B. Hill, K. J. Pettinger, J. Wright, A. R. Hart, J. Dickerson, M. Mon-Williams
Summary: This study indicates that children who reach a good level of development through holistic school readiness evaluations perform better in later academic assessments, particularly for those with special educational needs. Such evaluations can help identify 'at risk' children.
LEARNING AND INSTRUCTION
(2022)
Article
Computer Science, Artificial Intelligence
AliAkbar ForouzeshNejad
Summary: This study provides a hybrid data-driven framework for selecting investment projects in the telecommunication industry. By reviewing the theoretical literature and surveys of experts, project evaluation criteria through sustainability paradigm as well as strategic issues are identified. The performance of each project is determined separately for each year using data envelopment analysis (DEA), and then evaluated with machine learning algorithms such as random forest and support vector regressors.