Literature DB >> 30323397

The Application of Classification Trees to Pharmacy School Admissions.

Samuel C Karpen1, Steve C Ellis2.   

Abstract

In recent years, the American Association of Colleges of Pharmacy (AACP) has encouraged the application of big data analytic techniques to pharmaceutical education. Indeed, the 2013-2014 Academic Affairs Committee Report included a "Learning Analytics in Pharmacy Education" section that reviewed the potential benefits of adopting big data techniques.1 Likewise, the 2014-2015 Argus Commission Report discussed uses for big data analytics in the classroom, practice, and admissions.2 While both of these reports were thorough, neither discussed specific analytic techniques. Consequently, this commentary will introduce classification trees, with a particular emphasis on their use in admission. With electronic applications, pharmacy schools and colleges now have access to detailed applicant records containing thousands of observations. With declining applications nationwide, admissions analytics may be more important than ever.3.

Keywords:  admissions; decision tree; predictive analytics

Mesh:

Year:  2018        PMID: 30323397      PMCID: PMC6181165          DOI: 10.5688/ajpe6980

Source DB:  PubMed          Journal:  Am J Pharm Educ        ISSN: 0002-9459            Impact factor:   2.047


  5 in total

1.  Pharmacy Practice, Education, and Research in the Era of Big Data: 2014-15 Argus Commission Report.

Authors:  Jeffrey N Baldwin; J Lyle Bootman; Rodney A Carter; Brian L Crabtree; Peggy Piascik; Jeffrey O Ekoma; Lucinda L Maine
Journal:  Am J Pharm Educ       Date:  2015-12-25       Impact factor: 2.047

2.  Report of the 2013-2014 Academic Affairs Committee.

Authors:  Jeff Cain; Jeannine M Conway; Margarita V DiVall; Brian L Erstad; Paul R Lockman; John C Ressler; Amy H Schwartz; Scott Stolte; Ruth E Nemire
Journal:  Am J Pharm Educ       Date:  2014-12-15       Impact factor: 2.047

3.  Computer-Assisted Decision Support for Student Admissions Based on Their Predicted Academic Performance.

Authors:  Eugene Muratov; Margaret Lewis; Denis Fourches; Alexander Tropsha; Wendy C Cox
Journal:  Am J Pharm Educ       Date:  2017-04       Impact factor: 2.047

4.  Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.

Authors:  Timothy Hayes; Satoshi Usami; Ross Jacobucci; John J McArdle
Journal:  Psychol Aging       Date:  2015-09-21

5.  An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

Authors:  Carolin Strobl; James Malley; Gerhard Tutz
Journal:  Psychol Methods       Date:  2009-12
  5 in total

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