Determining graduation rates in engineering for community college transfer students using data mining

• Autores: Marcia Laugerman, Diane Rover, Mack Shelley, Steve Mickelson
• Localización: The International journal of engineering education, ISSN-e 0949-149X, Vol. 31, no. 6 (Parte A), 2015, págs. 1448-1457
• Idioma: inglés
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• Resumen

  • This study presents a unique synthesized set of data for community college students entering the university with the intention ofearning a degree in engineering. Several cohorts of longitudinal data were combined with transcript-level data from both thecommunity college and the university to measure graduation rates in engineering. The emphasis of the study is to determineacademic variables that had significant correlations with graduation in engineering, and levels of these academic variables. Thearticle also examines the utility of data mining methods for understanding the academic variables related to achievement in science,technology, engineering, and mathematics. The practical purpose of each model is to develop a useful strategy for policy, based onsuccess variables, that relates to the preparation and achievement of this important group of students as they move through thecommunity college pathway.