LEARNING STYLE AND STUDENT SUCCESS IN AN AUTOMATIC IDENTIFICATION AND DATA CAPTURE COURSE

Benny Senjaya, Gregory T. Hales, Jurica Seva, Stephen Elliott, Mathias Sutton

Abstract


Industrial Technology (IT) 345, a junior-level courseat Purdue University, has been assessing students’ learning stylesevery semester since spring 2008 to understand how to best sendinformation to the student. IT 345 is a hands-on, lecture, andlaboratory course on the subject of automatic identification anddata capture technology including barcodes, scanning technology,card technology, and biometric technology. The Index of LearningStyles (ILS) questionnaire by Felder and Silverman wasadministered to assess students’ learning styles and categorizestudents according to their learning style as active/reflective,sensing/intuitive, visual/auditory, or sequential/global learners.The goals of this paper are to understand the categories of studentsthat perform well in the course and whether the teaching methodsand the media used to deliver this information are sufficientlyuniversal to satisfy all students.Index Terms ⎯  automatic identification and data capture;index of learning styles; industrial technology; student success.

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