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

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

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
IGIP'2011 ⎯ FORMING INTERNATIONAL ENGINEERS FOR THE INFORMATION SOCIETY / - , 2011, 133-136

Skup
XL IGIP International Symposium on Engineering Education

Mjesto i datum
Santos, Brazil, 27.03.2011. - 30.03.2011

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
automatic identification and data capture; index of learning styles; industrial technology; student success

Sažetak
⎯Industrial Technology (IT) 345, a junior-level course at Purdue University, has been assessing students’ learning styles every semester since spring 2008 to understand how to best send information to the student. IT 345 is a hands- on, lecture, and laboratory course on the subject of automatic identification and data capture technology including barcodes, scanning technology, card technology, and biometric technology. The Index of Learning Styles (ILS) questionnaire by Felder and Silverman was administered to assess students’ learning styles and categorize students 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 students that perform well in the course and whether the teaching methods and the media used to deliver this information are sufficiently universal to satisfy all students.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA