
Learning Styles of Mexican Food Science and Engineering Students
Author(s) -
Palou Enrique
Publication year - 2006
Publication title -
journal of food science education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.271
H-Index - 13
ISSN - 1541-4329
DOI - 10.1111/j.1541-4329.2006.00006.x
Subject(s) - learning styles , mathematics education , curriculum , style (visual arts) , psychology , disadvantaged , active learning (machine learning) , variety (cybernetics) , presentation (obstetrics) , strengths and weaknesses , test (biology) , learning sciences , pedagogy , experiential learning , computer science , social psychology , artificial intelligence , geography , ecology , medicine , archaeology , biology , political science , law , radiology
People have different learning styles that are reflected in different academic strengths, weaknesses, skills, and interests. Given the almost unlimited variety of job descriptions within food science and engineering, it is safe to say that students with every possible learning style have the potential to succeed as food scientists and engineers. They may not be equally likely to succeed in school, however, since they respond differently to different instructional approaches and the predominant mode of instruction favors some learning styles over others. The goals of the study were to test the degree to which student performance and attitudes were consistent with expectations based on learning style theory and prior studies. The Index of Learning Styles © (ILS) was administered to several groups of undergraduate and graduate food science and engineering students taking different courses at the Universidad de las Américas, Puebla . Those courses were taught in a manner that emphasized active and cooperative learning as well as inductive presentation of course material. Visual, sensing, and active learning styles were displayed by the majority of students. Significant differences ( P < 0.05) were observed between males and females for the Sensing/Intuiting and Sequential/ Global dimensions of the Felder‐Silverman model. Type differences in various academic performance measures and attitudes were noted as students progressed through the curriculum. Observations were generally consistent with predictions of type and learning style theories, and the instructional approach improved the performance of ILS types (actives and sensors) found in previous studies to be disadvantaged in the science and engineering curricula.