Though the sea of research on study of cognitive styles and/or learning styles was said to be common knowledge (Riener & Willingham, 2010), evidence-based research to support the literature on the existence of dissimilar learning styles in the classroom was sparse. The researchers conducted this study of six undergraduate classes, to identify the relationship of dissimilar cognitive style between instructor and student and learning strategies that students used to bridge the cognitive gap with their instructors. To measure cognitive styles, the Kirton Adaption-innovation Inventory (KAI) was used. With this problem-solving preference instrument, students were classified as more adaptive or more innovative. In order to determine dissimilarity of cognitive styles between student and instructor, the instructor's KAI score was subtracted from the student's KAI score. The Motivated Strategies for Learning Questionnaire (MSLQ) was used to measure student learning strategies.
The researcher found that for a majority of the classes, rehearsal was the primary study strategy which was used in these classes. Also, effort regulation was prominently used by students to increase their understanding of the course which was taught by the professor of a dissimilar problem-solving style. As gap increased for the more innovative and more adaptive students in Class Three, there was a positive association with the increased use of total resource management learning strategies. Findings of this study are important in further verifying the relationship between cognitive-style gap and study strategies. They are relevant for instructors, whether their cognitive style is more adaptive or more innovative. The findings of this study should also be meaningful to students, who may have perceived themselves to be limited by categorical labeling of learning styles; who feel that they may not be able to learn outside of the instructional method that suit the category in which they have been placed.
Recent research has continued to provide evidence supporting two seminal conclusions regarding cognitive styles. That is, cognitive style may be considered a factor in determining student academic success (Cassidy, 2004; Romanelli, Bird & Ryan, 2009), and cognitive style may be one avenue through which students can understand their preference to processing information, or how their instructor can better help them learn (Evans, Harkins & Young, 2008). Regardless of the depth of literature and numerous studies which have been carried out, making the cognitive styles field a popular one in general, a few studies (Cooper, Lingg, Puricelli & Yard, 1995; Friedel, 2006; Friedel & Rudd, 2009) exist concerning dissimilar cognitive styles between professor and student. Furthermore, while existing empiricism (Hendry, Heinrich, Lyon, Barratt, Simpson, Hyde, Gonsalkorale, Hyde & Mgaieth, 2005) substantiates the relationship between cognitive style and learning strategy, sparse research existed which examines relationships between dissimilar cognitive styles and student preferences of learning strategies, which may provide notable implications for students and instructors.
It is not a rare situation in higher education that students are enrolled in courses that do not support their cognitive styles, as many professors were unaware of the implications of students' cognitive style in the classroom (Evans & Waring, 2009). This may impact learning and eventually performance. Applying the F elder- Silverman Learning Style Model (FSLSM; Felder & Silverman, 1988), Kinshuk, Liu and Graf (2009) investigated whether students with a strong preference for a particular learning style had more learning difficulties if their styles were not supported in the learning environment. Only two years ago, their findings indicated that learners with strong preferences towards a particular orientation had significantly lower scores on the final exam than learners with no strong preference for any learning style dimension. …