How Do Students Want to Learn in Online Distance Education? Profiling Student Preferences
IRRODL Volume 16, Number 1, ISSN 1492-3831 Publisher: Athabasca University Press
How do (potential) students differ in their preferences for the organization of online and distance courses and programs, can these differences be grouped into preference profiles, and are there any associations between these profiles and variables, such as achievement and dropout, that are relevant for the promotion and design of online and distance teaching? In this study, three groups (enrolled students, N = 1939; prospective students, N = 296, people in the target group of the course or program, N = 255) completed a survey consisting of 28 items with which to identify their preferences. Various significant differences in preferences between the groups were found in the item scores. Exploratory factor analysis resulted in five meaningful factors that were used to create 32 preference profiles that are identified by the dichotomized scores on the factors. In this way, the profiles conserve their dimensional relationship instead of presenting profiles as distinct types. The factors in which student preferences differ are: collaboration (group work versus self-study), pacing (fixed time schedule versus flexibility in time and tempo), the degree to which the study has a practical orientation, the degree of proactive (versus reactive) teaching and a preference for indepth learning versus superficial learning. Significant associations have been found between preference profiles and the discipline in which the student group studies, the type of program (e.g., bachelor, master), and the number of study points obtained in the last year per discipline. The results indicate that the enrolled students are more aligned to the characteristics of the teaching-learning process than the other two groups.
Koper, R. (2015). How Do Students Want to Learn in Online Distance Education? Profiling Student Preferences. The International Review of Research in Open and Distributed Learning, 16(1), 307-329. Athabasca University Press.