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Educational Alternatives, Volume 17, 2019

EXPLORING ATTRIBUTES OF STUDENT SATISFACTION PERCEPTION OF E-LEARNING MEDICAL TERMINOLOGY COURSES
Miervaldis Karulis, Ināra Ābelīte
Pages: 246-254
Published: 13 Oct 2019
Views: 187
Downloads: 40
Abstract: Educators worldwide are searching for integrating e-learning systems into all study programmes, while fully respecting student’s interests and satisfaction. One of the solutions is blended learning, which includes both face-to-face and online learning, extending opportunities of exploiting various methods of learning/teaching, scheduling, modes of delivering and guidance. This study was dedicated to exploration of student perception of satisfaction of e-learning. The aim was to evaluate student satisfaction attributes (objective and subjective) in the blended learning setting of the study courses: Medical Terminology in Latin and English and to reveal homogenous groups of students of different study programmes Dentistry, Medicine, Nursing, Occupational Therapy, Physiotherapy and Public Health with respect to their satisfaction of e-learning at Rīga Stradiņš University. A cross-sectional study was carried out involving 418 students in December, 2018 and January, 2019. The survey comprised 6 domains: information quality, system quality, service quality, use, user satisfaction and net benefits. Satisfaction attributes (10) were evaluated according to students’ objective (fulfillment) and subjective (perception) aspects. For each attribute an index was created, which was used to reveal homogeneity of student groups. A two-step cluster analysis and non-parametric tests were performed using IBM SPSS Statistics 20. Generally, the results indicated a high rate of satisfaction of e-learning (46% - 67%), while the cluster analysis segregated 3 groups of students of different study programmes with respect to their responses. The obtained results can be taken into account when creating personalized e-learning courses for students of particular study programmes.
Keywords: e-learning, b-learning, satisfaction, perception, cluster analysis, medical terminology
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