Predictors of student satisfaction in distance-delivered graduate nursing courses: what matters most?
This article describes a study designed to investigate graduate nursing students' satisfaction with a course taught via interactive video teleconferencing (IVT) and the World Wide Web/Internet (WWW/INT). A correlational research design examined the relationships among 5 learner attributes and 3 instructional variables and student satisfaction. Regression analyses identified learner attributes and instructional variables predictive of student satisfaction. Forty-three graduate nurse students were surveyed using a 59-item Student Satisfaction Survey (SSS). Learner attribute predictors included: (1) previous technology courses, (2) technology competence, (3) between-class technology usage, (4) age, and (5) remote-site group size. Instructional predictors were clustered into 3 dimensions: instructor/instruction, technology, and course management. Student satisfaction was a composite of overall satisfaction with the course and comparison with conventional classroom courses. Instructor/instruction explained 21 percent of the variance in course satisfaction scores. Overall instructor rating strongly correlated with satisfaction. The most potent finding was that good pedagogy is important to students' perceived satisfaction with distance education. Students acclimate to the instructional reality-traditional, campus-based face-to-face instruction, or technology-mediated distance education-and once accustomed, it is the quality and effectiveness of instructor and instruction, not the technology, that is associated with satisfaction. The findings of this study provide essential information to faculty responsible for the design and delivery of effective instruction and to students pursuing flexible and convenient options for advanced education.
Debourgh
Gregory A
GA
School of Nursing, University of San Francisco, 2130 Fulton Street, San Francisco, CA 94117-1080, USA. debourghg@usfca.edu
D000328:Adult; D001291:Attitude of Health Personnel; D001292:Attitude to Computers; D002140:California; D003197:Computer Literacy; D003194:Computer-Assisted Instruction / Q000592:standards*; D020375:Education, Distance / Q000592:standards*; D004511:Education, Nursing, Graduate / Q000592:standards*; D006801:Humans; D020407:Internet / Q000592:standards*; D017145:Models, Educational; D020380:Needs Assessment; D015402:Nursing Education Research; D011237:Predictive Value of Tests; D015397:Program Evaluation; D012044:Regression Analysis; D013338:Students, Nursing / Q000523:psychology*; D013598:Systems Theory; D013685:Telecommunications / Q000592:standards*