BALANCING RESOURCES AND VALUE IN DISTANCE EDUCATION COURSE REVIEWS: A CASE STUDY AT A MID-SIZED PUBLIC UNIVERSITY

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Published: Oct 4, 2018

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William Swann
Youngstown State University
M. Kathleen Cripe
Youngstown State University

Abstract

This study examines the development and implementation of a distance education course review process at a mid-sized public university. Four primary goals were set for the process:  to provide substantive feedback, to cultivate engagement between DE faculty and staff, to provide support to course developers and reviewers, and to establish an effective balance between faculty resources and the value of feedback generated through the process. Feedback was collected through a survey of participating developers and reviewers (n=52). Responses broadly supported achievement of the four primary goals. Those who participated in multiple roles gave stronger ratings on all survey questions than those who participated through a single role. Based on qualitative and quantitative feedback, strengths, weaknesses, and possible adjustments to the process are discussed.

Article Details

Issue
Vol. 5 No. 4 (2018)
Section
Articles

Authors retain copyright to their work, licensing it under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License and grant the journal exclusive right  of first publication with the work simultaneously and it allows others to copy and redistribute the work for non-commercial purposes, with an acknowledgment of the work's authorship and initial publication in IOJET and provided that no changes were made on the article.

Author Biographies

William Swann, Youngstown State University

William Swann has worked in the fields of e-learning and distance education for two decades. He has developed courses and managed development projects in the corporate environment and provided instructional design assistance in the academic environment. He is the author of studies on applied pedagogy and courseware design.

M. Kathleen Cripe, Youngstown State University

Dr. Kathleen Cripe is Associate Professor of Teacher Education in the Beeghly College of Education at Youngstown State University, where she coordinates the Adolescent Young Adult Education program. She is the author of multiple studies on science and math education and received the 2017 Distinguished Professor Award for Excellence in Teaching.

References

Baddeley, A. D. (1986). Working memory. Oxford, UK: Oxford University Press.

Bandura, A. (1969). Social-learning theory of identificatory processes. In David A. Goslin (Ed.), Handbook of socialization theory and research (pp. 213-262). Chicago, IL: Rand McNally.

Berge, Z. L. (2002). Active, interactive, and reflective learning. Quarterly Review of Distance Education. 3, 181-190.

Bloom, B. S., Krathwohl, D. R., & Masia, B. B. (1956). Taxonomy of Educational Objectives: The Classification of Educational Goals (Vol. 1). N.p.: David McKay.

Blumberg, P. (2009). Maximizing learning through course alignment and experience with different types of knowledge. Innovative Higher Education. 34(2), 93-103. DOI: 10.1007/s10755-009-9095-2

Bonwell, C. C., & Eison, J. A. (1991). Active Learning: Crating Excitement in the Classroom. New York, NY: Wiley.

Bruner, J. (1966). Toward a Theory of Instruction. Cambridge, MA: Harvard University Press.

Dick, W., Carey, L., & Carey, J. O. (2001). The Systematic Design of Instruction. N.p.: Pearson Higher Ed.

Dresner, M., De Rivera, C., Fuccillo, K. K., & Heejun, C. (2014). Improving higher-order thinking and knowledge retention in environmental science teaching. Bioscience. 64(1), 40-48. DOI: 10.1093/biosci/bit005

Guidelines for the evaluation of distance education (on-line learning). (2009). Retrieved from Higher Learning Commission http://download.hlcommission.org/C-RAC_Distance_Ed_Guidelines_7_31_2009.pdf

Huang, H. (2002). Toward constructivism for adult learners in online learning environments. British Journal of Educational Technology. 33(1), 27-37.

Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in Learning Technology. 23(1), 1-13. DOI: https://doi.org/10.3402/rlt.v23.26507

Kuo, Y., Walker, A., Belland, B., & Schroder, K. (2013). A predictive study of student satisfaction in online education programs. The International Review of Research in Open and Distributed Learning. 14(1), 16-39. DOI: http://dx.doi.org/10.19173/irrodl.v14i1.1338

Mayer, R. E. (2008). Applying the science of learning: Evidence-based principles for the design of multimedia instruction. American Psychologist. 63(8), 760-769.

Mayer, R. E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? Journal of Educational Psychology. 93(2), 390-397.

Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds? Journal of Educational Psychology. 95(4), 806-812.

Paas, F., Tuovinen, J., Tabbers, H., & van Gerven, P. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist. 38(1), 63-71.

Reeves, T. (2006). How do you know they are learning?: The importance of alignment in higher education. International Journal of Learning Technology. 2(4), 294-309. DOI: 10.1504/IJLT.2006.011336

Smith, P. L., & Ragan, T. J. (2005). Instructional Design. (3rd ed.). New York, NY: Wiley & Sons.

Spanjers, I. E., Wouters, P., van Gog, T., & van Merriënboer, J. J. G. (2011). An expertise reversal effect of segmentation in learning from animated worked-out examples. Computers in Human Behavior. 27(1), 46-52. DOI: 10.1016/j.chb.2010.05.011

Spanjers, I. E., Gog, T., & Merriënboer, J. G. (2012). Segmentation of Worked Examples: Effects on Cognitive Load and Learning. Applied Cognitive Psychology. 26(3), 352-358. DOI: 10.1002/acp.1832

Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction. 2(1), 59–89.