Perceived media richness and performance outcomes: Testing the effects of Channel Expansion Theory on distance learning

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Education

Published on February 13, 2014

Author: SheenaMWilliams

Source: slideshare.net

Description

Presentation includes:

Identification of issues in distance learning
Introduction to Channel Expansion Theory (CET)
Application of CET to distance learning
Proposed hypothesis

Presented fall 2013 to my graduate course in Communication Theory

Testing the effects of Channel Expansion Theory on distance learning Sheena Williams

Overview  Identify issue  Introduce Channel Expansion Theory  Apply CET to issue  Present hypothesis

Distance Learning National Center for Education Statistics defines DL as:  “a formal educational process in which the instructor and the student are not in the same location….instruction might be synchronous or asynchronous” (Parsad & Lewis, 2008, para. 1).  Thus, technology has removed the restrictions of time and space

Students  Who benefits from distance learning courses?      Individuals with disabilities Parents Full-time employees Students in areas where transportation as an issue Military

Enrollment  Robust increase in enrollment  6.9 million students in 2012 (Allen & Seaman, 2013)  77% of campuses offer online courses (AndersonAvouris, Boyles, & Rainie, 2012)  70% of universities have DL as part of long-term strategy

FtF vs. CMC Can online education be as beneficial for students as classroom learning?

Course Design  Fundamental change from traditional learning  Heavily rely on communication (Hiltz, 1990; Schrum, 1995; Schrum & Lamb, 1996)    One-on-one with faculty Group work with peers Discussion Boards

DL Issue  High Attrition Rates  Poor performance (Owens, Hardcastel, & Richardson, 2009; Schrum, 1997; Sitzmann, Bell, & Bauer, 2010; Wiesenberg & Hutton, 1996)

Performance Outcomes The observed scores relating to the level of achievement that can be compared against a scale to determine a level of proficiency and/or comprehension

Student Performance  Student perceptions of technology and its use in communicating with faculty and peers  Students struggle with….  technical issues  understanding technology  communication with faculty and other students  course content and context (Owens, Hardcastel, & Richardson, 2009; Schrum, 1997; Sitzmann, Bell, & Bauer, 2010; Wiesenberg & Hutton, 1996)

Student Performance  Participation lower than expected (Wiesenburg & Hutton, 1996).  Students frequently felt isolated (Owens, Hardcastel, & Richardson, 2009)  Technology alters communication (Lea & Spears, 1991)

What to consider…. Technology alters a student’s ability to effectively communicate Participation and understanding of course material Affect performance outcome

Channel Expansion Theory Carlson & Zmud (1994)  Media richness depends on a user’s perception of the medium

CET Roots  Media Richness Theory (Daft & Lengel, 1986) Uncertainty Equivocality Media Richness

Media Richness  Important in creating a shared understanding in communication  Ability to encode and decode  Avoid misunderstandings/unclear messages

CET & Media Richness  Not dependant on channel’s characteristics but the user’s perception of the channel in reducing equivocality and uncertainty

Perceived Richness an individual’s self-reported appraisal of the ability of a medium to overcome uncertainty and equivocality

Effective Communication  “communication effectiveness and richness perceptions are strongly bounded by a channel user’s communication experiences” (Carlson & Zmud, 1999)

Perceptions of richness  Based on prior knowledge-building experience with:  Medium  Partner  Topic  Context

CET and Media Richness Channel Topic Context Richer Leaner Partner

CET and Media Richness  Media richness is:  Fluid  Subjective  Linear and developing across time.

Channel Selection  As you gain experience you are able to select which channel will fit your needs Experience Perceived Richness Effective Communication

CET Applied  Various media  Diverse situations  CET applied to educational context (Fernandez, Simo, Sallan, & Enache, 2013)  Different individuals showed different overall levels of perceived media richness  Experience with the channel and with the partner significantly relate to the perception of the online forum’s richness

Hypothesis The richer a student perceives a channel to be, the greater their performance outcome will be in a distance learning course using that channel.

References Allen, I. E. & Seaman, J. (2013). Changing course: Ten years of tracking online education in the United States. New York, NY: The Sloan Consortium. Retrieved from http://sloanconsortium.org/ Anderson, J.Q., Boyles, J.L., & Rainie, L. (2012). The future impact of the Internet on higher education: Experts expect more-efficient collaborative environments and new grading schemes; they worry about massive online courses, the shift away from on-campus life. Washington, D.C.: Pew Research Center, Pew Internet & American Life Project. Retrieved from http://www.pewinternet.org Burgoon, J. K., Bonito, J. A., Ramirez, A., Jr., Dunbar, N. E., Kam, K., & Fischer, J. (2002). Testing the interactivity principle: Effects of mediation, propinquity, and verbal and nonverbal modalities in interpersonal interaction. Journal of Communication, 52, 657-677. doi:10.1111/j.1460-2466.2002.tb02567.x Carlson, J. R., & Zmud, R. W. (1999). Channel expansion theory and the experiential nature of media richness perceptions. Academy of Management Journal, 42, 153-170.doi:10.2307/257090 Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32, 554–571. doi:10.1287/mnsc.32.5.554 Fernandez, V., Simo, P., Sallan, J. M., & Enache, M. (2013). Evolution of online discussion forum richness according to channel expansion theory: A longitudinal panel data analysis. Computers & Education, 62, 32-40. doi:10.1016/j.compedu.2012.10.020 Parsad, B. & Lewis, L. (2008). Distance education at degree-granting postsecondary institutions: 2006-07. (NCES 2009044). Washington D.C.: U.S. Department of Education, National Center for Education Statistics. Retrieved from http://nces.ed.gov Ngwenyama, Ojelanki K., & Lee, Allen S. (1997). Communication richness in electronic mail: Critical social theory and the contextuality of meaning. MIS Quarterly, 21, 145-167. doi:10.2307/249417 Owens, J., Hardcastel, L., & Richardson, B. (2009). Learning from a distance: The experience of remote students. Journal of Distance Education, 23, 57–74. Retrieved from http://www.jofde.ca/ Rozell, E. J., & Gardner, W. L. (2000). Cognitive, motivation, and affective processes associated with computer-related performance: A path analysis. Computers in Human Behavior, 16, 199-222. doi:10.1016/S0747-5632(99)00054-0 Schrum, L. (1998). On-line education: A study of emerging pedagogy. New Directions for Adult & Continuing Education, 78, 53-61. doi:10.1002/ace.7806 Schrum, L. (1995). Educators and the Internet: A case study of professional development. Computers & Education, 24, 221-228. doi: 10.1016/0360-1315(95)00012-B Schrum, L., & Lamb, T. A. (1996). Groupware for collaborative learning: A research perspective on processes, opportunities, and obstacles. Journal of Universal Computer Science, 2, 717–731. Retrieved from http://www.jucs.org/ Sitzmann, T., Ely, K., Bell, B. S., & Bauer, K. N. (2010). The effects of technical difficulties on learning and attrition during online training. Journal of Experimental Psychology: Applied, 16, 281-292. doi:10.1037/a0019968

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