American universities have adopted course management systems (CMSs) at levels that are unprecedented in learning technology. Researchers have investigated CMS use for a few reasons. First, they are interested in learning what universities are getting from the large investment into these systems. Second, there are so many features in a CMS that researchers are curious which features are used most. And third, identifying the most-used features can lead to further research into how these features can be used more effectively. Current research has provided helpful information, but it typically lacks statistical analysis, performance-based data, and longitudinal data. The study described here built on previous research by addressing these issues. CMS use at one university was studied from 2005 to 2007. Results showed that few significant changes in CMS use occurred in this time, with CMSs primarily used to transmit information to students and occasionally used for student interaction. Recommendations for further research are included.
Get full access to this article
View all access options for this article.
References
1.
AllenI. E.SeamanJ. (2004). Entering the mainstream: The quality and extent of online education in the United States, 2003 and 2004 (Research Report No. 0-9677741-8-7). Needham, MA: Sloan Center for Online Education.
2.
AllenI. E.SeamanJ. (2005). Growing by degrees: Online education in the United States, 2005 (Research Report No. 978-0-9766714-2-8). Needham, MA: Sloan-Center for Online Education.
3.
AllenI. E.SeamanJ. (2010). Learning on demand online education in the United States, 2009. [Needham, MA]; [Wellesley, MA]: Sloan Consortium; Babson Survey Research Group.
4.
AllenI. E.SeamanJ.SloanC. (2007). Online nation: Five years of growth in online learning (No. 181156262). Needham, MA.: Sloan-Center for Online Education.
5.
AndersonJ. R. (1990). Cognitive psychology and its implications (3rd ed.). New York: W. H. Freeman.
6.
AndersonJ. R. (2005). Cognitive psychology and its implications. New York: Worth Publishers.
7.
AndrewsJ. J.BondG. D.SpellerL. F. (2009). When course management systems fail: Student and instructor ‘on-the-fly’ adaptation behaviors. Cognitive Technology, 14(1), 10.
8.
AnsorgeC. J.BendusO. (2003). The pedagogical impact of course management systems on faculty, students and institutions. In BruningR. H.HornC. A.PytlikZilligL. M. (Eds.), Web-based learning: What do we know? Where do we go? (pp. xxii, 275 p.). Greenwich, CT: Information Age Publishers.
9.
BatesT. (1995). Technology, open learning, and distance education. London/New York: Routledge.
10.
BeerC.JonesD.ClarkK. (2009, December 6–9). The indicators project identifying effective learning: Adoption, activity, grades and external factors. Paper presented at the ASCILITE, Auckland City, New Zealand.
11.
BlackE. W.BeckD.DawsonK.JinksS.DiPietroM. (2007). The other side of the LMS: Considering implementation and use in the adoption of an LMS in online and blended learning environments. TechTrends: Linking Research and Practice to Improve Learning, 51(2), 35–39, 53.
12.
BonkC. J. (2009). The world is open: How web technology is revolutionizing education. San Francisco, CA: Jossey-Bass.
13.
BorgW. R.GallM. D. (1989). Educational research: An introduction (5th ed.). New York: Longman Publishing Group.
14.
BrowneT.JenkinsM.WalkerR. (2006). A longitudinal perspective regarding the use of VLEs by higher education institutions in the United Kingdom. Interactive Learning Environments, 14(2), 177–192.
15.
CastroF.VellidoA.NebotÀ.MugicaF. (2007). Applying data mining techniques to e-Learning problems. In JainL. C.TedmanR. A.TedmanD. K. J. (Eds.), Evolution of teaching and learning paradigms in intelligent environment (pp. 183–221). Berlin/New York: Springer.
16.
ClarkR. E. (2001). Learning from media: Arguments, analysis, and evidence. Greenwich, CT: Information Age Publishers.
17.
ClarkR. E.FeldonD. F.Van MerrienboerJ. J. G.YatesK.EarlyS. (2008). Cognitive task analysis. In SpectorJ. M. (Ed.), Handbook of research on educational communications and technology. Hillsdale, NJ: Lawrence Erlbaum Associates.
18.
ClayJ.WheelerS.AttwellG. (2009). The VLE is dead. Paper presented at the ALT-C 2009, the 16th International Conference of the Association for Learning Technology. from http://altc2009.alt.ac.uk/talks/6776
19.
CoatesH.JamesR.BaldwinG. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary Education and Management, 11(1), 19–36.
20.
CohenJ. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
21.
CraigD. V. (2002). View from an electronic learning environment: Perceptions and patterns among students in an online graduate education course. Journal of Educational Technology Systems, 30(2), 197–219.
22.
DickW.CareyL.CareyJ. O. (2005). The systematic design of instruction (6th ed.). Boston, MA: Pearson/Allyn and Bacon.
23.
DriscollM. P. (2000). Psychology of learning for instruction (2nd ed.). Boston, MA: Allyn and Bacon.
24.
DriscollM. P. (2005). Psychology of learning for instruction (3rd ed.). Boston, MA: Pearson Allyn and Bacon.
25.
DuttonW. H.CheongP. H.ParkN. (2004). An ecology of constraints on e-learning in higher education: The case of a virtual learning environment. Prometheus, 22(2), 131–149.
26.
FalvoD. A.JohnsonB. F. (2005, March). Use and implementation of learning management systems in the US. Paper presented at the Society for Information Technology & Teacher Education, 16th Annual International Conference, Phoenix, AZ.
27.
GagnéR. M.BriggsL. J.WagerW. W. (1992). Principles of instructional design (4th ed.). Fort Worth, TX: Harcourt Brace Jovanovich College Publishers.
28.
GreenJ. L.CamilliG.ElmoreP. B. (2006). Handbook of complementary methods in education research. Mahwah, NJ/Washington, DC: Lawrence Erlbaum Associates; Published for the American Educational Research Association.
GustafsonK. L.BranchR. M. (1997). Survey of instructional development models. Syracuse, NY: ERIC Clearinghouse on Information & Technology, Syracuse University.
31.
HannafinM. J.OrrillC.KimH.KimM. (2005). Educational technology research: Promise, problems, and prospects. Journal of Computing in Higher Education, 16(2), 3–22.
32.
HannafinM. J.RieberL. P. (1989). Psychological foundations of instructional design for emerging computer based instructional technologies, Part 2. Educational Technology Research & Development, 37(2), 102–114.
JohnsonD. W.JohnsonR. T. (2004). Cooperation and the use of technology. In JonassenD. H. (Ed.), Handbook of research on educational communications and technology (2nd ed., pp. 785–811). Mahwah, NJ: Lawrence Erlbaum Associates.
35.
LeechN. L.BarrettK. C.MorganG. A. (2008). SPSS for intermediate statistics use and interpretation. New York/Oxon: Lawrence Erlbaum Associates.
36.
MalikowskiS. R. (2008). Factors related to breadth of use in course management systems. Internet & Higher Education, 11(2), 81–86.
37.
MalikowskiS. R.TheisJ. G. (2006). How course management systems are used and factors affecting use. Paper presented at the 22nd Annual Conference on Distance Teaching and Learning, University of Wisconsin, Madison.
38.
MalikowskiS. R.ThompsonM. E.TheisJ. G. (2006). External factors associated with adopting a CMS in resident college courses. Internet & Higher Education, 9, 163–174.
39.
MalikowskiS. R.ThompsonM. E.TheisJ. G. (2007). A model for research into course management systems: Bridging technology and learning theory. Journal of Educational Computing Research, 36(2), 149–173.
40.
MooreB. (2005). Key issues in web-based education in the human services: A review of the literature. Journal of Technology in Human Services, 23, 11–28.
41.
MorganG. (2003). Faculty use of course management systems. Boulder, CO: EDUCAUSE Center for Applied Research.
42.
NeisserU. (1967). Cognitive psychology. New York: Appleton-Century-Crofts.
43.
NicklesG. M.III (2006). Identifying measures of student behavior from interaction with a course management system. Journal of Educational Technology Systems, 34(1), 111–126.
44.
ReganA. E.WalcherS. (2005). Environmentalist approaches to portals and course management systems. Journal of Library Administration, 43(1/2), 173–188.
45.
RomeroC.VenturaS.GarcíaE. (2008). Data mining in course management systems: Moodle case study and tutorial. Computers & Education, 51(1), 368–384.
46.
RussellT. L. (1999). The no signifIcant difference phenomenon. Raleigh, NC: North Carolina State University.
SaettlerL. P. (1990). The evolution of American educational technology. Englewood, CO: Libraries Unlimited.
49.
SenftS.GallegosF. (2009). Information technology control and audit. New York/Boca Raton: CRC Press.
50.
SmithG.HeindelA.Torres-AyalaA. (2008). E-learning commodity or community: Disciplinary differences between online courses. The Internet and Higher Education, 11(3), 152–159.
SolomonG.SchrumL. (2007). Web 2.0: New tools, new schools. Eugene, OR: International Society for Technology in Education.
53.
WilkieK. J. (in press). Academic continuity through online collaboration: Mathematics teachers support the learning of pupils with chronic illness during school absence. Interactive Learning Environments.
54.
WinnW. (2004). Cognitive perspectives in psychology. In JonassenD. H. (Ed.), Handbook of research on educational communications and technology (2nd ed., pp. 79–112). Mahwah, NJ: Lawrence Erlbaum Associates.
55.
WoodsR.BakerJ. D.HopperD. (2004). Hybrid structures: Faculty use and perception of web-based courseware as a supplement to face-to-face instruction. Internet & Higher Education, 7(4), 281–297.
