Did We Become a Community? 1Did We Becomea Community?A Review of the Literature Su-Tuan Lulee Ed. D. Student Professor Patric Fahy EDDE 801, Athabasca University September 20, 2009
Did We Become a Community? 2 Did We Become a Community? A Review of the Literature The authors, Schwier and Daniel, professors of University of Saskatchewan, Canada, employ avariety of evaluation methods to understand the nature of formal virtual learning communities in highereducation. Over the past decade, online distance education has been growing rapidly. More and moreschools are providing courses via the Internet. The term “learning community” has become a popularterm to describe the online learning environment. A number of contributions have been given to themethods for evaluating online learning environments (Fahy, Crawford, & Ally, 2001; Garrison, Anderson,& Archer, 2000; Hara, Bonk, & Angeli, 1998; Henri, 1992; & Gunawardena, Lowe, & Anderson, 1998,etc.) however; the researchers have been over-relying on transcript analysis. This paper (Schwier &Daniel, 2007) uses mixed tools derived from previous studies to describe a full picture of the onlinecommunity. They begin from determining the existence of communities (definition), then move onidentifying the constituent elements, and the interactions among the elements (analysis), finally, theypropose a community modeling technique (prediction). The authors argue that it is necessary to use avariety of methods when analyzing a system as complex as online learning community. Sense of Community Two instruments are used to define whether the online groups have become a community. Theauthors first use Chavis’ Sense of Community Index (SCI, Chavis, n.d.) to measure individuals’psychological sense of community. This 12-True/False-item Index is a classic instrument employedbroadly in community psychology. Four dimensions of the overall construction, membership, influence,reinforcement of needs, and shared emotional connection are measured. Due to the low reliability of thisIndex, the authors employ Classroom Community Scale (Rovai, & Jordan, 2004) as the second measure. Patterns of Interaction Analysis Techniques used to analyze patterns of interaction in this paper are basically from TAT(Transcript Analysis Tool) developed by Fahy et al. (2001). TAT examines the structural elements (thenetwork exchange patterns) of online interactions including the density and the intensity.
Did We Become a Community? 3 Density is defined as “the ratio of the actual numbers of links to the possible total” (Fahy, 2001).Through the calculation of density, researchers begin to understand to what extent the participants of anetwork connect with each other. Intensity is defined as “responsiveness and attentiveness of members to each other” (Fahy, 2001)including to what degree the participants exceed the course requirement for participation; how often theparticipants send and receive messages (signs of reciprocation); and by whom and to whom the messageswere sent (signs of control and leadership). Modeling Community To develop a model that can interpret the interactions among community variables, the authorstake the following steps. First, they identify characteristics of community through content (transcript) analysis and confirmtheir findings with participants through semi-structured interviews and the focus group. The results are 14characteristics. Second, they determine the relative importance of the 14 characteristics by asking students toconduct a paired-comparison among the characteristics. The results are described using Thurstone Scalethat represents the ranking and points of the 14 characteristics clearly. Third, they organize the 14 characteristics into a network map based on the Bayesian BeliefNetwork (BBN) model building technique. BBN is a graph that is composed of nodes and directionalarrows. Nodes represent the 14 characteristics as variables. Direction arrows illustrate the interactionsamong the variables including the dependencies and the strength of relationships (strong, medium, orweak) among variables. Initial probabilities for each relationship then are assigned to the network basedon the results gained from Thurstone Scale, the experts, or the raw data; however, the values of eachprobability will change due to the condition of the related variables. Updating the conditional probabilitytable and making inferences based on new evidence can help understand the various relationships amongvariables (the characteristics) in a community.Figure 1 BBN representation of relationships among virtual learning community variables. (Schwier & Daniel, 2007)
Did We Become a Community? 4Note. From Schwier, R., & Daniel, B. K. (2007). Did we become a community? Multiple methods for identifying community andits constituent elements in formal online learning environment. In User-evaluation and online communities (p. 47). Conclusion While the authors use a variety of methods to illustrate the process for understanding formalonline learning community persuasively, the following questions need to be elaborated: 1. What are the connections between patterns of interactions (density, intensity, reciprocity, etc.) and BBN modeling? Are there statistical relationships in between? 2. Before this paper, some researchers have studied on the characteristics of the communities (Brook & Oliver, 2003 and Brown, 2001) however none of them were mentioned in this paper. Have the study based on prior research? 3. Chavis & Acosta (2008) have published a revised version of Sense of Community Index (SC-2) that Chavis claimed to have much higher reliability. Why didnt this paper use the most updated version (SC-2 was published in about the same time with this paper)? 4. How many characteristics are identified, 15 or 14? The numbers show on page 41 are not consistent. References Brook, C., & Oliver, R. (2003). online learning communities: a design framework. Australian Journal of
Did We Become a Community? 5 Educational Technology, 19(2), 139-160. Retrieved September 21, 2009, from http://www.ascilite.org.au/ajet/ajet19/brook.html.Brown, R. (2001). The Process of Community-building in Distance Learning Classes. Journal of Asynchronous Learning Networks, 5(2). Retrieved from http://www.aln.org/publications/jaln/v5n2/ v5n2_brown.asp.Chavis, D. M. (, n.d). Sense of Community Index. Association for the Study and Development of Community. Retrieved from http://www.senseofcommunity.com/files/Sense%20of%20Community %20Index12607.pdf.Chavis, D. M., & Acosta, J. D. (2008). The Sense of Community (SCI) Revised: The Reliability and Validity of the SCI-2. Presented at the 2nd International Community Psychology Conference, Lisboa, Portugal: Association for the Study and Development of Community. Retrieved from http://www.senseofcommunity.org/files/SOC_II%20product.pdf.Fahy, P., Crawford, G., & Ally, M. (2001). Patterns of Interaction in a Computer Conference Transcript. International Review of Research in Open and Distance Learning, 2(1). Retrieved from http://www.irrodl.org/index.php/irrodl/article/viewFile/36/74.Garrison, D. Randy; Anderson, Terry; Archer, Walter. (2000). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2-3), 87-105. Retrieved February 19, 2008, from http://communitiesofinquiry.com/files/Critical_Inquiry_model.pdf.Gunawardena, Charlotte, N., Lowe, C. A., & Anderson, T. (1998). Transcript Analysis of Computer- Mediated Conferences as a Tool for Testing Constructivist and Social-Constructivist Learning Theories. In Proceedings of the Annual Conference on Distance Teaching & Learning, 14th (p. 8). Presented at the Distance Learning 98, Madison, Wisconsin.
Did We Become a Community? 6Hara, N., Bonk, C. J., & Angeli, C. (1998). Content Analysis of Online Discussion in an Applied Educational Psychology. CRLT Technical Report (pp. 115-152). Netherlands: Kluwer Academic Publishers. Retrieved March 16, 2008, from http://crlt.indiana.edu/publications/techreport.pdf.Henri, F. (1992). Computer Conferencing and Content Analysis. In Collaborative Learning Though Computer Conferencing: The Najaden Papers (pp. 115-136). New York, NY: Springer.Rovai, A. P., & Jordan, H. M. (2004). Blended Learning and Sense of Community: A comparative analysis with traditional and fully online graduate courses. The International Review of Research in Open and Distance Learning, 5(2). Retrieved September 17, 2009, from http://www.irrodl.org/index.php/irrodl/article/view/192/274.Schwier, R., & Daniel, B. K. (2007). Did we become a community? Multiple methods for identifying community and its constituent elements in formal online learning environment. In User- evaluation and online communities (pp. 29-53). Hershey, PA: Idea Group Publishing. Retrieved from http://www.scribd.com/doc/3882220/Did-we-become-a-community-Multiple-methods-for- identifying-community-and-its-constituent-elements-in-formal-online-learning-environments.