Learning Communities

Summary

Feeling part of and actively contributing to a learning community is directly linked to student motivation and resilience. Studying within learning groups can be an important foundation for effective interaction between students, their peers and teachers in support of deeper learning. Proactive support from teachers for learning within smaller groups, provided synchronously or asynchronously, is important if the benefits of intellectual rigour and deep engagement are to be achieved. This element supports enhanced learner-teacher and learner-learner engagement.

Rationale

Feeling part of and actively contributing to a learning community is directly linked to student motivation and resilience. By basic definition each cohort of students forms a community. Courses, and indeed subjects are comprised of members with a common interest. So it seems only natural that educators should maximise the opportunities presented by this social construct. The Learning Communities element aims to provide guidance regarding ways of organising subjects, grouping students, and designing and facilitating learning activities to support learning communities in social and academic engagement.

Social scientists have long studied the importance of community, with many during the later half of the 20th century, focussing on its impact within teaching and learning. For example MacMillan and Chavis (1986) provide criteria for a successful community while Doolittle and MacDonald (1978) explore the relationship between communication and “sense of community” in a neighborhood setting. Wenger’s (1998) seminal book extended the social theory of learning by providing a specific framework for educational design. He begins with four premises: being social is central to the human experience and therefore vital to learning, knowledge is contextual, knowledge is active and learning must be meaningful (Wenger, 1998, p. 4). Traditionally the term ‘community’ has been distinguished by two notions, the first territorial and the other relational (MacMillan & Chavis, 1986, p. 8). Parallels may be drawn to CSU’s differentiation between student cohorts as on campus of distance/online.

There can be no doubt advances in technology have greatly influenced how communities are formed and ways in which members interact. As a result, researchers including Wenger, McDermott, and Snyder (2002) and Garrison (2011) have revisited earlier works, adopting strategies to maximise the affordances of technologies to support community. Researchers such as Rovai (2002) have presented evidence that an online classroom has the potential to build and sustain a sense of community at levels that are comparable to face to face classrooms. Many researchers have highlighted the importance of establishing a cohesive learning community as a foundation for curriculum focused learning activities (see, for example, Salmon, 2004; Harasim, 1990; Hiltz, 1994). The notion of social presence has been argued to be a key underpinning requirement for effective online learning communities (Rovai, 2002; McInnerney & Roberts, 2004). Sung and Mayer (2012, p.1738) define social presence as “the degree to which a person is perceived as ‘real’ in mediated communication”. They identify five factors or constructs within the overarching notion of social presence: Social respect, Social sharing, Open mind, Social identity, and Intimacy.

Proactive facilitation from teachers for learning within online cohorts, provided synchronously or asynchronously, is important if the benefits of intellectual rigour and deep engagement are to be achieved. This facilitation is vital as students need support to engage in productive interaction and dialogue (Asterhan et al., 2012, p. 376). Assuming that students will automatically engage effectively with their peers in ways which will lead to learning benefits without deliberate work to help establish an effective learning community is one of the most common pitfalls of online collaborative learning designs (Kreijns et al., 2003). Importantly, though, effective learning communities depend on students seeing this as important and taking a degree of responsibility for the process (Conrad, 2005). Consequently a key aspect of the facilitation process is communication about the benefits of an effective learning community in order to get buy in from students for community development activities.

Researchers have proposed a number of online teaching models providing guidance for teachers on ways of establishing an effective learning community (see, for example, Coll, Rochera, & de Gispert, 2014; Rovai, 2002; Stacey, Smith, & Barty, 2004, Salmon, 2004). Some of the key recommendations emerging from this body of work are the following: set tasks and timelines, build group cohesion and a culture of participation, intervene through alternative means such as email or phone with students who are not participating, use knowledge about student interest to select small groups, and provide timely feedback. One of the more detail models is Salmon’s (2004) seminal eModerating model, which sets out five stages of the facilitation or moderation process: Access and motivation, Online socialisation, Information exchange, Knowledge construction, and Development.

A number of researchers have highlighted the online cohort size as a key consideration for the development of learning communities (Rovai, 2002; Kim, 2013; Aragon, 2003). The benefits of smaller class sizes in the school sector are well documented with most studies finding a small to moderate but consistent positive benefit for small classes (see, for example, Ehrenberg, Brewer, Gamoran & Willms, 2001; Hattie, 2012). In a higher education context research relating class size to student achievement has been somewhat inconclusive (see, for example, Toth & Montagna, 2002), suggesting that large classes are not necessarily a barrier to student success, if appropriate engagement strategies are incorporated into the subject design, with such strategies including effective use of tutorials and workshops to supplement large whole class lectures. Similarly, in an online context, the size of the overall enrolment within a subject is unlikely to be a major factor, but the size of the group of students studying together within the online space, that is, the online cohort size, is of more importance (Aragon, 2003) and consequently dividing larger cohorts into sub cohorts within the online space is strategy worthy of consideration (Kim, 2013; Rovai, 2002).

The dividing of students into smaller cohorts is an approach to learning support that has been adopted very successfully by the Open University in the UK over many years, with tutors allocated to support each group of students as they worked through their learning within a subject. At the Open University this was often done through face-to-face meetings with students grouped together with students from within the one geographic area allowing them to meet at local study centres. In the CSU context where students are dispersed across wide geographic areas regular face to face support for online cohorts is normally not possible, but many of the benefits of support for students within smaller cohorts are possible through synchronous and asynchronous online support.

A number of authors have recommended both lower and upper limits on cohort sizes for online study. For example Hiltz (1997), Rovai (2002) and Aragon (2003) all recommend that classes be divided into sub cohorts of no more than 30, while Turoff (1997) argues that a critical mass is needed in order to allow effective online engagement, with Rovai (2002) suggesting that this minimum should be 8-10 students. Some authors have highlighted information overload within large online cohorts as an issue (see, for example, Chen, Pedersen & Murphy, 2012), while others have implied that the depth of engagement in online discussions (evidenced by length of postings, thoroughness of reading of peer postings, or depth of interaction evident within postings) may be less within larger cohorts (Hewitt & Brett, 2007; Kim, 2013). In a CSU context the cost implications of very small cohort sizes is an important consideration and consequently we would suggest that a reasonable compromise might be the idea of dividing very large cohorts into sub cohorts of a maximum of 50 students.

Strategies

This section sets out a number of specific strategies that are known to be helpful in establishing a learning community. It is important to acknowledge that there is substantial synergy between the Teacher Presence, Interaction Between Students and Learning Communities elements of the model. Consequently many of the strategies listed Teacher Presence (e.g. welcome videos, communication tone, and responsiveness) and Interaction Between Students (e.g. asynchronous discussions, synchronous discussions, peer teaching and online reflective journals) will also have a positive impact on the establishment of an effective learning community.

Sub-cohorts - The creation of smaller sub cohorts within large cohorts, facilitated by a tutor who guides the community building, provides formative feedback through discussion forums and is responsible for the marking of summative assessment tasks;

Facilitated Socialisation - Learning activities which support students through orientation to the online environment, socialisation and personalisation of the environment, prior to undertaking curriculum focused community learning activities;

Shared Activity - Community building through contribution to a shared resource such as a gallery of photos containing examples of a concept or experiences from professional placement;

Social Media - Establishment of social media streams supporting the sharing of ideas and resources, using tools such as Twitter, Instagram or shared bookmarking tools.

References

Aragon, S. (2003). Creating social presence in online environments. New Directions for Adult and Continuing Education, 100, 57-68.

Asterhan, C. S. C., Schwarz, B. B., & Gil, J. (2012). Small-group, computer-mediated argumentation in middle-school classrooms: The effects of gender and different types of online teacher guidance. British Journal of Educational Psychology, 82(3), 375-397. doi: 10.1111/j.2044-8279.2011.02030.x

Chen, C. Y., Pedersen, S., & Murphy, K. L. (2012). The influence of perceived information overload on student participation and knowledge construction in computer-mediated communication. Instructional Science, 40(2), 325-349.

Conrad, D. (2005). Building and maintaining community in cohort-based online learning. Journal of Distance Education, 20(1), 1-20.

Doolittle, R. J. & MacDonald, D. (1978). Communication and a sense of community in a metropolitan neighbourhood : A factor analytic examination. Communication Quarterly, 26, 2-7.

Ehrenberg, R. G., Brewer, D. J., Gamoran, A., & Willms, J. D. (2001). Class size and student achievement. Psychological Science in the Public Interest, 2(1), 1-30.

Garrison, R. (2011). E-learning in the 21st Century: A framework for research and practice 2nd ed. Retrieved from EBook Library

Hattie, J. (2012). Visible learning for teachers: Maximizing impact on learning. Routledge.

Harasim, L. 1990, On-line Education: Perspectives on a New Environment, Praeger, New York.

Hewitt, J., & Brett, C. (2007). The relationship between class size and online activity patterns in asynchronous computer conferencing environments. Computers & Education, 49(4), 1258-1271.

Hiltz, S.R. 1994, The Virtual Classroom: Learning Without Limits via Computer Networks, Ablex, Norwood, NJ.

Hiltz, S.R. (1997). Impacts of college level courses via asynchronous learning networks: some preliminary results. Journal of Asynchronous Learning Networks, 1(2).

Kim, J. (2013). Influence of group size on students’ participation in online discussion forums. Computers & Education, 62(0), 123-129. Doi: http://dx.doi.org/10.1016/j.compedu.2012.10.025

Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Computers in human behavior, 19(3), 335-353.

McInnerney, J. M., & Roberts, T. S. (2004). Online learning: Social interaction and the creation of a sense of community. Educational Technology & Society, 7(3), 73-81.

MacMillan, D. & Chavis, D. (1986). Sense of community: A definition and theory, Journal of Community Psychology, 14, 6-20

Rovai, A. P. (2002). Building sense of community at a distance. The International Review of Research in Open and Distributed Learning, 3(1).

Salmon, G. (2004). E-moderating: The key to teaching and learning online. Psychology Press.

Sung, E., & Mayer, R. E. (2012). Five facets of social presence in online distance education. Computers in Human Behavior, 28(5), 1738-1747.

Toth, L. S., & Montagna, L. G. (2002). Class Size and Achievement in Higher Education: A Summary of Current Research. College Student Journal, 36(2).

Wenger, E. (1998). Communities of practice: learning, meaning, and identity. Cambridge, U.K. ; New York : Cambridge University Press.