521.3.2 – Reading Reflections

Originally published May 31, 2021. Backdated for public readers.

As I alluded to in my last blog, in Unit 3, we explored different educational methods and their respective strengths and weaknesses. In today’s reflection, I wish to outline the more significant structures at play so that you can also acknowledge such designs in your learning environments.

There are three major teaching philosophies or epistemologies:

    • Behaviourism
    • Cognitivism
    • Constructivism

Aside: Most interestingly, this unit’s reading proposed a 4th and new teaching philosophy, Connectivism, whereby learners optimize digital tools and maximize a learner-centred approach through social discourse.

John Watson’s theory of Behaviorism, influenced by Vladimir Bekhterev and Ivan Pavlov, proposed that learning results from external stimuli (Sprouts, 2020; Amin, 2017). For today’s discussion, this model is also considered a “teacher-based” approach. Examples include learning environments that rely heavily on lectures and assignments crafted by the teacher.

Cognitivism instead shifts the emphasis to the learner and explores the “thought process behind the behaviour” (Amin, 2017). Examples include the work of Jean Piaget, who hypothesized children build an understanding of the world through their senses, from breastfeeding to inductive reasoning, and this scaffolding or schema helps them understand how to interact with the world in a productive manner (Cherry, 2020). Alternatively, Lev Vygotsky believed that each generated passed down learning and that cognitive development could only be understood when social and cultural contexts were considered (Cheery, 2020). Cognitive theory presupposes that people make decisions based on logic, informed by information and memories (Amin, 2017). Therefore, although cognitivism lends well to the learner-centred approach, now held in high regard by academic intellectuals, it lacks an appreciation for the emotional component of learning.

Constructivism accommodates this need and incorporates both an appreciation for logic and humanistic elements (Amin, 2017). As a result, constructivist learning models believe that willfulness, creativity, and autonomy help learners accumulate knowledge in a meaningful way, improving retention, and inspiring interest to learn more (Amin, 2017).

This is where our Unit 3 readings jump in! We explored five different impact structures that our MALAT professors will be using to help facilitate our learning during this distance-education program: groups, nets, set, communities, and collectives.

      • Groups
          • According to Dron & Anderson (2014), groups may vary in size (dyads of 2, demes of 30, or tribes of up to 150) and are closed off to others. Dan Coyle (2010) discussed the benefits of the group and how it can help participants attend their sports practice and engage in deep learning in his book, The Talent Code.
          • Examples include the master/apprentice dyad, grade school class size, grad school seminar size, and project teams like our recent MALAT debate. When building cohesion in the group, leaders can use the work of Tuckman (1965) to help participants understand their role and how they can best contribute before adjourning in preparation for the next group activity.
          • Leaders and participants should remain vigilant to help avoid groupthink caused by “structural (insulation, impartial leadership, lack of methodological procedure, homogeneity across the group) or social (stress of external threats, recent failures, difficulty in decision-making, moral dilemmas) challenges” (Dron & Anderson, 2014, 2014. p. 115).
      • Networks
          • Conversely, networks are open to the public and feature a flexible membership that carries a mix of both strong and weak ties between participants (Oddone, 2016). Examples include discussion forums on the internet, social media websites, and perhaps in a more analog form, even the public library.
          • As a result, networks are very learner-centred, and self-determination is required to discover new information and consolidate conceptual frameworks (Oddone, 2016). This allows for the egocentric needs of the learner and can spark innovation in their field of interest (Oddone, 2016).
          • Veletsianos (2016) describes a network as a bounded system where people use a public or semi-public profile to build a list of friends or connections, and network connections can openly view that list (e.g. Facebook or LinkedIn).
      • Sets
          • To help narrow the overwhelmingly vast amount of information on the public web, sets, like data sets, help learners chose and sort through relevant information and acquire knowledge in a more productive manner (Dron & Anderson, 2014).
          • For example, think of hashtags on Twitter whereby users can drive into a topic or thread with greater efficiency. As a result, sets may contribute to stronger ties between participants, a topic we discuss further when defining communities (Dron & Anderson, 2014).

In summary, Dron & Anderson (2014) illustrate groups, nets, and sets and their respective modalities using the following Venn diagram (p.83).

Shifting the scope of our discussion from the 1,000-foot view to the 10,000-foot view, let us now explore the final two impact structures, Collectives and Communities.

    • Figure 3.1: Social forms for learning: Sets, nets, and groups (Dron & Anderson, 2014, P.73)

      Collectives

        • Collectives are an environment composed of people’s actions and their products (Dron & Anderson, 2014). For example, rating systems like eBay reviews or Facebook Likes organize information from various users to increase productivity.
        • In the right circumstances, they can “replicate or even improve upon the organizational value of groups, networks, and sets without the overhead of group processes, and take on many of the roles of a teacher” (Dron & Anderson, 2014, p.199).
        • However, collectives are susceptible to the Matthew effect, whereby users who submit reviews or likes first will significantly impact the likelihood of future ratings. Examples of the Mathew effect include people who vote in elections early, people who decided to like or not like a post when it is immediately published, and people who first submit an eBay or Google review for a new business. The input of those early users weighs more heavily than later users (Dron & Anderson, 2014); therefore, deliberate manipulation, loss of teacher and learner control, lack of pedagogical intent, and shifting contents can all impact the effectiveness of collectives (Ferreira-Meyers, 2015).
    •  Communities
          • Although some readers may be confused about how the attributes of a group and community differ in the context of online learning environments, as I was for a few weeks, Dron & Anderson (2014) define communities as intersections between the above impact structures.
          • A Community of Practice occurs at the intersection between the group and network environment. For example, such a ‘cluster’ may include many people who “share a purpose, practice, and often location, but [no]… explicit hierarchies, exclusions, and roles of a more defined group [exist]” (Dron & Anderson, 2014. p.80).
          • A Community of Interest, or Tribe, exists at the intersection of a group and a set. This can include a closed group of people who are “often bound by the interest in a topic more than by the group itself, although this may change in time” (Dron & Anderson, 2014. p.80). An example from the world of sport would be a Vancouver Canucks fan group or even a fantasy hockey league, whereby participants may come and go in time. Moreover, if the group agreed, they may switch their interests entirely to another sport.
          • The Circle, or your circle of friends, exists at the intersection between a network and a set (Dron & Anderson, 2014). For example, your friend group may expand and contract as circles of friends change or even combine. Within your circle of friends, invitations to specific events (concerts) are more casual than the traditionally defined ‘group,’ and the choice to attend the event is yours and yours alone (Dron & Anderson, 2014).
          • Indeed, there are many ways to define communities, and in digital spaces, Henri & Pudelko (2003) argue group cohesion is the critical factor in their four definitions.
                • Communities of interest
                • Goal‐oriented communities of interest
                • Learners’ communities, and
                • Communities of practice (COP), defined by Wenger (1998) as “groups of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly” (2). Furthermore, Wenger (1998) argues COP’s include three components:
                      • Mutual engagement (activities that promote social bonding),
                      • Negotiation of a joint enterprise (build something together),
                      • A shared repertoire (of tools and abilities).
          • Conversely, Riel and Polin (2004) identify three types of learning communities:
                • task‐based
                • practice‐based, and
                • knowledge‐based
  • Many factors drive the effectiveness of learning environments. When creating a distance-education curriculum in the digital space, teachers must carefully consider the ‘impact structure’ and curriculum design. Each learner will have their learning preferences, whether they prefer a teacher-based method with solid instruction, a learner-based method with greater freedom, or perhaps a social-based method found in Collectivism, but that is for another day.

In conclusion, I would like to illustrate the differences between groups, networks, and sets using the work of Dron & Anderson (2014). Building upon Paulson’s (2003) model of cooperative freedom (time, place, content, medium, pace, and access), they extrapolated ‘access’ into technology, method, relationship, delegation, and disclosure, increasing the number of metrics from 5 to 10 (Dron & Anderson, 2014). As a result, the cooperative freedom model illustrates the strengths and weaknesses of groups, networks, and sets in the context of a digital learning environment.

Figure 4.1: Notional cooperative freedom in groups (Dron & Anderson, 2014. p.99)
Figure 5. 1: Notional cooperative freedom in networks (Dron & Anderson, 2014. p.138)
Figure 6.1: Notional cooperative freedom in sets (Dron & Anderson, 2014. p.172)

These differences are fascinating and serve as a great introduction to our Unit 3 debate topic: Are digital learning environments equal? According to Veletsianos (2016), “teaching a group might require different instructional and assessment strategies than facilitating learning in a network” (p. 246), which seems apparent given the illustrations above. However, how do we define the word equal? And if definitions differ, who is more accurate? Instead, perhaps, as we discovered today, it is the careful definition of language that will help us arrive at a shared understanding and maximizes the use of the tools available.

Stay tuned for updates from the debate.

References:

Amin, Z. A. (2017, October 15). Learning Process: Behaviorism, Cognitivism and Constructivism. Slideshare. https://bit.ly/3wJRXuR

Cherry, K. (2020, March 31). The 4 Stages of Cognitive Development. Verywellmind.com. https://bit.ly/3uII6Ew

Cherry, K. (2020, April 16). A Biography of Lev Vygotsky, One of the Most Influential Psychologists. Verywellmind.com. https://bit.ly/34zz6H6

Coyle, D. (2010). The Talent Code. Arrow Books.

Dron, J, & Anderson, T. (2014). Teaching Crowds. Athabasca University Press.

Henri, F., & Pudelko, B. (2003). Understanding and analyzing activity and learning in virtual communities. Journal of Computer Assisted Learning, 19(4), 472–487.

Oddone, K. (2018, January 21). PLNs: Theory and Practice. linkinglearning.com. https://bit.ly/3uwHilS

Ferreira-Meyers, K. (2015). Dron, Jon and Terry Anderson (2014). Teaching Crowds – Learning and Social Media, Edmonton: AU Press. Journal of Learning for Development2(2). Retrieved from https://jl4d.org/index.php/ejl4d/article/view/123

Paulsen, M. (2003). Online education and learning management systems: global e-learning in a Scandinavian perspective. Information Retrieval. https://bit.ly/3wPTaB9

Riel, Margaret & Polin, Linda. (2004). Learning Communities: Common Ground and Critical Differences in Designing Technical Support. DOI:10.1017/CBO9780511805080.006.

Sprouts. (2020, April 20). Watson’s Theory of Behaviourism [VIDEO]. YouTube. https://youtu.be/V09FuazW8bc

Tuckman, B. (1965) Development Sequence in Small Groups. Psychological Bulletin. Volume 63, No. 6, 384-399. Naval Medical Research Institute, Bethesda, Maryland. https://bit.ly/3wMneO4

Veletsianos, G. (2016). Digital learning environments. In N. Rushby & D. Surry (Eds), Handbook of Learning Technologies (pp. 242-260). UK: John Wiley & Sons.

Wenger (1998) Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University Press. DOI: 10.1017/CBO9780511803932