Academic journal article Educational Technology & Society

The Search for Pedagogical Dynamism-Design Patterns and the Unselfconscious Process

Academic journal article Educational Technology & Society

The Search for Pedagogical Dynamism-Design Patterns and the Unselfconscious Process

Article excerpt

Implications of technology-driven decision making in education design

Universities are embracing the growth of Internet access, implementing strategic plans to offer online learning (Kim & Bonk, 2006). In the U.S., nine percent of universities have MOOCs (Massive Open Online Courses) in various planning stages (Allen & Seaman, 2013). Technology has become a great ally in the task of designing education and enhancing learning. Students are now able to study via different, more flexible, delivery platform. This trend is symptomatic of using educational technology in a bold move to pursue opportunities of converging, seamless teaching and learning. However, underpinning this trend, it is apparent that technology is driving decision-making about content and pedagogy. There are challenges of navigating through various technologies, trying to force-fit activities into online settings, or compromising activities due to technological constraints. What is increasingly missing is a focus on traditional course development and educational quality (Schmieder, 2008), or what Alexander (1979) termed "aliveness," leading to "fragmented, alienating and/or dispiriting experiences" (Goodyear & Retalis, 2010).

Within a typical educational design context, the choice of what to teach is generally followed with technologies used and pedagogical goals (Mishra & Koehler, 2006). Take for example, the task of designing a program to be delivered both online and on-campus. University processes necessitate students choose a delivery mode at enrolment e.g., either "On-campus" or "Online." As technologies are rarely designed with teaching and learning in mind, when such an operational/technological approach drives pedagogical strategy, then pedagogy and learning activities also become fixed by the chosen delivery mode (Goodyear, 2005; Means et al., 2010). Complexity arises in the design phase, such as the need to create different course profiles and pedagogies to suit each delivery platform (Figure 1). Also, the way students learn and teachers teach is not necessarily considered, making it more difficult to prioritise and react to individual student needs and offer a genuinely enhanced learning experience equivalent across the delivery modes. If a new mode for learning and teaching is then incorporated, it confronts basic design issues. A new delivery mode reconstructs the dynamic equilibrium between content, pedagogy and technology (Mishra & Koehler, 2006), creating additional pressure for educators to understand (Herring et al., 2014). Moreover, if the organisation adjusts processes and practices to meet the needs of the technology and not pedagogy, then everyone ends up serving "the machine" (Pollock & Cornford, 2005). The ability to make available a single set of materials and activities for all students, across all delivery platforms, accessible according to their circumstances, becomes increasingly complex (Phillips & Lowe, 2003; Flynn, Concannon & Ni Bheachain, 2005; Laurillard, 2009).

[FIGURE 1 OMITTED]

The following section unpacks the issue of a technology-driven approach amidst compounding, complex variables, using Mishra & Koehler's (2006) TPACK framework, to illustrate the need to move towards a more dynamic pedagogical framework.

The challenge of maintaining dynamic equilibrium as complex variables compound

According to Mishra & Koehler's (2006) TPACK framework, the three main aspects of learning environments--content, pedagogy and technology--must exist in a state of continuous dynamic equilibrium or tension, as in Figure 2. A change in Content Knowledge (CK), Pedagogical Knowledge (PK), or Technological Knowledge (TK), must be "compensated" by a change in the other two aspects to rebalance the state of equilibrium of good teaching.

Using our previous example of designing a course to be delivered "Online," "On-campus" or "Multi-mode," good pedagogy requires the Learning Objectives (LO) of a course be equivalent irrespective of delivery mode (Biggs & Tang, 2007; Meyers & Nulty, 2009), making the function CK (Learning Objectives) a fixed variable in TPACK. …

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