Learning Models in Virtual Learning Environments

by Michael MacKay

November, 28th, 2020

Instructional design models cover a broad spectrum of implementations, goals, and methodological approaches, yet at their core, these models attempt to help educators overcome perceived gaps in the learning process (Dousay, 2017, p. 8). Each model has an intended goal for its implementation; some, like the ADDIE model, focus on systematizing the development cycle (Bates, 2015), making it a flexible framework to be adjusted for a multitude of different learning environments and scenarios. Other models focus more directly on specific affordances that emerge in environments, learners, and emerging technologies. These more scoped approaches to learning design are needed as new technologies enable new learning environments and experiences that were previously inaccessible. A technology-enabled environment requires instructional designers to rethink old ideas on instructional design and learning theory and return to a mindset that encourages the freedom to imagine new methodological approaches and innovations (Morris, 2018). 

The model of learning in 3D virtual learning environments (VLE) was developed initially by Dalgarno and Lee to identify and utilize the learning affordances that are unique to 3D computer-facilitated environments (2010). To help remove ambiguity, Dalargno and Lee defined learning affordances as the “tasks, activities, and underpinning pedagogical strategies [that are] support[ed] or facilitated by the technology” (2010, pp. 17-18). Dalargno and Lee identified two unique characteristics for 3D VLEs: representational fidelity, the degree of realistic immersion based on sensory stimuli, and learner interactions, the individual, collaborative and environmental actions or constructs emboldened by the learner (2010, pp. 14 – 15). They believed that high fidelity visual representation coupled with consistent learner interactions would allow learners to develop a sense of identity and presence along with a co-presence with other learners in the VLE, which should enable learners to trust their virtual experiences sufficiently to insight learning and clear misconceptions (Dalargno & Lee, 2010, pp. 23 – 24). Resulting from these assumptions were five learning affordances unique to VLEs: spatial knowledge representation, experiential learning, engagement, contextual learning, and collaborative learning (Dalargno & Lee, 2010, pp. 18 – 23). While many researchers found the above model’s focus on learning affordances insightful (Merchant et al., 2012, p. 552; Wei et al., 2015, p. 222), others raised concerns that it had too narrow of a scope (Fowler, 2015, p. 413) and possible biases (Bower & Sturman, 2015, p. 346).

The model of learning in 3D VLEs created a compelling argument against Clark’s view of separating learning models and media or technology (1994) by indicating some technologies, like virtual environments (VE), can facilitate learning experiences that are unique to the technology (Dalargno & Lee, 2010, p. 25). Despite this rationalization, the model was not without its faults; for example, a practitioner attempting to utilize this model would struggle to translate the learning affordances into meaningful learning experiences because the model solely focused on technological affordances. As Fowler argued, “Dalgarno and Lee have mainly taken into account the technological perspective, specifically through the identification of learning benefits that arise from the technical affordances implicit in these 3-D learning environments” (2015, p. 412). Fowler further questioned the notion that higher levels of representational fidelity and learning interaction will translate to more profound learning, stating that many circumstances do not require these characteristics to meet the learner’s pedagogical needs (2015, p. 415). Echoing these arguments, it would seem improbable that better visual fidelity always benefits the learning process. More realistically, a threshold of these characteristics, representational fidelity and learner interactions are required to create a smooth learning experience. However, more research is needed to determine the validity of Dalargno and Lee’s 3D VLE model concerning learning benefits (Fowler, 2015, p. 421; Dalgarno & Lee, 2010, p. 23).

Fowler’s model, the enhanced model of learning in 3D VLEs, was constructed by the union of Mayes and Fowler’s learning cycle (1999) and Dalgarno and Lee’s model of learning in 3D VLEs (2010). Mayes and Fowler’s framework focused on mapping constructivist activities into a learning cycle that consisted of (1) conceptualization, the learner’s initial contact with new concepts and the process they have developed to understand new exposition, (2) construction, the operation of building and combining new ideas through content-related activities, and (3) application, where the learner tests and tunes new conceptualizations in their applied contexts (1999, p. 489). The enhanced model of learning in 3D VLE’s goal was to create a more pedagogical description by mapping the stages of learning and weighing them against the learning affordances introduced in Dalgarno and Lee’s model (Fowler, 2015, p. 412). He described this process of unifying the learning affordances with their learner outcomes as design for learning, which focused on linking the design process of specific learning outcomes to a single learning session or part of a course (Fowler, 2015, p. 417). Using Mayes and Fowler’s learning framework to determine the learning requirements and Dalargno and Lee’s model to identify the task affordances, practitioners could identify the specific learning specifications in a VLE (Fowler, 2015, p. 420).

From a design perspective, the enhanced model of learning in 3D VLEs is an exciting and novel approach that focuses on the specific learning affordances of the technology and the underpinning pedagogical affordances needed to unionize the technology and pedagogy. This “pedagogical understanding of technology [moves] beyond simplistic dichotomies such as ‘passive’ and ‘active’ or the ‘tech as tool’ metaphor to encompass a more sophisticated conception of choreographing learning through [VLEs]” (Southgate, 2020, p. 39). In practice, a practitioner attempting to utilize a related emerging technology, like virtual reality, now had a road map to understand the technological affordances unique to the technology. Likewise, once these affordances are identified, they could follow Fowler and Maye’s (1999) methodological approach to relate these affordances to the learning outcome. While this model can be view as the bridge between technology, learning theory, and pedagogy, more research is needed to understand:

  • How the technology aids the learning in the conceptualization, construction, and application cycle.
  • The viability of the development cycle.
  • The best practices for the designing and operation of such a model.

Despite the model’s novel nature, many related guidelines already exist for other applications, such as military VR programs and best practices for designing objects in virtual worlds (Fowler, 2015, p. 421). Moreover, the enhanced model of learning in 3D VLEs has the potential to close the gap, not only in learning but also in the minds of practitioners, designers, and researchers attempting to comprehend and implement learning experiences using VLEs.

Reference

Bates, T. (2015). Chapter 4.3 The ADDIE model. In Teaching in the digital age. BCcampus. https://opentextbc.ca/teachinginadigitalage/chapter/6-5-the-addie-model/

Bower, M., & Sturman, D. (2015). What are the educational affordances of wearable technologies? Computers and Education, 88, 343–353. https://doi.org/10.1016/j.compedu.2015.07.013

Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21-29. http://www.ucs.mun.ca/~bmann/0_ARTICLES/Media_Clark.html

Dalgarno, B., & Lee, M. J. W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32. https://doi.org/10.1111/j.1467-8535.2009.01038.x

Dousay, T. A. (2017). Chapter 22. Instructional Design Models. In R. West (Ed.), Foundations of Learning and Instructional Design Technology (1st ed.). https://edtechbooks.org/lidtfoundations/instructional_design_models

Fowler, C. (2015). Virtual reality and learning: Where is the pedagogy? British Journal of Educational Technology, 46(2), 412–422. https://doi.org/10.1111/bjet.12135

Mayes, J., & Fowler, C. (1999). Learning technology and usability: A framework for understanding courseware. Interacting with Computers, 11(5), 485–497. https://doi.org/10.1016/S0953-5438(98)00065-4

Merchant, Z., Goetz, E. T., Keeney-Kennicutt, W., Kwok, O. M., Cifuentes, L., & Davis, T. J. (2012). The learner characteristics, features of desktop 3D virtual reality environments, and college chemistry instruction: A structural equation modeling analysis. Computers and Education, 59(2), 551–568. https://doi.org/10.1016/j.compedu.2012.02.004

Morris, S. M. (2018). Critical Instructional Design. An Urgency of Teachers. Pressbooks. https://criticaldigitalpedagogy.pressbooks.com/chapter/critical-pedagogy-and-learning-online/

Southgate, E. (2020). >Virtual reality in curriculum and pedagogy: Evidence from secondary classrooms. Routledge.

Wei, X., Weng, D., Liu, Y., & Wang, Y. (2015). Teaching based on augmented reality for a technical creative design course. Computers and Education, 81, 221–234. https://doi.org/10.1016/j.compedu.2014.10.017

Mark as Complete
chevron_right