The science of digital innovation
Digital innovation continues to impact learning outcomes and teaching efficacy, largely in a positive way. Learning design expert, Nilanjana Saxena, investigates how Augmented Reality can support and extend learning in the classroom.
Despite all of the positives that have resulted from digital innovation, educators and the broader teaching and training community continue to grapple with how best to communicate abstract concepts to learners. Misconceptions that many students hold in multiple disciplines, especially science, are mostly due to concepts being abstract, counterintuitive and lacking relevance; thereby increasing cognitive load and decreasing motivation and learning.
In this article, I share some of the research on what learning science says about the benefits of deploying augmented reality (AR) in education.
Over the years AR has evolved. As generally perceived, AR includes technology that enables users to see an extra layer of digital content on top of a real world object. AR environments are characterised by flexibility, safety and ubiquity, finding application when concepts are cognitively challenging for learners, if taught through conventional means.
To understand how AR supports learning, it is relevant to understand learning as a cognitive process.
Learning involves the formation of associations between the new and prior knowledge. The deeper these associations, the longer and more lasting the memory codes, which can be retrieved later. This shows that learning and memory are interdependent. Forming associations is part of the processing of information, and this process is an iterative cycle involving the acquisition, storage and retrieval of data.
A well designed AR feature allows learners to explore through manipulations and observe trends by different variables such as time and dimensions, while at all times keeping them physically safe. AR applications for training professionals in high risk jobs – such as training surgeons or technicians repairing elevators – remove both the risk and fear, while providing a realistic training environment. Thus with AR, meaningful deep associations between prior and new knowledge can be formed which enable deeper processing, and long-lasting memory codes for future retrieval of information.
Learning sciences research offers evidence that AR based learning benefits learners by influencing their interaction with difficult concepts.
Literature supports that immersing learners in highly interactive visuals aids in creatively constructing knowledge and increasing motivation. A learning environment conducive for facilitating knowledge construction is needed to overcome most learning challenges. In their article, ‘Affordances of Augmented Reality in Science Learning: Suggestions for Future Research’, published in Journal of Science Education and Technology (August 2013), research by authors Kun-Hung Cheng and Chin-Chung Tsai shows how AR’s interactive and media-rich visuals provide the tools to create opportunities for learners to construct knowledge. Mobile AR additionally allows ubiquitous and flexible manipulations catering to differing learner needs, pace and styles; as Keith R. Bujak et al reveal in, ‘A psychological perspective on augmented reality in the mathematics classroom’, Computers and Education (October 2013).
Even the real time feedback and sense-stimulating environments created through such manipulations of what lies hidden beneath further motivates learners’ inquiry, problem solving and critical thinking (Matt Dunleavy, Chris Dede and Rebecca Mitchell in ‘Affordances and Limitations of Immersive Participatory Augmented Reality Simulations for Teaching and Learning’, Journal of Science Education and Technology, February 2009). Such learning settings are fertile for learners to create both meaning and relevance which adds to motivation and positivity towards learning.
Making abstract concepts relatable and relevant
AR environments can be used to demystify abstract concepts for they allow one to see the invisible. Through AR, learners can manipulate content right from the nano to the galactical level. These causal relationships and mechanisms underlying abstract concepts, along with hands-on work and sense-stimulating experiences made possible by AR, helps create an immersive experience, allowing deeper associations with abstract concepts by making them more concrete and relatable.
Pavio, 1969 (as cited in the 2010 book Psychology: Themes and Variations (8th edition) by Wayne Weiten) states that words with concrete images are retained better by memory. Imagery and manipulations offered by AR help create connections by making it possible for the learner to go deeper into the concept, view invisible concepts and improve spatial skills by viewing 3D objects from different planes (Cheng and Tsai, 2013). Such episodic memories enhance retrieval in new situations.
Managing cognitive load
AR learning environments afford chunking and clustering of information, enabling the working memory to deal with fewer interacting elements (new abstract entities) at any single time. This enhances processing and assimilation of information by reducing cognitive load, which is the effort associated with a specific topic.
Furthermore, an AR learning environment allows the user to focus on one screen with digital content overlaid in the real world. As highlighted by John Sweller in his article ‘Element Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load’, published in Educational Psychology Review (June 2010), this reduces splitting attention between screens and the real world while also collaborating with peers, enabling the learner to instead maintain and increase focus on the task at hand.
Through their research, as shown in their article ‘Making the Invisible Visible in Science Museums Through Augmented Reality Devices’, published in TechTrends (January 2014), authors Susan A. Yoon and Joyce Wang reveal that using AR added to greater team work, dynamic visualisations of invisible phenomena, and students gained in-depth knowledge about magnetic fields by increasing relatability, reasoning skills and reducing cognitive load.
Making content personally relevant
Learning is most effective when learners see content as personally relevant. Well-designed AR activities in learning help create relevance of class material to the real world.
Interaction and application of knowledge in the AR environment give rise to draw deeper associations and schemas. Through situated investigation, the learner finds learning personally relevant. For instance, being able to relate the theoretical triangles in textbooks with the real world triangles enables self-reference and thus greater motivation for self-directed learning.
AR has come a long way in making learning holistic, enjoyable, personalised and far reaching. For AR based learning to deliver all it promises, learning designers and trainers must themselves be clear about what the desired outcomes are. AR is well suited to be applied when learning outcomes cannot be well achieved through conventional teaching methods and tools.
As AR is ultimately a tool, its utilisation must be integrated with the overall learning experience that is envisaged. Like any other teaching aid, AR must be aptly fitted alongside teachers and conventional teaching methods. Careful consideration needs to be given in the design of any educational intervention, keeping in mind the fundamentals which underpin teaching and learning.
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