Digital Learning: Approaches and Pedagogies Beyond Video

The era of immersive computing offers us a unique opportunity to transform learning. ‘Massive Open Online Courses (MOOCs)’, an emergent technology, has been one such opportunity that’s come around and proliferated in the last decade. While MOOCs have significantly contributed towards the evolution of the educational landscape as well as bridging the accessibility divide, they have often been criticized for being largely video based, video driven. So, despite the new technology, there is a lot of reproduction. Instead of the blackboard there is a device screen, instead of the printed textbook there is an e-book. Instead of the instructor standing in front of the class and talking, there are instructors standing in the front of the camera and talking through videos. Thus, a lot of this is kind of new and interesting, and yet, not-so-new and mostly reproduced or repackaged.

This post curates three technology enabled interventions that harness the digital medium and offer effective instructional approaches, thus reducing the high dependency on video or reproduction in digital learning whilst improving instructional outcomes.

• Affinity Spaces

The wicked societal problems of today demand the skill of collaboration and working together to solve them, thus laying the premise for how collective intelligence is going to trump individual intelligence.

Affinity spaces leverage the argument by social constructivists, that all learning is in fact social — that “Understanding is in our interactions with the environment,” and that “what we learn is a function of the content, the context, the activity of the learner, and, perhaps most importantly, the goals of the learner” (Savery & Duffy 1996, p 136). This approach to learning begs to be placed diametrically opposed to the behaviorist view that knowledge is something that happens to students when it is transferred from someone who already has that knowledge (didactic pedagogy).

The affordance of today’s digital technologies makes it conducive to create collaborative relationships in the eLearning/ digital learning spaces. While, as instructional designers we may find it a challenge to find ways to assess this social learning — managing the kind of interactions that create collaborative intelligence lies at the very core of this challenge. This can include managing and employing assessment practices that measure these interactions. Formative assessments tend to work better than summative assessments in this regard, though it would also require assessing collaboration that encourages collective intelligence.

Affinity Spaces are spaces where learners interact as learning artifacts. These spaces exist all over the internet and are organized rather unconventionally as compared to formal spaces such as schools, colleges or universities. Experts and novices all come together driven by interest and passion only. Mentorship and leadership are flexible. Knowledge is distributed and dispersed and can also be customized. When a learner wants help, they may be provided with a tutorial, perhaps a didactic one. Or, a one-to-one instructional session. There are no defined norms. It’s an interweave of rather complex relationships among people, that stores and curates knowledge in a rather novel and modern way. Affinity spaces, old and new, organize teaching and learning in quite different and deeper ways than formal spaces do. Some examples of such spaces can include but are not limited to online fan fiction sites, Subreddit etc. These spaces lend themselves effective for the digital medium and eLearning/ digital learning can harness this affordance of affinity spaces.

• Exploratory Learning Environments (Simulation-Based Learning)

Simulations are instructional scenarios wherein a learner is placed in a ‘virtual space’ defined by the instructor/ instructional designer or even the learner themselves, in some cases. This space represents an alternate reality within which learners interact with the simulated artifacts. Learners experience the reality of the new, expected or unpredictable scenarios and create new meanings as a result of them. Instructional simulations as a form of experiential learning align well with the principles of learner-centric and constructivist learning and teaching and have the potential to engage students in ‘deep learning; learning that empowers understanding as opposed to ‘surface learning’ that requires only memorization (Carleton, 2018).

Exploratory online learning environments or simulation-based eLearning entails building circumstances, situations, opportunities, or experiences for learners that are difficult to have in a real classroom. Therein lies the crux of exploratory learning environments; they simulate these very real, authentic opportunities from the real word, take away some of the constraints, or the obstacles to using them and break them down to only those things that are essential for the learning.

Exploratory simulations challenge students to analyze available information and make critical decisions to solve problems, thereby enabling them to experiment with ideas and outcomes and ultimately master the application of these concepts in real-life situations. Besides opening-up these opportunities, this kind of a learning environment provides learners an ownership over the process. They are called exploratory because the learner is exploring. The learner is driving what they are doing. Experience or construction is personal; and it is different for everybody. The learner is given some free reign and is trusted to engage with it. It helps learners acquire the skills that they will need in the eventual, real world. When designing such a learning environment, it is important to ensure that the authenticity of whatever problem or activity is being recreated is preserved. There tends to be an inclination to gamify it — gamification does create motivation, but it is motivation that is not organic to the instructional content. A beautiful example of an exploratory simulation-based learning is http://www.worldwarfighter.com/hajikamal/activity/.

• Intelligent Tutoring Systems (ITS)

Intelligent Tutoring Systems (ITS), are an extension of individualized instruction and use artificial intelligence to personalize multimedia learning.

The Approach: What if every learner in an online course has a virtual teaching/ training assistant who pays attention to their learning needs, diagnoses and assesses problems whilst also assisting or providing feedback as per the specific needs of the learner. This virtual teaching assistant would not only encompass the subject matter and teaching expertise of experienced instructors, but also perform many of the routine instructional interventions.

ITS, thus entails creating educational systems that provide instruction tailored to the needs of individual learners, just as many good teachers do. It leverages the benefits of one-to-one instruction and encourages learners to practice their skills by carrying out tasks within highly interactive learning environments. ITS goes beyond training by resolving learner queries or issues and providing personalized guidance. Unlike most eLearning technologies, these tutoring systems assess each learner’s behavior within these interactive environments and develop a framework of their knowledge, skills, and expertise. They observe learner behavior and build a fine-grained cognitive model of the learner’s knowledge that can be compared with an expert model. They make inferences about a learner’s mastery of topics or tasks in order to dynamically adapt the instructional content or style of instruction to further provide explanations, hints, examples, demonstrations, and practice problems, as needed. Research on prototype systems indicates that ITS-taught students generally learn faster and translate the learning into improved performance better than classroom-trained or non-assisted online learners.

[This blog post was written by Natasha Mujgule, Instructional Design Consultant at IIMBx]

Source: IIMBx