Teaching On-line: A Cognitive Approach

Teaching On-line: A Cognitive Approach

Dr. Jamshed Bharucha, Vice Chancellor, Sai University, 0

Jamshed is a cognitive neuroscientist who has served in prominent leadership roles in higher education, and is currently the inaugural Vice Chancellor of Sai University, Chennai.

Teaching on-line has forced us to reckon with an inconvenient truth: lecturing for an hour, class after class, week after week, is deadly. As professors, we design our curriculum and we design our syllabus but we rarely design our pedagogy. As knowledge expands, we update what we teach but rarely how we teach. We revise the content, organization and delivery of our lectures but rarely question the lecture format.

Those of us who became academics sat in the first row and hung on our professor’s every word, but most students tune out quickly. I love to watch on-line lectures, but most people do so only under duress. Inattention to formal teaching is a problem in physical classrooms, but is magnified in virtual classrooms. Zoned out back benchers feigning interest have their fantasies to entertain them, but zoomed out on-liners feigning interest have the internet at their fingertips.

What principles should guide our design of on-line pedagogy? A growing literature on the cognitive science of learning offers a fresh approach based less on opinion and more on evidence. As masters of our classrooms, we believe we know what’s best for our students and demand that they learn what we teach. Instead, we should seek to understand how our students learn and demand of ourselves that we teach accordingly. Education researchers have advocated this perspective shift – from teaching to learning -- for decades. Learner-centric teaching can be effective even in a traditional lecture hall, but old habits die hard. When I stride into a classroom, I take my place at the front and begin expounding. I am energized by the few earnest faces before me. But what about all the others, present physically but absent mentally.

Connect with Students’ Existing Conceptual Framework

The mind represents knowledge as networks of concepts (conceptual or semantic networks), encoded in the brain as neural networks. A concept’s meaning is captured by the network within which it is embedded. At any given time, a small portion of one’s conceptual network is activated; this represents what we are currently thinking about, and is called active or working memory.

Conceptual networks have vertical and horizontal structure. The vertical structure represents a hierarchical organization of concepts from granular to abstract. For example, the concept of violent crime is subdivided into homicide, assault and other types of violent crimes. Violent crime is itself a subdivision of the more abstract concept of crime. The horizontal structure of concepts represents their relationship to other concepts. For example, the concept crime is related in specific ways to other concepts, such as statute and contract, each of which has its own vertical structure.

These networks are acquired through experiential and formal learning. Learning consists of modifying how concepts are networked. New concepts are formed when links between existing concepts converge in new ways. Existing concepts are altered when new linkages are established and older ones are pruned. The mind of an expert has more vertical layers of granularity and abstraction – and more highly elaborated horizontal links between concepts -- than does the mind of a novice.

Learning is optimal when new information links with existing conceptual networks. The teacher must first activate regions of the student’s current network where the new information can be linked, and then place the new information in that context. Otherwise, the student will be lost or resort to mindless note-taking and meaningless rote learning. Understanding a new idea means grasping linkages with existing networks.

Focus on Depth of Understanding & Breadth of Application, & Avoid an Information Deluge

A fundamental objective of education is to learn general principles that you can apply in novel situations. When a new principle is explained, perhaps with an illustrative case, we assume it will be encoded in students’ brains in its general form, and that it will leap to mind in new cases where applicable. Alas, learning is radically context-specific. A principle learned in the context of one case does not transfer easily to other applicable cases. This is called the problem of far transfer. I used to teach statistics from traditional textbooks,
which introduce probability theory using coins, dice and coloured marbles. Nice and clean. I was then chagrined when students failed to conceptualize identical problems framed with different objects.

The only known method to mitigate the failure of far transfer is to learn a new principle in as diverse a range of cases as possible. The general principle doesn’t become an abstract concept until it is connected to multiple memories of cases across a wide swath of the network. That’s when it acquires meaning; that’s when the students have the feeling of getting it – of having a deep understanding. That’s when their minds are likely to invoke that principle in a new case in the future.

University courses tend to focus on the theoretical, leaving the application to experience after graduation. That’s a flawed model. General principles and their applications and must be learned in tandem, back and forth, each strengthening the other’s links within a conceptual network.

We professors love to hold forth. This is a symptom of the curse of knowledge: the more you know, the harder it is to explain to someone who knows less. But unless the students’ brains can absorb our deluge into their existing conceptual networks, the exercise is futile. Reduce the number of new concepts you teach, but increase the discussion of their applications in varied real-life contexts. Focus on teaching only the most important new concepts – the ones that you want them to internalize -- and discuss them in varied cases.

A special case of varying the context involves the temporal context. If a principle is being taught using five illustrative cases, retention is better if the cases are sprinkled over a period of time, interleaved with other material, than if they are taught in quick succession. A seemingly well-organized syllabus might group principles together with applicable cases. This leads to rapid learning in the short term but poor recall in the long term. In contrast, a syllabus that weaves topics and cases throughout the semester appears disorganized but produces far greater recall in the long term. The seemingly disorganized approach is frustrating for the students unless you explain why it’s a deliberate strategy and they take ownership of the learning process. This is called metacognition. Students are more motivated to cooperate with a novel pedagogy if its metacognitive rationale is clear.

Make the Class Active, Not Passive, for the Student

Learning is deeper and more enduring when actively articulating or generating ideas than when passively listening or reading. This is called the generation effect. Students should be called upon to explain, generate and critique ideas, and we professors should curb our instincts to dominate the conversation space. This can be excruciating for those of us who have built up vast networks of knowledge in our own minds. But our job is help students learn, not to simply transmit information that they may or may not understand, retain, or know how to apply.

Exams compel students to respond and articulate, and they demand deep concentration. As such, they are instruments of active learning. Regrettably, they are used mainly for assessment. Instead of leaving students to mug up for final exams, give them weekly quizzes, with feedback, with inclusion of earlier material in later quizzes. Learning will be more meaningful and more enduring.

We come now to the most important prerequisite of learning: attention. We all know what attention is, and yet it has proven to be one of the most complex topics in the study of cognition. Attention is a special channel that processes information with a high level of acuity. We are conscious of what we attend to, and not conscious of what we do not attend to. We attend to the world outside of us when we perceive, and to the world inside of us when we think and feel. Conscious processing is just the tip of the cognitive iceberg. At any given moment, we are not conscious of most of what we know – or know how to do. We become conscious of something when a stimulus – either external or internal – grabs our attention, or when we willfully focus our attention.

The kind of knowledge we acquire in higher education requires an intense focus of attention in order to find its way into our conceptual networks. Most students find it difficult to focus their attention for the duration of a class. Attention is diverted easily by daydreaming, doodling and dawdling. It is even harder to maintain online, where social media offer endless seduction.

An effective teacher’s primary task is to get the attention of the students and to hold it -- minute after minute, class after class. Key to overcoming this challenge is to mix it up during the class. Lecture in snippets, interspersed by activities that put students’ minds at the center – activities that compel the students to ideate, cogitate, create, communicate, and collaborate. These cognitive states can be achieved by discussion, debate, problem solving, problem framing, speaking, writing, individual and small-group tutorials, and – yes – testing.