By Dennis Sale
IN previous columns on the impact of Artificial Intelligence, especially chatbots such as ChatGPT and the increasing capability for producing interactive video content, I asked if there was there now an ever-decreasing need for subject content knowledge teaching.
Certainly, AI technologies will become personal tutors for learners, both in and outside of educational institutions, and delivering factual content knowledge may become less important in the process of teaching. Instead, developing the ability to become self-directed learners as well as attaining high-level communication and collaboration competencies will increasingly come to the educational foreground, as will the capability to use emerging AI technologies.
Certainly, AI will serve up increasingly accurate, varied and customised content, but this does not ensure that students are effectively processing this “recipe” information through the psychological and neurological channels that result in deep learning and understanding in long-term memory.
At a future time, if and when all information can be directly “downloaded” in its most pristine form into our brain circuitry – then we are at the point of radical evolution, the age of the cyborg. However, in the present AI context, teachers will still have the challenging job of using these AI technologies with their teaching skills to help students build deep understanding and competence.
Understanding is about making personal meaning of knowledge and seeing how it is used in real-world applications and problem-solving. When learners have developed a good understanding of a topic, they will have acquired an organised and accurate mental representation (often referred to as schemata) of the key concepts in their minds. Once attained, understanding will facilitate effective and efficient retrieval of the relevant knowledge of the topic from long-term memory, easy explanation of what the topic is about, its key components and areas of contention, as well as its thoughtful application in real-world problem-solving.
Furthermore, with a good understanding of something, whether it’s the working of mechanical systems or human learning models, it’s then possible to use this knowledge effectively across the domain field – what is referred to as transfer of learning. Transfer facilitates accurate diagnosis of problem situations and the capability to create solutions with a high degree of outcome prediction because it means that the person fully understands the knowledge bases involved.
For myself, I have little understanding of mechanical systems; hence I am unable to fix anything mechanical. My Jack Russell dog occasionally would sit on the remote-control devices that operate the television and related systems, often resulting in picture loss on the television. It typically ends up with me ringing the technical support helpline. I don’t know what many of the various buttons on the different remote-control devices mean, what aspect of the system behaviour they control, or their relationships to each other (buttons and the different remote-control devices). In a situation of picture loss, unless it is patently obvious what has happened (eg, the on button is now off), my understanding is so limited that I am effectively taking part in a lottery where there is a low probability of success; my chances of hitting the appropriate buttons on the relevant remote-control devices in the correct sequences are not good.
Furthermore, understanding is something students can achieve themselves only through the acquisition of relevant knowledge, actively making appropriate connections between the knowledge components to build an accurate mental picture – schemata – of the intended learning goal. The rote memorisation of knowledge, while fundamentally important in effective learning, will not in itself result in understanding, as this requires the learner to actively make the mental connections and create accurate internal representations. This involves what we refer to as “thinking”. However, thinking without knowledge is of no value – try thinking about nothing. As Lang (2016) emphasises:
“One of the first and most important tasks as a teacher is to help students develop a rich body of knowledge in our content areas – without doing so we handicap considerably their ability to engage in cognitive activities like thinking and evaluating and creating. …such cognitive skills require extensive factual knowledge. We have to know things, in other words, to think critically about them. Facts are related to other facts, and the more of those relationships we can see, the more we will prove capable of critical analysis and creative thinking. Students who don’t bother to memorise anything will never get much beyond skating over the surface of a topic.”
Notions that today all we need to do to get content is to search the internet and find it, and “hey presto” we have knowledge and understanding – even expertise – is highly dubious, as Keen (2007) exposed in his book The Cult of the Amateur: How Today’s Internet is Killing our Culture. In the days when we used physical encyclopaedias, went to the library and read books, information was there, but it did not mean that we could understand it. Good teachers get superior results for a reason and, amongst other important aspects, they can identify the key concepts essential to understanding the structure of a topic area in the context of learners’ prior knowledge and experience, and then work with this for extending their learning.
Cognitive science leads to the obvious conclusion that students must learn the concepts that come up again and again – the unifying ideas of each discipline. In summary, as Resnick (1989) summarised: “Study after study shows that people who know more about a topic reason more profoundly about that topic than people who know little about it.”
What this means in practice is that the acquisition, organisation and integration of relevant knowledge bases in one’s long-term memory system are foundational to better understanding – hence learning and attainment. However, understanding is a difficult learning goal, as it involves much cognitive work – which we typically refer to as thinking. As Willingham (2009) succinctly noted: “Understanding is hard for students. After all, if understanding were easy for students, teaching would be easy for you.”
In summary, being able to identify the key concepts and principles of a subject from the mass of tertiary information flying around is surely a core principle of learning and must be a key heuristic in planning and facilitating instruction. Equally, students need to be well informed and taught how to do this effectively. Brown’s (2014) reflection is worth “reflecting upon”: “Each of us has a large basket of resources in the form of aptitudes, prior knowledge, intelligence, interests and sense of personal empowerment that shape how we learn and how we overcome our shortcomings; some of these differences matter a lot – for example, our ability to extract underlying principles from new experiences and to convert new knowledge into mental structures. Other differences we may think count for a lot, for example, having a verbal or visual learning style, actually don’t.”
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Dennis Sale worked in the Singapore education system for 25 years as adviser, researcher and examiner. He coached over 15,000 teaching professionals and provided 100-plus consultancies in the Asian region. Dennis is author of the books Creative Teachers: Self-directed Learners (Springer, 2020) and Creative Teaching: An Evidence-Based Approach (Springer, 2015). To contact Dennis, visit dennissale.com.
