The Grammar of Learning in the Digital World

‘Of all the things that count, nothing is as important as the people in the process. Whiteboards, tablets computers, apps, and other technological advances may play an important role in education, but they cannot substitute for human relationships.’
Purkey, J. Novak and J. Fretz, 2020, P16: Developing Inviting Schools: A beneficial framework for teaching and leading.

Digitisation changes everything! It's a mantra you hear a lot these days. While it may be true for certain contexts, such as the world of work and industry, it is not only inadequate for education, it is even dangerous.

The mantra fails to recognise that human evolution is not the same as technological innovation. The grammar of learning that has emerged with the development of Homo sapiens can be used to illustrate this misconception.

Interactions between the teacher and student and students with each other are paramount. Relationships are for more than learning information; self-concept develops through human interaction and feedback is essential for healthy mental development.

Putting Learning Before Technology! (Zierer, 2019) explores the use of technology in education and discusses the impact on learning. Digital media should have quantifiable value adding as evidence of impact. Without the human and the emotional connection there can be no joy in education.

Digitisation of the classroom has the potential to improve student engagement however, technology is not enough to improve learning outcomes by simply facilitating information access and collaboration.

Improving the Pedagogy is Fundamental to Inviting Student Involvement
Covid-19 lockdowns taught us a lot about learning loss and the limitations of technology. Often the rhetoric extolling the benefits of technology does not match the reality of its impact on students’ outcomes and, inexorably the data ‘talks’.

The August (2022) data from the National Assessment of Education Progress (NAEP) in the USA indicated the worst decline in mathematics and reading scores in decades. Covid-19 lockdowns showed us that many kids missed their face-to-face school interactions with peers and teachers and that technology alone could understandably, not accelerate learning outcomes.
Self-concept theory shows us that school is a place where we learn with and from others; where education is about creating a sense of belonging, establishing trust and building respect for each individual.

No AI chatbot can replace the fundamental grammar of education. In recent months issues surrounding academic plagiarism have increased with the fast-paced evolution of artificial intelligence. Some institutions are contemplating a return to supervised, pen-and-paper examinations because of text generated by chatbots.

Asynchronisation Between Humans and Technology is a Wicked Problem
From a pedagogical point of view, AI chat is Janus-faced; assuredly, it facilitates one thing or another but simultaneously deprives people of the reason and freedom at the very heart of education. Human reasoning is lost because it is easier to ask the AI chat than think for oneself, one accepts the text (the answers) provided without knowing their source or accuracy.

Freedom is lost because AI chat creates dependencies that Günther Anders (1980) pointed out with the Promethean gradient. The distance between the product world created by humans becomes greater and greater and, with it, humankind’s dependence on the product world. In the wrong hands, technologies such as AI chat can manipulate people on a massive scale.

The Importance of Thinking Fast and Slow
Daniel Kahneman's book (2011) on thinking slowly and thinking fast is helpful to contemplate when discussing technology. Metacognition, thinking about thinking, is important when overcoming cognitive bias. Refined intelligence is required to overcome the limitations of artificial intelligence as social and ethical considerations must align with human values and a sense of justice.

Authentic knowledge is instigated by one’s original experience and as Mao Zedong once said:

“If you want to know the taste of a pear, you must change the pear by eating it yourself.”

Perception rather than reality too often shapes the thinking about what constitutes the good and bad quality of teaching and learning. It is a typical example of when the data that measures impact should trump opinion. Professor John Hattie’s research shows the effect size of technology on accelerating improved educational outcomes is unremarkable at 0.24 (Hattie & Zierer, 2019). The crucial factor is how technology amplifies learning; and pedagogy is the quintessential factor in the equation.

Access to technology has an uneven distribution with affluent schools having advantage over poorer ones. Wealthy schools can afford a range of screen-technology access for students whereas poorer schools struggle to match the high-cost/low value-add investment. The opportunity cost of investment in technology in schools needs better scrutiny.

5 Principles for Digitisation
The technology does not replace the pedagogy, and five principles have emerged in the wake of the digitalisation of classrooms.

First, Learning Requires Effort and Commitment
An idea put forward is that digitisation somehow changes the learning. Hermann Ebbinghaus’ Forgetting Curve refutes this assertion. To transfer information from short-term to long-term memory takes 6-8 repetitions. Psychological research studies verify the claim. If the repetitions, effort and commitment are missing, forgetting takes its course. Hence, the moment of forgetting begins at the moment of remembering. This is independent of whether learning was analogue or digital.

Second, Learning Requires Challenges
This is a consistent message from tech companies that digitisation makes learning easier. As nice as this sounds, it is wrong; education in general, and learning in particular, is not something easy. Learning progresses via detours, wrong paths, failure and generates mistakes. In this respect, education should not be about making learning as easy as possible. It must be about making learning as challenging as possible.

The flow experience is the best empirical proof of this grammar of learning. Students reach a state of deep satisfaction when they pursue a task that challenges them. A task where the probability of success is as great as the probability of failure. The effective digitization of education is contingent on the challenge set being greater. The challenge even better with the technology than without.

If digitisation is to be effective in education, it is essential that the challenge set is harder because of it and not easier with it.

Third, Learning Requires Positive Relationships
Central to anthropology is that man needs a counterpart to recognise himself. Martin Buber (1958) says:

'Through the Thou a person becomes I.'

If this counterpart is missing, one is like Robinson Crusoe: both lonely and abandoned. One becomes a stranger to oneself and lost in a world without support and orientation. This insight has empirical proof as with the dumb-and-dumber effect. People tend to overestimate or underestimate their possibilities. Only rarely does the image one paints of oneself hit the mark. The assessment of others is important to rub up against it and to question oneself.

Students need both learning guides and the opportunity for individualised learning. Nonetheless excessive individualised learning is nonsensical. Alongside a learning guide, students need what Professor Hattie calls a change agent. This is someone who holds up a mirror, one who encourages and sets the challenge. Guides are important to foster students’ self-belief and to temper unrealistic learning expectations.

The grammar of learning includes teacher intentionality; teachers who act with a conscious and responsible will and provide offers of learning for students.

Fourth, Learning Requires Motivation
The classic discussion about the added value of digitisation in education is the thesis that the use of tablets, smartphones and the like increases motivation to learn.

Empirically, this can be illustrated nicely and confirmed at first glance. However, a second look shows that this increase in motivation decreases again after two to four weeks - at the latest when learners realise that it's all about learning after all. Hence this digitisation argument suffers from the ignorance of the grammar of learning, that learning requires motivation. But in essence and in the long run, not a motivation that lies outside of learning, but one that is directed toward the thing that needs to be learned.

Fifth, Learning Requires Surface Understanding in Order to Develop Deep Understanding
In times of Alexa and Siri, it may be indisputable to many that thanks to digitisation, people no longer need factual knowledge. Knowledge is available anytime and anywhere, so that learners can concentrate fully on competence development.

This line of reasoning fails to recognise the difference between factual knowledge and cleverness, as well as the connection between surface understanding and deep understanding, as it has always been known in didactics.

For learners to enter the realm of deep understanding, which is the goal of education as meaningful, creative, and problem-solving thinking, they must have acquired a certain amount of reproducible knowledge. Just knowing where something is and where to find a piece of information is not enough. Deep understanding develops from surface understanding. And for learners to be able to process this further, the facts must be in their heads - and not on the circuit boards of computers.

Education is about what the individual makes of oneself rather than what is 'made' of the individual by something else. Education is not as simple as programming a computer and humans are not machines.

The core message from the principles of learning is visible:

‘As long as we humans are humans, learning will remain learning.’

Digitisation will not change this and as educators we must continue to focus on the grammar of learning.

Literature
Anders, G. (1980): Die Antiquiertheit des Menschen.
Hattie, J. & Zierer, K (2019): Visible Learning Insights.
Martin, B. (1958): I and Thou.
Kahneman, D. (2011): Thinking, Fast and Slow.
Purkey, W., Novak, J.& J. Fretz, J. (2020): Developing Inviting Schools: A beneficial framework for teaching and leading.
Zierer, K. (2019): Putting Learning Before Technology!