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The Day Education Technology Died

Science-fiction author Arthur C. Clarke’s Third Law states that any sufficiently advanced technology is indistinguishable from magic. Clarke’s law touches precisely on a sentiment present within modern society. We expect that new technology will work wonders, provide us with superpowers, and give us that same frisson reserved for magic. Clarke formulated his law many decades before the dizzying age in which we live, an age that makes us expect such magical innovations at a rate of one every few weeks. However, it is more than six decades of the realization of an intuition that it is possible to sprinkle the magic dust of technology on an educational world normally associated with less sparkling connotations. On the surface, the combination of technology and education has great potential to provide answers to some of educational challenges, and this potential did not escape the eyes of scientists, educators and entrepreneurs. However, technology has been able to meet such expectations in areas such as communication, advertising, transportation, health, and so on, but not in education.

The unsuccessful journey toward technological magic could be described as beginning in a spacious classroom, one in which all of the students wore a uniform “short-back-and-sides” haircut. The students, with serious visage, sit in pairs in front of small tables. In front of each student is a machine that takes up most of the table. The machine is new; it is both mysterious and prestigious in appearance, and carries with it the aroma of newness. The children are attentive, active, and highly motivated. They write their answers into the machine and receive immediate feedback. A tall, bespectacled man, with the air of a researcher, walks around among the students. This man, B.F. Skinner, one of the founders of modern psychology, is in the classroom to demonstrate his teaching machine before the cameras. Skinner’s machine allows each student to learn on their own, progressing at their own pace. The machine was presented as a way of coping with the problem of the heterogeneous classroom, and the challenge of motivating students. It is easy to find this 1957 film on YouTube. The gap between the educational technology presented in that clip, and what we today call educational technology, is comparable to the gap between the silent movies of the early twentieth century and the cinema of the Netflix era. Nonetheless, and in spite of countless relevant developments, Skinner not only created one of the first solutions in the field, but also set the tone for the solutions that followed him. The promise of the machine is that a student goes in on one side not knowing, and comes out educated at the other end. The machine aspires to be a kind of magic solution that saves the teacher time to deal with more important issues. Many solutions in the world of educational technology, perhaps most of them, have made similar promises – saving teacher time and covering a significant part of the teaching process.

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What Does Educational Technology Do?

The Skinner paradigm’s answer to the question “What does educational technology do?” – helps us educate just as we have always done, but more efficiently. Such an answer is relevant as long as our learning framework exists without technology, and where technology is a kind of external add-on that we can add, or not add, as we choose. However, in the present age, technology has moved from a tiny corner on the periphery of learning, and has taken center stage. In today’s world, all stakeholders – students, parents and teachers – have come to live and operate within the internet realm. Each of them conducts a significant portion of their interpersonal communications through technological means, belongs to virtual communities, learns from YouTubers. Each of the stakeholders makes their decisions primarily on information that is accessible in the palm of their hand, and acquires skills through video games. In such a world, technology is the space, the environment, in which we operate, as well as also being the medium. Whether we like it or not, technology is redefining the whole of the learning setting – the library, the textbook, the classroom and the teacher: all of them take on new significance in the information era. In an era, such as this, there is no real justification for a defined sphere named “educational technology”; its interactive content is not substantially different from other interactive content that we encounter in social networks, digital games or in current affairs websites. There is the collection of data, but this does not have to differ from the collection of data on any other platform trying to optimize its outcomes. The difference between educational platforms and other platforms is becoming more akin to the difference between a textbook and any other book – just like a textbook, platforms are educational because they are intended to teach us something, they are directed at an audience in a particular age range, and they maintain certain ethic limitations that other platforms are not obligated by. Educational technology in the old sense is dead, because of – or thanks to – the success of the technological revolution that has overtaken mankind.

The Skinner Spell

Skinner’s learning machines not only defined the boundaries of educational technology, but also presented an in-built pedagogic conception. Some would describe the pedagogic influence of Skinner’s learning machines as the “Skinner Spell,” a kind of magic spell cast over the field and which influenced it dramatically, but which extracted from it a very high pedagogic price. Skinner’s learning machines offer a paradigm that has seven characteristics which are, to a large extent, still as true today as they were in Skinner’s days.

Alone: The proposed solution is aimed at the individual learner, located in the classroom but progressing at his own pace. This is an arena in which the student sits alone in front of the machine, generally without any social or communal interaction with other learners.

Savings: The machine’s great promise is at savings in work – it substitutes the teacher in practice and review, in setting and checking assignments, and in individual communication with each student. The teacher’s time can be devoted to what is really important – speaking to the group as a whole.

Aid: The technology is an aid to maintaining the routine of the classroom. It does not offer alternatives to existing structures or modes of learning, it makes them more efficient.

Choice: The backbone of these machines is multiple choice tasks that require the learner to make choices. These tasks may be packaged in a shiny wrapper, in a game or story framework, but it comes down to choosing the right answer from a number of options which enable immediate feedback, and are easy to implement – whether with the technology of the fifties or with the technology of the 21^st century.

Linearity: Progress in learning is linear. The student cannot progress to the next stage before demonstrating understanding of the present stage. Learning is rigid and unidimensional – one proceeds along a single, pre-defined axis.

Immediacy: The system is reactive, and accustoms the learner to a high level of reactivity – he gives an answer and knows immediately if it is right or wrong.

Behaviorism: These systems operate under the assumptions of behavioristic psychology, of which Skinner was one of the founders. Under this approach, stimulus and response play an important role in learning. The system creates a stimulus – asks a question, the student responds – answers the question, and the system responds providing him with positive reinforcement or a negative signal. The motive force of the learning process is positive reinforcement, which generates motivation in the learner to act so as to obtain further reinforcement. Such a mechanism works well with pigeons, with mice, and with students as well.

It is not for nothing that the educational paradigm of Skinner’s machines has survived for so long. Skinner, one of the intellectual giants of the 20^th century, had a broad vision and world view, combined with a pragmatic, results-oriented approach. His machine relies on a systematic educational philosophy based on a well-reasoned psychological view of the world, one that had been successfully tested in a variety of contexts. However, the vision that aspired to open new pedagogic horizons with infinite reach, and to create personalization, emotional connection and flexibility, did not achieve its promise. Instead, it created a narrow, linear passageway, one that invites the learner to sisyphically work their way along it, on their own, using a very limited range of actions. This is years away from the magic that we are looking for in technology.

When the Dinosaur Cried

Our entry into an age in which technology surrounds us on all sides has brought about another dramatic change. “Technology” has ceased to serve solely as a tool that we use, or as a device that we hold – we have moved from a world of using tools to one in which we have a relationship with the tools. This revolution may be demonstrated when we think about Pleo. Pleo is a cute little dinosaur, crawling across the floor, along comes someone who picks him up by the tail. Paleo cries and squirms helplessly, begging for his life. Pleo is a robot, a machine, and yet we do not remain indifferent to his behavior. Kate Darling, a researcher at MIT, asked a group of subjects to kill dinosaurs such as Pleo, giving them all sorts of justifications. Even though the participants knew that these were merely machines, all of them categorically refused to do so. In another experiment, investigators at Stanford shows that research subjects felt embarrassment when asked to touch intimate areas on the body of a robot. A variety of similar studies shows that we relate with empathy to machines with human characteristics, even when those characteristics are partial at best. An empathic response occurs not only when we are talking about robots that simulate humans or animals, such as Pleo, but even when we are talking about robots used to remove bombs, domestic vacuum cleaners, or mechanical cockroaches. Robots offer a good way of clarifying this point, but we are not talking of some futuristic story along the lines of Westworld. Today we already have daily relationships and complex interactions with devices such as our telephones, with voice assistants such as Alexa, and a variety of software. We live in an environment in which, along with human beings and animals, there are also smart machines.

Invisible Interfaces

The more we become immersed in these relationships, the easier it is for us to forget that, behind all of this interaction, there is a person who intentionally designed it, who wrote the underlying program, and who specified the interface through which we operate the machine. The better the interface design, the less we feel its presence. The machines of a previous generation required handles and buttons to operate them. As technology progressed, the interfaces through which we operated the machines came to take up a much smaller volume – first we moved to the keyboard, and then to graphic interfaces. Today we activate a significant portion of the interface simply by moving from one place to the other, with a sensor translating that movement into a request or command. Or, we can say something, and a voice sensor translates our speech into a task. Greater efficiency in the interface makes our use of technology natural and smoother, but it creates a challenge to our ability to understand the world that we are using. The world in which we operate takes on a perfect stage performance, in which we forget that there also exists a world behind the scenes of the stage on which we act. This obliviousness creates dangers and challenges. First, we become more vulnerable and exposed to manipulation or to malicious use of technology. A range of malicious web phenomena, ranging from viruses to fake news, flourishes in a world whose functioning and motivations we do not understand. Apart from the immediate dangers, an experience that is powerful on the one hand and yet smooth and natural on the other, leads us to take the mechanisms that serve us for granted, without pausing for a moment to understand how they operate, what their limitations are, and how we can obtain more from them.

New Knowledge Domains

In order to cope with these challenges, we need to learn about new knowledge domains that did not exist in the past, and that will enable us to be active, aware and watchful users of the new universe taking shape before our eyes.These may be divided into four main categories:

Understanding: The mode of operation of the machines that surround us, is different from human modes of operation. In certain areas the performance of these machines exceeds that of human beings, while in other areas they lag behind. In order to understand these machines, and the deep level on which they operate, we need to learn the fundamentals of machine logic, the way in which complex systems behave, and basic concepts such as “variable” or “loop” – areas under computational thinking. If computational thinking gives us an understanding of the operation of smart machines, data literacy provides us with an infrastructure to function in a world in which data plays a decisive role. Data literacy helps us understand how to explore and represent data, build an argument, and hoe these representations influence our conclusions.

Communication: In order to operate in a technology-oriented world we need to understand how to communicate with machines, and more importantly, how to communicate with other people whom we meet through internet. Subjects such as new media expand our expressive horizons through tools such as video or infographics. Media literacy assists us in reading between the lines, and in distinguishing between well-founded information and “fake news.” And exposure to e-activism encourages use to be active, smart citizens of cyberspace.

Defense: A technology-based environment is also one that faces many threats. The first of these threats include viruses, ransomware and malware. The knowledge domain relating to this area is cyber studies – from general cyber literacy to professional training in cyber professions.

Creativity: The fourth, and most important, side of this framework is the one that ensures that all of us can be partners in this space, not only on the user side but also on the creator side. In this area we encounter, of course, the field of programming, but also such fields as design thinking, and user experience design.

Human Machine Pedagogy

These subject areas are not just additional knowledge domains to subjects such as language or physics, but they require a formulation of a new pedagogy, and different management from those customary in the disciplines with which we are familiar. These fields have four characteristics that require a different kind of readiness on our part:

Corpus – In these domains, a significant portion of the content is constantly changing. In cyber, for example, we talk of replacing about 30% of the material studied each year. This highly dynamic situation requires flexibility and independent learning ability on the part of all those concerned.
Teaching – Assuming that these domains are studied on a system level, and not as ad-on, those who will need to transmit them are the teachers already in the system, many of whom lack the professional background required for these knowledge areas. These teachers will need to use relevant content specialists (virtual teachers, for example) to bridge these gaps. However, the fact that they do not need to be busy with content, will enable them to focus more on pedagogical, emotional and social aspects, as well as broader aspects such as the ethical effects of these technologies.
Performance – It is difficult, perhaps impossible, to learn these topics passively, by only reading or listening. Each of these areas has a significant practical side, which can only be learned through doing/ performing an action.
Multidisciplinary – Each of these fields touches on a broad range of areas, and all together create a combination that is not easily classified – these domains involve aspects of exact sciences, of engineering, of humanities, social sciences, and arts.

These unique characteristics also create an extraordinary opportunity. In a perfect world, we would be happy to also see traditional disciplines, such as mathematics or language, taught with flexibility, interactivity and wide-ranging learning. Human Machine Pedagogy and the tools to support it, may be a new opportunity for realizing the potential of the encounter between the magic of innovative technology and the challenges of the world of education.

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