The challenge of personalised education
Taken to its ultimate end, it challenges the entire structure of the currently practised global model of education where knowledge is packaged in units to be mastered within defined, often linear, time frames in a sequential way. In this case, the measure of mastery is primarily based on accumulation of certificates of completion that are later assembled into a diploma attesting to such an accumulation.
While this has been the measure of individual achievement, one could recast this system as being one of convenience for the systems providing the education rather than one of optimum benefit for the student.
Age-defined, lock-step cohorts are easy to manage from a records-keeping perspective. Knowledge can be packaged in units that are adjusted to a student community. Progress can be measured by standardised tests and then compared across communities, locally and globally.
The packaged knowledge can be offered in defined class spaces and for agreed upon periods of time. All activities can be documented, evaluated and recorded for affirming knowledge acquisition and thus a defined competency.
Shortcomings of the standard model
There are alternative models, but these have not had widespread acceptance. The advent of the Internet and very fast, low-cost computer systems has highlighted the fact that the standard model has serious shortcomings and that the disruption of information and communications technologies, or ICT, may be demanding that small patches and modifications, such as mapping brick space education into click space, cannot withstand the competitive alternatives, such as personalised learning.
It is already clear that deep learning, neural network computers can track individuals, including their likes, proclivities and other characteristics. This is evident from search and suggest algorithms, such as those of Google and Amazon. Basically, a learner’s current capabilities and progress can be individually tracked.
This is not the faculty being displaced by artificial intelligence, at least at the present moment. Rather it points out that an entire administrative infrastructure of education institutions can essentially be significantly disrupted by such a natural evolution of artificial intelligence and affect not only what one can know about student progress but what the cost can be.
Analysis of educational systems, particularly post-secondary institutions, has shown that administrative overheads have risen significantly faster than those of instructional programmes. It has also been noted that if one can define a ‘job’ in such a manner that it can be done by artificial intelligence, or AI, then it will be.
Thus, rather than looking at AI in the educational component of an institution, one needs to understand that much of the routine ‘back office’, including individual student tracking, can be done by intelligent computer systems, therefore eliminating a significant academic overhead.
The idea of artificial intelligence in the ‘classroom’ has been the subject of both science fiction and actual fact as programmes such as Apple’s Siri can serve as a surrogate for humans providing basic or textbook knowledge.
Basic knowledge is fungible, transferable across geo/political boundaries and its cost to access is asymptomatically approaching zero whether provided by adjunct faculty or artificial intelligence that is not necessarily proximally located.
It is unfortunate that AI, in academia, has been used to address the educational component when the real and accelerating costs have been in an intellectually and administratively protected area that is most readily displaced by machine intelligence.
In the past, academic institutions have had their unique character. The move to ’harmonise’ knowledge across the European Union and the similar effort to ‘tune’ institutional curricula in Africa admits to the idea of basic knowledge’s ubiquity and thus expectations of similar core knowledge being shared across geo/political boundaries.
This makes it imperative that institutions seek to find their unique personalities and areas of differentiation. This has significant ramifications for the role of institutions and the faculty who inhabit their physical and virtual spaces.
Personalised knowledge and the individual
We have known that individuals mature at different rates, both physically and mentally, yet we conveniently divide students by age for entering and proceeding through the education system. The reasons are complex and overlaid with cultural and political issues.
Until recently, with the arrival of artificial intelligent systems, it has been difficult to identify and respond fully to the needs of the student as an individual. The cultural impacts are potentially significant, even in societies such as North America and Europe, and it might not be possible at the pre-kindergarten to secondary school level, though the concept of ‘badging’ for certifying individual mastery of certain skills may be a first move in this direction.
The problems in the current system become evident when students graduate to a post-secondary institution. Even though the school system is designed as a lock-step, age-defined, cohort programme, students, even from the same institutions, are arriving at the end differentiated by mastery of even basic skills such as reading, writing and mathematics. The efforts to try to bring all students to a similar level points out the impossibility of this system and the need to consider allowing the fixed system to open up to allow for individual skills to develop.
Neal Stephenson in his prescient novel, The Diamond Age, imagines such a possibility existing, but even he chooses not to deal with the larger social or cultural issues of an increasingly global and complex cultural milieu confronting even societies that are relatively homogeneous.
While we would like to see education being continuous and lifelong, today there is a leap from the basic primary and secondary system to the post-secondary world. And while we would like the basic introductory English class to have some equivalency across programmes, we know that not only are there content differences but also the demand level and expectations of the various institutions differ substantively.
Admissions policies also reflect that the differential among students that is evident at the end of secondary schools becomes amplified in the post-secondary world.
The growing capabilities of artificial intelligence make clear the importance of addressing the possibilities of personalised education.
Personalised education: the institutional level
Education has always involved a combination of self-directed learning and an awareness and knowledge gained from individuals with greater knowledge and experience. As societies developed, learning from such masters became institutionalised in various ways. Much of this learning was transmitted orally and then through various media, from writing to today’s digital communication systems that enlarge the resource base and elevate it to a global level.
The avoided issue is the cost of a hand-crafted, individually curated learning experience, at least for the acquisition of basic skills and core knowledge which is increasingly accessible in an interconnected, global society. As the cost of ICT becomes smaller and cheaper, individuals can walk around with access to this knowledge world in their pockets.
This is becoming increasingly evident, particularly at the post-secondary level, and particularly in the United States, where the value of a faculty member responsible for delivering this basic knowledge is continually being devalued both in terms of the level of the faculty being hired to deliver it and their compensation.
While there is a movement to more adequately compensate these individuals, it is being done within the context of maintaining the current educational model. This model, in part, is the result of the desire for institutions to acquire research scholars, many of whom become dependent on the maintenance of the current system. It’s a model that is designed to perpetuate itself.
A critical analysis by writer Brian Marsh points to the fact that, with the exception of selected institutions in the developing economies, the need for individuals with advanced degrees can be defined by the ratio of 7:2:1 where the '1’ is a PhD or equivalent, '2’ is for masters prepared or advanced bachelor degree and the '7’ are individuals with a variety of post-secondary degrees or certificates.
The author Upton Sinclair wrote: "It's difficult to get a man to understand something if his salary depends upon his not understanding it."
Universities and those who inhabit the Ivory Tower are caught in this self-evident idea, one that has been articulated differently by Harvard Business School Professor Clayton Christensen in his writings on disruptive innovation. The confluence of increasingly capable AI coupled with the emergence of the idea of competency-based education and personalised programmes of learning has “called the question”. The entire administrative structure that has grown up almost unquestioningly now needs to be re-examined.
Additionally, it is becoming clear that the basic differences between the pre-K-12 system and the post-secondary world, is an artificial construct when examined under the emergent competency-based, personalised knowledge acquisition system.
Personalised education – including competency-based and similar complementary systems – points to a significant challenge to the standard pre-K-12 models that are increasingly failing to maintain their cohort system. This is even more evident in the post-secondary institutions as increasing costs and expanded opportunities are challenging the packaged four-year diploma model, a continuation of the pre-K-12 system.
The challenge becomes amplified in a global society connected increasingly by high-speed electronic networks and access to increasingly large, low-cost sources of basic and even specialised knowledge.
Coupled with advancing artificial intelligence systems, much of the cost for higher education institutions’ overheads can be significantly reduced. Additionally, for basic knowledge, much can be provided by the advancing artificial intelligence system.
This significantly changes the role and function of traditional academics as both teachers and researchers. It also challenges the mix of academic personnel both within and outside of the Ivory Tower.
Tom P Abeles is president of consultancy firm Sagacity Inc and can be contacted on: firstname.lastname@example.org.