Why Technology is Not Going to Transform Higher Education
“As universities develop their own digital competencies, what started as a short-term response to a crisis will likely become an enduring digital transformation of higher education.” —
The idea that technology can be the basis of disruptive innovation owes a lot to the thinking of Clayton Christensen, a Harvard business school professor who worked extensively to better understand the nature of innovation as a socio-economic process. His key idea was simple:
“An innovation that is disruptive allows a whole new population of consumers at the bottom of a market access to a product or service that was historically only accessible to consumers with a lot of money or a lot of skill. Characteristics of disruptive businesses, at least in their initial stages, can include: lower gross margins, smaller target markets, and simpler products and services that may not appear as attractive as existing solutions when compared against traditional performance metrics. Because these lower tiers of the market offer lower gross margins, they are unattractive to other firms moving upward in the market, creating space at the bottom of the market for new disruptive competitors to emerge.”
Examples of this kind of disruption include Netflix, Expedia, Amazon, Apple Music and Airbnb. The suggestion is that companies like Zoom, Coursera and larger players like Google, Apple and Microsoft and their educational software can disrupt the provision of education because they can achieve scale at a low marginal cost.
The key here is scale. The transformation agenda is based on the idea that higher education is “broken” and can only be “fixed” through technology, replacing local classes and local instructors with master classes taught by leading experts who are supported by technology.
They look not to Harvard or MIT as models, but to Amazon, Netflix and AI-enabled chatbots to replace teachers. The idea is to achieve scale supported by AI-enabled and marked assessment. A class of 100 is too small; 10,000 would be better.
The problems the transformation pioneers are trying to fix are also clear. The human costs of delivering face-to-face instruction are high and growing, and the quality of instruction varies from great to good to mediocre. Given the growing costs of higher education, access to quality learning is restricted by price and location. Technology-enabled online learning lowers the per-student costs, increases access and can enable a higher degree of quality control.
Why Technology Will Not Transform Higher Education
There are five reasons technology will not transform higher education.
1. Misunderstanding the purpose of learning
The notion that technology will transform colleges and universities is based on a misunderstanding of the purpose of learning.
In higher education, learning is about more than being able to recall information. It is about engaging in the creative and social use of knowledge and nurturing lifelong inquiry. Cardinal John Henry Newman, the first English saint of the modern age, said of universityan academical system without the personal influence of teachers upon pupils, is an arctic winter; it will create an ice-bound, petrified, cast-iron University, and nothing else." He saw university as a place of intellectual engagement, where professors explored the frontiers of knowledge and understanding and shared their learning with students to engender a sense of meaning and purpose to their pursuit of knowledge and understanding. He felt students should leave university able "to think and to reason and to compare and to discriminate and to analyze.”
The adaptive learning engines built into contemporary learning management systems are not that different from Sidney Pressey’s teaching machine from 1924, but more sophisticated. They permit students to receive additional instruction based on scores on a quiz or their response to a challenge. With the addition of chatbots providing instant “personalized” feedback, there is the sense that “someone is in the machine,” but the model of learning is limited. As Canadian educator and scholar Phil McRae observes, this is a misunderstanding of what learning is for:
“Adaptive learning systems (the new teaching machines) do not build more resilient, creative, entrepreneurial or empathetic citizens through their individualized, linear and mechanical software algorithms. Nor do they balance the desire for greater choice, in all its manifest forms, with the equity needed for a society to flourish. Computer adaptive learning systems are reductionist and primarily attend to those things that can be easily digitized and tested. They fail to recognize that high quality learning environments are deeply relational, humanistic, creative, socially constructed, active and inquiry-oriented.”
Bill Rankin, an innovative learning designer, also refers to this misunderstanding about the purpose of learning in his provocative article, Education is Over. He notes that the promise of ed-tech transformation is based on a lie — information is the most important education component — and the learner’s ask is to demonstrate mastery and ability to remember and use information. Rankin is reinforcing McRae’s point: higher education is about discovery, exploration, creation, engagement and community.
2. Personalization, isolation and depersonalization
The second reason technology won’t transform higher education relates to the idea of “personalization,” which in fact means depersonalization.
Vendors and advocates of technology-based learning use an intense focus on information mastery — what Rankin calls “instructionism” — to suggest education can be personalized through the use of responsive algorithms, adaptive engines and empathic artificial intelligence. They suggest that reducing learning to components or learning objects and using technology to provide these learning objects, students can learn content and develop skills independently of both context and a teacher. The social, collective and interactive nature of education is replaced by an ambiguous construct called “personalized learning,” meaning a learning system responds to tests taken by the learner and rearranges the sequence of learning activities until the learner scores a specific score on a competency test. Some call this “learnification” placing the learner at the centre of everything we do. Others would call this depersonalization and isolated learning.
Some organizations are dedicated to delivering this kind of intense learning “mastery” through individual instruction. In China, a company called Squirrel uses AI and chatbot tutors to teach a curriculum. Valued at $1 billion, it is among the fastest-growing companies in China, with 2,000 learning centres in 200 cities, more than 1 million registered students, and plans to expand to 2,000 more centres domestically within a year and then to operate globally. A variety of similar systems are emerging in North America.
At Squirrel, a high school math course is broken down into 1,000 “components.” Students master each component, are assessed and then move on to the next component. Meaning, purpose, context and relationships are non-existent in this student-machine-test interface. It is more like a system of banking learning outcomes than authentic learning that can transform a learner’s life.
The de-personalization and isolation of the learner is an essential feature of achieving scale. If 10,000 students take a course, how can the experience be personalized and engaging? There is a danger that the loneliness of the long-distance learner becomes an accepted feature of the transformation agenda, and that the community of inquiry on which college and university programs are based gets lost in the rush to scale.
3. Teaching is what colleges and universities are all about
The third reason technology won’t transform higher education is that it fails to fully understand the work teachers do.
In an important book, The Rediscovery of Teaching (2017), Gert Biesta suggests teachers make a substantial difference to the experience of education and can shape students’ understanding of knowledge and the nature of the world. He argues against a “banking” model of learning, instead favouring collective engagement in learning directed and shaped by a teacher.
According to Biesta, it’s important to understand that in the banking model of education the student can only appear as object of the teacher’s actions, not as a subject in his or her own right. Teaching is then seen as a form of control aimed at the effective production of pre-specified learning outcomes easily delivered by technology. The teacher is reduced to the role of “outcome manager” rather than inspirer, challenger, coach, enabler of insights, imagineer, thought guide, network connector.
He argues that the teacher can enable the discovery of students’ creative energies and capacities, and can make connections to people, ideas, resources and opportunities that even the smartest technologies can’t. Indeed, Biesta suggests that the teacher in higher education is a vehicle of emancipation and reimagination of citizenship and a creative talent. Although this can occur in an online space, teaching presence and student presence together with cognitive presence must be design features of that learning. For many online and technology solutions, it is not.
4. Costs, quality and the experience of learning
The fourth argument rejects the claim that technology lowers cost of higher education.
The claim is that the most significant costs — of instruction, management and space — can be “transformed” by the adoption of technology-enabled learning without the quality of learning outcomes being impacted. These claims depend on three assumptions:
- That higher education can be reduced to a transactional agenda (the banking model of learning) with inputs (instruction by means of digital resources), outputs (assessments) and traceability (analytics)
- That these processes can be automated, with fewer people costs
- That quality is about outcomes, not the experience of learning, and that outcomes aren’t impacted by the transformation
In this mindset, augmented and virtual reality and artificial intelligence will gradually replace teachers and learning will take place anytime, anywhere. Collaborations can be a part of the “designed” experience, but the key is to produce students who have attested knowledge and competencies. Students still relate to knowledge (content) and to each other (social media) and an expert (AI chatbot tutors and some instructors) but can master the knowledge and skills on demand. Uber comes to college.
The first challenge to this position is that this is not what most students want. They want a collective, collaborative, engaged experience of campus and learning. They see learning as relational, recursive, socially constructed and life-changing. They value the social networks created just as much as the knowledge mastered and skills gained. They do not buy the impoverished view of what higher education could be if transformed by technology. They do see technology playing a role, but not as a basis for ending their experiential learning.
Although some students simply want to credential — and the “banking” model of instruction using technology suits them— they willingly sacrifice the creative opportunities afforded by peer interaction, group projects and related activities so as to get to the credential faster. Others never get to the credential, but have great experiences that can’t be replicated online.
The second challenge is that the evidence that technology enabled learning is “cheaper” only applies when we cast away the existing structures of higher education: classes, teacher-to-student ratios, teaching hours, buildings and decision-making. Unbundling services within the college or university and re-imagining the work at scale are essential to cost reduction. Bolting technology on to the current infrastructure and expecting it to lower costs will not work and may in fact increase costs significantly.
The third challenge is the idea that learning outcomes are not impacted by whether learning takes place in class or online. This thinking is based on the substantial evidence that there is no significant difference in test scores based on mode of delivery. That is, if we reduce the purpose of learning to test scores, then it makes no difference how students acquire the knowledge being tested. But if learning is about exploration, engagement with peers in the pursuit of ideas, creativity and developing a passion or responding to a challenge, then we do not have the evidence that online learning is as good or better than shared in-person experiences.
At stake here is the reduction of the value of education to what can be measured and costed. This is especially evident when we look at issues like the role of the college or university education process related to social justice, equity or race. Not everything that matters in the process of learning is or can be easily measured. Just because something can be measured does not make it the key outcome of higher education.
5. Technology offers a fix for the wrong problem
The final reason technology won’t transform higher education is that it is focused on the wrong problem.
The key challenge is making college and university accessible and relevant to more people who are normally denied access and who, when given access, often are not successful.
Technology can magnify socioeconomic disparities and enshrine inequalities. Massive Open Online Courses (MOOCs) are a good example: more middle-class and moderately to highly successful people study MOOCs than lower-income young adults. Despite the massive expansion of higher education around the world, inequality persists and is reinforced by the way higher education functions, according to author Thomas Piketty and many others.
One simple indicator is helpful: the probability of a student taking a college or university program based on whether their parents did. In the US, students whose parents hold a degree are 6.8 times more likely to seek a degree in college or university than those whose parents do not have a degree. Canada is only slightly different, with just 20% of students at an Ontario college or university being first-generation students.
Another indicator of inequality is the proportion of Canada’s Indigenous population enrolled in higher education. In 1981, just 2% of adults who identified as Indigenous held a degree; by 2006 this had risen to 7.7%. For non-Indigenous Canadians, the figure was 8.1% in 1981and 23.4% in 2006. Among Indigenous people aged 25 to 64, 28.9% had no certificate, diploma or degree; the figure for non-Indigenous people in the same age group was 12.1%.
The key issues are affordability and access. Since the 1990s, governments in Canada and elsewhere have reduced their investment in public education, both per capita and as a percentage of university and college overall funding. As a result, students must cover more of the costs of their own education. Between 1996 and 2016, Canadian student tuition fees rose 40%. But as costs rise, fewer students from low-income families, single parents and Indigenous learners can afford to attend. Since online learning costs the same as face-to-face tuition, the format makes no difference to the cost of access. While online learning is the only way many can access programs and courses from remote or rural locations or when balancing work and family, the cost of doing so continues to rise.
About 20% of Canadians live in remote or rural communities. For them, access and affordability of higher education is a challenge. About 10% of households — mostly in rural areas — lack reliable broadband Internet, and 60% lack download speeds suitable for streaming. Indigenous students are over-represented in these categories, especially those living on reserves.
Income in rural and remote areas is lower than in urban areas by 14%. About one in four lower-income Canadian households use smartphones as their primary Internet access. Until affordable broadband access is seen as a human right — as it is in Finland, Cost Rica, Spain and several other countries — and until instructional design becomes embedded in how we think about all teaching and learning, people in these communities will continue to face access and learning challenges.
For students with accessibility concerns, technology-based learning poses new challenges, despite the steps taken by colleges and universities to meet their special needs. Significant advances have helped ensure accessibility of online courses following the principles of universal design and the widespread adoption of best practices to meet the special needs of teachers and learners.
But technology adds costs, complexity and challenges to the already difficult problem of access to higher education for low-income families. Rather than making access more affordable, it makes it more difficult.
What Technology Will Change
Technology-enabled learning will develop and grow. It will become a feature of all learning in classrooms, in blended and “flipped” environments and in fully online programs. The key point is that it won’t transform higher education in the way some commentators are suggesting. Instead, it will enhance effective teaching.
There are six key ways in which technology will enhance teaching and learning in higher education:
- It will create more opportunities for students to find, connect to and create content. Content is ubiquitous. Students can use technology to find the version of content that works for them and helps them understand and apply knowledge. Faculty will spend less time creating or curating content and more time developing the relationships with students that make learning powerful. They can also spend time connecting learning to the real-world challenges that make that learning authentic.
- It will create more opportunities for students who are struggling to master a body of knowledge, develop a skill or enhance a capability. Despite their limitations, adaptive learning engines assisted by AI can help some students master a skill or better understand a complex idea and provide opportunities for the safe exploration and practice of that skill. One example is the use of augmented and virtual reality simulations. AI chatbot-tutors can provide coaching and guidance 24x7, and these resources will simply get better over time. Compared to the level of interaction between a faculty member and a student in a face-to-face class, these chatbots will be a significant enhancement to the learning experience.
- It will enable more connections with others around the world. Technology will enhance connections to people studying the same things in different places, to experts and to practitioners no matter where in the world they may be. A class in a remote community can connect to learners in South Africa and experts in Venezuela all at the touch of a button.
- It will permit faster connection to support services within our colleges and universities. Whether these are career counsellors, psychological counsellors, writing or math coaches, librarians, study skills strategists, librarians or others who provide outstanding services, students will benefit from faster connections the pandemic has highlighted the emergence of shared services across institutions to enable more frequent connections and a wider range of services.
- It will enable greater flexibility in terms of the “offer” to students. On demand learning will grow, especially as micro-credentials and modular, stackable learning begin to form key parts of the “offer” from colleges and universities. Greater flexibility in the duration of learning, modes of learning and location of learning will allow students to mix and match how and what they learn based on their personal circumstances. Learner mobility is a feature of this future, making transfer of learning an urgent policy priority.
- It will create new ways in which people and technology can combine to create powerful, authentic, memorable learning. New simulations, serious games, immersive learning, visual exploration, AI-enabled conversations, new uses for “smart glasses” in location-based learning, new devices for learning, instant translation — all are emerging technologies that will support powerful learning.
Rather than spending valuable investor capital on start-ups that promise to transform higher education, technology vendors who engage in genuine partnerships with teachers and students to improve the learning experience, connect learning to real-world challenges and support effective teaching are more likely to find success.
Investing in creative instructional design supports, enhanced access to open education resources (especially simulations, serious games and online laboratories) are all better uses of available capital. Enhancing good teaching and enabling memorable learning is where the future of technology lies.