Can Technology Fix Personalized Learning?


This article is part of a series on personalized learning (part 2 of 6).

Educational professor Dr. Don Ely once famously asked: “If technology is the answer, what is the question?”  With renewed interest in personalized learning, we should be cautious of the techno-centric tendency. In China, billions of dollars are being pumped into various online learning platforms and providers, but most of such effort only creates online mirror images of the classrooms, with little to no change in learner goals, interests, paths and assessments. The investment will eventually lead to educational bubbles, as long as it is a game played by venture capitalists, leaving out key stakeholders in education: teachers, students, parents and the broader community.

Technology giants are also not the only ones showing an interest in promoting personalized learning. Other than people like Mark Zuckerberg and Bill Gates, cognitive scientists and social psychologists are also interested in playing roles in the advance towards personalized learning. Howard Gardner, who invented the framework about multiple intelligences, wrote for Washignton Post that personalized learning should involve a redesign of learning. He wrote about four "primers" to get people ready for a more fruitful discussion of personalized learning: "a single learning path" with varied paths, "favored content", "different learning styles", which he shows doubt about, and "different intelligences". Gardner has extended the personalized learning discussion beyond the technology realm by adding a psychology dimension.

Obviously technology is not the whole answer, it can play a major role, if used wisely. I think technology presents three horizons of utility for learners and educators. 

Abundance: Technology is presenting to learners abundant learning resources. One can access the best of lectures or learning objects from around the world. Unfortunately I found that students are vastly different in their ability consume such abundance, relying instead of teachers to tell them what to read, write or do. In 1993, James Gleick wrote for New York Times Magazine: “An ocean of data is sloshing around out there, and most of us are trying to sip it through a very narrow straw.”

Analytics: Technology is also giving teachers insights into students’ behaviors (if not minds) by having data for analysis. Teachers can now track the learner footprints through the use of access or interaction data. Such data create profile for individual learners. Data can also be ranked and filtered to divide students into clusters, for instance, clusters of students who have not completed a certain assignment, or students who may have missed certain pages. Teachers can apply intervention before it is too late when such patterns are discerned.

Adaptability: While students learn from teachers, teachers can also make their courses learn about their students, just as text-to-speech programs can learn and memorize users’ speech patterns. Sophisticated algorithm is an approach to accomplish this kind of learning. Lower-tech methods such as selective release of content based on test results should also do the trick. Beware, however, of possible bias in using technology alone for learner adaptability. Graham Brown-martin from Learning Without Borders expressed a similar concern in his 2014 Keynote speech for WISE. He is apprehensive of the algorithm biases that may become counterproductive if we put technology in the driver's seat. In my line of work, I find that people either refrain from using technology, or using technology for everything, when a simple written note or announcement is equally effective as a complex, intelligent program.

I hope we have passed the stage to argue whether or not to use technology in teaching. This argument of technology-no technology is dual, not reflecting the complex realities we now live in. Instead, most educators are operating anywhere on a continuum of technology integration in which humans always play vital roles. Both teachers and students should learn to be literate in technology tools in order to succeed in giving or getting personalized learning. Otherwise, what is the use of abundance when learners are waiting for the “right” choice?  What is the use of analytics, if they are gathered by machines and ignored by humans? What is the use of adaptability if pathways are created and people always get into various detours?

Learning (Blended, Personalized, Formal, Informal), Education Technology, Future of Education, Big Data

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