Although the learner-centered bandwagon has been with us for quite a while, there are three main reasons why this teaching strategy should undergo a reanalysis and re-thinking, providing the future will still entertain the idea of human-to-human formal teaching and learning.
- Learner-centered approaches do not let learners get out of their comfort zones both from the perspective of content and that of learning styles.
- Learner-centered approaches do not let learners stretch their imagination and do not open their eyes to what’s beyond their horizon.
- Learner-centered approaches end up with learners who are reaffirmed in their world view without an ability to pose probing questions about their own perspective.
It is instructive to view learner-centered pedagogy as a stepping-stone to machine teaching, big data algorithms, and a sedate, hedonistic citizenry. One of the fall-outs of learner-centered teaching has been the unceasing lack of abilities to ask probing questions about even the most frequent and matter-of-fact developments. Students who major in sciences are dashing headlong to innovate, technologize everything, seemingly without thinking about the real reasons for innovations, and technological breakthroughs. Distractions, rather than focus, tend to be created: “immersive computing” is a perfect illustration of this tendency. Why do we need immersive gadgets? What will be they good for? Are they just another means to create trash (both real and metaphorical)? These questions do not even touch the surface of the technological developments written about in “Google has a new favorite phrase” .
Media algorithms are another result of the drive to a “learner-centered” world. My computer informs me of newly-published articles about topics which according to the algorithm, I was interested in previously. But my interests are not circumscribed to those topics, far from it! The algorithm’s limiting abilities to really find out where all my interests reside is appallingly myopic. Since the digital technology satisfies the supposedly personal interest, it may be more useful for schools to actually bring previously unseen topics to the classrooms. It may be important for the machine-learning computer designers to know that learning is subconscious: Is Language Learning A Subconscious Process?.
In conclusion, if the world needs engaged and concerned citizenry, learner-centered pedagogy is not the way to proceed. Computers can deliver massive amounts of data on any given topic of personal interest, but human teachers can do much more than that: they can expand learners’ interests to where they have not even imagined to wonder/wander and nudge them to comparison, analyses, syntheses of topics hereto not encountered.