Education and technology are in a new and often exhilarating partnership that continues to grow as new edtech players pop up around the world. But as edtech grows, it runs the risk of becoming disengaged from educators and turning a solution into a new problem.
Technology has set education on the course of its most significant experiment ever, and the results can only be seen as the experiment is carried out. This is true of adaptive learning as well as algorithm-based learning, in which an algorithm requires input to develop and implement a personalized learning plan.
Adaptive learning programs are growing in popularity in edtech and the world of educational publishing, and are aggressively overtaking assessment- and target-driven educational markets. They offer possible alternatives to other programs and materials that exponentially increase the costs of education. Adaptive learning programs are designed to address that issue. Developers often work with publishers and content creators, assessment organizations and even the educational institutions themselves.
Adaptive learning is no longer a buzzword reserved for higher education. It’s also used in the adult learning sphere, especially where languages are concerned. But the promises of adaptive learning and related learning outcome improvements are not as clear-cut as they may appear. This is because developing personalized learning plans requires ongoing on-screen engagement with educational materials, and assessments are required. But optimal learning occurs when students interact, solve problems, and debate in a collaborative environment under the supervision of and with the guidance of a teacher.
Also, in true adaptive learning environments, technology is increasingly defining how and what students learn, and identifying their academic strengths and weaknesses. Parents must carefully consider both the benefits and the drawbacks of this environment. Developing targeted education plans based on what your child already knows and doesn’t yet know may sound compelling and positive. But developing the personalized approach based on limited interactions with algorithm-fed computers is something else entirely. This is where the technology would benefit from some humanity and humility.
It’s somewhat fair to contend that adaptive learning programs tend to favor math and STEM-subjects, which fare better with algorithms than other subjects do. Languages and the humanities are gaining some traction, but continue to give the algorithm a bit of difficulty.
One final point to consider is the ethics of big data involvement in education. Among consenting adults, it’s likely not viewed as a significant problem, depending on how the data is used and potentially monetized. But what about with young children and adolescents? How do algorithms define and capture them, or even predict their futures? How is their data used? It’s certainly a significant ethical issue.
Adaptive learning programs and the technologies behind them are both fascinating and exciting. They include a cornucopia of promises and improvements in learning outcomes. More than ever, the world needs well-rounded citizens who can communicate well, apply life-skills, solve problems, and think critically, whether in academia or vocations. Algorithms are not able to develop or nurture those characteristics.