More than 2300 years ago, the Chinese philosopher Confucius and his students developed what is perhaps the world’s oldest discussions on education, a collection of texts called “Xue Ji” (https://ctext.org/liji/xue-ji). Among these discussions, a simple statement was reasoned out: “teaching and learning help each other and would allow each other to grow”. Although little was said regarding the real “purpose” of teaching and learning, one may infer that Confucius probably left it out on purpose, as “teaching and learning” can really be applied towards everything. Today, “teaching and learning” is part of everyday academic life and is perhaps the most fundamental activity of education. However, I cannot help but wonder why Confucius said teaching and learning would help each other. What is it, which led Confusus to believe, that teaching and learning together form an effective integral system towards higher learning? Reflecting on myself, motivated to become a better learner (investigator of nature) and an effective future teacher, I have been trying to solve this question by reconstructing the thought process of myself “teaching” something to another person. More recently, I have been attending the Kaufman Teaching Certificate Program offered at MIT, a real opportunity for me to get a stub at this age-old problem. This essay is a result of these self-reflections as well as new ideas provoked during the class.
I’ve come to believe that the ultimate purpose of academic activity is to organize knowledge and to support the continuum discovery and incorporation of new information. Knowledge is power, and indeed much of the knowledge can be made practical into tools, machines, methods that together keep the human society function normally. Other types of knowledge, such as art, fashion, religions are used in a higher form sense, to appreciate and to feel. But all in all, the academic activity is tasked to find ways to organize: what the world is made of, how things work, facts and tables, etc., as well as to realize unknowns, uncertainties, questions and ideas that no one would know for sure. Thus the two main tasks of academia are (1) to organize and pass on existing knowledge and (2) to explore new knowledge. To pass on existing knowledge, we would need to teach. To explore new knowledge, we would need research. It appears, then, that the two domains do not really cross each other.
Wrong. In examining the syllabus that the instructor Meghan made for us, she clearly emphasized to apply latest “research on how college students learn” to instruct teaching. It appears then that we don’t really know how we actually learn yet in terms of cognitive processing. Thus, actual teaching should certainly be modified to maximize its effectiveness. This is point 1. Point 2 is that Meghan also mentioned in the syllabus “evidence-based teaching concepts”. As a scientist working in and out in the lab, I think I immediately caught what this means. It means that we are collecting some type of data during the teaching process. It makes sense, of course, to improve teaching, knowing and gaining feedback at every opportunity would be extremely helpful for fine-tuning the teaching-learning system.
So far I also learned some valuable information from the readings. For example, John Biggs wrote in “Aligning teaching for constructing learning” about the concept of “constructive alignment”, suggesting that having defined the Intended Learning Outcomes (ILOs), one should immediately formulate an assessment strategy. This assessment is then “aligned” with the ILOs, instructing how the teaching/learning activities would proceed. While I agree with Biggs on the general logic of this strategy for its effectiveness, I do not agree whole-heartedly with the philosophy. While it may work, I do not believe the goal of education is to “trap” students into a system that they “find it difficult to escape without learning appropriately”. It may work for some students, or most students. But I argue that doing so in such a “machine-like” strict program can potentially destroy the creativity of some really good students, who are motivated by curiosity rather than good grades. We then must ask ourselves, what it is that we want to produce through an education program? All of us don’t necessarily learn the same way and thus some flexibility should be allowed to appreciate the uniqueness in each individual.
The Wiggins and McTighe’s chapter “Backward Design” is a well-written text on the topic “Teachers are designers”, which I enjoyed very much. It is also a thought-provoking piece which concluded, convincingly, that the “backward design” is a superior process to craft a teaching system that would optimize learning. By starting with the goals (learner’s perspective), the ultimate output of the education, rather than inputs (teacher’s perspective), while aligning assessment, or evidence of learning with its goals, one may arrive at an optimal strategy to plan the teaching/learning activity. I also agree with the authors that the “evidence of learning” is not necessarily quiz or tests, but an overview of all the information collected. However, computationally, deriving meaningful information from this variety of data remain a challenge, in my opinion (a research topic on its own in data sciences).