Skip to main content

Research on Habits and Homework vs. Practice (Part 2)

The habit that educators are hoping that students will establish is to meaningfully practice the learning that happened during class time to deepen the neural connections being created, identify gaps in understanding to seek clarification, and understand that repetition and effort are necessary for improvement. All of this is centered around the idea that the educator is the expert, the student is the novice, and the student should therefore trust that the teacher knows what is best for the student to be able to progress. That is true in a general sense, but in reality what each student needs is something different for them to be able to learn. This is not a "learning styles" idea, the concept of teaching a student to their preferred learning style has been thoroughly debunked by this point and needs to be put to rest. What we all need is opportunities for multiple attempts at learning through multiple different means. Audio, visual, and kinesthetic are all ways we learn, and its not based on preference but on accessing through all modes over time and repeatedly that makes the difference for anything we are learning.

The learning phase cannot be high stakes, cannot be judgmental, and should not be done in isolation. Assigning grades to the practice makes all three of those a reality, and in the end causes less students to actively do the work and more to cheat or get help to get it done than actually learn. There is a common belief in education that if it isn't graded students won't do the work. And for some students this is absolutely true. For almost half the students, it means they still won't do the work or will cheat to get it done. For many students who get the work done, it is not a focused, engaged, all in for the learning process. It is a busy form of compliance, without true learning and retention happening. So all of this leads to the question of what is a better way forward. 

Part of the plan needs to be considering Ebbinghaus' Curve of Forgetting. The graph has been replicated many times to show the idea behind his research, and the graph below is one model of his curve:


The basic concept is that as soon as we learn something, our brain starts forgetting that information. Our brain has so much it needs to attend to that unless that information really is critical to our lives, it will prune the information away. Without attention to the material we just learned, in one hours time we will have forgotten nearly 65% of that information, and within 24 hours over 80% of that will be gone, and consistently decline over time. This can be interrupted if 1 hour after we learn something, we go back to it. That one simple touch back will help us retain a higher percent of information longer than if we do not do it. But then the brain needs a chance to forget some of the information, and then go through the struggle of remembering it, so giving a week's time and then going back to the original content restrengthens the neurons. Finally, coming back a month later, giving us time to forget and then actively retrieve the information builds the strong connections that our brain needs to keep that information.

So students doing the homework that night helps to interrupt the forgetting, and refresh the information if they do it and are focused on learning it. The theory of homework stands up and is critical to building long term knowledge, and for being able to connect one concept to the next. So the idea for educators is not to stop providing practice and re-learning opportunities. The idea is to maximize the chance that those we are helping to learn will do the work that is necessary for them to be able to keep progressing. And that is where the autonomy piece comes in, and also changes in the behaviors of educators and how we see and run our classes becomes critical.



Comments

Popular posts from this blog

Vulnerability

I cannot claim to be an expert on vulnerability, that title belongs to Brene Brown. Through her work, I have learned that being vulnerable is key to major breakthroughs in life. The opposite of this is true as well. Being unwilling to take risks, fearing failure or embarrassment, leads to stilted growth and eventual regression. The unwillingness to struggle in the short term leads to eventual major disappointment. That struggle is unpleasant, painful, draining, aggravating, defeating, and necessary. As a teacher, vulnerability arises when teaching a new grade level or content area. It happens when a re-designed lesson is taught for the first time, a new resource is used, and when being observed. Leaders face vulnerability when launching a new initiative and taking questions from stakeholders. Coaches face vulnerability when they meet with a new client or a client who operates outside the coach's wheelhouse of knowledge or skills. Humans are adept at procrastinating, which is a phys...

Navigating Uncertainty

One thing most people can agree on in early April 2024 is that no one knows what to expect right now. Federal agencies are being closed at a record pace, tariffs are rocking global finances, AI is changing faster than most people can keep up with, everyone has an opinion on this, and no one can anticipate what might happen next. The stock market is a prime example of the uncertainty, and on the day I started writing this the Dow Jones surged by 800 points and ultimately fell by 600. Today as I continue writing, it rose by nearly 3000 points. There are countless ways to reach when life becomes chaotic. Some people "don't look up" as the movie's title states, because as long as you can't see the asteroid heading straight towards you it does not exist. Some like to lean into the chaos, acting like Loki, the Norse god of mischief and disruption. Others protest through marches, speeches, and boycotts. All of these are human reactions on which I place no judgment. Based...

Scheduling - A School's Heuristic Problem

Students learn about algorithms in Computer Science to solve complex problems in reasonable times. Some issues are too complex even for the best algorithms to perfectly solve, and those are known as heuristics. The example commonly used is the traveling salesman. While a little outdated, and I have updated the example to be the logistics of UPS delivering packages, the story goes like this.  A traveling salesman arrives in a new town intending to get to each house in the most efficient path possible. They get a road map of all the homes they will visit and their hotel room and start mapping out paths. The math works out to show the following: Let's nerd out for a moment. Each number of possible paths is the mathematical factorial of the number of homes on the path. So 3 homes means 3*2*1 = 6 paths. 7 homes means 7*6*5*4*3*2*1 = 5040 homes. Just 10 homes, and we are at 10 factorial or 3,682,800 pathways! How can one possibly solve for the best route with that many choices? It is too...