We live in an era in which every product, process, and organization is being constantly examined, analyzed, and rebuilt to adapt to ever-changing circumstances, of which education is no stranger.
This is a post in a multi-part series to explore how design impacts various aspects of education.
Textbooks and Design
Ever since Brian Zhao published Graphic Design and Organic Chemistry two years ago, I’ve been inspired to create something similar. I loved the way that Brian broke down the concepts of Organic Chemistry into a natural flow of concepts that could be easily understood.
Textbooks have always been an object of contention in my mind. Because while textbooks represent a bundle of knowledge intentionally packaged for students, textbooks are usually written to maximize the content that it can deliver. Chapters and sections are written in a way that is convenient for the author, which is usually not the most effective flow for a student’s learning.
You could say that Brian wrote his textbook by first considering the student, or that he applied lessons from user-centered design into textbook publishing. Implementing user-centered design into the writing of a textbook led to visually simple pages, minimalistic graphs and diagrams that portrayed only the important attributes, and redesigns of traditional charts.
My fascination with the way that people learn started out of a desire to improve the way that I learn. It’s old news that traditional lectures and homework are not the most efficient at achieving mastery, but research has not been able to give us a precise method for learning.
But while pedagogical research is still trying to understand what works best through cognitive and psychological research, the recent transformation of our world into a globally interconnected digital society means that learning must also undergo this transformation. It is this digitization that has launched MOOCs, opened online textbooks, and created flipped classrooms.
But just like the first generation of television was nothing more than radio with a video channel or taped broadway shows, our nascent implementations of digital learning have yet to take advantage of the full potential of online learning platforms. We’ve barely encountered the tip of the iceberg when it comes to education technology.
Online Enhanced Teaching and Learning
In my last quarter at UC San Diego, I took a graduate course from Elizabeth Simon called Online Enhanced Teaching and Learning. Perhaps the most significant takeaway from that class was understanding the difference in attitude between a student learning in a classroom and a student learning online.
Students who learn in a classroom often do so not because they genuinely want to take the class, but usually because the class is a prerequisite for another class, which is a requirement for graduation. Students who have paid money to attend a school inadvertently have a leash around their necks that forces attendance and studying. However, students who take courses online choose to do so instead of browsing Facebook, watching movies, etc. Thus, the threshold for quality of a student enrolled in an institution is lower than a student taking a class online.
Because online classes must be significantly more engaging than in-person classes, every sentence, slide, video, and quiz must serve a clear purpose to the student. Students will be more likely to do assignments and exercises they feel are interesting and helpful than exercises that seem to do little more than fill time.
Perhaps the most important distinction here is the difference between summative and formative assessments. Summative assessments are what most students think of when the hear the word “test”. Summative assessments are assessments that usually come at the end of a section or term, used for grading a student’s performance and mastery of a subject. Formative assessment on the other hand is geared toward improving a student’s mastery of a subject. For instance, a summative assessment will give the student feedback on where they went wrong and give them the opportunity to learn from their mistakes.
Through carefully created feedback on incorrect and correct answers to a question, this kind of “elaborative feedback” can be extremely helpful for students to metacognitively assess their learning.
Teaching Machine Learning
The learning process of STEM fields in schools has generally not been a very smooth learning experience. STEM subjects in college are often taught through lectures in which lecturers attempt to explain complex mathematical models or scientific theories through abstractions. While there definitely are students who are able to understand and easily absorb these kinds of abstractions, the majority of students have to review lecture notes / homework assignments over and over to properly understand the concepts taught in a class.
Combining the inspiration of a well designed textbook, online platforms as a method for teaching and learning, and my love for computer science, I set out to create a tool that would help people understand the mechanics of artificial intelligence. Artificial intelligence is made up of mathematical algorithms that can be hard to understand, but just like learning any complex subject, having right breakdowns and visualizations can help make a complex subject manageable.
I started by breaking down one specific aspect of artificial intelligence known as the perceptron. In AI, the perceptron is one of the fundamental building blocks for more advanced concepts such as neural networks. While it sounds complex, the perceptron is simply a type of algorithm that finds a line that separates data with a certain label from data with a different label.
Algorithms such as the perceptron are often expressed through linear algebra functions such as the dot product, which can be hard to intuitively grasp. Just like a graph and animation can make the equation of the trajectory of a basketball shot much more intuitive, charting out and being able to interact with the functions of a machine learning algorithm can make the mathematical manipulations more intuitive.
With my learning tool, students are able to manipulate lines, data points, and vectors on a plane to see how the algorithm behaves. By having the ability to interact with the algorithm, students are better able to intuitively identify where their knowledge is not completely correct, and metacognitively assess how to learn.
Designing Learning Experiences
Of course, the content is only a minuscule piece of the larger picture of education experiences. Online education is only one tool among many that we need to take the time to improve pedagogy for. I don’t pretend that online education is going to be the solution for everything, because quite frankly, no technology is going to solve all our problems in teaching and learning.
For as long as we’ve been developing new technologies, there have been self-proclaimed experts saying that the most recent new technology is going to revolutionize education, only to have it negligibly improve education after having it deployed in all of our schools. In that sense, I don’t believe that VR is the future of education.
It is for this reason that we should focus first on the pedagogy of education before we pick up the tools. New tools will make no difference under an old pedagogy, while improving pedagogy can work with almost any tool. Learning experiences include everything from social interactions, student participation, educational content, and so much more.
“Design is a deliberate intervention in the world to make things better” – Don Norman