This semester I am taking the iSchool’s Introduction to Databases class. This is one of those classes that I really want to take, and I really want to learn about databases because they are both interesting and useful… but I’m also a little bit intimidated by it, because I don’t have a computer science background or a higher math background. Everything I know about computer science I learned from this video series by CrashCourse, and the highest level math class I’ve completed was Calculus 1, way back in high school (I took some statistics classes in college, but I don’t know if I would classify them as a higher level of math than calculus). And database design involves set theory and learning a whole new language and specific diagram methods that all relate back to these higher level concepts of entities and relationships and attributes… and it could all very easily be overwhelming (despite a fantastic instructor and a comprehensive and informative - if dry - textbook).
Learning about databases
But… you know what? It’s kind of not (overwhelming). And there is one very specific reason why: I have a mental reference. A dataset that I know extremely well and am extremely interested in. A dataset that I put together at a time when I knew virtually nothing about how databases worked - forcing me to learn from the ground up. A dataset that I vitally needed in order to accomplish my goal: completing my undergraduate honors thesis (and thus graduating with honors).
Using my thesis research as a base of understanding
Every time the textbook introduces a new concept, a new term, a new method… I think about how that would work in my database (if I turned my thesis dataset into a database). And furthermore, none of it is quite new. It may be a more formal framing of databases and database design, but I had to fight to create these conceptions myself from scratch - from working with data that I was interested in analyzing and figuring out for myself how to make it work. (Granted, I am only beginning to learn about databases and I have no doubt that very soon there will be a lot of new material, but at least I’m starting with some kind of foundation.)
And along the way, I had a lot of help. I cannot emphasize that enough - it wasn’t just me figuring all of this out with the internet as my only resource. I owe a huge debt of gratitude to my thesis advisor, Dr. Stephen Gent, not only for guiding me through Stata (the program I used to create, manage, and analyze my dataset) but encouraging me to pursue the quantitative analysis path in the first place (something that I wanted to do but lacked the confidence to commit to due to my lack of experience). I could have gone the qualitative route and written my thesis based off of anecdotal evidence alone (i.e. case studies), but I knew that quantitative data and analysis would be a better investigative method - showing the real trends, even if those trends did not match my initial hypothesis. Dr. Gent’s help (including impromptu Stata tutorials) was invaluable - but even more valuable was the fact that he never told me exactly what to do. I had to figure out most of it on my own, and as a result I learned how to conduct ground-up quantitative research. I also couldn’t have even gotten started without the Odum Institute (a division within UNC’s libraries dedicated to social science research), because some of the datasets I was merging together required transformation that was a bit too advanced for me to do myself. But after that initial transformation, it was just me and Stata grinding it out, adding more datasets and figuring out what to so with null values (learning what null values were!), creating new variables derived from multiple other variables to use in my analysis, figuring out how to do a regression analysis (and what all of the output actually meant!). Who knew that spending hours… days… weeks… wrestling with my data in Stata would prove to be one of the most valuable experiences of my undergraduate career?
So when I read about key attributes, I already understand many of their complexities because I had to discover for myself why datasets need a unique ID variable. Composite keys? That’s the kind of unique ID I created for my dataset. Multivalued attributes? How many times did I wish something like this existed for my some of my variables in Stata? Derived attributes? The most important variables for my analysis were derived. Even new concepts that don’t apply to datasets, like the entity-relationship model, weren’t completely new because I could re-design my dataset to fit the ER model - and it would be better for it. Foreign keys? I essentially had to create and work with a kind of foreign key in order to merge in new datasets. I also had to deal with one-to-one and one-to-many and many-to-many cardinalities when I merged new data into my master dataset. There are some new concepts that I did not consider before, like total and partial entity participation in relationships, but all I have to do to cement my understanding of these new concepts is to think about how they would work in my database (my hypothetical new and improved thesis dataset). And furthermore, most of the questions I ask in class are because I’m thinking about how to re-do my thesis dataset as a relational database. Everything I learn in this class, I’m able to learn well because I can mentally reference my thesis research experience.
Looking back, I’m so grateful to have had that experience - to have learned by doing, by working on a project that I was very passionate about (and still am). But I also remember that the process itself was an immensely difficult and frustrating one. In the moment, I didn’t feel like I was learning… I felt like I was failing. In our education system, we “learn” first and “do” last. You are judged by your grades, and a GPA doesn’t take into account whether you learned from failure - just that you failed. So if you felt uncertain, if you were encountering new material in a graded situation, that meant that you hadn’t learned enough… and you weren’t ready to “do” yet. And usually, “doing” means taking a test - not very applicable to the real world.
This method of test-based learning (and teaching) is a huge disservice for students, because in the real-world they aren’t going to be taking tests - they’re going to be doing projects. And I have yet to meet someone who has a real passion for taking tests just for the sake of the test, while I know plenty of people who will learn new and unfamiliar things every day for the sake of a passion project. You can’t expect students to learn just because you told them to do so - that’s not how people work. You need to take into account and work within the existing psychological framework, and make personal motivation and passion a fundamental feature of the learning process. Of course, that is easier said than done. And for students used to learning for the test, the switch to experiential and project-based learning can be quite the shock.
My first introduction to project-based learning: high-school astronomy
I took an astronomy elective my freshman year of high school, because I was stubborn (higher-level math than I knew would be used) and I loved space (thank you, science fiction). It was, by far, the most frustrating and rewarding class that I took that year (possibly all of high school, but it would have to tie with my newspaper class). I still remember going home and ranting to my mother about how my astronomy teacher wasn’t teaching. Instead, he gave us topics (that we knew nothing about!) to research and then teach to the class. The tests were weird (we were allowed to fill up one sheet of paper with as much information as we wanted to use during the test… and it wouldn’t always help very much), and we spent a vast amount of time learning how to take and edit photos. I genuinely liked my astronomy teacher as a person, but for most of the class I also thought that he was a horrible teacher.
It took me an embarrassingly long time to realize that he simply had a different method - stand back and let the students learn by doing. I learned how to take photographs of astronomical subjects like nebulas using a telescope in Chile (via a web interface) and edit those photos to make them pretty (colorize the various filtered photos and merge them into one beautiful composite image). And I discovered that not only did I enjoy this painstaking process, but I was pretty good at it! (for a 13-year-old). I took a great deal of pride in my pretty nebula images, and I even presented them at a local amateur astronomy meetup. I had accomplished something real, discovered new interests, and learned new skills that I enjoyed using.
It took me a bit longer to appreciate his method of letting the students teach concepts (that I thought I would have learned better if the real teacher had been the one presenting them), but I eventually realized that it wasn’t so important that we memorize and completely understand every concept we encountered in class - instead, he was trying to teach us the more important skills of gathering information on a topic we were unfamiliar with, working with other people with different sets of knowledge/skills, internalizing and organizing that subset of information we were assigned so that we would be able to teach it, and then presenting that information to our peers. Those project-based skills were what we would actually use down the road, whether we went into astronomy or not.
No more tests! … finally.
I’m taking three classes this semester for my MSLIS program, and guess what? There are no tests. None. The closest thing to a test is an online reading check in one of my classes that allows unlimited retakes. Instead, grades are drawn from projects. There are many different types of projects - writing short essays, solving programming problems, creating diagrams, etc - but they are all projects (instead of tests). And I don’t think I’m going to encounter a single test in this program. Why did it take me until my Master’s degree to encounter an educational program that is project-based instead of test-based?
It probably has something to do with the fact that this is a very career-oriented program that is entirely focused on preparing you to enter the workforce within a specific field, and the reputation of the school is more dependent on employers being happy with their new employees than on some arbitrary goal for average test scores. It’s also a much smaller program, with smaller class sizes and teaching assistants to help professors with the grading, so dedicating the time to grading projects is more feasible (whereas tests can be graded very quickly and easily scales to much larger class sizes).
But… what if we could switch K-12 schools to be project-based instead of test-based? It’s not impossible - other countries have done it (Finland!). But it would require a lot of money, a change in educational culture, and a fundamental shift in values. Smaller classes, better trained (and paid and valued) teachers, new curriculums, new ways of evaluating school performance… and overall shifting our culture to better value quality education - which means everything from paying our teachers more, treating them better (that applies to students, parents, and administrators!), changing programs so that students are excited to learn (not waiting for the bell to ring), teaching different subjects (critical thinking via philosophy) in different ways (flipping the classroom, digital methods), and so much more.
And maybe if we didn’t train students to focus only on tests (over actual learning) half the questions the undergrads ask in my logic class wouldn’t be about the test…
But, improving our education system is a whole `nother topic that I would like to explore at length in a different post at some point in the future. For now, I just want to say this: projects help you learn in a way that tests simply can’t. The primary reason that I am able to understand many of the concepts in my database class, and am interested and engaged in class, is because of my experience working on my thesis. It was an incredible experience, and I am so grateful to have had that experience - it has informed my career path in ways that I could never have anticipated, and will likely continue to do so.