Learning a new computer language is a discipline in its own right, as is evident from the doctoral research of TU/e computer scientist Daphne Miedema. In a world of ones and zeros, students are quick to get the grasp of familiar programming languages such as Java, Python or C++. However, learning to program with database language SQL does not come as easily to many computer science students. This is why Miedema returned to the lecture halls, to investigate the pitfalls. By developing new teaching materials, she aims to optimize SQL education.
To an outsider, all programming languages may seem similar, but the currently most in-demand language SQL is of a totally different caliber, says Daphne Miedema.
With a master's degree in both Computer Science and Human Technology Interaction under her belt, she set out to examine current SQL education from different perspectives. On Friday January 12th, she defended her PhD dissertation at the Department of Mathematics and Computer Science, which also serves as the occasion for the mini-symposium "Data Education for the Future Engineer".
Command or description
What is it that makes SQL so different from other commonly used programming languages?
"Structured Query Language (SQL) has a very different structure. It looks a bit like ordinary English, but structured in such a way that it is understood by database management programs. It allows you to communicate with databases and you can use it for data management, for example; it forms the basis of any website. Instead of giving step-by-step commands telling a computer how to solve a problem, SQL allows for declarative programming, where the emphasis is on describing the problem itself, rather than how to solve it. In short, SQL uses descriptions, whereas other languages have commands as the key elements. And with a command list, it's much easier to work through things step-by-step, for example when looking for programming errors. With SQL, that's not quite as easy."
Organizing data
Now that data science is becoming increasingly important in our society - think of the use of all kinds of artificial intelligence applications, but also the large-scale collection and interpretation of data - Miedema argues that it is crucial to have a good understanding of how to organize that data.
"The path from data to a prediction or AI model is not straightforward. Database management is still an underexposed area, but a good foundation is essential."
For current jobs in the computer science field, SQL is the most in-demand programming language, which also indicates that we need to properly train our students in it, Miedema emphasizes.
Many students run into problems when learning the SQL programming language. Although the language has been around since the 1970s and is built into every computer scientist's standard toolbox nowadays, relatively little is known about those problems in SQL education.
For Miedema - who is passionate about imparting knowledge - this is an opportunity to fill a gap. "Ever since secondary school, I've been tutoring in the science subjects, which evolved into several student assistant positions here at TU/e. Through a PhD Teaching Assistant position, I became increasingly involved in teaching and eventually developed some lectures of my own."
Misconceptions
Over the past years, Miedema spent a lot of time in lecture halls, talking to students from beginner level to SQL experts and analyzing large stacks of completed assignments.
How do students solve problems, and how do they translate from English to SQL, for example? Has this provided more insight into the mistakes students make and why? Miedema nods. "Many students already know another programming language before they learn SQL. We often see that students underestimate the difficulty of learning SQL because they can already program. We also see that a certain thought pattern emerges: 'I've learned that something works this way, so that must be how it works in SQL too.' This way, students incorrectly carry something over to a new language that works very differently. These misconceptions are a new development within data systems education."
New textbook
Now that there is more insight into how students learn SQL and what the pitfalls may be, Miedema is eager to address them in SQL education, using her dissertation as a guideline.
She initially developed a workshop to make lecturers aware of research on learning SQL, which she has already presented at several international conferences. The reception has been positive, she hesitantly admits.
"There is a serious need for innovation in education. What we see here at TU/e is a global issue, an eye-opener for many lecturers. It helps that we can now get a closer look into the student's mind."
In a new study, Miedema will examine whether and how misconceptions can be reversed; she is already putting more emphasis on this in her own lectures. "This is how I bring my research into the classroom."
Meanwhile, Miedema has an American adventure to look forward to, also aimed at optimizing SQL instruction for beginning students. She hopes that she can compile all the accumulated theory into new material to help lecturers. Because she is very clear about her final goal: it would be great if those beginning students could learn from her new textbook one day.
Source: Cursor (Nicole Testerink).
