
Students in science, technology, engineering and math (STEM) fields perform better when they use a strategy known as “subgoal learning” to break down problems into smaller parts.
Research has shown that when students learn subgoals, they are better able to use their problem-solving skills to tackle new problems.
“The problem we have in instruction, especially in higher education, is that the people who are teaching are experts and don’t remember what it’s like to be a novice. They don’t know what is common knowledge and what isn’t common knowledge, so they tend to not break things down enough for novices,” said Assistant Professor Lauren Margulieux, who focused her dissertation on subgoal learning and its impacts on programming education. “So, subgoal learning works with experts to get at this tacit knowledge that they have.”
For her dissertation, which earned her the Outstanding Doctoral Research Award from Emerald Group Publishing and the Higher Education Teaching and Learning Association, Margulieux wanted to know whether students could improve their problem-solving skills if they were introduced to more engaging ways of learning subgoals.
To explore this, she conducted a study that asked participants to work through a programming problem in App Inventor, a programming language used to make Android apps, to build a music app.
Some participants were automatically given specific subgoals as they created their music apps; others were either asked to choose from a list of subgoals or create their own. Those creating their own subgoals received either hints about the subgoals they created, feedback on their answers from experts, both hints and feedback, or no support at all.
“The way I like to think about these different conditions is giving students a range from the most support from their instructors to the least support,” Margulieux explained. “It’s been theorized that you want to provide just enough support but not too much, so that’s what we were looking for – that sweet spot.”
In this case, Margulieux found that participants who received both hints and feedback didn’t do as well as the people who received just one or the other, which speaks to the “sweet spot” she and other researchers have discussed.
Along those same lines, participants who didn’t receive any support at all didn’t fare as well as those who received some level of feedback.
Though this project focused on programming education, the findings may have implications for educators in other STEM fields.
“I think this applies to complex problem solving and could work the same way with engineering, calculus or other areas where there’s a high mental load on the student,” she said.
