Why and How to Measure Self-Directed Learning Skills

September 1, 2023 | By Jorge Mahecha, Research Associate, Community College Research Center

Illustration of researchers viewing survey results

The ability to manage one’s own learning processes, known as self-directed learning (SDL), is a crucial factor in students’ academic success and one that learning scientists consider being open to improvement. At the Postsecondary Collaborative, we focus on SDL skills, such as asking for help, staying motivated in a course, and managing time to accomplish different goals. Developing such SDL skills is particularly important in online learning environments, which pose unique challenges to college students’ performance, persistence, and attainment.

To support online students in developing SDL skills, researchers need effective metrics to track the extent to which students have developed these skills. This blog post describes what Collaborative researchers are learning about measuring SDL skills and how these skills influence students’ college outcomes.

Measuring SDL skills is not as straightforward as measuring someone’s height or weight. The instruments used to measure these skills are specially designed surveys that conform to a scale such that higher scale scores correspond to higher levels of particular SDL skills. One of the first steps we took when creating a survey was to review existing literature about the measurement of these skills and select which scales could be more informative for our research purposes.

We found several available survey instruments that asked respondents to report on their engagement with key SDL behaviors. The researchers designing each of these surveys took somewhat different approaches to defining observable behaviors that can be interpreted as evidence of the presence of SDL skills. Some scales explored a particular SDL skill in depth, while others touched on several skills. For instance, some researchers consider SDL as a one-dimensional personality trait that can be measured with a rather short survey of 10 questions. In contrast, others consider SDL a multidimensional trait requiring an 81-question survey to be properly assessed.

Key to our survey design was also an inquiry about students’ final course grades so we could test whether SDL scores had predictive validity with student outcomes. With information about SDL skill levels and final grades, we can check, for example, if students reporting better time management also earn better grades. If this were the case, it would provide empirical evidence for the relevance of an intervention to improve time management skills. To test our hypothesis about the relationship between SDL skills and student outcomes, we surveyed 245 students in two community colleges. In our survey, we used scales to measure several SDL skills (self-efficacy in time management, general academic self-efficacy, help-seeking behavior, sense of belonging, and others), and we also requested their grades. In such a way, we could test whether SDL skills and outcomes had a relationship.

Those who earned the lower grades seemed to be under a self-fulfilling prophecy: They reported, for example, that they did not believe they were able to get a high grade, and indeed that turned out to be the case.

As we expected based on past theory and research, our preliminary results show interesting associations between SDL skills and grades. Students with higher self-ratings of self-efficacy in time management achieved better course grades than those with lower self-ratings. Students with lower SDL scale scores seem to have more difficulty avoiding distractions and allocating time to study for class. Students with high general self-efficacy earned higher course grades, and those with low self-efficacy earned lower course grades. Those who earned the lower grades seemed to be under a self-fulfilling prophecy: They reported, for example, that they did not believe they were able to get a high grade, and indeed that turned out to be the case. Finally, our exploration of help-seeking behaviors showed that neither high- nor low-performing students reported either aptitude or willingness to ask for help.

These preliminary results highlight the importance of SDL skills as malleable factors of student success and provide evidence of predictive validity between SDL skill levels and final grades. The results support the relevance of teaching students how to ask for help, how to manage their time, and how to change preconceived notions about their performance and skills. There is evidence that even short interventions in social belonging (30 minutes) can have important effects on persistence and retention in higher education.

The Collaborative’s Rapid-Cycle Experiments team is currently testing short video interventions that support students’ sense of belonging and time management skills. These short interventions require minimal instructor involvement, facilitating implementation at scale while providing students with key messages on SDL skills that can improve their outcomes. To know how to refine these interventions, it is important to use metrics to detect what SDL skills might be low and hence, in need of an intervention that can ultimately impact student outcomes.