By Carolina Kuepper-Tetzel

One aspect that seems important when it comes to self-regulated learning is the ability to plan one’s own learning and, for instance, to decide what material to study next, how long to study the material for, and how to study the material. Being allowed to be in charge of such planning promises to have positive effects on motivation – at least when considering learning within the framework of the self-determination theory (1). Two important components of this influential motivation theory are Competence and Autonomy. Competence refers to the need of learners to experience mastery. This is fostered when learners take control of their own learning, which is reflected in Autonomy. Learners will experience autonomy when they independently make decisions regarding their learning. Thus, if students plan their own studying, their motivation to study would increase as a consequence. Furthermore, this positive effect could affect learning outcomes as well. Hence, compared to a learning situation in which the study plan is determined by someone or something else, a learner-generated study plan could lead to more learning. The reason for this is that strategically planning what to study when affords some basic understanding and evaluation of the material which can be conducive to learning itself.

Thus, the question is whether it indeed makes a difference if students plan studying themselves versus have it planned by – let’s say – an app. An experiment by Bonestroo and de Jong (2) tested this question and investigated whether learning outcome, motivation, and metacognition would be affected by study plans that were either generated by the learner or generated by a computer. Participants in their study were university students. In the experiment, they were asked to plan or follow a plan for studying intro statistics material. In the next step, participants studied the material according to the plan and later took a test measuring their knowledge. Importantly, all participants experienced both conditions; thus, studied using both self-generated plans and computer-generated plans. In addition to performance, motivation was measured as well as metacognitive aspects – such as the perceived effectiveness of and their preference for the two planning approaches (i.e., self-generated vs computer-generated study plans).

The results revealed that planning condition (self-generated vs computer-generated study plans) did not have an effect on test performance in the end. Participants were able to produce equal intro stats knowledge independently of who was in charge of study planning. Furthermore, the researchers found no effect on motivation. Thus, participants did not rate they motivation higher when they had to do their own planning versus when the computer performed the planning for them. Interestingly, a significant effect was found between the two planning conditions on metacognitive measures: Participants indicated that they thought that they obtained more knowledge when planning studying themselves compared to having studying planned by a computer. They further stated that for their own studying they would prefer to plan it themselves. However, if they were to create a plan for someone else, they would prefer to rely on the computer-generated plan. What is striking is that here again people’s metacognitive judgments in regard to the effectiveness of the two planning approaches was not accurate: Even though the self-generated study plans were perceived as being more successful to acquire knowledge than the computer-generated ones, there was no difference in knowledge assessment between the two conditions.

At first glance the present study might suggest to throw learner-generated study plans over board and stick with computer- or teacher-generated plans. In fact, learner-generated study plans took considerably longer to create than computer-generated plans (another finding of the present study). But, not so fast! The study comes with some important limitations that we need to take into consideration before jumping to conclusions:

1. The software that was used in the experiment to create the study plans only allowed participants to make a restricted range of moves. Only if the self-generated study plans were consistent with a predetermined structure, the participants were allowed to proceed. This is quite different to any study environment that students will encounter in the authentic educational settings, where they have full freedom to decide what to study next (for better or for worse).
2. Knowledge was assessed within the same session as planning and studying occurred. This is never the case in real-world studying, where there will always be lags between planning and studying and assessment. Plus, it would have been interesting to see the effects on retention of knowledge after a longer delay.
3. All measures were assessed during the single session that lasted approx. 100 minutes. However, we already know that metacognitive judgments are usually quite poor when assessed immediately after studying and improve when given at a delay. Thus, it is possible that delayed metacognitive judgments would have been a better reflection of actual performance.
4. Participants in this study had no prior knowledge of the material that was used. However, careful planning of studying requires a certain degree of basic understanding and prior knowledge of the material. Without that, study planning occurs in a vacuum that makes it difficult to make sensible decisions. In an educational setting this means to select material to study that has not been mastered yet and postpone studying material that has been understood better (3).

Given these limitations, we cannot draw strong conclusions from the presented study for real-world studying. However, the study gives us food for thought and makes us reflect about different theories (such as the self-determination theory) and the broader concept of self-regulated learning in students. It shows us quite plainly how complex studying actually is and how many different factors we can consider when trying to explain it.

References

(1)  Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68-78.

(2)  Bonestroo, W., & de Jong, Ton (2012). The planning illusion: Does active planning of a learning route support learning as well as learners think it does? Educational Studies, 38, 559-571.

(3)  Metcalfe, J., & Kornell, N. (2005). A region of proximal learning model of study time allocation. Journal of Memory and Language, 52, 463-477.