Over the last three decades, educational and psychological research on learning has shown the need for a shift from teacher-centered to more student-centered approaches. Many of these approaches emphasize engaging students in solving real-world, complex problems (e.g. Jonassen, 1997; 2011). Concurrently, advances in educational technology are moving an increasing amount of higher education instruction online, placing more responsibility on students for their own learning (Sungur & Tekkaya, 2006). Research shows that students are more successful academically when they can regulate their own learning. However, they often find it difficult to regulate themselves in unfamiliar learning situations, especially if they are not used to regulating their own behavior. In online environments, some research indicates that providing support may be more effective than allowing students to manage their own learning (Azvedo, Moos, Greene, Winters, & Cromley, 2008). Specifically, scaffolding learning by using methods such as embedding cognitive and metacognitive prompts into online learning environments may provide better learning outcomes.
Self-monitoring is essential for successful self-regulation during learning. It is particularly important when students must perform meaningful activities in online learning environments with little guidance. However, when performing these types of activities, monitoring can actually lower performance on learning activities (such as real-world problem solving) that require more student effort.
This study examines the design of two levels of self-monitoring support during an online real-world problem-solving activity. Specifically, it looks at the effects of two types of self-monitoring intervention. One group will receive only a 10 minute tutorial on a self-monitoring method to use during the problem-solving activity. The second group will additionally receive self-monitoring reflection prompts during each of four related problem-solving activities and will be required to answer questions about the prompts during four separate phases of the problem-solving activity. The third control group will receive no self-monitoring instruction or prompts. Findings will discuss the independent and interactive effects of self-monitoring instruction and prompts on undergraduate students’ knowledge and problem-solving within a Web-based learning environment.
Stay tuned to the CogBlog to find out about the results of this interesting research and Naomi’s journey to a Doctoral degree!
Azevedo, R., Moos, D. C., Greene, J. A., Winters, F. I., & Cromley, J. G. (2008). Why is externally-facilitated regulated learning more effective than self-regulated learning with hypermedia?. Educational Technology Research and Development, 56(1), 45-72.
Jonassen, D. H. (1997). Instructional design models for well-structured and iII-structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65-94.
Jonassen, D. H. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. New York: Routledge.
Sungur, S., & Tekkaya, C. (2006). Effects of problem-based learning and traditional instruction on self-regulated learning. The journal of educational research, 99(5), 307-320.
Van Gog, T., Kester, L., & Paas, F. (2011). Effects of concurrent monitoring on cognitive load and performance as a function of task complexity. Applied cognitive psychology, 25(4), 584-587.
Photo Credit: Flickr, Ron Lewis, Virginia Tech