As an adaptive learning system, Realizeit provides tremendous flexibility for students, allowing them to learn in their own way, at their own pace, and at times that are most convenient for them. This kind of flexibility can be immensely beneficial to students who may live busy lives with diverse responsibilities that limit their opportunities for study. However, flexibility must be balanced with guidance so that students can achieve the best possible results. Students in the system currently receive guidance from instructors, and in some cases from interaction with their fellow students, but one of our latest internal projects is designed to enable Realizeit to automatically provide students with the kinds of learning supports that a tutor would provide at the times the students need feedback, while still allowing students to retain the freedom and control the system already provides. This project is part of our ongoing internal research to enhance and evolve the platfom, and will be part of a future release.

Self-Regulated Learning (SRL) was a natural concept to focus on in providing this support. SRL is an established concept in learning research, and it relates to the capacity of the student to support their own learning by deploying various techniques to increase understanding and retain information. Factors involved in SRL include cognitive, metacognitive, behavioural, motivational, and emotional aspects of learning. Everyone engages in SRL to some extent, so we’re all familiar to varying degrees with many of these techniques, such as goal-setting, time management, revision, self-testing, note-taking, help-seeking, along with many other behaviours that improve the student’s learning, and which fall under the umbrella of SRL.

Researchers studying SRL have long been interested in what separates successful learners from their unsuccessful counterparts. It has been demonstrated that learners who use SRL to a greater extent, and especially certain particularly beneficial SRL strategies, tend to achieve their goals more than those who use these behaviours to a lesser extent (as discussed by Zimmerman, 1990, among others). We’re interested in learning from these successful students by trying to figure out how we can encourage all learners to use these behaviours to enhance their own understanding and retention, and how we can facilitate the use of SRL within Realizeit. Modern researchers have shown that SRL can be successfully encouraged and supported, and that this does lead to improved learning outcomes (e.g. Bannert & Mengelkamp, 2013).

The Realizeit adaptive learning platform already offers many tools that support SRL behaviours, but without encouragement we may see students engaging in these behaviours only to the extent that they would naturally – thus maintaining the achievement gap between strong self-regulated learners and weak ones. Since we want to help all learners, we decided to investigate two mechanisms to encourage SRL use in the system. Realizeit is a natural platform for this project because, as an adaptive learning platform, it is already focused on raising the standard of all students, and it enables detailed observation of student learning, measurement of that learning, and intervention where needed by instructor or by the system. Researchers have found that delivering information on SRL can boost SRL behaviours, as well as learning outcomes. We are focused on two main ways of doing this: pre-course education (e.g. Hofer & Yu, 2009), and mid-course prompts (e.g. Bannert & Reimann, 2008; Lehmann, Hähnlein & Ifenthaler, 2014).

The first of these involves students completing a course, before they begin learning their core course material, on how to learn. This should explain how they can control and improve their learning process by deploying SRL techniques as they learn. The second involves monitoring student learning, engagement and behaviour, and delivering prompts to the student as they learn, suggesting that they deploy SRL techniques in their learning. The first approach has the advantage of limiting disruption to the student’s core learning, but the second allows the system to address learning deficits that become apparent in real-time.

We are planning to explore both pre-course and mid-course options to increase student use of SRL strategies. In a future post we will outline the exciting way we are working on measuring student SRL behaviour, and deploying encouraging interventions where the system estimates that student learning could be improved by using SRL techniques. In the meantime, any questions, feedback or suggestions on SRL are welcome!


  1. Barry J. Zimmerman (1990) Self-Regulated Learning and Academic Achievement: An Overview, Educational Psychologist, 25:1, 3-17, DOI: 10.1207/s15326985ep2501_2. Article
  2. Bannert, Maria & Mengelkamp, Christoph. (2013). Scaffolding Hypermedia Learning Through Metacognitive Prompts. International Handbook of Metacognition and Learning Technologies. 171-186. 10.1007/978-1-4419-5546-3_12. Article
  3. Hofer, Barbara & L. Yu, Shirley. (2003). Teaching Self-Regulated Learning Through a “Learning to Learn” Course. Teaching of Psychology - TEACH PSYCHOL. 30. 30-33. 10.1207/S15328023TOP3001_05. Article
  4. Bannert, Maria & Reimann, P. (2008). Design and Effects of Metacognitive Support for Hypermedia Learning. Proceedings - ICCE 2008: 16th International Conference on Computers in Education. 18. 969-970. 10.17471/2499-4324/287. Article
  5. Lehmann, T., Hähnlein, I., Ifenthaler, D. (2014). Cognitive, metacognitive and motivational perspectives on preflection in self-regulated online learning.Computers in Human Behavior. Volume 32, March 2014, Pages 313-323. Article