Illustration about a Metacognition-based learning detection system conceived to improve web-based self-regulated learning

Many learners have found that it is difficult to complete their web-based learning plan. Once on the Internet, they can´t help browsing more interesting Web pages instead of continuing to do their learning tasks. This situation we called Information Trek. To solve this problem, this study proposes an learning detection system which can discover whether the contents of a web page a student viewing is about learning or not. If a student is detected to be in the state of viewing the non-learning pages, then the alert reinforcement window will be shown. If the attentive time in learning has been reached, then encouraging reinforcement feedback is given. We must consider adequately about personalization given the different levels of Metacognition. In this system, preferring the method to let learner go back to the learning state themselves, we design some functions to guide learners regulate themselves based on the essential process of online self-regulated leaning integrating Metacognitive process.