Opportunities to facilitate learning on the Internet are widely recognized across subject matters, levels of education and situations ranging from extending one’s hobbies to life-long learning relating to workers’ changing roles in the workplace. However, information available in the Internet, even in formal academic courses, is rarely presented using empirically proven findings from the learning sciences. Often, learners are left “on their own” to figure out which tactics work best for them in seeking and understanding information, and studying to learn it. Given that most learners have weak skills in these areas and in self-regulating learning, this sets a stage for major failures in sensemaking and learning that can have dire societal consequences. On the other hand, there are open issues with the existing (a) tools that are typically designed for a hypothetical but factually non-existent “average” user; and (b) methods that are too often based on self-reports (e.g., questionnaires) that are insufficient to advance research on sensemaking and complex learning processes that involve dynamic feedback loops.
This talk (i) discusses results of several studies, in which we have addressed the above challenges, and (ii) outlines promising research topics that spans across the three main research cornerstones – computational, socio-cognitive, and user-centered design.