Learning Analytics for Adaptive Systems supporting Self-regulated Social Learning

今天，在互联网和社交媒体上以各种形式促进学习的机会，从小学到中学后、工作场所和终身学习，以及在不同层面上都得到了广泛承认。然而，互联网上提供的信息和社交媒体上的学习活动，即使是通过正式的学术课程，主要也不是基于来自学习科学的经验证的建议。通常，学习者只能“自己”找出最适合他们的学习策略。正如学习科学研究报告所述，这是一个严重的威胁，因为大多数学习者的自我调节学习技能较弱。这可能会对他们的学习成功产生严重影响，带来许多社会后果，如高辍学率和劳动力对职业过渡缺乏准备。

Opportunities to facilitate learning, in all forms from elementary schools to post-secondary, workplace, and life-long learning and at different levels, on the Internet and with social media are widely recognized today. However, information offered on the Internet and learning activities in social media, even via formal academic courses, are mainly not based on empirically-proven recommendations from learning sciences. Often, learners are left "on their own" to figure out which study tactics best work for them. This is a serious threat given that most learners have weak skills for self-regulated learning, as reported in learning science research. This can have severe effects on their learning success with numerous societal consequences such as high dropout rates and workforce unprepared for career transitions.