Processes of self-regulation in a digital task-based learning environment for physics undergraduates

近年来，数字化学习环境在德国大学中扮演着越来越重要的角色。在其他目标中，这些环境旨在帮助先前知识不足的学生赶上进度，从而有助于他们的学业成功。数字环境的使用似乎很有前途，因为它们允许学生以自主和灵活的方式学习。然而，实证研究结果表明，这些环境往往表现出学生的低持久性和高辍学率，这表明许多学习者无法利用他们的潜力。据推测，在数字环境下的自主学习对学生的自我调节能力提出了很高的要求，这至少在一定程度上导致了辍学率的上升。例如，为了成功地使用数字环境，学生需要现实地评估自己的能力和知识差距，为自己设定相应的目标，并选择匹配的学习任务。为了帮助学习者应对自我调节学习的挑战，研究人员和教育工作者需要深入了解学习者的自我调节过程以及他们在数字环境中学习时遇到的困难。到目前为止，对学生自主学习的研究主要是在以信息（事实、解释等）为主要内容的环境中进行的，例如以文本或视频的形式（如超媒体环境）。相比之下，对于学生在主要由任务和问题组成的环境中的自我调节学习知之甚少，这些任务和问题需要学习者处理和应用所提供的信息。文献中的这一差距是至关重要的，因为通过解决任务来处理信息被认为是自然科学学习的必要条件。为了解决这一差距，将进行第一项研究，旨在捕捉物理学生在数字任务学习环境中工作的自我调节过程和相应的困难。它还将调查这些过程和特定困难的发生如何与学习者特征以及学习成功相关。在第一项研究中获得的见解不仅有助于我们理解数字环境中发生的自我调节过程，而且还可以为制定支持学生自我调节学习的措施提供信息。根据第一项研究的结果，将在环境方面制订和实施具体的支助措施。在实施后，我们将进行第二项研究，以调查这些措施对学生自我调节过程和学习成功的影响。总之，这两项研究将有助于我们理解任务型环境中成功和不成功的自我调节学习的机制，并帮助我们获得成功的支持措施。

Digital learning environments play an increasingly important role at German universities in recent years. Among other objectives, these environments are intended to support students with insufficient prior knowledge in catching up and thereby contribute to their academic success. The use of digital environments seems promising because they allow students to learn in an autonomous and flexible way. However, empirical findings show that these environments often exhibit low student persistence and high drop-out rates, indicating that many learners are unable to take advantage of their potential. It is assumed that the drop-out rates are at least partly caused by the fact that autonomous learning with digital environments places high demands on students' ability to self-regulate their learning. For instance, to use a digital environment successfully, students need to assess their own abilities and knowledge gaps realistically, set themselves corresponding goals, and select matching learning tasks. To support learners in facing such challenges of self-regulated learning, researchers and educators need insights into the self-regulation processes of learners and the difficulties they encounter while learning in digital environments. So far, students' self-regulated learning has primarily been investigated in environments that mainly consist of information (facts, explanations etc.) being presented to students, for example, in the form of texts or videos (e.g., hypermedia environments). In contrast, little is known about students' self-regulated learning in environments that primarily consist of tasks and problems which require learners to process and apply the information provided. This gap in the literature is critical because processing information by solving tasks is assumed to be essential for learning in the natural sciences. To address this gap a first study will be conducted that aims to capture the self-regulation processes and corresponding difficulties of physics students working in a digital task-based learning environment. It will also be investigated how these processes and the occurrence of specific difficulties are related to learner characteristics as well as learning success. The insights gained in the first study may not only contribute to our understanding of the self-regulation processes taking place in digital environments but can also inform the development of measures to support students in self-regulating their learning. Based on the results of the first study, specific support measures will be developed and implemented in the environment. Following the implementation, a second study will be conducted to investigate the effect of these measures on students' self-regulation processes and their learning success. Together, these two studies will contribute to our understanding of the mechanisms of successful and unsuccessful self-regulated learning in task-based environments and help us to derive successful support measures.