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Background: Providing feedback in massive open online courses (MOOCs) is challenging due to the massiveness and heterogeneity of learners' population. Learning analytics (LA) solutions aim at scaling up feedback interventions and supporting instructors in this endeavour. Paper Objectives: This paper focuses on instructor‐led feedback mediated by LA tools in MOOCs. Our goal is to answer how, to what extent data‐driven feedback is provided to learners, and what its impact is. Methods: We conducted a systematic literature review on the state‐of‐the‐art LA‐informed instructor‐led feedback in MOOCs. From a pool of 227 publications, we selected 38 articles that address the topic of LA‐informed feedback in MOOCs mediated by instructors. We applied etic content analysis to the collected data. Results and Conclusions: The results revealed a lack of empirical studies exploring LA to deliver feedback, and limited attention on pedagogy to inform feedback practices. Our findings suggest the need for systematization and evaluation of feedback. Additionally, there is a need for conceptual tools to guide instructors' in the design of LA‐based feedback. Takeaways: We point out the need for systematization and evaluation of feedback. We envision that this research can support the design of LA‐based feedback, thus contributing to bridge the gap between pedagogy and data‐driven practice in MOOCs. Lay Description: What is known about this topic: Learners' scale and diversity hinder timely feedback in massive open online courses (MOOCs).Learning analytics (LA) can optimise learners' support by scaling the feedback interventions. What this paper adds: We present a literature review on LA‐based feedback in MOOCs in the last 12 years.We focused on LA approaches that support instructors in providing feedback.Results show a scarcity of empirical studies related to these LA‐based tools.Results show that limited attention is paid to pedagogical and contextual aspects. Implications of the study findings for practitioners: We address knowledge gaps related to LA‐based tools for feedback in MOOCs.There is a need of LA‐based interventions to consider the course context.There is a need to evaluate the impact of LA‐based feedback in MOOCs empirically. [ABSTRACT FROM AUTHOR]

People can learn a lot through (collaborative) reflection at work: In organizations, staff debate experiences and due to issues every day, thus reflecting together and learning from each other. While this is desirable, it is often hindered by differences in time and space. Online discussions in community-like systems may provide a means to overcome this issue and enable staff to share experiences and learn from them. In this paper, we study two different data sets from two software systems to support online collaborative reflection in order to analyze what possible factors influence the occurrence of aspects of reflection in online discussions, like experiences, suggestions and learning. Our results include findings that partially approve existing models of (collaborative) reflection, but also others that add to or even challenge these models. Overall, we found that collaborative reflection may take different paths towards learning. From this we derive that facilitation mechanisms need to take up these paths, and that facilitation may be successful in different ways than anticipated from existing literature. We describe possible facilitation mechanisms and discuss their implementation. [ABSTRACT FROM AUTHOR]