No abstract
We compared discussion posts from a data science ethics MOOC that was hosted on two platforms. We characterized one platform as “open” because learners can respond to discussion prompts while viewing and responding to others. We characterized the other platform as “locked” because learners must respond to a discussion prompt before they can view and respond to others. Our objective is to determine whether these platform differences are consequential and have the potential to impact learning. We analyzed direct responses to two discussion prompts from two modules located in modules two and six of an eight module course. We used conventional content analysis to derive codes directly from the data. Posts on the “open” platform were characterized by failure to completely address the prompt and showed evidence of persuasion tactics and reflective activity. Posts on the “locked” platform were characterized by an apparent intent to complete the task and an assertive tone. Posts on the “locked” platform also showed a diversity of ideas through the corpus of responses. Our findings show that MOOC platform interfaces can lead to qualitative differences in discussion posts in ways that have the potential to impact learning. Our study provides insight into how “open” and “locked” platform designs have the potential to shape ways that learners respond to discussion prompts in MOOCs. Our study offers guidance for instructors making decisions on MOOC platform choice and activities situated within a learning experience.We used conventional content analysis to derive codes directly from the data. Posts on the “open” platform were characterized by failure to completely address the prompt and showed evidence of persuasion tactics and reflective activity. Posts on the “locked” platform were characterized by an apparent intent to complete the task and an assertive tone. Posts on the “locked” platform also showed a diversity of ideas through the corpus of responses. Our findings show that MOOC platform interfaces can lead to qualitative differences in discussion posts in ways that have the potential to impact learning. Our study provides insight into how “open” and “locked” platform designs have the potential to shape ways that learners respond to discussion prompts in MOOCs. Our study offers guidance for instructors making decisions on MOOC platform choice and activities situated within a learning experience.
Background: Select and enact appropriate learning tactics that advance learning has been considered a critical set of skills to successfully complete highly flexible online courses, such as Massive open online courses (MOOCs). However, limited by analytic methods that have been used in the past, such as frequency distribution, sequence mining and process mining, we lack a deep, complete and detailed understanding of the learning tactics used by MOOC learners.Objectives: In the present study, we proposed four major dimensions to better interpret and understand learning tactics, which are frequency, continuity, sequentiality and role of learning actions within tactics. The aim of this study was to examine to what extent can a new analytic technique, the ordered network analysis (ONA), deepen the understanding of MOOC learning tactics compared to using other methods. Methods:In particular, we performed a fine-grained analysis of learning tactics detected from more than 4 million learning events in the behavioural trace data of 8788 learners who participated in a large-scale MOOC 'Flipped Classroom'. Results and Conclusions:We detected eight learning tactics, and then chose one typical tactic as an example to demonstrate how the ONA technique revealed all four dimensions and provided deeper insights into this MOOC learning tactic. Most importantly, based on the comparison with different methods such as process mining, we found that the ONA method provided a unique opportunity and novel insight into the roles of different learning actions in tactics which was neglected in the past.Takeaway: In summary, we conclude that ONA is a promising technique that can benefit the research on learning tactics, and ultimately benefit MOOC learners by strengthening the strategic support.
We explore new tools and methods for learning designers and researchers to characterize pedagogical approaches that are applied to the design of MOOCs. This paper makes three main contributions to literature on MOOC design and evaluation: (1) an Expanded Assessing MOOC Pedagogies instrument for use by learning designers and researchers within their own contexts, (2) a demonstration of how nearest neighbor cluster analysis can be used to identify pedagogically similar MOOCs, and (3) a preliminary analysis of the clusters to account for features and factors that contribute to pedagogical similarity of MOOCs within clusters. This work advances research in the development of MOOC typologies, to allow learning designers and researchers to ask nuanced questions about pedagogical aspects of MOOC design.
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