In this paper we analyse the way students tag recorded lectures. We compare their tagging strategy and the tags that they create with tagging done by an expert. We look at the quality of the tags students add, and we introduce a method of measuring how similar the tags are, using vector space modelling and cosine similarity. We show that the quality of tagging by students is high enough to be useful. We also show that there is no generic vocabulary gap between the expert and the students. Our study shows no statistically significant correlation between the tag similarity and the indicated interest in the course, the perceived importance of the course, the number of lectures attended, the indicated difficulty of the course, the number of recorded lectures viewed, the indicated ease of finding the needed parts of a recorded lecture, or the number of tags used by the student.
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This study analyses the interactions of students with the recorded lectures. We report on an analysis of students' use of recorded lectures at two Universities in the Netherlands. The data logged by the lecture capture system (LCS) is used and combined with collected survey data. We describe the process of data pre-processing and analysis of the resulting full dataset and then focus on the usage for the course with the most learner sessions. We found discrepancies as well as similarities between students' verbal reports and actual usage as logged by the recorded lecture servers. The analysis shows that recorded lectures are viewed to prepare for exams and assignments. The data suggests that students who do this have a significantly higher chance of passing the exams. Given the discrepancies between verbal reports and actual usage, research should no longer rely on verbal reports alone.
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A lot of research into the use of recorded lectures has been done by using surveys or interviews. We will show that triangulation of multiple data sources is needed. We will discuss how students use recorded lectures according to their self-report and what actual usage of the recorded lectures can be derived from the data on the system. We will present the data collections and cover areas where the data can be triangulated to increase the credibility of the results or to question the students' responses. The triangulation shows that we lack data for a number of areas. We will need high-quality surveys and interviews combined with the log data to get a complete picture. We need to be able to link data sets together based on the identification of the individual students, which might raise privacy issues.
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