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Learning analytics and performance indicators in higher education

机译：学习高等教育中的分析和绩效指标

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The availability of large amounts of information associated with the teaching and learning process challenges researchers to explore this information by using learning analytics to obtain indicators that can contribute to improving the teaching and learning process, particularly in terms of learning outcomes and the relationship students have with the educational institutions they attend. Considering that failure and dropping out of school have very negative consequences for a large number of young people, we have sought to obtain indicators associated with these problems through the use of quantitative methodology and documental analysis procedures, by analyzing data from a sample of 1588 students with regard to their frequency of access to the virtual environment of the institution, the number of presences in onsite lessons, the number of course units they passed and the average mark in the course units they passed. From the obtained results, we emphasize that there is a degree of positive association, with moderate correlation, between each pair of the mentioned variables. After organizing the sample in four distinct groups resulting from the division of the data regarding the number of accesses to the institution virtual environment into quartiles, it was found that there are significant differences regarding the number of course units passed between the groups with higher numbers of accesses to the virtual learning environment and the ones with lower numbers of accesses, to the benefit of the groups with the greatest number of accesses.
机译：与教与学过程相关的大量信息的挑战性要求研究人员通过使用学习分析方法来获取这些信息，以获取有助于改善教与学过程的指标，特别是在学习成果和学生与学生之间的关系方面他们参加的教育机构。考虑到失败和辍学对许多年轻人有非常不利的影响，我们通过分析1588名学生样本中的数据，寻求通过定量方法和文献分析程序来获得与这些问题相关的指标关于他们访问机构虚拟环境的频率，现场课程的出席人数，通过的课程单元数以及通过的课程单元的平均分数。从获得的结果中，我们强调在每对提到的变量之间存在一定程度的正相关，且具有适度的相关性。在将有关对机构虚拟环境的访问次数的数据划分为四分位数后，将样本分为四个不同的组，然后发现，在具有较高数量的组之间通过的课程单元数存在显着差异访问虚拟学习环境以及访问次数较少的环境，以使访问次数最多的组受益。

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