Assessment of Learning Achievements in Higher Education Using Moodle Virtual Classrooms and H5P: A Case Study

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Abstract
The assessment of learning achievements is a topic of great interest and has been widely addressed in educational institutions worldwide. Especially in the university context, it is a topic that has been widely addressed from different perspectives using quantitative and qualitative tools. This study presents the evaluation model for the achievement of learning outcomes in the Food Engineering career of the State Polytechnic University of Carchi, which is carried out at the end of each academic period by applying a structured test in each subject at each level. The data addressed in this study correspond to the academic period 2022A, which was collected in a database and processed using a proposed protocol of statistical tests composed of Mahalanobis distances as data processing technique and Kruskal-Wallis and Dunn- Šidák tests as tests for differences. The results show that the data collected through structured tests for the evaluation of learning achievements are susceptible to the presence of atypical observations and generally present a non-parametric behavior, so the application of data processing techniques before inferential analysis it's of vital importance. Furthermore, it has been found that not all subjects or levels tested show significant differences so subjects showing lower performance should only be classified as having learning problems if the differences observed by a statistical test are significant. In addition, the use of mean, median, mode, and trimmed mean as metrics for comparing attainment was compared and it was found that the most appropriate metrics for this task were the median and the trimmed mean.

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