In this work we use the software IntelliBoard to obtain from the Moodle platform analytical reports regarding to what the statistical data gives about the student progress in the subject “Infinitesimal Calculus” taught in the Computer Science Degree during the academic year 2019/20.During this course the University of Extremadura has developed a pilot project consisting of the integration of the Intelliboard tool in the virtual classroom of some subjects belonging to different degrees. These virtual spaces are housed in the Moodle platform. By using the software IntelliBoard this project pretends to obtain analytical data about the student learning trajectory in the subject.One of the subjects that participates in the pilot project is “Infinitesimal Calculus” taught in the first Computer Engineering course to 155 students. Calculus is one of the theoretical bases in Engineering since it plays an essential role for the particular knowledge and the reasoning skills underlying later key concepts. However, this mathematical discipline presents an abstract nature which normally represents learning difficulties, especially because in general it is scheduled in the first course of the engineering degrees. In order to improve the teaching of the subject “Calculus” the software IntelliBoard has been integrated in its virtual classroom.IntelliBoard is an easy use software that provides analytical and reporting learning services in the form of printable charts, graphs and analyzes. Some reports that we can collected from the Calculus Moodle virtual classroom thanks to IntelliBoard are regarding to:- Qualification of activities by dates- Activity statistics- Engaged / not engaged per course- Student status- Student success- Inactive users- Content utilization.In order to identify at-risk learners we analyze and interpret reports, assignments, analytics, notifications and material intended for the evaluation of each lesson provided by the IntelliBoard software. The information contained in the IntelliBoard reports can be collected in an excel table and analyzed descriptively with the aim to studied numerically how each activity influence the final evaluation results of the subject through the statistical analysis of their influence by studying the correlation between the variables involved. These conclusions allows us to implement alternative learning methodologies that will be adapted to any kind of student or even modify those activities that should be reviewed due to their difficulty or inefficiency in learning key concepts.
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