Working Paper Article Version 1 This version is not peer-reviewed

Model for the Collection and Analysis of Data from Teachers and Students, Supported by Academic Analytics

Version 1 : Received: 18 July 2020 / Approved: 19 July 2020 / Online: 19 July 2020 (20:37:39 CEST)

How to cite: Simanca H., F.A.; Hernández Arteaga, I.; Unriza Puin, M.E.; Blanco Garrido, F.; Paez Paez, J.; Cortes Méndez, J. Model for the Collection and Analysis of Data from Teachers and Students, Supported by Academic Analytics. Preprints 2020, 2020070437 Simanca H., F.A.; Hernández Arteaga, I.; Unriza Puin, M.E.; Blanco Garrido, F.; Paez Paez, J.; Cortes Méndez, J. Model for the Collection and Analysis of Data from Teachers and Students, Supported by Academic Analytics. Preprints 2020, 2020070437

Abstract

Business Intelligence, defined by [1] as "the ability to understand the interrelations of the facts that are presented in such a way that it can guide the action towards achieving a desired goal", has been used since 1958 for the transformation of data into information, and of information into knowledge, to be used when making decisions in a business environment. But, what would happen if we took the same principles of business intelligence and applied them to the academic environment? The answer would be the creation of Academic Analytics, a term defined by [2] as the process of evaluating and analyzing organizational information from university systems for reporting and making decisions, whose characteristics allow it to be used more and more in institutions, since the information they accumulate about their students and teachers gathers data such as academic performance, student success, persistence, and retention [5]. Academic Analytics enables an analysis of data that is very important for making decisions in the educational institutional environment, aggregating valuable information in the academic research activity and providing easy to use business intelligence tools. This article shows a proposal for creating an information system based on Academic Analytics, using ASP.Net technology and trusting storage in the database engine Microsoft SQL Server, designing a model that is supported by Academic Analytics for the collection and analysis of data from the information systems of educational institutions. The idea that was conceived proposes a system that is capable of displaying statistics on the historical data of students and teachers taken over academic periods, without having direct access to institutional databases, with the purpose of gathering the information that the director, the teacher, and finally the student need for making decisions. The model was validated with information taken from students and teachers during the last five years, and the export format of the data was pdf, csv, and xls files. The findings allow us to state that it is extremely important to analyze the data that is in the information systems of the educational institutions for making decisions. After the validation of the model, it was established that it is a must for students to know the reports of their academic performance in order to carry out a process of self-evaluation, as well as for teachers to be able to see the results of the data obtained in order to carry out processes of self-evaluation, and adaptation of content and dynamics in the classrooms, and finally for the head of the program to make decisions.

Subject Areas

Academic Analytics; data storage; education and big data; analysis of data; learning analytics

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