Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations
The pandemic crisis has forced the development of teaching and evaluation activities exclusively online. In this context, the emergency remote teaching (ERT) process, which raised a multitude of problems for institutions, teachers, and students, led the authors to consider it important to design a m...
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Format: | Article |
Language: | English |
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MDPI AG
2021-11-01
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Series: | Sensors |
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Online Access: | https://www.mdpi.com/1424-8220/21/23/7998 |
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author | Emilia Corina Corbu Eduard Edelhauser |
author_facet | Emilia Corina Corbu Eduard Edelhauser |
author_sort | Emilia Corina Corbu |
collection | DOAJ |
description | The pandemic crisis has forced the development of teaching and evaluation activities exclusively online. In this context, the emergency remote teaching (ERT) process, which raised a multitude of problems for institutions, teachers, and students, led the authors to consider it important to design a model for evaluating teaching and evaluation processes. The study objective presented in this paper was to develop a model for the evaluation system called the learning analytics and evaluation model (LAEM). We also validated a software instrument we designed called the EvalMathI system, which is to be used in the evaluation system and was developed and tested during the pandemic. The optimization of the evaluation process was accomplished by including and integrating the dashboard model in a responsive panel. With the dashboard from EvalMathI, six online courses were monitored in the 2019/2020 and 2020/2021 academic years, and for each of the six monitored courses, the evaluation of the curricula was performed through the analyzed parameters by highlighting the percentage achieved by each course on various components, such as content, adaptability, skills, and involvement. In addition, after collecting the data through interview guides, the authors were able to determine the extent to which online education during the COVID 19 pandemic has influenced the educational process. Through the developed model, the authors also found software tools to solve some of the problems raised by teaching and evaluation in the ERT environment. |
first_indexed | 2024-03-10T04:45:04Z |
format | Article |
id | doaj.art-0bde39d58566478eac3538365debfefd |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-03-10T04:45:04Z |
publishDate | 2021-11-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-0bde39d58566478eac3538365debfefd2023-11-23T03:02:27ZengMDPI AGSensors1424-82202021-11-012123799810.3390/s21237998Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching SituationsEmilia Corina Corbu0Eduard Edelhauser1Department of Mathematics and Informatics, University of Petrosani, 332003 Petrosani, RomaniaDepartment of Management and Industrial Engineering, University of Petrosani, 332003 Petrosani, RomaniaThe pandemic crisis has forced the development of teaching and evaluation activities exclusively online. In this context, the emergency remote teaching (ERT) process, which raised a multitude of problems for institutions, teachers, and students, led the authors to consider it important to design a model for evaluating teaching and evaluation processes. The study objective presented in this paper was to develop a model for the evaluation system called the learning analytics and evaluation model (LAEM). We also validated a software instrument we designed called the EvalMathI system, which is to be used in the evaluation system and was developed and tested during the pandemic. The optimization of the evaluation process was accomplished by including and integrating the dashboard model in a responsive panel. With the dashboard from EvalMathI, six online courses were monitored in the 2019/2020 and 2020/2021 academic years, and for each of the six monitored courses, the evaluation of the curricula was performed through the analyzed parameters by highlighting the percentage achieved by each course on various components, such as content, adaptability, skills, and involvement. In addition, after collecting the data through interview guides, the authors were able to determine the extent to which online education during the COVID 19 pandemic has influenced the educational process. Through the developed model, the authors also found software tools to solve some of the problems raised by teaching and evaluation in the ERT environment.https://www.mdpi.com/1424-8220/21/23/7998online educationlearning analyticsemergency remote teachingresponsive dashboardeLearning and digital transformation of educationIT for education |
spellingShingle | Emilia Corina Corbu Eduard Edelhauser Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations Sensors online education learning analytics emergency remote teaching responsive dashboard eLearning and digital transformation of education IT for education |
title | Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations |
title_full | Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations |
title_fullStr | Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations |
title_full_unstemmed | Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations |
title_short | Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations |
title_sort | responsive dashboard as a component of learning analytics system for evaluation in emergency remote teaching situations |
topic | online education learning analytics emergency remote teaching responsive dashboard eLearning and digital transformation of education IT for education |
url | https://www.mdpi.com/1424-8220/21/23/7998 |
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