Big Data representation for grade analysis through Hadoop framework

Verma, Chitresh; Pandey, Rajiv

doi:10.1109/confluence.2016.7508134

Cited by 22 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…ML works in conjunction with Big data to establish academic recommendation and monitoring systems. In addition, there are traditional systems that are in continuous generation of information such as LMS, academic and financial systems ( Verma & Pandey, 2016 ). All the volume and variety of data is processed by a Big data framework that is responsible for generating knowledge of the data.…”

Section: Methodsmentioning

confidence: 99%

Proposal of a remote education model with the integration of an ICT architecture to improve learning management

Villegas-Ch

García-Ortiz

Román-Cañizares

et al. 2021

PeerJ Computer Science

View full text Add to dashboard Cite

University education is at a critical moment due to the pandemic generated by the Coronavirus Disease 2019. Universities, to guarantee the continuity of education, have considered it necessary to modify their educational models, implementing a transition towards a remote education model. This model depends on the use of information and communication technologies for its execution and the establishment of synchronous classes as a means of meeting between teachers and students. However, moving from face-to-face classes to online classes is not enough to meet all the needs of students. By not meeting the needs and expectations of students, problems are generated that directly affect learning. In this work, Big data and artificial intelligence are integrated as a solution in a technological architecture that supports the remote education model. This integration makes it possible to identify the state of learning and recommend immediate actions to its actors. Teachers, knowing the variables that affect academic performance, have the ability to change the components of learning or the method used. Improving learning and validating the capacity of information technologies to generate digital environments suitable for the generation of knowledge. In addition to improving the functionality of educational models and their adaptability to the new normal.

show abstract

Section: Methodsmentioning

confidence: 99%

Proposal of a remote education model with the integration of an ICT architecture to improve learning management

Villegas-Ch

García-Ortiz

Román-Cañizares

et al. 2021

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…These sources are important to determine the student's situation regarding her performance and if this has any inconvenience, the framework crosses the data from all sources to determine where the problem originates. Other sources are sensor and actuator systems [42]. The information they generate is specifically from the interaction of students with the university campus.…”

Section: Data Analysis Architecturementioning

confidence: 99%

Analysis of Educational Data in the Current State of University Learning for the Transition to a Hybrid Education Model

et al. 2021

View full text Add to dashboard Cite

Currently, the 2019 Coronavirus Disease pandemic has caused serious damage to health throughout the world. Its contagious capacity has forced the governments of the world to decree isolation and quarantine to try to control the pandemic. The consequences that it leaves in all sectors of society have been disastrous. However, technological advances have allowed people to continue their different activities to some extent while maintaining isolation. Universities have great penetration in the use of technology, but they have also been severely affected. To give continuity to education, universities have been forced to move to an educational model based on synchronous encounters, but they have maintained the methodology of a face-to-face educational model, what has caused several problems in the learning of students. This work proposes the transition to a hybrid educational model, provided that this transition is supported by data analysis to identify the new needs of students. The knowledge obtained is contrasted with the performance presented by the students in the face-to-face modality and the necessary parameters for the transition to this modality are clearly established. In addition, the guidelines and methodology of online education are considered in order to take advantage of the best of both modalities and guarantee learning.

show abstract

“…There are different tools for managing big data-Hadoop (standard framework for storing large volumes of data and subsequent distributed processing in clusters) and Spark (seen as a natural evolution of Hadoop analytics in search of more optimized models) stand out for their functionality. The two frameworks belong to the Apache project and are open source [22].…”

Section: Big Datamentioning

confidence: 99%

Data Analysis as a Tool for the Application of Adaptive Learning in a University Environment

et al. 2020

View full text Add to dashboard Cite

Currently, data are a very valuable resource for organizations. Through analysis, it is possible to profile people or obtain knowledge about an event or environment and make decisions that help improve their quality of life. This concept takes on greater value in the current pandemic, due to coronavirus disease 2019 (COVID-19), that affects society. This emergency has changed the way people live. As a result, the majority of activities are carried out using the internet, virtually or online. Education is not far behind and has seen the web as the most successful option to continue with its activities. The use of any computer application generates a large volume of data that can be analyzed by a big data architecture in order to obtain knowledge from its students and use it to improve educational processes. The big data, when included as a tool for adaptive learning, allow the analysis of a large volume of data to offer an educational model based on personalized education. In this work, the analysis of educational data through a big data architecture is proposed to generate learning based on meeting the needs of students.

show abstract

Big Data representation for grade analysis through Hadoop framework

Cited by 22 publications

References 8 publications

Proposal of a remote education model with the integration of an ICT architecture to improve learning management

Proposal of a remote education model with the integration of an ICT architecture to improve learning management

Analysis of Educational Data in the Current State of University Learning for the Transition to a Hybrid Education Model

Data Analysis as a Tool for the Application of Adaptive Learning in a University Environment

Contact Info

Product

Resources

About