CALL FOR PAPERS

Special Issue "Data Analytics and Machine Learning in Education"

Applied Sciences
ISSN: 2076-3417 / Impact factor (2020): 2.679 (Q2)
Section "Computing and Artificial Intelligence"

https://www.mdpi.com/journal/applsci/special_issues/Data_Analytics_Machine_Learning


Special Issue Information:
==========================

Dear Colleagues,

The generalization of the use of advanced technological tools in the field of educational is leading to the generation of big data related to academic activities which involve students and teachers. For example, the inclusion of virtual campuses as a regular educational management tool encourages the virtualization of teaching, the online management of grades, the monitoring of student progress, the recording of all kinds of educational variables, etc. In this way, technology-enhanced learning (TEL) platforms allow one to generate and store data that stand out, not only for their huge amount and heterogeneity, but above all, for their link to a time dimension that allows one to analyze and predict student behaviour in its dynamic context, among other purposes.

There are many interesting research lines that deserve to be explored in the education area, such as analyzing and predicting students' behaviour, developing advanced tools for supporting learning stages, recommending activities, predicting dropout, optimizing resources, etc. For these purposes, there are advanced methods from computational science that have demonstrated a high effectiveness when handling data and processes that are strongly interconnected. Data mining, big data, machine learning, deep learning, collaborative filtering, and recommender systems, among other fields related to artificial intelligence, allow for the development of advanced techniques that provide a significant potential for the above purposes, leading to new applications and more effective approaches in academic analysis and prediction.

This Special Issue provides a collection of papers of original advances in the analysis, prediction, and recommendation of applications propelled by artificial intelligence, data science, data analytics, big data, and machine learning, especially in the TEL context. Papers about these topics are welcomed.

Prof. Dr. Juan A. Gómez-Pulido
Prof. Dr. Young Park
Prof. Dr. Ricardo Soto
Prof. Dr. José M. Lanza-Gutiérrez
Guest Editors


Keywords:
=========

Technology-enhanced learning and teaching
Personalized learning
Intelligent tutoring Systems
Data science and analytics
Data mining and big data analysis
Intelligent systems
Machine and deep learning
Recommender systems
Collaborative filtering
Deep learning-based recommendations
Review-based recommendations
Performance prediction
Knowledge analysis
Optimization


Deadline for manuscript submissions:
====================================

15 January 2022


Special Issue Editors:
======================

Prof. Dr. Juan A. Gómez-Pulido
Department of Technologies of Computers and Communications, Universidad de Extremadura, Cáceres, Spain

Prof. Dr. Young Park
Department of Computer Science and Information Systems, Bradley University, Peoria, IL 61625, USA

Prof. Dr. Ricardo Soto
School of Computer Engineering, Pontificia Universidad Católica de Valparaíso, Valparaiso, Chile

Prof. Dr. José M. Lanza-Gutiérrez
Department of Computer Sciences, University of Alcala, Alcala de Henares, Spain


Manuscript Submission Information:
==================================

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.