Tuesday, May 21, 2019

[DMANET] Special Issue "Advanced Techniques in the Analysis and Prediction of Students' Behaviour in Technology-Enhanced Learning Contexts"

Special Issue "Advanced Techniques in the Analysis and Prediction of
Students' Behaviour in Technology-Enhanced Learning Contexts"

Applied Sciences
ISSN: 2076-3417 / Impact factor (2017): 1.689
Section "Computing and Artificial Intelligence"

Special Issue Information:
Dear Colleagues,

Analysing and predicting individuals' behaviour are important topics in
academic environments, especially after the increasing development and
deployment of software tools for supporting learning stages. The automation
of many processes involved in the usual students' activity allows for
processing massive volumes of data collected from teaching-enhanced
learning (TEL) platforms, leading to useful applications for academic
personnel. In this way, monitoring and analysing students' behaviour are
key activities required for the improvement of students' learning.
Recommendations of activities, dropout prediction, performance and
knowledge analysis, and resources optimization, among other
students-centred interests, are complex tasks that involve many elements
that need to be considered. Therefore, it becomes necessary that these
efforts search for support from other fields in the 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 intelligent systems, 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 the analysis and prediction of the students' behaviour in
academic contexts.
This Special Issue provides a collection of papers of original advances in
the analysis, prediction, and recommendation of applications propelled by
artificial intelligence, 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
Guest Editors

Teaching-enhanced learning and teaching
Personalized learning
Intelligent tutoring Systems
Data mining and big data analysis
Intelligent systems
Machine and deep learning
Recommender systems
Collaborative filtering
Software tools
Performance prediction
Knowledge analysis

Deadline for manuscript submissions:
30 November 2019

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

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 1500 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.

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