WLA 2014 - 1st Workshop on Learning Analytics (WLA 2014)

Educational data analysis oriented towards decision making and improvement of educational processes, also known as Learning Analytics or Academic Analytics, has raised increasing interest among researchers and other educational agents and stakeholders.
The idea behind Learning Analytics is that the large volumen of data (popularly known as big data) used in ICT-based educational processes is far too high to be useful for decision making without further processing. Therefore, application of adequate data mining, analysis and visualization techniques is required in order to better understand educational processes and support decision making for all agents involved: teachers, students, course designers and educational institutions.
To this day, these techniques have focused on the relation between data recorded in e-learning systems, such as Learning Management Systems (LMS) or Virtual Learning Environments (VLEs). Nevertheless, the emergence of other ICT-based learning modalities, such as Massive Online Open Courses (MOOCs) or Personal Learning Environments (PLEs) have given new impulse to this field of study.
The interest on Learning Analytics has gathered researchers from many different fields. Thus, scholars from very different areas, such as computing, information systems, education, psychology, statistics, semantic and network analysis, among others, are orienting their efforts towards the application of different techniques and approaches aimed to study and understand the information extracted from educational data, as well as the improvement of training and educational processes.
Some examples of these improvements are focused on increase of students’ academic performance and achievement, the design of early-warning systems to predict and lower attrition rates, automation of adaptive educational systems, visualization of aggregated data, enhancement of social dynamics or the use of recommendation systems for training and education.
However, current research is astoundingly disperse in terms of application field and scope. And this dispersion hinders in most cases generalizability of results. Thus, it is possible at this time to come across empirical studies on Learning Analytics in settings as small as a single course with few students, and analysis of a great number of courses with thousands of students in MOOCs or large organizations.
Furthermore, determining the adequacy of one or another approach to the analysis of educational data becomes a difficult task. Hence, while analyses based on small datasets (small data) may offer very detailed information for specific settings, the analysis of big data may provide relevant information for wider scope course management. Even more, as of now there is no consensus on a valid criterion to determine the limit between small and big data.
Because of the many different approaches to Learning Analytics, the main objective of this Workshop is to bring together the multiple perspectives and disciplines and establish a common framework of Learning Analytics practices and research experiences in this field.
As a result of this approximation of different approaches, two main results are expected from the research contributions in this Workshop: first, the sharing of Learning Analytics initiatives as a first step towards fostering and strengthening collaboration among participants, aiming for a wider generalizability of results; and second, the comparison between research based on small data and big data may offer a space to debate and find common issues which facilitate future investigation of issues in Learning Analytics.
Topics
As a summary of the preceding discussion, the following topics of interest are proposed for this Workshop:
? Differences between small data and big data in Learning Analytics
? Replication of studies based on big data using small data, and vice versa
? Application of Learning Analytics for decision making
? Representation and visualization of educational data
? Learning Analytics for automation of educational processes.
? Algorithms, procedures and application of educational data mining techniques in Learning Analytics
? Educational recommender systems based on Learning Analytics
? Application of Learning Analytics as support to policy making in educational institutions
? Semantic analysis applied to Learning Analytics
? Social network analysis of educational processes
? Integration of PLEs data in Learning Analytics
? Influence of psycho-social factors in learning processes using Learning Analytics
? Analysis of curriculum data for in Learning Analytics
Submissions
All papers must follow the formatting rules (DOT, PDF) and be written in Portuguese, Spanish or English.
The version of papers for evaluation by the Scientific Committee should not include any identification, e-mail or affiliation of the authors. This information should only be available in the final version of papers accepted for presentation and publication.
The evaluation version of the papers should be saved in PDF. However, the final version for publication must be saved in Word format.
Submissions should be sent to https://www.easychair.org/conferences/?conf=cisti2...
Important Dates
? Deadline for paper submission: February 22, 2014
? Notification of paper acceptance: March 29, 2014
? Deadline for final versions and conference registration: April 12, 2014
? Deadline for Workshop final papers delivery to CISTI organizers: April 19, 2014
? Conference dates: June 18-21, 2014
Organizing Committee
? Francisco J. García Peñalvo ( fgarcia-AT-usal.es)
o Instituto de Ciencias de la Educación (IUCE). Grupo de investigación GRIAL. Universidad de Salamanca (Spain).
? Ángel Hernández García ( angel.hernandez-AT-upm.es)
o Departamento de Ingeniería de Organización, Administración de Empresas y Estadística. Universidad Politécnica de Madrid (Spain).
? Miguel Ángel Conde González ( miguel.conde-AT-unileon.es)
o Departamento de Ingenierías Mecánica, Informática y Aeroespacial. Universidad de León (Spain).
Program Committee
? Dr. Aitor Almeida
o Universidad de Deusto (Spain).
? Dr. Gustavo Ribeiro Alves
o Instituto Superior de Engenharia do Porto (Portugal).
? Dr. Sergio Araya Guzmán
o Universidad del Bío-Bío (Chile)
? Dr. Hector Gonzalo Barbosa León
o Instituto Tecnológico de Colima (Mexico).
? Dr. Miguel Ángel Conde González
o Universidad de León (Spain).
? Dr. Adam Cooper
o Institute for Educational Cybernetics. University of Bolton (United Kingdom).
? Dr. Camino Fernández Llamas
o Universidad de León (Spain).
? Dr. Baltasar Fernández Manjón
o Universidad Complutense de Madrid (Spain).
? Dr. Antonio Fumero Reverón
o Universidad Politécnica de Madrid (Spain).
? Dr. Francisco J. García-Peñalvo
o Universidad de Salamanca (Spain).
? Dra. Inés González González
o Universitat Oberta de Catalunya (Spain).
? Dr. Ángel Hernández-García
o Universidad Politécnica de Madrid (Spain).
? Dr. José Antonio Jerónimo Montes
o Universidad Nacional Autónoma de México (Mexico).
? Dra. Ana Isabel Jiménez Zarco
o Universitat Oberta de Catalunya (Spain).
? Dr. Mark Johnson
o Institute for Educational Cybernetics. University of Bolton (United Kingdom).
? Dra. Maria Arcelina Marques
o Instituto Superior de Engenharia do Porto (Portugal).
? Dr. Vicente Matellán Olivera
o Universidad de León (Spain).
? Dr. Milos Milovanovic
o Laboratory for Multimedia Communications. University of Belgrade (Serbia).
? Dr. Miroslav Minovic
o Laboratory for Multimedia Communications. University of Belgrade (Serbia).
? Dr. José Adriano Pires
o Instituto Superior de Engenharia do Porto (Portugal).
? Dr. Salvador Ros Muñoz
o Universidad Nacional de Educación a Distancia (Spain).
? Dr. Roberto Therón
o Universidad de Salamanca (Spain).
? Dra. Clara Viegas
o Instituto Superior de Engenharia do Porto (Portugal).
? Ángel Francisco Agudo-Peregrina
o Universidad Politécnica de Madrid (Spain).