STUMS 2014 - First International Workshop on Semantic Technologies in Ubiquitous, Massive and Smart Learning (STUMS 2014)

Website stums2014.altervista.org/WS2014 | Edit Freely

Category STUMS 2014

Deadline: May 01, 2014 | Date: September 10, 2014-September 12, 2014

Venue/Country: SALERNO, Italy

Updated: 2014-03-22 00:04:49 (GMT+9)

Call For Papers - CFP

Ubiquitous Learning allows a person to learn anytime and anywhere, thus it is considered as the next generation e-learning. Ubiquitous Learning potentially overcomes the limitations of e-learning by building serendipitous, seamless, creative, novel, high degree of autonomy and learner-centered learning environments which are not subject to the constraints of space and time and exploit context and situation awareness to improve the learning process. So, ubiquitous learning environments are settings for pervasive learning, where the learning experiences "immerse" learners who are involved in formal as well as informal (intentional or accidental) activities. The concept of Ubiquitous Learning derives from the Ubiquitous Computing that is usually associated with a large number of small devices (which have computation and communication capabilities) such as smartphones, tablets, glasses, sensor network nodes, and other technologies like, for instance, NFC (Near Field Communication) or Bluetooth 4.0 which are being used in our daily life.

MOOCs (massive open online courses) are, typically, free courses deployed over the Web, that are away from the traditional classrooms and support a huge number of enrolled students (even thousands of students per course). In successful MOOCs, we can find authentic strong communities, including learners who desire to master content and instructors (teachers, tutors, coaches, etc.) who help learners to succeed in their challenges. A MOOC usually provides a course syllabus, a set of video lectures (possibly associated with transcripts), weekly activities, quizzes, Q&A sessions, links to many of the freely available resources that are needed and projects. Coursera, edX, Udacity, Khan Academy and Udemy are just a few among the existing MOOC Platforms. In this context, some drawbacks emerge: MOOCs are also very expensive to create (e.g. costs of video lectures, tutoring, etc.), MOOC dropout rate is 90%, there is no real interoperability among different MOOC Platforms and among MOOCs and formal University Curricula.

Smart Learning Environments represent a new frontier for educational systems which aim at achieving the effective synergy among pedagogy, technology and their fusion in order to improve learning processes. A learning environment can be considered smart when the learner is supported, for instance, by “adaptive” and “intelligent” technologies which follow the learner from childhood to their adult life, at work, through formal, non-formal and informal learning activities. Among the most important features of a smart learning environment it is important to underline that it offers a high degree of autonomy, adapts itself when context changes, and communicates with learners by means of natural interfaces. Intelligent, context-aware and semantic technologies are able to reduce the amount of interaction required by the learners. These capabilities can also provide important features such as the detection of anomalous behaviors during the learning process.

The main goal of this workshop is to bring together researchers and practitioners who are interested in addressing issues and challenges related to Ubiquitous Learning, MOOCs and Smart Learning Environments mostly by leveraging on Semantic Technologies and Computational Intelligence techniques. Interdisciplinary works (e.g. fusion of pedagogies and technologies), theoretical papers and papers describing practical experiences (also in designing and developing systems and applications) will be welcome.

Topics of interest include but are not limited to:

Integration and Interoperability for Seamless Learning

Storage, Inference and Querying strategies for Semantic Data in Cloud

Semantic Web in Big Data and Learning Analytics

Extracting Actionable Knowledge from Learning Resources

Educational Data Mining to face dropouts and increase Engagement and Motivation

Affective Computing and Emotion Detection in Smart Learning Environments

Situation, Context, Learner and Group Modeling

Ontology-driven methodologies and tools for Content Authoring and Instructional Design

Modeling and Reasoning Approaches for Competences, Competencies and Capabilities

Reasoning with Semantic Web-based Metadata and Ontologies for Learning Resources

Adaptive/Personalized Learning and Intelligent Tutoring Systems

Context-awareness and Situation-awareness in Smart and Ubiquitous Learning Systems

Social Semantic Web as Enabling Platform for MOOCs and MOOC Networks

Internet of Things support for Learning and Smart Learning Environment

Semantic and Social Sensor Networks support for Situation Assessment in Learning Scenarios

Semantic, Mobile and Gesture-based Interfaces

Social and Semantic Technologies to enable Serendipitous Learning

Collective Knowledge supporting (semi) automatic generation of Learning Content