Architecture of a system for context-based adaptation in m-learning

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. E. Martin, N. Andueza, and R.M. Carro, “Architecture of a system for context-based adaptation in m-learning”, in Conference on Advanced Learning Technologies, 2006. Sixth International, Kerkrade, 2006, pp. 252-254In this paper, the architecture of a system that supports context-based adaptation for m-learning is presented. This system manages data about users and activities so that the most suitable activities to be accomplished at each time are proposed to each user. This decision is not only based on the user's personal features, preferences or previous actions but also on information about the specific user's context, including spare time, location and available devicesThis work has been funded by the Spanish Ministry of Science and Education, project TIN2004-0314

Augmented Reality and Context Awareness for Mobile Learning Systems

Learning is one of the most interactive processes that humans practice. The level of interaction between the instructor and his or her audience has the greatest effect on the output of the learning process. Recent years have witnessed the introduction of e-learning (electronic learning), which was then followed by m-learning (mobile learning). While researchers have studied e-learning and m-learning to devise a framework that can be followed to provide the best possible output of the learning process, m-learning is still being studied in the shadow of e-learning. Such an approach might be valid to a limited extent, since both aims to provide educational material over electronic channels. However, m-learning has more space for user interaction because of the nature of the devices and their capabilities. The objective of this work is to devise a framework that utilises augmented reality and context awareness in m-learning systems to increase their level of interaction and, hence, their usability. The proposed framework was implemented and deployed over an iPhone device. The implementation focused on a specific course. Its material represented the use of augmented reality and the flow of the material utilised context awareness. Furthermore, a software prototype application for smart phones, to assess usability issues of m-learning applications, was designed and implemented. This prototype application was developed using the Java language and the Android software development kit, so that the recommended guidelines of the proposed framework were maintained. A questionnaire survey was conducted at the University, with approximately twenty-four undergraduate computer science students. Twenty-four identical smart phones were used to evaluate the developed prototype, in terms of ease of use, ease of navigating the application content, user satisfaction, attractiveness and learnability. Several validation tests were conducted on the proposed augmented reality m-learning verses m-learning. Generally, the respondents rated m-learning with augmented reality as superior to m-learning alone

Creación de entornos adaptativos móviles: recomendación de actividades y generación dinámica de espacios de trabajo basadas en información sobre usuarios, grupos y contextos

Tesis doctoral inédita. Universidad Autónoma de Madrid. Escuela Politécnica Superior, octubre de 200

A mobile context-aware learning schedule framework with Java learning objects

The focus of this thesis is the study of mobile learning, specifically learning in different locations and under various contextual situations, from the perspective of university students. I initially derived and designed a theoretical mobile context-aware learning schedule (mCALS) framework from an extensive literature review. Its objective is to recommend appropriate learning materials to students based on their current locations and circumstances. The framework uses a learning schedule (i.e. electronic-based diary) to inform the location and available time a student has for learning/studying at a particular location. Thereafter, a number of factors are taken into consideration for the recommendation of appropriate learning materials. These are the student’s learning styles, knowledge level, concentration level, frequency of interruption at that location and their available time for learning/studying. In order to determine the potential deployment of the framework as a mobile learning application by intended users, I carried out three types of feasibility studies. First, a pedagogical study was conducted using interviews to explore together with students (a) what their learning requirements were when studying in a mobile environment, (b) whether the framework could potentially be used effectively to support their studies and, (c) using this user-centred understanding, refined user requirements of the framework. Second, a diary study was conducted where I collected data and analysed the usability feasibility of the framework by (a) determining whether students could plan their daily schedule ahead and keep to it, (b) ascertaining which learning contexts were important and, (c) establishing which learning materials were appropriate under which situations. Two validation studies were conducted. The first one was an online experiment utilising Java learning objects. Participants of this study were suggested appropriate learning objects to study with, based on their amount of available time, current motivation level for learning and their proficiency level of Java. The second validation study was an investigation into high-quality Java learning objects available in the public domain. Finally, a technical design of the framework was carried out to determine whether the framework at present could realistically be implemented using current mobile technologies. The data analyses of the feasibility studies show that (a) a learning schedule approach is successful to an extent in obtaining location and available time information to indicate accurate values of these contexts, (b) different learners may require different personalisation strategies when selecting appropriate learning materials for them in mobile environments, and (c) the mCALS framework is particularly well-suited for self-regulated students. I also proposed a set of suggestion rules which can be used to recommend appropriate Java learning materials to students in different contexts. The validation studies show that 1) the proposed suggestion rules are effective in recommending appropriate materials to learners in their situation, in order to enhance their learning experiences, and 2) there are a sufficiently large number of high-quality LOs available in the public domain that can be incorporated for use within my framework. Finally, the development of mCALS has been considered from three perspectives – pedagogical, usability and technical. These perspectives consist of critical components that should be considered when developing and evaluating mobile learning software applications. The results demonstrated that the mCALS framework can potentially be used by students in different locations and situations, and appropriate learning materials can be selected to them, in order to enhance their learning experiences.EThOS - Electronic Theses Online ServiceGBUnited Kingdo