The dynamics of the world today demands a change in traditional education paradigms to enable the creation of more efficient learning environments, where students will learn more effectively and will play a more active role in their education. They should interact with the knowledge at anytime-anywhere. In order to tackle this problem we should take advantage of mobile communication devices (e.g., smartphones and tablets) which are widely used by students and which have excellent processing storage and connectivity capabilities. In this research work, a context-aware system stimulating active learning by students was developed. This system places the student in an intelligent learning environment and is capable of delivering appropriate context-related learning contents, based on location, time, date, interaction of the student, profile of the student, and so on. Within its architecture, the system includes reasoning capability that using context-based ontology is able to deliver efficient learning resources. The experimental results obtained from various learning experiences in nursery, medicine, and systems engineering support the validity of our approach.

A Contextualized System for Supporting Active Learning

In recent times, there has been an uptake of mobile learning (hereafter, abbre- viated as m-learning), i.e. learning with mobile technologies, especially in the form of mobile apps. Apps are particularly useful as they are small applications usually with a single-purpose and allow the users to view learning content offline from their mobile devices. They can be a good supplement to formal learning/training and can be very efficient informal learning tools, allowing learners to learn anytime and anywhere. In this paper, we present our ‘‘Learning Java’’ app, which was designed based on the theoretical framework ‘‘context-aware personalized m-learning application with m-learning prefer- ences’’ (Yau and Joy 2011). The app utilizes a personalized user profile consisting of location, noise and time of day, as well as the learner’s knowledge level. Additionally, an understanding of different m-learning preferences by learners is represented in our app as their individual user profile, for example, a learner may concentrate the best in a quiet library and the app will select appropriate (more difficult and longer) material based on this information, as opposed to shorter and easier materials. Video materials are also used by learners. This app was tested by 40 volunteers; 10 of which completed a long questionnaire regarding the usage of the app in terms of personalized user profile, context-awareness factors and whether the app helped increase their motivation for learning and their learning effectiveness for the subject. The results highlighted that participants could optimize their spare times for most effective learning (e.g. video-watching with headphones) in busy and/ or noisy environments. Findings also showed other chosen learning strategies by learners to make their learning more effective. Future work includes (1) extending the app for other subjects and disseminating it for use by remote learners, for example, those who are situated in developing countries without frequent access to wireless internet and/or educational materials, and (2) including learning analytical support to students to enhance their study success.

Evaluation of an extendable context-aware "Learning Java" app with personalized user profiling

Latest educational technology that called mobile learning or m-learning is a new style of learning as the development of mobile technology which can help to hold attention and make students more on self-study at anywhere and anytime. The paper focuses on a proposed model of m-learning for Technical and Vocational Education and Training (TVET) students in Malaysia. Development of the model is based on the user requirements from the TVET students in accordance to three aspects; device, user and social technology. The proposed model will be used as a guideline in the development of m-learning application which can improve teaching and learning quality and also motivate students to have interest on the learning.

A proposed model of m-learning for technical and Vocational Education Training (TVET) students

Mobile technologies are increasingly becoming an integral part of student’s lives in academia. Devices such as smartphones, tablets, and e-book readers connect users to the world instantly, heightening access to information and enabling interactivity with others. Applications that run on these devices let users not only consume but also discover and produce content. As such, they continue to transform how college students learn, as well as influence their learning preferences, both within and outside the classroom. This study survey the adoption of mobile phones among university students and their attitudes on the uses of cell phones as a venue for learning their class handouts and hunt ground for educational materials. The findings show that 53.3% of students own smart-phones while 41.8% own basic cell-phone (Featured phone). 42.4% of them use their cell phones to search educational reference materials online, 7.3% of them use cell phones to play games, 24.3% use their cell phones to read online news, 33.3% use their cell phones to connect to social networks. Overall these results suggest mobile phone as promising device for delivering learning materials to students.

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Mobile Learning a new Wave of Learning: A Survey among University of Dodoma Students

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Modeling, Designing, and Implementing an Ad- hoc M-Learning Platform that Integrates Sensory Data to Support Ubiquitous Learning

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.

Jane Yin-Kim Yau

Papers

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