Using cloud computing and mobile devices to facilitate students' learning through e-learning games

The recent advance in cloud computing and mobile devices empowers many innovative e-learning systems or games with increased interactivity and improved features. In this paper, we consider an innovative framework of cloud-based e-learning games that can be assessed through mobile devices to enhance students' learning anytime and anywhere. Being model-based, our proposal is adaptive and highly portable that can be easily customized to any existing cloud platform. Besides, our proposed framework allows course instructors or game designers to flexibly modify any part of an e-learning game, and continuously monitor the performance of individuals who try to compete with each other to attain better results. It is worth noting that this paper reports an on-going work, namely the iGame@Cloud system, for which a thorough evaluation will be conducted later. After all, our proposal stimulates many interesting directions for further exploration. © 2013 IEEE.published_or_final_versio

Innovative Techniques for the Implementation of Adaptive Mobile Learning Using the Semantic Web

Adaptive Mobile Learning has constantly faced many challenges in order to make course learning more adaptive. This research presents a conceptual framework for using the Semantic Web to obtain students’ data from other educational institutions, enabling the educational institutions to communicate and exchange students’ data. We then can use this information to adjust the students’ profiles and modify their learning paths. Semantic Web will create a more personalized dynamic course for each student according to his/her ability, educational level, and experience. Through the Semantic Web, our goal is to create an adaptive learning system that takes into consideration previously completed courses, to count the completed topics, and then adjust the leaning path graph accordingly to get a new shortest path. We have applied the developed model on our system. Then, we tested the students on our system and a control system to measure the improvements in the students’ learning. We also have analyzed the results collected from the AML Group and the Control Group. The AML system provided a 44.80% improvement over the Control System. The experimental results demonstrate that Semantic Web can be used with adaptive mobile learning system (AML) in order to enhance the students’ learning experience and improve their academic performance

An Automated Adaptive Mobile Learning System Using Optimal Shortest Path Algorithms

Technological innovation opens the door to create a personal learning experience for any student. In this research, we discuss adaptive learning techniques and the style of learning that integrates existing learning techniques combined with new ideas. To create an effective user friendly learning environment, adaptive learning techniques should be used in order to identify the personal needs of students and reduce their individual knowledge gaps. The result will produce learning path containing relevant content that will provide a better learning direction for each student. This dissertation explores the opportunity of using adaptive learning techniques to identify the personal needs of each student by combining different learning styles, student profiles and individualized course content. By using a directed graph, we are able to represent an accurate picture of the course descriptions for online courses through computer-based implementation of various educational systems. E-learning (electronic learning) and m-learning (mobile learning) systems are modeled as a weighted directed graph where each node represents a course unit. The Learning Path Graph represents and describes the structure of the domain knowledge, including the learning goals, and all other available learning paths. In this research, we propose a system prototype that implements optimal adaptive learning path algorithms using students’ information from their profiles and their learning style. Our goal is to improve students’ learning performances through the m-learning system in order to provide suitable course contents sequenced in a dynamic form for each student

FGPE+: the mobile FGPE environment and the Pareto-optimized gamified programming exercise selection model - an empirical evaluation

This paper is poised to inform educators, policy makers and software developers about the untapped potential of PWAs in creating engaging, effective, and personalized learning experiences in the field of programming education. We aim to address a significant gap in the current understanding of the potential advantages and underutilisation of Progressive Web Applications (PWAs) within the education sector, specifically for programming education. Despite the evident lack of recognition of PWAs in this arena, we present an innovative approach through the Framework for Gamification in Programming Education (FGPE). This framework takes advantage of the ubiquity and ease of use of PWAs, integrating it with a Pareto optimized gamified programming exercise selection model ensuring personalized adaptive learning experiences by dynamically adjusting the complexity, content, and feedback of gamified exercises in response to the learners’ ongoing progress and performance. This study examines the mobile user experience of the FGPE PLE in different countries, namely Poland and Lithuania, providing novel insights into its applicability and efficiency. Our results demonstrate that combining advanced adaptive algorithms with the convenience of mobile technology has the potential to revolutionize programming education. The FGPE+ course group outperformed the Moodle group in terms of the average perceived knowledge (M = 4.11, SD = 0.51).info:eu-repo/semantics/publishedVersio

Pengembangan Aplikasi Mobile Learning Berbasis Augmented Reality Materi Bangun Ruang

Mobile learning as an alternative to today's adaptive learning services by the development of science and technology offers convenience, speed, flexibility, and attractiveness. In addition, the use of learning media is increasingly diverse and interactive, one of which is currently emerging is the use of augmented reality (AR) technology. It is necessary to develop a mobile learning application based on augmented reality for the material contained in the Mathematics Education II course at the PGSD FKIP Study Program at the Open University so that the material is easy to understand. The formulation of the research problem is how to develop the application. The purpose of this research is to develop to conduct a feasibility test of the application. The benefit of this research is knowing the steps taken in developing the application. The research method used is research and development (R&D) with a quantitative descriptive research approach with a questionnaire as a data collection technique. The stages of research and development are by the theory proposed by Borg & Gall. This research focuses on the application development section which consists of two stages. The first stage is the initial trial to create the content and appearance of the application. The second stage is the feasibility of the application according to language, material, and media experts. The results of this study are the quality and feasibility of a mobile learning application based on augmented reality building materials.   Keywords: mobile learning, augmented reality, application, learning media, geometr

Profile transformation in mobile technology based educational systems : a thesis presented in partial fulfillment of the requirements for the degree of Master of Information Science in Information Systems at Massey University, Palmerston North, New Zealand

In order to meet the learning needs from various types of students, computer aided education systems try to include new methods to provide personalized education to every student. From the early 1970s, a lot of adaptive educational systems have been created to provide training on a variety of subjects. Combined with the Internet, the adaptive educational systems have become web-based and even more popular. Recently, the development of mobile technology has made the web-based adaptive educational systems accessible through mobile phones. It is necessary that the students can also receive adaptive educational contents on mobile phones. This research project investigated the possible student's preference differences between Personal Computer (PC) and mobile phone, and then proposed a student profile transformation framework to address such differences. This research project conducted two surveys on the student profile transformation between PC and mobile phone. A demo web-based educational system that could be accessed from both PC and mobile phone was also developed for participants of the surveys to give more real and precise responses. Based on Felder-Silverman Learning Style Theory (Felder, 1993; Felder & Silverman, 1988) and the results of the surveys, this thesis proposes a student profile template and a student profile transformation framework, which both fully considered the influences of device capabilities and locations on students' preferences on mobile phones. Furthermore, the proposed framework integrates a solution for unsupported preferences and preference conflicts. By implementing the proposed template and framework, the students' preference changes between PC and mobile phone are automatically updated according to various device capabilities and locations, and then the students can receive adaptive educational contents that meet their updated preferences

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Developing a Just-in-Time Adaptive Mobile Platform for Family Medicine Education: Experiential Lessons Learned

EASEL is a platform designed to provide just-in-time adaptive support to students during experiential learning interviews conducted as part of required work in an online course in a family medicine education program in a Midwestern urban university setting EASEL considers the time and location of the student and provides questions and content before, during, and after the interviews take place EASEL will provide a new way to facilitate and support online family medicine students as they meet with patients and healthcare professionals This paper presents a look at the considerations, issues, and lessons learned during the development process of this interdisciplinary collaborative effort between the platform designers and family medicine faculty while working toward completion of the stud