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2016 | Book

A Clustering Algorithm Based on Minimum Spanning Tree with E-learning Applications Read chapter Read first chapter

Current Developments in Web Based Learning

ICWL 2015 International Workshops, KMEL, IWUM, LA, Guangzhou, China, November 5-8, 2015, Revised Selected Papers

Editors: Zhiguo Gong, Dickson K. W. Chiu, Di Zou

Publisher: Springer International Publishing

Book Series : Lecture Notes in Computer Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book constitutes the thoroughly revised selected papers of the workshops of the 14th International Conference of Web Based Learning, ICWL 2015, held in Guangzhou, China, in November 2015. This volume comprises papers of three workshops:

1. The 5th International Symposium on Knowledge Management and E-Learning, KMEL 2015

2. The first International Workshop on User Modeling for Web Based Learning, IWUM 2015

3. The International Workshop on Learning Analytics

Table of Contents

Frontmatter

Knowledge Management and E-Learning

Frontmatter
A Clustering Algorithm Based on Minimum Spanning Tree with E-learning Applications
Abstract
The rapid development of web-based learning applications has generated large amounts of learning resources. Faced with this situation, clustering is valuable to group modeling and intelligent tutoring. In traditional clustering algorithms, the initial centroid of each cluster is often assigned randomly. Sometimes it is very difficult to get an effective clustering result. In this paper, we propose a new clustering algorithm based on a minimum spanning tree, which includes the elimination and construction processes. In the elimination phase, the Euclidean distance is used to measure the density. Objects with low densities are considered as noise and eliminated. In the construction phase, a minimum spanning tree is constructed to choose the initial centroid based on the degree of freedom. Extensive evaluations using datasets with different properties validate the effectiveness of the proposed clustering algorithm. Furthermore, we study how to employ the clustering algorithms in three different e-learning applications.
Siyang Wang, Zeping Tang, Yanghui Rao, Haoran Xie, Fu Lee Wang
Analysis of Heart Rate Monitors for Evaluating Student’s Mental Working Capacity
Abstract
It is necessary to develop smart e-learning systems that can evaluate in real time not only student’s knowledge, skills and experience, but also his functional state. The learning load and intensity should not lead to a reduction of student’s functional state, including learner’s mental working capacity. Student’s functional state can be evaluated by analysis of heart rate variability, since heart rhythm responds to all changes in the human body and environment. There are a lot of devices for measuring heart rate variability, which called heart rate monitors. In massive e-learning more accessible monitors should be used but such monitors may not be sufficiently accurate. This paper studies three devices that can be used to estimate student’s mental working capacity.
Elena Berdnikova, Andrey Lyamin, Anton Skshidlevsky
Pedagogical Principles of the Implementation of Social Networks at Schools
Abstract
At present technologies have already penetrated in all spheres of human life. All fully employed people cannot imagine their work without a computer nowadays. In addition, more and more people also use social network sites on a regular daily basis, either for private and/or business purposes. In this study the authors attempt to firstly define a concept of social network sites as well as explore their types. Secondly, the authors of this article discuss pedagogy behind the creation of a social network from all stakeholders’ point of view. Thirdly, they set a few pedagogical principles, including the universal principles set already by Jan Amos Comenius in the 17th century. Finally, they emphasize the potential of educational social networks in students’ motivation to learn.
Blanka Klimova, Petra Poulova
Virtual Reality Assistant Technology for Learning Primary Geography
Abstract
A virtual reality based enhanced technology for learning primary geography is proposed, which synthesizes several latest information technologies including virtual reality(VR), 3D geographical information system(GIS), 3D visualization and multimodal human-computer-interaction (HCI). The main functions of the proposed system are introduced, i.e. Buffer analysis, Overlay analysis, Space convex hull calculation, Space convex decomposition, 3D topology analysis and 3D space intersection detection. The multimodal technologies are employed in the system to enhance the immersive perception of the users.
Zhihan Lv, Xiaoming Li
Setting up a Virtual Test Environment for User Group Specific Practical Exercises in eHealth eLearning Courses
Abstract
In recent years e-Health – the support for healthcare processes by means of information and communication technology – has become an essential issue for governments, organizations, companies and citizens all over the world. Although at the moment the use of e-Health solutions is expected to bring primarily regional advantages, a series of factors show that the topic has to be considered in an international context and qualified human resources are seen as a key ingredient for success. Therefore the “eLearning4eHealth Network” project at the University of Applied Sciences Technikum Wien aims to develop internationally coordinated eLearning curses for e-Health based on specific knowledge profiles that have been developed in the project. Practical trainings with real world tools (which at best are even in live operation) need to be an important part of the courses. Thus, a set of tools were evaluated and an appropriate suite of them were selected based on knowledge group specific use cases. Currently they are integrated in the eLearning environment and into the courses content.
Alexander Mense, Mathias Forjan, Juliane Herzog, Philipp Urbauer, Stefan Sauermann
Development of the ‘Learning to Learn’ Competence Through Wiki Tools in CA-CLIL: Pilot Course
Abstract
The paper presents the results of learners’ feedback on Social Science lessons at Secondary school for EU administration in Prague, Czech Republic. In the lessons the computer-assisted content and language integrated learning (CA-CLIL), wiki tools and methods of collaborative learning are applied. Such a model aims at developing the ‘learning-to-learn’ competence as defined by European Union documents. Totally 60 students participated in the pedagogical experiment; its main objective was to prove expected contributions of this approach to the process of instruction. Learners’ feedback was collected by the questionnaire and analyzed.
Vladimira Froldova, Ivana Simonova
Learning Styles in the e-Learning Environment: Meta-analysis of Longitudinal Changes
Abstract
The paper introduces results of meta-analysis focused on the field of learning styles in the e-learning environment held in two periods (2001–2007, 2008–2014) within selected journals in database systems ProQuest Central, Elsevier Science Direct and ERIC. Totally 5,361 relating papers were collected in both periods. The papers were structured according to three criteria. Collected data underwent the chí-squared test for independence and analysis of adjusted residuals on the significance level α = 0.05. The results did not prove any statistically significant change. Results were discussed and relating conclusions provided.
Pavel Doulik, Jiri Skoda, Ivana Simonova
Social Networks Supporting the Higher Education in the Czech Republic
Abstract
In this paper results of survey focused on social networking, particularly of the exploitation of social networks in the higher education are presented. The research question is what social networks are preferred and who their users are (from the point of gender and study programme). Moreover, the use of mobile devices is also investigated, as they often are the means through which students access to social networks. Data were collected by the method of questionnaire in the research sample of 205 students of the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic, matriculated in IT and Management study programmes in 2013/14 academic year. Three social networks were detected as the most frequently accessed (Facebook, Google + and LinkedIn) by both male and female users but differences were discovered between the groups of IT students and Management students. The collected data verified didactic recommendations defined by other authors on how the potential of social networks can be used towards independent learning on the higher education level.
Petra Poulova, Ivana Simonova
e-Learning in Practice: Tracking Students’ Performance
Abstract
The hybrid learning exploited as a tool supporting the face-to-face form of instruction started to be implemented in this process two decades ago. Providing a wide rate of tools and strategies to each student, the information and communication technologies make efforts to support efficient learning. As a result students are positively motivated and able to develop their level of knowledge in the shortest time period spending least efforts. To reach such a level in the real process of instruction, the requirement for optimizing the teaching/learning arose, particularly the call for improving the flexibility of the process, mainly by applying the individualized approach.
Ivana Simonova, Petra Poulova
Investigating the Determinants of Information Sharing Intentions of Learners in Collaborative Learning
Abstract
This study investigates the determinants of learners’ information sharing intentions in collaborative learning through the adoption of open learner models. Statistical analyses are performed on the data collected from 235 undergraduate students in Malaysian universities through survey to test the relationship between perceived usefulness, perceived ease of use, trust and the information sharing intention of learners. The result reveals that all three factors have a significant impact on learners’ information sharing behaviors in collaborative learning through the adoption of open learner models. Such findings are useful for educational institutions in their adoption of open learner models for information sharing in technology-based collaborative learning.
Yong Wee Sek, Hepu Deng, Elspeth McKay, Wei Xu
Towards an Architecture for e-Learning Infrastructures on a National Level: A Case Study of AfgREN
Abstract
National Research and Education Networks (NRENs) are for sharing resources between member organizations. NRENs play an important role in e-learning activities as they provide necessary communication. Heterogeneous infrastructures used for e-learning are a challenge for system design, integrity and interoperability. This paper proposed a NREN e-learning reference model and affiliated NREN e-learning architectural patterns that considered communication, reliable access, cooperation between e-learning infrastructures and interoperability. Research exists about different architecture including services oriented Cloud computing, For example, the E-School Systems and other institutional e-learning systems use traditional client server architectures. However, no research has been carried out on NREN e-learning architectures. For deeper insight, we investigate and compare in this paper the Estonian Education and Research Network (EENet) as an NREN example of a developed country, the Pakistan Education and the Research Network (PERN) as an example of a developing country and the Afghanistan Research and Education Network (AfgREN).
Salim Saay, Alex Norta, Mart Laanpere

User Modeling for Web-Based Learning

Frontmatter
Predicting Pre-knowledge on Vocabulary from e-Learning Assignments for Language Learners
Abstract
In the current big data era, we have witnessed the prosperity of emerging massive open online courses, user-generated data and ubiquitous techniques. These evolving technologies and applications have significantly changed the ways for people to learn new knowledge and access information. To find users’ desired data in an effective and efficient way, it is critical to understand/model users in applications involving in such a large volume of learning resources. For instance, word learning systems can be promoted significantly in terms of learning effectiveness if the pre-knowledge on vocabulary of learners can be predicted accurately. In this research, we focus on the issue of how to model a specific group of users, i.e., language learners, in the context of e-learning systems. Specifically, we try to predict the pre-knowledge on vocabulary of learners from their previous learning documents such as writing assignments and reading essays. The experimental study on real participants shows that the proposed predicting model is very effective and can be exploited for various applications in the future.
Di Zou, Haoran Xie, Tak-Lam Wong, Yanghui Rao, Fu Lee Wang, Qingyuan Wu
A Density-Based Clustering Algorithm with Educational Applications
Abstract
With the rapid development of Web 2.0 and interactive technologies, learning resources are proliferating online. Confronting such large volume of educational data, users require effective and efficient methodologies to organize and manage them, which reveals the importance of clustering. In this paper, we first propose a method to estimate the data density, and then apply it to merge learning resources. The proposed algorithm estimates the confidence of any two learning resources to be a pair of neighbors, and conducts clustering by combining the above confidence with the similarities among resources. Experiments are designed to evaluate the performance of our algorithm using the standard clustering datasets. We also demonstrate how to employ the proposed algorithm in educational applications, including e-learner grouping, resource recommendation and usage patterns discovery.
Zitong Wang, Peng Kang, Zewei Wu, Yanghui Rao, Fu Lee Wang
Personalized Resource Recommendation for Staff Training in Complaint Management Systems
Abstract
In this paper, a personalized resource recommendation method is proposed for staff training in complaint management systems. Historical processing logs are extracted to form a complaint space. Complaint processing skills of staff members are assessed in terms of quantity, efficiency and quality on various topics. Similar staff members are clustered according to their behavioral characteristics. A resource recommendation algorithm is proposed to recommend complaint processing records from highly skilled colleagues in the cluster for the staff member to learn. Preliminary experiment results show good performance of the proposed method.
Li Guangjie, Ling Junmin, Shengguang Meng, Liao Yumin
Social Network Application Development Based on Cloud Computing for Web-based Learning
Abstract
Social network applications and Massive Online Open Course (MOOC) have been widely used in Web-based learning, which have generated large amounts of users and learning materials. Thus, it is useful to manage various learners and share the data efficiently. We here develop a social network application, V-share to facilitate the learner communication and share the learning data based on cloud computing. The V-share has achieved functions of sending and receiving instant voice messages, images and expressions, taking pictures, uploading learning materials instantly, and online voice call. To evaluate the effectiveness of the developed V-share, we compare it to the classical e-learning system on Web-based learning by various metrics. Experimental results based on the usage data of ten learners indicate that V-share could improve the activeness of learners in terms of the averaged browsing time, flow, learners’ satisfaction, and frequency of data sharing.
Zhongyin Guo, Yanghui Rao, Fu Lee Wang
Exploring Reviews and Ratings on Reviews for Personalized Search
Abstract
With the development of e-commerce, e-commerce websites become very popular. People write reviews on products and rate the helpfulness of reviews in these websites. Reviews written by a user and reviews rated by a user actually reflect a user’s interests and disinterest. Thus, they are very useful for user profiling. In this paper, we explore users’ reviews and ratings on reviews for personalized search and propose a review-based user profiling method. And we also propose a priority-based result ranking strategy. For evaluation, we conduct experiments on a real-life data set. The experimental results show that our method can significantly improve the retrieval quality.
Yang Yang, Shuyue Hu, Yi Cai, Qing Du, Ho-fung Leung, Raymond Y. K. Lau
Designing an Online Learning and Peer Feedback Platform for GRE Writing Test Preparation
Abstract
In this paper, an online platform for learning GRE writing and providing peer feedback is designed. The platform consists of 4 modules: the first module helps the users to get familiar with the rhetorical moves and linguistic features found in the model essays; the second module trains the users to recognise the problems with content and form and prepare the users for peer review; the third module simulates the test environment for the users to practice writing with time constraints; the final module allows the users to review other users’ writing from module 3.
Simon Ho Wang
Individualization of Foreign Language Teaching Through Adaptive eLearning
Abstract
Lifelong learning has become an essential part of each profession. For this reason, personalized and adaptive learning has been drawing attention of professionals in the field of formal as well as informal education in the last few years. The effort has been made to design adaptive study supports regarding students’ requirements, abilities and current knowledge. In the Czech Republic, particularly at the University of Ostrava, a team of educators, didactics professionals and IT professionals has been applying their mind to personalized learning in the electronic environment. They have been developing a suitable learning environment to fit students’ learning styles. The paper describes a general model and a theory of adaptive eLearning from the perspective of the University of Ostrava professionals. It also demonstrates hard facts of the research in the field of language learning.
Katerina Kostolanyova, Stepanka Nedbalova

Learning Analytics

Frontmatter
Research on Visualized Design for Role-Based Online Learning Analytics
Abstract
The in-depth application of new technologies have brought about an explosion of educational data and people are placing more and more emphasis on learning analytics. Against this background, how to make better use of these data and display them in a visualized manner has become an urgent issue in applying learning analytics to education and learning process. This paper introduced the current research status and relevant cases of learning analytics visualization, brought forward learning analytics visualization model, and then displayed the design connotation of learning analytics visualization from the perspectives of different stakeholders (students, teachers and administrators).
Lamei Wang, Jun Xiao, Yuanyi Qi, Ye Yu
Construction on Learning Analytics Object for Sharing and Interoperation of Educational Big Data
Abstract
Educational Big Data (EBD) come from various types of Educational Systems such as LMS, CMS, ITS, SLS, and MOOCs. How to share and interoperate Educational Big Data for Learning Analytics (LA) has garnered a lot of research attention. In the paper, we probe into the process of Learning Analytics, outline the dataflow of EBD, define the Learning Analytics Object, and propose a new data format model for the Learning Analytics object to actualize the sharing and interoperability of Learning Analytics.
Yonghe Wu, Wei Zhong, Chun Zhou, Xiaoling Ma
Using Learning Analytics to Support Personalized Learning and Quality Education: A Case Study of China’s “Everyone Connected” Project
Abstract
The “Everyone Connected” project plays a very important role in the construction of the twelfth Five-year Plan of Educational Informatization in China. The project serves personal learning level, and expresses the real implementation of the needs of personalized learning and quality education. By using learning analytics through the organic interactive mechanism between personal learning space via the “Everyone Connected” project and “Two Platforms”, personalized push of resources and services and customized report of learning can be effectively realized.
Xiaohua Yu, Jueqi Guan, Jing Leng
Backmatter
Metadata
Title
Current Developments in Web Based Learning
Editors
Zhiguo Gong
Dickson K. W. Chiu
Di Zou
Copyright Year
2016
Electronic ISBN
978-3-319-32865-2
Print ISBN
978-3-319-32864-5
DOI
https://doi.org/10.1007/978-3-319-32865-2

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