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Dive into the research topics where Wilton Fok is active.

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Featured researches published by Wilton Fok.


Engineering Education | 2009

Evaluating learning experiences in virtual laboratory training through student perceptions: a case study in Electrical and Electronic Engineering at the University of Hong Kong

Cecilia Chan; Wilton Fok

Abstract With recent advances in information technologies, a new mode of laboratory known as the “virtual laboratory” has begun to revolutionise engineering education. This development has generated discussion about the fundamental learning outcomes of laboratory training courses and, ultimately, an interest in the consequent changes to the student’s learning experiences. This exploratory case study describes the initial phase of a research agenda that is focused on investigating the effectiveness of virtual laboratories in the Department of Electrical and Electronic Engineering (EEE) in a research-intensive university. The long-term goals of the agenda are to add to the literature of how effective virtual EEE laboratories are (in terms of delivering specific learning outcomes, and also engaging and motivating students and teachers), and to discover whether they can ultimately become a substitute for traditional laboratory training by providing an equivalent and comparable learning experience for students.


international conference on e-business engineering | 2006

Experimental Analysis of an RFID Security Protocol

Zongwei Luo; Terry Chan; Jenny S. Li; Edward C. Wong; William K. Cheung; Victor C. Ng; Wilton Fok

Radio frequency identification (RFID) technology is expected to become a critical and ubiquitous infrastructure technology of logistics and supply chain management (SCM) related processes and services. Low-cost has been the key to RFID adoption in many logistics/SCM applications. However, the deployment of such tags may create new threats to user privacy due to the powerful track and trace capabilities of the tags, in addition to tag/reader manufacturing challenges. As a result, some security mechanisms must be imposed on the RFID tags for addressing the privacy problems. This paper provides detailed discussion on our proposal of a lightweight RFID security protocol. It examines the features and issues through experimental analysis pertinent to efficiency and scalability to meet the requirements of the proposed security protocol in metering and payment e-commerce applications


international conference on advanced learning technologies | 2008

Turning Mobile Phones into a Mobile Quiz Platform to Challenge Players' Knowledge: An Experience Report

Vincent Tam; S. W. Cheung; Wilton Fok; King-Shan Lui; Jade Wong; Beta Yip

In the past few years, many new mobile technologies including the 3G, WiFi or mobileTV have created unprecedented learning opportunities on mobile devices. Furthermore, such technologies continuously fuel the rapid growth of new fields of research like the edutainment for educational entertainment. In a recent project awarded by the Hong Kong Wireless Development Center, we have developed a mobile quiz game system on 3G mobile phone networks in China, Hong Kong or other countries to facilitate learning anytime and anywhere. Our developed mobile quiz system is so generic that it can be readily extended to any wireless network. In this paper, we discuss about the design and possible uses of our quiz system in mobile learning, and also share the relevant experience in system development with the evaluation strategies carefully examined. After all, our work shed light on many interesting directions for future exploration.


ieee international conference on teaching assessment and learning for engineering | 2015

Enhancing educational data mining techniques on online educational resources with a semi-supervised learning approach

Vincent Tam; Edmund Y. Lam; S. T. Fung; Wilton Fok; Allan H. K. Yuen

Both educational data mining (EDM) and learning analytics (LA) focus on applying analytics and data mining techniques to extract useful information from large data sets. EDM is generally more interested in automated methods for discovery within the educational data while LA is relatively keen on applying human-led methods to understand the involved learning processes. Among the various fields of challenging studies in EDM, domain structure discovery is aimed to find the structure of knowledge in an educational domain, such as formulating the prerequisite requirements among various knowledge components through online educational resources. However, with the vast amount of knowledge components in specific subjects, the process of such formulation is very complicated and time-consuming no matter being done manually or semi-automatically. In this work, we propose a systematic framework of a semi-supervised learning approach in which a concept-based classifier is co-trained with an explicit semantic analysis (ESA) classifier to derive a common set of prerequisite rules based on a diverse set of online educational resources. To demonstrate its feasibility, a working prototype is built with some impressive results obtained in specific engineering subjects. More importantly, our proposal sheds light on many possible directions for future exploration.


international symposium on computational intelligence and design | 2015

Application of Naive Bayesian Classifier for Teaching Reform Courses Examination Data Analysis in China Open University System

Liu Fang; Zhang Luan-Qiao; Wang Ying; Lu Feng; Sun Fu-Wan; Zhang Shao-Gang; Wilton Fok; Vincent Tam; Jiaqu Yi

Open education quality guarantee is a core issue in field of distance education. Data mining techniques are used to design effective teaching reform courses examination data analysis method would be a good way for checking teaching reform effects and could provide objective basis for open education quality assurance. This paper proposes a teaching reform courses examination data analysis solution based on Naive Bayesian classifier for checking the impacts of teaching reform measures act on open education quality. Naive Bayesian classifier is a famous classifying method, as a supervised learning, can extract valuable classifying rules by using data whose class label is known to train the classifier, and the trained classifier or classifying rules can be used to classify new data whose class label is unknown, and who is based on Bayes principal, has characteristics of accuracy and fast in aspect of classifying data in large scale database. Proposed solutions effectiveness is verified by processing practical teaching reform courses examination data in China Open University system. Hidden rules in teaching reform courses examination data are revealed, and also changing conditions of examination data caused by teaching reform measures are presented, which would be valuable in aspect of modifying open education quality assurance measures.


international conference on advanced learning technologies | 2014

Multidimensional Discussions on an Interactive Mobile Platform for Language Education -- A Case at the University of Hong Kong

Wilton Fok; I. H. M. Wong; Vincent Tam; Jiaqu Yi; H. H. Auyeung; K.Y. Law

Many lecturers in universities are held in big lecture theater which may not be the most desirable environment to carry out effective class discussions. Class, an interactive mobile learning platform developed and adopted in the University of Hong Kong, enables real-time interactive discussion among students and lecturer through their tablet PCs and smartphones and facilitates classroom discussion of various sizes and styles, gathering opinions from all classmates in an organized manner that is conducive to effective and fruitful discussions. It is a useful tool in facilitating multidimensional discussions that accommodate various types of discussion and teaching styles required in language learning. Learning no longer stresses on the one-way knowledge transmission from teachers to students, but in enhancing the capacity of the student to develop critical thinking ability to analyze issues from multiple angles in an organized and logical way. Discussions have hence become an increasingly important part of interactive learning. This system encourages more active participation from students to foster a more interactive class environment that is optimal for effective language learning and teaching.


international conference on big data and cloud computing | 2014

Cloud-Based Educational Big Data Application of Apriori Algorithm and K-Means Clustering Algorithm Based on Students' Information

Jiaqu Yi; Sizhe Li; Maomao Wu; H.H. Au Yeung; Wilton Fok; Ying Wang; Fang Liu


trust security and privacy in computing and communications | 2014

Data Mining Application of Decision Trees for Student Profiling at the Open University of China

Wilton Fok; Haohua Chen; Jiaqu Yi; Sizhe Li; H.H. Au Yeung; Wang Ying; Liu Fang


international conference on e-business engineering | 2006

Quality Management using RFID and Third Generation Mobile Communications Systems

Hon Wah Ng; Wilton Fok; Edward C. Wong; Zongwei Luo


international conference on information management | 2018

Prediction model for students' future development by deep learning and tensorflow artificial intelligence engine

Wilton Fok; Y.S. He; H.H. Au Yeung; K.Y. Law; Kh Cheung; Yy. Ai; P. Ho

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Jiaqu Yi

University of Hong Kong

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Vincent Tam

University of Hong Kong

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Cky Chan

University of Hong Kong

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Hon Wah Ng

University of Hong Kong

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K.Y. Law

University of Hong Kong

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Sizhe Li

University of Hong Kong

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Zongwei Luo

University of Hong Kong

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Liu Fang

Open University of China

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