Advanced Science Letters
ISSN: 1936-6612 (Print): EISSN: 1936-7317 (Online)
Copyright © 2000-2015 American Scientific Publishers. All Rights Reserved.
EDITORIAL BOARD
EDITOR-IN-CHIEF
Dr. Hari Singh Nalwa, USA
Editorial Office:
ADVANCED SCIENCE LETTERS
American Scientific Publishers
26650 The Old Road, Suite 208
Valencia, California 91381-0751, USA
Tel. (661) 799-7200
Fax: (661) 799-7230
E-mail: science@aspbs.com
EUROPEAN EDITOR
Prof. Dr. Wolfram Schommers
Forschungszentrum Karlsruhe
Institut für Wissenschaftliches Rechnen
D-76021 Karlsruhe, Germany
Tel.: +49-7247-82-2432
Fax: +49-7247-82-4972
HONORARY EDITORS
Richard Ernst*, ETH Zürich, Switzerland
Eric B. Karlsson+, Uppsala University, Sweden
Douglas Osheroff*, Stanford University, USA
*Nobel Prize Laureate
+Member of the Nobel Committee for Physics 1987-1998 (chairman in 1998)
ASSOCIATE EDITORS
Diederik Aerts (Quantum theory, Cognition, Evolution theory)
Brussels Free University, Belgium.
Yakir Aharonov (Physics, Quantum Physics)
School of Physics and Astronomy, Israel.
Jim Al-Khalili (Foundations of Physics, Nuclear Reaction Theory)
University of Surrey, UK.
Jake Blanchard (Engineering Physics, Nuclear Engineering)
University of Wisconsin–Madison, USA.
Simon Baron-Cohen (Cognitive Neuroscience)
University of Cambridge, UK.
Franz X. Bogner (Cognitive Achievement)
University of Bayreuth, Germany.
John Borneman (Anthropology)
Princeton University, USA.
John Casti (Complexity Science)
Internationales Institut für Angewandte Systemanalyse, Austria.
Masud Chaichian (High Energy Physics, String Theory)
University of Helsink, Finland.
Sergey V. Chervon(Gravitation, Cosmology, Astrophysics)
Ulyanovsk State Pedagogical University, Russia
Kevin Davey (Philosophy of Science)
University of Chicago, Chicago, USA.
Tania Dey (Colloids/Polymers/Nanohybrids)
Canada.
Roland Eils (Bioinformatics)
Deutsches Krebsforschungszentrum Heidelberg, Germany.
Thomas Görnitz (Quantum theory, Cosmology)
University of Frankfurt, Germany.
Bert Gordijn (Nanoethics, Neuroethics, Bioethics)
Radboud University Nijmegen, The Netherlands.
Ji-Huan He (Textile Engineering, Functional Materials)
Soochow University, Suzhou, China.
Nongyue He (Biosensors/Biomaterials)
China.
Irving P. Herman (Materials and Solid State Physics)
Columbia University, USA.
Jucundus Jacobeit (Climate, Global Change Ecology)
University of Augsburg, Germany.
Yuriy A. Knirel (Bioorganic Chemistry)
N. D. Zelinsky Institute of Organic Chemistry, Russia.
Arthur Konnerth (Neurophysiology, Molecular Mechanisms)
University of Munich, Germany.
G. A. Kourouklis (Physics Solid State Physics)
Aristotle University Thessaloniki, Greece.
Peter Krammer (Genetics)
Deutsches Krebsforschungszentrum Heidelberg, Germany.
Andrew F. Laine (Biomedical Engineering)
Columbia University, USA.
Minbo Lan (Organic Functional Materials)
China.
Martha Lux-Steiner (Physics, Materials Science)
Hahn-Meitner-Institut Berlin, Germany.
Klaus Mainzer (Complex Systems, Computational Mind, Philosophy of Science)
University of Augsburg, Germany.
JoAnn E. Manson (Medicine, Cardiovascular Disease)
Harvard University, USA.
Mark P. Mattson (Neuroscience)
National Institute on Aging, Baltimore, USA.
Lucio Mayer (Astrophysics, Cosmology)
ETH Zürich, Switzerland.
Efstathios Meletis (Physics, Thin films, Nanomaterials, Corrosion, Tribology)
University of Texas at Arlington, USA.
Karl Menten (Radioastromy)
Max-Planck-Institut für Radioastromie, Germany.
Yoshiko Miura (Biomaterials/Biosensors)
Japan.
Fred M. Mueller (Solid State Physics)
Los Alamos National Laboratory, USA.
The Institute for Molecular Medicine, Huntington Beach, USA.
Nina Papavasiliou (DNA Mutators, Microbial Virulence, Antiviral Defence, Adaptive
Immunity, Surface Receptor Variation)
The Rockefeller University, New York, USA.
Panos Photinos (Physics)
Southern Oregon University, USA.
Constantin Politis (Physics, Engineering)
University of Patras, Greece.
Zhiyong Qian (Biomedical Engineering, Biomaterials, Drug Delivery)
Sichuan University, CHINA.
Reinhard Schlickeiser (Astrophysics, Plasma Theory and Space Science)
Ruhr-Universität Bochum, Germany.
Surinder Singh (Sensors/Nanotechnology)
USA.
Suprakas Sinha Ray (Composites/Polymer Science)
South Africa.
Koen Steemers (Architechture, Environmental Building Performance)
University of Cambridge, UK.
Shinsuke Tanabe (Environmental Chemistry and Ecotoxicology)
Ehime University, Japan.
James R. Thompson (Solid State Physics)
The University of Tennessee, USA.
Uwe Ulbrich (Climat, Meteorology)
Freie Universität Berlin, Germany.
Ahmad Umar (Advanced Materials)
Najran University, Saudi Arabia.
Frans de Waal (Animal Behavior and Cognition)
Emory University, USA.
EDITORIAL BOARD
Filippo Aureli, Liverpool John Moores University, UK
Marcel Ausloos, Université de Liège, Belgium
Martin Bojowald, Pennsylvania State University, USA
Sougato Bose, University College, London, UK
Jacopo Buongiorno, MIT, USA
Paul Cordopatis, University of Patras, Greece
Dionysios Demetriou Dionysiou, University of Cincinnati, USA
Simon Eidelman, Budker Institute of Nuclear Physics, Russia
Norbert Frischauf, QASAR Technologies, Vienna, Austria
Toshi Futamase, Tohoku University, Japan
Leonid Gavrilov, University of Chicago, USA
Vincent G. Harris, Northeastern University, USA
Mae-Wan Ho, Open University, UK
Keith Hutchison, University of Melbourne, Australia
David Jishiashvili, Georgian Technical University, Georgia
George Khushf, University of South Carolina, USA
Sergei Kulik, M.V.Lomonosov Moscow State University, Russia
Harald Kunstmann, Institute for Meteorology and Climate Research, Forschungszentrum
Karlsruhe, Germany
Alexander Lebedev, Laboratory of Semiconductor Devices Physics, Russia
James Lindesay, Howard University, USA
Michael Lipkind, Kimron Veterinary Institute, Israel
Nigel Mason, Open University, UK
Johnjoe McFadden, University of Surrey, UK
B. S. Murty, Indian Institute of Technology Madras, Chennai, India
Heiko Paeth, Geographisches Institut der Universität Würzburg, Germany
Matteo Paris, Universita' di Milano, Italia
David Posoda, University of Vigo, Spain
Paddy H. Regan, University of Surrey, UK
Leonidas Resvanis, University of Athens, Greece
Wolfgang Rhode, University of Dortmund, Germany
Derek C. Richardson, University of Maryland, USA
Carlos Romero, Universidade Federal da Paraiba, Brazil
Andrea Sella, University College London, London, UK
P. Shankar, Indira Gandhi Centre for Atomic Research, Kalpakkam, India
Leonidas Sotiropoulos, University of Patras, Greece
Roger Strand, University of Bergen, Norway
Karl Svozil, Technische Universität Wien, Auastria
Kit Tan, University of Copenhagen, Denmark
Roland Triay, Centre de Physique Theorique, CNRS, Marseille, France
Rami Vainio, University of Helsinki, Finland
Victor Voronov, Bogoliubov Laboratory of Theoretical Physics, Dubna, Russia
Andrew Whitaker, Queen's University Belfast, Northern Ireland
Lijian Xu, Hunan University of Technology, China
Alexander Yefremov, Peoples Friendship University of Russia, Russia
Avraam Zelilidis, University of Patras, Greece
TABLE OF CONTENTS
A SPECIAL SECTION
Selected Peer-Reviewed Articles from the 2nd International Conference on Internet Services Technology and Information Engineering (ISTIE 2014), Bali, Indonesia, 31 May-1 June, 2014
Guest Editors:Ford Lumban Gaol, Suhono Supangkat, Mohan Kankanhalli, and Benfano Soewito Adv. Sci. Lett. 20, 1731-1733 (2014)
REVIEWS
Image Segmentation of Repetitive Patterns: A Review
Kamelia Kamel, Nursuriati Jamil, Azlina Narawi, and Abdul Rahman Gobil
Adv. Sci. Lett. 20, 1734-1739 (2014)
Trend of Case Based Reasoning in Diagnosing Chronic Disease: A Review
Daniel Hartono Sutanto, Nanna Suryana Herman, and Mohd. Khanapi Abd. Ghani
Adv. Sci. Lett. 20, 1740-1744 (2014)
RESEARCH ARTICLES
Development of Resistive Random Access Memory Simulation Model for Defect Analysis and Testing
Norsuhaidah Arshad, Nor Zaidi Haron, Zahriladha Zakaria, and Norhayati Soin
Adv. Sci. Lett. 20, 1745-1750 (2014)
Multi-Sensor Fusion Based Effective Obstacle Avoidance and Path-Following Technology
Byambaa Dorj, Doopalam Tuvshinjargal, KilTo Chong, Dong Pyo Hong, and Deok Jin Lee Adv. Sci. Lett. 20, 1751-1756 (2014)
Design a Broadband Dual-Polarized Antenna
Kho Shin Phoo, Mohamad Zoinol Abidin Abd. Aziz, Badrul Hisham Ahmad, and F. Abd. Malek
Adv. Sci. Lett. 20, 1757-1760 (2014)
Investigation of Multi Slot Stacked on Dipole Antenna Mohamad Hafize Ramli, Mohamad Zoinol
Abidin Abd. Aziz, Abdul Halim Dahalan, and Mohd Azlishah Othman
Adv. Sci. Lett. 20, 1761-1765 (2014)
Interpretive Structural Modeling to Improve National Productivity Using E-Commerce and M-Commerce Based Practices in Indian Context
Sujata P. Deshmukh and G. T. Thampi
Adv. Sci. Lett. 20, 1766-1777 (2014)
Design of an Integrity Homecare Application for Self-Physical Rehabilitations
Hao-Hsinag Ku and Miao Ou Yang
Adv. Sci. Lett. 20, 1778-1782 (2014)
FPGA Based Maximum Power Point Tracking of Photovoltaic System Using Perturb and Observe Method During Shading Condition
Abd Kadir Mahamad, Sharifah Saon, and King Diaw
Design of Antenna with Rectifying Circuit for Low Power Wireless Sensor Network Application
Z. Zakaria, N. A. Zainuddin, M. N. Husain, M. N. I. Kamaruzaman, M. Z. A. Abd Aziz, N. Z. Haron, A. A. M. Isa, and M. A. Mutalib
Adv. Sci. Lett. 20, 1788-1792 (2014)
Geospatial Content for Smartphone
Khairul Anshar and Nanna Suryana Herman
Adv. Sci. Lett. 20, 1793-1797 (2014)
Power Quality and Electromagnetic Interference Noise Problems of Fluorescent Lamp System to Control Systems
Chutipon Uyaisom and Werachet Khan-Ngern
Adv. Sci. Lett. 20, 1798-1802 (2014)
All-in-One PC or Desktop Saves More Energy But Poses Worse Power Quality Problem with Effect to Control System
Chutipon Uyaisom
Adv. Sci. Lett. 20, 1803-1807 (2014)
Position Control and Optimization Using the Electronic Circuit Module with the Rotary Encoder
Anna Antonyová, Peter Antony, and Benfano Soewito
Adv. Sci. Lett. 20, 1808-1812 (2014)
Detecting, Determining and Localizing Multiple Attacks in Wireless Sensor Network
Rajalakshmi and Umamaheswari
Adv. Sci. Lett. 20, 1813-1816 (2014)
Design of Rugby Ball Patch Microstrip Antenna with Circle Slot for Ultra Wideband Frequency (UWB)
Rudy Yuwono, Silvi A. D. Permata, Erfan A. Dahlan, and Ronanobelta Syakura
Adv. Sci. Lett. 20, 1817-1819 (2014)
Accurate Heading Estimation of a Vehicle Using Low-Cost GPS Only
Ganduulga Gankhuyag, Lim Shin Taek, Deok Jin Lee, and Kil To Chong
Adv. Sci. Lett. 20, 1820-1823 (2014)
A Novel Approach to Signal Encryption: Improved Version of Conventional Direct Sequence Spread Spectrum Scheme
A. Hira, N. Sakib, N. Sarker, M. N. Mollah, S. B. Mohamed, and M. A. Rashid
Adv. Sci. Lett. 20, 1824-1828 (2014)
A Wireless System and Embedded Sensors on Spindle Rotating Tool for Condition Monitoring
Muhammad Rizal, Jaharah A. Ghani, Mohd Zaki Nuawi, and Che Hassan Che Haron
Adv. Sci. Lett. 20, 1829-1832 (2014)
Designing Cham Fonts for Windows and Macintosh
Van Ngoc Sang and Mohamad Bin Bilal Ali
Adv. Sci. Lett. 20, 1833-1836 (2014)
Multi-Camera View Synthesis Based on Depth Image Layer Separation (DILS) Algorithm
Nurulfajar Abd Manap, Masrullizam Mat Ibrahim, John Soraghan, and Lykourgos Petropoulakis
Development of PC Based Fuzzy Logic Controller for DC Motor
Abd Kadir Mahamad, Sharifah Saon, and Wan Hassan Wan Hamat
Adv. Sci. Lett. 20, 1842-1845 (2014)
Improved Location and Positioning in WiMAX Networks with Virtual Multiple Input Multiple Output Base Stations
A. A. M. Isa, M. H. Othman, M. S. I. M. Zin, M. S. M. Isa, M. S. M. Saat, N. Z. Haron, and Z. Zakaria
Adv. Sci. Lett. 20, 1846-1850 (2014)
An Efficient Resource Allocation for Infrastructure-as-a-Service in Cloud Computing Environments
Wen-Hwa Liao, Chih-Kai Yu, and Ssu-Chi Kuai
Adv. Sci. Lett. 20, 1851-1855 (2014)
Secure Mutual Authentication and Key-Agreement Protocol for IP Multimedia Server-Client
Deebak Bakkiam David, Muthaiah Rajappa, Thenmozhi Karupuswamy, and Swaminathan Pitchai Iyer
Adv. Sci. Lett. 20, 1856-1863 (2014)
Fusing Data from Multiple Inexpensive Global Positioning System and an Electronic Compass to Increase Heading Accuracy in Real Time
Felipe P. Vista IV, Deok Jin Lee, and Kil To Chong
Adv. Sci. Lett. 20, 1864-1868 (2014)
Correlation Coefficient for Energy Monitoring Based on Human Activity in the Office Room
Nur Hanim Mustafa, Mohd Nor Husain, Mohamad Zoinol Abidin Abd Aziz, Mohd Azlishah Othman, and Fared Malek
Adv. Sci. Lett. 20, 1869-1872 (2014)
Design of Wideband Monopole Antenna with Co-Planar Waveguide Feeding Technique
Teik Kean Ong, Badrul Hisham Ahmad, Mohamad Zoinol Abidin Abd. Aziz, and Mohd Fareq Abd. Malek
Adv. Sci. Lett. 20, 1873-1875 (2014)
Enhanced Endocardial Boundary Detection in Echocardiography Images Using B-Spline and Statistical Method
Slamet Riyadi, Mohd Marzuki Mustafa, and Aini Hussain
Adv. Sci. Lett. 20, 1876-1880 (2014)
A Barrier Coverage Mechanism in Wireless Mobile Sensor Networks
Chih-Yung Chang, Chao-Tsun Chang, Ching-Sheng Wang, and Cheng-Chang Chen
Adv. Sci. Lett. 20, 1881-1884 (2014)
Time Frame Selection Based Feature Extraction for Fire Detection in Video Surveillance
Guruh Fajar Shidik and Fajrian Nur Adnan
Adv. Sci. Lett. 20, 1885-1889 (2014)
Performance Optimization of a Distributed Transcoding System Based on Hadoop for Multimedia Streaming Services
Myoungjin Kim, Yun Cui, Seungho Han, and Hanku Lee
Qiblah Direction: An Android Application
Sera Syarmila Sameon and Muhammad Saddiq B. Salleh
Adv. Sci. Lett. 20, 1895-1899 (2014)
Dynamic Interaction Network to Model Co-Integration in IDX Leading Stocks
Harya Widiputra
Adv. Sci. Lett. 20, 1900-1904 (2014)
Application of Genetic Algorithm for the Optimization of Energy Saving Glass Coating Structure Design
Fauzi Mohd Johar, Farah Ayuni Azmin, Abdul Samad Shibghatullah, Mohamad Kadim Suaidi, Badrul Hisham Ahmad, Siti Nadzirah Salleh, Mohamad Zoinol Abidin Abd Aziz, Mahfuzah Md Shukor, Liew Voon Bin, and Wong Wei Yang
Adv. Sci. Lett. 20, 1905-1909 (2014)
Comparative Analysis of Compact Defected Microstrip Structure (DMS) with Band-Reject Characteristics
Z. Zakaria, M. A. Mutalib, A. Ismail, N. A. Zainuddin, W. Y. Sam, M. S. M. Isa, A. A. M. Isa, and N. Z. Haron
Adv. Sci. Lett. 20, 1910-1913 (2014)
Geometrical-Invariant Grid-Based Colour Moment (GBCM) for Plant Identification
Nuril Aslina Che Hussin, Nursuriati Jamil, Sharifalillah Nordin, and Khalil Awang
Adv. Sci. Lett. 20, 1914-1917 (2014)
Texture Classification Using Random Forest
Mohammed M. Razooq and Md Jan Nordin
Adv. Sci. Lett. 20, 1918-1921 (2014)
Target Coverage Mechanism for Wireless Mobile Sensor Networks
Chih-Yung Chang, Gwo-Jong Yu, and Tzu-Chia Wang
Adv. Sci. Lett. 20, 1922-1926 (2014)
Mobile Robot Obstacle Avoidance Techniques
Aamir Reyaz, Bayanjargal Baasandorj, Sung Ho Park, Deok Jin Lee, and Kil To Chong
Adv. Sci. Lett. 20, 1927-1931 (2014)
The Role of Information and Communication Technology Sectors in Indonesian National Economy from 1990 Through 2008: An Analysis Using Input-Output Approach
Ubaidillah Zuhdi
Adv. Sci. Lett. 20, 1932-1935 (2014)
A Student Modeling Based on Bayesian Network Framework for Characterizing Student Learning Style
Adhistya Erna Permanasari, Indriana Hidayah, and Sapta Nugraha
Adv. Sci. Lett. 20, 1936-1940 (2014)
Tri-Band Frequency Selective Surface (FSS) on Hybrid Material
Teik Kean Ong, Kho Shin Phoo, Mahfuzah Md. Shukor, Mohamad Zoinol Abidin Abd. Aziz, Badrul Hisham Ahmad, Mohamad Kadim Suaidi, Fauzi Mohd Johar, Siti Nadzirah Salleh, Farah Ayuni Azmin, and Fareq Malek
A Comparison Framework of Classification Models for Software Defect Prediction
Romi Satria Wahono, Nanna Suryana Herman, and Sabrina Ahmad
Adv. Sci. Lett. 20, 1945-1950 (2014)
Neural Network Parameter Optimization Based on Genetic Algorithm for Software Defect Prediction
Romi Satria Wahono, Nanna Suryana Herman, and Sabrina Ahmad
Adv. Sci. Lett. 20, 1951-1955 (2014)
High Performance Large Sparse PDEs with Parabolic and Elliptic Types Using AGE Method on DPCS
Norma Alias, Maizatul Nadirah Mustaffa, Hafizah Farhah Saipan Saipol, and Asnida Che Abd. Ghani
Adv. Sci. Lett. 20, 1956-1960 (2014)
High Speed Computation of Muscle Stress Problem Using Crack Propagation Modelling on DPCS Platform
Norma Alias, Hala Mokhtar, Yin San, Hafizah Farhah Saipan Saipol, Maizatul Nadirah Mustaffa, Norfarizan Mohd Said, and Norhalena Mohd Nor
Adv. Sci. Lett. 20, 1961-1966 (2014)
Vehicle Tracking Through Location Prediction and Feature Similarity in Traffic Video Streams
Du-Hyung Cho and Seok-Lyong Lee
Adv. Sci. Lett. 20, 1967-1971 (2014)
A Royalty Optimization Model for Radio Spectrum Allocation
Ki-Seok Choi
Adv. Sci. Lett. 20, 1972-1975 (2014)
Mobile Robot Obstacle Avoidance Using Potential Field Method
Bayanjargal Baasandorj, Aamir Reyaz, Deok Jin Lee, and Kil To Chong
Adv. Sci. Lett. 20, 1976-1979 (2014)
Decision Support System for Agricultural Appraisal in Dryland Areas
Arif Imam Suroso, Sugiharto, and Arief Ramadhan
Adv. Sci. Lett. 20, 1980-1986 (2014)
An Assessment Model for Government Enterprise Architecture Establishment Phase
Nur Azaliah A. Bakar, S. Harihodin, and Nazri Kama
Adv. Sci. Lett. 20, 1987-1991 (2014)
Dependable Adaptive Failure Detection
Ahmad Shukri Mohd Noor, Mustafa Mat Deris, and Md Yazid Md Saman
Adv. Sci. Lett. 20, 1992-1995 (2014)
Optimising Interdependent Distributed Environment with Co-Existence Neighbourhood
Ahmad Shukri Mohd Noor, Mustafa Mat Deris, and Md Yazid Md Saman
Adv. Sci. Lett. 20, 1996-1999 (2014)
Investigation of Impedance Modeling for Dual Band Frequency Selective Surface (FSS) by Using Hybrid Materials
Adv. Sci. Lett. 20, 2000-2003 (2014)
Factors Affecting on Security Perception in Online Purchase Intention
Fatemeh Meskaran, Bharanidharan Shanmugamm, and Zuraini Ismail
Adv. Sci. Lett. 20, 2004-2008 (2014)
Comparative Study: The Implementation of Machine Learning Method for Sentiment Analysis in Social Media. A Recommendation for Future Research
Miftah Andriansyah, Adang Suhendra, and I Wayan Simri Wicaksana
Adv. Sci. Lett. 20, 2009-2013 (2014)
Enhancement of Student Motivation in Learning Through BLOSSOMS Video Activity
Nurul'Izzati Hamizan and Norasykin Mohd Zaid
Adv. Sci. Lett. 20, 2014-2017 (2014)
Design and Implementation of Web-Based Paddy Crop Management System Based on Open Source Tools and Web Service Technologies
Sohailah Safie, Mohamad Fairol Zamzuri Che Sayuti, and Rubiyah Yusof
Adv. Sci. Lett. 20, 2018-2021 (2014)
Therapeutics Approach in Microenterprise E-Business System: The SOAPIE Method
Hanitahaiza Hairuddin, Erne Suzila Kassim, Ariff Md Ab Malik, Noor Zalina Zainal, and Nor Laila Md Noor
Adv. Sci. Lett. 20, 2022-2025 (2014)
Optimization of Pre-Processing of Extensive Projects in Geographic Information Systems
Dalibor Bartonek, Jirí Bureš, and Irena Opatrilová
Adv. Sci. Lett. 20, 2026-2029 (2014)
Call Center Technology and Interactive Voice Response Based VoIP
M. Firdaus, Warnia Nengsih, and Ibnu Surya
Adv. Sci. Lett. 20, 2030-2033 (2014)
Adaptive Principal Component Analysis Based Recursive Least Squares for Artifact Removal of EEG Signals
Arjon Turnip and Mery Siahaan
Adv. Sci. Lett. 20, 2034-2037 (2014)
IT Strategy Alignment in University Using IT Balanced Scorecard Framework
Muhammad Izman Herdiansyah, Suzi Oktavia Kunang, and Muhammad Akbar
Adv. Sci. Lett. 20, 2038-2041 (2014)
Green IT Implementation Strategy: Development of a Tracking Indicator
Sri Fatiany Abdul Kader Jailani, Erne Suzila Kassim, and Hanitahaiza Hairuddin
Adv. Sci. Lett. 20, 2042-2045 (2014)
Preserving Privacy for Mobile Ad-Hoc Network Emergency Services via Heterogeneous Access Control Model
Asmidar Abu Bakar, El-Munzir Hassan El-Talib, and Roslan Ismail
Field Programmable Gate Arrays Implementation of Multiplier Free Architecture for Image Compression
Parvatham Vijay and Seetharaman Gopalakrishnan
Adv. Sci. Lett. 20, 2050-2054 (2014)
Application Specific Integrated Circuit Implementation of Multiplier Free Modified Flipping Architecture for Image Compression
Parvatham Vijay and Seetharaman Gopalakrishnan
Adv. Sci. Lett. 20, 2055-2059 (2014)
A Representational State Transfer Based Architecture for Web Services Using Unmanned Aerial Vehicles
Keunyoung Park, Doohyun Kim, Sangil Lee, Dong Kuk Ryu, and Dongwoon Jeon
Adv. Sci. Lett. 20, 2060-2063 (2014)
Comparison of CST and Customize Program in Theoretical for Scattering Transmission Parameter for Energy Saving Glass (ESG) Application
F. M. Johar, S. N. Salleh, F. A. Azmin, M. K. Suadi, M. Md. Shukor, B. H. Ahmad, and A. S. Shibghatullah
Adv. Sci. Lett. 20, 2064-2068 (2014)
A Data Envelopment Analysis-Based Index to Measure the Progress of the e-Service Society in Europe
Corrado lo Storto
Adv. Sci. Lett. 20, 2069-2072 (2014)
Subjective Judgment, Cognitive Style and Ecommerce Website Evaluation: A Non-Parametric Approach
Corrado lo Storto
Adv. Sci. Lett. 20, 2073-2077 (2014)
Improved Indoors Location Awareness Architecture in Mobile Phones
Vahid Davoudi, Salwani Mohd Daud, Mahdieh Abosadeghi, and Meysam Ahmadi Oskooei
Adv. Sci. Lett. 20, 2078-2081 (2014)
Pollution Instrumentation Using Global Positioning System and Data Logger Based-On Propeller
Ferry Wahyu Wibowo
Adv. Sci. Lett. 20, 2082-2086 (2014)
E-Learning Model for Mastery Learning Based on Gama Feedback Learning Model
Dwijoko Purbohadi
Adv. Sci. Lett. 20, 2087-2091 (2014)
HTML Format Tables Extraction with Differentiating Cell Content as Property Name
Detty Purnamasari, Lintang Yuniar Banowosari, I Wayan Simri Wicaksana, and Suryadi Harmanto
Adv. Sci. Lett. 20, 2092-2096 (2014)
Extension of NS2 Framework for Wireless Sensor Network
Mohamed Doheir, Atheer Kadhim, Khyrina Airin Fariza Abu Samah, Burairah Hussin, and Abd Samad Hasan Basari
On Measuring Business Value of Radio Frequency Identification Technology on Logistics Service
Moon-Soo Kim
Adv. Sci. Lett. 20, 2102-2105 (2014)
Performance of Meta-Heuristic Techniques in Freeman Chain Code (FCC) Extraction for Handwritten Character Recognition
Dewi Nasien, Habibollah Haron, Siti Sophiyati Yuhaniz, Aini Najwa Azmi, and Haswadi Hassan
Adv. Sci. Lett. 20, 2106-2110 (2014)
Multi-Criterial Analysis Based on Comparison with Etalon
Dalibor Bartonek and Stanislava Dermeková
Adv. Sci. Lett. 20, 2111-2114 (2014)
Software Engineering Challenges in Multi Platform Mobile Application Development
Hammoudeh S. Alamri and Balsam A. Mustafa
Adv. Sci. Lett. 20, 2115-2118 (2014)
Efficiency Energy Consumption in Cloud Computing Based on Constant Position Selection Policy in
Dynamic Virtual Machine Consolidation Guruh Fajar Shidik and Ahmad Ashari
Adv. Sci. Lett. 20, 2119-2124 (2014)
A Methodology for Investigating Opportunities for Service Technologies
Chulhyun Kim and Moon-Soo Kim
Adv. Sci. Lett. 20, 2125-2128 (2014)
Comparison Neural Network and Support Vector Machine for Production Quantity Prediction
Nur Rachman Dzakiyullah, Burairah Hussin, Chairul Saleh, and Aditian Maytri Handani
Adv. Sci. Lett. 20, 2129-2133 (2014)
Toward a Trend-Based Web Page Rank by Using Big Data on Smartphones
Dae-Young Choi
Adv. Sci. Lett. 20, 2134-2137 (2014)
Energy Monitoring System in Common Room Based on Human Behavior in Malaysia
Nur Hanim Mustafa, Mohd Nor Husain, Mohamad Zoinol Abidin Abd Aziz, Mohd Azlishah Othman, and Fared Malek
Adv. Sci. Lett. 20, 2138-2141 (2014)
The Process of Incorporating Online Collaborative Learning: An Analysis of Malaysian Tertiary ICT Educators' Perceptions
Mohd Nihra Haruzuan Mohamad Said, Lokman Tahir, Mohd Fadzli Ali, and Norasykin Mohd Zaid
Adv. Sci. Lett. 20, 2142-2146 (2014)
Controlling Algorithm for Energy-Consumption, Radio Bandwidth and Signal Strength Deploying Single Fitness Function to Solve Coverage Area Problems
Kalid Abdlkader Marsal, Ismail Abdullah, Waidah Ismail, and Khairi Abdul Rahim
Adv. Sci. Lett. 20, 2147-2151 (2014)
An Endosymbiotic Evolutionary Algorithm for Designing Hub and Spoke Network with Asymmetric Allocation
Adv. Sci. Lett. 20, 2152-2156 (2014)
Generating Data Recovery Keys Using Chinese Remainder Theorem
Pramote Kuacharoen
Adv. Sci. Lett. 20, 2157-2161 (2014)
A Survey of Spray-and-Wait Routing Protocol in Pocket Switched Network
Deni Yulianti, Satria Mandala, Dewi Nasien, Mohd. Sharizal Sunar, A. Hanan Abdullah, and Abdul Samad Ismail
Adv. Sci. Lett. 20, 2162-2165 (2014)
The Integrated Software Visualization Model to Support Novices' Program Comprehension
Affandy, Nanna Suryana, and Burairah Husin
Adv. Sci. Lett. 20, 2166-2170 (2014)
Support Vector Machine (SVM) in Handwritten Character Recognition Using Freeman Chain Code (FCC)
Dewi Nasien, Habibollah Haron, Aini Najwa Azmi, and Siti Sophiayati Yuhaniz
Adv. Sci. Lett. 20, 2171-2175 (2014)
Information Privacy Concerns in the Use of Social Media Among Healthcare Practitioners: A Systematic Literature Review
Fiza Abdul Rahim, Zuraini Ismail, and Ganthan Narayana Samy
Adv. Sci. Lett. 20, 2176-2179 (2014)
The Application of Multi Layer Feed Forward Artificial Neural Network for Learning Style Identification
Bilal Luqman Bayasut, Gede Pramudya, and Halizah Basiron
Adv. Sci. Lett. 20, 2180-2183 (2014)
A Review on Barriers in Adopting Healthcare Information System
Noor Hafizah Hassan, Zuraini Ismail, and Fiza Abdul Rahim
Adv. Sci. Lett. 20, 2184-2187 (2014)
Data Quality Mining Implementation on Sistem Operasi Terpadu (SOT) Data
Bobby Suryajaya
Adv. Sci. Lett. 20, 2188-2192 (2014)
Blended Learning: The Evaluation Studies
Mohd Fadzli Ali, Gordon Joyes, and Linda Ellison
Adv. Sci. Lett. 20, 2193-2197 (2014)
Evaluation of Students' Knowledge on Information Security at Technical and Vocational Training Corporation in Saudi Arabia
Hassan Almalki, Ganthan Narayana Samy, and Bharanidharan Shamugam
Adv. Sci. Lett. 20, 2198-2201 (2014)
Model of Inbound Asean Economics Community Tourists in Thailand by Using Twining of Feature Selection and Classification Algorithms
Anongnart Srivihok and Arunee Intrapairot
Study on the Reluctance of Organization Toward IPv6 Adoption in Indonesia Using Bajnath's Model
Gadang Ramantoko and Archenar
Adv. Sci. Lett. 20, 2206-2210 (2014)
Impact of Functional Test Automation for Web Systems
Viviane Tani, Charles Prada, Priscila Fagundes, Aline de Oliveira, and Lidiane Visintin
Adv. Sci. Lett. 20, 2211-2214 (2014)
The Mediating Effect of e-Satisfaction Between e-Service Quality and e-Loyalty in Internet Banking
Zohreh Bang Tavakoli, Mohd Shoki Md Ariff, Kamaruzaman Abdul Rahim, Norhayati Zakuan, and Khalid Ismail
Adv. Sci. Lett. 20, 2215-2219 (2014)
Examining Adoption of Internet Banking System Among Future Managers and ICT Professionals Using Unified Theory of Acceptance and Use of Technology Model
Yip Poh Yen, Mohd Shoki Md Ariff, Kamaruzaman Abdul Rahim, Norhayati Zakuan, Ahmad Jusoh, and Khalid Ismail
Adv. Sci. Lett. 20, 2220-2224 (2014)
A Hybrid Computational Intelligence Computing for the Hub Location-Routing Problem
Ji Ung Sun
Adv. Sci. Lett. 20, 2225-2229 (2014)
Success Model of Internet Banking: A Conceptual Framework
Masoomeh Jafarpoor, Norhayati Zakuan, Alireza Parvari, Muhamad Zameri Mat Saman, and Mohd Shoki Md Ariff
Adv. Sci. Lett. 20, 2230-2233 (2014)
Field Programmable Gate Arrays and Application Specific Integrated Circuits Implementation of COordinate Rotation DIgital Computer Using Wave-Pipelined Circuits
Rengaprabhu Paramasivam, Venkatasubramanian Adhinarayanan, and Seetharaman Gopalakrishnan
Adv. Sci. Lett. 20, 2234-2238 (2014)
Implementation of One Level and Two Level 2D-DWT Using Application Specific Integrated Circuit
Venkatasubramanian Adhinarayanan, Rengaprabhu Paramasivam, and Seetharaman Gopalakrishnan
Adv. Sci. Lett. 20, 2239-2243 (2014)
Multiple Criteria Decision Making for Indirect Procurement Division on Electronic Auction at Consumer Goods Company in Indonesia
M. Dachyar and Yupita
Adv. Sci. Lett. 20, 2244-2247 (2014)
Trust in Virtual Team Software Development
Rasimah Che Mohd Yusoff, Roslina Ibrahim, Nurazean Maarop, and Noor Azlinda Mat Seman
RESEARCH ARTICLE
Adv. Sci. Lett. 20 (10/11/12), 2087-2091, 2014
1 Adv. Sci. Lett. Vol. 20, No. 10/11/12, 2014 2087-2091/2014 doi:10.1166/asl.2011.1261
Copyright © 2014 American Scientific Publishers Advanced Science Letters All rights reserved Vol 20, 2087-2091, 2014 Printed in the United States of America
E-learning Model for Mastery Learning
Based on Gamma Feedback Learning Model
Dwijoko Purbohadi*
Information Technology Department, Universitas Muhammadiyah Yogyakarta, DI Yogyakarta, 55253 Indonesia
Gama Feedback Learning Model (GFLM) is a method of learning that adapted from a feedback-control system in engineering. It is designed especially for the mastery learning that uses e-learning. Students will receive more complete and perfect learning environment. With enough time and the right way of learning, students can achieve mastery. The objective of this paper is to build a blended learning model that combines face-to-face and e-learning based on the GFLM. The e-learning models that have been built then tested in the group of students who attend English courses for grammatical mastering. The obtained results are very significant, 100% of the students in the experimental group achieved mastery, and 40% of students in the control group achieve mastery. Whereas for the testing of implementation by using Partial Least Square (PLS) stated that mastery is 93.4% affected by the interface, the effectiveness of a tutorial, the learning treatment, the student motiva tion, and the student activities, and 6.6% affected by the unknown variable.
Keywords: GFLM, blended Learning, mastery learning .
1. INTRODUCTION
Mastery learning is a learning method that uses a concept: if every student is given the opportunity to study with enough time it is possible for them to achieve mastery1. Mastery learning is accomplished if done in the right conditions, and all students are able to learn well2, otherwise mastery learning cannot accomplish if students are not motivated3. The implementation of mastery learning requires a thorough learning model that can be applied easily and should use e-learning4.
Ideal learning is one lecturer for one student, supported by adequate equipment and appropriate methods. As time goes by, the ratio of the lecturer compares to student is getting smaller, meaning that lecturer manages learning groups with a growing number of students. This condition causes the lecturer to be difficult to manage learning activities; as a result the possibility of students to achieve mastery is reduced, big number student gives a negative effect on learning5.
*
Email Address: purbohadi@umy.ac.id
The Model of face-to-face learning group with a lot of participants had some limitations, such as limited in lecturer-student interaction. This condition also makes difficult to monitor learning outside the classroom activities, difficult to know every student learning problems, and difficult to motivate students who are having learning difficulties. The problems mentioned above show how important the new concept of e-learning model that suitable for mastery learning.
Adv. Sci. Lett. 20 (10/11/12), 2087-2091, 2014
RESEARCH ARTICLE
2
2. THEORITICAL FRAMEWORK
E-learning provides the advantages in teaching and learning because they have the ability to interact with students individually especially for the presentation of information, management, and tutorials through the internet. One important development of e-learning is a Learning Management System (LMS) in 19977. LMS is an internet-based application. LMS has the reliability and success is higher when compared to other systems, especially successful in improving the quality of web-based education management. LMS is an integrated system that supports number of students. LMS provides a place to organize and change the course of both their latest material and material that is being given, is known as the Learning Object (LO). Learning objects are a new way of learning content design, development, and delivery. LO provide all of the material for an entire course or lecture, a learning object provides material for a single lesson or lesson-topic within a course, i.e. simulations, interactive data sets, quizzes, surveys, annotated texts, and adaptive learning modules8.
The paper uses the definition of e-learning: e-learning is the content and instructional methods that rely on the use of computer tools to build knowledge or skills appropriate learning objectives9. The development of e-learning models must use technologies and pedagogical approaches. One innovation of e-learning that gives a lot of influence on education is the emergence of LMS, such as Moodle, Sakai, A Tutor, Blackboard, etc. LMS can equipped with activity recorder features and score (e-portfolio) to monitor student behavior10. However, LMS is not a teaching tool, so it need teaching modules. The development of LMS leads to the interoperability another LMS issue, so that standard SCORM (Shareable Content Object Reference Model) arises. Authoring tools are one of SCORM development tools, especially for building the content easily, quickly, and having a professional output11.The rapid development of technology has affected educational approaches; particularly, the internet which caused students to prefer more customizable and interactive systems for learning.
3. GAMA FEEDBACK LEARNING MODEL
Learning model with feedback-control techniques are learning control model which by this more students can achieve mastery. Further explained, mastery is likely to be achieved when students are motivated to actively learn and always under the supervision of lecturers. If a lecturer finds problems, actions will be taken to motivate students. This method has similarities with the principles of feedback-control in engineering. Gama Feedback-feedback-control Learning Model (GFLM) is an e-learning based model which specifically designed to adapt the principles of feedback control and apply it in teaching-learning so that each student achieves mastery. GFLM designed for a learning group model, but it can provide monitoring and improvement of individual learning so that all students achieve mastery. Mastery can be achieved by every student because GFLM gives students: flexible learning time, continuous learning, an assistance when they have difficulties, and motivation to
be willing to learn continuously active until they reach mastery. In GFLM, the lecturer has a duty to oversee, detects problems, and provides motivated task and comments to the students. Figure 1 shows the GFLM block diagram.
Figure 1. GFLM Block Diagram
The GFLM process control consists of: (a) the measurement of learning achievement through online tutorials to get scores for mastery criteria and learning achievement comparison, (b) finding learning problems, (c) evaluate for selecting improvement strategies, and (d) providing motivation and improvement actions. To realize the GFLM process control study implementation, then e-learning environment such as LMS, which is equipped with an Intelligent Tutoring System (ITS) and the appropriate instructional plan is used. The main important task of an ITS is the application of its “intelligence”. This means applying different technique of teaching for different students, without any intervention from the human teachers12. Using ITS concepts, learning activities can be carried out entirely by students using the LMS facility. Thus, by combining ITS and LMS, students can learn independently and freely, but observed, while more lecturer serve as supervisors and mentors so that students are willing to perform tasks such as an instructional plan. Finally, the learning model as a mastery learning concept in experimental group can be realized.
4. METHOD
RESEARCH ARTICLE
Adv. Sci. Lett. 20 (10/11/12), 2087-2091, 2014
3
4.1 Procedures
GFLM have a dependent variable that will be measured by the independent variables. The dependent variable is the mastery (Y), while the independent variables consist of the convenience of the interface (T), the effectiveness of online tutorials (E), the influence of treatment (B), motivation (M) and activity (A). The independent variables were the effectiveness of online tutorials, motivations and activities of an independent variable that is temporary (intervening). The convenience of the interface (T) is the independent variable that determines the success of the model. A great interface is not perceived by students, but the poor interface will decrease due to lower interest in providing motivation (M). In this case, the motivation is a very important element in learning. Effectiveness (E) can be seen from the results of the use of interactive modules which is an online learning tool in the achievement of the course objectives.
The core of interactive modules is to help students achieve mastery of each topic as it will affect the success of the overall student achieve mastery. Treatment (B) contains information for students after completing the activities. The comments are coming from the e-learning facility or from the lecturer for motivation treatments. The score information can become a trigger the process of improvement and reinforcement. Motivation (M) is an intermediate variable to achieve mastery. With a strong motivation, mastery is easier to achieve. Students who have high motivation are willing to work on any given task. Activity (A) is an in-class activity, i.e tutorial or discussion. Activities outside the classroom carried out independently by the LMS as working on the pre-test, post-test and using ITS. Activity is closely related to the motivation. If the motivation is high the activity is also high. The higher activity means greater the chances for success. Thus GFLM modeled as follows:
Y = T + B + M + A + E
Where:
Y = Mastery T = Interface B = Treatment M = Motivation A = Activity
E = Tutorial Effectiveness
Model Testing needs to be done to see the success of learning implementation. Due to this model applies to the actual learning activities involving human nature that is difficult to exactly quantify, it needs to have some hypotheses. Calculations can be performed to test the hypothesis qualitatively and quantitatively. The several hypotheses describe as follows:
H1: The experimental group had a significant increase in
student achievement compared to the control group.
H2: There is a 95% of the experimental group students
who achieve mastery1.
H3: Mastery is strongly influenced by the degree of
activity1, the higher the score the more likely the activity achieves mastery.
H4: Activity is influenced by motivation 13
, the higher the motivation, the more the students eager to collect activity score.
H5: Effectiveness of tutorial influence motivation. More
effective the tutorial, the student will have higher motivation to use it.
H6: The interface will influence the effectiveness of a
tutorial for users to feel comfortable using it.
H7: Learning treatment give effect on motivation 14
, the lecturer comments can determine whether students were motivated to use the tutorial or not
Hypotheses H1 and H2 are used to test the successfulness
of the model and H3, H4, H5, H6, and H7 are used to test the
influence variables of the model. These parameters are used to construct the research model to develop the relationships between constructs like as in Figure 2. The model consists of effectiveness of a tutorial and treatment construct that influence on motivation[2],[13]. The Effectiveness of the tutorial is influenced by the interface (display appearance). Motivation affects activity and it will ultimately determine student mastery[14].
Interface Tutorial
Motivation Activity Mastery
Treatment
Figure 2. Design of Research Model
4.2 Data analysis
Adv. Sci. Lett. 20 (10/11/12), 2087-2091, 2014
RESEARCH ARTICLE
4
between variables, both endogenous and exogenous latent while outer model explains the relationship between the latent variables and the indicators to measure the reliability and validity of the measurement results. The criteria of inner model are shown in table 1 Dan outer model is shown in table 2.
Table 1. Inner model criteria
Criteria Value Explanation
R2 (Determination
Coefficient) Min 0.67
R2 value indicates how far the endogenous latent variables influenced by exogenous latent variables. R2 values above 0.67 are
affected stronger, less than 0:19 are less affected, of which is said to be affected[16].
Q2
(Cross Validity) Positive
Q2 Is a measure of how well the
observed values reconstructed by the model. Q2 positive means construct has relevance to the prediction model, the negative Q2 means it has no relevance to the prediction model. Cross-validated commonality Q2 for all latent variables and cross-validated redundancy Q2 for endogenous latent variables. Smart PLS could see Q2 to
level constructs and indicators. GoF
(Goodness of Fit) Min 0.48
Shows how well the values observed by the model
An inner model evaluated by looking at the percentage of variance or R-square value on the dependent latent constructs (mastery). Inner model (structural model) has functioned to explain the relationship between latent variables (LV) to the entire model. An inner model is evaluated by looking at the percentage of variance or R-square value on the dependent latent constructs (mastery).
Table 2. Outer model criteria.
Criteria Value Explanation
Loading
factor Min 0.7 To study the reliability
Cross loading factor
The highest value of the construct [17]
To see the discriminant validity, a factor loading indicator of a construct should be higher than the loading factor indicator for the other constructs.
Cronbach’s
alpha Min 0.7 To see the internal reliability, i.e. how well a reflective latent variable through the indicator.
Composite
reliability Min 0.7
[18]
AVE and
Composite reliability
Min 0.5 and 0.6
[19] To see the construct validity and
reliability
AVE Min 0.5 [20] To see whether a construct has good discriminant validity or not
AVE
Higher than the correlation value between constructs
To see whether a construct has good discriminant validity or not
The value of cross loading showed the good discriminate validity if the correlation between the indicators of its constructs is higher than the value of the indicator correlation with other constructs. Blindfolding testing is used to see how well the size of the observed values reconstructed by means positive model. Q2 constructs have relevance to the prediction model, the negative Q2 means it
has no relevance to the prediction model. Smart PLS can show Q2 to level constructs and indicators.
4.3 Techniques
The experiment of the model was conducted at a nursing department in a college in Palembang, Indonesia. The model applied to English subject. The data are taken randomly and directly in real teaching activity. There are three learning objectives, namely: grammar, pronunciation, and fluency. The model includes the practice of computer-assisted learning study at home independently, and theory or practice in the classroom. Thus, students are required to skillfully communicate effectively using English. There are 17 sessions in each semester, consist of 2 hours tutorial, 2 hours practice, and one hour of homework. From earlier study found that lecturers did not have enough time to teach all the grammar topics in both practice sessions and theory sessions. These conditions are considered suitable for the use of GFLM, with the aim that all students are able to achieve mastery of grammatical by utilizing time outside the classroom.
The research population consisted of students participating in an English course. The number of students participating in learning was 113 students. Experiments conducted during one semester in the first academic year of 2011/2012. To measure the successfulness of the model required the data of pretest, posttest, and activity.
Implementation test required the data that’s collected
through questionnaires which were collected at the end of the semester. All students are given the opportunity to use the facilities of the model (e-learning). This is done to avoid new problems arising outside the context of the learning and the research themselves. The research was carried out without being noticed by faculty and students, this is to avoid a change in attitude because they know if the area being studied. Data is collected from the experimental group and the control group. What is meant by the experimental group were students who score at least 40% of tutorials and the rest goes to the control group.
5. RESULT
From the PLS calculations, the R2 value (coefficient of determination) in the mastery is 0.934 (above 0.8, very high), which means that 93.4% mastery influences by variables in the model and the remaining 6.6% mastery is influenced by other variables that are not known. This value indicates that the relationship between endogenous variables (dependent) with exogenous variables (independent) very closely. GoF is one of the techniques to calculate the validity of the model in the global PLS[17]. From the calculated values, it is obtained that the GoF value is 0.5502. GoF value is larger than Ward's criterion (0.48), so it can be concluded that the observed values are considered quite good models. The value of Q2 for all levels of constructs and indicators are positive, it indicates that the model can provide a good prediction.
RESEARCH ARTICLE
Adv. Sci. Lett. 20 (10/11/12), 2087-2091, 2014
5
AVE values interface are below 0.5. When it is observed from the composite reliability values, it is shown that the construct activities, learning treatment, tutorials effectiveness, mastery, and the interface have a composite reliability value above 0.8, only the construct of motivation that is less than 0.8.
The two model measurement above, inner model and outer model above, shows that all constructs have good reliability. It means that the model meets the inner and outer test model and bootstrapping calculation can be done to see the path coefficients (t-test calculation results). Bootstrapping tests performed using resampling techniques (bootstrapping) with 109 numbers of cases and 2000 numbers of samples. Bootstrap uses resampling techniques as a representation of the population.
5.1 Successfulness test
There is no significant difference between the grammatical knowledge in the two groups (homogeneous) before using the model. The mean value of pretest result in the experimental group is 60.8 and the control group has the mean value of 54.5. So, there are differences in the mean value of 5.3. There is a significant difference between grammatical knowledge in the two groups after using the model. The mean post-test in the experimental group is 72.5. It is higher than the post test control group which has a mean of 55.6. Hence, there is difference in the mean value of 16.9. From the analysis, there were 24 students included in the experimental group and all of them achieve mastery (100%). Is associated with significant differences in post-test between the control and experimental, it can be stated that the model works and can be used as e-learning model for English mastery learning concept in level 1.
From the explanation above, Hypothesis H1 is proven;
the experimental group had a significant increase in achievement compared to the control group. Hypothesis H2
also proved, there is 100% (greater than 95%) of the experimental group students who achieve mastery.
5.2 Influence variable tests
Bootstrapping test in PLS is used to test the weight coefficients and path coefficients with H0: w = 0 and the
alternative hypothesis H1: w ≠ 0. If the Tcount<Ttable, the H0
is rejected, (significant regression coefficient) and the alternative hypothesis stated in this study received at a significance level of 5%. Because this testing is to prove the “influence” existence to the value of the Tstatictic, thus, the
Tstatistic should be compared with the value of T2-tail
significance table. Rated Ttable (2-tail) at the 5% significance
level (probability value) by the number of resampling 2000 and five latent variables (degrees of freedom are considered in the 1000) is 1.962.
Table 3 shows the construct of display, the effectiveness of a tutorial, motivation, and activity have a positive influence in the other construct, with Tcount>Ttable (1.962). It
can be concluded that all hypotheses are accepted.
R2 value in mastery construct is 0.934 which means that variable in interface, tutorial effectiveness; treatment, motivation and activity have an influence value of 93.4% to the mastery variable. Mastery is influenced by the unknown
variable as much as 6.6%. From the testing model using PLS, it can be seen that the success is influenced by the activity, the activity is influenced by motivation, motivation is influenced by the treatment and the effectiveness of a tutorial and the tutorial is influenced by the effectiveness of the interface; all hypothesis: H3, H4, H5, H6, and H7 are
proven. If it is seen in the influence coefficients, in which they all are positive, it means that the nature of the effect is also positive.
Table 3. PLS’s bootstrapping test
Path T Hypothesis R2
Statistics Table
Activity >
Mastery 102.76 1.962 H3 Accepted 0.9341 Motivation >
Activity 10.503 1.962 H4 Accepted 0.3894 E-Tutorial >
Motivation 7.5259 1.962 H5 Accepted 0.4332
Interface >
E-Tutorial 8.9799 1.962 H6 Accepted 0.3154
Treatment >
Motivation 1.9987 1.962 H7 Accepted 0.4332
6. DISCUSSION
Returned to the design of GFLM, to achieve mastery, each student is treated on an individual basis using the model of learning with feedback-control. Success is measured by the number of students in the experimental group who achieve mastery; in this study proved that 100% achieve mastery. These results may not be achieved for the next test so as to know by looking at the factors that affect the model.
Learning model with feedback-control requires online tutorial and instructional design, as defined Clark and Mayer (2008); in order to the treatment for each student can run well so that the student can achieve mastery individually. Successfulness includes a process determined by the instructional design and the factors that are considered influential on the model. These factors become research variables, including: the interface (computer display) can give a negative effect if it cannot provide convenience. A great interface will make visitors feel convenient to use the online facility. Thus, the first hypothesis (H1) are proven that
interface influence the effectiveness of online tutorial. Treatment influenced the motivation. Good treatment will provide additional motivation for students. The effectiveness of online tutorials (third hypothesis) can be derived from the score. The effectiveness of online tutorial effect on motivation. Each student needs motivation, without motivation students will not be willing to use e-learning facilities. Each student has an internal motivation that this learning model evokes an external desire to enhance internal motivation.
Adv. Sci. Lett. 20 (10/11/12), 2087-2091, 2014
RESEARCH ARTICLE
6
GFLM learning with feedback-control system on an English course. In order to GFLM can be implemented on all courses were taught course required to provide that: (a) E-learning consists of LMS and interactive content. LMS is used to manage learning activities and online tutorial. The online interactive module is effectively used to replace the teaching faculty outside the classroom. (b) Instructional design integrates learning activities in the classroom and outside the classroom (hybrid models), it's also run feedback-control mechanism, and (c) The lecturers not only provide a tutorial, but also should be able to use e-learning resources to support the activities to be carried out. Lecturers also required to be able to monitor, evaluate, discrimination, class action, and especially being able to motivate students in order to more active to achieve mastery.
In subsequent lessons for different students, testing is done by eliminating the step of evaluation and treatment. Students are given the freedom to use the interactive modules or not. There are 88 students that are divided into two groups A and group B. Of the experiment, there are only 5 students from group A and group B 3 students used interactive modules and the amount has not been entered in the meet for the experimental group. Total number of student pass in post test is only 53.4%. So, from this experiment could not be performed statistical analyzes to compare between the experimental group and the control group. These experiments have shown that GFLM a strong influence on learning. Without using GFLM, students are not motivated to use the interactive module because the evaluation and treatment activities are not carried out
7. CONCLUSSION
Based on the above analysis and discussion can be concluded that statistically, in learning English can be said that: (1) E-learning model using GFLM can provide significant difference compared with no model. (2) E-learning model using GFLM can demonstrate the successfulness as a model of mastery learning because the number of students in the control group who achieve mastery is 100% (greater than Bloom’s criteria 95%). (3) The interface has an impact on the effectiveness of online tutorials (4) Motivation is influenced by the effectiveness of the tutorial and treatment, and (5) Motivation affects the activity, and activity affects mastery. The variable in interface, tutorial effectiveness, treatment, motivation and activity has an influence value of 93.4% to the mastery variable. Mastery is influenced by the unknown variable as much as 6.6%
REFERENCES
[1] Bloom, B.S., Learning for Mastery, Instruction and Curriculum. RELCV Topical Papers and Reprints No. 1., University of California, USA, (1968).
[2] Yamin, M., Desain Pembelajaran Berbasis Tingkat Satuan Pendidikan. Gaung Persada Press, Jakarta, Indonesia, (2007) 130-141
[3] Liu C.L. and Yang H.L., A Process-Oriented E-learning System: From Mastery Learning Perspective, Cheng Chi University, Taiwan, (2008).
[4] Cole, M.S. and Field, H.S, Student Learning Motivation and Psychological Hardiness: Interactive Effects on Students’ Reactions to a Management Class. Academy of Management Learning and Education, 3 (1), (2004). 64–85.
[5] Monks, J. and Schmidt, The Impact of Class Size and Number of Students on Outcomes in Higher Education, Robins School of Business, University of Richmond, (2010).
[6] Purbohadi D., Nugroho L., Santosa I., Kumara A., GaMa Feedback Learning Model: Basic Concept and Design, Journal of e-Learning and Knowledge Society, 9 (3), Italy, (2013) 67-77 [7] Davis, D. and Sorrell, J., Mastery learning in public schools.
Educational Psychology Interactive. Valdosta, GA: Valdosta State University, (1995).
[8] Pukkhem, N. and Vatanawood, W. Personalised learning object based on multi-agent model and learners’ learning styles, Maejo International Journal of Science and Technology, l5 (3), (2011). [9] Clark, R.C. and Mayer, R.E., E-Learning Science of and the
Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning. Pfeiffer, San Francisco, Vol 3, (2008) 8-11. [10] Kurz, S., Kammerl, R., and Heinrich, W., How to enhance a
Learning Management System with e-Portfolio capabilities. In C. Bonk et al. (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare and Higher Education, Chesapeake, AACE, (2010) 955-963.
[11] Khademi, M., Haghshenas, M., Kabir, Hoda, A Review On Authoring Tools, 5th International Conference on Distance Learning and Education, IPCSIT vol.12, IACSIT Press, Singapore, (2011)
[12] Chakraborty, S., Roy, D., and Basu, A., Development of Knowledge Based Intelligent Tutoring System, TMRF e-book Advanced Knowledge Based Systems: Model, Applications & Research. Eds. Sajja&Akerkar, Vol. 1, (2010) 74 –100.
[13] Ryan, R.M. and Deci, E.L., Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Academic Press University of Rochester, USA, (2000) 54-67.
[14] Kirkpatrick, D.L., Another look at evaluating training programs. Alexandria, VA: American Society for Training & Development, (1998).
[15] Hartono, J., Metodologi Penelitian Sistem Informasi: Pedomandan Contoh Melakukan Penelitian di Bidang Sistem Teknologi Informasi. CV. Andi Offset, Yogyakarta, Indonesia, (2008).
[16] Chin, W.W., The Partial Least Squares Approach to Structural Equation Modeling, in G.A. Marcoulides (Eds.). Modern Methods for Business Research, Mahwah, Lawrence Erlbaum Associates, Publishing, USA, (1998) 295-336.
[17] Vinzi, V.E., Trinchera, L., & Amato, S., PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. Handbook of partial least squares, Heidelberg, Springer. (2010) 47–82.
[18] Wertz, C., Linn, R., & Jo¨reskog, K., Intraclass reliability estimate: Testing structural assumptions. Educational and Psychological Measurement, 34 (1). (1974) 25–33.
[19] Bagozzi, R. P., & Yi, Y., On the evaluation of structural equation models. Journal of the Academy of Marketing Science,16, (1988) 74–94.
[20] Fornell, C., and Larcker, D.F., Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research, 18 (3), (1981) 328– 388.
