Intelligent Database Systems Lab Presenter : HONG, CHIA-TSE Authors : Yueh-Min Huang, Yong-Ming Huang, Shu-Hsien Huang, Yen-Ting Lin 2012, CE A ubiquitous.

Slides:

Advertisements

Similar presentations

Intelligent Database Systems Lab Presenter: WU, JHEN-WEI Authors: Jorge Gorricha, Victor Lobo CG Improvements on the visualization of clusters in.

Advertisements

How does a web-service’s apparent trustworthiness affect people’s intention to adopt? a.k.a. “Seal of Approval and Multidimensionality of Perceived Trustworthiness.

Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Validating Transliteration Hypotheses Using the Web: Web.

Intelligent Database Systems Lab Presenter: YU-TING LU Authors: Laurens van der Maaten and Geoffrey Hinton ML Visualizing non-metric similarities.

ISEM 3120 Seminar in ISEM Semester

Intelligent Database Systems Lab Presenter: NENG-KAI, HONG Authors: G. PANKAJ JAIN, VARADRAJ P. GURUPUR, JENNIFER L. SCHROEDER, AND EILEEN D. FAULKENBERRY.

1 Factors Influencing Intention to Gamble Online Chang Boon Patrick Lee and Lin Hammer Xia Faculty of Business Administration University of Macau 14 th.

Intelligent Database Systems Lab Presenter: HONG, CHIA-TSE Authors: Yen-Hsien Lee, Chih-Ping Wei, Tsang-Hsiang Cheng, Ching-Ting Yang DSS Nearest-neighbor-based.

Advisor: 謝焸君教授 Student: 賴千惠

LOG O Development of a diagnostic system using a testing-based approach for strengthening student prior knowledge Computers & Education (September 2011)

Predictors of Engagement and Participation in an On-Line Course Miller, M. D., Rainer, R. K. & Coley, J. K. (2003). Predictors of engagement and participation.

Organizational Training Climate and Employees' Perception and Acceptance of Competency-based E-learning at the Workplace Bo Cheng, Minhong Wang Faculty.

Intelligent Database Systems Lab Presenter: YU-TING LU Authors: Liang-Chu Chen, Ting-Jung Yu, Chia-Jung Hsieh ACM KeyGraph-based chance discovery.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. BNS Feature Scaling: An Improved Representation over TF·IDF for SVM Text Classification Presenter : Lin,

An Extended TAM for Analyzing Adoption Behavior of Mobile Coupon Sudarsan Jayasingh Swinburne University of Technology Jalan Simpang Tiga 93350, Kuching,

Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Shih-Hwa Liu*,Gwo-Guang Lee 2013.CE Using a concept map knowledge management system.

Intelligent Database Systems Lab Presenter : NENG-KAI, HONG Authors : CÉSAR DOMÍNGUEZ, ARTURO JAIME 2014, CE Database design learning: A project-based.

 Collecting Quantitative  Data  By: Zainab Aidroos.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Evaluation of novelty metrics for sentence-level novelty mining Presenter : Lin, Shu-Han Authors : Flora.

Marica Romano1 Teaching English Language in Mixed Ability Classes The Challenge of Heterogeneous Classes.

Enhancing English Language Skills using Multimedia: Tried and Tested 報告人：張純瑋 Johanna Klassen, Philip Milton. Enhancing English Language Skills using.

Intelligent Database Systems Lab Presenter: WU, MIN-CONG Authors: Zhiyuan Liu, Xinxiong Chen, Yabin Zheng, Maosong Sun 2011, FCCNLL Automatic Keyphrase.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. A Web 2.0-based collaborative annotation system for enhancing knowledge sharing in collaborative learning.

Intelligent Database Systems Lab Presenter : JHOU, YU-LIANG Authors :Shady Shehata, Fakhri Karray, Mohamed S. Kamel, Fellow 2012, IEEE An Efficient Concept-Based.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Determining the best K for clustering transactional datasets – A coverage density-based approach Presenter.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. A Coursework Support System for Offering Challenges and Assistance by Analyzing Students’ Web Portfolios.

Joanna Huang YE4A Analysis of Mobile Shopping Behavior of Taiwanese Consumers.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. A semantic similarity metric combining features and intrinsic information content Presenter: Chun-Ping.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. An IPC-based vector space model for patent retrieval Presenter: Jun-Yi Wu Authors: Yen-Liang Chen, Yu-Ting.

Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology Concept similarity in Formal Concept Analysis-An information.

Research Design for Assessing Attitudes in Technology Acceptance: Chinese Americans and Internet Banking Lloyd G. Gibson, D.Sc. Director, MBA Program Assistant.

Intelligent Database Systems Lab Presenter : Kung, Chien-Hao Authors : Medhdi Khashei, Mehdi Bijari 2011, ASOC A novel hybridization of artificial neural.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Development of a reading material recommendation system based on a knowledge engineering approach Presenter.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Word sense disambiguation of WordNet glosses Presenter: Chun-Ping Wu Author: Dan Moldovan, Adrian Novischi.

Intelligent Database Systems Lab Presenter: Wu, Jhen-Wei Authors: Fabian Bürger, Josef Pauli ICPRAM. Representation Optimization with Feature Selection.

Intelligent Database Systems Lab Presenter : Chang,Chun-Chih Authors : CHRISTOS BOURAS, VASSILIS TSOGKAS 2012, KBS A clustering technique for news articles.

Intelligent Database Systems Lab Presenter : Chang,Chun-Chih Authors : David Milne *, Ian H. Witten 2012, AI An open-source toolkit for mining Wikipedia.

Intelligent Database Systems Lab Presenter: CHANG, SHIH-JIE Authors: Kevin Meijer, Flavius Frasincar, Frederik Hogenboom 2014.DSS. A semantic approach.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Unsupervised word sense disambiguation for Korean through the acyclic weighted digraph using corpus and.

Surveying instructor and learner attitudes toward e-learning Presenter: Jenny Tseng Professor: Ming-Puu Chen Date: April 12, 2008 Liaw, S., Huang, H.,

Intelligent Database Systems Lab Presenter: Bei-YI Jiang Authors: Chantal Baril, Viviane Gascon, Stephanie Cartier CIE Design and Analysis of an.

Intelligent Database Systems Lab Presenter : JIAN-REN CHEN Authors : Wen Zhang, Taketoshi Yoshida, Xijin Tang 2011.ESWA A comparative study of TF*IDF,

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Validity index for clusters of different sizes and densities Presenter: Jun-Yi Wu Authors: Krista Rizman.

Intelligent Database Systems Lab Presenter: CHANG, SHIH-JIE Authors: Longzhuang Li, Yi Shang, Wei Zhang 2002.ACM. Improvement of HITS-based Algorithms.

Definition Title: Motivation and Attitude toward Integrated Instruction through Technology in College-level EFL Reading and Writing in Taiwan Integrated.

College of Computer Science, SCU Computer English Lecture 1 Computer Science Yang Ning 1/46.

Intelligent Database Systems Lab Presenter : YAN-SHOU SIE Authors : MARCO PIASTRA NN Self-organizing adaptive map: Autonomous learning of curves.

Intelligent Database Systems Lab Presenter : Chuang, Kai-Ting Authors : Rafael Odon de Alencar, Clodoveu Augusto Davis Jr., Marcos André Gonçalves 2010,

Intelligent Database Systems Lab Presenter: NENG-KAI, HONG Authors: HUAN LONG A, ZIJUN ZHANG A, ⇑, YAN SU 2014, APPLIED ENERGY Analysis of daily solar.

By: Nelson Webster. Algorithm Engineers Algorithm engineers study the effectiveness and efficiency of procedures of solving problems on a computer.

Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Self Organizing Maps and Bit Signature: a study applied.

Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Modeling Semantic Similarities in Multiple Maps Presenter.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Towards comprehensive support for organizational mining Presenter : Yu-hui Huang Authors : Minseok Song,

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Using annotation services in a ubiquitous Jigsaw cooperative learning environment Presenter : Su, Wun-Huei.

Intelligent Database Systems Lab Presenter: YU-TING LU Authors: Junping Zhang, Hua Huang and Jue Wang IEEE INTELLIGENT SYSTEMS Manifold Learning.

Intelligent Database Systems Lab Presenter: YU-TING LU Authors: Vittorio Carlei, Massimiliano Nuccio PRL Mapping industrial patterns in spatial agglomeration:

Analysis of Mobile Shopping Behavior of Taiwanese Consumers Joanna Huang Professor: Dr. Aiden Yeh.

Intelligent Database Systems Lab Presenter: HONG, CHIA-TSE Authors:Yang Liu, Yan Liu, Keith C. C. Chan, Kien A. Hua TONNAL. Hybrid Manifold Embedding.

Intelligent Database Systems Lab Presenter : Chang,Chun-Chih Authors : Emilio Corchado, Bruno Baruque 2012 NeurCom WeVoS-ViSOM: An ensemble summarization.

Intelligent Database Systems Lab Presenter : YU-TING LU Authors : Hsin-Chang Yang, Han-Wei Hsiao, Chung-Hong Lee IPM Multilingual document mining.

Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Chun Fu Lin, Yu-chu Yeh, Yu Hsin Hung, Ray I Chang 2013.CE. Data mining for providing.

Intelligent Database Systems Lab N.Y.U.S.T. I. M. 1 Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques.

GGGB6012 ACADEMIC WRITING 1 The Use of e-dictionaries Among Low Proficiency ESL Learners in UKM NURAIDAWANY BINTI RASHID P79206.

Intelligent Database Systems Lab Presenter : BEI-YI JIANG Authors : JAMAL A. NASIR, IRAKLIS VARLAMIS, ASIM KARIM, GEORGE TSATSARONIS KNOWLEDGE-BASED.

The Students’ Acceptance of Learning Management Systems in Saudi Arabia: A Case Study of King Abdulaziz University Sami Binyamin1,2 , Malcolm Rutter1,

Prof Yaacov Katz and Dr Yaacov Yablon School of Education

teachers The English Language Centre EPORTFOLIOS!

Michael Moreno Saavedra & Christian Bach BUSINESS INTELLIGENCE

Main Predictors of Attitudes toward the Use of Moodle for Learning Business Administration Courses in an International University Setting Jhon Bueno, Stanislav.

Title First name, last name, university, city, country

Presentation transcript:

Intelligent Database Systems Lab Presenter : HONG, CHIA-TSE Authors : Yueh-Min Huang, Yong-Ming Huang, Shu-Hsien Huang, Yen-Ting Lin 2012, CE A ubiquitous English vocabulary learning system: Evidence of active/passive attitudes vs. usefulness/ease-of-use

Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments 1

Intelligent Database Systems Lab Motivation Vocabulary is the foundation of language learning. Students often adopt ineffective and inefficient ways to learn vocabulary. 2

Intelligent Database Systems Lab Objectives To develop a ubiquitous English vocabulary learning system to assist students in experiencing a systematic vocabulary learning (SVL) process in which ubiquitous technology is used to develop the system. EncounteringGettingUnderstandingConsolidatingUsing 3

Intelligent Database Systems Lab Methodology-System design 4

Intelligent Database Systems Lab Methodology-System demonstration 5

Intelligent Database Systems Lab Methodology-System demonstration 6

Intelligent Database Systems Lab Methodology-Research questions What are students’ perspectives on the UEVL system? Are the perspectives of active students on the UEVL system similar to that of passive students? 7

Intelligent Database Systems Lab Methodology-Research theoretical fundamentals: the technology acceptance model TAM- – Perceived usefulness – Perceived ease of use – Attitude toward use – Behavioral intention 8

Intelligent Database Systems Lab Methodology-Research model and hypotheses 9

Intelligent Database Systems Lab Methodology-Participants and grouping 40 students from a university in Tainan city – 20 active students – 20 passive students They have 3 to 16 years of computer experience. 10

Intelligent Database Systems Lab Methodology-Measurement 11

Intelligent Database Systems Lab Methodology-Experimental procedure Executing a learninig activity through the UEVL system. Fill out the questionnaire. 12

Intelligent Database Systems Lab Experiments-Measurement model 13

Intelligent Database Systems Lab Experiments-Structural model 14

Intelligent Database Systems Lab Experiments-Analysis of active and passive students’ perspectives 15

Intelligent Database Systems Lab Conclusions The UEVL system was accepted by the students in the sample. Active students were more concerned about the perceived usefulness of the system, while passive students were more concerned about the perceived ease of use of the system. 16

Intelligent Database Systems Lab Comments Advantages – Students can promote their English vocabulary ability and learn vocabulary more efficiently. Applications – Instructional software. 17