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Instructional Design Strategies for Teaching Technological Courses Online

Instructional Design Strategies for Teaching Technological Courses Online

Date: September 28, 2011
Creator: Chen, Jiangping & Knudson, Ryan
Description: Abstract: This paper describes different instructional design strategies for teaching computer technological courses online. Two of the three courses discussed in the paper have been taught on the Internet for over five years. The course content, assignments, and interaction have been designed and implemented based on the distinct challenges of the courses, their learning objectives, and the computing backgrounds of students. Students' evaluations of these courses are presented. The authors discuss important factors that may affect teaching and learning effectiveness for distance education.
Contributing Partner: UNT College of Information
Resource and Resource Sharing in Intelligent Information Access

Resource and Resource Sharing in Intelligent Information Access

Date: October 2008
Creator: Chen, Jiangping & Li, Fei
Description: This paper reports an exploratory study on resources and resource sharing among researchers in Intelligent Information Access (IIA). The investigation consists of two stages. In Stage One, the authors conducted a content analysis to identify resources used in 145 research papers and reports in two subfields of IIA; and in Stage Two, the authors carried out an online survey of IIA researchers to understand resource-sharing channels and the researchers' perspectives on resource sharing. The results demonstrate that IIA researchers make use of various types of resources developed by others. Most of these resources are knowledgeable sources or software systems that are freely available online. However, IIA researchers encounter various difficulties during the course of resource acquisition and use. The study suggests that a resource management system built on a well-established knowledge-management model could greatly facilitate the creation, sharing, and use of resources in the IIA community.
Contributing Partner: UNT College of Information
Metadata Records Translation: The Case of The Portal to Texas History

Metadata Records Translation: The Case of The Portal to Texas History

Date: 2011
Creator: Chen, Jiangping; Ding, Ren & Jiang, Shan
Description: Article discussing metadata records and translation. Abstract: In this paper, performance of online translation systems including Google, Systran and Bing on translating metadata records derived from the digital library- Portal to Texas History- is manually evaluated using four measures: Fluency, Adequacy, Incorrect Translation, and Missing Translation. The authors propose exploring multi-engine machine translation for improving the quality of translation and point out three possible strategies of implementing multilingual information access in digital libraries applying machine translation of metadata records.
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A preliminary evaluation of metadata records machine translation

A preliminary evaluation of metadata records machine translation

Date: 2012
Creator: Chen, Jiangping; Ding, Ren; Jiang, Shan & Knudson, Ryan
Description: Article discussing a preliminary evaluation study of metadata records machine translation. The purpose of this study is to evaluate freely available machine translation (MT) services' performance in translating metadata records. This study is partially supported by the Institute of Museum and Library Services (IMLS) grant LG-06-10-0162-10.
Contributing Partner: UNT College of Information
UNT at TREC 2004: Question Answering Combining Multiple Evidences

UNT at TREC 2004: Question Answering Combining Multiple Evidences

Date: 2004
Creator: Chen, Jiangping; Ge, He; Wu, Yan & Jiang, Shikun
Description: This paper discusses Question Answering (QA) combining multiple evidences. QA aims at identifying answers to users' natural language questions. A QA system can release the users from digesting large amounts of text in order to locate particular facts or numbers. The research has drawn great attention from several disciplines such as information retrieval, information extraction, natural language processing, and artificial intelligence. TREC QA track has provided comparable QA system evaluation on a set of test questions since 1999. The degree of difficulty of the test questions has increased substantially in recent two years, which push the research toward applying more sophisticated strategies and better understanding of English texts. This article discusses this research.
Contributing Partner: UNT College of Information
Chinese Information Retrieval Using Lemur: NTCIR-5 CIR Experiments at UNT

Chinese Information Retrieval Using Lemur: NTCIR-5 CIR Experiments at UNT

Date: December 2005
Creator: Chen, Jiangping; Li, Rowena & Li, Fei
Description: This paper discusses Chinese information retrieval using Lemur. Abstract: This paper describes our participation in NTCIR-5 Chinese Information Retrieval (IR) evaluation. The main purpose is to evaluate Lemur, a freely available information retrieval toolkit. Our results showed that Lemur could provide above average performance on most of the runs. We also compared manual queries vs. automatic queries for Chinese IR. The results show that manually generated queries did not have much effect on IR performance. More analysis will be carried out to discover causes behind hard topics and ways to improve the overall retrieval performance.
Contributing Partner: UNT College of Information
Chinese QA and CLQA: NTCIR-5 QA Experiments at UNT

Chinese QA and CLQA: NTCIR-5 QA Experiments at UNT

Date: December 2005
Creator: Chen, Jiangping; Li, Rowena; Yu, Ping; Ge, He; Chin, Pok; Li, Fei et al.
Description: Abstract: This paper describes our participation in the NTCIR-5 CLQA task. Three runs were officially submitted for three subtasks: Chinese Question Answering, English-Chinese Question Answering, and Chinese-English Question Answering. We expanded their TREC experimental QA system EagleQA this year to include Chinese QA and Cross-Language QA capabilities. Various information retrieval and natural language processing tools were incorporated with their home-built programs such as Answer Type Identification, Sentence Extraction, and Answer Finding to find answers to the test questions. Future development will focus on investigating effective question translation and answer finding solutions.
Contributing Partner: UNT College of Information
UNT 2005 TREC QA Participation: Using Lemur as IR Search Engine

UNT 2005 TREC QA Participation: Using Lemur as IR Search Engine

Date: 2005
Creator: Chen, Jiangping; Yu, Ping & Ge, He
Description: This paper reports the authors' TREC 2005 QA participation. The authors' QA system Eagle QA developed last year was expanded and modified for this year's QA experiments. Particularly, the authors used Lemur 4.1 as the Information Retrieval (IR) Engine this year to find documents that may contain answers for the test questions from the document collection. The authors' result shows Lemur did a reasonable job on finding relevant documents. But certainly there is room for further improvement.
Contributing Partner: UNT College of Information
The Development and Assessment of an Instrument for Measuring Mental Model Styles in Korea

The Development and Assessment of an Instrument for Measuring Mental Model Styles in Korea

Date: 2012
Creator: Chermack, Thomas J.; Song, Ji Hoon; Nimon, Kim F.; Choi, Myungweon & Korte, Russel F.
Description: This article discusses a research study on the development and assessment of an instrument for measuring mental model styles in Korea. Abstract: This research study documents the development and validation of a new instrument for measuring individual mental model styles. In particular, the instrument is developed for use in organizational performance and change settings. Existing approaches to accessing and assessing mental models are reviewed, and the conclusion is drawn that none are survey-based, quantitative measures useful in organizational settings. Instrument development procedures with an expert panel are described, as well as data collection and analysis. The resulting instrument is provided along with exploratory factor analysis, and confirmatory factor analysis results. Recommendations for further research and establishing continued validity are provided.
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Educators', Administrators' and Students' Perceptions of Principles of Technology Programs in Pennsylvania

Educators', Administrators' and Students' Perceptions of Principles of Technology Programs in Pennsylvania

Date: 1998
Creator: Chinoda, Michelle D. & Allen, Jeff M.
Description: This article discusses educators', administrators' and students' perceptions of principles of technology programs in Pennsylvania. Abstract: This study assesses the Principles of Technology Applied Science high school courses taught in Pennsylvania. Specifically, this study determines: 1) the number of Level I and II Principle of Technology courses taught; 2) teachers', administrators' and students' perceptions toward the Principle of Technology high school curriculum; 3) Principle of Technology teachers' perceptions of student achievement on state outcomes in science and technology; and 4) how Principle of Technology courses are being infused into the existing curriculum. Findings from this study indicate that both administrators, teachers, and students react favorably to the Principle of Technology Applied Science high school courses.
Contributing Partner: UNT College of Information