Chong Ho Yu, Ph.D., CNE, MCSE
Students will learn different research paradigms and specific research tools that are applicable to the development and evaluation of web-based instruction. By the end of this course, learners will be able to conceptualize a theoretical framework, develop a web-based course, map specific mental constructs and behavioral outcomes to specific media properties, select proper samples and subsamples, design an experiment, construct and validate an instrument, collect data, and perform statistical analysis.
This course is intended for students who have a strong interest in quantitative research for technology-based instruction, or quantitative research in general. Students who have a strong quantitative background and want to construct a coherent research methodology should also take this course.
A background in statistics and computing is expected (e.g. COE 501, COE 502, COE 552, COE 554, or equivalents). Since the course will use resources on the Internet, basic web proficiency is also required.
Attendance is not mandatory. If you cannot come to class, you can discuss research with me during my office hours or make an appointment. Email discussion or threaded discussion will also be arranged.
- Location: Computer Commons 207
- Time: Mon thru Thru--5:00 p.m. to 7:30 p.m.
- Office hours: Mon, Wed, Friday 2:00 p.m. to 3:00 p.m.
Some materials for this class are drawn from existing resources spanning across my website. Please use the Back button in your browser instead of the navigation panels, unless you see "Go up to the main menu" at the bottom of the page. If you cannot locate certain pages, please use the internal search engine. A link to the search engine is at the bottom of every page.
Also, some materials are targeted for other audience groups and are provided here for optional reading. Titles followed by a green asterik (*) are not mandatory, but you are encouraged to read them to equip yourself with more research tools.
Additional materials will be given in the class (So students get their money's worth, otherwise who wants to pay for a web-based course when everyone can access my website?) If you cannot attend a class, please come to my office (3S 70 Computer Commons) to pick up the handouts.
- Black-box Vs. structural input-process-output model
- Media properties, mental constructs, and behavioral outcomes
- Circular dependency--relationships among treatment, instrument, and subjects
- Networking issues *
- Web-enabled databases
- Introduction to File Maker Pro Web Publishing
- Using SAS/IntrNet for evaluating Web-based instruction *
- Using SAS to analyze user access log *
- Using JMP to analyze user access log *
Sample and population
- Population, sampling distributions, and sample
- Hypothesis testing, Type I and Type II error
- Power analysis and sample size
- Meta analysis and effect size
Design of experiment
- Design, measurement, and statistical analysis
- Experiment and non-experiment
- Variance control
- Threats to validity of experimental design
- Types of experimental design
- Classical test theory, Item response theory and differential item functioning
- Conventional and alternate views to reliability and validity
- How to assess reliability
- Reliability of self-reported data
- Latent constructs and factor analysis
- How to explore the factor structure
- Structural equation modeling
School of statistical analysis
- Basic of Statistics (Tutorial: HyperStatistics) *
- Statistics Advisor *
- Statistical reasoning
- Logic of quantitative method
- Probabilistic inferences or dichotomous answers?
- Mathematical reality
- Beyond Fisher
- Parametric tests
- Resampling methods
- Exploratory data analysis
- Data visualization
There will be no exams. Students will submit a project for evaluation. The due day of the project can be extended to Fall semester, but you will receive a grade in advance instead of receiving "incomplete."
- The project can be a conceptual paper, a proposal with a treatment (e.g. a software module for web-based instruction), or an experimental-based paper with empirical data.
- Students should identify a target conference or refereed journal for submitting the paper.
- Students can work individually or work as a team. All students will receive mentoring from the instructor during the research process.
- The paper should conform to APA style.
All class notes will be available on the web. In addition to the website, the following textbooks are required or recommended:
- Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design and analysis issues. Boston, MA: Houghton Mifflin Company.
- Lipsey, M. W. (1990). Design sensitivity: Statistical power and experimental research. Newbury Park: Sage Publication.
- Montgomery, D. C. (1997). Design and analysis of experiments. New York : Wiley.
- Maxwell, S. E., & Delaney, H. D. (1990). Design experiments and analyzing data: A model comparison perspective. Belmont, CA: Wadsworth Publishing company.
Full name: Chong Ho Yu
Nick name: Alex
Home town: Hong Kong
Gender: Can you tell from the picture?
You can contact me via different channels: email, phone, fax...etc. A link to the contact info is at the bottom of every page. To be fair to those who pay for this class, I answer questions related to research from my students only.
Let me introduce myself. Perhaps most people misunderstand my background. I was not trained to be a statistician. Yes, I got a degree in measurement and statistics, but it was not my original program. Many years ago I was in the doctoral program of instructional psychology and technology at the University of Oklahoma (something like ASU's Educational Media and Computers program). When my advisor, Dr. John Behrens, accepted a job as a professor of measurement and statistics at Arizona State University, I followed him to ASU as a transfer student. All my credits at OU were transferred and thus I was allowed to take just four more classes to earn a degree at ASU.
I regard myself as a methodologist rather than a statistician. Indeed, statistics is only a small part of my life. I have a wide variety of interests including philosophy, theology, social sciences, fine art, literature, computer technology, and many others. To unveil the "true Alex Yu," please look at the following sites:
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