1 / 17

Impact of Website Design on Content Validity Perception: A Research Overview

This document provides an outline for analyzing how website design influences visitors’ perceptions of the validity of content. It includes formulations for a research question, such as whether one of two standard deviation formulas is easier to use. Additionally, the text discusses various statistical concepts including chi-squared tests and correlation, as well as practical exercises for group work and real research implementation. Useful resources and assignment details are also provided, emphasizing the importance of methodical approaches to research in education.

dusan
Télécharger la présentation

Impact of Website Design on Content Validity Perception: A Research Overview

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. INF 397CFall, 2003Days 13

  2. Designing Research • Finishing the exercise from last week . . . • Question 3 (groups 5 and 6): Does design of a Web site affect visitors’ perception of the validity of the content?

  3. Homework • http://www.environ.wa.gov.au/community/results.asp • http://www.yogapoint.com/info/research.htm • http://www.main.nc.us/bcsc/Chess_Research_Study_I.htm • http://www.econ.upenn.edu/Centers/CARESS/CARESSpdf/00-15.pdf • http://www.georgetowncollege.edu/departments/education/portfolios/Franzen/research_paper.htm • http://www.pbats.com/articles/foot/Foot_Postures.pdf • http://www.cwrl.utexas.edu/currents/spring02/wakefield.html • http://www.neuhaus.org/paper3.htm

  4. Other “T scores” • http://www.rehabinfo.net/rrtc/publications/research_summaries/neropsychfunction/default.asp • “T scores” – “Standardized T scores for the WAIS-R, WISC-R, and HRB” • http://collection.nlc-bnc.ca/100/201/300/cdn_medical_association/cim/vol-21/issue-2/0094.htm • Yet new “T scores.”

  5. Other measures • Confidence intervals • http://www.hortnet.co.nz/publications/nzpps/proceedings/95/95_294.htm • Anova • http://www.ischool.utexas.edu/~adillon/publications/empirical.html

  6. Chi-squared • Hinton, p. 239

  7. Chi square test • Let’s work an example. • Just know that you use the chi square test when you have FREQUENCY data.

  8. Correlation • With correlation, we return to DESCRIPTIVE statistics. (This is counterintuitive. To me.) • We are describing the strength and direction of the relationship between two variables. • And how much one variable predicts the other.

  9. Hinton, p. 259

  10. Break

  11. Let’s conduct some REAL research • Research question: Is one of the two formulae for Standard Deviation easier to use? • H0: µ1 = µ2 • HA: µ1 ≠ µ2 • Population: iSchool Research Methods students • Sampling technique: Random • IV: Particular formula (derivative formula vs. computational formula • DVs: 1) Speed, 2) Accuracy

  12. Procedure • Who has a calculator? • Number off, 1 to N. • We’re gonna choose 10. • Randomly assign 5 to Group 1 and 5 to Group 2. • http://www.random.org/sform.html • Group 1 – Derivative formula first. • Group 2 – Computational formula first. • For each testee (wink), need one volunteer to time the completion. • Test participant: Please start when I say “Go,” and tell your observer when you think you have the answer.

  13. Test Materials -- A • Please calculate the Standard Deviation of the following distribution of scores: • 5 • 6 • 2 • 8 • 3 • 9 • 4

  14. Test Materials -- B • Please calculate the Standard Deviation of the following distribution of scores: • 4 • 6 • 8 • 7 • 3 • 9 • 2

  15. Scoring • Observers, please collect the following data: • Test Participant number • Materials A problem: Correct (y/n) • Materials A problem: Time to complete? • Materials B problem: Correct (y/n) • Materials B problem: Time to complete? • Difference score: Time for derivative (whether it was A or B) minus time for computational formula (whether it was A or B) • Let’s build a spreadsheet with the data.

  16. End game • Calculate t. • Reject or not? • Conclusion. • Now, REALLY, to whom do these results generalize?

  17. Let’s talk about the final • Course evaluation • Q-and-A session, Monday, December 1, 5:30 – 6:30, place TBD. • Sample problems handed out next week.

More Related