EDRE6605 - Quantitative Research Methods in Education I

Gabriella Belli, Ph.D.

office: 703.538.8477
home: 301.951.5291
e-mail: gbelli@vt.edu

Office: Room#454

Catalogue Description: This two-course sequence [EDRE 6605-6606] is designed to provide an overview of basic research design, measurement and statistical concepts in social and behavioral research. Emphasis will be placed on understanding the process of social and educational research in
field settings, hands on experience of designing and conducting research and analysis of data.

EDRE 6605 (fall semester) – Intro to research methods and to descriptive and inferential statistics. The focus will be on experimental and quasi-experimental research designs and analyses used to compare
group differences: t-tests, ANOVA, and ANCOVA. In addition to text an online materials, published research articles will be read and critiqued.

EDRE 6606 (spring semester) – The focus on research methods will be on non-experimental quantitative
designs, survey research, and qualitative designs. The quantitative part of the course will deal with
measurement issues and the statistical analyses often used with survey data and to explore relationships
between variables: correlation, regression, and chi-square analyses.

TEXT AND TEACHING AIDS
1) Blackboard: Course materials, announcements, discussion groups, email, etc. will be available on the Web via a program called “Blackboard” that allows for a number of online interactions. Do the following to familiarize yourself with what is available with it:
   a) open your web browser (Explorer, Netscape, etc.)
   b) go to the Blackboard site - http://learn.vt.edu
   c) logon using your VT PID and password
   d) click on EDRE 6605, which should be shown in your “List of Courses”
   e) familiarize yourself with the component parts – Review additional links under WEBSITE button.
2) Texts and Electronic Resources:
   a) Methods text: Slavin, R.E. (2007). Educational Research in an Age of Accountability. Pearson Education Inc.
   b) Statistics text: several online texts and resources will be used. URLs will be provided in class and via Blackboard.
3) Readings (Available in Blackboard. Additional readings will be posted during the semester.)
   a) Cross, L. H. & Belli, G. M, (2004) Experimental research to inform educational policy. In K. deMarrais and S. D. Lapan (eds.) Foundation for research: Methods of inquiry in education and the social sciences (pp. 329-351). Hillsdale, NJ: Lawrence Erlbaum Associates.
   b) Newman, M. & Edbourne, D. (2004). Improving the usability of educational research: Guidelines for the REPOrting of primary empirical research Studies in Education (The REPOSE Guidelines). Evaluation and Research in Education, 18(4), 201-212.
4) Software: JMP Statistical Software. We will have in-class demonstrations and hands on practice in the Computer Lab (room 102). JMP is a software environment for statistical computing and graphics, brought by the SAS Institute Inc. The University has currently an agreement with SAS, so that JMP
can be used for free by all faculty and graduate students through the Software Network. Log on at the following site using your VT PID and password:
https://www.ita.vt.edu/Apps/WebObjects/NetSoftware and scroll down to: SAS JMP 6.0.2
5) Important Note about Text: Slavin (2007) concludes every chapter with the following:
   • Research Navigator
       o Key terms
       o Activity
   • Exercises
   • Further reading
Please review these sections and use www.researchnavigator.com in studying for each chapter.
Additionally, consider using Google Scholar (http://scholar.google.com/) for finding articles (or go to
www.google.com; click on “more” and select “scholar” from the list.
6) Communication: Blackboard email lists contain VT PIDs. IF YOU DO NOT USE YOUR VT EMAIL, PLEASE MODIFY IT SO THAT ANY MESSAGES WILL REDIRECT TO YOUR OWN ACCOUNT.
   • SENDING EMAIL – Please put EDRE 6605 in subject line.
   • SENDING ATTACHMENTS – Send files using the following format for file names:
       EDRE6605-your last name-descriptive name for file.doc

COURSE STRUCTURE/GRADES:
The tenets of the Virginia Tech Graduate Honor Code will be strictly enforced in this course, and all graded assignments shall be subject to the stipulations of the Graduate Honor Code. For more information on the Graduate Honor Code, please refer to the GHS Constitution, located online at http://fbox.vt.edu/studentinfo/gradhonor/. Please note that ungraded assignments may (and probably should) be done with classmates. There will
be three graded exams, whose formats will vary and could include short essays or article reviews. Additional assignments will be given using JMP, the web, or articles. If you miss a deadline, assignments need to be turned in before the next class meeting, when the graded papers are returned to class. Final
grade will be assigned based on total percentage points, generally in the following manner, after adjusting for class average, which is usually a B.
95-100% - A 85-89% - B+ 70-74% - C+ Below 60% - F
90-94% - A- 80-84% - B 65-69% - C
75-79% - B- 60-64% - CAdditional

References – some textbooks used in the past
Elmore, P.B. and Woehlke, P.L. (1997) Basic Statistics. NY: Longman.
Howell, D.C. (2002). Statistical Methods for Psychology (5th ed.). Pacific Grove, CA: Wadsworth
Publishing.
Pedhazur, E.J. and Schmelkin, L.P. (1991) Measurement, Design, and Analysis: An Integrated Approach.
NJ: Lawrence Erlbaum Associates, Publishers. (a great reference book; lots of detail)

Additional References – supplemental and fun stuff found by previous students
Carr, J.J. (1994) A Crash Course in Statistics: An Innovative Book/Multimedia Approach to Collecting, Organizing, and Analyzing Data. Salana Beach, CA: High Text Publications Inc. (ncludes CD).
Gonick, L. & Smith, W. (1993) The Cartoon Guide to Statistics. NY: Harper Perennial.
Graham, A. (1994) Teach Yourself Statistics. Chicago, IL: NTC Publishing Group.
Hinton, P.R. (1995) Statistics Explained: A Guide for Social Science Students. NY: Routledge.
Langley, R. (1970) Practical Statistics Simply Explained. NY: Dover Publications, Inc.
Phillips, J.L. (1982) Statistical Thinking (2nd ed). NY: W.H. Freeman and Company.
Rowntree, D. (1981) Statistics Without Tears: A Primer for Non-Mathematicians. NY: Charles Scribner’s Sons.

Course Schedule
The following pages provide a tentative course schedule, which we will follow as closely as possible. Modifications may be made throughout the semester.

Week	Slavin (2007) text chapters Information about class activities and HW	Topics in Text
PART I	Introduction & Setting the Stage
1. 8/22	Chapter 1. Educational research in an age of accountability 8:30-9:00 Intro to EndNote software                 (by Dave Beagle) Read: Newman, M. & Edbourne, D. (2004) Wilkinson (1999)	Evidence-based education • The role of research in evidenced-based education • Educational policy and reform What is research? • The best possible answer to the best possible question • Types of research in education Research design • The logic of research design • Important elements in research (Hypotheses, theory, statistical significance, Type I and Type II errors, internal and external validity)
		Essentials of research design Research navigator
2. 8/29	Chapter 12a (pp. 218-228) Planning the study	Planning your own study
Lab	Computer searches – library research skills development lesson (by Debbie Cash) HW: Find 3-5 articles describing empirical studies related to some topic of interest. Read the articles and begin summarizing them.	Choosing a problem • Criteria for a good research topic • Other considerations in choosing a topic Reviewing the literature • Gathering preliminary information • Widely focused literature search • Primary resources for information gathering in education • Choosing search terms • Summarizing studies • Inclusion criteria • Writing the review
		• Methodology • Significance • Writing style Meta-analysis
3. 9/5	Chapter 15. Writing up the study	Writing a thesis or dissertation
Lab	Discussion of articles and summarization process. Practice with article searches and EndNote software	• Format and style • Parts of your thesis Writing a journal article or conference paper • Format and style of journal articles and papers • Choosing a journal • Conference papers • Tips on getting an article published
PART II	Experimental Research Designs
4. 9/12	Chapter 2. Randomized experimental designs Read: Cross & Belli (2004) HW: Write and critique hypotheses	Experimental comparisons in an age of accountability Random assignment • Random assignment of individuals • Stratified random assignment Randomized experimental comparisons • Control groups • Intent to treat • Pretesting Experiments with more than two treatments • Interactions in factorial experiments • Ordinal versus disordinal interactions • Factorial designs with more than two factors Alternatives to random assignment of individuals • Random assignment of classes, schools, & teachers • Delayed treatment control group designs • Within-teacher random assignment • Example of an experiment
5. 9/19	Chapter 3. Quasi-experiments HW: Critique an experimental or quasi-experimental research article	Conducting quasi-experiments Minimizing selection bias in quasi-experiments Making comparisons • Pre-post comparisons • Successive year comparisons • Artificial control groups What if pretests are not equal in different treatment groups?
Exam 1 – handout out Week 5 Due Week 6
6. 9/26	Chapter 4. Time series designs	Single-case experiments • Reversal (ABA) designs • Multiple-baseline designs Groups as single cases Statistics in single-case designs Limitations of single-case designs
7. 10/3	Chapter 11. Threats to internal and external validity Discuss Cross & Belli (2004)	Threats to internal validity • History • Maturation (passage of time) • Testing effects • Instrumentation effects • Selection bias • Statistical regression • Mortality (attrition) • Confounding variables Threats to external validity • Lack of internal validity • Non-representativeness • Artificiality • Reactivity o Hawthorne effects o John Henry effects • Mistaken causal models
PART III Data Analysis
8. 10/10	Chapter 13. Basic statistics	Descriptive statistics • Computing statistics (SPSS) • Scales of measurement
9. 10/7	Intro to JMP	• Measures of central tendency • Measures of dispersion
Lab		• The normal curve • z-scores
10. 10/24 Lab	See online texts	• Skewed distributions • Kurtosis • Standard error of the mean
		Inferential statistics • The null hypothesis • One-tailed and two-tailed tests of significance • t-test for comparisons of two independent group means • t-test for comparison of two means from matched groups
Exam 2 – handout out Week 10 Due Week 11
11. 10/31	Chapter 14a. Intermediate statistics (pp271-280)	Analysis of variance (ANOVA) • Comparison of 3 groups: 3×1 ANOVA
12. 11/7 Lab		• Two-factor ANOVA Analysis of covariance (ANCOVA) • ANOVA versus ANCOVA • Individual comparisons
13. 11/14		• Effect size
Lab
11/21 BREAK WEEK – no class
14. 11/28 Lab	Continuation of statistical analyses. Making academic presentations. Read: Renfrow & Impara (1989)	Review and discuss: Newman, M. & Edbourne, D. (2004) & Wilkinson (1999) from Week 1.
15. 12/5	Final discussion; Student presentations
16. 12/12	Exam 3 – handed out Week 15	Due Week 16 -Exam Week

Published by admin on September 26 of 2008