EAF 510: RESEARCH METHODOLOGY AND STATISTICS IN EDUCATION II

SUMMER 2007

Instructor: John K. Rugutt, Ph.D.

Place of work: 323 DeGarmo

Phone: (309) 438-2051

Office Hours: By appointment (Email preferable).

Class Meets: Monday & Wednesday 5:30-9:20pm, Room: DEG 306

Click here for a word version of the course syllabus

Department Name	Educational Administration and Foundations
Course Number	EAF 510
Course Title	Research Methodology and Statistics in Education II
Catalog Description	Logic of statistical inference; introductory study of analysis of variance and multiple regression, with a computer oriented approach. Prerequisite: EAF 508/509 or equivalent.
Course Overview	This is the third part of a five-semester course that covers a wide range of statistical methods and their applications. Similar to the first and second course, instead of concentrating on how to enter numbers in formulas, emphasis is on understanding concepts and processes behind statistical procedures. The purpose of this course is to introduce students to intermediate statistical techniques for analyzing educational data. Various univariate and multivariate procedures will be discussed. The emphasis of the course will be on practical applications of statistical techniques. The course will concentrate more on statistical inference involving t-test, simple and factorial ANOVA, bivariate correlation/regression analysis, multiple linear regression, repeated measures ANOVA and Chi-square using conceptual definitions, without access to formulas. Ability to use SPSS for data analysis is also expected.

Topics

| Student Performance and Evaluation | Delivery System |ISU Policies |

Topical/Content Outline...Subject to Change

The instructor reserves the right to make changes to the course syllabus as necessary.

It is the student's responsibility to keep up with changes to the syllabus

Topical/Content Outline

Week	Date	Topic	Assignment	Chapter
1	06/18	Introduction and Review Describing Data Research Design, Measurement, and Analysis		BA, Ch12* Vogt, Ch1**
1	06/20	Introduction to t-statistic Hypothesis tests--two independent samples Developing Ideas for Research Variables and relationships among them Uses of descriptive statistics		Other*** BA, Ch2 Vogt, Ch3, 4
2	06/25	Hypothesis tests with related samples Introduction to Analysis of Variance Multiple Comparison Procedures Reviewing the Literature		Other BA, Ch3
2	06/27	Two-factor Analysis of Variance Survey and Sampling Observations and Sampling	Assignment #1 Due	Other Vogt, Ch5 BA, Ch5, 6
3	07/02	Two-factor Analysis of Variance Statistical Inference Using Inferential Statistics Using Survey Research		Other Vogt, Ch8 BA, 13 BA, Ch8
3	07/04	Independence Day Holiday - No Classes	--	----
4	07/09	Midterm Examination!!!	--	----
4	07/11	Repeated Measures Analysis of Variance Using Single-Subject Designs Correlation Analysis Standard Deviation and Correlation	Assignment #2 Due	Other BA, Ch11 Other Vogt, Ch2
5	07/16	Simple Linear Regression Regression Analysis Reviewing, Critiquing, and Synthesizing Research Choosing a Research Design Using Nonexperimental Research		Other Vogt, Ch10, 17 BA, Ch4 BA, Ch7
5	07/18	Multiple Linear Regression Back to Regression Using Multivariate Design Analysis	Project Presentation	Other Vogt, Ch9 BA, Ch14
6	07/23	Ordinal and Nominal Procedures (Non-Parametric Statistics: Chi-square Distributions Methods for Categorical Variables: Contingency Tables Reporting Your Research Results		Other Vogt, Ch11 (pp. 191-197) BA, Ch15
6	07/25	Final Examination!!!	Final Project Due

Note: * Research Designs and Methods (Kenneth, S. Bordens & Bruce B. Abbott)

** Quantitative Research Methods for Professionals (W. Paul, Vogt)

*** Notes from the instructor

1 Research Methodology and Statistics In Education II

1.1 Course Objectives

Upon completion of this course, students will be able to:

a. Identify a variety of research designs (mostly quantitative paradigms).

b. Understand the concepts of internal and external validity.

c. Identify a researchable problem and conduct research on it.

d. Use a research library and other public sources of data and research.

e. Demonstrates ones’ ability to critically analyze and interpret published research (through literature

reviews and/or article critiques).

f. Understand the issues related to the concepts of instrument validity and reliability.

g. Correctly calculate and interpret basic descriptive and inferential statistics.

h. Understand the logic of statistical inference and hypothesis testing.

i. Be able to calculate and interpret inferential statistics on z, t, F, r, chi-square statistics.

j. Write according to APA guidelines.

1.2 Class Format

The format of the course will be a combination of lectures, seminar, and computer time. Each topic that we

cover will have a combination of lecturing by me, to give you the necessary background for the topic, lab

exercises so that we can learn how to interpret output, and a discussion period where we all read assigned

work that apply the topic.

1.3 Texts and Software

Required texts are:

(BA) Bordens, K. S. & Abbott, B. B. (2005). Research Design and Methods: A Process Approach (sixth

ed). McGraw Hill. ISBN: 13: 978-0-07-297571-0

(Vogt) Vogt, W. P. (2007): Quantitative Research Methods for Professionals. Allyn & Bacon.

ISBN: 0-205-35913-2

Primary software: SPSS (Statistical Package for the Social Sciences). We will use the Windows version

as much as possible. The examples I will offer in class and the lab computer exercises will be computed

in SPSS. SPSS online tutorials are available on http://people.coe.ilstu.edu/jkrugut/SPSS/

1.4 Required Student Tasks

Course Requirements and Required Student Tasks:

Participate in all class activities, complete all assigned readings, and be prepared to discuss them in class;
Complete the assignments by the due dates;
Complete a final paper and deliver presentation of the paper.

1. Class Participation/Attendance. Attendance and active participation in class is very important

and will be part of your grade. Note that work on data analysis using computers will be primarily an

in-class activity, so attendance is particularly crucial. Being sick will not count as an absence. You

will receive a maximum of 5 points for class participation and attendance.

2. Assignments. Each student will complete two major assignments that together describe a process

for writing a research paper. More details are provided on the assignment link within the WebCT courseware.

1.5 Student Performance Evaluation Methods

The following point allocation will be used to determine final grades for the class:

1. Class participation/attendance 5 points

2. Assignments 1 & 2 20 points

3. Midterm 25 points

4. Final Project 20 points

5. Presentation of Final Project 5 points

6. Final Exam 25 points

Assignments. Assignments 1-2 are worth 10 points a piece for a maximum of 20 points. Handing in a well

thought out and well written assignment on the due date is worth 10 points. Assignments turned in late

will receive half-credit of 5 points if well done. A high-quality final paper submitted on time will receive

20 points. Final papers turned in one day late will receive a maximum of 15 points and final papers turned

in more than one day late will receive half-credit, or a maximum of 10 points. A well-done final presentation

of your results will receive 5 points. Students who do not present their results in will not receive credit for

the presentation.

Letter grades will be assigned in accordance with the following scheme:

Points Letter Grade
90-100 A (Exceptional Performance)

            80-89                  B (Above Average Performance)
            70-79                  C (Average Performance)
            60-69                  D (Below Average Performance)
            0-59                    F (Failing)

1.6 Delivery System

This course will be presented using a variety of delivery systems: The class will combine lecture,

seminar/discussion (in-class and through online), statistical computing and student presentation.

1.7 ISU Policies

ISU Regulations state:

"Written or other work a student submits in a course must be the product of his/her own efforts: plagiarism, cheating, or other forms of academic dishonesty are prohibited." Cases of suspected copying, cheating, or plagiarism are referred to Student Dispute Office for a University hearing.

Any student who needs to arrange a reasonable accommodation for a documented disability should contact Disability Concerns at 350 Fell Hall, 438-5853 (voice), 438-8620 (TDD).