MATHEMATICS (TURKISH, PHD)
PhD TR-NQF-HE: Level 8 QF-EHEA: Third Cycle EQF-LLL: Level 8

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
EDT6001 Quantitative Methods in Educational Research Fall 3 0 3 9
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: Tr
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. ALİ BAYKAL
Course Lecturer(s): Prof. Dr. ALİ BAYKAL
Course Objectives: The course will address ways to design and assess higher order cognitive objectives and tasks to improve research skills.
 The primary aim is to understand the significance of educational interventions for the human participants in the life events.
 Participants are expected of analysis, and interpretation of research
 Descriptive, explanatory and prescriptive involvement in research design and assessment...
 Reflective, critical and creative mind-set in observations and narrations...
 Voluntary acceptance of unity and diversity of all learning experiences…
 Enthusiasm to propose and realize original research examples to enhance students’ learning, and educators' functioning...

Learning Outputs

The students who have succeeded in this course;
The course is designed and will be assessed with respect to followings outcomes:
These will be the evidence for successful completion of the course.
* Appropriate use of research terminology
* Identify the structural components educational research
* Properly interpret observations and evidence
* Explain the role of design and assessment in educational research
* Develop and manage research proposals of their own
* Recognize both the potentialities and limitations of the research methods

Course Content

MEASUREMENT CONCEPTS
Sources of data
Populations, parameters, samples and statistics
Descriptive and inferential statistics
Parametric and non-parametric statistics
Scales of measurement
The nominal scale
The ordinal scale
The interval scale
The ratio scale
Discrete and continuous variables
Limits of numbers
The frequency table
PRESENTING DATA
Bar graph
Histogram
Frequency polygo
Cumulative frequency graph or ogive
MEASURING TYPICAL ACHIEVEMENT
Calculating the mean from ungrouped data
The median
Calculating the median
The mode
Choosing a measure of central tendency
Use the mean
Use the median
Use the mode
The normal curve
A practical application of the normal probability curve
Some mathematical characteristics of the normal probability curve
MEASURING VARIATIONS IN ACHIEVEMENT
The range
Average deviation (A.D)
The standard deviation (S.D)
Calculating the standard deviation from ungrouped data
Coefficient of variation (V)
MEASURING RELATIVE ACHIEVEMENT
Percentiles
Method 1: Calculating percentile points
Method 2: Calculating percentile ranks for individual scores
Standard scores or Z scores
T-scale
Example problem
Grading
Example
MEASURING ASSOCIATION
Departure from independence between two factors
Magnitude of subgroup differences
Summary of pair-by-pair comparisons
Proportional reduction in error measures of association
Measures involving correlation
Calculating the product moment correlation coefficient r
Rank order correlation coefficients
Kendall's rank order correlation coefficient (t, tau)
Some further thoughts on relationships
The coefficient of determination
REGRESSION ANALYSIS
Simple linear regression
Multiple regression
Using the coefficient of determination in multiple regression analysis
INFERENTIAL STATISTIC
Sampling methods
Simple random sampling
Systematic sampling
Stratified sampling
Cluster sampling
Stage sampling .»
Sampling error
Levels of confidence
distributions
Degrees of freedom
Hypothesis formulation and testing
Statistical significance
One-tailed and two-tailed tests
Type 1 and Type 2 error
Independent and dependent variable
Correlated and uncorrelated data
Parametric and non-parametric statistics: some further observations
ONE GROUP DESIGN: SINGLE OBSERVATIONS ON ONE VARIABLE
Using the chi square one-sample test
Using the Kolmogorov-Smirnov one-sample test
ONE GROUP DESIGN: ONE OBSERVATION PER SUBJECT ON EACH OF TWO OR MORE VARIABLES
Using the Pearson product moment correlation coefficient
Using simple linear regression
Using Spearman's rank order correlation coefficient (rho)
Using Kendall's rank order correlation coefficient (tau)
Using the point biserial correlation coefficient
Using the correlation coefficient tetrachoric r
Using partial correlation
Using the phi coefficient
Using Yule's Q
Using the contingency coefficient
Choosing a measure of association
ONE GROUP DESIGN: REPEATED OBSERVATIONS ON THE SAME SUBJECTS UNDER TWO CONDITIONS OR BEFORE AND AFTER
Using the r test for correlated data
Using the Wilcoxon matched pairs signed ranks test
ONE GROUP—MULTI-TREATMENT (TRIALS): TREATMENTS AS INDEPENDENT VARIABLE
Using the one-way analysis of variance for correlated means (with repeated
measures on the same sample or separate measures on matched samples)
Using the Friedman two-way analysis of variance by ranks
TWO GROUP DESIGNS: STATIC COMPARISONS ON ONE OR MORE VARIABLES
Using the (test for independent samples (pooled variance)
Using the t test for independent samples (separate variance)
Using the Mann-Whitney U test (for moderately large samples N2 between 9
Using the Mann-Whitney U test (for large samples JV2 20)
Using x2, chi square (2 x k)
Using the Kolmogorov-Smirnov two-sample test
MULTI GROUP PESIGN: MORE THAN TWO GROUPS, ONE SINGLE VARIABLE
Using one-way analysis of variance, independent samples.
Using the Kruskal-Wallis one-way analysis of variance by ranks
Using chi square in (fcxn) tables
FACTORIAL DESIGNS—THE EFFECT OF TWO INDEPENDENT VARIABLES ON THE DEPENDENT VARIABLE
(a) No repeated measures on factors
(b) Repeated measures on ONE factor
(c) Repeated measures on BOTH factors

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Scales of measurement The nominal scale The ordinal scale The interval scale The ratio scale Error of Isomorphism Read Listen Discuss Reflect Recite Review
2) Discrete and continuous variables Limits of numbers The frequency table Bar graph Histogram Frequency polygo Cumulative frequency graph or ogive Read Listen Discuss Reflect Recite Review
3) Calculating the mean from ungrouped data The median Calculating the median The mode Choosing a measure of central tendency Use the mean Use the median Use the mode The normal curve A practical application of the normal probability curve Some mathematical characteristics of the normal probability curve The range Average deviation (A.D) The standard deviation (S.D) Calculating the standard deviation from ungrouped data Coefficient of variation (V) percentiles Method 1: Calculating percentile points Method 2: Calculating percentile ranks for individual scores Standard scores or Z scores T-scale Example problem Grading Example
4) Departure from independence between two factors Magnitude of subgroup differences Summary of pair-by-pair comparisons Proportional reduction in error measures of association Measures involving correlation Calculating the product moment correlation coefficient r Rank order correlation coefficients Kendall's rank order correlation coefficient (t, tau) Some further thoughts on relationships The coefficient of determination Observe Attend Exemplify Scan Read Reproduce Recite
5) Using the Pearson product moment correlation coefficient Using simple linear regression Using Spearman's rank order correlation coefficient (rho) Using Kendall's rank order correlation coefficient (tau) Using the point biserial correlation coefficient Using the correlation coefficient tetrachoric r Using partial correlation Using the phi coefficient Using Yule's Q Using the contingency coefficient Choosing a measure of association Graziano, A. M., & Raulin, M. L. (1993). Research methods: A process of inquiry. HarperCollins College Publishers.
6) Using the r test for correlated data Using the Wilcoxon matched pairs signed ranks test Using the (test for independent samples (pooled variance) Using the t test for independent samples (separate variance) Read Listen Discuss Reflect Recite Review
7) Using the Mann-Whitney U test (for moderately large samples N2 between 9 Using the Mann-Whitney U test (for large samples JV2 20) Read Listen Discuss Reflect Recite Review
8) Using the one-way analysis of variance for correlated means (with repeated measures Read Listen Discuss Reflect Recite Review
9) Using the Friedman two-way analysis of variance by ranks Read Listen Discuss Reflect Recite Review
10) Using x2, chi square (2 x k) Using the Kolmogorov-Smirnov two-sample test Read Listen Discuss Reflect Recite Review
11) Using one-way analysis of variance, independent samples. Using the Kruskal-Wallis one-way analysis of variance by ranks Read Listen Discuss Reflect Recite Review
12) MIDTERM EXAMINATION Open book and open not-book exam Scan Read Listen Discuss Reflect Recite Review
13) Using chi square in (fcxn) tables Read Listen Discuss Reflect Recite Review
14) (a) No repeated measures on factors (b) Repeated measures on ONE factor (c) Repeated measures on BOTH factors Read Listen Discuss Adapt Exemplify Reflect Recite Review

Sources

Course Notes: Cohen, L., Manion, L., Morrison, K. (n.d.). Research methods in education: http://knowledgeportal.pakteachers.org/sites/knowledgeportal.pakteachers.org/files/resources/RESEARCH%20METHOD%20COHEN%20ok.pdf
References: Airasian, G. Mills (2014). Educational Research: Competencies for Analysis and Applications. Pearson: USA Al-Habaish, S. M. (2012). The Correlation between General Self-Confidence and Academic Achievement in the Oral Presentation Course. Theory and Practice in Language Studies, 2(1), 60-65. Antonios, R. (2013). Interpereting quantitative data with IBM SPSS statistics. Sage Publications. Ary, D., Jacobs, L., Razavieh, A. & Sorensen, C. (2009) Introduction to Research in Education. Canada: Wadsworth Cengace Learning. Bachman, L. F. (2004). Statistical Analyses for Language Assessment. Cambridge University Press. Campbell, D. T., Stanley, J. C. (1966). Experimental and quasi-experimental designs for research. Boston: Houghton Mifflin Company. Cohen, L., & Holliday, M. (1982). Statistics for Social Scientists: An Introductory Text with Computer Programs in Basic. Harper and Row Publisher (pp.206-306) London Cohen, L., Manion, L., Morrison, K. (n.d.). Research methods in education. Retrieved from http://knowledgeportal.pakteachers.org/sites/knowledgeportal.pakteachers.org/files/resources/RESEARCH%20METHOD%20COHEN%20ok.pdf Creswell, J. W. (2002). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Saddle River, NJ: Prentice Hall. Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Fourth Edition, Lincoln: Sage Publications. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (Vol. 8). New York: McGraw-Hill. Gay, L.R., Mills, G.E., & Airasian, P.W. (2014) Educational Research: Competencies for Analysis and Application (10th ed.). Pearson New International. 66, 124, 343, 503. Graziano, A. M., & Raulin, M. L. (1993). Research methods: A process of inquiry. HarperCollins College Publishers. Jackson, S. L. (2011) Research Methods and Statistics: A Critical Thinking Approach. United States: Wadsworth Cengace Learning.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance 10 % 15
Laboratory 0 % 0
Application 0 % 0
Field Work 0 % 0
Special Course Internship (Work Placement) 0 % 0
Quizzes 0 % 0
Homework Assignments 10 % 20
Presentation 0 % 0
Project 0 % 0
Seminar 0 % 0
Midterms 1 % 25
Preliminary Jury 0 % 0
Final 1 % 40
Paper Submission 0 % 0
Jury 0 % 0
Bütünleme % 0
Total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 13 3 39
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 0 0 0
Presentations / Seminar 0 0 0
Project 0 0 0
Homework Assignments 12 12 144
Quizzes 0 0 0
Preliminary Jury 0 0 0
Midterms 1 3 3
Paper Submission 0 0 0
Jury 0 0 0
Final 1 3 3
Total Workload 189

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution