| EDUCATIONAL TECHNOLOGY (TURKISH, PHD) | |||||
| PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| EDT6001 | Quantitative Methods in Educational Research | Fall | 3 | 0 | 3 | 9 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
| Language of instruction: | Turkish |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Assist. Prof. ZEYNEP CÖMERT |
| Course Lecturer(s): |
Prof. Dr. ALİ BAYKAL |
| Recommended Optional Program Components: | None |
| 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... |
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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 |
| 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 |
| Week | Subject | Related Preparation |
| 1) | MEASUREMENT CONCEPTS Measurement Assessment Evaluation 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 Error of Isomorphism | Read Listen Discuss Reflect Recite Review |
| 2) | PREPARATION AND PRESENTING DATA Discrete and continuous variables Limits of numbers The frequency table Bar graph Histogram Frequency polygo Cumulative frequency graph | Read Listen Discuss Reflect Recite Review |
| 3) | MEASURING TYPICAL ACHIEVEMENT MEASURING RELATIVE ACHIEVEMENT MEASURING VARIATIONS IN 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 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) | MEASURING ASSOCIATION, DEPENDENCY AND RELATIONSHIP 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) | 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 | Graziano, A. M., & Raulin, M. L. (1993). Research methods: A process of inquiry. HarperCollins College Publishers. |
| 6) | ONE GROUP DESIGN: REPEATED OBSERVATIONS ON THE SAME SUBJECTS UNDER TWO CONDITIONS OR BEFORE AND AFTER TWO GROUP DESIGNS: STATIC COMPARISONS ON ONE OR MORE VARIABLES 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) | TWO GROUP DESIGNS: STATIC COMPARISONS ON ONE OR MORE VARIABLES 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) | ONE GROUP—MULTI-TREATMENT (TRIALS): TREATMENTS AS INDEPENDENT VARIABLE Using the one-way analysis of variance for correlated means (with repeated measures | Read Listen Discuss Reflect Recite Review |
| 9) | ONE GROUP—MULTI-TREATMENT (TRIALS): TREATMENTS AS INDEPENDENT VARIABLE Using the Friedman two-way analysis of variance by ranks | Read Listen Discuss Reflect Recite Review |
| 10) | TWO GROUP DESIGNS: STATIC COMPARISONS ON ONE OR MORE VARIABLES Using x2, chi square (2 x k) Using the Kolmogorov-Smirnov two-sample test | Read Listen Discuss Reflect Recite Review |
| 11) | 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 | Read Listen Discuss Reflect Recite Review |
| 12) | MIDTERM EXAMINATION | Scan Read Listen Discuss Reflect Recite Review |
| 13) | MULTI GROUP PESIGN: MORE THAN TWO GROUPS, ONE SINGLE VARIABLE Using chi square in (fcxn) tables | Read Listen Discuss Reflect Recite Review |
| 14) | 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 | Read Listen Discuss Adapt Exemplify Reflect Recite Review |
| Course Notes / Textbooks: | 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. |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | 10 | % 15 |
| Homework Assignments | 10 | % 20 |
| Midterms | 1 | % 25 |
| Final | 1 | % 40 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Study Hours Out of Class | 1 | 20 | 20 |
| Project | 1 | 10 | 10 |
| Homework Assignments | 12 | 15 | 180 |
| Midterms | 1 | 20 | 20 |
| Final | 1 | 40 | 40 |
| Total Workload | 312 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | To comprehend current and advanced knowledge in the field of educational technology and being able to relate this knowledge information with education. | 5 |
| 2) | To comprehend relations between Educational Technology and others disciplines and being able to state ideas concerning possible implementations in framework of these relations. | 3 |
| 3) | To be able to evaluate, improve and design applications, methods generate new ideas which are innovative for educational technology. | 3 |
| 4) | Being able to manage original research in educational technology using interdisciplinary perspective. | 4 |
| 5) | Being able to investigate original issues within the frame of scientific research techniques as independently or in cooperation with others. Then being able to present the obtained results as research report. | 5 |
| 6) | Being able to advocate original views in discussions in the field of educational technologies. | 3 |
| 7) | Being able to communicate with experts in the field of educational technologies in written, orally and visually. | 2 |
| 8) | Being able to create new ideas and techniques concerning educational technology using high level mental process such as creative and critical thinking, problem solving and decision making. | 3 |
| 9) | Being able to make contributions to the society in being an information society and sustaining this by following the emerging scientific, technological, social and cultural developments. | 3 |
| 10) | To make contribution to solve social, scientific, cultural and ethic problems in issues related to e-learning technologies and promote development of these values. | 3 |
| 11) | Being able to make contributions to the knowledge in the field by publishing a scientific article in the field of educational technologies at national or international journals. | 4 |
| 12) | Being able to lead the situations when original and interdisciplinary problems are needed to be solved. | 3 |