Students are introduced to basic concepts of quantitative research design, methodology, and interpretation of results. Students analyze data sets to become adept at interpreting a wide range of statistical results. Quantitative analysis and interpretation are applied to typical local based samples and large databases. This set of conceptual and methodological skills is applied to proposed research designs.
Course Objectives:
This course presents the broad scope and methods of quantitative research. Students will be introduced to and supported to use generally accepted methods for quantitative data organization and management. Students will employ specific analytical approaches in interpreting data. Students will be introduced to several quantitative methodologies and required to articulate the ways that researchers organize and execute quantitative inquiry to inform organizational inquiry and transformation.
Note: It will be assumed that students have prior knowledge of some basic statistics terminology and applications to fully understand the concepts introduced in this course. Advanced computational mathematics and statistics will not be required to complete the course assignments, but a foundational understanding of applied statistics concepts may be necessary. Students may gain this knowledge with recommended supplemental readings embedded within the course modules.
Student Learning Outcomes:
Self-Assessments
Self-assessment should address all of the readings and tasks you completed individually and in your small group for the assigned time period. Refer to your mastery of objectives, clarity/accuracy, and participation in the assigned tasks during the time assigned, providing a recommended grade (low pass, pass, high pass) and a justification for your recommendation.
Class and Small Group Discussion Board Posts & Comments
Online discussions provide participants with opportunities to make meaning of new theory, key concepts, and applications of theory to practice. Participants contribute to the intellectual development of the cohort by offering insights, synthesizing understandings, and responding to the postings of others. The co-construction of knowledge is especially transparent in the online environment, unlike face to face classrooms where only a few individuals may offer ideas in a public forum. While somewhat less formal than a paper, the quality of your postings should reflect the standards of a submitted paper.
Assignments: Reading Synthesis, Statistical and Quantitative Research Definitions Quiz, and Preparing Data for Correlation Analysis
The three assignments required for this course (Reading Synthesi>s, Statistical and Quantitative Research Definitions Quiz, Preparing Data for Correlation Analysis) vary somewhat in the nature of the task. However, each rubric addresses the general expectations of the work. Specific comments/feedback relevant to each assignment may be added by the instructor on assessed work.
Quantitative Research Analysis & Evaluation Essay
Read one summary report and three full reports of empirical studies. In this essay, you should analyze and evaluate the methods, findings, conclusions and presentation of data of all four reports. Discuss elements that are common to the reports collectively, as well as, some characteristics that may be specific to individual reports. In your evaluation, identify a strength of one or multiple reports. In addition, identify one weakness in a quantitative methodology of one of the three original studies and propose an alternative that would strengthen this area.
Your grade in this course will be determined by the following criteria:
Assignments | Points |
---|---|
Discussion Board Posts & Comments (5 points each) | 30 |
Assignments (10 points each) | 30 |
Self-Assessments (5 points each) | 10 |
Quantitative Research Analysis & Critique Essay | 30 |
Total | 100 |
The criteria for all courses in the Ed. D. program are described in the modules and/or rubrics. Assignments will include guidelines with rubrics, descriptions of expectations, or examples, and include point values. Coursework will be assessed and graded using individual evaluation protocols that are provided for the three major assignments. Final “grades” will reflect the following schema:
Note** The instructor will determine if an assignment may be revised and resubmitted for rescoring. Candidates may proceed to subsequent courses in the curriculum with one LP grade, and although there is no failing grade, a second LP course grade results in termination from the doctoral program.
All assignments are to be completed in a timely manner with appropriate accuracy, detail, thought and reflection fitting of doctoral-level degree candidates. All assignments (done in writing or with other media applications) are graded on the basis of faculty assessment of your ability to accurately apply concepts from readings, organization, and mechanics. Please note that you must save all submitted documents in Microsoft Word/Excel/PowerPoint in order for them to transmit successfully. All work must be properly identified and include author(s)’ name(s). Submit all written work in APA style (Refer to the APA Publication Manual for guidance; Purdue OWL is an excellent, user-friendly resource).
Notes:
Week |
Topic |
Activities & Assignments |
Due Date |
1 5/2-5/6 |
Quantitative Methods |
Introduction Class Discussion Board (DB) Reading Synthesis Assignment Readings: Creswell ch.1, 2 & 4; Cassuto; Mukherjee |
Intro DB (Ungraded) – by 11:59 PM ET on Sunday, 5/6 Reading Synthesis – by 11:59 PM ET on Sunday, 5/6 |
2 5/7-5/13 |
Quantitative Data Collection |
Data Collection Data Collection Small Group DB & Comments Self Assessment Readings: Smith & Rabin; Creswell ch.5; Jensenius Viewings: sample NCES data set; online databases |
Sm Group DB Initial Post – by 11:59 PM ET on Wednesday, 5/9 Sm Group DB Comments – by 11:59 PM ET on Sunday, 5/13 Self-Assessment – by 11:59 PM ET on Sunday, 5/13 |
3 5/14-5/20 |
Quantitative Research Designs |
Small Group Work – Definitions & Quiz Class DB Post & Comments – Research Topic Readings: Creswell ch.10-12; Gorman; Nunez et al.; Ladd |
Class DB Initial Post – by 11:59 PM ET on Wednesday, 5/16 Class DB Comments – by 11:59 PM ET on Sunday, 5/20 |
4 5/21-5/27 |
Statistics & Quantitative Data Analysis |
Small Group Work – Definitions Small Group Quiz Stats & Quant Research Quiz & Self Assess Readings: Creswell ch.6; Lazer et al. Recommended: Agresti & Finlay; Thompson et al.; DeCoster; Baker; Fisher; stats videos |
Sm Group-Developed Quiz – by 11:59 PM ET on Wednesday 5/23 Research Quiz Self Assessment – by 11:59 PM ET on Sunday 5/27 |
5 5/28-6/3 |
Quantitative Data Preparation |
Data Preparation Individual Assignment Class DB Post & Comments – Data Preparation Readings: Creswell; Microsoft; Hellerstein; Trochim |
Data Preparation Assignment – by 11:59 PM ET on Wednesday, 5/30 Class DB Data Preparation Post – by 11:59 PM ET on Friday, 6/1 Class DB Comments – by 11:59 PM ET on Sunday, 6/3 |
6 6/4-6/10 |
Interpretation of Results & Reporting Findings |
Class DB Post & Comments – Presenting Data Readings: Nellie Mae report & supporting studies; SPSS output; DataGraph scatterplot; S.Moon data map; data viz galleries Small Group: DRAFT Quantitative Research Analysis & Evaluation Essay: Interpreting and Critiquing Reports of Research Findings |
Class DB Data Presentation Post – by 11:59 PM ET on Wednesday, 6/6 Class DB Comments – by 11:59 PM ET on Friday 6/8 Small DB Draft Essay – by 11:59 PM ET on Sunday, 6/10 |
7 6/11-6/17 |
Review & Epistemology |
Class DB Post & Comments – Methodology & Epistemology Small Group: Peer Review Comments of DRAFT Quantitative Research Analysis & Evaluation Essays Readings: Pole; Johnson & Onwuegbuzie; Feynman; Smith & Heshusius Quantitative Research Analysis & Evaluation Essay |
Small DB Peer Review Comments – by 11:59 PM ET on TUESDAY, 6/12 Class DB Method & Epistemology Post – by 11:59 PM ET on Wednesday, 6/13 Class DB Comments – by 11:59 PM ET on Sunday, 6/17 Essay – by 11:59 PM ET on Sunday, 6/17 |
8 6/18-6/24 |
Course Reflections & Evaluation |
Class DB Post – Course Final Reflections Self Assessment |
Class DB Post – by 11:59 PM ET on Wednesday, 6/20 Course Self Assessment – by 11:59 PM ET on Friday, 6/22 |
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