2018–2019 Walden University Student Handbook (September 2018) 
    
    Apr 03, 2020  
2018–2019 Walden University Student Handbook (September 2018) [ARCHIVED CATALOG]

Doctoral Research Sequence


Return to: Learning and Research Resources  

Internal and external researchers and program leaders representing Walden University’s fields of doctoral study key stakeholders collaborated to generate a list of specific research competencies expected of all doctoral graduates from Walden.

Research competency standards of PhD programs in typical graduate programs were reviewed, as were those of external higher education associations such as The Higher Learning Commission of the North Central Association of Colleges and Schools and the Council of Graduate Schools, as well as several professional accrediting bodies.

The result of this extensive review and collaboration resulted in establishing 48 specific areas of competency organized around the following seven broad areas:

  1. Philosophy of research
  2. Research project design and approaches
  3. Quantitative research techniques
  4. Qualitative research techniques
  5. Quantitative quality assurance
  6. Qualitative quality assurance
  7. Professional practice

The doctoral research sequence described below was designed to ensure that doctoral students at Walden meet the minimum research competencies. Also see these courses in the Walden University Catalog.

RSCH 8110 - Research Theory, Design, and Methods (5 cr.)
In this research course, students are provided with core knowledge and skills for understanding, analyzing, and designing research at the graduate level. Students explore the philosophy of science, the role of theory, and research processes. Quantitative, qualitative, and mixed-methods research designs and data collection methods are introduced. The alignment of research components is emphasized. Students also explore ethical and social change implications of designing and conducting research. Students demonstrate their knowledge and skills by developing an annotated bibliography.

RSCH 8210 - Quantitative Reasoning and Analysis (5 cr.)
In this research course, students are provided with the opportunity to develop core knowledge and skills for designing and carrying out quantitative research at the doctoral level, including the application of statistical concepts and techniques. Students explore classical common statistical tests, the importance of the logic of inference, and social change implications of conducting quantitative research and producing knowledge. Students approach statistics from a problem-solving perspective with emphasis on selecting appropriate statistical tests for a research design. Students use statistical software to derive statistics from quantitative data and interpret and present results.

RSCH 8310 - Qualitative Reasoning and Analysis (5 cr.)
Students in this research course are provided with the opportunity to develop basic knowledge and skills for conducting qualitative research at the doctoral level. Students explore the nature of qualitative inquiry; how theory and theoretical and conceptual frameworks uniquely apply to qualitative research; data collection procedures and analysis strategy; and how the role of the researcher is expressed in the ethical and rigorous conduct of qualitative research. Students practice collecting, organizing, analyzing, and presenting data, and they develop a detailed research topic for conducting a qualitative study.

Together these three courses will provide an introductory-level background in each of the 48 competencies identified as being common to Walden faculty expectations, the expectations of similar programs in well-respected traditional universities, and the standards of a wide range of accrediting bodies.

All PhD students are required to complete one advanced-level research course that mirrors the methodology of their intended dissertations. The university offers three advanced courses. Students should refer to their specific programs of study to determine program-specific requirements.

RSCH 8260 - Advanced Quantitative Reasoning and Analysis (5 cr.)
Students in this research course build upon knowledge and skills acquired in the prerequisite quantitative reasoning course and are presented with opportunities to apply them. They are provided with more specialized knowledge and skills for conducting quantitative research at the doctoral level, including understanding multivariate data analysis and applying more advanced statistical concepts, such as factorial ANOVA, mediation, moderation, logistic regression, ANCOVA, and MANOVA. Students explore existing datasets and apply suitable statistical tests to answer research questions with social change implications. In this course, they approach statistics from a problem-solving perspective with emphasis on selecting the appropriate statistical tests for more complex research questions and social problems. Students use statistical software to perform analyses and interpret and present results. They will apply and synthesize their knowledge and skills by carrying out a quantitative research project. (Prerequisite(s): RSCH 8110/RSCH 8210.)

RSCH 8360 - Advanced Qualitative Reasoning and Analysis (5 cr.)
Students build upon the knowledge and skills acquired in RSCH 8310 - Qualitative Reasoning and Analysis. and have experience applying them. Students develop a more sophisticated understanding of the theoretical antecedents and practical applications of eight contemporary qualitative approaches. Students gain experience developing qualitative interview guides, collecting data, and managing the process from transcription through analysis. The unique challenges of confidentiality and ethical issues are explored as well as implications for social change. Students will apply and synthesize their knowledge and skills by developing a qualitative research plan using a topic relevant to their capstone. (Prerequisite(s): RSCH 8110 or RSCH 7110 or RSCH 6110 and RSCH 8310.) Note: This course was previously RSCH 8350.

RSCH 8460 - Advanced Mixed Methods Reasoning and Analysis (5 cr.)
Students build upon knowledge and skills acquired in RSCH 8210 - Quantitative Reasoning and Analysis and RSCH 8310 - Qualitative Reasoning and Analysis for more specialized knowledge and skills to design mixed-methods research at the doctoral level. Students are provided with more specialized knowledge and skills for designing mixed-methods research at the doctoral level. They gain an understanding of the types of mixed-methods designs and how to select the most appropriate approach for the research question(s). The emphases of this course are on integrating quantitative and qualitative elements into true mixed-methods studies, practice in data analysis, and integration of qualitative and quantitative data within a research writeup. Students will apply and synthesize their knowledge and skills by developing a mixed-methods research plan that incorporates qualitative and quantitative elements appropriately. (Prerequisite(s): RSCH 8110 or RSCH 7110 or RSCH 6110 and RSCH 8210 or RSCH 7210 or RSCH 6210 and RSCH 8310 or RSCH 7310 or RSCH 6310.) Note: This course was previously RSCH 8450.

Completion of the doctoral research sequence (RSCH 8110, RSCH 8210, and RSCH 8310) and the additional advanced-level courses required within each student’s program will enable students to achieve mastery of the specific set of these research competencies required for their field of study and professional goals.

Doctoral Research Sequence Course Numbers

Program Research Sequence
PhD in Education RSCH 8110D, 8210D, 8310D
PhD in Management (formerly PhD in Applied Management and Decision Sciences) RSCH 8110Z, 8210Z, 8310Z
PhD in Health Services RSCH 8110X, 8210X, 8310X
PhD in Human Services RSCH 8110U, 8210U, 8310U
PhD in Public Health RSCH 8110H, 8210H, 8310H
PhD in Public Policy and Administration RSCH 8110P, 8210P, 8310

Doctoral Research Competencies and Related Learning Objectives 

Topic Areas and Competencies Example of Competency-Related Learning Objectives
Philosophy of Research
Empiricism Identify the influence of empiricism on quantitative research methodology.
Positivism and post-positivism Explain how the scientific method is based on positivism and post-positivism.
Interpretivism Contrast interpretivism with positivism.
Constructivism Contrast constructivism with determinism.
Deconstructivism or critical theory Explain how critical theory research approaches use the concepts of power and justice.
Research Project Design and Approaches
Formulating the research question Utilize a gap in past research on a topic to generate a testable research question.
Quantitative/qualitative distinctions Determine the types of research questions most appropriately addressed by quantitative, qualitative, and mixed-method designs.
Experimental research Explain why the experimental method is required for determining cause-effect relationships.
Quasi-experimental research Identify the advantages and disadvantages of key quasi-experimental designs.
Non-experimental designs (descriptive, correlational) Determine when it is appropriate to use non-experimental quantitative designs.
Program evaluation Distinguish program evaluation from other approaches to research.
Case studies Utilize case study findings to generate testable hypotheses.
Phenomenology Explain the purpose of research from a phenomenological perspective.
Ethnographic methods Contrast ethnography from other approaches to qualitative research.
Grounded theory methods Identify the key assumptions of grounded theory research.
Historical research Identify multiple sources of archival data relevant to their professional field and the limitations associated with such data.
Action research Explain why the advantages of action research may also be limitations.
Narrative inquiry Describe multiple forms of stories used in narrative analysis and how the “story” differs from a case study.
Quantitative Research Techniques
Descriptive statistics Know the definitions of mean, mode, and median and describe the situations where each should be used to describe the “average” value.
Probability distributions Know the characteristics of a normal distribution and explain how those characteristics are used in hypothesis testing with reference to the Central Limit Theorem.
Hypothesis testing Correctly test a hypothesis using quantitative data. Correctly interpret the results of that test with reference to Type I and II errors.
Multivariate analysis appropriate to field Describe how multivariate analyses are used in the students’ professional field.
Correlation Correctly calculate and interpret a Pearson correlation coefficient.
Non-parametric methods Understand the concept of rank and how it used in non-parametric statistics that test the difference between two or more groups.
Linear regression Know the assumptions of and correctly interpret ordinary least squares linear regression.
Quantitative analysis software (SPSS) Construct a data set using statistical software. Use that software to produce descriptive and inferential statistics.
Qualitative Research Techniques
Field notes Demonstrate skills in preparing field notes.
Pilot studies/field studies Identify different ways to collect qualitative data (i.e., individual or group interviewing; participant-observer journaling) and compare the relative tradeoffs of each approach.
Document (content) analysis Organize and analyze data through classification and coding.
Observation strategies Observe individuals, groups, objects, and settings in great detail.
Interviewing Understand how to develop an interview protocol and what is necessary for conducting effective interviews.
Focus groups Understand how to conduct focus groups in open-ended question and structured activity formats.
Questionnaires Demonstrate an understanding of conducting research using questionnaires.
Journaling Identify different ways to collect qualitative data (i.e., individual or group interviewing; participant-observer journaling).
Identifying themes in qualitative data Analyze data for meaning and make connections across categories.
Qualitative analysis software (Nvivo-NUDIST, Atlas) Produce multiple codes for a set of documents within qualitative analysis software. Use that software to show the relationship between at least two codes.
Quantitative Quality Assurance
Validity Describe what is meant by validity and how to assess external and internal validity.
Reliability Describe what is meant by reliability and how to assess external and internal reliability.
Sampling (random and deliberate) Define a random sample and explain why a researcher may use non-random samples in research.
Qualitative Quality Assurance
Trustworthiness Describe specific ways in which qualitative research is judged as rigorous.
Authenticity Discuss “fairness” in the integration of one’s own and others’ perspectives into the research process.
Sampling (purposive) Identify specific strategies within purposive sampling and explain why each might be used.
Professional Practice
Disseminating research to professional audiences (e.g., conferences) Identify at least two ways for disseminating research in their professional field and describe scholarly expectations associated with each.
Human subjects’ protection Explain the legal and ethical basis of human subjects’ protection along with the basic rights of participants participating in any research study.
Grant-writing Describe at least two sources of grants for conducting research in their field and basic requirements for securing grants from each source.
Integrating research with social change activity Describe past, current, and future potential contributions of research in their professional field to the public good.
Working with stakeholders (e.g., community-based research) Identify potential non-academic stakeholders in research from their professional field along with specific considerations in working with each stakeholder.
Professional writing Utilize appropriate conventions for professional writing when reviewing, reporting, and interpreting research findings.

EdD Research Sequence—Richard W. Riley College of Education and Leadership

Specialization in Administrator Leadership for Teaching and Learning

In this specialization, the research sequence consists of the following two courses:

  • EDAD 8141 - Applied Research in Education
  • EDAD 8145 - Project Study: Research in Practice

In addition to this, research modules will be embedded in the following three courses:

  • EDAD 8142 - Leading to Promote Learning
  • EDAD 8143 - Leading Professional Learning Communities
  • EDAD 8144 - School Leadership Capstone: Trends, Issues, and Global Perspectives

Specialization in Teacher Leadership

In this specialization, the research sequence consists of the following two courses:

  • EDUC 8141 - Applied Research in Education
  • EDUC 8145 - Project Study: Research in Practice

In addition to this, research modules will be embedded in the following three courses:

  • EDUC 8142 - Teaching and Learning: Theory and Research
  • EDUC 8143 - Collegial Interactions and Professional Development
  • EDUC 8144 - Teacher Leadership Capstone: Trends, Issues, and Global Perspective

Registering, Completing, and Receiving Credit for the Research Sequence Courses

Students register for the Research Sequence courses using the regular course registration process.