Module 5 Chapter 5: Course Conclusions

This concludes the reading activities for the first course in our two-course sequence, SWK 3401. In these five modules you covered a great deal of information related to the course title: Research & Statistics for Understanding Social Work Problems and Diverse Populations. Here is a brief synopsis of what you learned in each module.

Module 1.The Importance of Research to Social Work Practice; Research Ethics

The first course module provided an orientation to the important relationship research and evidence play in social work practice and promoting social justice, including the profession’s mandates regarding the place for research in social work. This orientation analyzed different types and sources of knowledge (“ways of knowing”) used by social workers in developing an understanding of social work problems, diverse populations, and social phenomena. It also provided a context for understanding the place of research and empirical evidence in the wider realm of knowledge we use. The module presented principles of critical thinking engaged by social workers, and presented key distinctions between science, pseudoscience, and opinion. Within this orientation, the philosophical roots of different approaches to evidence were identified (positivism, empiricism, and ethnoepistemology in quantitative and qualitative research), as were relationships between theory, research, and practice. Strategies for locating sources of empirical evidence were explored in this first module. Finally, a great deal of attention was directed to the ethical conduct of research and important considerations for research involving human participants.

Module 2. Identifying and Applying Evidence

Our second course module extended what was learned in the first by developing a framework for understanding different types of research questions and study specific aims. The distinction between research questions and research hypotheses was explained, as were differences between background/foreground, exploratory, descriptive, and explanatory research questions. The relationship between types of questions and scientific approach was addressed. A translational science framework explained differences between basic, intervention, and implementation science, as well as “research for and about research.” These categories were developed as strong influences on all subsequent decisions made by investigators. This module analyzed the role of theory in research and identified ways of identifying and assessing empirical evidence regarding social work problems, diverse populations, and social phenomena. Furthermore, a great deal of emphasis was placed on evaluating empirical literature and distinguishing between empirical and non-empirical literature. In the course of completing Module 2, you were introduced to working with Excel spreadsheets.

Module 3. Research Approaches, Designs, and Methods

Our third course module extended from the background presented in Modules 1 and 2 to explore specific approaches, designs, and methodologies used in qualitative, quantitative, and mixed methods research. The relationship between research questions and research approaches was elaborated in this module with an overview and details for each approach (qualitative, quantitative, mixed methods). Six major traditions in qualitative research were explored: narrative, phenomenological, grounded theory, ethnographic, participatory action, and content analysis research. Design issues of generalizability, internal and external validity, cross-sectional and longitudinal study were examined with regard to quantitative research traditions. Distinctions between descriptive, correlational, and experimental research were identified, as was the distinction between correlation and causality. Delving deeper into quantitative methods, a great deal of attention was directed to recognizing different types of variables and their implications for study design, measurement, and analysis (demographic, independent, dependent, categorical/nominal, ordinal, interval/continuous). Measurement issues in quantitative science were addressed, including measurement validity and reliability, as well as cultural competence in measurement approaches. Different strategies for collecting qualitative and quantitative data were explored: naturalistic observation, Photovoice, artifact/content analysis, administrative and secondary data, geographic information systems (GIS), key informant information, surveys, clinical screening or assessment tools, interviews, focus groups, journaling, ecological momentary assessment (EMA), concept maps, and social network analysis. The final methodology chapter was devoted to study participants. Distinctions were made between samples and populations, and key issues related to the recruitment and retention of study participants were explored. Not only were matters of sample size and diversity addressed, strategies for participant selection were analyzed (random selection as probability sampling, convenience and snow-ball selection as non-probability sampling). In the course of completing Module 3, your introduction to working with Excel spreadsheets and data files was extended.

Module 4. Understanding Descriptive and Inferential Statistics

The fourth module in this course was devoted to approaches used in analyzing data collected from the methods described in Module 3—qualitative, quantitative, and mixed methods analyses. In the chapter concerning qualitative analysis, you were introduced to data preparation, field notes, coding, coding confirmation, and cross-checking coding decisions. The subsequent chapters introduced quantitative analysis strategies and issues. These included distinguishing between univariate and bivariate analyses, use of inferential statistics, the role and interpretation of a null hypothesis, Type I and Type II error, and different types of analyses related to the nature of the variables and the research questions. You learned to conduct and interpret univariate descriptive analyses involving the frequency, proportion, mean, median, mode, variance, standard deviation, probability, and normal distribution of data. In addition, you learned to conduct and interpret five types of bivariate analyses: one-sample t-test, independent samplest-test, one-way analysis of variance (Anova), chi-square, and correlation analysis. The idea behind non-parametric analysis and two examples were also developed in this module. In the course of studying this content, you learned to conduct different types of analyses using Excel spreadsheets and data files.

Module 5. Presenting Evidence

By now you may recognize that the course has been structured, loosely, along the structure of an empirical report: an introduction (Module 1 and Module 2), Methods (Module 3), Results (Module 4), and Discussion (Module 5). Module 5 itself concerned ways that social workers communicate with various types of audiences about empirical evidence and scientific data concerning social work problems, diverse populations, and social phenomena. The module discussed important aspects of empirical manuscripts and professional reports, features of strong presentations, creating figures (graphs and charts), and creating infographics. With this concluding chapter of Module 5, you are now well-prepared to succeed in meeting the goals of the second course in our two-course sequence. In SWK 3402 your skills and knowledge will be applied to understanding social work interventions. Together the content in these two courses prepares you to engage effectively with evidence in social practice, regardless of the nature of practice in which you engage.

Stop and ThinkWhat do you believe was the single best thing you learned about in this course? Consider sending your answer to your instructor and/or including it in your course evaluation comments.


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Social Work 3401 Coursebook Copyright © by Dr. Audrey Begun is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, except where otherwise noted.

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