Chao Wrote:

Some trends that influence human resource are, Leadership Development and Learning Opportunities, Data and Analytics, Compliance and Regulation, Controlling and Containing Costs, and More Competition for Talent. But the one that I like and think its much important is leadership development and learning opportunity because in this role, companies give the employees the opportunity to learn and grow with the leadership training and this will show employees that the company wants employee to be more engage. Plus, this kind of program can also help nurture leadership abilities and professional development. The other trend I think that plays a very important role is knowing the compliance and regulations because in this area, compliance and regulation changes all the time and companies need to be more pro-active and make changes as they have updates with any new compliance or regulations. For this, many companies turn to technology solutions to minimize the costs and resources devoted to this task, freeing up HR professionals to focus on other aspects of their work. Some strategic resource examples include recruitment, learning and development, compensation, and performance appraisal.

Quane Wrote:

Hi Dr. Clark and Classmates,

Through my assigned reading for week 1, I've learned that one-third of large U.S. businesses selected non-Human Resources managers to operate in top tier executive positions. Consequently, the most successful Human Resource executive do have prior Human Resources experience so for the select few managers without a Human Resource background that get the opportunity to serve in a Human Resource executive will increase their probability of successful career progression. The new tentative transition for businesses is to outsource the majority of their Human Resource operational needs to large Human Resource firms that service multiple businesses. Many frequently utilized services will be offered to employees online in order to address the increased demand for specialized Human Resource services as well as shorten response times and increase efficiency.

Strategic Human Resource Management is the process of determining ways to evaluate an organization's unique Human Resources need and create a plan that facilitates the establishment and maintenance of efficient personnel management systems that support the short term and long term functionality and sustained growth of an organization.

Exercise 8 - Case Study Research

Develop a hypothetical research scenario that would warrant the application of the case study.

What type of approach within the qualitative method would be used? Why or why not?

Exercise 9 - Perspectives in Qualitative Methods

Develop a hypothetical research scenario that would warrant the application of the ethnographic, narrative or phenomenological approach.

What type of design would be best utilized along with this approach?

Exercise 10 - Factors in Mixed Methods Research

What are the strengths to conducting a mixed method study?

Discuss the three major factors that should be considered when conducting a mixed method study (i.e., emphasis, timing, and interpretation of mixing the finding).

The Case Study

Many disciplines use various forms of the case study to examine an individual or phenomenon within a specified context. The approach and application of case study designs also can vary widely between various disciplines such as medicine, law, and the social sciences. However, in the social and behavioral sciences, case studies are often referred to as uncontrolled studies. Yin (2013) defined the case study as an empirical inquiry that investigates a phenomenon within its real-world context, when the boundaries between phenomena and context are not clearly evident, in which multiple data sources are used. Yin referred to the case study as a “method” as opposed to confining it to only an approach or a “tradition” within the various forms of qualitative research (e.g., Creswell, 2012). Generally, the focus of the case study is on developing a narrative or revealing a phenomenon based on an in-depth, real-time, or retrospective analysis of a case. Therefore, issues related to experimental control and internal validity are nonfactors within this approach. Although case studies do not infer causation and the results should not be generalized, the findings can provide rich insight toward phenomena and serve as support for theories and the generation of hypotheses. However, if desired, Yin does offer approaches and models for researchers interested in attempting to infer causation from case study designs (which differs from QCA analysis).

The emphasis in a case study is primarily the qualitative method; however, cross sections of quantitative data are usually collected as supplementary data throughout the analyses (see mixed method embedded case study design). The label of case study is often applied to many social science examinations as a catchall term, many times misapplying the concept (Malcolm, 2010). However, the case study design can be applied to any of the approaches within the qualitative method, such as the most commonly applied narrative and phenomenological approach in psychology (Singer & Bonalume, 2010a) or the ethnographic approach in education (Creswell, 2014). Creswell took a different angle than Yin (2013) regarding the type and description of designs for the case study. Gall, Gall, and Borg (2007) succinctly described a case study “as (a) the in-depth study of (b) one or more instances of a phenomenon (c) in its real-life context that (d) reflects the perspective of the participants involved in the phenomenon” (p. 447).

Confusion does arise when authors use different terminology for similar constructs. These semantic differences can be seen in the work of Yin, who uniquely defined and applied the terms holistic and embedded (see Appendix B) differently than their traditional uses; for example, the term embedded has an entirely different meaning when used by Creswell. Another example of this is the term case study design, used within the qualitative method and most often associated with the ethnographic and phenomenological approaches. However, the case study can also be applied to the narrative approach and arguably any other approach within the qualitative method, as long as the “case” being explored is bound by time, place, person, or environment. When deciding to use a case study, we refer the reader to Yin’s (2004, 2012, 2013) books for a review of his unique and widely accepted approach to the case study. See Appendix B for a list of case study designs defined by Yin (2013) and Creswell (2014).

Recommended programs for qualitative data analyses: ATLAS/TI, The Ethnograph, HyperRESEARCH, NVivo, NUD*IST, SPSS Text Analysis for Surveys™

We refer the reader to the following books and book chapter for further details regarding qualitative methods:

· Creswell, J. W. (2012). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). Thousand Oaks, CA: Sage.

· Lincoln, Y. S., Linham, S. A., & Guba, E. G. (2011). Paradigmatic controversies, contradictions, and emerging influences., revisted. In N. K. Denzin & Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (4th ed.), pp. 191–215. Thousand Oaks, CA: Sage.

· Wertz, F. J., Charmaz, K., McMullen, L. M., Josselson, R., Anderson, R., & Emalinda, M. (2011). Five ways of doing qualitative analysis: Phenomenological psychology, grounded theory, discourse analysis, narrative research, and intuitive inquiry. New York, NY: Guilford Press.

Chapter 11 Grounded Theory Perspective

The grounded theory approach was first developed by Glaser and Strauss (1967) as a way to generate a theory based on data that are systematically gathered and analyzed. In general, this is an inductive process in which the theoretical propositions are not presented a priori; rather, the theory emerges from the data that are being collected. However, this process often becomes abductive, with testing of the theory occurring as it emerges from the data. The emerging theory is constantly being compared to the evidence brought forth from new data that are analyzed, as in the “constant comparative method.” The use of memoing (i.e., the process of recording the personal thoughts and ideas of the researcher throughout the data collection procedures) is critical when using a systematic, emerging, or constructivist design. Qualitative researchers often use memoing to help make conceptual links between raw data and abstractions to better explain the phenomena being studied within its appropriate context. See Birks, Chapman, and Francis (2008) for an in-depth discussion of memo-writing techniques.

According to Corbin and Strauss (2015), a good grounded theory should (a) fit the phenomenon; (b) provide understanding; (c) provide generality, in that the theory includes extensive variation and is abstract enough to be applicable to a wide variety of contexts; and (d) provide control, in the sense of stating the conditions under which the theory applies and describing a reasonable basis for action.

Systematic Design

· The systematic design is the most structured of the grounded theory approaches, with rigid procedures and a preconceived framework for categories. This design emphasizes theory verification based on the theory that is generated (i.e., inductive-deductive process). The design uses the three-stage coding method (open, axial, and selective) to help generate a visual depiction of a theory.

Emerging Design

The emerging design is also a theory generation design; however, it is less prescriptive than the systematic design. This design allows the theory to emerge “naturally” from the data. The key components of this design are fit, work, relevance, and modifiability.

Constructivist Design

The constructivist design further distances itself from the procedurally laden systematic design, stressing the role of the researcher as an active participant who interacts with the field being explored. Constructivist researchers are interested in the co-construction of knowledge between researcher and participant and embrace and explore the inherent biases within this interaction. This design recognizes that knowledge emerging from the data is not only “discovered” but also created. It is important to be cognizant of the assumptions brought to the investigation by the researcher. Also, one should be aware of the socially constructed meanings that occur during the collection of data and those socially constructed meanings that were in place prior to engaging with the participant.

When to Use Grounded Theory

· To build/discover theory inductively

· To build/discover substantive and/or formal theory

· When there is little or no prior information on an area or phenomenon

· To study the microcosm of interaction

We refer the reader to the following books for further details regarding the grounded theory approach:

Charmaz, K. (2014). Constructing grounded theory: A practical guide through qualitative analysis (2nd ed.). London, England: Sage.

Corbin, J., & Strauss, A. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory (4th ed.). Thousand Oaks, CA: Sage.

Glaser, B. G., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Hawthorne, NY: Aldine Transaction.

Figure 11.1 Systematic Design

Example for Figure 11.1

Han, G. S., & Davies, C. (2006). Ethnicity, health and medical care: Towards a critical realist analysis of general practice in the Korean community in Sydney. Ethnicity and Health, 11(4), 409–430.

Research Question: What are the general practitioners’ views on the health of Koreans and the complex process of providing and seeking effective and satisfactory medical care?

Procedures: This study investigated the use and provision of biomedicine among men on the basis of interview data from eight doctors. Semistructured interview schedules were prepared around the doctors’ 

Chapter 12 Ethnographic Perspective

Ethnography is an approach that was developed to describe cultures; this includes any culture that shares group characteristics such as values, beliefs, or ideas. The ethnographic researcher is interested in understanding another way of life from the point of view of the participants who make up the culture or group being studied. Because this perspective is based on understanding anything associated with human behavior and belief, it is well-suited for the fields of education and the social and behavioral sciences, including more recent areas of study like the research of culture and its relation to the Internet (see Hine, 2015).

Ethnography can be defined as research designed to describe and analyze the social life and culture of a particular social system, based on detailed observations of what people actually do. The researcher is embedded within the culture and takes a firsthand account of the beliefs, motivations, and behaviors of the individuals in the group. The data that are collected are used to (a) document the lives of the participants within the context of the culture, (b) understand the experiences of the individuals within the culture, or (c) interpret the behaviors shaped by the cultural context.

Realist Design

Van Maanen (1988) stressed three aspects of the realist design: (a) the invisible author (i.e., narrating in third person), (b) thick descriptions of the mundane (using a system of standard categories to organize the descriptions), and (c) interpretive “omnipotence” (i.e., allowing the author the final word in presenting the culture). The realist design offers one researcher’s overall perspective of a phenomenon from facts that are meticulously culled down to support a perspective. Thus, although the researcher’s duty is to objectively (without bias) present the facts, ultimately the interpretations of the facts come from the “omnipotent” researcher. In general, Spradley’s (1979, 1980) designs are less “narrative” or “literary” than those of van Maanen (1988) and Geertz (1998).

Critical Design

The critical design allows for the critiquing (i.e., challenging the status quo) of some existing system while maintaining a level of scientific inquiry. It provides a scientific framework for advocacy or a structure for directly examining relationships among cultural features, economic systems, knowledge, society, and political action. Put simply, Madison (2011) and Thomas (1993) both asserted that the critical design is used to describe, analyze, and scrutinize hidden agendas, power centers, and assumptions that inhibit, repress, and constrain. Thus, the real utility of a critical design is the structure it provides for researchers who are interested in explaining some form of ideology or power relations through the transformation of meaning and conceptualization of existing social systems.

Case Study Design

The case study design is often used with the ethnographic perspective; however, it has some distinct differences from traditional ethnography. While traditional ethnography is focused on group behavior, the case study design allows for the investigation of individuals as a whole (Creswell, 2012).1 This design provides the framework for an in-depth contextual analysis of a finite number of events or conditions and their associations. More specifically, the ethnographic case study allows for the examination of an actual case within some cultural group. The “case” being explored also can be a group bound by time, place, or environment (i.e., a group must be considered a unit, which is more than just a homogenous group). Researchers interested in exploring activities of a group, rather than shared patterns of group behavior, should follow this design.

When to Use Ethnography

· Studying a school, organization, or program in-depth

· Studying what people do

· Studying how things work or run

· Studying “insiders”

· Studying aspects of “culture” (e.g., practices, rituals, lives, interconnections, customs, values, beliefs, everyday life)

We refer the reader to the following books for further details regarding the ethnographic approach:

Fetterman, D. M. (2009). Ethnography: Step-by-step (3rd ed.). Thousand Oaks, CA: Sage.

Madison, D. S. (2011). Critical ethnography: Methods, ethics, and performance (2nd ed.). Thousand Oaks, CA: Sage.

Makagon, D., & Neumann, M. (2008). Recording culture. Thousand Oaks, CA: Sage.

Van Maanen, J. (1988). Tales of the field: On writing ethnography. Chicago, IL: University of Chicago Press.

Example for Figure 12.1

Purser, G. (2009). The dignity of job-seeking men: Boundary work among immigrant day laborers. Journal of Contemporary Ethnography, 38(1), 117–139.

Research Aim: Examine the discourses through which Latino immigrant day laborers make sense of, and find dignity within, their ongoing quest for work.

Procedures: The data collection involved ethnographic fieldwork and interviews with individual day laborers. The researcher conducted a total of 22 in-depth, loosely structured interviews with day laborers, 10 of whom regularly sought work out of the employment center and

Chapter 13 Narrative Perspective

The narrative approach involves gathering information, in the form of storytelling by the participant, for the purpose of understanding a phenomenon. Humans are storytelling beings by nature; we lead storied lives, both individually and collectively. Ultimately, the narrative approach is most widely used in the disciplines of psychology and psychiatry and is the study of the multitude of ways humans experience the world. Specifically, this approach involves collaboration between the researcher and participant, as a way to understand phenomena through stories lived and told. The narrative design involves (a) the exploration of a single participant or a small sample of participants, (b) gathering data through the collection of stories, (c) retelling the stories (restorying), and (d) reviewing the story with the participant to help validate the meaning and subsequent interpretation. The narrative design can be either biographical or autobiographical.

Dialogic listening skills are essential to the narrative approach; this type of “listening” is used throughout the whole process, as the researcher gathers data through conversations and engaged interchanges of ideas and information with the participant(s). The narrative approach can be conceptualized as descriptive, explanatory, or critical by design and follows the “underlying assumptions that there is neither a single, absolute truth in human reality nor one correct reading or interpretation of a text” (Polkinghorne, 1988, p. 2). There is also a structural approach in the way individual stories are studied (Riessman, 2007).

Dan McAdams (creating self in narrative) and Jefferson Singer (explanatory potential of the life story) have had a profound influence on the development and use of the narrative approach within the social and behavioral sciences. McAdams, Josselson, and Lieblich’s (2006) contributions included (a) the Life Story Interview method, (b) the Guided Autobiography, (c) the Loyola Generativity Scale, and (d) a set of coding manuals to analyze the stories of research participants. Singer’s (1997) book Message in a Bottle focused on men whose addictions were resistant to the traditional 12-step method and served as an excellent exemplar of the narrative approach. Singer also used the explanatory potential of the life story of individuals within the therapeutic context (see Singer & Bonalume, 2010a and 2010b, for more on autobiographical narrative approaches for case studies in psychotherapy).

Descriptive Design

The descriptive design involves the description of any one or more of the following: (a) individual or group narratives of life stories or specific life events, (b) the conditions or contextual factors supporting the story, (c) the relationship between individual stories and the culture the stories are embedded within, and (d) how certain life events impact the participants’ story line. Thus, the descriptive design is used to explore the status of some phenomenon and to describe what exists with respect to the individual, group, or condition.

Explanatory Design

The explanatory design is used to provide an account of some phenomenon by means of why something happened. Thus, the explanatory design is used to explore the causes and reasons of phenomena.

Critical Design

Van Maanen (1988), in his book on ethnography, discussed the use of “critical tales.” These critical tales are conceptualized as narrative approaches using a critical framework. A critical tale may illuminate individual experiences as well as larger social, political, symbolic, or economic issues. Thus, the critical design within the narrative approach involves the same structure or framework as the critical design within the ethnographic approach. Ultimately, this design allows for the critiquing of some existing system while maintaining a level of scientific inquiry.

When to Use Narrative Inquiry

· Telling stories about stories

· Exploring identity and conflict

· Examining the structure of experience

· Focusing on how people create meaning in their lives

· Exploring the interaction of individual stories with cultural narratives

We refer the reader to the following books for further details regarding the narrative approach:

Clandinin, D. J., & Connelly, F. M. (2004). Narrative inquiry: Experience and story in qualitative research. San Francisco, CA: Wiley.

Lieblich, A., Tuval-Mashiach, R., & Zilber, T. (1998). Narrative research: Reading, analysis, and interpretation. Thousand Oaks, CA: Sage.

Riessman, C. K. (2007). Narrative methods for the human sciences. Thousand Oaks, CA: Sage.

Example for Figure 13.1

Lapadat, J. C. (2004). Autobiographical memories of early language and literacy development. Narrative Inquiry, 14(1), 113–140.

Research Aim: To explore adults’ memories of their own acquisition of language and literacy learning

Procedures: Participants kept a journal in which they made regular entries over the semester, reflecting on their own personal history of learning language and literacy from the preschool years through the end of adolescence. The participants were asked to recall personally significant events, situations, and people that made a difference to their learning, as well as 

Chapter 14 Phenomenological Perspective

Phenomenology, put simply, is the description of an individual’s immediate experience. The phenomenological approach was born out of Edmond Husserl’s philosophical position that the starting point for knowledge was the self’s experience of phenomena, such as one’s conscious perceptions and sensations that arise from life experience. From this philosophy emerged the modern-day phenomenological approach to research with the goal of understanding how individuals construct reality. Researchers use the phenomenological approach when they are interested in exploring the meaning, composition, and core of the lived experience of specific phenomena. The researcher explores the conscious experiences of an individual in an attempt to distill these experiences or get at their essence.

Existential Design

The aim is to illuminate the essential general meaning structure of a specific phenomenon, with a focus on grasping the whole meaning of the experience, instead of dividing it into parts. Researchers using the existential design move from the concrete description of the experience of a given participant (co-researcher) to the interpretation of said experience. The participants (co-researchers) are asked for a description of their concrete experiences. The ultimate goal is to comprehend human experience as it is actually lived in the “real world” rather than in some artificial environment (von Eckartsberg, 1997).

Basic themes of existential phenomenology are (a) lived experience, (b) modes of being, and (c) ontology (the study of the nature of being, existence, or reality). In fact, the existential phenomenology associated with Heidegger’s philosophy is often referred to as ontological phenomenology, as it is primarily concerned with “being.” This differs from transcendental phenomenology, which is most associated with Husserl’s epistemological philosophy (concerned with knowledge).

Transcendental Design

Some key tenets of the transcendental design are (a) intentionality (consciousness is always intentional), (b) eidetic reduction (researcher accesses the consciousness of the participant to get at the pure essence of some phenomenon, thus revealing the essential structure), and (c) constitution of meaning (returning to the world from consciousness). This design is descriptive in nature, as it is through analysis and description of how things are constituted in, and by, consciousness that allows us to understand various phenomena. This design is useful for researchers who are interested in gathering data to grasp the essence of the human experience.

Hermeneutic Design

Some key tenets of the hermeneutic design are (a) interpretation, (b) textual meaning, (c) dialogue, (d) pre-understanding, and (e) tradition. The hermeneutic design deviates from the descriptive nature of which the phenomenological approach is most often associated. This design has a strong focus on reflective interpretation, made evident by Heidegger, who asserted that description is inextricably linked to interpretation. Essentially, this design is based on the fundamental theory that all forms of human awareness are interpretive.

Case Study Design

The case study design is also often used with the phenomenological perspective. This design lends itself well to the exploration of meaning of a lived experience of some phenomenon. This design provides the framework for an in-depth analysis of a finite number of participants. Researchers interested in exploring activities of an individual or small group, rather than the shared patterns of group behavior, should follow this design.

When to Use Phenomenology

· Studying people’s experiences

· Studying how people make meaning in their lives

· Studying relationships between what happened and how people have come to understand these events

· Exploring how people experience the essence of a particular phenomenon

· Examining the commonalities across individuals

We refer the reader to the following books for further details regarding the phenomenological approach:

Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretive phenomenological analysis: Theory, method, and research. Thousand Oaks, CA: Sage.

Vagle, M. D. (2014). Crafting phenomenological research. Walnut Creek, CA: Left Coast Press.

van Manen, M. (2014). Phenomenology of practice: Meaning-giving methods in phenomenological research and writing. Walnut Creek, CA: Left Coast Press.

Example for Figure 14.1

Smith, M. E. (2007). Self-deception among men who are mandated to attend a batterer intervention program. Perspectives in Psychiatric Care, 43(4), 193–203.

Research Aim: Gain an understanding of the perceptions of perpetrators of intimate partner violence (IPV) prior to beginning a Batterers’ Intervention Program (BIP).

Procedures: Qualitative methods used in this study were conducted according to the existential-phenomenological method outlined by Pollio, Henley, and Thompson (1997). The method of existential phenomenology was used in this study to provide men the opportunity to describe their perceptions concerning the meaning attached to being mandated to attend a BIP.

Part IV Mixed Methods

This part includes four popular approaches to mixed methods, followed by some of the associated basic designs (accompanied by brief descriptions of published studies that use the design). Most of the diagrams of mixed method designs were compiled and adapted from two major sources (Creswell & Plano Clark, 2011; Tashakkori & Teddlie, 2010a). Visit the companion website at  study.sagepub.com/edmonds2e  to access valuable instructor and student resources. These resources include PowerPoint slides, discussion questions, class activities, SAGE journal articles, web resources, and online data sets.

Mixed methods examinations combine various aspects of quantitative and qualitative methods (often referred to as quantitative and qualitative strands). Because this type of methodology mixes both the quantitative and qualitative method, the logic of inquiry may include the use of induction, deduction, and abduction. This approach allows researchers to further examine constructs at a “deeper” level, where the quantitative strand reveals what the qualitative strand leaves out and vice versa. From a philosophical viewpoint, a link has been established between pragmatism and mixed methods. That is, this method was developed as an attempt to legitimatize the use of multiple methodological strategies when answering research questions within a single study, which is considered a more practical approach to research. To conduct a sound mixed method study, it is critical that the researcher has a firm understanding of the distinguishing characteristics of quantitative methods (deduction, confirmation, hypothesis testing, explanation, prediction, standardized data collection, and statistical analysis) and qualitative methods (induction, discovery, exploration, theory generation, researcher as an instrument of data collection, and qualitative analysis). The mixed method includes the collection and analyses of quantitative (closed-ended and numerical) and qualitative (open-ended and textual) data (i.e., a quantitative and qualitative research question must be posed, individually analyzed and interpreted, and followed up with an overall interpretation).

Creswell and Plano Clark (2011) noted that one of the primary objectives in designing a mixed method study is to determine if the design should be fixed or emergent. Specifically, a fixed mixed method design is applied when the researcher predetermines the application and integration of a qualitative and quantitative method within a study. On the other hand, an emergent design is conducted when a researcher decides to include a qualitative or quantitative strand within an ongoing examination, purely based on necessity. The presentation within this guide falls more toward a typology-based approach—that is, we emphasize the various designs that are classified and developed for the use and application for mixed methods studies. Following those tenets, a researcher must consider many aspects regarding the implementation of a mixed method study. For example, the priority (or emphasis) of the qualitative and quantitative strands should be considered. Equal emphasis can be placed on the qualitative and quantitative method, or one strand can take priority over the other. The timing of the strands is also relevant. The strands can be implemented concurrently, sequentially, nested (embedded), or multilayered. The mixing of the strands should also be considered, which can happen during the interpretation phase, data collection, data analysis, or at the level of the design.

Philosophically speaking, although mixed methods studies are considered pragmatic, researchers should still be cautious when using the typology-based approach to mixed method research (Collins & O’Cathain, 2009). Many of the “established” mixed methods designs may not fully address the needs of the variety of research scenarios across the various disciplines. Therefore, a more general or generic approach may be warranted. Tashakkori and Teddlie (2010a) produced a sound matrix of the various mixed methods designs, which is summarized in Appendix C. However, most of the designs presented within this part follow Creswell and Plano Clark’s (2011) design typology. Within their book, they referred to these designs as variants. In addition, in an earlier version of their text, they referred to these designs as models, many with different names than those seen in their more recent text.

Mixed Methods Legend

The following notations are used in the depiction of the various mixed methods approaches and designs:

Chapter 15 Convergent-Parallel Approach

The convergent-parallel approach is a concurrent approach and involves the simultaneous collection of qualitative and quantitative data (usually both QUAL and QUAN are the emphasis), followed by the combination and comparisons of these multiple data sources (i.e., the two methods are ultimately merged). This approach involves the collection of different but complementary data on the same phenomena. Thus, it is used for the converging and subsequent interpretation of quantitative and qualitative data. This approach is often referred to as the concurrent triangulation design (single-phase) because the data is collected and analyzed individually but at the same time.

Parallel-Databases Design

The parallel-databases design is structured so the QUAN and QUAL data are collected separately (not within the same measures) but at the same time (concurrently). The analyses of data are also analyzed concurrently. The results are then converged by comparing and contrasting the data en route to one overall interpretive framework. This design allows researchers to validate data by converging the QUAN results with the QUAL findings. This design is also referred to as a triangulation design and convergence model, as seen in Seifert, Goodman, King, and Baxter Magolda’s (2010) examination.

Data-Transformation Design

The data-transformation design allows the researcher to collect QUAN and QUAL data separately but concurrently. Following the subsequent analyses, data are transformed by either transforming QUAN to QUAL or QUAL to QUAN. Therefore, the data are mixed during this stage, followed by the subsequent analyses.

Data-Validation Design

The validating quantitative data design is used to validate QUAN data with qual findings. Data from QUAN and qual are collected together (within the same measures), not separately. Within this design, the qual findings are not the emphasis; therefore, they are not subject to rigorous data reduction or analysis.

Multilevel Design

The multilevel design was originally introduced by Tashakkori and Teddlie (2002). This design allows the researcher to use different methodological techniques for addressing QUAN and QUAL data within a system. The QUAN results and QUAL findings from each level are then merged to provide an overall interpretation.

Figure 15.1 Parallel-Databases Design

Note: Any research design designated as experimental, quasi-experimental, or nonexperimental research can be used for the QUAN phase, and any approach designated under the qualitative method can be used for the QUAL phase.

Example for Figure 15.1

Hall-Kenyon, K. M., Bingham, G. E., & Korth, B. B. (2009). How do linguistically diverse students fare in full- and half-day kindergarten? Examining academic achievement, instructional quality, and attendance. Early Education and Development, 20, 25–52.

Research Questions

· Quantitative: What are the effects of instructional quality on academic achievement (math and literacy)?

· Qualitative: What are teacher and administrator perceptions of full- and half-day programs, and how do teachers’ instructional behaviors influence academic achievement?

· Mixed Method: To what extent do the QUAN data and QUAL data converge?

Procedures

· Quantitative: Eight kindergarten classrooms were used—four full-day classrooms and four half-day classrooms. The four kindergarten classrooms from the treatment school were in the first year of implementing a full-day pilot program. The four classrooms were receiving a half-day program as usual. Students’ academic achievement was assessed prior to and at the 

Chapter 16 Embedded Approach

The embedded approach is a nested approach and is used when one type of data (QUAN or QUAL) is most critical to the researcher. This approach is used when different questions require different types of data (qualitative and quantitative). The embedded approach is appropriate when one type of data clearly plays a secondary role and would not be meaningful if not embedded within the primary data set. The embedded approach is also useful when the researcher logistically cannot place equal priority on both types of data or simply has little experience with one of the forms of data. Many variants of the embedded approach have been proposed, such as the embedded narrative and ethnographic designs. For many years, clinical psychologists have used a form of the embedded narrative case study design for cases classified in abnormal psychology (see Oltmanns et al., 2014)—that is, a clinician would collect relevant quantitative indices and qualitative data and develop a cohesive narrative account, explaining the clinical features of the individual case. Based on theoretical and logistical considerations, many other design variants of the embedded approach can be meshed with many of the traditional designs presented in this book. These are sometimes referred to as hybrid designs.

Embedded-Experiment Design

The embedded-experiment design allows the researcher to embed qual data within experimental research. If the research is considered quasi-experimental, then the design can be referred to as an embedded quasi-experimental design. The researcher can use any research design that is designated as such (i.e., within- or between-subject approaches). This model can be further designated as one-phase, which allows the researcher to collect the qual data during the intervention, or two-phase, in which the researcher collects qual data before and after the experimental or quasi-experimental phase.

Embedded-Correlational Design

The embedded-correlational design allows the researcher to embed qual data within nonexperimental research (observational approach). The designs can be either predictive or explanatory. QUAN data is the emphasis within this design.

Embedded Case Study Design

The embedded case study design can be applied as a means to explore a phenomenon within its real-world context when the boundaries between phenomena and context are not clearly evident in which multiple data sources and types (QUAL and quan) are used. QUAL data is the emphasis, while the quan data provides a supplementary role to the qualitative findings. An ethnographic or narrative approach is commonly applied to guide the tenets of the case study design.

Figure 16.1 Embedded-Experiment Design (One-Phase)

Note: Any research design designated as a between-subjects or repeated-measures approach can be used for the QUAN phase, and a cross section of qualitative data can be collected for the qual phase.

Example for Figure 16.11

Zydney, J. M. (2008). Cognitive tools for scaffolding students defining an ill-structured problem. Journal of Educational Computing Research, 38(4), 353–385.

Research Questions

· Quantitative and Qualitative: What is the effect of cognitive tools in scaffolding students defining an ill-structured problem, as measured by (a) students’ problem understanding, (b) ability to generate questions, and (c) ability to formulate hypotheses on how to solve the problem?

· Mixed Method: How do the qual results inform the development of the treatment? What additional information is obtained during the trial from the qual data? How do the qual results expand on the QUAN data?

Procedures: During the first session, students were introduced to the project and completed the fluency test. During the second session, students met 

Chapter 17 Explanatory-Sequential Approach

The explanatory-sequential approach is a sequential approach and is used when the researcher is interested in following up the quantitative results with qualitative data. Thus, the qualitative data is used in the subsequent interpretation and clarification of the results from the quantitative data analysis. In many instances, because the QUAN design is the emphasis, a generic qual design is used in explanatory approaches. This two-phase approach is particularly useful for a researcher interested in explaining the findings from the first phase of the study with the qualitative data collected during Phase 2. However, either the qualitative or quantitative data (or both equally) may be the primary focus of the study (see introductory figure). For example, the qualitative phase is often emphasized when using the participant-selection design.

Follow-Up Explanations Design

The follow-up explanations design provides a framework for the researcher to collect qual data in order to expand on the QUAN data and results. Within this design, a researcher analyzes the relevant QUAN results and then uses the qual findings to further explain the initial QUAN results. Thus, the primary emphasis is on the QUAN results.

Participant-Selection Design

The participant-selection design involves a two-phase process: First, the participant selection (Phase 1) is conducted using a quantitative method, followed by a qualitative data collection phase (Phase 2). Participants are selected during the first phase based on parameters set a priori by the researcher as a means of purposeful sampling. Thus, the quan phase is strictly used to generate the sample.

Figure 17.1 Follow-Up Explanation Design

Note: Any research design designated as experimental, quasi-experimental, or nonexperimental research can be used for the initial QUAN phase of this design, and cross sections of qualitative data can be collected for the qual phase.

Example for Figure 17.1

Lee, K. S., Osborne, R. E., Hayes, K. A., & Simoes, R. A. (2008). The effects of pacing on the academic testing performance of college students with ADHD: A mixed methods study. Journal of Educational Computing Research, 39(2), 123–141.

Research Questions

· Quantitative and Qualitative: What is the relationship between computer-paced and student-paced item presentation on the academic test performance in college students diagnosed with attention-deficit/hyperactivity disorder (ADHD)?

· Mixed Method: In what ways do the qual data help to explain the QUAN results?

Procedures: Participants were randomly assigned to one of two treatment conditions. In the computer-paced testing condition, the students were allowed 90 seconds per question and were forced to move on to the next question when the time expired. In the student-paced testing condition, students were allowed an average of 90 seconds per question but were not forced to move on to the next question. Upon completion of either the computer-paced or student-paced test, each participant was individually interviewed face to face by the primary investigator to explore the student’s perception of the testing experience.

This exploratory study used a follow-up explanation with quasi-experimental design (QUAN) to explore and explain the effects of paced-item presentation for college students diagnosed with ADHD. The goal was to analyze two testing conditions and interpret their impact on a small number of participants who participated in the study.

Figure 17.2 Participant-Selection Design

Note: Cross sections of quantitative data can be collected for the initial quan phase, and any approach and design designated under the qualitative method can be used for the QUAL phase.

Chapter 18 Exploratory-Sequential Approach

The exploratory-sequential approach is a sequential approach and is used when the researcher is interested in following up qualitative findings with quantitative analysis. This two-phase approach is particularly useful for a researcher interested in developing a new instrument, taxonomy, or treatment protocol (Creswell & Plano Clark, 2011). The researcher uses the qualitative (exploratory) findings from the first phase to help develop the instrument or treatment and then tests this product during the second phase (quantitative). In general, when variables are unknown, this approach is useful to identify important variables (Phase 1) for subsequent quantitative analysis (Phase 2). It is also a useful approach for revising existing instruments and treatment protocols, as well as for developing and testing a theory. Although the QUAL phase is usually the primary focus, either the qualitative or quantitative phase (or both equally) may be the primary emphasis of the study (see introductory figure).

Instrument-Development Design

The instrument-development design is often QUAN emphasized and provides a framework for the researcher to first develop and then test (psychometrically) an instrument on a specific population. With this design, the researcher uses the qualitative results to help construct the instrument and validates the instrument during the subsequent quantitative phase. Either the qualitative or quantitative data (or both equally) may be the primary emphasis of the study.

Theory-Development Design

The theory-development (and taxonomy-development) design is often QUAL emphasized. The researcher uses the qualitative data collected during the first phase to identify, develop, and construct a classification system or theory. The taxonomy or theory is subsequently analyzed quantitatively during Phase 2. Oftentimes, researchers will use the qualitative findings to develop their research questions, which guide the quantitative phase of the study. Either the qualitative or quantitative data (or both equally) may be the primary emphasis of the study.

Treatment-Development Design

The treatment-development design is both QUAL and QUAN emphasized and provides a framework for the researcher to develop and then test a treatment protocol or approach with a specific population. With this design, the researcher uses the qualitative results to help construct the treatment protocol and then tests the efficacy of the treatment during the subsequent quantitative phase. Either the qualitative or quantitative data (or both equally) may be the primary emphasis of the study.

Figure 18.1 Instrument-Development Design

Note: Cross sections of qualitative data can be collected for the qual phase, and an explanatory design within the observational approach is typically used for the QUAN phase of this design.

Example for Figure 18.1

Zolotor, A. J., Runyan, D. K., Dunne, M. P., Jain, D., Petrus, H. R., Ramirez, C., . . . Isaeva, O. (2009). ISPCAN Child Abuse Screening Tool Children’s Version (ICAST-C): Instrument development and multi-national pilot testing. Child Abuse & Neglect, 33(11), 833–841.

Research Aims and Question

· Phase 1: Develop a child victimization survey.

· Phase 2: Examine the performance of the instrument through a set of international pilot studies.

· Mixed Method: What items and scales represent the qual findings?

Procedures: The researchers developed the initial draft of the instrument after receiving input from scientists and practitioners representing 40 countries. The original instrument contained 82 screener questions regarding the potentially victimizing experiences at home and school or work. Volunteers from the larger group of scientists participating in the Delphi review of the ISPCAN Child Abuse Screen Tool–Parent Version (ICAST-P) and Retrospective Version (ICAST-R) reviewed the Children’s Version (ICAST-C) by e-mail in two rounds, resulting in a final instrument. The ICAST-C was then translated and back-translated into six languages and field tested in four countries 

Chapter 19 Mixed Methods, Case Studies, and Single-Case Approaches

The primary reason for using mixed methods is to maximize the use of blending methods to answer research questions within a study (i.e., converge and confirm results from different methodological techniques). Keep in mind that the use and application of mixed methods in education and the social and behavioral sciences are still relatively new and evolving (see Tashakkori & Teddlie, 2010b). Many of the designs presented are difficult to locate in the literature; that is, authors typically do not indicate the name of the mixed method research design (or use different names) in their published manuscripts. Nonetheless, there is a growing interest and need for the application of mixed methods as a means to reveal complex and relevant scientific inquiries. There are many applications of mixed methods not yet identified in the literature or in textbooks that we propose. Based on our observations in the field, we recommend combining qualitative methodology with the family of A-B designs (i.e., the single-case approach). Developing a structure and framework for mixed method single-case approaches can strengthen the results from N = 1 designs en route to implying causal relations.

The mixed method single-case approach still maintains the key characteristics (as defined by the quantitative methodological tenets), which are (a) continuous assessment (repeated measures), (b) baseline assessment, (c) accounting for stability in performance, and (d) the introduction of varied phases. However, the qualitative (qual) method should serve as a secondary role to the quantitative (QUAN) method (i.e., the emphasis is on the design of the single-case approach). Because the qualitative method is secondary, a sound generic qualitative design should usually suffice for these applications. For example, a cross section of qual data can be collected concurrently, sequentially, or can be nested (embedded) within the design. When applying these designs and staying true to the tenets of mixed methodology, it is critical to discuss how the qual findings add to, explain, and expand on the QUAN results.

Mixed Method A-B-A Designs

Although we present diagrams of the A-B-A mixed method design, any version of the A-B family of designs can be used (e.g., A-B-A-B, A-B-C, multiple baseline, changing criterion, etc.). Diagram 19.1 is the A-B-A concurrent design. The qual data is collected concurrently (simultaneously) throughout the process of the design. Next, Diagram 19.2 illustrates the A-B-A sequential design. Within this design, qual data is collected sequentially throughout the various phases of the treatment and baseline applications. In addition to collecting qual data between each session, the qual data can also be collected prior to and after the baseline and follow-up sessions. Last, Diagram 19.3 is an A-B-A nested design. This design allows the researcher to collect qual data prior to and following the application of the entire design. See the diagrams for diagrammatic representations of the mixed methods single-case approaches. The applications of these designs should always be based on theoretical and logistical considerations.

Diagram 19.1 A-B-A Concurrent Design

Note: Multiple forms and types of qual data can be collected during each phase.

Diagram 19.2 A-B-A Sequential Design

Note: A cross section of qual data can be collected at any point between treatment and baseline phases.

Diagram 19.3 A-B-A Nested Design

Note: A cross section of qual data is collected prior to and following the completion of the study.

Sequential Case Study Single-Case Design

As seen in Figure 19.1, we propose the application of combining the case study design and the single-case approach as a means to provide a truly in-depth and rigorous analysis and assessment of a single participant (N = 1). This design would be considered an exploratory approach, and the emphasis would be both on qualitative (QUAL) and quantitative (QUAN) methods sequentially delivered. This design is applicable in a wide array of disciplines, such as education, psychiatry, rehabilitation, and medicine. The general steps would include, for example, using the case study approach to detail and reveal the intricate cognitive and behavioral patterns associated with a child diagnosed with a pervasive developmental disorder. For example, information gathered from the case study can be applied to a form of cognitive behavioral therapy and the effects assessed through the use of an A-B-A design. As with all mixed methods studies, the results from the case study and A-B-A design should be analyzed and discussed individually and collectively.

Figure 19.1 Sequential Case Study Single-Case Design

Note: Any version of the case study (see Appendix B) can be used as defined by Yin (2013) or Creswell (2014), and any version of the A-B family of designs can be used.

Chapter 20 Action Research Approaches

The action research approach is a form of research that enables individuals to reveal functional solutions to problems encountered in the context in which they operate or work. The general framework (which can be likened to the scientific method) includes a cyclical approach, starting with the identification of the problem, data collection, analysis, and then a feedback phase. Chevalier and Buckles (2013) discussed action research as a spiral of activity, including the phases of plan, act, observe, and reflect. Stringer (2013) presented the action research model in three phases: look, think, and act. Action research is best suited for educational, health, and community organizations in which the intent is to generalize the findings back to the sample and context where the research takes place, as opposed to extending the findings to the population. We would like to point out that many texts on action research claim that action research is not like traditional scientific inquiry because the findings are not intended to be generalized (i.e., external validity) to populations outside of the research focus. However, the traditional application of the scientific method and experimental research is primarily intended to ensure aspects of internal validity (i.e., the findings can be attributed to the program or treatment).

We have also found in reviewing many action research texts that authors provide the general cyclic framework for action research then discuss a mixed bag of quantitative and qualitative data collection strategies as a means to answer (or solve) the stated problems. Using mixed methods for action research is advisable, but it is vital to include the data collection strategies as part of a greater research-design framework to ensure the results can ultimately be attributed to the program or treatment of interest. Therefore, when applying the action research approach it is advisable to follow the steps of the scientific method and use the sound principles and application of research designs that are known to produce results while ensuring adequate levels of internal validity.

Where action research begins to diverge from the traditional form of experimental research is with the role of the researcher. The researcher is considered more or less a facilitator or consultant to the stakeholders who generally drive the research-question process, although this is clearly not true in all circumstances. Nonetheless, this, in many ways, is more like the program evaluation model, only on a smaller scale. This lends itself to what is known as the participatory action research (PAR) model, in which the research is based on community-driven goals, and all those affected participate and take action. This is often referred to as community-based action research. The action research approach is an attempt to involve the interest of those affected and who are concerned about problems by providing a framework that delivers workable solutions.

We should note that the action research approach is still evolving, and new ideas and frameworks are often introduced and refined to suit specific research contexts. For example, researchers have proposed and demonstrated that the application of collaborative and analytic autoethnography can be combined with the action research approach (Acosta, Goltz, & Goodson, 2015). PAR models have also been combined with the Delphi technique as a means to address specific research objectives (see Fletcher & Marchildon, 2014). Helmer (1967) originally developed the Delphi technique as a systematic approach to garner relevant and appropriate data from those who are considered experts in a respective field in the absence of a standard theoretical framework. This is a complementary approach for the PAR model and should be used more often in relevant contexts. We refer the reader to learn more about the application of the Delphi technique in the health sciences (Keeney, McKenna, & Hasson, 2011) and in education (Manley & Zinser, 2012).

The action research approach is iterative and cyclical and can be represented as the following characteristic cycle:

· Explore

· Deliver the intervention

· Observe

· Reflect and revise

Figure 20.1 The Cyclical Action Research Approach

We refer the reader to the following books to learn more about the action research approach:

· Chevalier, J. M., & Buckles, D. J. (2013). Participatory action research: Theory and methods for engaged inquiry. London, England: Routledge.

· Stringer, E. T. (2013). Action research (4th ed.). Thousand Oaks, CA: Sage.

Embedding Research Designs Within the Action Research Approach

We recommend four basic research designs that can be embedded within the action research approach. Because this approach is indeed cyclical and participatory in nature, it does not preclude it from including relevant aspects of the research design framework to secure the internal validity of the findings. That is, the researcher can confidently attribute the findings to the program or treatment under examination and reduce the probability of reporting spurious results. Keep in mind that the findings are intended to feed back into the environment from which the research takes place, and they are not intended to generalize to the greater population of interest.

We detail the components of a design used within the action research approach in Table 20.1. Dependent variables (O1) should be indicated after 

Chapter 21 Conclusion

Philosophical Tenets

The goal of this guide is to provide practical applications and visual representations of the most common research designs in the fields of education, health and the social and behavioral sciences. We hope that the presentation of each design and the relevant applied examples will encourage researchers to apply many of these theoretically sound designs, which, in our opinion, are underused (particularly mixed methods). This is an applied text, focused on presenting visual aids and real-world examples, to illustrate the key points rather than covering foundational and theoretical issues. However, the importance and relevance of the theory and philosophy related to the various research methods should be noted. That is, there are many theoretical tenets and philosophical principles undergirding the use of a particular method and associated design. More specifically, quantitative researchers focus on testing an a priori theory with an emphasis on deductive reasoning, and they are more in line with postpositivism. Alternatively, qualitatively oriented researchers often use inductive reasoning (or abductive), which is reflective of constructivism. Mixed methods can be viewed more as pragmatic in that this form most efficiently combines both the philosophical approaches of inductive and deductive reasoning. Some researchers would argue that all research should include mixed methods in that the form addresses the complexity of current research problems and counteracts the limitations inherent in using only one type of method. The reader is referred to Creswell (2012) for an in-depth overview of philosophical approaches to quantitative, qualitative, and mixed methods.

Evaluation Approaches

Within this book, we cover some of the most common research designs in quantitative, qualitative, and mixed methods. We have not included evaluation approaches or program evaluation models within the book. Evaluation approaches are primarily used to judge (or evaluate) the merit or worth of an entire program or the product or processes of a program. Although many evaluation approaches have emerged from the traditional framework of social science research, there is a point when evaluation and research diverge in several key areas. More specifically, the primary goal of research (quasi-experimental or experimental and nonexperimental) is to (a) expand, confirm, or develop theories; (b) seek outcomes; (c) generalize the findings (to the subject or population of interest in quantitative methods); and (d) disseminate the results. Alternatively, the primary goal of an evaluation is to draw judgments based on the findings; however, instead of disseminating the findings, the results are fed back to the stakeholders and ultimately integrated into the program of interest. Another key distinction between research and evaluation is that a researcher develops the research objectives or questions, whereas the stakeholders typically develop the aims or objectives for the evaluator to pursue.

Despite these differences, there are many instances where research and evaluation do overlap (i.e., converge). Based on the objectives set forth by the stakeholders and considering the type of program evaluation model to be employed, the appropriate research design should be embedded within the evaluation approach. Specifically, the process of selecting a research design within a program evaluation can take place once the research questions or objectives have been determined by the stakeholder. The most appropriate research design is then incorporated to answer the stated questions. Logistically speaking, it is usually not feasible or relevant to use experimental research within a program evaluation; however, observational, survey, time-series approaches, or regression point-displacement designs (RPD; see Linden, Trochim, & Adams, 2006; Trochim & Campbell, 1996) can serve as strong design alternatives. Most leaders in the field of evaluation agree that mixed methods is the best method to be used by evaluators. Creswell and Plano Clark’s (2011) mixed method multiphase design is an ideal variant to be combined with program evaluation models. The reader is referred to Stufflebeam and Coryn (2014) for an in-depth review of evaluation models and applications. To see an exhaustive list of checklists related to evaluation, including the CIPP (context, input, process, product) model, the reader is referred to D. Stufflebeam’s Evaluation Checklist at http://www.wmich.edu/evaluation/checklists.

Data Analytics

We want to emphasize again that referring to the research designs presented in this reference guide as “common” can be misleading and does not mean that the designs are less powerful or that the results yielded will have less meaning. Practical and statistical significance can be ensured as long as validity is secured throughout the process (i.e., instrumentation, data collection, analysis, and reporting) and an adequate number of data points and participants are included (i.e., statistical power). Issues related to statistical power and determining the number of participants to include in any given study can be reviewed in Kraemer and Blasey (2015) and a freeware program called G*Power (Faul, Erdfelder, Lang, & Buchner, 2007). The statistical or data-analytic techniques are driven by (a) the research questions or hypotheses and (b) the research design of choice. After the presentation of each design, we recommend the most appropriate statistical procedure (parametric) be used, and we offer recommendations of data-analytic software for qualitative methods. Statistical procedures will vary with the application of each design, and there may be instances when nonparametric procedures should be applied. We refer the reader to Green and Salkind (2013) and Leech, Barrett, and Morgan (2014) for sound texts that detail statistical procedures and techniques using statistical software packages (SPSS), as well as statistical applications using Microsoft Excel 07–13 (e.g., Pace, 2011). We also refer the reader to Bazeley and Jackson (2013) for techniques related to qualitative data analyses.

Final Remarks

There are many different types of approaches to research (some considered to be more obscure) that are not research or method specific, and they are