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Quantitative, qualitive and mixed research designs

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Educational quantitative, qualitive and mixed research designs

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Quantitative, qualitive and mixed research designs

  1. 1. QUANTITATIVE METHOD Aras BOZKURT https://twitter.com/ARASBOZKURT http://about.me/arasbozkurt
  2. 2. QUANTITATIVE METHODDESIGN
  3. 3. QUANTITATIVE METHOD DESIGN • 1. EXPERIMENTAL DESIGN • In an experiment, you test an idea (or practice or procedure) to determine whether it influences an outcome or dependent variable. You first decide on an idea with which to “experiment,” assign individuals to experience it (and have some individuals experience something different), and then determine whether those who experienced the idea (or practice or procedure) performed better on some outcome than those who did not experience it. • When Do You Use an Experiment? • You use an experiment when you want to establish possible cause and effect between your independent and dependent variables. This means that you attempt to control all variables that influence the outcome except for the independent variable. Then, when the independent variable influences the dependent variable, we can say the independent variable “caused” or “probably caused” the dependent variable. Because experiments are controlled, they are the best of the quantitative designs to use to establish probable cause and effect.
  4. 4. QUANTITATIVE METHOD DESIGN • Before you consider how to conduct an experiment, you will find it helpful to understand in more depth several key ideas central to experimental research. These ideas are: • A-Random assignment • B-Control over extraneous variables • C-Manipulation of the treatment conditions • D-Outcome measures • E-Group comparisons • G-Threats to validity
  5. 5. QUANTITATIVE METHOD DESIGN • A-Random Assignment • As an experimental researcher, you will assign individuals to groups. The most rigorous approach is to randomly assign individuals to the treatments. Random assignment is the process of assigning individuals at random to groups or to different groups in an experiment. The random assignment of individuals to groups (or conditions within a group) distinguishes a rigorous, “true” experiment from an adequate, but less- than-rigorous, “quasi-experiment” • You use random assignment so that any bias in the personal characteristics of individuals in the experiment is distributed equally among the groups. By randomization, you provide control for extraneous characteristics of the participants that might infl uence the outcome (e.g., student ability, attention span, motivation). The experimental term for this process is “equating” the groups. Equating the groups means that the researcher randomly assigns individuals to groups and equally distributes any variability of individuals between or among the groups or conditions in the experiment • You should not confuse random assignment with random selection. Both are important in quantitative research, but they serve different purposes. Quantitative researchers randomly select a sample from a population. In this way, the sample is representative of the population and you can generalize results obtained during the study to the population.
  6. 6. QUANTITATIVE METHOD DESIGN • B-Control Over Extraneous Variables • In randomly assigning individuals, we say that we are controlling for extraneous variables that might influence the relationship between the new practice. Extraneous factors are any influences in the selection of participants, the procedures, the statistics, or the design likely to affect the outcome and provide an alternative explanation for our results than what we expected. • Pretests and Posttests: To “equate” the characteristics of the groups, experimental researchers may use a pretest. A pretest provides a measure on some attribute or characteristic that you assess for participants in an experiment before they receive a treatment. After the treatment, you take another reading on the attribute or characteristic. A posttest is a measure on some attribute or characteristic that is assessed for participants in an experiment after a treatment. • Covariates: Because pretests may affect aspects of the experiment, they are often statistically con trolled for by using the procedure of covariance rather than by simply comparing them with posttest scores. Covariates are variables that the researcher controls for using statistics and that relate to the dependent variable but that do not relate to the independent variable
  7. 7. QUANTITATIVE METHOD DESIGN • B-Control Over Extraneous Variables • Matching of Participants: Another procedure used for control in an experiment is to match participants on one or more personal characteristics. Matching is the process of identifying one or more personal characteristics that influence the outcome and assigning individuals with that characteristic equally to the experimental and control groups. Typically, experimental researchers match on one or two of the following characteristics: gender, pretest scores, or individual abilities. • Homogeneous Samples: Another approach used to make the groups comparable is to choose homogeneous samples by selecting people who vary little in their personal characteristics. • Blocking Variables: One such procedure is to “block” for grade level before the experiment begins. A blocking variable is a variable the researcher controls before the experiment starts by dividing (or “blocking”) the participants into subgroups (or categories) and analyzing the impact of each subgroup on the outcome. The variable (e.g., gender) can be blocked into males and females; similarly, high school grade level can be blocked into four categories: freshmen, sophomores, juniors, and seniors
  8. 8. QUANTITATIVE METHOD DESIGN • C-Manipulating Treatment Conditions • Once you select participants, you randomly assign them to either a treatment condition or the experimental group. In experimental treatment, the researcher physically intervenes to alter the conditions experienced by the experimental unit • Treatment Variables • In experiments, you need to focus on the independent variables. These variables influence or affect the dependent variables in a quantitative study. The two major types of independent variables were treatment and measured variables. In experiments, treatment variables are independent variables that the researcher manipulates to determine their effect on the outcome, or dependent variable. Treatment variables are categorical variables measured using categorical scales. For example, treatment independent variables used in educational experiments might be: – Type of instruction (small group, large group) – Type of reading group (phonics readers, whole-language readers)
  9. 9. QUANTITATIVE METHOD DESIGN • C-Manipulating Treatment Conditions • Conditions • In both of these examples, we have two categories within each treatment variable. In experiments, treatment variables need to have two or more categories, or levels. In an experiment, levels are categories of a treatment variable • Intervening in the Treatment Conditions • In an experiment, the researcher physically intervenes (or manipulates with interventions) in one or more condition so that individuals experience something different in the experimental conditions than in the control conditions.
  10. 10. QUANTITATIVE METHOD DESIGN • D-Outcome Measures • In experiments, the outcome (or response, criterion, or posttest) is the dependent variable that is the presumed effect of the treatment variable. It is also the effect predicted in a hypothesis in the cause-and-effect equation • E-Group Comparisons • A group comparison is the process of a researcher obtaining scores for individuals or groups on the dependent variable and comparing the means and variance both within the group and between the groups.
  11. 11. QUANTITATIVE METHOD DESIGN • F-Threats to Validity • Threats to validity refer to specific reasons for why we can be wrong when we make an inference in an experiment because of covariance, causation constructs, or whether the causal relationship holds over variations in persons, setting, treatments, and outcomes ( Shadish, Cook, & Campbell, 2002 ). Four types of validity they discuss are: – Statistical conclusion validity, which refers to the appropriate use of statistics (e.g., violating statistical assumptions, restricted range on a variable, low power) to infer whether the presumed independent and dependent variables covary in the experiment. – Construct validity, which means the validity of inferences about the constructs (or variables) in the study. – Internal validity, which relates to the validity of inferences drawn about the cause and effect relationship between the independent and dependent variables. – External validity, which refers to the validity of the cause-and-effect relationship being generalizable to other persons, settings, treatment variables, and measures.
  12. 12. QUANTITATIVE METHOD DESIGN • F-Threats to Validity • Threats to internal validity are problems in drawing correct inferences about whether the covariation (i.e., the variation in one variable contributes to the variation in the other variable) between the presumed treatment variable and the outcome reflects a causal relationship (Shadish, Cook, & Campbell, 2002 ). • Threats to external validity are problems that threaten our ability to draw correct inferences from the sample data to other persons, settings, treatment variables, and measures.
  13. 13. QUANTITATIVE METHOD DESIGN • WHAT ARE THE TYPES OF EXPERIMENTAL DESIGNS? • Although all experiments have common characteristics, their use and applications vary depending on the type of design used. The most common designs you will find in educational research are: • Between Group Designs – True (gerçek-tam) experiments (pre- and posttest, posttest only) – Quasi (yarı) experiments (pre- and posttest, posttest only) – Factorial (faktöriyel) designs • Within Group or Individual Designs – Time series (zaman serisi) experiments (interrupted, equivalent) – Repeated measures (tekrar ölçümlü) experiments – Single subject (tek denekli) experiments
  14. 14. QUANTITATIVE METHOD DESIGN
  15. 15. QUANTITATIVE METHOD DESIGN • Between-Group Designs • The most frequently used designs in education are those where the researcher compares two or more groups. Illustrations throughout this chapter underscore the importance of these designs.
  16. 16. QUANTITATIVE METHOD DESIGN • True Experiments • True experiments comprise the most rigorous and strong experimental designs because of equating the groups through random assignment. The procedure for conducting major forms of true experiments and quasi- experiments, viewing them in terms of activities from the beginning of the experiment to the end. In true experiments, the researcher randomly assigns participants to different conditions of the experimental variable. Individuals in the experimental group receive the experimental treatment, whereas those in the control group do not. After investigators administer the treatment, they compile average (or mean) scores on a posttest. One variation on this design is to obtain pretest as well as posttest measures or observations. When experimenters collect pretest scores, they may compare net scores (the differences between the pre- and posttests). Alternatively, investigators may relate the pretest scores for the control and experimental groups to see if they are statistically similar, and then compare the two posttest group scores. In many experiments, the pretest is a covariate and is statistically controlled by the researcher.
  17. 17. QUANTITATIVE METHOD DESIGN • Because you randomly assign individuals to the groups, most of the threats to internal validity do not arise. Randomization or equating of the groups minimizes the possibility of history, maturation, selection, and the interactions between selection and other threats. Treatment threats such as diffusion, rivalry, resentful demoralization, and compensatory equalization are all possibilities in a between-group design because two or more groups exist in the design. When true experiments include only a posttest, it reduces the threats of testing, instrumentation, and regression because you do not use a pretest. If a pretest is used, it introduces all of these factors as possible threats to validity. Instrumentation exists as a potential threat in most experiments, but if researchers use the same or similar instrument for the pre- and posttest or enact standard procedures during the study, you hold instrumentation threats to a minimum.
  18. 18. QUANTITATIVE METHOD DESIGN • Quasi-Experiments • In education, many experimental situations occur in which researchers need to use intact groups. This might happen because of the availability of the participants or because the setting prohibits forming artificial groups. Quasi-experiments include assignment, but not random assignment of participants to groups. This is because the experimenter cannot artificially create groups for the experiment. For example, studying a new math program may require using existing fourth-grade classes and designating one as the experimental group and one as the control group. Randomly assigning students to the two groups would disrupt classroom learning. Because educators often use intact groups (schools, colleges, or school districts) in experiments, quasi-experimental designs are frequently used.
  19. 19. QUANTITATIVE METHOD DESIGN • Factorial Designs • In some experimental situations, it is not enough to know the effect of a single treatment on an outcome; several treatments may, in fact, provide a better explanation for the outcome. Factorial designs represent a modification of the between group design in which the researcher studies two or more categorical, independent variables, each examined at two or more levels (Vogt, 2005). The purpose of this design is to study the independent and simultaneous effects of two or more independent treatment variables on an outcome.
  20. 20. QUANTITATIVE METHOD DESIGN • Factorial Designs • Let’s examine more closely the steps in the process of conducting a factorial design. The researcher identifies a research question that includes two independent variables and one dependent variable, such as “Do rates of smoking vary under different combinations of type of instruction and levels of depression?” To answer this question, the experimenter identifies the levels of each factor or independent variable: • Factor 1—types of instruction – Level 1—a health-hazards lecture in civics class – Level 2—a standard lecture in civics class • Factor 2—levels of depression – Level 1—high – Level 2—medium – Level 3—low • Because you measure two levels of instruction and three levels of depression, the design is called a two by three factorial design. It is written as “2 × 3” to indicate the levels involved in each independent variable.
  21. 21. QUANTITATIVE METHOD DESIGN • Using a statistical software program, analysis of variance will produce statistical results for main effects and interaction effects. Main effects are the influence of each independent variable (e.g., type of instruction or extent of depression) on the outcome (e.g., the dependent variable, rate of smoking) in an experiment. Interaction effects exist when the influence on one independent variable depends on (or co-varies with) the other independent variable in an experiment.
  22. 22. QUANTITATIVE METHOD DESIGN • Within-Group or Individual Designs • In any given experiment, the number of participants may be limited and it may not be possible to involve more than one group. In these cases, researchers study a single group using a within-group experimental design. Also, the experimenter might examine single individuals (within- individual design). This type of design assumes several forms: time series, repeated measures, and single-subject designs.
  23. 23. QUANTITATIVE METHOD DESIGN • Time Series • When an experimental researcher has access to only one group and can study them over a period, a time series design is a good experimental approach. A time series design consists of studying one group, over time, with multiple pretest and posttest measures or observations made by the researcher. This design does not require access to large numbers of participants, and it requires only one group for the study. It is ideal for examining change in an entire system (e.g., a school district) where it would be difficult to find a control group or system willing to cooperate. However, this design is labor intensive because the researcher needs to gather multiple measures.
  24. 24. QUANTITATIVE METHOD DESIGN • Time Series • These multiple measures are seen in two important variations of this design. As shown in Table 10.5, the first is the interrupted time series design. This procedure consists of studying one group, obtaining multiple pretest measures for a period of time, administering an intervention (or interrupting the activities), and then measuring outcomes (or posttests) several times. Data analysis in this example consists of examining difference scores between the pretests and posttests or posttest-only scores and using the pretests as covariates. A variation, also seen in Table 10.5, uses an equivalent time series design, in which the investigator alternates a treatment with a posttest measure. The data analysis then consists of comparing posttest measures or plotting them to discern patterns in the data over time.
  25. 25. QUANTITATIVE METHOD DESIGN • Repeated Measures • Another experimental design that has the advantage of employing only a single group is a repeated measures design. In a repeated measures design, all participants in a single group participate in all experimental treatments, with each group becoming its own control. • The researcher compares a group’s performance under one experimental treatment with its performance under another experimental treatment. The experimenter decides on multiple treatments (as in factorial designs) but administers each separately to only one group. After each administration, the researcher obtains a measure or observation.
  26. 26. QUANTITATIVE METHOD DESIGN • Single-Subject Designs • In your experiment, assume that you seek to learn about the behavior of single individuals rather than groups. You also have an opportunity to observe their behavior over time. In these situations, single-subject experimental designs are ideal. Single-subject research (also called N of 1 research, behavior analysis, or within-subjects research) involves the study of single individuals, their observation over a baseline period, and the administration of an intervention. This is followed by another observation after the intervention to determine if the treatment affects the outcome. – An A/B design consists of observing and measuring behavior during a trial period (A), administering an intervention, and observing and measuring the behavior after the intervention – Multiple Baseline Design A frequently used single-subject design is the multiple baseline design, as shown in Figure 10.8. In this design, each participant receives an experimental treatment at a different time (hence, multiple baselines exist) so that treatment diffusion will not occur among participants. Researchers choose this design when the treatment (e.g., skill or strategy being taught) cannot be reversed and doing so would be unethical or injurious to participants. – An alternating treatment design is a single-subject design in which the researcher examines the relative effects of two or more interventions and determines which intervention is the more effective treatment on the outcome.
  27. 27. QUANTITATIVE METHOD DESIGN • 2-SURVEY RESEARCH • Survey research designs are procedures in quantitative research in which investigators administer a survey to a sample or to the entire population of people to describe the attitudes, opinions, behaviors, or characteristics of the population. survey studies describe trends in the data rather than offer rigorous explanations.
  28. 28. QUANTITATIVE METHOD DESIGN • Cross-Sectional Survey Designs: The most popular form of survey design used in education is a cross-sectional survey design. In a cross-sectional survey design, the researcher collects data at one point in time. • Longitudinal Survey Designs: An alternative to using a cross-sectional design is to collect data over time using a longitudinal survey design. A longitudinal survey design involves the survey procedure of collecting data about trends with the same population, changes in a cohort group or subpopulation, or changes in a panel group of the same individuals over time. Thus, in longitudinal designs, the participants may be different or the same people.
  29. 29. QUANTITATIVE METHOD DESIGN
  30. 30. QUANTITATIVE METHOD DESIGN • 3-CORRELATIONAL DESIGN • Correlational designs provide an opportunity for you to predict scores and explain the relationship among variables. In correlational research designs, investigators use the correlation statistical test to describe and measure the degree of association (or relationship) between two or more variables or sets of scores. • An explanatory (relational) research design is a correlational design in which the researcher is interested in the extent to which two variables (or more) co-vary, that is, where changes in one variable are reflected in changes in the other. Explanatory designs consist of a simple association between two variables (e.g., sense of humor and performance in drama) or more than two (e.g., pressure from friends or feelings of isolation that contribute to binge drinking). • The purpose of a prediction research design is to identify variables that will predict an outcome or criterion. In this form of research, the investigator identifies one or more predictor variable and a criterion (or outcome) variable
  31. 31. QUANTITATIVE METHOD DESIGN • 4-META ANALYSIS • In another extension of correlation research, authors integrate the findings of many (primary source) research studies in a meta-analysis by evaluating the results of individual studies and deriving an overall numeric index of the magnitude of results. • meta-analysis comprises statistical methods for contrasting and combining results from different studies in the hope of identifying patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies. Meta-analysis can be thought of as "conducting research about previous research." In its simplest form, meta-analysis is done by identifying a common statistical measure that is shared between studies, such as effect size or p-value, and calculating a weighted average of that common measure. This weighting is usually related to the sample sizes of the individual studies, although it can also include other factors, such as study quality.
  32. 32. QUALITATIVE METHOD Aras BOZKURT
  33. 33. QUALITATIVE METHOD DESIGN • Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern such behavior. The qualitative method investigates the why and how of decision making, not just what, where, when. Hence, smaller but focused samples are more often used than large samples.
  34. 34. QUALITATIVE METHOD DESIGN
  35. 35. QUALITATIVE METHOD DESIGN • 1. Case study • Case study research is a qualitative approach in which the investigator explores a bounded system (a case) or multiple bounded systems (cases) over time, through detailed, in-depth data collection involving multiple sources of information (e.g., observations, interviews, audiovisual material, and documents and reports), and reports a case description and case-based themes.
  36. 36. QUALITATIVE METHOD DESIGN • 1. Case study • The type of analysis of these data can be a holistic analysis of the entire case or an embedded analysis of a specific aspect of the case (Yin, 2003). • One analytic strategy would be to identify issues within each case and then look for common themes that transcend the cases (Yin, 2003).
  37. 37. QUALITATIVE METHOD DESIGN • 1. Case study • Holistic single • Embedded single • Holistic multible • Embedded multible
  38. 38. QUALITATIVE METHOD DESIGN • 2. Narrative Research • "Narrative" might be the term assigned to any text or discourse, or, it might be text used within the context of a mode of inquiry in qualitative research (Chase, 2005), with a specific focus on the stories told by individuals (Polkinghorne, 1995). • Polkinghorne (1995) takes this approach and distinguishes between "analysis of narratives" (p. 12), using paradigm thinking to create descriptions of themes that hold across stories or taxonomies of types of stories, and "narrative analysis," in which researchers collect descriptions of events or happenings and then configure them into a story using a plot line.
  39. 39. QUALITATIVE METHOD DESIGN • 3. Phenomenology • Whereas a narrative study reports the life of a single individual, a phenomenological study describes the meaning for several individuals of their lived experiences of a concept or a phenomenon. Phenomenologists focus on describing what all participants have in common as they experience a phenomenon (e.g., grief is universally experienced). • The basic purpose of phenomenology is to reduce individual experiences with a phenomenon to a description of the universal essence (a "grasp of the very nature of the thing," van Manen, 1990, p. 177).
  40. 40. QUALITATIVE METHOD DESIGN • 3. Phenomenology • Two approaches to phenomenology are highlighted in this discussion: hermeneutic phenomenology (van Marren, 1990) and empirical, transcendental, or psychological phenomenology (Moustakas, 1994). Van Marren (1990) is widely cited in the health literature (Morse & Field, 1995). • An educator, van Marren, has written an instructive book on hermeneutical phenomenology in which he describes research as oriented toward lived experience (phenomenology) and interpreting the "texts" of life (hermeneutics) (van Marren, 1990,p. 4 ). • Moustakas's (1994) transcendental or psychological phenomenology is focused less on the interpretations of the researcher and more on a description of the experiences of participants.
  41. 41. QUALITATIVE METHOD DESIGN • 3. Grounded Theory • Although a phenomenology emphasizes the meaning of an experience for a number of individuals, the intent of a grounded theory study is to move beyond description and to generate or discover a theory, an abstract analytical schema of a process (or action or interaction, Strauss & Corbin, 1998). • Participants in the study would all have experienced the process, and the development of the theory might help explain practice or provide a framework for further research. A key idea is that this theory- development does not come "off the shelf," but rather is generated or "grounded" in data from participants who have experienced the process (Strauss & Corbin, 1998). Thus, grounded theory is a qualitative research design in which the inquirer generates a general explanation (a theory) of a process, action, or interaction shaped by the views of a large number of participants (Strauss & Corbin, 1998).
  42. 42. QUALITATIVE METHOD DESIGN • 3. Grounded Theory • The two popular approaches to grounded theory are the systematic procedures of Strauss and Corbin (1990, 1998) and the constructivist approach of Charmaz (2005, 2006). • In the more systematic, analytic procedures of Strauss and Corbin (1990, 1998), the investigator seeks to systematically develop a theory that explains process, action, or interaction on a topic (e.g., the process of developing a curriculum, the therapeutic benefits of sharing psychological test results with clients). The researcher typically conducts 20 to 30 interviews based on several visits "to the field" to collect interview data to saturate the categories (or find information that continues to add to them until no more can be found). • A second variant of grounded theory is found in the constructivist writing of Charmaz (see Charmaz, 2005, 2006). Instead of embracing the study of a single process or core category as in the Strauss and Corbin (1998) approach, Charmaz advocates for a social constructivist perspective that includes emphasizing diverse local worlds, multiple realities, and the complexities of particular worlds, views, and actions.
  43. 43. QUALITATIVE METHOD DESIGN • 4. Ethnography • Although a grounded theory researcher develops a theory from examining many individuals who share in the same process, action, or interaction, the study participants are not likely to be located in the same place or interacting on so frequent a basis that they develop shared patterns of behavior, beliefs, and language. • An ethnographer is interested in examining these shared patterns, and the unit of analysis is larger than the 20 or so individuals involved in a grounded theory study. An ethnography focuses on an entire cultural group. Granted, sometimes this cultural group may be small (a few teachers, a few social workers), but typically it is large, involving many people who interact over time (teachers in an entire school, a community social work group). Ethnography is a qualitative design in which the researcher describes and interprets the shared and learned patterns of values, behaviors, beliefs, and language of a culture-sharing group (Harris, 1968).
  44. 44. QUALITATIVE METHOD DESIGN • 4. Ethnography • There are many forms of ethnography, such as a confessional ethnography, life history, autoethnography, feminist ethnography, ethnographic novels, and the visual ethnography found in photography and video, and electronic media (Denzin, 1989a; LeCompte, Millroy, & Preissle, 1992; Pink, 2001; VanMaanen, 1988). Two popular forms of ethnography will be emphasized here: the realist ethnography and the critical ethnography
  45. 45. QUALITATIVE METHOD DESIGN • 4. Ethnography • The realist ethnography is a traditional approach used by cultural anthropologists. Characterized by VanMaanen (1988), it reflects a particular stance taken by the researcher toward the individuals being studied. Realist ethnography is an objective account of the siruation, typically written in the thirdperson point of view and reporting objectively on the information learned from participants at a site. In this ethnographic approach, the realist ethnographer narrates the study in a third-person dispassionate voice and reports on what is observed or heard from participants. • For many researchers, ethnography today employs a "critical" approach (Carspecken & Apple, 1992; Madison, 2005; Thomas, 1993) by including in the research an advocacy perspective. This approach is in response to current society, in which the systems of power, prestige, privilege, and authority serve to marginalize individuals who are from different classes, races, and genders. The critical ethnography is a type of ethnographic research in which the authors advocate for the emancipation of groups marginalized in society (Thomas, 1993). Critical researchers typically are politically minded individuals who seek, through their research, to speak out against inequality and domination (Carspecken & Apple, 1992).
  46. 46. QUALITATIVE METHOD DESIGN • 5. Action research • Action research has an applied focus. Similar to mixed methods research, action research uses data collection based on either quantitative or qualitative methods or both. However, it differs in that action research addresses a specific, practical issue and seeks to obtain solutions to a problem. Thus, action research designs are systematic procedures done by teachers (or other individuals in an educational setting) to gather information about, and subsequently improve, the ways their particular educational setting operates, their teaching, and their student learning ( Mills, 2011 ).
  47. 47. QUALITATIVE METHOD DESIGN • 5. Action research (Eylem araştırması) • A review of the major writers in education, however, shows that the following two basic research designs are typically discussed ( Mills, 2011 ): Practical action research and Participatory action research • Practical Action Research: Teachers seek to research problems in their own classrooms so that they can improve their students’ learning and their own professional performance. Teams composed of teachers, students, counselors, and administrators engage in action research to address common issues such as escalating violence in schools. In these situations, educators seek to enhance the practice of education through the systematic study of a local problem. • Participatory Action Research: Participatory action research (PAR) has a long history in social inquiry involving communities, industries and corporations, and other organizations outside of education (e.g., Kemmis & McTaggart, 2005 ). Rather than focus on individual teachers solving immediate classroom problems or schools addressing internal issues, PAR has a social and community orientation and an emphasis on research that contributes to emancipation or change in our society. • The purpose of participatory action research is to improve the quality of people’s organizations, communities, and family lives ( Stringer, 2007 ). Although espousing many of the ideas of teacher and school-based practical action research, it differs by incorporating an emancipatory aim of improving and empowering individuals and organizations
  48. 48. QUALITATIVE METHOD DESIGN • 6. Design based research • Design research: to design/develop an intervention (such as programmes, teaching-learning strategies and materials, products and systems) with the aim to solve a complex educational problem and to advance our knowledge about the characteristics of these interventions and the processes to design and develop them. (p. 12) • Generally, the main purpose that design-based research aims at achieving is to “address complex problems in educational settings”(Sari & Lim, 2012, p. 2) in order to “build a stronger connection between educational research and real-world problems” while supporting design and development of prototypical products to solve complex authentic context- specific problem”
  49. 49. QUALITATIVE METHOD DESIGN • 6. Design based research • In DBR design is a crucial part of the research, whereas in action research the focus is on action and change, which can but need not involve the design of a new learning environment. DBR also more explicitly aims for instructional theories than does action research
  50. 50. QUALITATIVE METHOD DESIGN • 7. Historical • Purpose - describe and examine events of the past to understand the present and anticipate potential future effects • 8. Content analysis • In the social sciences and humanities, content analysis is the analysis of texts of various types including writing, images, recordings and cultural artifacts. Content analysis includes both qualitative and quantitative approaches. Content analysis is used for a variety of purposes including attribution of texts to authors, testing of hypotheses, theory building, and evaluation research.
  51. 51. QUALITATIVE METHOD DESIGN • 9. Meta-synthesis • Generally speaking, a qualitative meta-synthesis is a type of qualitative study that uses as data the findings from other qualitative studies linked by the same or a related topic. The sample for a meta-synthesis, then, is made up of individual qualitative studies selected on the basis of their relevance to a specific research question posed by the synthesist. Meta- synthesis is not an integrated review of qualitative literature on a given topic. Also, it is not secondary data analysis of primary data from the selected studies; rather, it is an analysis of the findings of these studies. That is, meta-synthesis is the synthesist’s interpretation of the interpretations of primary data by the original authors of the constituent studies.
  52. 52. QUALITATIVE METHOD DESIGN
  53. 53. MIXED METHOD Aras BOZKURT
  54. 54. MIXED METHOD DESIGN • A mixed methods research design is a procedure for collecting, analyzing, and “mixing” both quantitative and qualitative methods in a single study or a series of studies to understand a research problem (Creswell & Plano Clark, 2011). The basic assumption is that the uses of both quantitative and qualitative methods, in combination, provide a better understanding of the research problem and question than either method by itself.
  55. 55. MIXED METHOD DESIGN • When one combines quantitative and qualitative data, “we have a very powerful mix”. • Triangulation: Applied to research, it meant that investigators could improve their inquiries by collecting and converging (or integrating) different kinds of data bearing on the same phenomenon. • The three points to the triangle are the (1,2) two sources of the data and the (3) phenomenon. • philosophical worldview: pragmatism.
  56. 56. MIXED METHOD DESIGN • Figure 16.2 illustrates six mixed methods designs, with the first four as the basic designs in use today and the last two as complex designs that are becoming increasingly popular (Creswell & Plano Clark, 2011). • The designs are: • the convergent parallel design • the explanatory sequential design • the exploratory sequential design • the embedded design • the transformative design • the multiphase design
  57. 57. MIXED METHOD DESIGN • 1-The Convergent (concurrent) Parallel Design • The purpose of a convergent (or parallel or concurrent) mixed methods design is to simultaneously collect both quantitative and qualitative data, merge the data, and use the results to understand a research problem.
  58. 58. MIXED METHOD DESIGN • 2-The Explanatory Sequential Design • A mixed methods researcher might collect quantitative and qualitative information sequentially in two phases, with one form of data collection following and informing the other. • An explanatory sequential mixed methods design (also called a two-phase model; Creswell & Plano Clark, 2011) consists of first collecting quantitative data and then collecting qualitative data to help explain or elaborate on the quantitative results.
  59. 59. MIXED METHOD DESIGN • 3-The Exploratory Sequential Design • The mixed methods researcher begins with qualitative data and then collects quantitative information. The purpose of an exploratory sequential mixed methods design involves the procedure of first gathering qualitative data to explore a phenomenon, and then collecting quantitative data to explain relationships found in the qualitative data.
  60. 60. MIXED METHOD DESIGN • 4-The Embedded/nested Design • The purpose of the embedded design is to collect quantitative and qualitative data simultaneously or sequentially, but to have one form of data play a supportive role to the other form of data. The reason for collecting the second form of data is that it augments or supports the primary form of data.
  61. 61. MIXED METHOD DESIGN • 5-The Transformative Design • At a more complex level than the four previous designs, we have the transformative mixed methods design. The intent of the transformative mixed methods design is to use one of the four designs (convergent, explanatory, exploratory, or embedded), but to encase the design within a transformative framework or lens (Creswell & Plano Clark, 2011). • This framework provides an orienting lens for the mixed methods design. It informs the overall purpose of the study, the research questions, the data collection, and the outcome of the study. The intent of the framework is to address a social issue for a marginalized or underrepresented population and engage in research that brings about change. Thus, strength of this design is that it is value-based and ideological ( Greene, 2007). The typical frameworks found in mixed methods are feminist, racial, ethnic, disability, and gay or lesbian perspectives.
  62. 62. MIXED METHOD DESIGN • 5-The Transformative Design
  63. 63. MIXED METHOD DESIGN • 6-Multiphase Design • A multiphase design emerges from multiple projects conducted over time linked together by a common purpose. • the multiphase design is a complex design that builds on the basic convergent, explanatory, exploratory, and embedded designs. Multiphase mixed methods designs occur when researchers or a team of researchers examine a problem or topic through a series of phases or separate studies. The groups of phases or studies are considered to be a mixed methods design and the intent of the design is to address a set of incremental research questions that all advance one programmatic research objective (Creswell & Plano Clark, 2011). • The phases or studies may employ a combination of concurrent or sequential designs and this form of design is popular in large-scale health research and in evaluation research. The strength of this design lies in the use of multiple projects to best understand an overall program objective.
  64. 64. MIXED METHOD DESIGN • 6-Multiphase Design

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