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Experimental Design


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This file describes the types experimental research design with suitable examples.

Published in: Education

Experimental Design

  1. 1. EXPERIMENTAL RESEARCH DESIGN Dr. K. Thiyagu, Assistant Professor, Department of Education, Central University of Kerala, Kasaragod Dr. K. Thiyagu,
  2. 2. What is Research? A systematic means of problem solving (Tuckman 1978) 5 key characteristics: 1. Systematic – research process 2. Logical – induction/deduction 3. Empirical – evidence based 4. Reductive – generalisation 5. Replicable – methodology
  3. 3. Research Design Continuum Research Design Analytical Research Descriptive Research Experimental Research Reviews Historical Philosophical Case Study Survey Cross-Sectional Longitudinal Correlational Pre-designs Quasi-designs True-designs Statistical- designs Meta-Analyses
  4. 4. Analytical Research • Reviews • A critical account of present understanding • A meta-analysis is a quantitative method of review • Historical Research • Accessing both primary (e.g. witnesses) or secondary (e.g. literature) sources to document past events • Philosophical Research • Organising existing evidence into a comprehensive theoretical model
  5. 5. Descriptive Research • Case Study • Accrual of detailed information from an individual • Survey • Cross-sectional: Status of a various groups at a given point in time • Longitudinal: Status of a given group at various points in time • Correlational: Relationships between variables
  6. 6. Experimental Research • Experimental research involves a direct assessment of how one variable influences another • This allows the establishment of causality • All extraneous variables must be held constant while a single variable is manipulated and the effect measured
  7. 7. Independent Variable = this variable is the ‘cause’ / as the predictor variable Dependent Variable = this variable is the ‘effect’ / should only vary in response to the IV / also known as the criterion variable Extraneous Variables = must be controlled to isolate the effect of the IV on the DV Confounding Variables = extraneous variables which have co-varied with Variabl es
  8. 8. Experimental Method • Experimental is most scientifically sophisticated research method. • It is defined as ‘observation under controlled conditions’. • Experimental research design are concerned with examination of the effect of independent variable on the dependent variable, where the independent variable is manipulated through treatment or intervention(s), & the effect of those
  9. 9. EXPERIMENTAL RESEARCH Dependent VariableIndependent Variable Experimental or Treatment Variable Criterion or Outcome Variable Best research methodology to establish cause-and-effect relationships among
  10. 10. True Experimental Design
  11. 11. True Experimental Design True experimental research designs are those where researchers have complete control over the extraneous variables & can predict confidently that the observed effect on the dependable variable is only due to the manipulation of the independent variable.
  12. 12. ESSENTIAL CHARACTERISTICS… A true experimental research design must essentially consist of the following three characteristics: 1. Manipulation 2. Control 3. Randomization
  13. 13. Manipulation: • Manipulation refers to conscious control of the independent variable by the researcher through treatment or intervention(s) to observe its effect on the dependent variable.
  14. 14. Control: • Control is another essential element of true experimental design. • Control refers to use of control group & controlling the effects of extraneous variables on the dependent variable in which researcher is interested. • The subject in the control & experimental groups are similar in number & characteristics, but the subject in the control group receive no experimental treatment or any intervention at all.
  15. 15. Randomization: • Randomization means that every subject has an equal chance of being assigned to experimental or of study subjects on a random basis. Through random assignment of subject under experimental or control group, chances of systemic bias is eliminated. • Randomization is used in true experimental research design to minimize the threat of internal validity of the study & to eliminate the effect of extraneous variables on dependent variables. • Through randomization, on average the characteristics of the subject in experimental & control groups are similar, thus influence of extraneous variables on dependant variable is
  16. 16.  Random assignment of subject may done with simple flip of a coin for each subject; if coin lands on its ‘head’, subjects are assigned to first group & with ‘tail’ subjects are assigned to control group.  Another possible method is to write the names of the subjects on slips of paper & put the slips into a bowl & then draw lots. The first designated numbers of subjects are placed in one group, & rest are assigned under another group.  Thirdly a random table may be used to facilitate the randomization process. In this method, blind-folded subjects choose a number from a table of number horizontally (row) or vertically (columns), till a requisite number is reached for both experimental & control groups. METHODS OF RANDOMIZATION
  17. 17. TYPES OF TRUE EXPERIMENTAL DESIGN True Experiential Design Post-test only Factorial Pretest post-test only Crossove r Solomon 4 groups Randomize d block
  18. 18. Post-test-only Control Design: • Composed of two randomly assigned group, i.e. experimental & control, but neither of which is pretested before the implementation of treatment on the experimental group. • In addition, while treatment is implement on the experimental group only, post-test observation is carried out on both the group to assess the effect of manipulation. • This design can be helpful in situations where it is not possible to pretest the subjects.
  19. 19. Random assignment Exp. group Treatment Post-test Control group Post-test Post-test-only Control Design:
  20. 20. Example Post-test-Only Control Group Design 100 randomly selected teachers R 50 teachers X Dance for Peace Training- Workshop O Posttest: Faculty Self- Awareness Questionnaire R 50 teachers C No training O Posttest: Faculty Self- Awareness Questionnaire
  21. 21. Pretest-post-test-only design • In this research designs, subjects are randomly assigned to either the experimental pr the control group. • The effect of the dependent variable on both the groups is seen before the treatment (pretest). • Later, the treatment is carried out on experimental group only, & after-treatment observation of dependant variable is made on both the groups to examine the effect of the manipulation of independent variable on dependant variable. • For example, such a design could be used for ‘an experimental study to assess the effectiveness of cognitive behavioral therapy interventions for patients with breast
  22. 22. Random assignment Exp. group Treatmen t Post- test Control group Post- test pretest pretest Pretest-post-test-only design
  23. 23. Example Posttest-Only Control Group Design 100 randomly selected teachers R 50 teachers O Pretest: Faculty Self- Awareness Questionnair e X Dance for Peace Training- Workshop O Posttest: Faculty Self- Awareness Questionnaire R 50 teachers O Pretest: Faculty Self- Awareness Questionnair e C No training O Posttest: Faculty Self- Awareness Questionnaire
  24. 24. Solomon four-group design • There are two experimental groups (experimental group 1 & experimental group 2) & two control groups (control group 1 & control group 2). • Initially, the investigator randomly assigns subjects to the four groups. • Out of the four groups, only experimental group 1 & control group1 receives the pretest, followed by the treatment to the experimental group 1 & experimental group 2. • Finally, all the four groups receive post-test, where the effects of the dependant variables of the study are observed & comparison is made of the four groups to assess the effect of independent variable (experimental treatment) on the dependant variable. • The solomon four-group design is believed to be most
  25. 25. Random assignment Exp. Group 1 Control Group 1 Exp. Group 2 Control Group 2 pretest treatment Post-test pretest Post-test treatment Post-test Post-test Solomon four-group design
  26. 26. Example The Solomon Four- Group Design 100 randomly selected teachers R 25 teachers (Exp-1) O Pretest: Faculty Self-Awareness Questionnaire X Dance for Peace Training- Workshop O Posttest: Faculty Self-Awareness Questionnaire R 25 teachers (Con-1) O Pretest: Faculty Self-Awareness Questionnaire C No training O Posttest: Faculty Self-Awareness Questionnaire R 25 teachers (Exp-2) X Dance for Peace Training- Workshop O Posttest: Faculty Self-Awareness Questionnaire R 25 teachers C No training O Posttest:
  27. 27. Factorial design • In factorial design, researcher manipulates two or more independent variables simultaneously to observe their effects on the dependant variables. This design is useful when there are more than two independent variables, called factors to be tested. • This design also facilitates the testing of several hypothesis at a single time. • Typical factorial design incorporates 2X2 or 2X3 factorial, but it can be in any combination. • The first number (α) refers to the independent variables or the type of experimental treatments, & the second number (β) refers to the level or frequency of the treatment.
  28. 28. Factorial design Frequency of mouth care Protocols of the mouth care Chlorhexidine (α1) Saline (α2) 4 hourly (β1) α1….β1 α2….β1 6 hourly (β2) α1….β2 α2….β2 8 hourly (β3) α1….β3 α2….β3
  29. 29. Randomized block design • Control of inherent differences between experimental subjects & differences in experimental conditions is one of the difficult problems faced by researcher in biological sciences. • When there are a large number of experimental comparison groups, the randomized block design is used to bring homogeneity among selected different groups. • This is simple method to reduce the variability among the treatment groups by a more homogeneous combination of the subjects through
  30. 30. Randomized block design Types of antihypertensiv e drugs Blocks Patients with primary hypertension (I) Diabetic patients with hyper tension (II) Renal patients with hypertension (III) A A, I A, II A, III B B, I B, II B, III C C, I C, II C, III • For example, a researcher wants to examine the effects of three different antihypertensive drugs on patients with hypertension. • In this example, to ensure the homogeneity among the subjects under treatment, researcher randomly places the subjects in homogeneous groups (blocks) like patients with primary hypertension, diabetic patients with hypertension, & renal patients with hypertension .
  31. 31. Crossover design • In this design, subjects are exposed to more than one treatment, where subjects are randomly assigned to different orders of treatment. • It is also known as ‘repeat measures design’. • This design is more efficient in establishing the highest possible similarity among subjects exposed to different conditions, where groups compared obviously have equal distribution of characteristics. • Through crossover design is considered as an extremely powerful research design, sometimes it is not effective because when subjects are exposed to two different conditions, their responses of the second condition may be
  32. 32. Crossover design • For example, when we are comparing the effectiveness of the chlorhexidine mouth care protocol on group I & saline mouth care protocol on the subjects of group II. • Later, the treatment is swapped, where group I receives the saline mouth care & group II receives chlorhexidine. In such studies, subjects serve as their own control. Groups Protocols of the mouth care Group I Chlorhexidine (α1) Saline (α2) Group II Saline (α2) Chlorhexidine (α1)
  33. 33. Advantages of True experimental design • Experimental research designs are considered the most powerful designs to establish the causal relationship between independent & dependant variables. • Where the purpose of research is explanation, causal relationship may be established among the variables by experimentation, especially in studies involving physical objects, where the variables are more easily controlled than in human studies. • In this studies, the controlled environment in which the study is conducted can yield a greater degree of purity in observation. • When the experiment is conducted in a laboratory, experimental unit, or other specialized research setting, it is removed from the pressure & problems of real-life situations & the researcher can pursue his or her studies in a more leisurely, careful, & concentrated way.
  34. 34. Quasi – Experimental Research Design
  35. 35. • Quasi-experimental research design involves the manipulation of independent variable to observe to effect on dependant variable, but it lacks at least one of the two characteristics of the true experimental design; randomization or a control group. • In other words, quasi-experimental designs have an element of manipulation but lack at least one of the other two properties that characterize true experiments; randomization or a control group. • Quasi-experimental designs are generally used to establish the causality (effect of independent variable on dependent variable) in situations where researchers are not able to randomly assign the subjects to groups or for various Quasi – Experimental Research Design
  36. 36. Main characteristics… • Manipulation of the independent variables to observe the effects on the dependant variables. • Lack of at least one of the two other essential characteristics of the true experiment, i.e. random assignment of subject or a control group. • Quasi-independent variables are used instead of true independent variables. Where independent variable is not manipulates in complete controller situations.
  37. 37. Types of quasi-experimental design Quasi-experimental design Nonrandomized control group design Time-series design
  38. 38. Nonrandomized control group design • It is also known as the ‘nonequivalent control group design’. • This design is identical to the pretest-posttest control group design, except there is no random assignment of subjects in experimental & control groups. • In this design, experimental & control groups are selected without randomization, & dependent variables are observed in experimental as well as control groups before the intervention. • Later, the experimental group receives treatment & after that posttest observation of dependant variables is carried out for both the groups to assess the effect of treatment on experiment group.
  39. 39. Exp. group Control group Pretes t Pretes t Treatment Post-test Post-test Nonrandomized control group design
  40. 40. Time-series design • This design is useful when the experimenter wants to measure the effects of a treatment over a long period of time. • The experimenter would continue to administer the treatment & measure the effects a number of times during the course of the experiment. • Generally it is a single-subject research, in which the researcher carries out an experiment on an individual or on a small number of individuals, by alternating between administering & then withdrawing the treatment to determine the effectiveness of the intervention.
  41. 41. Exp. group O1 O3O2 O3O2O1Treatment Time-series design
  42. 42. Advantages of quasi-experimental design • Quasi-experimental designs are more frequently used because they are more practical & feasible to conduct research studies in different field, where in the absence of a large sample size, randomization &/ or availability of control groups are not always possible. • This design is more suitable for real-world natural setting than true experimental research designs. • It allows researchers to evaluate the impact of quasi- independent variables under naturally occurring conditions. • It may be able to establishing casual relationship. Wherein some of the hypotheses are practically answered through this design only.
  43. 43. Pre – Experimental Research Design
  44. 44. • This research design is considered very weak, because the researcher has very little control over the experiment Pre – Experimental Research Design One-shot case design One-group pretest-posttest design Pre – Experimental Research Design
  45. 45. One-shot case design • In this research design, a single experimental group is exposed to a treatment & observations are made after the implementation of that treatment. • There is no random assignment of subjects to the experimental group & no control group at all. Exp. group Treatment Post-test Example: suppose you wish to see if a new textbook increases student interest in your course (history, science, statistics, etc.)
  46. 46. One-group pretest-posttest design • It is the simplest type of pre-experimental design, where only the experimental group is selected as the study subjects. • A pretest observation of the dependant variables is made before implementation of the treatment to the selected group, the treatment is administered, & finally a posttest observation of dependant variables is carried out to assess the effect of treatment on the group. • Some researcher also argue this design as sub type of quasi-experimental research design. However in absence of both randomization & control group. • This design ethically can not be placed under the
  47. 47. Exp. group Pretes t Treatment Post-test One-group pretest-posttest design Example: suppose you want to assess the effects of weekly counselling sessions on the attitudes of identified bullies in school
  48. 48. ADVANTAGES OF PRE-EXPERIMENTAL DESIGN: o Very simple & convenient to conduct these studies in natural settings, especially in nursing. oMost suitable design for the beginners in the field of experimental research. DISADVANTAGES OF PRE-EXPERIMENTAL DESIGN: oConsidered a very weak experimental design to establish casual relationship between independent & dependant variables, because it controls no threat to internal validity. It has very little control over the research. oIt has a higher threat to internal validity of research, & may Advantages & Disadvantages of pre-experimental de
  49. 49. Research Validity • Internal Validity – the validity of findings with the research study; the technical soundness of a study, particularly concerned with the control of extraneous influences that might effect the outcome • External Validity – the degree to which the findings can be inferred to the population of interest or to other populations or settings; the generalizability of the results • Both are important in a study but they are frequently at odds with one another in planning and designing a study • Internal validity is considered the basic minimum for experimental research
  50. 50. Threats to Internal Validity • History – events occurring during the experiment that are not part of the treatment • Maturation – biological or psychological processes within participants that may change due to the passing of time, e.g., aging, fatigue, hunger • Testing – the effects of one test upon subsequent administrations of the same test • Instrumentation – changes in testing instruments, raters, or interviewers including lack of agreement within and between observers
  51. 51. Threats to Internal Validity • Statistical regression – the fact that groups selected on the basis of extreme scores are not as extreme on subsequent testing • Selection bias – identification of comparison groups in other than a random manner • Experimental mortality – loss of participants from comparison groups due to nonrandom reasons • Interaction among factors – factors can operate together to influence experimental results
  52. 52. Types of External Validity • Population Validity – • refers to the extent to which the results can be generalized from the experimental sample to a defined population • Ecological Validity – • refers to the extent to which the results of an experiment can be generalized from the set of environmental conditions in the experiment to other environmental conditions
  53. 53. Threats to External Validity • Interaction effects of testing – the fact that the pretest may make the participants more aware of or sensitive to the upcoming treatment • Selection bias – when participants are selected in a manner so they are not representative of any particular population • Reactive effects of experimental setting – the fact that treatments in constrained laboratory settings may not be effective in less constrained, real- world settings • Multiple-treatment interference – when participants receive more than one treatment, the effects of previous treatments may influence
  54. 54. Common Sources of Error • Many possible sources of error can cause the results of a research study to be incorrectly interpreted. The following sources of error are more specific threats to the validity of a study than those described previously • Selected examples: • Hawthorne Effect • Placebo Effect • John Henry Effect • Rating Effect • Experimenter Bias Effect
  55. 55. Hawthorne Effect • A specific type of reactive effect in which merely being a research participant in an investigation may affect behavior • Suggests that, as much as possible, participants should be unaware they are in an experiment and unaware of the hypothesized outcome
  56. 56. Placebo Effect •Participants may believe that the experimental treatment is supposed to change them, so they respond to the treatment with a change in performance
  57. 57. John Henry Effect • A threat to internal validity wherein research participants in the control group try harder just because they are in the control group
  58. 58. Rating Effect •Variety of errors associated with ratings of a participant or group • Halo effect • Overrater error • Underrater error • Central tendency error
  59. 59. Experimenter Bias Effect • The intentional or unintentional influence that an experimenter (researcher) may exert on a study
  60. 60. Dr. K. Thiyagu, Assistant Professor, Department of Education, Central University of Kerala, Kasaragod