Back to Course

Psychology (Optional) Notes & Mind Maps

0% Complete
0/0 Steps
  1. 1. INTRODUCTION

    1.1 Definition of Psychology
  2. 1.2 Historical antecedents of Psychology and trends in the 21st century
  3. 1.3 Psychology and scientific methods
  4. 1.4 Psychology in relation to other social sciences and natural sciences
  5. 1.5 Application of Psychology to societal problems
  6. 2. METHODS OF PSYCHOLOGY
    2.1 Types of research: Descriptive, evaluative, diagnostic, and prognostic
  7. 2.2 Methods of Research: Survey, observation, case-study, and experiments
  8. 2.3 Experimental, Non-Experimental and Quasi-Experimental Designs
  9. 2.4 Focused group discussions
  10. 2.5 Brainstorming
  11. 2.6 Grounded theory approach
  12. 3. RESEARCH METHODS
    3.1 Major Steps in Psychological research
    6 Submodules
  13. 3.2 Fundamental versus applied research
  14. 3.3 Methods of Data Collection
    3 Submodules
  15. 3.4 Research designs (ex-post facto and experimental)
  16. 3.5 Application of Statistical Technique
    5 Submodules
  17. 3.6 Item Response Theory
  18. 4. DEVELOPMENT OF HUMAN BEHAVIOUR
    4.1 Growth and Development, Principles of Development
  19. 4.2 Role of genetic and environmental factors in determining human behavior
  20. 4.3 Influence of cultural factors in socialization
  21. 4.4 Life span development (Characteristics, development tasks, promoting psychological well-being across major stages of the life span)
  22. 5. SENSATION, ATTENTION, AND PERCEPTION
    5.1 Sensation
    2 Submodules
  23. 5.2 Attention: factors influencing attention
    1 Submodule
  24. 5.3 Perception
    11 Submodules
  25. 6. LEARNING
    6.1 Concept and theories of learning (Behaviourists, Gestaltalist and Information processing models)
  26. 6.2 The Processes of extinction, discrimination, and generalization
  27. 6.3 Programmed learning
  28. 6.4 Probability Learning
  29. 6.5 Self-Instructional Learning
  30. 6.6 Types and the schedules of reinforcement
  31. 6.7 Escape, Avoidance and Punishment
  32. 6.8 Modeling
  33. 6.9 Social Learning
  34. 7. MEMORY
    7.1 Encoding and Remembering
  35. 7.2 Short term memory
  36. 7.3 Long term memory
  37. 7.4 Sensory Memory - Iconic, Echoic & Haptic Memory
  38. 7.5 Multistore Model of Memory
  39. 7.6 Levels of Processing
  40. 7.7 Organization and Mnemonic techniques to improve memory
  41. 7.8 Theories of forgetting: decay, interference and retrieval failure
  42. 7.9 Metamemory
  43. 8. THINKING AND PROBLEM SOLVING
    8.1 Piaget’s theory of cognitive development
  44. 8.2 Concept formation processes
  45. 8.3 Information Processing
  46. 8.4 Reasoning and problem-solving
  47. 8.5 Facilitating and hindering factors in problem-solving
  48. 8.6 Methods of problem-solving: Creative thinking and fostering creativity
  49. 8.7 Factors influencing decision making and judgment
  50. 8.8 Recent Trends in Thinking and Problem Solving
  51. 9. Motivation and Emotion
    9.1 Psychological and physiological basis of motivation and emotion
  52. 9.2 Measurement of motivation and emotion
  53. 9.3 Effects of motivation and emotion on behavior
  54. 9.4 Extrinsic and intrinsic motivation
  55. 9.5 Factors influencing intrinsic motivation
  56. 9.6 Emotional competence and the related issues
  57. 10. Intelligence and Aptitude
    10.1 Concept of intelligence and aptitude
  58. 10.2 Nature and theories of intelligence: Spearman, Thurstone, Guilford Vernon, Sternberg and J.P Das
  59. 10.3 Emotional Intelligence
  60. 10.4 Social Intelligence
  61. 10.5 Measurement of intelligence and aptitudes
  62. 10.6 Concept of IQ
  63. 10.7 Deviation IQ
  64. 10.8 The constancy of IQ
  65. 10.9 Measurement of multiple intelligence
  66. 10.10 Fluid intelligence and crystallized intelligence
  67. 11. Personality
    11.1 Definition and concept of personality
  68. 11.2 Theories of personality (psychoanalytical, sociocultural, interpersonal, developmental, humanistic, behaviouristic, trait and type approaches)
  69. 11.3 Measurement of personality (projective tests, pencil-paper test)
  70. 11.4 The Indian approach to personality
  71. 11.5 Training for personality development
  72. 11.6 Latest approaches like big 5-factor theory
  73. 11.7 The notion of self in different traditions
  74. 12. Attitudes, Values, and Interests
    12.1 Definition of attitudes, values, and interests
  75. 12.2 Components of attitudes
  76. 12.3 Formation and maintenance of attitudes
  77. 12.4 Measurement of attitudes, values, and interests
  78. 12.5 Theories of attitude change
  79. 12.6 Strategies for fostering values
  80. 12.7 Formation of stereotypes and prejudices
  81. 12.8 Changing others behavior
  82. 12.9 Theories of attribution
  83. 12.10 Recent trends in Attitudes, Values and Interests
  84. 13. Language and Communication
    13.1 Properties of Human Language
  85. 13.2 Structure of language and linguistic hierarchy
  86. 13.3 Language acquisition: Predisposition & critical period hypothesis
  87. 13.4 Theories of language development: Skinner and Chomsky
  88. 13.5 Process and types of communication – effective communication training
  89. 14. Issues and Perspectives in Modern Contemporary Psychology
    14.1 Computer application in the psychological laboratory and psychological testing
  90. 14.2 Artificial Intelligence and Psychology
  91. 14.3 Psychocybernetics
  92. 14.4 Study of consciousness-sleep-wake schedules
  93. 14.5 Dreams
  94. 14.6 Stimulus deprivation
  95. 14.7 Meditation
  96. 14.8 Hypnotic/drug-induced states
  97. 14.9 Extrasensory perception
  98. 14.10 Intersensory perception & simulation studies
  99. 15. Psychological Measurement of Individual Differences
    15.1 The nature of individual differences
  100. 15.2 Characteristics and construction of standardized psychological tests
  101. 15.3 Types of psychological tests
  102. 15.4 Use, misuse, limitation & ethical issues of psychological tests
  103. 15.5 Concept of health-ill health
  104. 15.6 Positive health & well being
  105. 15.7 Causal factors in mental disorders (Anxiety disorders, mood disorders, schizophrenia, and delusional disorders; personality disorders, substance abuse disorders)
  106. 15.8 Factors influencing positive health, well being, lifestyle and quality of life
  107. 15.9 Happiness Disposition
  108. 16. Therapeutic Approaches
    16.1 Introduction: Overview of Therapeutic Approaches and Their Importance in Mental Health
  109. 16.2 Psychodynamic therapies
  110. 16.3 Behavior Therapies
  111. 16.4 Client centered therapy
  112. 16.5 Indigenous therapies (Yoga, Meditation)
  113. 16.6 Fostering mental health
  114. 17. Work Psychology and Organisational Behaviour
    17.1 Personnel selection and training
  115. 17.2 Use of psychological tests in the industry
  116. 17.3 Training and human resource development
  117. 17.4 Theories of work motivation – Herzberg, Maslow, Adam Equity theory, Porter and Lawler, Vroom
  118. 17.5 Advertising and marketing
  119. 17.6 Stress and its management
  120. 17.7 Ergonomics
  121. 17.8 Consumer Psychology
  122. 17.9 Managerial effectiveness
  123. 17.10 Transformational leadership
  124. 17.11 Sensitivity training
  125. 17.12 Power and politics in organizations
  126. 18. Application of Psychology to Educational Field
    18.1 Psychological principles underlying effective teaching-learning process
  127. 18.2 Learning Styles
  128. 18.3 Gifted, retarded, learning disabled and their training
  129. 18.4 Training for improving memory and better academic achievement
  130. 18.5 Personality development and value education, Educational, vocational guidance and career counseling
  131. 18.6 Use of psychological tests in educational institutions
  132. 18.7 Effective strategies in guidance programs
  133. 19. Community Psychology
    19.1 Definition and concept of community psychology
  134. 19.2 Use of small groups in social action
  135. 19.3 Arousing community consciousness and action for handling social problems
  136. 19.4 Group decision making and leadership for social change
  137. 19.5 Effective strategies for social change
  138. 20. Rehabilitation Psychology
    20.1 Primary, secondary and tertiary prevention programs-role of psychologists
  139. 20.2 Organising of services for the rehabilitation of physically, mentally and socially challenged persons including old persons
  140. 20.3 Rehabilitation of persons suffering from substance abuse, juvenile delinquency, criminal behavior
  141. 20.4 Rehabilitation of victims of violence
  142. 20.5 Rehabilitation of HIV/AIDS victims
  143. 20.6 The role of social agencies
  144. 21. Application of Psychology to disadvantaged groups
    21.1 The concepts of disadvantaged, deprivation
  145. 21.2 Social, physical, cultural, and economic consequences of disadvantaged and deprived groups
  146. 21.3 Educating and motivating the disadvantaged towards development
  147. 21.4 Relative and prolonged deprivation
  148. 22. Psychological problems of social integration
    22.1 The concept of social integration
  149. 22.2 The problem of caste, class, religion and language conflicts and prejudice
  150. 22.3 Nature and the manifestation of prejudice between the in-group and out-group
  151. 22.4 Causal factors of social conflicts and prejudices
  152. 22.5 Psychological strategies for handling the conflicts and prejudices
  153. 22.6 Measures to achieve social integration
  154. 23. Application of Psychology in Information Technology and Mass Media
    23.1 The present scenario of information technology and the mass media boom and the role of psychologists
  155. 23.2 Selection and training of psychology professionals to work in the field of IT and mass media
  156. 23.3 Distance learning through IT and mass media
  157. 23.4 Entrepreneurship through e-commerce
  158. 23.5 Multilevel marketing
  159. 23.6 Impact of TV and fostering value through IT and mass media
  160. 23.7 Psychological consequences of recent developments in Information Technology
  161. 24. Psychology and Economic development
    24.1 Achievement motivation and economic development
  162. 24.2 Characteristics of entrepreneurial behavior
  163. 24.3 Motivating and training people for entrepreneurship and economic development
  164. 24.4 Consumer rights and consumer awareness
  165. 24.5 Government policies for the promotion of entrepreneurship among youth including women entrepreneurs
  166. 25. Application of psychology to environment and related fields
    25.1 Environmental psychology- effects of noise, pollution, and crowding
  167. 25.2 Population psychology: psychological consequences of population explosion and high population density
  168. 25.3 Motivating for small family norm
  169. 25.4 Impact of rapid scientific and technological growth on degradation of the environment
  170. 26. Application of psychology in other fields
    26.1 [Military Psychology] Devising psychological tests for defense personnel for use in selection, Training, counseling
  171. 26.2 [Military Psychology] Training psychologists to work with defense personnel in promoting positive health
  172. 26.3 [Military Psychology] Human engineering in defense
  173. 26.4 Sports Psychology
  174. 26.5 Media influences on pro and antisocial behavior
  175. 26.6 Psychology of Terrorism
  176. 27. Psychology of Gender
    27.1 Issues of discrimination
  177. 27.2 Management of Diversity
  178. 27.3 Glass ceiling effect
  179. 27.4 Self-fulfilling prophesy
  180. 27.5 Women and Indian society
Module 8 of 180
In Progress

2.3 Experimental, Non-Experimental and Quasi-Experimental Designs

⛶

Experimental Design

  • Definition: Experimental design is a method of investigating cause-and-effect relationships by manipulating one or more independent variables and measuring the effect on a dependent variable.
  • Purpose: The purpose of experimental design is to establish causal relationships between variables in a controlled environment.
  • True Experimental Design:
    • Definition: A true experimental design is a research method in which the researcher randomly assigns participants to different groups or conditions, and manipulates the independent variable to test the effect on the dependent variable.
    • Characteristics: True experimental designs typically have a control group that does not receive the manipulation, and a treatment group that does receive the manipulation. In addition, true experimental designs uses a random assignment process to eliminate selection bias.

    Types of True Experimental Designs:

    • Pre-test post-test control group design: This design involves giving a pre-test to all participants before the manipulation of the independent variable, and giving a post-test to all participants after the manipulation. Participants are randomly assigned to either the control group or treatment group. The control group does not receive the manipulation of the independent variable, while the treatment group does receive the manipulation. The post-test scores of the control group and treatment group are compared to see if there is a difference. This design is useful for determining causality. copyright©iasexpress.net
    • Post-test only control group design: This design involves giving a post-test to all participants after the manipulation of the independent variable. Participants are randomly assigned to either the control group or treatment group. The control group does not receive the manipulation of the independent variable, while the treatment group does receive the manipulation. The post-test scores of the control group and treatment group are compared to see if there is a difference. This design is useful when the pre-test would introduce bias.

    Advantages of True Experimental Design:

    • Establishing cause-and-effect relationships: By manipulating the independent variable and measuring the effect on the dependent variable, true experimental designs can establish causal relationships between variables.
    • Control of extraneous variables: In true experimental designs, the researcher can control extraneous variables that may influence the dependent variable by holding them constant across groups or randomly assigning participants to groups.
    • Studying variables that cannot be manipulated: True experimental designs allow the researcher to manipulate variables that cannot be manipulated in real-world settings.

    Disadvantages of True Experimental Design:

    • Practical and ethical limitations: In some situations, true experimental design may not be practical or ethical. For example, it may not be ethical to manipulate a variable that could cause harm to participants. copyright©iasexpress.net
    • Lack of external validity: True experimental designs are conducted in a controlled environment and may not be generalizable to the real-world.
    • Difficulty in controlling all extraneous variables: Despite efforts to control extraneous variables, it may not be possible to eliminate all sources of extraneous variability.
    • Costs and time-consuming: True experimental designs can be expensive and time-consuming, both for the researcher and for the participants.

Non-Experimental Design:

  • Definition: Non-experimental design is a method of investigating relationships between variables without manipulating the independent variable. Instead, it relies on observations or self-report data and does not involve random assignment to conditions or groups.
  • Characteristics: Non-experimental designs are used to describe a phenomenon or a specific population, and not to establish a causal relationship between variables. The researcher does not control or manipulate any variables and simply looks at the relationship between the two variables.

Types of Non-Experimental Designs:

  • Correlational research: Correlational research is a type of non-experimental research that examines the relationship between two or more variables. Correlational studies can be conducted using a variety of data collection methods such as surveys, observational studies, or experiments that do not manipulate an independent variable. A correlation coefficient is used to measure the strength and direction of the relationship between two variables. copyright©iasexpress.net
  • Survey research: Survey research is a non-experimental design method where participants are asked to answer a series of questions. Surveys can be administered through various methods such as mail, phone, online, or in-person interviews. Surveys are particularly useful when a researcher wants to obtain a large sample size and when the study participants are scattered across a wide geographic area.
  • Case study research: Case study research is a non-experimental design in which an in-depth examination of an individual or group is conducted. Case studies can provide a rich and detailed understanding of a particular case or group of cases and can allow for the examination of complex phenomena and contextual factors that may not be apparent in other research methods.
  • Naturalistic observation: Naturalistic observation is a non-experimental research method where the researcher observes and records the behavior of participants in their natural environment without manipulation of any variables. Naturalistic observation can be useful in understanding the behavior in real-life situations and can be used in a variety of settings such as homes, schools, workplaces, etc.
  • Longitudinal research: Longitudinal research is a non-experimental research design where data is collected from the same individuals at different points in time, over a period of months or years. Longitudinal research allows for the examination of change over time and can provide a more comprehensive understanding of a phenomenon than cross-sectional research. copyright©iasexpress.net
  • Cross-sectional research: Cross-sectional research is a non-experimental research design where data is collected from different individuals at the same point in time. This type of design allows for the comparison of different groups, often based on age or other demographic characteristics and can provide useful information on the prevalence or distribution of a phenomenon in a particular population.

Advantages of Non-Experimental Design:

  • Cost and time-efficient: Non-experimental designs are typically less expensive and time-consuming than experimental designs.
  • Examine variables that cannot be manipulated: Non-experimental designs allow the researcher to examine variables that cannot be manipulated, such as past events or traits.
  • Generating hypotheses: Non-experimental designs can be useful for generating hypotheses for further research.

Disadvantages of Non-Experimental Design:

  • Lack of causality: Non-experimental designs cannot establish a cause-and-effect relationship between variables.
  • Confounding variables: Non-experimental designs may be subject to confounding variables, which can influence the relationship between the independent and dependent variables.
  • Selection bias: Non-experimental designs often rely on a sample of participants that is not randomly selected, which can lead to selection bias. Selection bias occurs when the sample is not representative of the population being studied, and this can lead to inaccurate conclusions.
  • Lack of control: In non-experimental designs, the researcher does not have control over the independent variable and cannot control extraneous variables that may influence the dependent variable. copyright©iasexpress.net
  • Limited generalizability: Non-experimental designs may not be generalizable to other populations or settings due to the lack of random assignment and control over extraneous variables.

Quasi-Experimental Design:

  • Definition: Quasi-experimental design is an experimental design in which the researcher does not have complete control over the assignment of participants to conditions or groups. In other words, it is an experimental design where the researcher do not use random assignment to assign participants to groups, it use other methods that might have some limitations or biases, but still allows the researcher to infer causality between variables.
  • Characteristics: Quasi-experimental designs rely on statistical techniques to control for extraneous variables, and may not have a control group that does not receive the manipulation. They use non-randomized assignment, where the researcher either uses preexisting groups or convenience sampling to form groups.

Types of Quasi-Experimental Designs:

  • Nonequivalent Control Group Design: This type of design involves the selection of a control group that is not equivalent to the treatment group in terms of the variable being manipulated. The researcher makes an effort to match the two groups on relevant characteristics, but it is not a true randomization.
  • Interrupted Time Series Design: This type of design involves repeated measures of the dependent variable over time, both before and after the manipulation of the independent variable. It allows the researcher to control for temporal trends and to infer causality between the independent and dependent variable. copyright©iasexpress.net
  • Nonrandomized Control Group Pretest-Posttest Design: This design uses non-random assignment of participants to groups, and uses pretest-posttest measures to infer causality between variables.

Advantages of Quasi-Experimental Design:

  • Practicality: Quasi-experimental design can be useful when a true experimental design is not practical or ethical.
  • Establishing Causality: Quasi-experimental design can still establish a causal relationship between variables, despite not using random assignment.
  • Study of variables that cannot be manipulated: Quasi-experimental design can be used to study variables that cannot be manipulated in a true experimental design.

Disadvantages of Quasi-Experimental Design:

  • Selection bias: Quasi-experimental design may be subject to selection bias, which can influence the relationship between the independent and dependent variables.
  • Control of extraneous variables: The researcher may not have complete control over extraneous variables, which can lead to inaccurate conclusions.
  • Difficulty in generalizing: Quasi-experimental designs may not be generalizable to other populations or settings due to the lack of random assignment and control over extraneous variables.

Matching and Control in Quasi-Experimental Design:

  • Definition: Matching and control are techniques used in quasi-experimental designs to reduce the threat of selection bias, which occurs when the sample is not representative of the population being studied. They help control for extraneous variables, increasing the internal validity of the study. copyright©iasexpress.net

Different Techniques for Matching and Control in Quasi-Experimental Designs:

  • Propensity Score Matching: Propensity score matching is a statistical technique that helps to balance the treatment and control groups by using a numerical score that predicts the likelihood of being assigned to a certain group. Researchers use statistical models to compute the propensity scores and then match participants in the treatment group to those in the control group with similar scores.
  • Covariate Control: Covariate control is a technique that helps to control for extraneous variables by including them as covariates in the statistical analysis. Researchers can include demographic, background, and pre-existing characteristics as covariates in their analyses, to help control for their effects on the dependent variable.
  • Block Randomization: Block Randomization is a technique where researchers divide participants into blocks based on some pre-existing characteristics such as age, gender, etc., and then randomly assign participants within each block to the treatment and control groups. This technique helps to control for the effects of these characteristics on the dependent variable.
  • Restriction: Restriction is a technique in which researchers limit the population of participants they recruit to study. Researchers can restrict their sample by only recruiting participants who meet certain criteria, and this can help to reduce the effects of extraneous variables on the dependent variable. copyright©iasexpress.net

How Matching and Control are Used to Reduce the Threat of Selection Bias in Quasi-Experimental Designs:

  • By using these techniques to match or control for extraneous variables, researchers can reduce the threat of selection bias in their study. By controlling for extraneous variables, researchers can increase the internal validity of their study and make more accurate causal inferences.
  • By using propensity score matching, for example, researchers can match participants in the treatment group to those in the control group who are similar in terms of certain characteristics. This can help to balance the groups and reduce the threat of selection bias.
  • Using techniques such as block randomization or restriction, researchers can also reduce the threat of selection bias by limiting the population of participants they recruit or by randomly assigning participants within certain defined groups.

Analysis in Experimental and Quasi-Experimental Design:

  • Definition: Analysis in experimental and quasi-experimental designs involves using statistical techniques to examine the relationship between the independent and dependent variables, and to test hypotheses about the causal relationship between the variables.

Different Types of Statistical Analyses Used in Experimental and Quasi-Experimental Designs:

  • T-test: A t-test is a statistical test that is used to determine if there is a significant difference between the means of two groups. It can be used in experimental and quasi-experimental designs to compare the means of a treatment group and a control group. copyright©iasexpress.net
  • Analysis of Variance (ANOVA): ANOVA is a statistical test that is used to determine if there is a significant difference between the means of more than two groups. It can be used in experimental and quasi-experimental designs to compare the means of multiple treatment groups and a control group.
  • Multiple Regression: Multiple regression is a statistical technique that is used to examine the relationship between multiple independent variables and a single dependent variable. It can be used in experimental and quasi-experimental designs to examine the relationship between several independent variables and a single dependent variable, while controlling for the effects of other variables.
  • Propensity Score Analysis: Propensity score analysis is a statistical technique that is used to examine the relationship between an independent variable and a dependent variable, while controlling for the effects of other variables. It is specifically used for the matching in propensity score matching technique in Quasi-experimental designs.
  • Covariate Analysis: Covariate Analysis is a technique that helps to control for extraneous variables by including them as covariates in the statistical analysis. Researchers can include demographic, background, and pre-existing characteristics as covariates in their analyses, to help control for their effects on the dependent variable.

How to Correctly Interpret the Results of These Analyses: copyright©iasexpress.net

  • For t-tests and ANOVA, researchers should examine the p-value, which represents the probability that the results are due to chance. A p-value less than .05 is considered statistically significant, indicating that the results are unlikely to be due to chance.
  • For multiple regression and propensity score analysis, researchers should examine the coefficients of the independent variables, which represent the relationship between the independent variables and the dependent variable. A coefficient with a positive sign indicates a positive relationship, and a coefficient with a negative sign indicates a negative relationship.
  • For all statistical analyses, it is important to examine the effect size, which represents the magnitude of the relationship between the independent and dependent variables. Effect sizes can be reported as Cohen’s d, which indicates the standardized mean difference between the treatment group and the control group, or as r-squared, which indicates the proportion of variance in the dependent variable that is explained by the independent variables.
  • For Quasi-experimental designs, special attention should be given to how the groups were formed, how the researcher controlled for extraneous variables, and how the researcher interpreted the results considering the limitations of the design.

Responses

Your email address will not be published. Required fields are marked *

X
Home Courses Plans Account