Research Methods in Developmental Psychology & Education

Posted on Nov 27, 2024 in Psychology and Sociology

1. Inductive vs. Deductive Methods

Inductive Method

Inductive inference involves moving from particular observations of phenomena to universal statements that form a theory. It works from the specific to the general, and from data to theory. Inductive scientists believe abstract theories are valid only when derived from empirical data, arguing that preconceived ideas can distort research objectivity.

Stages of an inductive investigation:

1. Data collection through observation and recording of phenomena without specific hypotheses.
2. Data analysis, classifying results to find relationships between phenomena.
3. Evaluation and development of a theoretical model to explain relationships and generalize conclusions.

For example, to study when children start talking, researchers would systematically observe a sample of children and generalize from the observations to predict future experiences.

While useful, the inductive method has limitations, such as difficulty determining relevant data and potential logical inconsistencies from simply gathering data without a clear pattern.

Deductive Method

The deductive method uses theoretical abstractions to guide data collection and establish universal statements to derive specific ones. It works from general to specific, and from theory to data. The process involves constructing a theory, deducing conclusions, formulating a hypothesis, planning data collection, and confirming or rejecting the hypothesis.

2. Hypothetical-Deductive Method & Stages

The inductive and deductive methods are complementary, forming the hypothetical-deductive method. Research can start with a theory, from which a testable hypothesis is derived. The inductive method can uncover facts that form the basis for theoretical statements and hypotheses, which can then be verified deductively.

Stages of the scientific method (can occur in parallel):

1. Identify the research problem by evaluating existing knowledge and inconsistencies.
2. Build an explanatory model, including propositions about relevant variables.
3. Formulate hypotheses based on the model and empirical data.
4. Prepare a data collection plan to test predictions.
5. Collect and analyze data from selected subjects using appropriate statistical techniques.
6. Make decisions about the hypothesis based on statistical analysis.
7. Interpret findings and integrate results into the theory if supported. If not, propose new problems and hypotheses to guide future studies. The theoretical model can be amended based on empirical evidence.

This cyclical process allows for self-correction and refinement of theories.

3. Dependent vs. Independent Variables

In developmental psychology and education, manipulative methods involve manipulating a condition to observe a phenomenon. These methods utilize dependent and independent variables.

The dependent variable is the one being measured and observed. It can be directly observable (external behavior) or indirectly observable (internal states).

The independent variable is systematically manipulated by the experimenter. There are two levels: direct manipulation (researcher controls the variable) and selection (researcher cannot directly manipulate the variable).

4. Objective of Experimental Methodology

Experimental methodology aims to study changes in the dependent variable resulting from variations in the independent variable while controlling extraneous variables.

5. Non-Manipulative Research Strategies

Non-manipulative strategies involve collecting data without changing environmental conditions. These include observational approaches (strategies, phases, self-observation, clinical method), selective methods, and non-experimental designs (longitudinal, cross-sectional, time-interval, sequential).

6. Observational Method

The observational method involves systematically and objectively recording spontaneously emitted behavior in a given context to answer research questions. It focuses on overt, spontaneous behavior in real-life settings.

Observation as a technique: A tool for data collection.

Observation as a method: Aims to describe and explain phenomena.

Observation Strategies

Five criteria classify observation strategies:

1. Degree of structure: Unsystematic (lack of order, no hypotheses) vs. Systematic (structured recording, guided by research aims).
2. Degree of inference: Direct (recording observable behaviors) vs. Indirect (inferring behaviors).
3. Observer role: Non-participant (observer remains outside the situation) vs. Participant (observer interacts with subjects).
4. Setting: Natural (subject’s normal environment) vs. Laboratory (artificial context).
5. Subject’s awareness: Known (subject knows they are observed, potential reactivity) vs. Unknown (ethical concerns about privacy).

Phases of Observational Method

1. Define target behaviors and establish valid and reliable recording categories (frequency, latency, duration, amplitude, accuracy).
2. Establish a recording system (visual or auditory).
3. Define observation intervals and subject sampling.
4. Determine the observation location and control extraneous variables.
5. Recruit and train observers, considering their role and characteristics to minimize influence on subjects.

Self-Observation

Self-observation is useful when direct observation is impossible or behaviors are not readily accessible. It requires a detailed self-recording system with clear, exclusive, and exhaustive categories. Training is crucial and should include:

• Clear definition of target behavior.
• Instructions on recording.
• Simulations of problem situations.
• Initial monitoring to ensure accurate recording.

Potential biases include subject sincerity and reactivity.

Clinical Method

The clinical method involves intensive analysis of individual cases through behavioral observation. Characteristics:

• Inductive, based on observation in natural contexts.
• Diverse data collection techniques (spontaneous responses, interviews, small experiments).
• Development of specific materials.
• Dynamic and flexible procedure, adapting to new data.
• Interpretation of organized data to advance evolutionary theory.

Successful application depends on investigator training, minimizing researcher bias, and considering subject characteristics.

7. Selective Methods: Correlational Studies & Surveys

Selective methods include correlational studies and surveys.

Correlational studies analyze the association between two variables measured in the same subjects using a correlation coefficient. Examples include analyzing the relationship between intelligence and academic achievement, or using causal models and structural equations to analyze networks of relationships.

Surveys involve collecting data from a sample of a population to answer a research question, often using questionnaires.

Survey Methodology Phases

1. Formulate the research problem and objectives.
2. Define content, target population, and data collection procedures.
3. Design the questionnaire with clear and unambiguous questions, paying attention to order and presentation.
4. Prepare a data collection plan, including contact methods and explanations for respondents.
5. Select and train interviewers if necessary.
6. Conduct a pilot study to refine the questionnaire and plan.
7. Select a representative sample.
8. Collect and analyze data.
9. Draw conclusions and write the research report.

8. Non-Experimental Designs

Non-experimental designs include:

Longitudinal Designs

Involve repeated measurements of variables over time in the same group to analyze evolutionary change. Drawbacks include reactivity from repeated measurements, time commitment, and subject attrition. The advantage is the ability to analyze both intraindividual change and interindividual differences.

Cross-Sectional Designs

Analyze behavior in different subject groups simultaneously. Advantage: Efficient data collection. Disadvantage: Limited control over individual differences.

Time-Interval Designs

Examine generation effects by studying subjects of the same age.

Sequential Designs

Consider age, generation, and time of measurement using sequences of longitudinal, cross-sectional, and time-interval procedures. Types include sequential longitudinal, sequential cross-sectional, and sequential time-interval designs, which can be combined for more complex analyses.