Understanding Data and Systematic Data Collection Methods
Research Design Definitions and Classifications
Research Design: This refers to the overall plan and scheme for conducting a study. A researcher chooses a specific design to guide the investigation, which may include historical, descriptive, or experimental designs.
Descriptive Research Design: The primary purpose of this design is to describe the status of an identified variable, such as events, people, or subjects, as they exist in their natural state.
Descriptive research usually involves making comparisons, contrasts, and correlations.
In carefully planned and orchestrated descriptive researches, cause and effect relationships may be established to some extent.
Experimental Research Design: Also known as longitudinal or repeated-measure studies.
These are referred to as interventions because the researcher does more than just observe the subjects.
This design utilizes the scientific method to establish cause and effect among a group of variables that constitute a study.
Historical Research Design: The purpose of this research is to collect, verify, and synthesize evidence from the past.
This is done to establish facts that either defend or refute a proposed hypothesis.
Fundamental Concepts of Sampling
Sampling: This is the process of obtaining information from a proper subset of a population.
The fundamental purpose of all sampling plans is to describe the characteristics of the population using values obtained from a sample as accurately as possible.
For conclusions based on a small sample to be valid, the sample must imitate the behavior or characteristics of the original population as closely as possible.
Sampling Plan: This is a detailed outline specifying which measurements will be taken, at what times, on which material, in what manner, and by whom to support the purpose of an analysis.
Sampling plans must be designed so that resulting data contains a representative sample of the parameters of interest.
They must allow for all questions stated in the research objectives to be answered.
Steps in Developing a Sampling Plan:
Identify the parameters to be measured, the range of possible values, and the required solution.
Design a sampling scheme that details how and when samples will be taken.
Select sample sizes.
Design data storage formats.
Assign roles and responsibilities.
Slovin’s Formula and Sampling Techniques
Slovin’s Formula: Used to determine the necessary sample size relative to the population and margin of error.
The formula is expressed as:
is the sample size.
is the population size.
is the margin of error.
Probability Sampling: A technique where samples are obtained using an objective chance mechanism, involving randomization.
This requires the use of a sampling frame.
The probabilities of selection are known.
This is the only approach that makes representative sampling plans possible.
Non-Probability Sampling: A technique where there is no way of estimating the probability that each element has of being included in the sample.
There is no assurance that every element in the population has a chance of being included.
Research Instruments: Categories and Characteristics
Instruments: These are the data-gathering devices used in a study. They serve as testing devices for measuring specific phenomena.
Examples include paper-and-pencil tests, questionnaires, interviews, research tools, or observation guidelines.
Categories of Instruments:
Research Completed Instruments: Rating scales, Interview schedules/guides, Tally sheets, Flowcharts, Performance checklists, Time and motion logs, Observation forms.
Subject Completed Instruments: Questionnaires, Self-checklists, Attitude scales, Personality inventories, Achievement test/aptitude tests, Projective devices, Sociometric devices.
Validity: Refers to the extent to which the instrument measures what it intends to measure and performs as designed.
Content Validity: The extent to which a research instrument accurately measures all aspects of a construct.
Construct Validity: The extent to which a tool measures the intended construct.
Criterion Validity: The extent to which a research instrument is related to other instruments measuring the same variables.
Reliability: Relates to the extent to which the instrument is consistent.
The instrument should obtain approximately the same response when applied to respondents in similar situations.
Attributes of Reliability:
Internal Consistency/Homogeneity: The extent to which all items on a scale measure one construct.
Stability or Test-Retest Correlation: The consistency of results when using an instrument with repeated testing.
Equivalence: Consistency among responses of multiple users of an instrument, or among alternate forms of an instrument.
Sources of Data and Collection Methods: Interviews
Primary Sources: Known as primary data or raw data. These are obtained directly from researchers through surveys, observations, and interviews.
Secondary Sources: Known as secondary data. These are obtained from existing sources like reports, books, journals, documents, magazines, and the internet.
Interviews (Data Collection Method):
Structured Interview: The researcher asks a standard set of questions and nothing more. It follows a specific format and line of questioning to ensure every interviewee is presented with the same questions in the same order.
Face-to-Face Interview: The most frequently used method. It can be conducted in the respondent’s home, workplace, halls, or in the street.
Telephone Interview: Less time-consuming and less expensive. The researcher has ready access to anyone with a telephone.
Computer-Assisted Personal Interviewing (CAPI): A form of personal interview where the interviewer uses a laptop or handheld computer to enter information directly into a database instead of a paper questionnaire.
Data Collection Methods: Questionnaires
Five Sections of a Questionnaire:
Respondent’s Identification Data: Includes the respondent’s name, address, date of the interview, and name of the interviewer.
Introduction: The interviewer’s request for help, normally scripted. It includes the credentials of the research company, the purpose of the study, and confidentiality aspects.
Instruction: Directions for the interviewer and respondent on how to move through the questionnaire, including skip logic (which questions to skip based on certain answers).
Information: The main body of the document consisting of questions and response codes.
Classification Data and Information: Establishes important demographic characteristics of the respondent, located either at the front or the end of the questionnaire.
Types of Questionnaires:
Paper-pencil Questionnaire: Can be sent to a large number of people, saving time and money.
Web-based Questionnaire: A growing methodology using internet-based research.
Self-administered Questionnaire: Generally distributed through mail (or email), filled out by the respondent, and returned to the researcher.
Data Collection Methods: Observations, Tests, and Secondary Data
Observations: Gathering data by watching behavior, events, or noting physical characteristics in a natural setting.
Overt Observation: Everyone knows they are being observed.
Covert Observation: No one knows they are being observed; the observer is concealed.
Tests: Assess a subject’s knowledge and their capacity to apply that knowledge to new situations.
Norm-referenced tests: Provide information on how the target performs against a reference group or normative population.
Criterion-referenced tests: Determine if subjects have attained mastery of a specific skill or knowledge area.
Proficiency test: Provides assessment against a level of skill attainment, including standards for performance at varying levels.
Secondary Data Methods: Quantitative data collected by others for a different purpose (e.g., government planning, policy recommendation, or theory generation).
Paper-based sources: Books, journals, periodicals, abstracts, indexes, directories, research reports, conference papers, market reports, annual reports, internal records, newspapers, and magazines.
Electronic sources: CD-ROMs, online databases, internet, videos, and broadcasts.
Practical Guidelines for Reporting Results
Explanation of Data: Explain the collected data, the statistical treatment applied, and results relevant to the research problem.
Documenting Deviations: Describe unexpected events during collection. Explain how actual analysis differed from the planned analysis. Detail how missing data was handled and why it did not undermine validity.
Data Cleaning: Explain the techniques used to ‐clean‐ the data set.
Statistical Tools: Choose a statistical tool, discuss its use, and provide a reference for it. Specify any computer programs or software used.
Assumptions: Describe the assumptions for each procedure and the steps taken to ensure they were not violated.
Descriptive Statistics: Provide descriptive statistics, confidence intervals, and sample sizes for each variable.
Causality: Avoid interfering causality, particularly in non-randomized designs or without further experimentation.
Presentation:
Use tables for exact values.
Use figures for global effects.
Keep figures small and include graphic presentations of confidence intervals.
Inform the reader what to look for in tables and figures.
Writing the Methodology Section
Participants: Describe who they are, how many, and how they were selected. Explain gathering methods, randomization, and preparation.
Example: ‐The researchers randomly selected 100 children from elementary schools of Cebu City.‐
Materials: Describe materials, measures, equipment, or stimuli used (testing instruments, technical equipment, books, etc.).
Example: ‐Two stories from Sullivan et al.’s (1994) second-order false belief attribution tasks were used to assess children’s understanding of second-order beliefs.‐
Design: Describe the research design, variables, levels, and measurements. Specify if the design is within-groups or between-groups. Explain calculations and statistical techniques.
Example: ‐The experiment used a between-subjects design. The independent variables were age and understanding of second-order beliefs.‐
Procedure: Explain what participants do, how data was collected, and the order of steps. Observe ethical standards.
Example: ‐A researcher interviewed children individually in their school in one session that lasted 20 minutes on average. The researcher explained to each child that he or she would be told two short stories and that some questions would be asked after each story. All sessions were videotaped so the data could later be coded.‐
Strategic Tips for Methodology Writing
Tense: Always write the method section in the past tense (use future tense only for a research proposal/design stage).
Detail and Brevity: Provide enough detail for replication but focus on brevity. Avoid irrelevant details.
Formatting and Standards: Use proper APA format.
Collaboration: Review rough drafts with a teacher or research adviser.
Proofreading: Check for typos, grammar, and spelling manually; do not rely solely on spell checkers.
Consistency: Ensure steps mentioned in the method section align with elements in the results and discussion sections.", "title": "Understanding Data and Systematic Data Collection Methods"}