Data collection

Mastering Methods, Instruments, and Ethical Practices for Effective Data Gathering in Real-World Contexts

CAPS Grade 10 Mathematical Literacy

Good answers start with good data. Learners need to know how data is collected, how samples are chosen, and why unfair or unclear questions can spoil the results.

Data Collection Overview

In Grade 10 Mathematical Literacy, learners must be able to collect information in a fair and sensible way. That means choosing a method that fits the question, using clear questions, and making sure the data collected will actually help when it is time to organise, draw, and interpret results.

Data Collection Components

Surveys Questionnaires Observations Experiments Existing Sources Sampling Techniques Ethical Considerations Data Instruments

Data Collection Framework

Data Collection Decision Model

Method Selection

Appropriate Method = (Research Question + Population + Resources + Ethics)

This framework reminds learners to think before they collect data. Ask what you need to find out, who you need information from, what time or money is available, and whether the method is fair and respectful.

Selection Criteria

Research Question
What information needs to be collected?
Population
Who/What is being studied? Accessibility?
Resources
Time, budget, personnel available
Ethical Factors
Consent, privacy, potential harm

Question Design Principles

Survey & Questionnaire Design

Effective Question = Clear + Unbiased + Relevant + Appropriate Format

A good question is easy to understand and does not push people toward one answer. If the question is confusing or biased, the data will be weak from the start.

Interactive Method Selection Tool

Recommended Data Collection Methods:
Primary Method: Survey
Secondary Method: Existing Records
Sampling Approach: Stratified Random

Ethical Decision Simulator

Ethical Analysis:
Key Ethical Principles Violated:
Recommended Actions:

Data Collection Process

1

Define Research Objectives

Clearly identify what information needs to be collected, why it's needed, and what questions the data should answer.

Key Questions: • What do I want to know? • Why is this information important? • How will the data be used? • What decisions will it inform?
2

Select Appropriate Method

Choose data collection method(s) based on research objectives, population characteristics, available resources, and ethical considerations.

Method Options: Surveys: For attitudes, opinions, behaviors Observations: For behaviors, processes, patterns Experiments: For cause-effect relationships Existing Data: For historical or large-scale trends
3

Design Data Collection Instruments

Develop tools for gathering data, ensuring they are valid, reliable, and ethical.

Instrument Design: Clear, unambiguous questions Appropriate response formats Logical flow and organization Pilot testing for improvements
4

Determine Sampling Strategy

Select appropriate sampling technique to obtain a representative subset for data collection.

Sampling Techniques: Random: Equal chance selection Stratified: Proportional subgroup representation Convenience: Easy accessibility Systematic: Regular interval selection
5

Implement Ethical Data Collection

Conduct data collection while adhering to ethical principles.

Ethical Requirements: Informed consent from participants Confidentiality and anonymity Right to withdraw without penalty Minimization of potential harm Honest representation of purpose

Primary Data Collection Methods

Surveys

Surveys collect data from a group of people through structured questioning. They are commonly used for gathering information about attitudes, opinions, behaviors, or characteristics.

Best for: Large populations, quantitative data, opinions and attitudes

Observations

Data collection through direct, systematic watching and recording of behaviors, events, or processes. Particularly useful when subjects cannot report accurately or when behavior is the focus.

Best for: Behavioral studies, natural settings, non-verbal data

Experiments

Systematic investigation where variables are manipulated to observe effects on other variables. Used primarily for establishing cause-effect relationships in controlled settings.

Best for: Cause-effect relationships, controlled testing, scientific research

Secondary Data & Sampling Techniques

Existing Sources

Data collected by others for different purposes but relevant to current research. Includes government statistics, organizational records, research studies, media reports, and online databases.

Sampling Techniques

Methods for selecting a representative subset from a larger population when studying the entire population is impractical or impossible.

Data Instruments

Tools and technologies used to gather, record, and store data during the collection process.

Ethical Data Collection Framework

I
Inform

Informed Consent Process

Clearly explain the research purpose, procedures, risks, benefits, and rights to potential participants before obtaining their voluntary agreement to participate.

Key Elements: Purpose explanation, procedures description, time commitment, potential risks/benefits, confidentiality assurance, right to withdraw, contact information, voluntary participation statement.
P
Protect

Privacy & Confidentiality Protection

Safeguard participants' personal information and ensure data cannot be traced back to individuals unless explicitly agreed otherwise.

Protection Methods: Anonymous data collection (no identifiers), confidential handling (limited access), secure data storage, data aggregation for reporting, timely data destruction protocols.
M
Minimize

Risk & Harm Minimization

Identify and reduce potential physical, psychological, social, or economic risks to participants throughout the data collection process.

Risk Assessment: Physical safety considerations, psychological wellbeing (avoid distress), social consequences (stigma, reputation), economic impacts (time, costs), debriefing procedures if distress occurs.
H
Honest

Honest Representation & Reporting

Accurately represent the research purpose and methods, avoid deception unless absolutely necessary, and report findings truthfully without distortion.

Integrity Standards: Truthful purpose description, accurate method reporting, honest data presentation, acknowledgement of limitations, avoidance of selective reporting, disclosure of conflicts of interest.
R
Respect

Respect for Participants & Data

Treat participants with dignity, respect their time and contributions, and handle collected data responsibly for the stated purposes only.

Respectful Practices: Courteous interaction, cultural sensitivity, accommodation of special needs, respectful data use (not beyond consented purposes), acknowledgement of contributions, sharing results with participants when appropriate.