Training Course on Designing and Implementing Education Surveys

Training Course on Designing and Implementing Education Surveys

Introduction

In the era of data-driven decision-making, educational institutions and policymakers increasingly rely on well-designed education surveys to collect accurate, actionable insights. Training Course on Designing and Implementing Education Surveys provides participants with comprehensive knowledge and practical skills to develop, execute, and analyze education-related surveys effectively. By integrating survey design principles, data analytics, and technology tools, the course empowers learners to support evidence-based education planning and policy formulation.

Through hands-on activities and real-world case studies, participants will learn to formulate research questions, choose appropriate methodologies, minimize biases, and interpret findings with clarity. This program emphasizes modern survey technologies, AI-enhanced analytics, and inclusive education research, making it a vital resource for those seeking to lead or support survey initiatives in academic or policy environments.

Course Objectives

Participants will be able to:

1. Understand the fundamentals of educational research and survey methodology.
2. Design surveys aligned with education research goals.
3. Identify appropriate sampling techniques for diverse school populations.
4. Use digital tools and platforms for survey creation and distribution.
5. Implement data quality assurance strategies.
6. Analyze quantitative and qualitative data using modern tools.
7. Minimize bias and improve response rates in surveys.
8. Develop ethical and culturally responsive survey practices.
9. Apply AI and machine learning in education survey analysis.
10. Generate actionable reports from survey data.
11. Communicate findings to stakeholders effectively.
12. Align surveys with policy and program evaluation needs.
13. Build sustainable systems for ongoing data collection and feedback.

Target Audiences

1. Education policymakers
2. School administrators
3. Curriculum developers
4. Educational researchers
5. Data analysts in education
6. NGOs focused on education
7. Government officials in education planning
8. EdTech professionals

Course Duration: 10 days

Course Modules

Module 1: Introduction to Education Surveys

• Importance of survey research in education
• Key terminology and concepts
• Overview of survey lifecycle
• Research design vs. survey design
• Types of education surveys
• Case Study: Global Monitoring Survey by UNESCO

Module 2: Formulating Research Questions

• Identifying education problems
• Writing measurable objectives
• Aligning questions with policy needs
• Incorporating stakeholder input
• Differentiating between qualitative and quantitative aims
• Case Study: National Assessment of Educational Progress (NAEP)

Module 3: Sampling and Participant Selection

• Sampling techniques (random, stratified, cluster)
• Sample size determination
• Addressing accessibility and inclusivity
• Mitigating sampling bias
• Managing consent in school surveys
• Case Study: Kenya Certificate of Primary Education (KCPE) Sampling Analysis

Module 4: Questionnaire Design

• Constructing clear, bias-free questions
• Choosing question formats (MCQ, Likert, open-ended)
• Logical sequencing of items
• Piloting and pretesting
• Language and cultural adaptations
• Case Study: UNICEF Multiple Indicator Cluster Surveys (MICS)

Module 5: Digital Tools for Surveys

• Online vs. offline survey platforms
• Mobile data collection tools (e.g., KoboToolbox)
• Survey automation and scheduling
• Cloud-based data storage
• Data security and encryption
• Case Study: World Bank’s EdTech Survey Platform

Module 6: Data Collection Techniques

• Face-to-face vs. remote surveys
• Enumerator training protocols
• Managing fieldwork logistics
• Ethics in data collection
• Monitoring real-time data
• Case Study: Learning Poverty Surveys during COVID-19

Module 7: Data Cleaning and Preparation

• Detecting outliers and inconsistencies
• Data coding strategies
• Dealing with missing data
• Using Excel and SPSS for cleaning
• Documenting cleaning procedures
• Case Study: African Education Data Initiative (AEDI)

Module 8: Quantitative Data Analysis

• Descriptive statistics overview
• Inferential statistics and regressions
• Visualizing survey results
• Interpreting p-values and confidence intervals
• Using R or STATA for education data
• Case Study: National Education Panel Study (NEPS)

Module 9: Qualitative Data Analysis

• Thematic coding of open-ended responses
• NVivo and MAXQDA tools
• Validating qualitative insights
• Linking qualitative and quantitative data
• Writing qualitative summaries
• Case Study: Voices of Teachers Study

Module 10: Ethics in Education Research

• Informed consent and confidentiality
• Navigating ethical review boards
• Sensitive topics in school surveys
• Child data protection laws (GDPR, COPPA)
• Addressing power imbalances
• Case Study: Save the Children Ethical Protocols

Module 11: Using AI in Survey Analysis

• Natural Language Processing for open responses
• Predictive analytics for dropout risk
• Clustering responses by themes
• Real-time data dashboards
• AI-assisted translation of survey content
• Case Study: AI in Indian Learning Outcome Survey

Module 12: Communicating Results

• Report structure and clarity
• Designing infographics for stakeholders
• Storytelling with data
• Targeting policy briefs and press releases
• Managing media communication
• Case Study: OECD PISA Results Communication Strategy

Module 13: Integrating Surveys into Monitoring & Evaluation (M&E)

• Setting M&E indicators
• Longitudinal vs. cross-sectional surveys
• Feedback loops in programs
• Linking to Sustainable Development Goals (SDGs)
• Budgeting for survey M&E
• Case Study: World Bank Education M&E Framework

Module 14: Scaling Survey Projects

• Creating repeatable survey frameworks
• Cloud systems for large-scale surveys
• Managing partnerships (NGOs, ministries)
• Cross-border data harmonization
• Open data sharing
• Case Study: Global Education Evidence Advisory Panel (GEEAP)

Module 15: Capstone Project & Survey Simulation

• Design your own education survey
• Choose and defend methodology
• Simulate real-time data collection
• Clean and analyze dataset
• Present findings to a review panel
• Case Study: Simulated National Student Feedback Survey

Training Methodology

• Blended learning (online and in-person)
• Instructor-led sessions with real-time Q&A
• Interactive workshops and group assignments
• Hands-on simulations and tool demonstrations
• Assessment through quizzes and project work
• Peer reviews and feedback sessions

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LD account, as indicated in the invoice so as to enable us prepare better for you.