EXECUTIVE CERTIFICATE IN AI-POWERED EDUCATIONAL RESEARCH & DATA SECURITY

Programme Description

The Executive Certificate in AI-Powered Educational Research & Data Security is designed to equip educators, researchers, education administrators and postgraduate students with practical skills to use Artificial Intelligence (AI), digital research tools and data-analysis techniques in educational research while maintaining high standards of research ethics, privacy and data security.

The programme combines educational research methodology, AI-assisted research, educational data management, data analysis, research ethics and data protection. Participants will learn how to use AI responsibly throughout the research process—from identifying a research problem and reviewing literature to analysing data and preparing research reports.

Programme Overview

Item	Details
Institution	Kingdom Royal Institute (KRI)
Programme	Executive Certificate in AI-Powered Educational Research & Data Security
Duration	4 Weeks
Sessions	3 sessions per week
Total Sessions	12
Session Duration	2 hours
Total Contact Hours	24 hours
Mode	Online / Blended
Level	Executive Professional Certificate
Fee	GHC1500.00
Award	KRI Executive Certificate

 

 

Programme Description

The Executive Certificate in AI-Powered Educational Research & Data Security is designed to equip educators, researchers, education administrators and postgraduate students with practical skills to use Artificial Intelligence (AI), digital research tools and data-analysis techniques in educational research while maintaining high standards of research ethics, privacy and data security.

The programme combines educational research methodology, AI-assisted research, educational data management, data analysis, research ethics and data protection. Participants will learn how to use AI responsibly throughout the research process—from identifying a research problem and reviewing literature to analysing data and preparing research reports.

 

 

 

PROGRAMME STRUCTURE

MODULE 1: AI IN EDUCATIONAL RESEARCH

Session 1: Introduction to AI in Educational Research

• Meaning and applications of AI in research
• AI in the educational research process
• Generative AI and research
• Benefits and limitations of AI
• AI tools for researchers

Practical: Identify research tasks that can appropriately be supported by AI.

Session 2: AI-Assisted Literature Review & Information Retrieval

• Searching for scholarly information
• AI-assisted literature discovery
• Search strategies and query formulation
• Summarising and organising literature
• Identifying themes and research gaps
• Verifying AI-generated information

Practical: Develop an AI-assisted literature search strategy.

Session 3: AI for Research Problem & Proposal Development

• Identifying research problems
• Developing research objectives and questions
• Conceptualising research topics
• AI-assisted brainstorming
• Developing research outlines
• Avoiding fabricated references and information

Practical: Develop a preliminary research concept using AI responsibly.

 

 

MODULE 2: EDUCATIONAL DATA COLLECTION & ANALYSIS

Session 4: Educational Data Collection

• Quantitative and qualitative data
• Primary and secondary data
• Questionnaires and interviews
• Digital data collection
• Sampling and respondent selection
• Data quality

Practical: Design a short educational research questionnaire.

Session 5: Educational Data Management & Security

• Data organisation
• Data cleaning
• Data classification
• Secure data storage
• Access control
• Data backup
• Protecting research participants' information

Practical: Develop a basic Educational Research Data Management Plan.

Session 6: AI-Assisted Educational Data Analysis

• Introduction to data analysis
• Descriptive statistics
• Identifying patterns and trends
• AI-assisted data analysis
• Interpreting tables and findings
• Limitations of AI-generated analysis

Practical: Analyse a small educational dataset and interpret the findings.

 

MODULE 3: AI, RESEARCH ETHICS & DATA PRIVACY

Session 7: Research Ethics in the Age of AI

• Principles of research ethics
• Informed consent
• Participant protection
• Academic integrity
• Researcher responsibility
• Ethical use of AI

Practical: Analyse ethical issues in an AI-assisted research scenario.

Session 8: Data Privacy & Protection in Educational Research

• Educational research data and privacy
• Personally identifiable information
• Confidentiality and anonymity
• Data minimisation
• Secure data sharing
• Data breaches and their consequences

Practical: Identify privacy risks in a sample educational research project.

Session 9: Academic Integrity, AI & Research Quality

• Plagiarism and AI-generated content
• Proper attribution
• AI hallucinations
• Fabricated references
• Bias in AI
• Human verification of AI outputs
• Maintaining researcher originality

Practical: Evaluate an AI-generated research passage for accuracy, bias and academic-integrity concerns.

MODULE 4: AI-ASSISTED EDUCATIONAL RESEARCH PROJECT

Session 10: AI-Assisted Research Design

• Developing a research topic
• Research objectives
• Research questions
• Methodology
• Data collection strategy
• Data security plan

Practical: Develop the research design for the final project.

Session 11: AI-Assisted Analysis & Research Reporting

• Organising research findings
• AI-assisted interpretation
• Tables and visualisation
• Discussion of findings
• Conclusions and recommendations
• Referencing and citation verification

Practical: Prepare a short research findings and discussion section.

Session 12: Final Research Project Presentation

Participants will present an:

AI-Powered Educational Research & Data Security Project

The project should demonstrate:

1. Research topic
2. Background/problem
3. Research objectives/questions
4. Literature search strategy
5. Research methodology
6. Data collection approach
7. Data security plan
8. Appropriate use of AI
9. Data analysis
10. Findings
11. Conclusions/recommendations
12. Ethical and privacy considerations

 

Learning Outcomes

By the end of the programme, participants should be able to:

• Apply AI appropriately throughout the educational research process.
• Conduct more effective digital literature searches.
• Develop research questions and research instruments.
• Collect and manage educational research data securely.
• Apply basic data-analysis techniques.
• Use AI to support—but not replace—researcher judgement.
• Identify AI hallucinations, bias and inaccurate information.
• Apply research ethics and data-privacy principles.
• Develop a research data-security plan.
• Produce an AI-assisted educational research project.

 

Target Participants

The programme is particularly suitable for:

• Teachers
• Educational researchers
• M.Ed. and Ph.D. students
• Education administrators
• School Improvement Support Officers
• University lecturers
• Education officers
• Postgraduate students
• Research assistants
• Educational consultants
• School administrators

 

Assessment

Assessment	Weight
Practical activities	15%
Individual assignments	20%
Data analysis exercise	15%
Research ethics & privacy case study	15%
Final research project	25%
Project presentation	10%
Total	100%

 

Final Project

Participants will produce a mini educational research project demonstrating the responsible integration of AI + educational research + data analysis + data security.