Training Course on Data-Driven Decision-Making with EdTech Analytics
Training Course on Data-Driven Decision-Making with EdTech Analytics offers a comprehensive dive into how educational stakeholders can harness analytics to inform decisions, identify trends, and predict outcomes, promoting accountability and performance optimization.
Course Overview
Training Course on Data-Driven Decision-Making with EdTech Analytics
Introduction
In today’s rapidly evolving digital education landscape, data-driven decision-making has emerged as a crucial component for educators, school leaders, and policymakers. Leveraging EdTech analytics allows institutions to improve student learning outcomes, streamline teaching practices, and ensure strategic educational planning. Training Course on Data-Driven Decision-Making with EdTech Analytics offers a comprehensive dive into how educational stakeholders can harness analytics to inform decisions, identify trends, and predict outcomes, promoting accountability and performance optimization.
With the integration of AI-powered dashboards, predictive analytics, and real-time data visualization, EdTech is transforming how we measure success in education. Participants will gain hands-on experience with analytics platforms, explore case studies from leading institutions, and develop actionable insights to drive student engagement, personalized learning, and institutional excellence.
Course Objectives
- Understand the fundamentals of data-driven educational leadership.
- Analyze the role of real-time analytics in classroom performance tracking.
- Implement predictive modeling for student retention and performance.
- Use learning analytics dashboards to monitor and enhance engagement.
- Interpret key EdTech performance indicators for strategic planning.
- Develop data literacy and fluency for effective education data management.
- Evaluate adaptive learning technologies through data insights.
- Explore ethical use and data privacy in EdTech analytics.
- Customize intervention strategies based on learner data patterns.
- Integrate AI in education analytics for automated decision support.
- Apply evidence-based approaches to teaching using student feedback data.
- Design outcome-focused EdTech improvement plans.
- Conduct data storytelling to influence stakeholders in education.
Target Audiences
- School administrators
- Instructional coordinators
- Curriculum developers
- Higher education faculty
- Data analysts in education
- EdTech consultants
- Government education planners
- Professional development trainers
Course Duration: 5 days
Course Modules
Module 1: Foundations of Data-Driven Decision-Making
- Define key terms in educational data analytics
- Explore the evolution of EdTech in modern education
- Identify the benefits of using data in academic settings
- Understand types of education-related data
- Analyze roles and responsibilities in data management
- Case Study: How a public school district improved test scores through data-informed planning
Module 2: Understanding Learning Analytics Tools
- Review popular learning analytics platforms (e.g., Power BI, Tableau)
- Examine key metrics used in student tracking
- Discuss system integration with LMS (Canvas, Moodle)
- Demonstrate dashboard creation and customization
- Identify barriers to effective analytics implementation
- Case Study: A university’s use of dashboards to boost first-year student retention
Module 3: Predictive Analytics and Student Success
- Learn the basics of machine learning in education
- Identify indicators of at-risk students
- Create intervention plans based on data predictions
- Explore early warning systems
- Discuss ethical use of predictive analytics
- Case Study: Predictive modeling at a charter school to reduce dropout rates
Module 4: Enhancing Teaching Through Data Insights
- Analyze student engagement and participation data
- Align teaching methods with data feedback
- Integrate formative assessment analytics
- Use heat maps and trend graphs for improvement
- Promote data-based personalized instruction
- Case Study: Teacher improvement through classroom behavior data analytics
Module 5: Data Privacy, Ethics, and Governance
- Understand FERPA and GDPR compliance in EdTech
- Discuss ethical considerations in student data use
- Identify data governance roles and responsibilities
- Establish data-sharing policies in institutions
- Promote digital citizenship and student awareness
- Case Study: Ethical data practices in a global virtual school network
Module 6: AI and Automation in EdTech Analytics
- Define AI applications in educational data analysis
- Review intelligent tutoring systems
- Automate data collection and analysis workflows
- Explore chatbots and virtual assistants for learning
- Address bias and fairness in AI systems
- Case Study: AI-based adaptive learning in a STEM learning app
Module 7: Building a Culture of Data-Driven Leadership
- Promote leadership buy-in for analytics adoption
- Conduct professional development on data use
- Design institutional KPIs and success metrics
- Monitor progress using institutional scorecards
- Foster cross-departmental data collaboration
- Case Study: Leadership transformation at a K-12 academy through data culture
Module 8: Capstone: Creating an Analytics Implementation Plan
- Conduct institutional needs assessment
- Draft an EdTech data strategy blueprint
- Set goals and define key success metrics
- Develop an evaluation and review process
- Pitch data plans to stakeholders and leaders
- Case Study: End-to-end analytics transformation of a private learning center
Training Methodology
- Interactive Workshops using real-time dashboards and simulations
- Hands-on Labs with tools like Power BI, Google Data Studio, and LMS plugins
- Peer Collaboration Projects to build a data-driven school improvement plan
- Case Study Analysis and application of strategies in real scenarios
- Expert-Led Lectures on emerging trends in EdTech and learning analytics
- Assessment Tasks including quizzes, mini-projects, and presentations
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 LTD account, as indicated in the invoice so as to enable us prepare better for you.