Educational Leadership and Management

Training Course on Formative and Summative Assessment Data Analysis

Introduction

In today’s data-driven educational landscape, the ability to effectively analyze formative and summative assessment data is critical for driving student achievement and improving instructional strategies. Training Course on Formative and Summative Assessment Data Analysis equips educators, instructional leaders, and school administrators with advanced skills in educational data analysis, data-driven decision-making, and performance evaluation using evidence-based practices. Participants will explore how to collect, interpret, and apply assessment data to personalize learning, monitor student progress, and align instructional planning with learning outcomes.

With a strong emphasis on real-time analytics, data visualization, and educational technology integration, this course bridges the gap between raw data and actionable insights. By the end of the training, attendees will be able to confidently leverage both formative assessments (ongoing assessments to inform instruction) and summative assessments (end-of-instruction evaluations) to enhance academic performance, support teacher development, and meet institutional goals for continuous improvement and accountability.

Programme Curriculum

Training Course on Formative and Summative Assessment Data Analysis

Introduction

Course Objectives

Understand the differences between formative and summative assessments.
Apply data-driven decision-making in instructional planning.
Analyze student performance data using assessment tools.
Use data dashboards for real-time academic insights.
Create visual reports from assessment data for stakeholders.
Integrate learning analytics with curriculum adjustments.
Develop strategies to close achievement gaps.
Align assessments with learning outcomes and standards.
Utilize AI-powered assessment tools effectively.
Monitor student growth using longitudinal data.
Promote teacher collaboration using shared data insights.
Evaluate instructional effectiveness through data trends.
Establish assessment literacy among educators and leaders.

Target Audience

Classroom Teachers (K-12)
School Principals and Vice Principals
Instructional Coaches
Curriculum Coordinators
District Administrators
Special Education Professionals
Educational Data Analysts
Teacher Education Faculty

Course Duration: 10 days

Course Modules

Module 1: Introduction to Assessment Types

Define formative and summative assessments
Explore purposes of each assessment type
Discuss advantages and limitations
Understand assessment timing and frequency
Identify stakeholders in the assessment process
Case Study: Assessment Misalignment in Middle School Math

Module 2: Principles of Data-Driven Instruction

Define data-driven instruction
Align instruction with assessment results
Set SMART goals using data
Identify key performance indicators (KPIs)
Create feedback loops for continuous improvement
Case Study: Using Data to Transform Instruction in Urban Schools

Module 3: Designing Effective Formative Assessments

Characteristics of effective formative assessments
Types of formative tools (exit tickets, quizzes, journals)
Student self-assessment and peer assessment
Use of digital formative assessment platforms
Linking formative assessment to instructional next steps
Case Study: Real-Time Feedback in a Science Classroom

Module 4: Designing Summative Assessments

Align assessments to learning standards
Balance objective and subjective assessment formats
Create rubrics for performance-based assessments
Address test reliability and validity
Prevent assessment bias and inequity
Case Study: Standardized Test Revisions in High Schools

Module 5: Collecting and Organizing Data

Set up digital assessment platforms
Use spreadsheets and LMS exports
Organize data by standards and benchmarks
Track student growth over time
Conduct error and trend analysis
Case Study: Data Disaggregation in English Language Learning

Module 6: Analyzing Quantitative Data

Understand descriptive statistics (mean, median, mode)
Use frequency distribution and histograms
Apply item analysis to test questions
Analyze subgroup performance
Leverage statistical software (Excel, SPSS)
Case Study: Equity Gap Analysis in Reading Performance

Module 7: Analyzing Qualitative Data

Collect open-ended student feedback
Conduct coding and theme development
Integrate teacher reflections and observational data
Use student work samples as evidence
Combine qualitative with quantitative data
Case Study: Mixed-Methods Analysis in Project-Based Learning

Module 8: Visualizing Data for Impact

Select appropriate graphs and charts
Use dashboards to monitor performance
Share data with students and families
Develop data presentations for stakeholders
Customize reports by subject/grade
Case Study: Interactive Dashboard Use in Elementary School

Module 9: Using Technology in Data Analysis

Use Google Forms and Sheets for quick analysis
Integrate LMS with data platforms
Analyze data with AI tools
Automate feedback and progress reports
Ensure data security and privacy
Case Study: Leveraging EdTech in a District-Wide Rollout

Module 10: Data-Driven Instructional Planning

Identify student learning needs
Group students based on performance
Adjust pacing and differentiation strategies
Plan targeted interventions
Monitor plan implementation effectiveness
Case Study: Response to Intervention (RTI) Based on Data

Module 11: Building Assessment Literacy

Define assessment literacy
Build shared vocabulary among staff
Develop data interpretation skills
Provide professional development on data use
Foster a culture of collaboration
Case Study: PLCs and Data Use in a High-Performing School

Module 12: Promoting Equity Through Data

Identify inequities in assessment outcomes
Support culturally responsive assessment
Adjust practices to ensure fairness
Use data to inform equitable policies
Train educators on equity-centered analysis
Case Study: Closing the Opportunity Gap Using Data

Module 13: Monitoring and Reporting Student Growth

Track growth targets by semester/year
Use growth percentile and SGPs
Report data transparently to families
Compare growth across cohorts
Design student-led data conferences
Case Study: Longitudinal Tracking of Math Growth

Module 14: Enhancing Teacher Effectiveness with Data

Use evaluations linked to student data
Facilitate teacher self-assessment using metrics
Conduct classroom walkthroughs with data focus
Use coaching tied to assessment results
Create teacher data portfolios
Case Study: Improving Instructional Practices via Coaching

Module 15: Creating a Data-Informed School Culture

Involve all staff in data conversations
Hold regular data meetings
Recognize and celebrate data-driven success
Align school improvement plans with data findings
Foster trust in transparent data use
Case Study: Building a Data Culture in a Title I School

Training Methodology

Interactive workshops with hands-on data exercises
Real-world case studies and scenario simulations
Group discussions and collaborative data analysis
Use of digital tools for live data interpretation
Ongoing assessments and reflection activities
Access to post-training resources and templates

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

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 Fineskill Training CenterANCY LD account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Data interpretation assessment strategies improvement planning

Programme Fee

Duration: 10 Days

Method: Online or Physical

Online Price: $2,000

Physical Price: $3,000

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 30 Oct 2026

💻 Online / Virtual session

Online $2,000