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Measuring Learning and Assessment Models
- 1: Limitations of Traditional Assessment Methods
- 2: Introduction to the Growth Assessment Model
- 3: Role of Data and Real-Time Feedback
1 - Limitations of Traditional Assessment Methods
Traditional assessments often fail to align with data-driven, merit-based principles, lacking the ability to accurately track individual growth and proficiency through objective metrics.
Standardized tests that provide only comparative scores without detailing specific skill mastery may not reflect actual learning progress.
Exploring alternative assessment models emphasizes the importance of measuring individual growth based on merit.
2 - Introduction to the Growth Assessment Model
Growth assessment models utilize data analytics to objectively validate progress, focusing on individual trajectories rather than relative comparisons.
A learning platform tracks a student’s progress through skill levels, providing detailed analytics that showcase personal growth over time.
Real-time feedback enhances the ability to track and reinforce merit-based progress.
3 - Role of Data and Real-Time Feedback
Data analytics and immediate feedback support objective assessments of performance, ensuring growth is measurable and verifiable.
Students receive instant feedback on assignments via digital platforms, allowing them to correct errors and understand concepts more thoroughly.
These approaches enhance educational practices, aligning with a merit-based framework.