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Related Experiment Video

Updated: Jun 24, 2026

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Published on: June 20, 2020

Tools for measuring academic growth.

G Gage Kingsbury¹, Martha McCall, Carl Hauser

¹Northwest Evaluation Association, Lake Oswego, OR 97035, USA. gage.kingsbury@nwea.org

Journal of Applied Measurement

|March 21, 2009

Summary

This summary is machine-generated.

Measuring academic growth is crucial for student learning. New tools like the Rasch model and computerized adaptive testing enable better growth measurement and modeling for educators.

Related Experiment Videos

Last Updated: Jun 24, 2026

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Published on: June 20, 2020

Area of Science:

Educational Measurement
Psychometrics
Learning Sciences

Background:

Recent policy changes, like incorporating growth into No Child Left Behind, have increased interest in growth measurement.
Developing effective methods for measuring and modeling student academic growth is a significant challenge in education.

Purpose of the Study:

To investigate key aspects of academic growth measurement.
To explore the development of vertical scales and instruments for measuring growth.
To examine techniques for modeling individual student growth and its classroom applications.

Main Methods:

Utilizes the Rasch model for developing vertical scales.
Incorporates computerized adaptive testing for efficient data collection.
Focuses on statistical procedures for individual student growth modeling.

Main Results:

Advanced measurement tools facilitate high-quality data collection for growth assessment.
The study addresses challenges in designing instruments for academic growth.
Techniques for modeling individual student growth are explored.

Conclusions:

The Rasch model and computerized adaptive testing are valuable for measuring and modeling student growth.
Growth information, presented in norm-referenced and standards-referenced formats, can improve educational practices.
Enhanced ability for educators to enrich student learning through better growth insights.