Skip to main content

Breadcrumb

Home arrow_forward_ios Information on ... arrow_forward_ios Collab-ITS: Aut ...
Home arrow_forward_ios ... arrow_forward_ios Collab-ITS: Aut ...
Information on ...
Contract Closed

Collab-ITS: Autoscoring Collaborative Online Science Labs for Grades 3–5 that Integrate Math and Writing

NCER
Program: Small Business Innovation Research
Award amount: $250,000
Project director: Mike Sao Pedro
Awardee:
Apprendis
Year: 2023
Award period: 8 months (06/23/2023 - 02/23/2024)
Project type:
Phase I Development
Contract number: 91990023C0031

Purpose

Research demonstrates that many elementary school students are not learning foundational competencies in STEM. Through prior ED/IES SBIR, IES, and projects funded through other government programs, the team developed and evaluated InqITS, an on-line science laboratory that employs Artificial Intelligence for students to conduct virtual experiments and receive feedback to inform learning and instruction in real time. The project team will develop a new component of InqITS, a prototype lab to integrate writing within science experiments to extend how elementary students learn STEM.

Project Activities

In Phase I, the project team will develop prototype labs that automatically score elementary students' science writing through natural language processing scoring algorithms, as well as an educator dashboard with information on student progress. At the end of Phase I, a pilot study will include 5 grade 3 to 5 educators with 25 students per class. The researchers will examine if the prototype functions as intended, if educators are able to use the labs in classrooms with their students, if the system can accommodate for a range of students' written responses across different competencies, and how well students in grades 4 and 5 rate using the prototype to support writing in the context of STEM.

Products and publications

Project website:

https://www.apprendis.com

Related projects

ASSISTment Meets Science Learning (AMSL)

R305A090170

The Development of an Intelligent Pedagogical Agent for Physical Science Inquiry Driven by Educational Data Mining

R305A120778

Inq-Blotter: Revolutionizing How Teachers Identify and Support Students Needing Help During Inquiry

EDIES15C0018

Recognizing How Teachers Identify and Support Students Needing Help During Inquiry

EDIES16C0014

Questions about this project?

To answer additional questions about this project or provide feedback, please contact the program officer.

 

Tags

MathematicsWriting

Share

Icon to link to Facebook social media siteIcon to link to X social media siteIcon to link to LinkedIn social media siteIcon to copy link value

Questions about this project?

To answer additional questions about this project or provide feedback, please contact the program officer.

 

You may also like

Zoomed in IES logo
Research insights

From Evidence to Classroom Practice: The Toolkit t...

February 02, 2026 by Riley Stone
Read More
Rectangle Blue 1 Pattern 1
Thought leadership

What's on the Horizon for the 2026 Nation's Report...

January 21, 2026 by Matthew Soldner
Read More
A teacher kneels on a classroom rug with elementary students seated on the floor, working collaboratively in small groups on writing.
Research insights

Why Modeling Matters in Elementary Writing Instruc...

January 16, 2026 by Laura Dyer
Read More
icon-dot-govicon-https icon-quote