Technology

Connecting Classroom Assessment with Learning Goals and Instruction Through Theories of Learning

In this report section, we discuss the importance of aligning classroom assessments with learning goals and instructional practices to both shape and evaluate students’ learning opportunities. We describe a plausible solution for improving alignment by integrating theories of learning in the design of classroom assessments. We discuss ways in which the specification of theories of learning as learning progressions can improve alignment between classroom assessments and instruction by focusing on the content, task design, and data generated from classroom assessments.

Author/Presenter

Leanne R. Ketterlin-Geller

Christopher J. Harris

Year
2023
Short Description

In this report section, we discuss the importance of aligning classroom assessments with learning goals and instructional practices to both shape and evaluate students’ learning opportunities.

Can Generative AI and ChatGPT Outperform Humans on Cognitive-Demanding Problem-Solving Tasks in Science?

This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four 2019 NAEP science assessment tasks were coded by content experts using a two-dimensional cognitive load framework, including task cognitive complexity and dimensionality.

Author/Presenter

Xiaoming Zhai

Matthew Nyaaba

Wenchao Ma

Lead Organization(s)
Year
2024
Short Description

This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items.

Can Generative AI and ChatGPT Outperform Humans on Cognitive-Demanding Problem-Solving Tasks in Science?

This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four 2019 NAEP science assessment tasks were coded by content experts using a two-dimensional cognitive load framework, including task cognitive complexity and dimensionality.

Author/Presenter

Xiaoming Zhai

Matthew Nyaaba

Wenchao Ma

Lead Organization(s)
Year
2024
Short Description

This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items.