Assessment

ChatGPT for Next Generation Science Learning

This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.

Zhai, X. (2023). ChatGPT for Next Generation Science Learning | XRDS: Crossroads, 29(3), 42-46. https://doi.org/10.1145/3589649

Author/Presenter
Xiaoming Zhai
Lead Organization(s)
Year
2023
Short Description

This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.

Investigating Teachers’ Understanding Through Topic Modeling: A Promising Approach to Studying Teachers’ Knowledge

Examining teachers’ knowledge on a large scale involves addressing substantial measurement and logistical issues; thus, existing teacher knowledge assessments have mainly consisted of selected-response items because of their ease of scoring. Although open-ended responses could capture a more complex understanding of and provide further insights into teachers’ thinking, scoring these responses is expensive and time consuming, which limits their use in large-scale studies.

Author/Presenter

Yasemin Copur-Gencturk

Hye-Jeong Choi

Alan Cohen

Year
2022
Short Description

Examining teachers’ knowledge on a large scale involves addressing substantial measurement and logistical issues; thus, existing teacher knowledge assessments have mainly consisted of selected-response items because of their ease of scoring. Although open-ended responses could capture a more complex understanding of and provide further insights into teachers’ thinking, scoring these responses is expensive and time consuming, which limits their use in large-scale studies. In this study, we investigated whether a novel statistical approach, topic modeling, could be used to score teachers’ open-ended responses and if so, whether these scores would capture nuances of teachers’ understanding.

Examining Elementary Science Teachers' Responses to Assessments Tasks Designed to Measure Their Content Knowledge for Teaching About Matter and its Interactions

Despite the importance of developing elementary science teachers' content knowledge for teaching (CKT), there are limited assessments that have been designed to measure the full breadth of their CKT at scale. Our overall research project addressed this gap by developing an online assessment to measure elementary preservice teachers' CKT about matter and its interactions. This study, which was part of our larger project, reports on findings from one component of the item development process examining the construct validity of 118 different CKT about matter assessment items.

Author/Presenter

Jamie N. Mikeska

Dante Cisterna

Heena Lakhani

Allison K. Bookbinder

David L. Myers

Luronne Vaval

Lead Organization(s)
Year
2022
Short Description

Despite the importance of developing elementary science teachers' content knowledge for teaching (CKT), there are limited assessments that have been designed to measure the full breadth of their CKT at scale. Our overall research project addressed this gap by developing an online assessment to measure elementary preservice teachers' CKT about matter and its interactions. This study, which was part of our larger project, reports on findings from one component of the item development process examining the construct validity of 118 different CKT about matter assessment items.

Flip It: An Exploratory (Versus Explanatory) Sequential Mixed Methods Design Using Delphi and Differential Item Functioning to Evaluate Item Bias

The Delphi method has been adapted to inform item refinements in educational and psychological assessment development. An explanatory sequential mixed methods design using Delphi is a common approach to gain experts' insight into why items might have exhibited differential item functioning (DIF) for a sub-group, indicating potential item bias. Use of Delphi before quantitative field testing to screen for potential sources leading to item bias is lacking in the literature.

Author/Presenter
Kristin L.K. Koskey
Toni A. May
Yiyun “Kate” Fan
Dara Bright
Gregory Stone
Gabriel Matney
Jonathan D. Bostic
Year
2023
Short Description

The Delphi method has been adapted to inform item refinements in educational and psychological assessment development. An explanatory sequential mixed methods design using Delphi is a common approach to gain experts' insight into why items might have exhibited differential item functioning (DIF) for a sub-group, indicating potential item bias. Use of Delphi before quantitative field testing to screen for potential sources leading to item bias is lacking in the literature. An exploratory sequential design is illustrated as an additional approach using a Delphi technique in Phase I and Rasch DIF analyses in Phase II. We introduce the 2 × 2 Concordance Integration Typology as a systematic way to examine agreement and disagreement across the qualitative and quantitative findings using a concordance joint display table.

Flip It: An Exploratory (Versus Explanatory) Sequential Mixed Methods Design Using Delphi and Differential Item Functioning to Evaluate Item Bias

The Delphi method has been adapted to inform item refinements in educational and psychological assessment development. An explanatory sequential mixed methods design using Delphi is a common approach to gain experts' insight into why items might have exhibited differential item functioning (DIF) for a sub-group, indicating potential item bias. Use of Delphi before quantitative field testing to screen for potential sources leading to item bias is lacking in the literature.

Author/Presenter
Kristin L.K. Koskey
Toni A. May
Yiyun “Kate” Fan
Dara Bright
Gregory Stone
Gabriel Matney
Jonathan D. Bostic
Year
2023
Short Description

The Delphi method has been adapted to inform item refinements in educational and psychological assessment development. An explanatory sequential mixed methods design using Delphi is a common approach to gain experts' insight into why items might have exhibited differential item functioning (DIF) for a sub-group, indicating potential item bias. Use of Delphi before quantitative field testing to screen for potential sources leading to item bias is lacking in the literature. An exploratory sequential design is illustrated as an additional approach using a Delphi technique in Phase I and Rasch DIF analyses in Phase II. We introduce the 2 × 2 Concordance Integration Typology as a systematic way to examine agreement and disagreement across the qualitative and quantitative findings using a concordance joint display table.

Examining the Influence of COVID-19 on Elementary Mathematics Standardized Test Scores in a Rural Ohio School District

In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID-19 pandemic offered a multitude of learning modalities (e.g., hybrid, socially distanced face-to-face instruction, virtual environment), it becomes critical to examine how this learning disruption influenced elementary mathematic performance.

Author/Presenter

Dara Bright

Yiyun “Kate” Fan

Chris Fornaro

Kristin L. K. Koskey

Toni A. May

Jonathan D. Bostic

Dolores Swineford

Year
2022
Short Description

In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID-19 pandemic offered a multitude of learning modalities (e.g., hybrid, socially distanced face-to-face instruction, virtual environment), it becomes critical to examine how this learning disruption influenced elementary mathematic performance. This study tested for

differences in mathematics performance on fourth grade standardized tests before and during COVID-19 in a case study of a rural Ohio school district using the Measure of Academic Progress (MAP) mathematics test.

Examining the Influence of COVID-19 on Elementary Mathematics Standardized Test Scores in a Rural Ohio School District

In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID-19 pandemic offered a multitude of learning modalities (e.g., hybrid, socially distanced face-to-face instruction, virtual environment), it becomes critical to examine how this learning disruption influenced elementary mathematic performance.

Author/Presenter

Dara Bright

Yiyun “Kate” Fan

Chris Fornaro

Kristin L. K. Koskey

Toni A. May

Jonathan D. Bostic

Dolores Swineford

Year
2022
Short Description

In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID-19 pandemic offered a multitude of learning modalities (e.g., hybrid, socially distanced face-to-face instruction, virtual environment), it becomes critical to examine how this learning disruption influenced elementary mathematic performance. This study tested for

differences in mathematics performance on fourth grade standardized tests before and during COVID-19 in a case study of a rural Ohio school district using the Measure of Academic Progress (MAP) mathematics test.

AI for Tackling STEM Education Challenges

Artificial intelligence (AI), an emerging technology, finds increasing use in STEM education and STEM education research (e.g., Zhai et al., 2020b; Ouyang et al., 2022; Linn et al., 2023). AI, defined as a technology to mimic human cognitive behaviors, holds great potential to address some of the most challenging problems in STEM education (Neumann and Waight, 2020; Zhai, 2021). Amongst these is the challenge of supporting all students to meet the vision for science learning in the 21st century laid out, for example in the U.S.

Author/Presenter

Xiaoming Zhai

Knut Neumann

Joseph Krajcik

Year
2023
Short Description

To best support students in developing competence, assessments that allow students to use knowledge to solve challenging problems and make sense of phenomena are needed. These assessments need to be designed and tested to validly locate students on the learning progression and hence provide feedback to students and teachers about meaningful next steps in their learning. Yet, such tasks are time-consuming to score and challenging to provide students with appropriate feedback to develop their knowledge to the next level.

AI for Tackling STEM Education Challenges

Artificial intelligence (AI), an emerging technology, finds increasing use in STEM education and STEM education research (e.g., Zhai et al., 2020b; Ouyang et al., 2022; Linn et al., 2023). AI, defined as a technology to mimic human cognitive behaviors, holds great potential to address some of the most challenging problems in STEM education (Neumann and Waight, 2020; Zhai, 2021). Amongst these is the challenge of supporting all students to meet the vision for science learning in the 21st century laid out, for example in the U.S.

Author/Presenter

Xiaoming Zhai

Knut Neumann

Joseph Krajcik

Year
2023
Short Description

To best support students in developing competence, assessments that allow students to use knowledge to solve challenging problems and make sense of phenomena are needed. These assessments need to be designed and tested to validly locate students on the learning progression and hence provide feedback to students and teachers about meaningful next steps in their learning. Yet, such tasks are time-consuming to score and challenging to provide students with appropriate feedback to develop their knowledge to the next level.

AI for Tackling STEM Education Challenges

Artificial intelligence (AI), an emerging technology, finds increasing use in STEM education and STEM education research (e.g., Zhai et al., 2020b; Ouyang et al., 2022; Linn et al., 2023). AI, defined as a technology to mimic human cognitive behaviors, holds great potential to address some of the most challenging problems in STEM education (Neumann and Waight, 2020; Zhai, 2021). Amongst these is the challenge of supporting all students to meet the vision for science learning in the 21st century laid out, for example in the U.S.

Author/Presenter

Xiaoming Zhai

Knut Neumann

Joseph Krajcik

Year
2023
Short Description

To best support students in developing competence, assessments that allow students to use knowledge to solve challenging problems and make sense of phenomena are needed. These assessments need to be designed and tested to validly locate students on the learning progression and hence provide feedback to students and teachers about meaningful next steps in their learning. Yet, such tasks are time-consuming to score and challenging to provide students with appropriate feedback to develop their knowledge to the next level.