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Zhai, Xiaoming; Shi, Lehong; Nehm, Ross H. – Journal of Science Education and Technology, 2021
Machine learning (ML) has been increasingly employed in science assessment to facilitate automatic scoring efforts, although with varying degrees of success (i.e., magnitudes of machine-human score agreements [MHAs]). Little work has empirically examined the factors that impact MHA disparities in this growing field, thus constraining the…
Descriptors: Meta Analysis, Man Machine Systems, Artificial Intelligence, Computer Assisted Testing
Keith Cochran; Clayton Cohn; Peter Hastings; Noriko Tomuro; Simon Hughes – International Journal of Artificial Intelligence in Education, 2024
To succeed in the information age, students need to learn to communicate their understanding of complex topics effectively. This is reflected in both educational standards and standardized tests. To improve their writing ability for highly structured domains like scientific explanations, students need feedback that accurately reflects the…
Descriptors: Science Process Skills, Scientific Literacy, Scientific Concepts, Concept Formation
Zhai, Xiaoming; Yin, Yue; Pellegrino, James W.; Haudek, Kevin C.; Shi, Lehong – Studies in Science Education, 2020
Machine learning (ML) is an emergent computerised technology that relies on algorithms built by 'learning' from training data rather than 'instruction', which holds great potential to revolutionise science assessment. This study systematically reviewed 49 articles regarding ML-based science assessment through a triangle framework with technical,…
Descriptors: Science Education, Computer Assisted Testing, Science Tests, Scoring
Hong Jiao, Editor; Robert W. Lissitz, Editor – IAP - Information Age Publishing, Inc., 2024
With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better…
Descriptors: Artificial Intelligence, Natural Language Processing, Psychometrics, Computer Assisted Testing
Çinar, Ayse; Ince, Elif; Gezer, Murat; Yilmaz, Özgür – Education and Information Technologies, 2020
Worldwide, open-ended questions that require short answers have been used in many exams in fields of science, such as the International Student Assessment Program (PISA), the International Science and Maths Trends Research (TIMSS). However, multiple-choice questions are used for many exams at the national level in Turkey, especially high school…
Descriptors: Foreign Countries, Computer Assisted Testing, Artificial Intelligence, Grading
New York State Education Department, 2024
The instructions in this manual explain the responsibilities of school administrators for the New York State Testing Program (NYSTP) Grades 3-8 English Language Arts, Mathematics, and Grades 5 & 8 Science Tests. School administrators must be thoroughly familiar with the contents of the manual, and the policies and procedures must be followed…
Descriptors: Testing Programs, Language Arts, Mathematics Tests, Science Tests
Gerard, Libby; Kidron, Ady; Linn, Marcia C. – International Journal of Computer-Supported Collaborative Learning, 2019
This paper illustrates how the combination of teacher and computer guidance can strengthen collaborative revision and identifies opportunities for teacher guidance in a computer-supported collaborative learning environment. We took advantage of natural language processing tools embedded in an online, collaborative environment to automatically…
Descriptors: Computer Assisted Testing, Student Evaluation, Science Tests, Scoring
Lottridge, Susan; Wood, Scott; Shaw, Dan – Applied Measurement in Education, 2018
This study sought to provide a framework for evaluating machine score-ability of items using a new score-ability rating scale, and to determine the extent to which ratings were predictive of observed automated scoring performance. The study listed and described a set of factors that are thought to influence machine score-ability; these factors…
Descriptors: Program Effectiveness, Computer Assisted Testing, Test Scoring Machines, Scoring
Mullis, Ina V. S., Ed.; Martin, Michael O., Ed.; von Davier, Matthias, Ed. – International Association for the Evaluation of Educational Achievement, 2021
TIMSS (Trends in International Mathematics and Science Study) is a long-standing international assessment of mathematics and science at the fourth and eighth grades that has been collecting trend data every four years since 1995. About 70 countries use TIMSS trend data for monitoring the effectiveness of their education systems in a global…
Descriptors: Achievement Tests, International Assessment, Science Achievement, Mathematics Achievement
Nebraska Department of Education, 2020
The Spring 2020 Nebraska Student-Centered Assessment System (NSCAS) General Summative testing was cancelled due to COVID-19. This technical report documents the processes and procedures that had been implemented to support the Spring 2020 assessments prior to the cancellation. The following sections are presented in this technical report: (1)…
Descriptors: English, Language Arts, Mathematics Tests, Science Tests
Lee, Hee-Sun; Pallant, Amy; Pryputniewicz, Sarah; Lord, Trudi; Mulholland, Matthew; Liu, Ou Lydia – Science Education, 2019
This paper describes HASbot, an automated text scoring and real-time feedback system designed to support student revision of scientific arguments. Students submit open-ended text responses to explain how their data support claims and how the limitations of their data affect the uncertainty of their explanations. HASbot automatically scores these…
Descriptors: Middle School Students, High School Students, Student Evaluation, Science Education
Nebraska Department of Education, 2019
This technical report documents the processes and procedures implemented to support the Spring 2019 Nebraska Student-Centered Assessment System (NSCAS) General Summative English Language Arts (ELA), Mathematics, and Science assessments by NWEA® under the supervision of the Nebraska Department of Education (NDE). The technical report shows how the…
Descriptors: English, Language Arts, Summative Evaluation, Mathematics Tests
Mao, Liyang; Liu, Ou Lydia; Roohr, Katrina; Belur, Vinetha; Mulholland, Matthew; Lee, Hee-Sun; Pallant, Amy – Educational Assessment, 2018
Scientific argumentation is one of the core practices for teachers to implement in science classrooms. We developed a computer-based formative assessment to support students' construction and revision of scientific arguments. The assessment is built upon automated scoring of students' arguments and provides feedback to students and teachers.…
Descriptors: Computer Assisted Testing, Science Tests, Scoring, Automation
Wagemaker, Hans, Ed. – International Association for the Evaluation of Educational Achievement, 2020
Although International Association for the Evaluation of Educational Achievement-pioneered international large-scale assessment (ILSA) of education is now a well-established science, non-practitioners and many users often substantially misunderstand how large-scale assessments are conducted, what questions and challenges they are designed to…
Descriptors: International Assessment, Achievement Tests, Educational Assessment, Comparative Analysis

Braun, Henry I.; And Others – Journal of Educational Measurement, 1990
The accuracy with which expert systems (ESs) score a new nonmultiple-choice free-response test item was investigated, using 734 high school students who were administered an advanced-placement computer science examination. ESs produced scores for 82 percent to 95 percent of the responses and displayed high agreement with a human reader on the…
Descriptors: Advanced Placement, Computer Assisted Testing, Computer Science, Constructed Response
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