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Olivera-Aguilar, Margarita; Lee, Hee-Sun; Pallant, Amy; Belur, Vinetha; Mulholland, Matthew; Liu, Ou Lydia – ETS Research Report Series, 2022
This study uses a computerized formative assessment system that provides automated scoring and feedback to help students write scientific arguments in a climate change curriculum. We compared the effect of contextualized versus generic automated feedback on students' explanations of scientific claims and attributions of uncertainty to those…
Descriptors: Computer Assisted Testing, Formative Evaluation, Automation, Scoring
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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
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Institute of Education Sciences, 2017
In September, 2016, the National Center for Special Education Research (NCSER) and the National Center for Education Research (NCER) of the Institute of Education Sciences (IES) convened a group of experts to discuss and provide input on research needs in the area of middle and high school writing for students, including English learners (ELs) and…
Descriptors: Writing Research, Educational Research, Research Needs, Secondary Education
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Deane, Paul – Assessing Writing, 2013
This paper examines the construct measured by automated essay scoring (AES) systems. AES systems measure features of the text structure, linguistic structure, and conventional print form of essays; as such, the systems primarily measure text production skills. In the current state-of-the-art, AES provide little direct evidence about such matters…
Descriptors: Scoring, Essays, Text Structure, Writing (Composition)
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating