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Gallo, Katarzyna Zaruska – ProQuest LLC, 2018
Prominent Feature Analysis (PFA) is a reliable and valid writing assessment tool, derived from the writing it is used to assess. PFA, used to assess on-demand expository essays in Grades 3-12, uncovers positive and negative characteristics of a sample. To extend PFA to a new academic level and genre, I assessed scientific writing of 208…
Descriptors: Undergraduate Students, Technical Writing, Content Area Writing, College Science
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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
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Allen, Laura; Crossley, Scott; Kyle, Kris; McNamara, Danielle S. – Grantee Submission, 2014
The current study examined relationships between expert human judgments of text quality and grammar and mechanical errors in student writing. A corpus of essays (N = 100) written by high school students in the W-Pal system was collected, coded for grammar and mechanical errors, and scored by expert human raters. Results revealed weak relations…
Descriptors: Grammar, Writing Evaluation, Writing Instruction, Essays
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Müller, Amanda – Higher Education Research and Development, 2015
This paper attempts to demonstrate the differences in writing between International English Language Testing System (IELTS) bands 6.0, 6.5 and 7.0. An analysis of exemplars provided from the IELTS test makers reveals that IELTS 6.0, 6.5 and 7.0 writers can make a minimum of 206 errors, 96 errors and 35 errors per 1000 words. The following section…
Descriptors: English (Second Language), Second Language Learning, Language Tests, Scores
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Omosewo, Esther Ore; Akanbi, Abdulrasaq Oladimeji – Acta Didactica Napocensia, 2013
The study attempt to find out the types of error committed and influence of gender on the type of error committed by senior secondary school physics students in metropolis. Six (6) schools were purposively chosen for the study. One hundred and fifty five students' scripts were randomly sampled for the study. Joint Mock physics essay questions…
Descriptors: Foreign Countries, Secondary School Students, High School Seniors, Secondary School Science
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Blanchard, Daniel; Tetreault, Joel; Higgins, Derrick; Cahill, Aoife; Chodorow, Martin – ETS Research Report Series, 2013
This report presents work on the development of a new corpus of non-native English writing. It will be useful for the task of native language identification, as well as grammatical error detection and correction, and automatic essay scoring. In this report, the corpus is described in detail.
Descriptors: Language Tests, Second Language Learning, English (Second Language), Writing Tests
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection