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What Works Clearinghouse Rating
Direct linkYi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
Download full textSteedle, Jeffrey; Quesen, Sarah; Boyd, Aimee – Partnership for Assessment of Readiness for College and Careers, 2017
On the Partnership for Assessment of Readiness for College and Careers (PARCC) assessments, the attainment of performance level 4 is intended to indicate college readiness or being "on track" to college and career readiness. Students who achieve Level 4 should have a 0.75 probability of attaining at least a C in entry-level,…
Descriptors: College Readiness, Career Readiness, Test Validity, Longitudinal Studies
Peer reviewedEvensen, Lars Sigfred; Berge, Kjell Lars; Thygesen, Ragnar; Matre, Synnove; Solheim, Randi – Curriculum Journal, 2016
The Berge et al. article in this volume presents the functional construct of writing that underlies summative and formative assessment of writing as a key competency in Norway. A functional construct implies that specific acts of writing and their purposes constrain what is a relevant selection among the semiotic resources that writing generally…
Descriptors: Foreign Countries, Academic Standards, Writing Evaluation, Evaluation Methods
Allen, Jeff – ACT, Inc., 2014
This report focuses on the initial development of the predicted score paths for ACT Aspire reporting. The paths provide predicted score ranges for the next two years--as well as predicted ACT score ranges for tests administered at grades 9 and 10. Longitudinal ACT Aspire data for students tested in spring 2013 and spring 2014, as well as…
Descriptors: College Readiness, Career Readiness, Achievement Tests, Scores
Hoyle, Craig D.; O'Dwyer, Laura M.; Chang, Quincy – Regional Educational Laboratory Northeast & Islands, 2011
The Maine Department of Education wanted to use longitudinal data from its data system to better understand whether and how student and school characteristics are associated with student performance on the state-mandated Maine High School Assessment (MHSA). It was particularly interested in understanding the factors associated with changes in test…
Descriptors: High Schools, Critical Reading, Educational Improvement, Federal Programs
Hoyle, Craig D.; O'Dwyer, Laura M.; Chang, Quincy – Regional Educational Laboratory Northeast & Islands, 2011
The Maine Department of Education wanted to use longitudinal data from its data system to better understand whether and how student and school characteristics are associated with student performance on the state-mandated Maine High School Assessment (MHSA). It was particularly interested in understanding the factors associated with changes in test…
Descriptors: High Schools, Intervals, Critical Reading, Educational Improvement
Attali, Yigal; Burstein, Jill – ETS Research Report Series, 2005
The e-rater® system has been used by ETS for automated essay scoring since 1999. This paper describes a new version of e-rater (v.2.0) that differs from the previous one (v.1.3) with regard to the feature set and model building approach. The paper describes the new version, compares the new and previous versions in terms of performance, and…
Descriptors: Essay Tests, Automation, Scoring, Comparative Analysis
