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Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
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Wan, Qian; Crossley, Scott; Allen, Laura; McNamara, Danielle – Grantee Submission, 2020
In this paper, we extracted content-based and structure-based features of text to predict human annotations for claims and nonclaims in argumentative essays. We compared Logistic Regression, Bernoulli Naive Bayes, Gaussian Naive Bayes, Linear Support Vector Classification, Random Forest, and Neural Networks to train classification models. Random…
Descriptors: Persuasive Discourse, Essays, Writing Evaluation, Natural Language Processing
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2021
Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…
Descriptors: Computer Assisted Testing, Scoring, Natural Language Processing, Computer Software
Panaite, Marilena; Ruseti, Stefan; Dascalu, Mihai; Balyan, Renu; McNamara, Danielle S.; Trausan-Matu, Stefan – Grantee Submission, 2019
Intelligence Tutoring Systems (ITSs) focus on promoting knowledge acquisition, while providing relevant feedback during students' practice. Self-explanation practice is an effective method used to help students understand complex texts by leveraging comprehension. Our aim is to introduce a deep learning neural model for automatically scoring…
Descriptors: Computer Assisted Testing, Scoring, Intelligent Tutoring Systems, Natural Language Processing
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Baral, Sami; Botelho, Anthony; Santhanam, Abhishek; Gurung, Ashish; Cheng, Li; Heffernan, Neil – International Educational Data Mining Society, 2023
Teachers often rely on the use of a range of open-ended problems to assess students' understanding of mathematical concepts. Beyond traditional conceptions of student open-ended work, commonly in the form of textual short-answer or essay responses, the use of figures, tables, number lines, graphs, and pictographs are other examples of open-ended…
Descriptors: Mathematics Instruction, Mathematical Concepts, Problem Solving, Test Format
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Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
Guerrero, Tricia A.; Wiley, Jennifer – Grantee Submission, 2019
Teachers may wish to use open-ended learning activities and tests, but they are burdensome to assess compared to forced-choice instruments. At the same time, forced-choice assessments suffer from issues of guessing (when used as tests) and may not encourage valuable behaviors of construction and generation of understanding (when used as learning…
Descriptors: Computer Assisted Testing, Student Evaluation, Introductory Courses, Psychology
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Papasalouros, Andreas; Chatzigiannakou, Maria – International Association for Development of the Information Society, 2018
Automating the production of questions for assessment and self-assessment has become recently an active field of study. The use of Semantic Web technologies has certain advantages over other methods for question generation and thus is one of the most important lines of research for this problem. The aim of this paper is to provide an overview of…
Descriptors: Computer Assisted Testing, Web 2.0 Technologies, Test Format, Multiple Choice Tests
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Zesch, Torsten; Horbach, Andrea; Melanie Goggin, Melanie; Wrede-Jackes, Jennifer – Research-publishing.net, 2018
We present a tool for the creation and curation of C-tests. C-tests are an established tool in language proficiency testing and language learning. They require examinees to complete a text in which the second half of every second word is replaced by a gap. We support teachers and test designers in creating such tests through a web-based system…
Descriptors: Language Tests, Language Proficiency, Second Language Learning, Second Language Instruction
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Lang, David; Stenhaug, Ben; Kizilcec, Rene – Grantee Submission, 2019
This research evaluates the psychometric properties of short-answer response items under a variety of grading rules in the context of a mobile learning platform in Africa. This work has three main findings. First, we introduce the concept of a differential device function (DDF), a type of differential item function that stems from the device a…
Descriptors: Foreign Countries, Psychometrics, Test Items, Test Format
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of writing proficiency generally includes analyses of the specific linguistic and rhetorical features contained in the singular essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing might more closely capture writing skill.…
Descriptors: Writing Evaluation, Writing Tests, Computer Assisted Testing, Writing Skills
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Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2014
This study explores correlations between human ratings of essay quality and component scores based on similar natural language processing indices and weighted through a principal component analysis. The results demonstrate that such component scores show small to large effects with human ratings and thus may be suitable to providing both summative…
Descriptors: Essays, Computer Assisted Testing, Writing Evaluation, Scores
Baker, Eva L.; And Others – 1988
Evaluation models are being developed for assessing artificial intelligence (AI) systems in terms of similar performance by groups of people. Natural language understanding and vision systems are the areas of concentration. In simplest terms, the goal is to norm a given natural language system's performance on a sample of people. The specific…
Descriptors: Artificial Intelligence, Comparative Analysis, Computer Assisted Testing, Computer Science
Hancock, Anne Campbell; Byrd, Diana – 1984
A study tested the hypothesis that learning disabled (LD), specifically reading disabled, children differ from "normal" children in their ability to acquire automatic perceptual processes. The subjects were 16 third grade and 15 sixth grade students, of whom 7 third grade and 3 sixth grade students were classified as LD. LaBerge's letter…
Descriptors: Attention, Cognitive Processes, Comparative Analysis, Computer Assisted Testing