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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
Buczak, Philip; Huang, He; Forthmann, Boris; Doebler, Philipp – Journal of Creative Behavior, 2023
Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…
Descriptors: Computer Assisted Testing, Scoring, Automation, Creative Thinking
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
Binglin Chen – ProQuest LLC, 2022
Assessment is a key component of education. Routine grading of students' work, however, is time consuming. Automating the grading process allows instructors to spend more of their time helping their students learn and engaging their students with more open-ended, creative activities. One way to automate grading is through computer-based…
Descriptors: College Students, STEM Education, Student Evaluation, Grading
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
Myers, Matthew C.; Wilson, Joshua – International Journal of Artificial Intelligence in Education, 2023
This study evaluated the construct validity of six scoring traits of an automated writing evaluation (AWE) system called "MI Write." Persuasive essays (N = 100) written by students in grades 7 and 8 were randomized at the sentence-level using a script written with Python's NLTK module. Each persuasive essay was randomized 30 times (n =…
Descriptors: Construct Validity, Automation, Writing Evaluation, Algorithms
Heng Lu – PASAA: Journal of Language Teaching and Learning in Thailand, 2023
The test view is on the Duolingo English Test (DET), an alternative online English proficiency test with a machine-driven characteristic. The review covers essential information of the DET such as test purpose, usage, score-mapping with CEFR scale, price, and publisher. Meanwhile, the test usefulness is discussed with focuses on reliability,…
Descriptors: Computer Software, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
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

Clauser, Brian E.; Margolis, Melissa J.; Clyman, Stephen G.; Ross, Linette P. – Journal of Educational Measurement, 1997
Research on automated scoring is extended by comparing alternative automated systems for scoring a computer simulation of physicians' patient management skills. A regression-based system is more highly correlated with experts' evaluations than a system that uses complex rules to map performances into score levels, but both approaches are feasible.…
Descriptors: Algorithms, Automation, Comparative Analysis, Computer Assisted Testing
Schnipke, Deborah L.; Reese, Lynda M. – 1997
Two-stage and multistage test designs provide a way of roughly adapting item difficulty to test-taker ability. All test takers take a parallel stage-one test, and, based on their scores, they are routed to tests of different difficulty levels in subsequent stages. These designs provide some of the benefits of standard computerized adaptive testing…
Descriptors: Ability, Adaptive Testing, Algorithms, Comparative Analysis

Wainer, Howard; Lewis, Charles – Journal of Educational Measurement, 1990
Three different applications of the testlet concept are presented, and the psychometric models most suitable for each application are described. Difficulties that testlets can help overcome include (1) context effects; (2) item ordering; and (3) content balancing. Implications for test construction are discussed. (SLD)
Descriptors: Algorithms, Computer Assisted Testing, Elementary Secondary Education, Item Response Theory

Clauser, Brian E.; Ross, Linette P.; Clyman, Stephen G.; Rose, Kathie M.; Margolis, Melissa J.; Nungester, Ronald J.; Piemme, Thomas E.; Chang, Lucy; El-Bayoumi, Gigi; Malakoff, Gary L.; Pincetl, Pierre S. – Applied Measurement in Education, 1997
Describes an automated scoring algorithm for a computer-based simulation examination of physicians' patient-management skills. Results with 280 medical students show that scores produced using this algorithm are highly correlated to actual clinician ratings. Scores were also effective in discriminating between case performance judged passing or…
Descriptors: Algorithms, Computer Assisted Testing, Computer Simulation, Evaluators
Hicks, Marilyn M. – 1989
Methods of computerized adaptive testing using conventional scoring methods in order to develop a computerized placement test for the Test of English as a Foreign Language (TOEFL) were studied. As a consequence of simulation studies during the first phase of the study, the multilevel testing paradigm was adopted to produce three test levels…
Descriptors: Adaptive Testing, Adults, Algorithms, Computer Assisted Testing