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Schneider, Johannes; Richner, Robin; Riser, Micha – International Journal of Artificial Intelligence in Education, 2023
Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading. The statistical and black-box nature of state-of-the-art machine learning models makes them…
Descriptors: Grading, Natural Language Processing, Computer Assisted Testing, Ethics
Peguero, Wendy – ProQuest LLC, 2022
Administration and scoring of cognitive assessments have evolved from a paper-based platform to a digital format. Since this advancement, Pearson has created a system (Q-interactive) that allows examiners to administer the WISC-V via two iPads. However, limited research exists exploring the effects of this new method of administration when…
Descriptors: Children, Intelligence Tests, Examiners, Computer Assisted Testing
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Dalton, Sarah Grace; Stark, Brielle C.; Fromm, Davida; Apple, Kristen; MacWhinney, Brian; Rensch, Amanda; Rowedder, Madyson – Journal of Speech, Language, and Hearing Research, 2022
Purpose: The aim of this study was to advance the use of structured, monologic discourse analysis by validating an automated scoring procedure for core lexicon (CoreLex) using transcripts. Method: Forty-nine transcripts from persons with aphasia and 48 transcripts from persons with no brain injury were retrieved from the AphasiaBank database. Five…
Descriptors: Validity, Discourse Analysis, Databases, Scoring
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Ganzfried, Sam; Yusuf, Farzana – Education Sciences, 2018
A problem faced by many instructors is that of designing exams that accurately assess the abilities of the students. Typically, these exams are prepared several days in advance, and generic question scores are used based on rough approximation of the question difficulty and length. For example, for a recent class taught by the author, there were…
Descriptors: Weighted Scores, Test Construction, Student Evaluation, Multiple Choice Tests
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Nutbrown, Stephen; Higgins, Colin – Computer Science Education, 2016
This article explores the suitability of static analysis techniques based on the abstract syntax tree (AST) for the automated assessment of early/mid degree level programming. Focus is on fairness, timeliness and consistency of grades and feedback. Following investigation into manual marking practises, including a survey of markers, the assessment…
Descriptors: Programming, Grading, Evaluation Methods, Feedback (Response)
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English, John; English, Tammy – Journal of Information Technology Education: Innovations in Practice, 2015
In this paper we discuss the use of automated assessment in a variety of computer science courses that have been taught at Israel Academic College by the authors. The course assignments were assessed entirely automatically using Checkpoint, a web-based automated assessment framework. The assignments all used free-text questions (where the students…
Descriptors: Computer Science Education, Computer Assisted Testing, Foreign Countries, College Students
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Grimaldi, Phillip J.; Karpicke, Jeffrey D. – Journal of Educational Psychology, 2014
Retrieval practice is a powerful way to promote long-term retention and meaningful learning. However, students do not frequently practice retrieval on their own, and when they do, they have difficulty evaluating the correctness of their responses and making effective study choices. To address these problems, we have developed a guided retrieval…
Descriptors: Information Retrieval, Computer Assisted Instruction, Electronic Learning, Evaluation Methods
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Finkelman, Matthew D.; Weiss, David J.; Kim-Kang, Gyenam – Applied Psychological Measurement, 2010
Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC…
Descriptors: Computer Assisted Testing, Hypothesis Testing, Measurement, Item Analysis
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Hasselbring, Ted S.; And Others – 1989
This monograph provides an overview of computer-based assessment and error analysis in the instruction of elementary students with complex medical, learning, and/or behavioral problems. Information on generating and scoring tests using the microcomputer is offered, as are ideas for using computers in the analysis of mathematical strategies and…
Descriptors: Behavior Problems, Computer Assisted Testing, Computer Managed Instruction, Diagnostic Teaching
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Woodward, John; Howard, Lisa – Exceptional Children, 1994
TORUS, a prototype technology-based educational diagnostic program, is described. The usefulness of TORUS to identify and remediate the mathematics misconceptions of students with learning disabilities is reported. Results suggest the need for greater emphasis on conceptual understanding in mathematics instruction. (Author/DB)
Descriptors: Cognitive Development, Computer Assisted Testing, Diagnostic Teaching, Educational Diagnosis
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