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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2024
Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…
Descriptors: Student Evaluation, Computer Assisted Testing, Artificial Intelligence, Comprehension

Andreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…
Descriptors: Difficulty Level, Reading Tests, Test Items, Reading Comprehension
Doewes, Afrizal; Kurdhi, Nughthoh Arfawi; Saxena, Akrati – International Educational Data Mining Society, 2023
Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…
Descriptors: Essays, Writing Evaluation, Evaluators, Accuracy
Sylla, Khalifa; Babou, Birahim; Ouya, Samuel – International Association for Development of the Information Society, 2022
This paper deals with a solution allowing digital universities to extend the functionalities of their distance learning platform to offer a secure solution for the dematerialization of assessments. Currently we are witnessing the rise of digital universities, this is the case in Africa, particularly in Senegal. We are witnessing strong growth in…
Descriptors: Foreign Countries, Virtual Universities, Computer Assisted Testing, Educational Technology
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
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
Derar Serhan; Natalie Welcome – International Society for Technology, Education, and Science, 2023
Recently, institutions have increased their online course offerings as well as their online degrees. With this significant growth in online offerings, assessment integrity becomes a concern. In response to this concern, many institutions have adopted the use of online proctoring services. The aim of using these online proctoring services is to…
Descriptors: Computer Assisted Testing, Privacy, Student Attitudes, Ethics
Matayoshi, Jeffrey; Uzun, Hasan; Cosyn, Eric – International Educational Data Mining Society, 2022
Knowledge space theory (KST) is a mathematical framework for modeling and assessing student knowledge. While KST has successfully served as the foundation of several learning systems, recent advancements in machine learning provide an opportunity to improve on purely KST-based approaches to assessing student knowledge. As such, in this work we…
Descriptors: Knowledge Level, Mathematical Models, Learning Experience, Comparative Analysis
Doris Zahner; Jeffrey T. Steedle; James Soland; Catherine Welch; Qi Qin; Kathryn Thompson; Richard Phelps – Online Submission, 2023
The "Standards for Educational and Psychological Testing" have served as a cornerstone for best practices in assessment. As the field evolves, so must these standards, with regular revisions ensuring they reflect current knowledge and practice. The National Council on Measurement in Education (NCME) conducted a survey to gather feedback…
Descriptors: Standards, Educational Assessment, Psychological Testing, Best Practices
Samarakou, Maria; Fylladitakis, Emmanouil D.; Prentakis, Pantelis; Athineos, Spyros – International Association for Development of the Information Society, 2014
In laboratory courses, the assessment of exercises and assignments typically is treated as a simple, quantifiable approach. This approach however rarely includes qualitative factors, especially if the grading is being automatically performed by the system, and provides little to no feedback for the students to reflect on their work. The role of…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Evaluation Methods, Engineering Education
Madhyastha, Tara M.; Tanimoto, Steven – International Working Group on Educational Data Mining, 2009
Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…
Descriptors: Web Based Instruction, Computer Assisted Testing, Computer Software, Computer Science Education
Brammer, Robert – 1997
The ways in which experience and academic training influence the types of questions therapists ask of their clients were studied. Psychologists and psychology students of varying degrees of expertise (n=138) were provided an artificial intelligence program that simulated a date rape client's responses to typed questions and were asked to conduct a…
Descriptors: Artificial Intelligence, Clinical Experience, Computer Assisted Testing, Knowledge Level
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
Perkins, Kyle; And Others – 1994
This paper reports the results of using a three-layer backpropagation artificial neural network to predict item difficulty in a reading comprehension test. Two network structures were developed, one with and one without a sigmoid function in the output processing unit. The data set, which consisted of a table of coded test items and corresponding…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Expert Systems, Item Analysis
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1986
The rule space model permits measurement of cognitive skill acquisition, diagnosis of cognitive errors, and detection of the strengths and weaknesses of knowledge possessed by individuals. Two ways to classify an individual into his or her most plausible latent state of knowledge include: (1) hypothesis testing--Bayes' decision rules for minimum…
Descriptors: Artificial Intelligence, Bayesian Statistics, Cognitive Development, Computer Assisted Testing