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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
Student Approaches to Generating Mathematical Examples: Comparing E-Assessment and Paper-Based Tasks
George Kinnear; Paola Iannone; Ben Davies – Educational Studies in Mathematics, 2025
Example-generation tasks have been suggested as an effective way to both promote students' learning of mathematics and assess students' understanding of concepts. E-assessment offers the potential to use example-generation tasks with large groups of students, but there has been little research on this approach so far. Across two studies, we…
Descriptors: Mathematics Skills, Learning Strategies, Skill Development, Student Evaluation
Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
Ulrike Padó; Yunus Eryilmaz; Larissa Kirschner – International Journal of Artificial Intelligence in Education, 2024
Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need for high-quality models, which is exacerbated for languages with fewer resources than English; a usability…
Descriptors: Grading, Automation, Test Format, Computer Assisted Testing
Running out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time
Burhan Ogut; Ruhan Circi; Huade Huo; Juanita Hicks; Michelle Yin – International Electronic Journal of Elementary Education, 2025
This study explored the effectiveness of extended time (ET) accommodations in the 2017 NAEP Grade 8 Mathematics assessment to enhance educational equity. Analyzing NAEP process data through an XGBoost model, we examined if early interactions with assessment items could predict students' likelihood of requiring ET by identifying those who received…
Descriptors: Identification, Testing Accommodations, National Competency Tests, Equal Education
Yusha Lv; Xiaoli Wang; Xuemei Zhang; Juan Li – PRIMUS, 2024
This paper first analyzed the shortcomings of the summative final exam methods which focuses only on final exams. Then, we showed the specific implementation of the quantitative formative assessment which includes objective results and subjective scores. Objective results include the traditional written chapter test score, online mid-term and…
Descriptors: Mathematics Tests, Formative Evaluation, Scores, Student Evaluation
Qutaiba I. Ali – Discover Education, 2024
This paper contributes to the ongoing efforts aimed at enhancing Outcome-Based Education (OBE) assessment methodologies by addressing some critical gaps and exploring new solutions. Our work focuses on two main areas: firstly, this study proposes an improved assessment method for OBE. It refines traditional approaches by classifying course…
Descriptors: Outcome Based Education, Evaluation Methods, Student Evaluation, Artificial Intelligence
Ethan Roy; Mathieu Guillaume; Amandine Van Rinsveld; Project iLead Consortium; Bruce D. McCandliss – npj Science of Learning, 2025
Arithmetic fluency is regarded as a foundational math skill, typically measured as a single construct with pencil-and-paper-based timed assessments. We introduce a tablet-based assessment of single-digit fluency that captures individual trial response times across several embedded experimental contrasts of interest. A large (n = 824) cohort of…
Descriptors: Arithmetic, Mathematics Skills, Tablet Computers, Grade 3
Andersen, Øistein E.; Yuan, Zheng; Watson, Rebecca; Cheung, Kevin Yet Fong – International Educational Data Mining Society, 2021
Automated essay scoring (AES), where natural language processing is applied to score written text, can underpin educational resources in blended and distance learning. AES performance has typically been reported in terms of correlation coefficients or agreement statistics calculated between a system and an expert human examiner. We describe the…
Descriptors: Evaluation Methods, Scoring, Essays, Computer Assisted Testing
Colette Melissa Kell; Yasmeen Thandar; Adelle Kemlall Bhundoo; Firoza Haffejee; Bongiwe Mbhele; Jennifer Ducray – Journal of Applied Research in Higher Education, 2025
Purpose: Academic integrity is vital to the success and sustainability of the academic project and particularly critical in the training of ethical and informed health professionals. Yet studies have found that cheating in online exams was commonplace during the COVID-19 pandemic. With the increased use of online and blended learning…
Descriptors: Foreign Countries, Universities, Integrity, Cheating
Pearson, Christopher; Penna, Nigel – Assessment & Evaluation in Higher Education, 2023
E-assessments are becoming increasingly common and progressively more complex. Consequently, how these longer, more complex questions are designed and marked is imperative. This article uses the NUMBAS e-assessment tool to investigate the best practice for creating longer questions and their mark schemes on surveying modules taken by engineering…
Descriptors: Automation, Scoring, Engineering Education, Foreign Countries
Alexis Polanco Jr.; Tsai Lu Liu – Journal of Educational Technology Systems, 2024
The process by which user experiences (UX) for children are created is uncertain, especially for deaf and hard of hearing (DHH) children. This paper seeks to (I) describe the origins of UX and child-computer interaction and to describe what is being taught to designers today; (II) use the example of digital assessment to extract insights from…
Descriptors: Design, Deafness, Hearing Impairments, Computer Assisted Testing
Abdessamad Chanaa; Nour-eddine El Faddouli – Journal of Education and Learning (EduLearn), 2024
Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning…
Descriptors: Electronic Learning, Evaluation Methods, Artificial Intelligence, Taxonomy
Griffiths, Barry J. – Research on Education and Media, 2022
This pilot study looks at how the author proactively sought to mitigate the issue of cheating when giving online tests during the Spring 2021 semester, at a time when the COVID-19 pandemic forced many teachers around the world to use modalities that involved distance learning. The genesis, implementation and results of the strategy used during the…
Descriptors: Computer Assisted Testing, Supervision, Cheating, Educational Technology
Das, Bidyut; Majumder, Mukta; Phadikar, Santanu; Sekh, Arif Ahmed – Research and Practice in Technology Enhanced Learning, 2021
Learning through the internet becomes popular that facilitates learners to learn anything, anytime, anywhere from the web resources. Assessment is most important in any learning system. An assessment system can find the self-learning gaps of learners and improve the progress of learning. The manual question generation takes much time and labor.…
Descriptors: Automation, Test Items, Test Construction, Computer Assisted Testing