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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
Alhadi, Moosa; Zhang, Dake; Wang, Ting; Maher, Carolyn A. – Computers in the Schools, 2023
This research synthesizes studies that used a Digitalized Interactive Component (DIC) to assess K-12 student performance during Computer-based-Assessments (CBAs) in mathematics. A systematic search identified ten studies, including four that provided language assistance and six that provided response-construction support. We reported on the one…
Descriptors: Computer Assisted Testing, Mathematics Tests, Student Evaluation, Elementary Secondary Education
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
Jian Zhao; Elaine Chapman; Peyman G. P. Sabet – Education Research and Perspectives, 2024
The launch of ChatGPT and the rapid proliferation of generative AI (GenAI) have brought transformative changes to education, particularly in the field of assessment. This has prompted a fundamental rethinking of traditional assessment practices, presenting both opportunities and challenges in evaluating student learning. While numerous studies…
Descriptors: Literature Reviews, Artificial Intelligence, Evaluation Methods, Student Evaluation
Arif Cem Topuz; Kinshuk – Educational Technology Research and Development, 2024
Online assessments of learning, or online exams, have become increasingly widespread with the rise of distance learning. Online exams are preferred by many students and are perceived as a quick and easy tool to measure knowledge. On the contrary, some students are concerned about the possibility of cheating and technological difficulties in online…
Descriptors: Computer Assisted Testing, Student Evaluation, Evaluation Methods, Student Attitudes
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
Petrilli, Michael J. – Education Next, 2022
In the late 1960s, when federal officials and eminent psychologists were first designing the National Assessment of Educational Progress (NAEP), they probably never contemplated testing students younger than nine. The technology for mass testing at the time--bubble sheets and No. 2 pencils--only worked if students could read the instructions and…
Descriptors: Kindergarten, Student Evaluation, National Competency Tests, 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
E. Marano; P. M. Newton; Z. Birch; M. Croombs; C. Gilbert; M. J. Draper – Higher Education Quarterly, 2024
Remote or online proctoring (invigilating) is a technology primarily used to improve the integrity of online examinations. The use of remote proctoring increased significantly as the world switched to online assessment during the COVID-19 pandemic. Remote proctoring received negative media attention, including concerns about user privacy,…
Descriptors: Student Experience, Supervision, Distance Education, Technology Uses in Education
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