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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
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
Xuefan Li; Marco Zappatore; Tingsong Li; Weiwei Zhang; Sining Tao; Xiaoqing Wei; Xiaoxu Zhou; Naiqing Guan; Anny Chan – IEEE Transactions on Learning Technologies, 2025
The integration of generative artificial intelligence (GAI) into educational settings offers unprecedented opportunities to enhance the efficiency of teaching and the effectiveness of learning, particularly within online platforms. This study evaluates the development and application of a customized GAI-powered teaching assistant, trained…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation, Academic Achievement
Wallace N. Pinto Jr.; Jinnie Shin – Journal of Educational Measurement, 2025
In recent years, the application of explainability techniques to automated essay scoring and automated short-answer grading (ASAG) models, particularly those based on transformer architectures, has gained significant attention. However, the reliability and consistency of these techniques remain underexplored. This study systematically investigates…
Descriptors: Automation, Grading, Computer Assisted Testing, Scoring
Esteban Guevara Hidalgo – International Journal for Educational Integrity, 2025
The COVID-19 pandemic had a profound impact on education, forcing many teachers and students who were not used to online education to adapt to an unanticipated reality by improvising new teaching and learning methods. Within the realm of virtual education, the evaluation methods underwent a transformation, with some assessments shifting towards…
Descriptors: Foreign Countries, Higher Education, COVID-19, Pandemics
Mohd Elmagzoub Eltahir; Nagaletchimee Annamalai; Arulselvi Uthayakumaran; Samer H. Zyoud; Antonia Ramírez García; Viktorija Mažeikiene; Bilal Zakarneh; Najeh Rajeh Al Salhi – SAGE Open, 2023
Online assessment is a new introduction in many developing countries during the COVID-19 pandemic, including Malaysia, Lithuania, and Spain. The current study conducted a phenomenology study to probe insights about fairness in online assessment. The interview data were interpreted from the perspective of social psychology theory that emphasizes…
Descriptors: Foreign Countries, COVID-19, Pandemics, Scoring Rubrics
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
Celeste Combrinck; Nelé Loubser – Discover Education, 2025
Written assignments for large classes pose a far more significant challenge in the age of the GenAI revolution. Suggestions such as oral exams and formative assessments are not always feasible with many students in a class. Therefore, we conducted a study in South Africa and involved 280 Honors students to explore the usefulness of Turnitin's AI…
Descriptors: Foreign Countries, Artificial Intelligence, Large Group Instruction, Alternative Assessment
Malik, Ali; Wu, Mike; Vasavada, Vrinda; Song, Jinpeng; Coots, Madison; Mitchell, John; Goodman, Noah; Piech, Chris – International Educational Data Mining Society, 2021
Access to high-quality education at scale is limited by the difficulty of providing student feedback on open-ended assignments in structured domains like programming, graphics, and short response questions. This problem has proven to be exceptionally difficult: for humans, it requires large amounts of manual work, and for computers, until…
Descriptors: Grading, Accuracy, Computer Assisted Testing, Automation
Rowlett, Peter – International Journal of Mathematical Education in Science and Technology, 2022
A partially-automated method of assessment is proposed, in which automated question setting is used to generate individualized versions of a coursework assignment, which is completed by students and marked by hand. This is designed to be (a) comparable to a traditional written coursework assignment in validity, in that complex and open-ended tasks…
Descriptors: Mathematics Education, College Mathematics, Computer Assisted Testing, Evaluation Methods
Parisa Aqdas Karimi; Seyyed Kazem Banihashem; Harm J. A. Biemans – International Journal of Technology in Education and Science, 2023
The current paper focusses on the teachers' attitude towards and experiences with e-learning tools at two universities in different phases of e-learning implementation. The study population comprises teachers at university level and a simple random sampling method was used. A total of 45 teachers in bachelor programmes from the Faculty of…
Descriptors: College Faculty, Teacher Attitudes, Electronic Learning, Technology Uses in Education
Nejdet Karadag – Journal of Educational Technology and Online Learning, 2023
The purpose of this study is to examine the impact of artificial intelligence (AI) on online assessment in the context of opportunities and threats based on the literature. To this end, 19 articles related to the AI tool ChatGPT and online assessment were analysed through rapid literature review. In the content analysis, the themes of "AI's…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Natural Language Processing, Grading
Haldeman, Georgiana; Babes-Vroman Monica; Tjang, Andrew; Nguyen, Thu D. – ACM Transactions on Computing Education, 2021
Autograding systems are being increasingly deployed to meet the challenges of teaching programming at scale. Studies show that formative feedback can greatly help novices learn programming. This work extends an autograder, enabling it to provide formative feedback on programming assignment submissions. Our methodology starts with the design of a…
Descriptors: Student Evaluation, Feedback (Response), Grading, Automation
Hickey, Daniel; Harris, Tripp – Distance Education, 2021
Increased online learning is helping many appreciate that online grading, formative assessment, and summative testing can cause instructor burnout and leave little time for more productive instructor interactions. We reimagined grading, assessment, and testing in an extended program of design-based research using situative theory to refine online…
Descriptors: Computer Assisted Testing, Grading, Student Evaluation, Online Courses
Stowe, Ryan L.; Esselman, Brian J.; Ralph, Vanessa R.; Ellison, Aubrey J.; Martell, Jeffrey D.; DeGlopper, Kimberly S.; Schwarz, Cara E. – Journal of Chemical Education, 2020
The affordances given to a structured, timed, and proctored paper exam are not as readily applicable in a digital medium. Accordingly, the rapid shift from in-person to online enactments may have forced instructors to consider changing their assessment practices and priorities. As assessments convey strong implicit messages about "what…
Descriptors: Student Evaluation, Organic Chemistry, Online Courses, Computer Assisted Testing