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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
Ramnarain-Seetohul, Vidasha; Bassoo, Vandana; Rosunally, Yasmine – Education and Information Technologies, 2022
In automated essay scoring (AES) systems, similarity techniques are used to compute the score for student answers. Several methods to compute similarity have emerged over the years. However, only a few of them have been widely used in the AES domain. This work shows the findings of a ten-year review on similarity techniques applied in AES systems…
Descriptors: Computer Assisted Testing, Essays, Scoring, Automation
Guher Gorgun; Okan Bulut – Education and Information Technologies, 2024
In light of the widespread adoption of technology-enhanced learning and assessment platforms, there is a growing demand for innovative, high-quality, and diverse assessment questions. Automatic Question Generation (AQG) has emerged as a valuable solution, enabling educators and assessment developers to efficiently produce a large volume of test…
Descriptors: Computer Assisted Testing, Test Construction, Test Items, Automation
Wang, Hei-Chia; Maslim, Martinus; Kan, Chia-Hao – Education and Information Technologies, 2023
Distance learning frees the learning process from spatial constraints. Each mode of distance learning, including synchronous and asynchronous learning, has disadvantages. In synchronous learning, students have network bandwidth and noise concerns, but in asynchronous learning, they have fewer opportunities for engagement, such as asking questions.…
Descriptors: Automation, Artificial Intelligence, Computer Assisted Testing, Asynchronous Communication
Jessie S. Barrot – Education and Information Technologies, 2024
This bibliometric analysis attempts to map out the scientific literature on automated writing evaluation (AWE) systems for teaching, learning, and assessment. A total of 170 documents published between 2002 and 2021 in Social Sciences Citation Index journals were reviewed from four dimensions, namely size (productivity and citations), time…
Descriptors: Educational Trends, Automation, Computer Assisted Testing, Writing Tests
Huawei, Shi; Aryadoust, Vahid – Education and Information Technologies, 2023
Automated writing evaluation (AWE) systems are developed based on interdisciplinary research and technological advances such as natural language processing, computer sciences, and latent semantic analysis. Despite a steady increase in research publications in this area, the results of AWE investigations are often mixed, and their validity may be…
Descriptors: Writing Evaluation, Writing Tests, Computer Assisted Testing, Automation
Muuli, Eerik; Tõnisson, Eno; Lepp, Marina; Luik, Piret; Palts, Tauno; Suviste, Reelika; Papli, Kaspar; Säde, Merilin – Education and Information Technologies, 2020
There are thousands of participants in different programming MOOCs (Massive Open Online Courses) which means thousands of solutions have to be assessed. As it is very time-consuming to assess that amount of solutions manually, using automated assessment is essential. Since task requirements must be strict for the solutions to be automatically…
Descriptors: Online Courses, Programming, Computer Assisted Testing, Visual Stimuli
Wijanarko, Bambang Dwi; Heryadi, Yaya; Toba, Hapnes; Budiharto, Widodo – Education and Information Technologies, 2021
Automated question generation is a task to generate questions from structured or unstructured data. The increasing popularity of online learning in recent years has given momentum to automated question generation in education field for facilitating learning process, learning material retrieval, and computer-based testing. This paper report on the…
Descriptors: Foreign Countries, Undergraduate Students, Engineering Education, Computer Software
Murad, Dina Fitria; Heryadi, Yaya; Isa, Sani Muhamad; Budiharto, Widodo – Education and Information Technologies, 2020
The recommender system has gained research attention from education research communities mainly due to two main reasons: increasing needs for personalized learning and big data availability in the education sector. This paper presents a hybrid user-collaborative, rule-based filtering recommendation system for education context. User profiles are…
Descriptors: Automation, Online Systems, Electronic Learning, Prediction