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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Ngoc My Bui; Jessie S. Barrot – Education and Information Technologies, 2025
With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Hosnia M. M. Ahmed; Shaymaa E. Sorour – Education and Information Technologies, 2024
Evaluating the quality of university exam papers is crucial for universities seeking institutional and program accreditation. Currently, exam papers are assessed manually, a process that can be tedious, lengthy, and in some cases, inconsistent. This is often due to the focus on assessing only the formal specifications of exam papers. This study…
Descriptors: Higher Education, Artificial Intelligence, Writing Evaluation, Natural Language Processing
Zaki, Nazar; Turaev, Sherzod; Shuaib, Khaled; Krishnan, Anusuya; Mohamed, Elfadil – Education and Information Technologies, 2023
Quality control and assurance plays a fundamental role within higher education contexts. One means by which quality control can be performed is by mapping the course learning outcomes (CLOs) to the program learning outcomes (PLO). This paper describes a system by which this mapping process can be automated and validated. The proposed AI-based…
Descriptors: Program Evaluation, Outcomes of Education, Natural Language Processing, Higher Education
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
Using GPT and Authentic Contextual Recognition to Generate Math Word Problems with Difficulty Levels
Wu-Yuin Hwang; Ika Qutsiati Utami – Education and Information Technologies, 2024
Automatic generation of math word problems (MWPs) is a challenging task in Natural Language Processing (NLP), particularly connecting it to real-life problems because it can benefit students in developing a higher level of mathematical thinking. However, most of the MWPs are presented within a scholastic setting in a decontextualized way. This…
Descriptors: Artificial Intelligence, Technology Uses in Education, Mathematics Education, Word Problems (Mathematics)
Wai Tong Chor; Kam Meng Goh; Li Li Lim; Kin Yun Lum; Tsung Heng Chiew – Education and Information Technologies, 2024
The programme outcomes are broad statements of knowledge, skills, and competencies that the students should be able to demonstrate upon graduation from a programme, while the Educational Taxonomy classifies learning objectives into different domains. The precise mapping of a course outcomes to the programme outcome and the educational taxonomy…
Descriptors: Artificial Intelligence, Engineering Education, Taxonomy, Educational Objectives