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Direct linkAditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
Matt Bower; Jodie Torrington; Jennifer W. M. Lai; Peter Petocz; Mark Alfano – Education and Information Technologies, 2024
There has been widespread media commentary about the potential impact of generative Artificial Intelligence (AI) such as ChatGPT on the Education field, but little examination at scale of how educators believe teaching and assessment should change as a result of generative AI. This mixed methods study examines the views of educators (n = 318) from…
Descriptors: Artificial Intelligence, Teacher Evaluation, Surveys, Computer Assisted Testing
Lei Jiang; Na Yu – Education and Information Technologies, 2024
This research aims to address the challenges of digital transformation in education by understanding the digital competence of teachers through a mixed-methods approach. The grounded theory is employed to develop the Teachers' Digital Competence Model (TDCM), which is structured around three facets: development, pedagogy, and ethics. Within these…
Descriptors: Educational Technology, Teacher Competencies, Technological Literacy, Ethics
