While AI has the potential to streamline assessment development in higher education, there are concerns about its reliability, fairness, and potential to perpetuate bias. This study sought to understand the perceptions of academics and teaching and learning (T&L) specialists on the use of AI tools and large language models on assessment…

The development of explanations for scientific phenomena is crucial in science assessment. However, the scoring of students' written explanations is a challenging and resource-intensive process. Large language models (LLMs) have demonstrated the potential to address these challenges, particularly when the explanations are written in English, an…

Artificial intelligence (AI), as an emerging technology, has been widely used in STEM education to promote the educational assessment. Although AI-driven educational assessment has the potential to assess students' learning automatically and reduce the workload of instructors, there is still a lack of review works to holistically examine the field…

The abrupt emergence and rapid advancement of generative artificial intelligence (AI) technologies, transitioning from research labs to potentially all aspects of social life, has brought a profound impact on education, science, arts, journalism, and every facet of human life and communication. The purpose of this paper is to recapitulate the use…

Background: The increasing capabilities of generative artificial intelligence (AI), exemplified by OpenAI's transformer-based language model GPT-4 (ChatGPT), have drawn attention to its application in educational contexts. This study evaluates the potential of such models in generating German reading comprehension texts for educational large-scale…

The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…

Generative AI has the potential to transform higher education assessment. This study examines the opportunities and challenges of integrating AI into coursework assessments, highlighting the need to rethink traditional paradigms. A case study is presented that explores AI as an auxiliary learning tool in postgraduate coursework. Students found AI…

This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less…

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…