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Haug, Tobias; Mann, Wolfgang; Holzknecht, Franz – Sign Language Studies, 2023
This study is a follow-up to previous research conducted in 2012 on computer-assisted language testing (CALT) that applied a survey approach to investigate the use of technology in sign language testing worldwide. The goal of the current study was to replicate the 2012 study and to obtain updated information on the use of technology in sign…
Descriptors: Computer Assisted Testing, Sign Language, Natural Language Processing, Language Tests
Valentina Albano; Donatella Firmani; Luigi Laura; Jerin George Mathew; Anna Lucia Paoletti; Irene Torrente – Journal of Learning Analytics, 2023
Multiple-choice questions (MCQs) are widely used in educational assessments and professional certification exams. Managing large repositories of MCQs, however, poses several challenges due to the high volume of questions and the need to maintain their quality and relevance over time. One of these challenges is the presence of questions that…
Descriptors: Natural Language Processing, Multiple Choice Tests, Test Items, Item Analysis
Shuqiong Luo; Di Zou – European Journal of Education, 2025
Recent AI-based language learning research highlights learners' crucial role, yet university learner readiness in ChatGPT-based English learning remains unexplored. Accordingly, this current research attempted to develop and validate a tool to evaluate university learner readiness for ChatGPT-assisted English learning (LRCEL) to address the…
Descriptors: College Students, Readiness, Artificial Intelligence, Natural Language Processing
Shin, Jinnie; Gierl, Mark J. – International Journal of Testing, 2022
Over the last five years, tremendous strides have been made in advancing the AIG methodology required to produce items in diverse content areas. However, the one content area where enormous problems remain unsolved is language arts, generally, and reading comprehension, more specifically. While reading comprehension test items can be created using…
Descriptors: Reading Comprehension, Test Construction, Test Items, Natural Language Processing
Naveed Saif; Sadaqat Ali; Abner Rubin; Soliman Aljarboa; Nabil Sharaf Almalki; Mrim M. Alnfiai; Faheem Khan; Sajid Ullah Khan – Educational Technology & Society, 2025
In the swiftly evolving landscape of education, the fusion of Artificial Intelligence's ingenuity with the dynamic capabilities of chat-bot technology has ignited a transformative paradigm shift. This convergence is not merely a technological integration but a profound reshaping of the fundamental principles of pedagogy, fundamentally redefining…
Descriptors: Artificial Intelligence, Technology Uses in Education, Readiness, Technological Literacy
Carmen Köhler; Johannes Hartig – Contemporary Educational Technology, 2024
Since ChatGPT-3.5 has been available to the public, the potentials and challenges regarding chatbot usage in education have been widely discussed. However, little evidence exists whether and for which purposes students even apply generative AI tools. The first main purpose of the present study was to develop and test scales that assess students'…
Descriptors: Artificial Intelligence, College Students, Natural Language Processing, Technology Uses in Education
Yu, Xiaoli – International Journal of Language Testing, 2021
This study examined the development of text complexity for the past 25 years of reading comprehension passages in the National Matriculation English Test (NMET) in China. Text complexity of 206 reading passages at lexical, syntactic, and discourse levels has been measured longitudinally and compared across the years. The natural language…
Descriptors: Reading Comprehension, Reading Tests, Difficulty Level, Natural Language Processing
Aldabe, Itziar; Maritxalar, Montse – IEEE Transactions on Learning Technologies, 2014
The work we present in this paper aims to help teachers create multiple-choice science tests. We focus on a scientific vocabulary-learning scenario taking place in a Basque-language educational environment. In this particular scenario, we explore the option of automatically generating Multiple-Choice Questions (MCQ) by means of Natural Language…
Descriptors: Science Tests, Test Construction, Computer Assisted Testing, Multiple Choice Tests
Liu, Chao-Lin; Lin, Jen-Hsiang; Wang, Yu-Chun – Online Submission, 2010
The authors report an implemented environment for computer-assisted authoring of test items and provide a brief discussion about the applications of NLP techniques for computer assisted language learning. Test items can serve as a tool for language learners to examine their competence in the target language. The authors apply techniques for…
Descriptors: Cloze Procedure, Listening Comprehension, Test Items, Foreign Countries