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Direct linkHyangeun Ji; Insook Han; Soyeon Park – Language Learning & Technology, 2024
This study investigated the usage of conversational artificial intelligence (CAI) to support learners in foreign language classrooms. It employed Google Assistant and focused on the interactions between the teacher, learners, and CAI, as well as the teacher's collaboration with CAI. Using social network and content analyses of two 50-minute…
Descriptors: Second Language Learning, Artificial Intelligence, Computer Mediated Communication, Natural Language Processing
Quan Yang; Huajian Xin; Xuehua Ji; Fae Mai – International Journal of Web-Based Learning and Teaching Technologies, 2024
This article analyses the significance of ideological and political education for college students in Tibet and proposes a natural language model for an ideological education curriculum to improve the accuracy of students' document search. The segmentation results are optimized to enhance literature search accuracy, promoting the development of…
Descriptors: Universities, Geographic Regions, Educational Change, Educational Innovation
Download full textBilal Khallel Younis – Online Learning, 2024
This study aims to investigate students' self-regulation skills, confidence to learn online, and perception of satisfaction and usefulness of online classes in three learning environments that integrates ChatGPT. In this study, a quasi-experiential design was used to compare three online learning environments that integrate ChatGPT (independent,…
Descriptors: Self Management, Self Esteem, Electronic Learning, Student Attitudes
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
Bozkurt, Aras; Xiao, Junhong; Lambert, Sarah; Pazurek, Angelica; Crompton, Helen; Koseoglu, Suzan; Farrow, Robert; Bond, Melissa; Nerantzi, Chrissi; Honeychurch, Sarah; Bali, Maha; Dron, Jon; Mir, Kamran; Stewart, Bonnie; Costello, Eamon; Mason, Jon; Stracke, Christian M.; Romero-Hall, Enilda; Koutropoulos, Apostolos; Toquero, Cathy Mae; Singh, Lenandlar; Tlili, Ahmed; Lee, Kyungmee; Nichols, Mark; Ossiannilsson, Ebba; Brown, Mark; Irvine, Valerie; Raffaghelli, Juliana Elisa; Santos-Hermosa, Gema; Farrell, Orna; Adam, Taskeen; Thong, Ying Li; Sani-Bozkurt, Sunagul; Sharma, Ramesh C.; Hrastinski, Stefan; Jandric, Petar – Asian Journal of Distance Education, 2023
While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are…
Descriptors: Artificial Intelligence, Technology Uses in Education, Affordances, Teacher Role
Zuzana Suchánová – International Society for Technology, Education, and Science, 2023
The expanding domain of Artificial Intelligence (AI) offers a diverse array of educational applications and tools. However, the scholarly exploration of AI's suitability for enhancing English as a Foreign Language (EFL) instruction at the university level remains notably limited. This research gap impedes educators from fully harnessing AI's…
Descriptors: Artificial Intelligence, Preservice Teachers, English (Second Language), Second Language Instruction
Wang, Qianying; Liao, Jing; Lapata, Mirella; Macleod, Malcolm – Research Synthesis Methods, 2022
We sought to apply natural language processing to the task of automatic risk of bias assessment in preclinical literature, which could speed the process of systematic review, provide information to guide research improvement activity, and support translation from preclinical to clinical research. We use 7840 full-text publications describing…
Descriptors: Risk, Natural Language Processing, Medical Research, Networks
Jia, Qinjin; Young, Mitchell; Xiao, Yunkai; Cui, Jialin; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2022
Providing timely feedback is crucial in promoting academic achievement and student success. However, for multifarious reasons (e.g., limited teaching resources), feedback often arrives too late for learners to act on the feedback and improve learning. Thus, automated feedback systems have emerged to tackle educational tasks in various domains,…
Descriptors: Student Projects, Feedback (Response), Natural Language Processing, Guidelines
Weinstein, Theresa J.; Ceh, Simon Majed; Meinel, Christoph; Benedek, Mathias – Creativity Research Journal, 2022
Evaluating creativity of verbal responses or texts is a challenging task due to psychometric issues associated with subjective ratings and the peculiarities of textual data. We explore an approach to objectively assess the creativity of responses in a sentence generation task to (1) better understand what language-related aspects are valued by…
Descriptors: Creativity, Sentences, Natural Language Processing, Computation
Bóbó, Míria L. D. R.; Campos, Fernanda; Stroele, Victor; David, José Maria N.; Braga, Regina; Torrent, Tiago Timponi – International Journal of Distance Education Technologies, 2022
Dropping out of school comes from a long-term disengagement process with social and economic consequences. Being able to predict students' behavior earlier can minimize their failures and disengagement. This article presents the SASys architecture based on a lexical approach and a polarized frame network. Its main goal is to define the author's…
Descriptors: Dropout Prevention, Psychological Patterns, Learner Engagement, Electronic Learning
Bonikowski, Bart; Luo, Yuchen; Stuhler, Oscar – Sociological Methods & Research, 2022
Radical-right campaigns commonly employ three discursive elements: anti-elite populism, exclusionary and declinist nationalism, and authoritarianism. Recent scholarship has explored whether these frames have diffused from radical-right to centrist parties in the latter's effort to compete for the former's voters. This study instead investigates…
Descriptors: Political Attitudes, Nationalism, Authoritarianism, Voting
Boon, Ian Gregory – ProQuest LLC, 2022
It is standardly believed that some occurrences of expressions designate singularly, while other occurrences of expressions designate plurally. For instance, the singular expression the student may be used on an occasion to talk about one particular student, while the plural expression the students may be used on an occasion to talk about several…
Descriptors: Grammar, Morphemes, Language Usage, Essays
Alex Warstadt – ProQuest LLC, 2022
Data-driven learning uncontroversially plays a role in human language acquisition--how large a role is a matter of much debate. The success of artificial neural networks in NLP in recent years calls for a re-evaluation of our understanding of the possibilities for learning grammar from data alone. This dissertation argues the case for using…
Descriptors: Language Acquisition, Artificial Intelligence, Computational Linguistics, Ethics
Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
