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Direct linkAtharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
Mengfei Zhao; Dongjie Jiang; Jun Wang – Cognitive Science, 2025
Previous research suggests that statistical learning enhances memory for self-related information at the individual level and that individuals exhibit better memory for partner-related items than they do for irrelevant items in joint contexts (i.e., the joint memory effect, JME). However, whether statistical learning improves memory for…
Descriptors: Memory, Task Analysis, Classification, Chinese
Suping Yi; Wayan Sintawati; Yibing Zhang – Journal of Computer Assisted Learning, 2025
Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…
Descriptors: Reflection, Feedback (Response), Cooperative Learning, Natural Language Processing
Torres-Jimenez, Jose; Lescano, Germán; Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo – Education and Information Technologies, 2023
Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…
Descriptors: Conflict, Identification, Computer Assisted Instruction, Cooperative Learning
Pablo Flores Romero; Kin Nok Nicholas Fung; Guang Rong; Benjamin Ultan Cowley – npj Science of Learning, 2025
Large Language Models (LLMs) present a radically new paradigm for the study of "information foraging behavior." We study how LLM technology is used for pedagogical content creation by a sample of 25 participants in a doctoral-level Artificial Intelligence (AI) in Education course, and the role of computational-thinking skills in shaping…
Descriptors: Man Machine Systems, Artificial Intelligence, Natural Language Processing, Interaction
Chia-Ju Lin; Wei-Sheng Wang; Hsin-Yu Lee; Yueh-Min Huang; Ting-Ting Wu – Journal of Educational Computing Research, 2025
This study uses a quasi-experimental design to explore the role of natural language processing (NLP) and speech recognition technologies in supporting teacher interventions during collaborative STEM activities. The Speech Recognition Keywords Analysis System (SRKAS) was developed to extract keywords from student discussions, enabling real-time…
Descriptors: Natural Language Processing, Computational Linguistics, Technology Uses in Education, STEM Education
Scott Aubrey; Andrew Philpott – Language Teaching Research, 2025
This study examined the impact of collaborative pre-task strategic planning followed by rehearsal on the quantity and novelty of content used in task performances when strategic planning is performed in different language conditions in an online classroom. Forty Japanese university students of English as a foreign language (EFL) from two intact…
Descriptors: Online Courses, Language Usage, Native Language, Second Language Learning
Download full textJay Fie Paler Luzano – International Journal of Technology in Education, 2025
Integrating artificial intelligence (AI) technologies into various educational domains has garnered significant attention. Among these technologies, ChatGPT stands out as a powerful tool that holds the potential to revolutionize the landscape of mathematics education. This study aims to explore the emerging trends and critical issues surrounding…
Descriptors: Mathematics Education, Educational Trends, Artificial Intelligence, Technology Uses in Education
Lee McCallum – Journal for Multicultural Education, 2024
Purpose: This paper aims to present a lesson that showcases how artificial intelligence (AI) tools may be chiefly used in L2 language classrooms to design culture-focussed telecollaboration tasks and aid their completion by students. Design/methodology/approach: The paper begins by reviewing traditional approaches and guidance for developing…
Descriptors: Artificial Intelligence, Intercultural Communication, Second Language Learning, Telecommunications
Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
Colin Green; Eric Brewe; Jillian Mellen; Adrienne Traxler; Sarah Scanlin – Physical Review Physics Education Research, 2024
This project aims to understand physics faculty responses to transitioning to online teaching during the COVID-19 pandemic. We surveyed 662 physics faculty from the United States following the Spring 2020 term; of these, 258 completed a follow-up survey after the Fall 2020 term. We used natural language processing to measure the sentiment scores…
Descriptors: Teacher Attitudes, Online Courses, Physics, Science Instruction
Rui Du; Heidi Salaets – Interpreter and Translator Trainer, 2025
Over the past two decades, there has been a surge in empirical research examining collaborative learning (CL) within translator and interpreter training contexts, with a particular emphasis on elucidating the perceptions and experiences of participants. In the present study, we explored qualitative studies on this topic through a meta-study…
Descriptors: Translation, Cooperative Learning, Teaching Methods, Second Languages
Yang, Jing – Journal of Advertising Education, 2023
With artificial intelligence (AI) technologies making significant evolutions over the past few years, there is a growing need for advertising students to get familiarized with the different types of AI technologies and explore and experiment with ways to adapt to such changes. This article illustrates the development and implementation of the…
Descriptors: Advertising, Professional Education, Merchandise Information, Course Descriptions
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
Haering, Marlo; Bano, Muneera; Zowghi, Didar; Kearney, Matthew; Maalej, Walid – IEEE Transactions on Learning Technologies, 2021
With the vast number of apps and the complexity of their features, it is becoming challenging for teachers to select a suitable learning app for their courses. Several evaluation frameworks have been proposed in the literature to assist teachers with this selection. The iPAC framework is a well-established mobile learning framework highlighting…
Descriptors: Automation, Courseware, Computer Software Evaluation, Computer Software Selection
