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Charalampos-S Charitsis – ProQuest LLC, 2023
The employment rate of software developers has risen significantly over the last 30 years. As a result, more students are considering computer science as a potential career path. Over the last 15 years, introductory programming course (CS1) enrollment has been increasing at a much faster rate than the increase in the number of CS faculty, with no…
Descriptors: Computer Science Education, Programming, Natural Language Processing, Computer Software
Peter Organisciak; Selcuk Acar; Denis Dumas; Kelly Berthiaume – Grantee Submission, 2023
Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…
Descriptors: Automation, Computer Assisted Testing, Scoring, Creative Thinking
Bogdan Nicula; Marilena Panaite; Tracy Arner; Renu Balyan; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2023
Self-explanation practice is an effective method to support students in better understanding complex texts. This study focuses on automatically assessing the comprehension strategies employed by readers while understanding STEM texts. Data from 3 datasets (N = 11,833) with self-explanations annotated on different comprehension strategies (i.e.,…
Descriptors: Reading Strategies, Reading Comprehension, Metacognition, STEM Education
David W. Brown; Dean Jensen – International Society for Technology, Education, and Science, 2023
The growth of Artificial Intelligence (AI) chatbots has created a great deal of discussion in the education community. While many have gravitated towards the ability of these bots to make learning more interactive, others have grave concerns that student created essays, long used as a means of assessing the subject comprehension of students, may…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Software, Writing (Composition)
Adam Keath; James Wyant; Brooke Towner – Journal of Physical Education, Recreation & Dance, 2024
AI tools can revolutionize physical education (PE) by assisting teachers in various ways, such as curriculum development, providing feedback, enhancing content knowledge and data analysis, and promoting student engagement. This article explores various ways in which PE teachers can utilize AI tools like ChatGPT to improve their instruction and…
Descriptors: Physical Education, Physical Education Teachers, Technology Uses in Education, Artificial Intelligence
William Cain – TechTrends: Linking Research and Practice to Improve Learning, 2024
This paper explores the transformative potential of Large Language Models Artificial Intelligence (LLM AI) in educational contexts, particularly focusing on the innovative practice of prompt engineering. Prompt engineering, characterized by three essential components of content knowledge, critical thinking, and iterative design, emerges as a key…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Prompting
Jacqueline Zammit – Technology in Language Teaching & Learning, 2024
The Chat Generative Pretrained Transformer (ChatGPT) is a state-of-the-art artificial intelligence (AI) language model developed by OpenAI. It employs advanced deep-learning algorithms to generate text that mimics human language. ChatGPT, launched on November 30, 2022, has rapidly gained widespread recognition. Its influence on the future of…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Second Language Learning
Yu Bai; Jun Li; Jun Shen; Liang Zhao – IEEE Transactions on Learning Technologies, 2024
The potential of artificial intelligence (AI) in transforming education has received considerable attention. This study aims to explore the potential of large language models (LLMs) in assisting students with studying and passing standardized exams, while many people think it is a hype situation. Using primary education as an example, this…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Andrew Williams – International Journal of Educational Technology in Higher Education, 2024
The value of generative AI tools in higher education has received considerable attention. Although there are many proponents of its value as a learning tool, many are concerned with the issues regarding academic integrity and its use by students to compose written assessments. This study evaluates and compares the output of three commonly used…
Descriptors: Content Area Writing, Artificial Intelligence, Writing Assignments, Biomedicine
Giovanni Zimotti; Claire Frances; Luke Whitaker – Technology in Language Teaching & Learning, 2024
This study explores the perceptions of second language (L2) educators on the surge of Large Language Models (LLMs) like ChatGPT, and their potential impact on language education. We surveyed over 100 L2 instructors, asking questions about their ideas for AI-proofing assignments, their policies, and their perceptions of how this tool will impact…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Second Language Instruction
Bima Sapkota; Liza Bondurant – International Journal of Technology in Education, 2024
In November 2022, ChatGPT, an Artificial Intelligence (AI) large language model (LLM) capable of generating human-like responses, was launched. ChatGPT has a variety of promising applications in education, such as using it as thought-partner in generating curricular resources. However, scholars also recognize that the use of ChatGPT raises…
Descriptors: Cognitive Processes, Difficulty Level, Artificial Intelligence, Natural Language Processing
Wai Tong Chor; Kam Meng Goh; Li Li Lim; Kin Yun Lum; Tsung Heng Chiew – Education and Information Technologies, 2024
The programme outcomes are broad statements of knowledge, skills, and competencies that the students should be able to demonstrate upon graduation from a programme, while the Educational Taxonomy classifies learning objectives into different domains. The precise mapping of a course outcomes to the programme outcome and the educational taxonomy…
Descriptors: Artificial Intelligence, Engineering Education, Taxonomy, Educational Objectives
Leila Mirzoyeva; Zhanna Makhanova; Mona Kamal Ibrahim; Zoya Snezhko – Cogent Education, 2024
The objective of this research is to investigate the effectiveness of integrating natural language processing (NLP) technologies into an English language learning program aimed at enhancing auditory and speaking competencies. The methodology of the research is grounded in the development and testing of the intervention effectiveness of neural…
Descriptors: Foreign Countries, Undergraduate Students, Language Skills, Auditory Training
Ferdiye Çobanogullari – The EUROCALL Review, 2024
This literature review delves into the applications and implications of ChatGPT, an artificial intelligence-driven chatbot, in educational settings. As technology continues to permeate the field of education, ongoing debates persist regarding the potential impact on learners' critical thinking skills and the evolving role of educators. Instead of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Educational Strategies
Xi Lin – Adult Learning, 2024
This study explores the potential of ChatGPT as a virtual tutor to facilitate self-directed learning (SDL) among adult learners in asynchronous online contexts. Although SDL has been identified as a critical skill, factors such as the lack of skills to find resources and the absence of a supportive learning environment could impede adult learners'…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Student Motivation