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Letty Rising – Montessori Life: A Publication of the American Montessori Society, 2024
In the ever-evolving landscape of education, you have most likely experienced a significant expansion in your teaching responsibilities. Your role may have stretched to encompass being proficient in various technology platforms, nurturing the social and emotional learning of your students, and adjusting to amplified documentation requirements.…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Bihao Hu; Longwei Zheng; Jiayi Zhu; Lishan Ding; Yilei Wang; Xiaoqing Gu – IEEE Transactions on Learning Technologies, 2024
This study explores and analyzes the specific performance of large language models (LLMs) in instructional design, aiming to unveil their potential strengths and possible weaknesses. Recently, the influence of LLMs has gradually increased in multiple fields, yet exploratory research on their application in education remains relatively scarce. In…
Descriptors: Artificial Intelligence, Natural Language Processing, Instructional Design, Prompting
Leung, Javier; Abramenka-Lachheb, Victoria; Sankaranarayanan, Rajagopal; Lachheb, Ahmed; Seo, Grace – TechTrends: Linking Research and Practice to Improve Learning, 2023
The purpose of this follow-up study was to investigate further the expressed needs of Instructional Designers (IDers) from a large public Facebook group. Our previous original research (Abramenka-Lachheb et al., 2021a) reported that IDers expressed needs during the pandemic in several categories, including: (1) educational technology, (2)…
Descriptors: COVID-19, Pandemics, Instructional Design, Natural Language Processing
Jinhee Kim; Seongryeong Yu; Rita Detrick; Na Li – Education and Information Technologies, 2025
The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within…
Descriptors: Student Attitudes, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Katarína Žáková; Diana Urbano; Ricardo Cruz-Correia; José Luis Guzmán; Jakub Matišák – Education and Information Technologies, 2025
Understanding how students interact with AI bots is a first step towards integrating them into instructional design. In this report, the results of a survey conducted in three European higher education institutions, and in the context of four different areas are presented. Among other things, they reveal for what purposes students use ChatGPT,…
Descriptors: Student Attitudes, Teacher Attitudes, Artificial Intelligence, Natural Language Processing
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
Javier Leung – Quarterly Review of Distance Education, 2023
This research brief comprises three articles published in the three-article dissertation at the University of Missouri (MU) in February 2023. The three-article dissertation, "An Exploration of Online Information Spaces That Support Instructional Design and Teacher Professional Development," examined three online communities of practice…
Descriptors: Communities of Practice, Instructional Design, Faculty Development, Educational Technology
Lippert, Anne; Shubeck, Keith; Morgan, Brent; Hampton, Andrew; Graesser, Arthur – Technology, Knowledge and Learning, 2020
This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Natural Language Processing, Educational Technology
Lippert, Anne; Shubeck, Keith; Morgan, Brent; Hampton, Andrew; Graesser, Arthur – Grantee Submission, 2020
This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Natural Language Processing, Educational Technology
Sheri Conklin; Tom Dorgan; Daisyane Barreto – Discover Education, 2024
We investigated the utility of ChatGPT 3.5 in the creation of a fully online asynchronous higher education course. Our collaborative effort with ChatGPT resulted in developing a Master's level course on Trends and Issues in Instructional Design using the Backward Design Model. Throughout this process, we recognized the critical role of precise…
Descriptors: Design, Technology Uses in Education, Artificial Intelligence, Instructional Design
Afzal, Shazia; Dempsey, Bryan; D'Helon, Cassius; Mukhi, Nirmal; Pribic, Milena; Sickler, Aaron; Strong, Peggy; Vanchiswar, Mira; Wilde, Lorin – Childhood Education, 2019
As artificially intelligent systems make their foray into the day-to-day educational experiences of students, we need to pay careful attention to the relationship between the system and the student. In this article, the authors discuss designing the personality of a virtual tutoring system called IBM Watson Tutor. The AI personality is key to the…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Instructional Design, Learner Engagement
Feng, Shihui; Law, Nancy – International Journal of Artificial Intelligence in Education, 2021
In this study, we review 1830 research articles on artificial intelligence in education (AIED), with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary research field from 2010 to 2019. A novel three-step approach in the analysis of the keyword co-occurrence networks (KCN) is proposed to identify the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Research, Intelligent Tutoring Systems
Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh – TechTrends: Linking Research and Practice to Improve Learning, 2017
With augmented intelligence/knowledge based system (KBS) it is now possible to develop distance learning applications to support both curriculum and administrative tasks. Instructional designers and information technology (IT) professionals are now moving from the programmable systems era that started in the 1950s to the cognitive computing era.…
Descriptors: Artificial Intelligence, Information Technology, Distance Education, Instructional Design
Graesser, Arthur C.; Forsyth, Carol M.; Lehman, Blair A. – Grantee Submission, 2017
Background: Pedagogical agents are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with the students in natural language. Dialogues occur between a tutor agent and the student in the case of AutoTutor and other intelligent tutoring systems with natural language…
Descriptors: Intelligent Tutoring Systems, Computer Managed Instruction, Natural Language Processing, Instructional Design
McNamara, Danielle S.; Jacovina, Matthew E.; Snow, Erica L.; Allen, Laura K. – Grantee Submission, 2015
Work in cognitive and educational psychology examines a variety of phenomena related to the learning and retrieval of information. Indeed, Alice Healy, our honoree, and her colleagues have conducted a large body of groundbreaking research on this topic. In this article we discuss how 3 learning principles (the generation effect, deliberate…
Descriptors: Learning Processes, Instructional Design, Intelligent Tutoring Systems, Writing Instruction