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Li Chen; Gen Li; Boxuan Ma; Cheng Tang; Masanori Yamada – International Association for Development of the Information Society, 2024
This paper proposes a three-step approach to develop knowledge graphs that integrate textbook-based target knowledge graph with student dialogue-based knowledge graphs. The study was conducted in seventh-grade STEM classes, following a collaborative problem solving process. First, the proposed approach generates a comprehensive target knowledge…
Descriptors: Concept Mapping, Graphs, Cooperative Learning, Problem Solving
Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Attention, Natural Language Processing

Yang Zhong; Mohamed Elaraby; Diane Litman; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2024
This paper introduces REFLECTSUMM, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of REFLECTSUMM is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization…
Descriptors: Documentation, Writing (Composition), Reflection, Metadata
Claudio-Rafael Vasquez-Martinez; Francisco Flores-Cuevas; Felipe-Anastacio Gonzalez-Gonzalez; Luz-Maria Zuniga-Medina; Graciela-Esperanza Giron-Villacis; Irma-Carolina Gonzalez-Sanchez; Joaquin Torres-Mata – Bulgarian Comparative Education Society, 2024
Language is the basis of human communication and is the most important key to complete mental development and thinking. Therefore, children must learn to communicate using appropriate language. For this to happen, the development of language in the child must be understood as a biological process, complete with internal laws and with marked stages…
Descriptors: Infants, Morphology (Languages), Syntax, Phonology
John Y. H. Bai; Olaf Zawacki-Richter; Wolfgang Muskens – Turkish Online Journal of Distance Education, 2024
Artificial intelligence in education (AIEd) is a fast-growing field of research. In previous work, we described efforts to explore the possible futures of AIEd by identifying key variables and their future prospects. This paper re-examines our discussions on the governance of data and the role of students and teachers by considering the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Governance
Tianyuan Yang; Baofeng Ren; Chenghao Gu; Boxuan Ma; Shin 'ichi Konomi – International Association for Development of the Information Society, 2024
As education increasingly shifts towards a technology-driven model, artificial intelligence systems like ChatGPT are gaining recognition for their potential to enhance educational support. In university education and MOOC environments, students often select courses that align with their specific needs. During this process, access to information…
Descriptors: Concept Formation, Artificial Intelligence, Computer Uses in Education, MOOCs
Ryusei Munemura; Fumiya Okubo; Tsubasa Minematsu; Yuta Taniguchi; Atsushi Shimada – International Association for Development of the Information Society, 2024
Course planning is essential for academic success and the achievement of personal goals. Although universities provide course syllabi and curriculum maps for course planning, integrating and understanding these resources by the learners themselves for effective course planning is time-consuming and difficult. To address this issue, this study…
Descriptors: Curriculum Development, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Maria Goldshtein; Jaclyn Ocumpaugh; Andrew Potter; Rod D. Roscoe – Grantee Submission, 2024
As language technologies have become more sophisticated and prevalent, there have been increasing concerns about bias in natural language processing (NLP). Such work often focuses on the effects of bias instead of sources. In contrast, this paper discusses how normative language assumptions and ideologies influence a range of automated language…
Descriptors: Language Attitudes, Computational Linguistics, Computer Software, Natural Language Processing
Danijela Blanuša Trošelj; Sven Maricic; Antonia Curic – International Society for Technology, Education, and Science, 2024
Although AI in education has been written about for decades, recent years have seen exponential growth in this area. The aim of this paper was to determine the distribution of content and areas of education in which AI is researched. The article provides an overview of the newest research in the field of AI in education, available in open access…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Research, Definitions

Ha Tien Nguyen; Conrad Borchers; Meng Xia; Vincent Aleven – Grantee Submission, 2024
Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…
Descriptors: Middle School Mathematics, Intelligent Tutoring Systems, Caregivers, Caregiver Attitudes

Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Pedro Isaias; Tania Hoque; Paula Miranda – International Association for Development of the Information Society, 2024
While the higher education sector is continuously searching for innovative technologies, the use of chatbots requires extensive research and careful consideration of their pedagogical value. The lessons learned from lecturers who experiment with chatbots can constitute important evidence to support their use. This paper presents a chatbot…
Descriptors: Instructional Material Evaluation, Artificial Intelligence, Technology Uses in Education, Natural Language Processing

Sami Baral; Li Lucy; Ryan Knight; Alice Ng; Luca Soldaini; Neil T. Heffernan; Kyle Lo – Grantee Submission, 2024
In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…
Descriptors: Visual Learning, Visual Perception, Natural Language Processing, Freehand Drawing
Yandres Answo Djedelbert Lao; Sukardi Weda; Muhammad Basri – International Society for Technology, Education, and Science, 2024
First language (L1) has been an affecting factor in learning English as a foreign language (EFL) that causes negative transfer including in thesis writing. The effect can be observed by looking at English productive skills, more specifically written form, as well as thesis writing. This research investigated how L1 interfered student's English…
Descriptors: Translation, Psycholinguistics, Brain Hemisphere Functions, English (Second Language)