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The Automatic Translation of Arabic Psychological Verbs Using the NooJ Platform 1

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17th International Conference on Automatic Processing of Natural-Language Electronic Texts with NooJ (NooJ)

作者： Amzali, Asmaa Mourchid, Mohammed Ibn Tofail Univ Sci Res Lab Fac Sci Kenitra Morocco

ISBN: (数字)9783031566462

ISBN: (纸本)9783031566455;9783031566462

In this paper, we are going to conduct a comprehensive study of the inflectional morphology of psychological verbs in both English and Arabic. The focus is also on clarifying the points of convergence and divergence between the inflectional systems of both languages. Moreover, we propose a methodology to develop an Arabic psychological verb translator. Then, we created an automatic translation system based on a carefully curated dictionary containing approximately 400 verb entries. Those entries were generated from our lexicon-grammar table of Arabic psychological verbs. Finally, we finish by testing the efficiency of this translator on texts and corpora.

关键词： Natural Language Processing NooJ Arabic Psychological Verbs Automatic Translation

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Large Language Models for Career Readiness Prediction 25th

Large Language Models for Career Readiness Prediction

引用

25th International Conference on Artificial Intelligence in Education (AIED)

作者： Cui, Chenwei Abdalla, Amro Wijaya, Derry Solberg, Scott Bargal, Sarah Adel Boston Univ Boston MA 02215 USA Georgetown Univ Washington DC USA Arizona State Univ Tempe AZ 85287 USA

ISBN: (纸本)9783031643149;9783031643156

Large Language Models (LLMs) have recently achieved state-of-the-art performance on many benchmark Natural Language Processing (NLP) tasks. In this work, we are introducing a novel application, career readiness prediction, in the area of NLP for education. We analyze a dataset of student narratives and explore how reliably different LLMs classify them using Marcia's (1980) identity statuses. We explore the capabilities and limitations of LLMs on this new task and find that there is good potential for automated career readiness evaluation, and for improved survey design that enables larger-scale data collection.

关键词： Large Language Models Career Readiness Prediction Natural Language Processing Classification GPT

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Video Games and Adaptation: An Introduction 1

引用

13th International Conference on Videogame sciences and Arts (VJ)

作者： Ristic, Tatjana Kubik, Darjan Univ Belgrade Fac Philol Studentski Trg 3 Belgrade Serbia

ISBN: (数字)9783031514524

ISBN: (纸本)9783031514517;9783031514524

The main idea of the paper is to analyse the relation of video games and adaptation both synchronically and diachronically. The synchronic aspect of the paper builds on contemporary academic insights while the diachronic one is founded in the gaming industry itself. In the first part, we outline a theoretical framework which is mainly derived from Linda Hutcheon's idea of adaptation as re-mediation between three modes of engagement: the telling, showing and participatory mode. Her insights are then compounded with contemporary video game studies in order to shed a light on the unique features of video games as a medium and how other media are transcoded into and from the semiotic sign system constituted in these features. In the second part, we analyse examples from crucial periods of video game history. These include the badly received E.T. and Cyberpunk 2077, and influential video game series such as Warcraft, The Witcher and Halo. By looking into video games that chart all possible relations the participatory mode has with those of showing and telling, we wish to open up case-study examinations into the field of video game adaptation. The goal of the paper is therefore not to offer a comprehensive guide to the theory or history of video game adaptation but rather an overview meant to direct researchers toward possible and highly required further work in the field.

关键词： Video Games Adaptation Transmediality Media Convergence

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Can Generative AI Improve the Standardisation of Student Feedback Across a Business School Faculty? 12th

Can Generative AI Improve the Standardisation of Student Fee...

引用

12th International Conference on Learning Technology for Education Challenges (LTEC)

作者： Holdcroft, Craig Sch Digital Technol Innovat & Business Catalyst BldgLeek Rd Stoke On Trent ST4 2DF Staffs England

ISBN: (纸本)9783031616778;9783031616785

The aim of this research is to investigate the faculty's current digital capabilities and openness to using AI for enhancing feedback standardisation across academic disciplines. The research assesses the faculty's digital literacy, behaviours, and initial perceptions of generative AI. Questionnaires were employed at different stages: before and after an informative presentation on the proposed AI methodology. Findings suggest that while there is a general openness to integrating AI in educational feedback, complexities related to digital literacy, technology adoption, and perceptions of AI must be carefully navigated. This study contributes to understanding the preconditions for successful AI adoption in education, pointing towards the need for enhanced digital literacy and supportive frameworks that facilitate technological innovation while respecting the unique contributions of human educators. Future research will focus on developing strategies to bridge the digital capability gap and fully realise the potential of generative AI in standardising student feedback, thus aligning pedagogical practices with the evolving digital landscape in higher education.

关键词： Open AI ChatGPT Standardising student feedback Digital literacy Change theory

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Towards a Linguistic Annotation of Arabic Legal Texts: A Multilingual Electronic Dictionary for Arabic 1

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17th International Conference on Automatic Processing of Natural-Language Electronic Texts with NooJ (NooJ)

作者： ElFqih, Khadija Ait Di Buono, Maria Pia Monti, Johanna Univ Naples Lorientale UNIOR NLP Res Grp Naples Italy

ISBN: (数字)9783031566462

ISBN: (纸本)9783031566455;9783031566462

Terminology translation plays a significant role in domain-specific machine translation. However, some knowledge domains and languages still suffer from the lack of high-quality machine translation results due to the mistranslation of terminology. This is the case in the legal domain and the Arabic language. Most machine translation systems fail in their results to produce the exact equivalence of most legal terms for Arabic into other languages, mainly English and French. This failure highlights the lack of terminology resources related to the legal domain, the unfamiliarity of the legal systems to render the appropriate equivalences and the terminology linguistic characteristics of this type of discourse. This difficulty recalls the need for more legal terminology resources. In fact, even though there are many Arabic legal dictionaries, most of them are not machine-readable, and cannot be used in machine translation or other Natural Language Processing applications. As a pipeline, we first extract our terms using NooJ grammars, and then proceed with the creation of our dictionary using NooJ morpho-syntactic information (part of speech (POS), gender, number, etc.), syntactic information (transitive, intransitive, Naqis, etc.), and the creation of our semantic tags that describe our domain-knowledge terms including legal, Juri-religion, etc., and geoUsage to indicate where a given term is adapted to express a legal practice. Finally, we propose the translation. In this phase, the process relies on consulting many sources, including EUR-Lex, EuroVoc and IATE, to be then validated by our legal expert. Our electronic dictionary should enable the automatic annotation of the majority of legal documents in Arabic.

关键词： Legal Terminology Resources Multilingualism Arabic Legal Dictionary Machine Translation NooJ

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Effects of Generative Artificial Intelligence on Instructional Design Outcomes and the Mediating Role of Pre-service Teachers' Prior Knowledge of Different Types of Instructional Design Tasks 25th

Effects of Generative Artificial Intelligence on Instruction...

引用

25th International Conference on Artificial Intelligence in Education (AIED)

作者： Krushinskaia, Kristina Elen, Jan Raes, Annelies Katholieke Univ Leuven Ctr Instruct Psychol & Technol Leuven Belgium

ISBN: (纸本)9783031643118;9783031643125

Generative artificial intelligence (GenAI) is increasingly becoming a tool used in many spheres, including education. A key question is whether GenAI can support teachers in one of their major roles: designing learning environments. This research aims to bridge the gap in understanding how different types of GenAI use impact instructional design outcomes. To achieve this, the study design includes three experimental conditions: 1) with GenAI, 2) with a GenAI bot pre-trained as a co-instructional designer, 3) automated by GenAI and one control condition (no use of GenAI). Participants, who are pre-service teachers, are tasked with designing a lesson blueprint and developing a lesson plan. The quality of instructional design outcomes and any common patterns across conditions are evaluated. Moreover, the impact of teachers' interactions with GenAI on the instructional design outcomes is analyzed. Additionally, the study aims to reveal a relationship between participants' prior familiarity with instructional design tasks and the way they design instruction with and without different uses of GenAI. This research study is crucial for exploring GenAI's potential to become a valuable partner for teachers in co-designing instruction and providing students with better learning opportunities.

关键词： Generative AI GenAI Artificial intelligence Instructional design Lesson planning Design for learning

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DQD: The Data Quality Definition Ontology 17th

DQD: The Data Quality Definition Ontology

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17th Research Conference on Metadata and Semantic Research (MTSR)

作者： Schrott, Johannes Meindl, Rainer Lettner, Christian Woess, Wolfram Ehrlinger, Lisa Software Competence Ctr Hagenberg GmbH Hagenberg Austria Johannes Kepler Univ Linz Linz Austria

ISBN: (纸本)9783031659898;9783031659904

Data quality measurement is a prerequisite to assure and improve the quality of data, thus enabling reliable decision-making. In alignment with the "fitness for use" definition, most existing solutions for measuring data quality are either (1) tailored to a specific use case and cannot be easily reused, or (2) too general, i.e., they do not provide specific metrics and require a high level of user involvement to be implemented. To address this research gap, we developed the Data Quality Definition (DQD) ontology, which is based on semantic web standards and provides a framework on how to define data quality metrics. DQD is intended to be used as input for data quality measurement tools and enables reusing domain knowledge defined in external sources (e.g., ontologies). Using DQD allows comparing data quality measurement results between different tools, use cases, data assets, and over time. In this paper, we introduce the structure of DQD and show its applicability with an example.

关键词： Data quality Ontology Application profile

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Gendered Responses to AI Governance: Insights from a Quantitative National Survey on ChatGPT Usage Among Students and Educators 25th

Gendered Responses to AI Governance: Insights from a Quantit...

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25th International Conference on Artificial Intelligence in Education (AIED)

作者： Qasserras, Lahcen Univ North Carolina Charlotte Charlotte NC 28223 USA

ISBN: (纸本)9783031643149;9783031643156

This study employs quantitative analysis to investigate how gender differences and educational policies influence students' and educators' willingness to engage with ChatGPT in the face of potential restrictions. Leveraging data from a national survey, which saw participation from 1,500 respondents across the United States, this research offers insights from a varied group encompassing both students and educators, thus ensuring a broad perspective on the subject. The findings reveal significant gender disparities in the inclination to use ChatGPT if it were banned, emphasizing the considerable impact of school policies. Critical Race Structuralism (CRS) was employed as a theoretical lens to delve deeper into these findings.

关键词： Artificial Intelligence Education ChatGPT Gender Policy

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Math-Masters: An Educational Game to Practice the Mathematical Operations 1

引用

13th International Conference on Videogame sciences and Arts (VJ)

作者： Marques, Joao A. B. T. Ferreira, Joao L. A. P. Silva, Frutuoso G. M. Univ Beira Interior Covilha Portugal Inst Telecomunicacoes Covilha Portugal

ISBN: (数字)9783031514524

ISBN: (纸本)9783031514517;9783031514524

Educational games have gained significant popularity in recent years as an innovative and engaging means of enhancing learning. These games use technology and game design principles to create a fun learning environment. Educational games have changed how we learn by combining fun and learning goals. They offer an engaging, interactive, and personalized learning experience, promoting critical thinking, problem-solving, and collaboration. However, the design of educational games must combine the fun factor with the learning goals, which sometimes does not happen, creating the impression that educational games are not fun. In this paper, we describe an educational game to learn multiplication operations in a fun way. The game is a point-and-click deck-building and partially rogue-lite third-person educational game with the purpose of teaching multiplication operations in mathematics. It is themed around medieval fantasy, with monsters on one hand and magic spells on the other. The player has a card deck that he can use to solve the mathematical questions and defeat the monsters. Some preliminary tests were carried out with fifty-eight students, which showed the potential of this kind of tool. Most of the students agreed that the game helped them with the multiplication operation and that they would like to play more levels of the game.

关键词： Educational Game Math Game Serious Game Adventure Game

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Eighth Graders and a Math Intelligent Tutoring System: A Deep Neural Network Analysis 25th

Eighth Graders and a Math Intelligent Tutoring System: A Dee...

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25th International Conference on Artificial Intelligence in Education (AIED)

作者： Lu, Kelun Hao, Lingxin Wang, I-Jeng Liu, Anqi Johns Hopkins Univ Sch Educ Baltimore MD 21218 USA Johns Hopkins Univ Dept Sociol Baltimore MD 21218 USA Johns Hopkins Univ Appl Phys Lab Baltimore MD 21218 USA Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA

ISBN: (纸本)9783031643118;9783031643125

Intelligent tutoring systems (ITS) typically employ scaffolding to provide learning opportunities for needed students. To assess the ITS effectiveness, most past research relies on the end-of-year exam outcome. However, it is important to assess ITS' immediate effectiveness after the scaffolding. To address this gap, this paper draws principles from theory on scaffolding and zone of proximal development to guide the analysis of micro-level, time-stamped student action data from the ASSISTments. Using a deep neural network to analyze the data, we reveal that the appropriate use of scaffolds in the ITS fosters modest growth of math problem-solving skills. Excessive use, however, is counterproductive when students are overly reliant on ITS. Our findings suggest that scaffolding in ITS or AI tutoring should encourage student active learning and prevent over-reliance on intelligent systems.

关键词： Intelligent tutoring system Scaffolding Deep neural network Student action Data

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