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Contemporary Semantic Search Techniques in Libraries: Research Gaps and Future Directions for Improving User Experience 17th

Contemporary Semantic Search Techniques in Libraries: Resear...

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

作者： Spyropoulos, Alexandros Z. Baliou, Anthoula Bratsas, Charalampos Garoufallou, Emmanouel Tsiantos, Vassilis Democritus Univ Thrace DUTH Sch Sci Dept Phys Lab Computat & Appl Math Kavalas Campus Kavala 65404 Greece Int Hellen Univ IHU Sch Social Sci Dept Lib Sci Arch & Informat Syst MetaDATA Informat Management & DATA LabMetaDATA Alexander Campus Thessaloniki 57400 Greece Int Hellen Univ IHU Dept Informat & Elect Engn Alexanders Campus Thessaloniki 57400 Greece

ISBN: (纸本)9783031659898;9783031659904

This bibliographic study explores semantic search within the context of modern libraries to identify existing research gaps and outline potential directions for future investigation. A nuanced analysis of user behaviour, the historical evolution of search engines, and query optimisation techniques is conducted to address the questions: 'How do contemporary methods and understanding of user behaviour influence the efficiency of search engines in libraries? What are the prospective measures to enhance the search experience?' The conclusions underscore the significance of semantic capture, the employment of cutting-edge techniques, the discernment of challenges, and the potential for innovation and future opportunities in the field. Ultimately, this research offers an exhaustive and persuasive overview of the domain, illuminating pathways for continued scholarly advancement and progress within modern library effectiveness.

关键词： Semantic Search Modern Libraries Search Engines Query Optimization Techniques User Behaviors Future Opportunities Search Efficiency Search Experience Innovation in Libraries

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StyloAI: Distinguishing AI-Generated Content with Stylometric Analysis 25th

StyloAI: Distinguishing AI-Generated Content with Stylometri...

引用

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

作者： Opara, Chidimma Teesside Univ Sch Comp Engn & Digital Technol Middlesbrough England

ISBN: (纸本)9783031643118;9783031643125

The emergence of large language models (LLMs) capable of generating realistic texts and images has sparked ethical concerns across various sectors. In response, researchers in academia and industry are actively exploring methods to distinguish AI-generated content from human-authored material. However, a crucial question remains: What are the unique characteristics of AI-generated text? Addressing this gap, this study proposes StyloAI, a data-driven model that uses 31 stylometric features to identify AI-generated texts by applying a Random Forest classifier on two multi-domain datasets. StyloAI achieves accuracy rates of 81% and 98% on the test set of the AuTextification dataset and the Education dataset, respectively. This approach surpasses the performance of existing state-of-the-art models and provides valuable insights into the differences between AI-generated and human-authored texts.

关键词： Stylometric Features AI in Education Natural Language Processing ChatGPT

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Effective and Scalable Math Support: Experimental Evidence on the Impact of an AI-Math Tutor in Ghana 1

引用

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

作者： Henkel, Owen Home-Robinson, Hannah Kozhakhmetova, Nessie Lee, Amanda Univ Oxford Oxford England Rising Acad Accra Ghana J PAL North Amer Cambridge MA USA

ISBN: (数字)9783031643156

ISBN: (纸本)9783031643149;9783031643156

This study is a preliminary evaluation of the impact of receiving extra math instruction provided by Rori, an AI-powered math tutor accessible via WhatsApp, on the math performance of approximately 500 students in Ghana. Students assigned to both the control and treatment groups continued their normal classes with identical curricula and classroom hours. Students in the treatment group were given access to a low-cost smartphone for one hour a week - during a monitored study hall period - and used Rori to independently study math. All other aspects of the groups' in-school experience were the same. We find that the math growth scores were substantially higher for the treatment group and statistically significant (p < 0.001). The effect size of 0.36 is considered large in the context of educational interventions: approximately equivalent to an extra year of learning. Importantly, Roriworks on basic mobile devices connected to low-bandwidth data networks, and themarginal cost of providing Rori is approximately $5 per student, making it a potentially scalable intervention in the context of LMICs' education systems. While the results should be interpreted judiciously, as they only report on year 1 of the intervention, they do suggest that chat-based tutoring solutions leveraging AI could offer a cost-effective and scalable approach to enhancing learning outcomes for millions of students globally.

关键词： LLMs conversational agents mobile-learning

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AI in K-12 Social Studies Education: A Critical Examination of Ethical and Practical Challenges 1

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

作者： Berson, Ilene R. Berson, Michael J. Univ S Florida Tampa FL 33620 USA

ISBN: (数字)9783031643156

ISBN: (纸本)9783031643149;9783031643156

The integration of Artificial Intelligence (AI) in K-12 social studies education presents a complex blend of opportunities and challenges. This paper explores the transformative potential and ethical dilemmas of employing AI, particularly in engaging with historical primary sources. Utilizing a Delphi methodology, this study captures insights from social studies educators on AI's role in enhancing or complicating the teaching and learning process. The research reveals the transformative potential of AI to deepen historical understanding and empathy through innovative tools, yet it also underscores significant concerns about the accuracy, representation of historical events and figures, and the authenticity of educational content. This exploration presents the paradox inherent in educational AI: its ability to radically transform learning experiences with innovative tools while also threatening to obscure the distinction between historical accuracy and fabrication. The emerging capabilities of generative AI prompt vital questions concerning the legitimacy of information, trustworthiness, and authenticity in historical representation. We consider the implications of AI for pedagogy, emphasizing the need for instructional approaches that engage students in the critical analysis of complex influences shaping historical narratives and visual representations. The paper also addresses the role of AI in perpetuating or challenging historical narratives and biases. It underscores the importance of critical theory in social studies education to analyze the impact of synthetic media and conversational AI agents on students' perceptions of history. We emphasize the need for collaboration between educators, technologists, and historians to ensure that AI tools enrich the educational landscape without compromising the integrity and complexity of historical understanding.

关键词： Social Studies Education AI Literacy Ethical Considerations Pedagogical Practices Primary Sources

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Images to Describe Research Data: A Case Study on the Use of Imagery Metadata 17th

Images to Describe Research Data: A Case Study on the Use of...

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

作者： Rodrigues, Joana Lopes, Carla Teixeira Univ Porto Fac Engn Rua Dr Roberto Frias P-4200465 Porto Portugal INESC TEC Rua Dr Roberto Frias P-4200465 Porto Portugal

ISBN: (纸本)9783031659898;9783031659904

Research data management includes activities that organize and manage the life of a research project and is crucial for consistent work performance. Some activities are related to the description, which is a fundamental step, since it allows data to be properly documented and interpreted, promoting their subsequent reuse and sharing. The description is usually done through text, but other typologies can also be used, such as images, taking advantage of their potential and particular characteristics to promote description. We used a qualitative method of investigation through an exploratory case study. We conducted 16 semi-structured interviews, with researchers who have produced, described, and published research data, in order to understand how images can assume the role of metadata in data description. We found that all interviewees would like to have the possibility of describing data with images, but they consider that the publishing platforms have to be prepared for this. Most researchers were able to identify descriptors that could include images and also describe those that they consider being the greatest advantages of the project. All researchers consider that images as metadata would be a more direct gateway to the data. The issue of data description through resources other than text has never been properly investigated. The existing literature does not develop the theme, although images have had an abrupt growth in society and science. This work aims to open new paths, raise new ideas and raise awareness of new and original practices.

关键词： Research data management Images Description Metadata Images as metadata Semi-structured interview

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Contextual Features for Automatic Essay Scoring in Portuguese 1

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

作者： Galhardi, Lucas Herculano, Maria Fernanda Rodrigues, Luiz Miranda, Pericles Oliveira, Hilario Cordeiro, Thiago Bittencourt, Ig Ibert Isotani, Seiji Mello, Rafael Ferreira SENAI PR Univ Ctr Londrina Brazil Univ Fed Alagoas Ctr Excellence Social Technol Maceio Brazil Univ Fed Rural Pernambuco Recife Brazil Fed Inst Espirito Santo Vitoria Brazil Harvard Grad Sch Educ Cambridge MA USA Ctr Estudos Avancados Recife Recife Brazil

ISBN: (数字)9783031643156

ISBN: (纸本)9783031643149;9783031643156

Automated Essay Scoring (AES) efficacy often varies across linguistic and contextual nuances. This study addresses this gap by proposing and evaluating a contextualized approach tailored for Portuguese. Unlike prior research, which often focused on overall scores or limited to general-purpose features, we explored devising contextualized feature extractors and investigated their impact on predictive performance. Our analysis encompassed the proposed specific features (conjunctions, syntactic quantification, and entity recognition) and two well-established baselines (i.e., TF-IDF and Coh-Metrix). Utilizing the Essay-BR dataset (n = 6,563 essays), we investigated our approach through classification and regression tasks supported by diverse machine learning algorithms and optimization techniques. Mainly, we found that our approach enhanced predictive performance when combined with existing techniques. Our findings reveal the importance of addressing and considering contextual nuances in AES, revealing insights that might help accelerate the evaluation of essays in a large-scale setting.

关键词： Essay Scoring Natural Language Processing Learning Analytics

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A Web Application for a Cost-Effective Fine-Tuning of Open-Source LLMs in Education 25th

A Web Application for a Cost-Effective Fine-Tuning of Open-S...

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

作者： Diez-Rozas, Victor Estevez-Ayres, Iria Alario-Hoyos, Carlos Callejo, Patricia Delgado Kloos, Carlos Univ Carlos III Madrid Dept Telemat Engn Madrid Spain

ISBN: (纸本)9783031643118;9783031643125

Many Generative Artificial Intelligence (GenAI) applications built on Large Language Models (LLMs) emerged in 2023 causing a great impact in the educational landscape. However, most of these GenAI applications require a subscription to access the most advanced models and functionalities. Therefore, the search for cost-effective solutions becomes an important concern, especially for instructors and educational institutions with limited resources. This article introduces a Web Application aimed at facilitating instructors in fine-tuning open-source LLMs and subsequently posing questions to them. Instructors only need to upload a dataset into the Web Application to fine-tune the opensource LLM, specifically Llama 2. This web application was developed using open-source tools (Hugging Face and Langchain), and techniques to reduce hardware resource consumption (LoRA and QLoRA). Preliminary results from the experiments conducted show that LLMs provide more accurate responses when fine-tuned for a specific task through the Web Application. These are the first steps in providing cost-effective GenAI solutions for instructors and educational institutions using opensource tools.

关键词： Generative Artificial Intelligence Large Language Models Web Application Open Source Models

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Flowing Through Virtual Realms: Leveraging Artificial Intelligence for Immersive Educational Environments 1

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

作者： Zwolinski, Grzegorz Kaminska, Dorota Lodz Univ Technol 116 Zeromskiego St PL-90924 Lodz Poland

ISBN: (数字)9783031643156

ISBN: (纸本)9783031643149;9783031643156

Virtual Reality presents a promising frontier for educational immersion, offering unparalleled opportunities for engaging learning experiences. However, the integration of artificial intelligence algorithms will be critical to realizing its full potential. This paper explores the fusion of VR and AI through the lens of Csikszentmihalyi's flow theory, with the aim of optimizing educational experiences for learners. AI emerges as a critical facilitator by aligning VR environments with the principles of flow, characterized by deep concentration, intrinsic motivation, and a balance between skill and challenge. Through adaptive learning pathways, personalized feedback mechanisms and dynamic content generation, AI-driven VR environments can tailor educational journeys to individual learners, fostering optimal engagement and learning outcomes. This paper discusses the conceptual framework for integrating AI into VR-based educational environments, highlighting the potential synergy between these technologies in creating immersive learning experiences conducive to flow states. At the same time, we propose a subjective, multidimensional assessment tool for evaluating VR educational applications, which assesses perceived flow based on feedback from students using VR during their educational journey.

关键词： VR AI Education Flow theory Flow measure

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From "Giving a Fish" to "Teaching to Fish": Enhancing ITS Inner Loops with Large Language Models 25th

From "Giving a Fish" to "Teaching to Fish": Enhancing ITS In...

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

作者： Pian, Yang Li, Muyun Lu, Yu Chen, Penghe Beijing Normal Univ Fac Educ Beijing Peoples R China Beijing Normal Univ Fac Educ Adv Innovat Ctr Future Educ Beijing Peoples R China

ISBN: (纸本)9783031643118;9783031643125

In this work, we aim to enhance the Intelligent Tutoring Systems (ITS) inner loop by incorporating Large Language Models (LLMs), shifting the educational approach from merely providing solution (giving a fish) to fostering deeper understanding and self-sufficiency (teaching to fish) in learning. Specifically, we propose a framework that utilizes LLMs to generate meaningful scaffoldings and facilitate insightful interactions within ITS tasks, guided by established learning science theories. Preliminary results from the model and educational experiments suggest that our LLM-generated scaffoldings could improve learning outcomes. From our current progress, we have gained valuable insights for further improvement. We hope this study will contribute to the development of smarter and more human-centered ITS solutions in the future.

关键词： Inner loop Intelligent tutoring system Scaffolding LLMs

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A Study Partner Recommender System Using a Community Detection Algorithm 20th

A Study Partner Recommender System Using a Community Detecti...

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20th International Conference on Smart Business Technologies (ICSBT)

作者： Obionwu, Chukwuka Victor Ilapavuluri, Devi Prasad Broneske, David Saake, Gunter Univ Magdeburg Magdeburg Germany German Ctr Higher Educ Res & Sci Studies Hannover Germany

ISBN: (纸本)9783031679032;9783031679049

The potential for an individual's interaction to be limited by an underlying inclination has significant implications when overlooked in situations where group contact is crucial. In university course projects, the absence of synergy among a project team often leads to failure. In order to provide students enrolled in our course projects with an optimal team recommendation, we have devised a highly efficient strategy. This strategy involves utilizing their personalities and assessing their collaborative effectiveness through individual personality questionnaires. Additionally, we employ community detection using the Leiden algorithm. In order to assess the soundness of our recommendation technique, we conducted an evaluation of current algorithms that have been employed for this purpose, taking into account their modularity scores and the decision to establish preferred team sizes. The assessment section presents results that demonstrate how the Leiden algorithm outperforms competing algorithms and techniques that rely on clustering coefficients. Specifically, the Leiden algorithm is capable of recommending study partners that possess many personality features that match the user and their respective teams.

关键词： Community detection Social network analysis Recommendation system Collaboration in teams

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