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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 25th

Contextual Features for Automatic Essay Scoring in Portugues...

引用

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: (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...

引用

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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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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Towards a Software Architecture to Provide Hybrid Recommendations for Smart Campuses 1

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15th International Conference on computer Supported Education (CSEDU)

作者： Maruyama, Martin Hideki Mensch Silveira, Luan Willig Dorneles, Ana Paula Militz Casanova, Gabriel Vieira Poy, Renan Bordignon da Silva Junior, Elvandi de Oliveira, Jose Palazzo M. Maran, Vinicius Univ Fed Santa Maria Lab Ubiquitous Mobile & Appl Comp LUMAC Polytech Sch Ave Roraima BR-1000 Santa Maria RS Brazil Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (数字)9783031536564

ISBN: (纸本)9783031536557;9783031536564

Currently, several initiatives have been proposed in order to offer solutions for intelligent university campus environments. It can be said that smart university campuses are a subdomain of the smart cities domain, with some similar problems, but with specificities. Recommender systems identify and suggest relevant information to the user, recognizing their potential interests through specialized algorithms and presenting resources that align with these interests. In the context of intelligent university campuses, recommender systems have been used to define which systems and technologies should be implemented. From this scenario, the objective of this article is to present a software architecture, called SmartC, structured in different services, to provide the essential infrastructure for the application of several recommender systems and a variety of types of items. The services and layers of the architecture were defined especially for intelligent university campuses and divided into three distinct sections: the access environment, the recommendations management environment and the persistence layer. The recommendation algorithms integrated to this architecture are considered hybrids, since they incorporate two types of filtering: content-based filtering and collaborative filtering. When users request new recommendations, the type of filtering will be switched, ensuring that new features are suggested with each system call and avoiding throttling. The developed prototype was evaluated from real item data and showed significant accuracy in the recommendation process.

关键词： Recommendation system Filtering techniques Hybrid filtering Collaborative filtering Content-based filtering Smart campus University Personalized recommendation Educational resources

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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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From Guidelines to Governance: A Study of AI Policies in Education 25th

From Guidelines to Governance: A Study of AI Policies in Edu...

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

作者： Ghimire, Aashish Edwards, John Utah State Univ Logan UT 84322 USA

ISBN: (纸本)9783031643118;9783031643125

Emerging technologies like generative AI tools, including ChatGPT, are increasingly utilized in educational settings, offering innovative approaches to learning while simultaneously posing new challenges. This study employs a survey methodology to examine the policy landscape concerning these technologies, drawing insights from 102 high school principals and higher education provosts. Our results reveal a prominent policy gap: the majority of institutions lack specialized guidelines for the ethical deployment of AI tools such as ChatGPT. Moreover, we observed that high schools are less inclined to work on policies than higher educational institutions. Where such policies do exist, they often overlook crucial issues, including student privacy and algorithmic transparency. Administrators overwhelmingly recognize the necessity of these policies, primarily to safeguard student safety and mitigate plagiarism risks. Our findings underscore the urgent need for flexible and iterative policy frameworks in educational contexts.

关键词： AI in Education Administrator's attitude AI Policy

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Visitor Perspectives on Event Marketing's Role in Local Tourism

Visitor Perspectives on Event Marketing's Role in Local Tour...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Machado, Renata Goncalves Santos, Deborah Oliveira Fernandes, Paula Odete Inst Politecn Braganca UNIAG Braganca Portugal Ctr Fed Educ Tecnol Minas Gerais Belo Horizonte MG Brazil

ISBN: (纸本)9783031834349;9783031834356

The Feira das Cantarinhas e Feira do Artesanato in Braganca is an event of great social and economic importance for the city and its population, as well as for local tourism. Despite its relevance, there are no studies that analyse the impact of this event on tourism in the city and the event marketing strategies used. That way, this study aims to analyse the visitors' perception regarding the Feira das Cantarinhas e Feira do Artesanato, based on satisfaction with the experience during the event, loyalty to the event, and motivations for participating in the event. A survey was conducted by a questionnaire during the fair days in the 2023 edition. To answer the study's objective, a descriptive analysis was carried out, and presented in this investigation. The main results showed that most visitors became aware of the event through family or friends, followed by the internet or social media, and then flyers or posters. The respondents' suggestions include increasing fair promotion, improving parking facilities, considering hosting the event in a covered area, better organization of the fair place, and arranging musical performances.

关键词： Feira das Cantarinhas Feira do Artesanato event marketing local tourism

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High Performance Computing for Auto Supervised Machine Learning Training: Parallel-Distributed Implementation of the Word2Vec Algorithm for Training Word Embeddings 11th

High Performance Computing for Auto Supervised Machine Learn...

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11th Latin American Conference on High Performance Computing

作者： Ottati, Rafael Castelli Viscardi, Ignacio Nesmachnow, Sergio Univ Republica Montevideo Uruguay

ISBN: (纸本)9783031800832;9783031800849

This article presents a parallel-distributed implementation of the Word2Vec algorithm for training word embeddings, a relevant problem in natural language processing. A client-server implementation is developed, adapted to execute on non-dedicated commodity clusters. The server implements load balancing to deal with different processing times of processes and nodes. The experimental evaluation of the developed implementation was performed on a commodity cluster of workstations, analyzing the performance for different problem instances and varying the number of computing resources. Accurate speedup values and a proper scalability behavior are reported.

关键词： Natural Language Processing Word embeddings High Performance Computing MPI Word2Vec

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A Novel Model for Multi-robot Task Assignment in Smart Warehouses 5th

A Novel Model for Multi-robot Task Assignment in Smart Wareh...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Sioud, Riheb Bamoumen, Meryem Hamani, Nadia Univ Picardie Jules Verne EIJV LTI F-02100 St Quentin en Yvelines France

ISBN: (纸本)9783031807749;9783031807756

Efficient task assignment to multiple robots becomes a core challenge for smart warehouse operations. This work falls within the context of automation and task management of modern intelligent logistics. A new mathematical model for solving the open path multi-depot asymmetric traveling salesman problem is developed in this paper, aiming at finding an optimized task allocation scheme for the robots in an intelligent warehouse. Our model aims at determining optimal task sets for each robot while minimizing operational costs and in order to enhance productivity without requiring each robot to return to its starting depot. By using CPLEX, we solved the small and medium sized scenarios and demonstrated superior performance compared with other models in computation time and solution quality.

关键词： Smart warehouse Task assignment Multi robot Optimization Open-path multi depot asymmetric traveling salesman problem (OP-MATSP) Integer linear programming (ILP)

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