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Breaking the Cycle: AI Boosting Communication Skills of Low-Income Students in Brazil 25th

Breaking the Cycle: AI Boosting Communication Skills of Low-...

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

作者： de Gama, Renata Miranda Chalco, Geiser Santos, Jario Reis, Marcelo Sobrinho, Alvaro Isotani, Seiji Bittencourt, Ig Ibert Univ Sao Paulo Sao Paulo Brazil Fed Rural Univ Semiarid Mossoro Brazil Univ Fed Alagoas Maceio Alagoas Brazil Fed Univ Agreste Pernambuco Garanhuns Brazil Harvard Grad Sch Educ Cambridge MA USA

ISBN: (纸本)9783031643149;9783031643156

Improving communication skills is challenging for low-income students because they do not have the same opportunities to access quality educational services as other students. To tackle this problem, Artificial Intelligence (AI) solutions have been proposed to improve students' written communication. However, engagement is essential to enhance students' writing skills when using such solutions. We propose a gamified approach based on Csikszentmihalyi's flow theory, evidencing effectiveness in helping students achieve a flow state and enhance their ability to produce texts. We conducted a pre-test/post-test quasi-experiment involving 27 high school students from a low-income Rio de Janeiro, Brazil area. The flow state and learning scores were higher when the solution was gamified. A higher flow state among students may be attributed to the rapid and clear feedback provided. Thus, we provide valuable insights into the gamification of extracurricular activities and the development of educational technologies, such as tutoring systems based on AI. Our approach can assist in planning the use of AI to reduce the risk of promoting inequalities instead of improving engagement and writing skills.

关键词： flow state gamification high education Portuguese

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EDEN: Enhanced Database Expansion in eLearning: A Method for Automated Generation of Academic Videos 25th

EDEN: Enhanced Database Expansion in eLearning: A Method for...

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

作者： Thareja, Rushil Dwivedi, Deep Garg, Ritik Baghel, Shiva Mohania, Mukesh Shukla, Jainendra Univ South Carolina Columbia SC 29208 USA Extramarks Educ Noida India IIIT Delhi Delhi India

ISBN: (纸本)9783031643149;9783031643156

Academic video databases, integral to e-learning platforms, necessitate continual updates for freshness and diversity. In addressing this challenge, we introduce EDEN, an end-to-end method for expanding academic video databases. When presented with user-defined topics, EDEN retrieves existing videos or, if unavailable, generates new ones in the same style as the original source database, ensuring seamless integration. The system's efficacy is evidenced by its addition of 3134 videos across diverse K-12 subjects, significantly enhancing an existing database's scope. Key performance indicators, including a +6% increase in F1 BERTScore and a +9.7% rise in mean Image Visual Relevance score, demonstrate the superiority of our fine-tuned LLM and stable diffusion models over standard versions. Notably, EDEN achieves remarkable efficiency, generating one second of video content in just 0.77 s using consumer-grade GPUs.

关键词： Online learning Generative AI Education Technology

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Ontological Modeling of Lists for Modern Greek Derivation 17th

Ontological Modeling of Lists for Modern Greek Derivation

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

作者： Vasilogamvrakis, Nikos Sfakakis, Michalis Ionian Univ Dept Arch Lib Sci & Museol Corfu Greece

ISBN: (纸本)9783031659898;9783031659904

In the present article, we explore ontological models about lists in order to test them towards a Modern Greek (MG) morphological test-bed. The research topic has been aroused because of the lack of coverage in the current morpho-ontological models and because a suitable list model would considerably facilitate morph behaviour and productivity, word-list complexity or contrastive derivational analysis. After defining a suitable morphological framework, two MG lexical instances are represented by each one of the explored list models, where applicable, to evaluate their suitability. Among the models, we stress the profound design of those like OLO and CO but, on the other hand, their incapability of representing our MG -X, 0, X modeling pattern. To deal with this, we propose a new MG ontological model, based on the CO, incorporating this characteristic.

关键词： Modern Greek morphology ontologies Semantic Web Linguistic Linked Open Data list models morph ordering

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Evolution and Comparative Analysis of Enterprise Architecture Tools 20th

Evolution and Comparative Analysis of Enterprise Architectur...

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20th International Conference on Smart Business Technologies (ICSBT)

作者： Heras, Federico Univ Pompeu Fabra Barcelona Spain

ISBN: (纸本)9783031679032;9783031679049

The discipline of Enterprise Architecture (EA) involves the creation and maintenance of essential artifacts, including documents and architectural diagrams, to deliver tangible benefits to stakeholders. This paper examines the historical evolution of Enterprise Architecture and the tools associated with it. As we will explore further, EA tools have evolved from being tools for a small audience reliant on complex notations and visualizations to becoming more collaborative and user-friendly tools accessible to all stakeholders. Then, a high-level assessment and comparison of the different types of EA tool is presented. Finally, we examine the practical application of these tools for different common relevant artifacts commonly used within the Enterprise Architecture discipline.

关键词： Enterprise architecture Enterprise architecture tools

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How Could Be Used Student Comments for Delivering Feedback to Instructors in Higher Education? 25th

How Could Be Used Student Comments for Delivering Feedback t...

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

作者： Astudillo, Gabriel Hilliger, Isabel Baier, Jorge Pontificia Univ Catolica Chile Dept Ciencia Comp Santiago Chile Pontificia Univ Catolica Chile Santiago Chile

ISBN: (纸本)9783031643118;9783031643125

In higher education, open-text comments from Student Evaluations of Teaching (SET) provide valuable insights into instructional strategies. However, processing these comments can be challenging, leading to limited feedback for instructors. This research aims to develop Natural Language Processing (NLP) strategies to transform student comments into actionable feedback. Two research questions guide this study: 1) How can NLP methods diagnose the effectiveness or mismatch of instruction in higher education? and 2) How can these diagnoses inform personalized recommendations for contextually relevant teaching practices? Using cosine similarity between vector representations of student comments and literature-based statements it is diagnosed the presence of effective teaching practices. This diagnosis will inform personalized feedback recommendations. Preliminary work has used Exploratory Factor Analysis was used to analyze latent dimensions in the comment-statement similarity matrix and results suggest that correlations are linked to pedagogically relevant latent variables. This methodology seems to be a valid strategy for diagnosing the effectiveness or mismatch of teaching practices in higher education. Future research directions include exploring text data representations from different theoretical perspectives on education and investigating the impact and implementation of teaching practices suggested by language models compared to those recommended by human agents.

关键词： Natural Language Processing Student comments Effective instruction Higher Education recommender systems

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Hack Beyond the Code: Building a Toolbox of Human-Centred Strategies for AI Literacy 25th

Hack Beyond the Code: Building a Toolbox of Human-Centred St...

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

作者： Schulten, Cleo Yuan, Li Gama, Kiev Holmes, Wayne Nolte, Alexander Hoel, Tore Chounta, Irene-Angelica Univ Duisburg Essen Duisburg Germany Beijing Normal Univ Zhuhai Peoples R China Univ Fed Pernambuco Recife Brazil UCL London England Eindhoven Univ Technol Eindhoven Netherlands Carnegie Mellon Univ Pittsburgh PA 15213 USA Oslo Metropolitan Univ Oslo Norway

ISBN: (纸本)9783031643118;9783031643125

Artificial Intelligence (AI) Literacy is quickly becoming an essential 21st-century skill. Be it discerning AI art and pictures from human-made ones, challenging answers from chatbots, or addressing ethical consequences of AI - with AI being ever more present in daily life, it is crucial for everyone to be aware of its utility but also potential pitfalls and challenges. This workshop aims to facilitate a hackathon in which AIED conference participants and local stakeholders will come together, exchange ideas and experiences, and collaborate with the aim of building a toolbox to promote AI Literacy. Our goal for this toolbox is to contain a spread of tools - in the form of lesson plans, apps, activities, and others - to support educators in teaching AI Literacy and students in learning or practicing AI Literacy.

关键词： Artificial Intelligence AI Literacy toolkit hackathon

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Students' Perception on the Perceived of Knowledge of the Cyber Threats Analysis Using Security Operation Centre 12th

Students' Perception on the Perceived of Knowledge of the Cy...

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

作者： Sulaiman, Salasiah Karim, Aidah Abdul Juremi, Julia Mansor, Ahmad Zamri Asia Pacific Univ Technol & Innovat Sch Comp & Technol Kuala Lumpur Malaysia Univ Kebangsaan Malaysia Fac Educ Bangi Malaysia

ISBN: (纸本)9783031616778;9783031616785

Cybersecurity education often demands practical experience, particularly in analyzing cyber threats. To address this challenge, lab sessions or simulations are essential for students to understand threats, conduct analysis, devise counteractive measure and reporting the threats. This research examines 30 students' perceptions of their knowledge in cyber threat analysis using the Security Operation Centre (SOC). Employing a mixed-methods approach, this paper will explore SOC (Security Operations Center) utilization among undergraduate cybersecurity students. Students' perceived knowledge was evaluated through survey questions regarding their SOC experience, supplemented by interviews to gain in-depth insights into their perceptions. The findings indicate a noticeable enhancement in students' understanding of cyber threat analysis. These results have implications for higher learning institutions and educators, suggesting avenues for improving student knowledge in cybersecurity. For future research, it is recommended to conduct student assessments to validate and examine the alignment between students' perceptions and their assessment grades.

关键词： Knowledge Security Operation Center Cybersecurity Cyber Threats

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Knowledge Management Model to Support the Virtual Education Organizations 12th

Knowledge Management Model to Support the Virtual Education ...

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

作者： Garcia, Victor Hugo Medina Torres, Leidy Tatiana Angulo Estrada, Lina Maria Medina Univ Dist Francisco Jose de Caldas Fac Ingn Bogota Colombia Univ Dist Francisco Jose de Caldas Fac Ciencias Educ Bogota Colombia

ISBN: (纸本)9783031616778;9783031616785

This work aims to strengthen the administrative processes that virtual education organizations perform around the knowledge that is generated in virtual learning environments. In education, it is pertinent to apply knowledge management models that encourage continuous academic and research production, as well as to guarantee the means for knowledge and ideas to flow among teachers, students and other actors in the training process mediated by ICTs;in the way that a knowledge management model is proposed that incorporates these elements together with the characteristics of learning analysis (learning analytics) which, in this case, have the purpose of anticipating the efficiency and quality of the educational process to inform decision-making and improve the methodologies of the educational organization. The verification of the proposed model is carried out from a graphical analysis of the attendance variable, which allows us to conclude that it is necessary to define in detail the different metrics and knowledge indicators that are extracted from the virtual platforms, in order to measure the behavior of the system with the implemented model.

关键词： Virtual education virtual learning environment knowledge management learning analytics virtual education organizations

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Automatic Disambiguation of the Belarusian-Russian Legal Parallel Corpus in NooJ 1

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

作者： Varanovich, Valery Suprunchuk, Mikita Zianouka, Yauheniya Hetsevich, Yuras Belarusian State Univ Minsk BELARUS Minsk State Linguist Univ Minsk BELARUS Natl Acad Sci Belarus United Inst Informat Problems Minsk BELARUS

ISBN: (数字)9783031566462

ISBN: (纸本)9783031566455;9783031566462

The article deals with the problem of lexical ambiguity in the legislative texts of the Belarusian legal codes. Specialists of the Speech Synthesis and Recognition Laboratory in Minsk translate law codes from Russian into Belarusian to ensure equal access to them for speakers of both official languages of our country. First, the texts are translated automatically and checked and edited by translators, linguists, and lawyers. Over 20 of the 26 codes have already been prepared. The article examines types of homonyms, their semi-automatic extraction and classification using the NooJ development environment. There are two dominant classes of ambiguity resolution mechanisms: automatic, implying a completely computerized solution to this problem and interactive (semi-automatic), supposing a joint solution by a person and a computer. It means the user has a set of alternatives from which he should choose one option. About 17% of words in the experimental corpus have homonyms. The article examines their types, and presents several syntactic NooJ grammars, which allow for removing different types of homonymy.

关键词： Ambiguity Automatic Translation Disambiguation Homonymy Natural Language Processing NooJ Text Corpus Text Tagging

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An Optimization Approach for Elementary School Handwritten Mathematical Expression Recognition 25th

An Optimization Approach for Elementary School Handwritten M...

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

作者： Chevtchenko, Sergio F. Carvalho, Ruan Rodrigues, Luiz Souza, Everton Rosa, Daniel Cordeiro, Ripe Pereira, Cicero Vieira, Thales Marinho, Rarcelo Dermeval, Diego Bittencourt, Ig Ibert Isotani, Seiji Macario, Valmir Univ Fed Rural Pernambuco Recife PE Brazil Univ Fed Alagoas Ctr Excellence Social Technol Maceio Alagoas Brazil Western Sydney Univ Penrith NSW Australia Harvard Grad Sch Educ Cambridge MA USA ISI TICs SENAI Innovat Inst Informat & Commun Tec Recife PE Brazil

ISBN: (纸本)9783031643118;9783031643125

This study introduces a novel approach to Handwritten Mathematical Expression Recognition (HMER), focusing on elementary school mathematical expressions. Recognizing the challenges posed by limited training data and the unique characteristics of elementary students' handwriting, we present a multiobjective optimization method tailored for small training datasets. We employ state-of-the-art HMER methods, including transformer-based and attention mechanism models, and optimize them using a custom dataset comprised of elementary school arithmetic equations. This dataset contains 1237 images and includes both horizontal and vertical equations and isolated numbers, featuring common errors in children's handwriting. Additional similar datasets are also leveraged for training augmentation. Our experimental results demonstrate the efficacy of the optimization approach, significantly improving the performance of the evaluated models in terms of expression recognition rate and inference speed. This study contributes to the field of HMER by providing an effective optimization approach for SOTA models and by introducing a specialized dataset for elementary school mathematics. The dataset is available upon request.

关键词： HMER Deep Learning Optimization

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