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Chinese Chorales Dataset: A High-Quality Music Dataset for Score Generation 2nd

Chinese Chorales Dataset: A High-Quality Music Dataset for S...

引用

2nd Summit on Music Intelligence (SOMI)

作者： Peng, Yongjie Zhang, Lei Wang, Zhenyu North China Elect Power Univ Sch Control & Comp Engn Beijing Peoples R China

ISBN: (纸本)9789819705757;9789819705764

For a long time, the JSB Chorales Dataset has served as the benchmark for choral composition generation, with numerous models and algorithms achieving remarkable results on this dataset, which is designed to generate Bach-style choral music. However, when we aim to tackle the task of generating Chinese vocal choral compositions, we encounter a lack of suitable Chinese music datasets for this purpose. The Chinese Chorales Dataset presented in this paper is a high-quality collection of Chinese choral music, comprising 125 Chinese choral songs stored in MusicXML format, divided into 441 musical segments. This dataset has been professionally crafted to meet the needs of Chinese composers seeking to create high-quality choral compositions. We also provide a *** file version containing pitch, fermata, tempo, and chord information, split into training, validation, and test sets. Additionally, we conducted multiple experiments on this dataset to validate the effectiveness of the information contained within. For access to the dataset and usage details, please visit https://***/123654ad/ChineseChorales-Dataset/tree/main.

关键词： music dataset Chinese chorales machine learning benchmark

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Natural Language Processing for a Personalised Educational Experience in Virtual Reality 25th

Natural Language Processing for a Personalised Educational E...

引用

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

作者： Alghamdi, Nuha Cristea, Alexandra, I Univ Durham Durham England Univ Jeddah Jeddah Saudi Arabia

ISBN: (纸本)9783031643118;9783031643125

Virtual Reality (VR) is a technology that creates a simulated immersive environment, allowing users to be more engaged and interactive. The user can interact with a VR environment using head-mounted displays, hand controllers, and, in some cases, speech. VR has been widely used in various industries and areas, one of which is education, to build simulated and interactive experiences. However, little prior research has explored the integration of speech input in VR educational environments. Moreover, there is currently a lack of understanding of how speech and verbal/textual interaction can support personalisation in VR in general, and in the educational domain, in particular. Thus, this research targets to fill this gap. Our long-term goal is to incorporate speech and text-based interaction in the VR learning environment, to support smooth and natural personalisation of the learning interaction. Personalisation here is used in the classical AI in Education sense, of adapting the learning system to a learner, e.g. to their level or needs. As a first step, we have started exploring and comparing different speech recognition models that support VR applications. Further, we will personalise the user experience, by utilising the text generated from the speech input and applying NLP and adaptation techniques to it. Furthermore, we will investigate the impact of this kind of personalisation on learner engagement and outcomes.

关键词： Natural Language Processing Virtual Reality Speech Recognition Voice Recognition

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Neural Automated Essay Scoring for Improved Confidence Estimation and Score Prediction Through Integrated Classification and Regression 25th

Neural Automated Essay Scoring for Improved Confidence Estim...

引用

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

作者： Uto, Masaki Takahashi, Yuto Univ Electrocommun Tokyo Japan

ISBN: (纸本)9783031643149;9783031643156

Essay writing questions are a type of constructed-response question commonly used in educational assessments. However, substantial scoring costs and reduced evaluation reliability due to rater biases can be problematic, especially in large-scale assessments. To overcome these challenges, automated essay-scoring models utilizing machine learning technologies have gained significant attention. In recent years, scoring models based on deep neural networks have achieved high accuracy. However, even highly accurate neural models still suffer from scoring errors, limiting their adoption in high-stakes assessments. To address this issue, recent studies have explored scoring models that provide confidence levels along with score predictions. This study proposes improvements to the latest confidence-predicting scoring model, enhancing its performance in both confidence estimation and score prediction.

关键词： Automated essay scoring reliability confidence estimation human-in-the-loop educational measurement

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Correlation Among Competences Involved in Digital Problem-Solving Activities with Upper Secondary School Students 1

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15th International Conference on computer Supported Education (CSEDU)

作者： Barana, Alice Fissore, Cecilia Lepre, Anna Marchisio, Marina Univ Turin Dept Mol Biotechnol & Hlth Sci Via Nizza 52 I-10126 Turin Italy

ISBN: (数字)9783031536564

ISBN: (纸本)9783031536557;9783031536564

In today's increasingly interconnected and technology-driven world, developing strong problem-solving and digital competences is the key to preparing students for a world where technology impacts society, work and education, and to achieving personal and professional fulfilment. The main aim of this paper is to investigate the correlation and the development of problem-solving and digital competences of secondary school students solving problems with an Advanced Computing Environment (ACE). During an online training, students solve a contextualized problem every ten days, collaborating asynchronously with other students. Each solution is evaluated using an evaluation rubric based on five indicators: comprehension, identification of a solution strategy, development of the solution process, argumentation, use of an ACE. The research questions are: (RQ1) "How students develop problem-solving and digital competences during the online training?" (RQ2) "How do the development of problem-solving competence (in its four indicators: comprehension, identification of a solution strategy, development of the solution process, argumentation) and the development of digital competence relate to each other during the online training?". To answer the research questions, the solutions of 158 grade 12 students to ten problems were analysed. The research methodology consists of three phases: analysis of two case studies;analysis of all students' grades;analysis of student responses to a final questionnaire. The analyses were carried out considering both the overall evaluations and the evaluations of each indicator. The correlations between the different indicators were also analysed, seeking confirmation of this evolution in the submissions of some exemplary case studies. The results show that solving contextualized problems with the ACE improved students' problem-solving and digital competences. The results also show a strong correlation between identifying a solving strategy and devel

关键词： Advanced computing environment Digital competence Mathematics education Problem solving Problem-solving competences

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Design Based Research of Multimodal Robotic Learning Companions 25th

Design Based Research of Multimodal Robotic Learning Compani...

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

作者： Yun, Hae Seon Huebert, Heiko Pinkwart, Niels Hafner, Verena V. Humbolt Univ Berlin Berlin Germany HTW Berlin Berlin Germany

ISBN: (纸本)9783031643118;9783031643125

This paper presents some initial findings from a design-based research study on multimodal robotic language learning companions. The study involved designing four robots with varying physical modalities, including two humanoid (Pepper and Nao) and two non-humanoid (Cozmo and MyKeepOn), to interact empathetically with participants during language learning scenarios. One German teacher participated in the development of these interactive scenarios. Pre- and post-tests were conducted to measure learning gains, and a survey was administered to gather insights from participants. The results showed that all participants exhibited improvements in targeted behaviors between pre- and post-tests, specifically by using longer and more grammatically correct sentences in their responses. However, unlike the strong preference for NAO, the survey revealed that Cozmo had the most characteristics of a learning companion.

关键词： Design Based Research HRI Learning Companion

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Ontology-Based Modeling of User-Environment Interaction in a Virtual Reality Exhibition 17th

Ontology-Based Modeling of User-Environment Interaction in a...

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

作者： Rikhtehgar, Delaram Javdani Wang, Shenghui Schlobach, Stefan Heylen, Dirk Univ Twente Enschede Netherlands Vrije Univ Amsterdam Amsterdam Netherlands

ISBN: (纸本)9783031659898;9783031659904

Virtual reality (VR) technology has transformed digital content experiences by providing immersive opportunities for users to explore virtual worlds. To accurately represent the intricate interactions between users and their virtual environments, it is crucial to effectively model objects, user and environment actions, as well as user interests and preferences. This paper proposes an ontology-based modeling approach for capturing user-environment interaction in a VR exhibition. By leveraging ontologies, which offer a formal representation of knowledge and define concepts, relationships, and rules within a domain, a structured framework can be established to capture the semantics of user behavior and environmental attributes. This approach presents several advantages, including standardized representation, interoperability, and compatibility across diverse platforms. Moreover, ontologies enable intelligent behavior modeling and adaptive interactions, enhancing semantic reasoning and inference capabilities. This paper delves into design principles, methodologies, and implementation considerations for developing ontologies that depict the dynamics of user behavior and environmental attributes. The research endeavors to contribute to the field of VR exhibition design, enabling personalized experiences for users.

关键词： Ontology-based User Modeling Human-Machine Interaction Virtual Reality Cultural Heritage

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Leveraging Existing Online Platforms to Support Knowledge Exchange Between Visual Arts Educators 12th

Leveraging Existing Online Platforms to Support Knowledge Ex...

引用

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

作者： Korepanova, A. Lightfoot, C. Pata, K. Tallinn Univ BFM Narva Mnt 25 EE-10120 Tallinn Estonia Tallinn Univ Sch Educ Sci Narva Mnt 25 EE-10120 Tallinn Estonia

ISBN: (纸本)9783031616778;9783031616785

Online education is experiencing a surge in technical advancement and adoption in the post-COVID world. Many universities are implementing digitally mediated courses. Art education is catching up with this development's pace;however, transitioning from in-person to online courses is fraught with complications. This paper proposes using open-source platforms to share knowledge about visual art education methodologies. We propose a framework for educators to quantitatively express the phenomenology of digitally mediated art education to improve knowledge transmission in online academic settings. We suggest using data visualizations and existing social platforms to structure, record, and share data about educational patterns to reach the defined objectives (Google Sheets and Observable Notebooks). When individual instructors have defined, recorded, and shared their findings on a relevant question, other instructors can follow, improve, and modulate their pattern, enhancing the scope of the original question and creating communities around enhancing pedagogical practices.

关键词： Art Education Online Teaching Educational Patterns Educational Objectives Observable notebooks JavaScript D3.js

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Encouraging Grading: Per Aspera Ad A-Stars 1

引用

15th International Conference on computer Supported Education (CSEDU)

作者： Niemela, Pia Hukkanen, Jenni Nurminen, Mikko Huhtamaki, Jukka Tampere Univ Fac Informat Technol & Commun Sci POB 1001 Tampere 33014 Finland

ISBN: (数字)9783031536564

ISBN: (纸本)9783031536557;9783031536564

The surge in computer science student enrollment in Data Structures and Algorithm course necessitates flexible teaching strategies, accommodating both struggling and proficient learners. This study examines the shift from manual grading to auto-graded and peer-reviewed assessments, investigating student preferences and their impact on growth and improvement. Utilizing data from Plussa LMS and GitLab, auto-graders allow iterative submissions and quick feedback. Initially met with skepticism, peer-review gained acceptance, offering valuable exercises for reviewers and alternative solutions for reviewees. Auto-grading became the favored approach due to its swift feedback, facilitating iterative improvement. Furthermore, students expressed a preference for a substantial number of submissions, with the most frequently suggested count being 50 submissions. Manual grading, while supported due to its personal feedback, was considered impractical given the course scale. Auto-graders like unit-tests, integration tests, and perftests were well-received, with perftests and visualizations aligning with efficient code learning goals. In conclusion, used methods, such as auto-grading and peer-review, cater to diverse proficiency levels. These approaches encourage ongoing refinement, deepening engagement with challenging subjects, and fostering a growth mindset.

关键词： Learning management system Next-generation learning environment Assessment and feedback Automatic grading Manual grading Peer-reviews Leaderboards Learning analytics Growth mindset The theory of formative assessment Flipped learning

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Modeling Learner Memory Based on LSTM Autoencoder and Collaborative Filtering 25th

Modeling Learner Memory Based on LSTM Autoencoder and Collab...

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

作者： Li, Tengju Bian, Cunling Wang, Ning Xie, Yangbin Chen, Kaiquan Lu, Weigang Ocean Univ China Dept Educ Technol Qingdao 266100 Peoples R China Ocean Univ China Coll Comp Sci & Technol Qingdao 266100 Peoples R China Zhejiang Lab Res Ctr Data Hub & Secur Hangzhou 311100 Peoples R China

ISBN: (纸本)9783031643118;9783031643125

Memory modeling, aimed at predicting the memory states of learners throughout their learning process, has become an integral component in online learning systems. This is particularly crucial for applications such as spaced repetition scheduling and knowledge tracking. However, existing machine learning-based memory modeling methods encounter challenges with weak supervision signals and sparse interaction data. To tackle these issues, we propose a novel approach named LSTM Autoencoder Collaborative Filtering (LACF) for modeling learner memory. Our model utilizes an LSTM autoencoder to extract temporal features from user-item interaction sequences. Additionally, a collaborative filtering module, based on the deepFM architecture, is employed to effectively learn interactions between different features, facilitating comprehensive low-order and high-order feature combinations. Experimental results demonstrate that LACF significantly outperforms existing state-of-the-art memory modeling methods, offering enhanced accuracy and precision in predictions.

关键词： Memory modeling Autoencoder Collaborative filtering Time series prediction

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Detection of Suboptimal Conditions in Photovoltaic Systems Integrating Data from Several Domains 1

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6th Iberoamerican Congress on Smart Cities (ICSC-Cities)

作者： Cardinale-Villalobos, Leonardo Murillo-Soto, Luis D. Jimenez-Delgado, Efren Sequeira, Jose Andrey Costa Rica Inst Technol San Carlos Costa Rica

ISBN: (数字)9783031525179

ISBN: (纸本)9783031525162;9783031525179

Researchers have been exploring methods to detect suboptimal conditions in photovoltaic (PV) modules, such as visual inspection, electrical analysis, and thermography. Each method has its advantages and limitations. To enhance the accuracy and efficiency of detecting these conditions, this research proposed an integrated Internet of Things (IoT) platform called the Multi-method system (MMS). This platform combines Infrared Thermography (IRT), visual inspection using RGB image processing, and electrical analysis. The MMS enables automated data capture, analysis, and remote accessibility. To validate the system, an experiment was conducted at the Costa Rica Institute of Technology. The MMS effectively detected suboptimal conditions due to soiling, partial shading, and short circuits. The system achieved a sensitivity of 0.97%, an accuracy of 0.98%, and a precision of 100%. This project functions as a proof of concept, in this case limited to a fixed location and for specific suboptimal conditions, however, it represents a solution with potential for industrial use. The research contributes to advancing PV system reliability and performance monitoring in Smart Cities, offering implications for improving solar energy efficiency and reducing maintenance costs.

关键词： Internet of things platform Photovoltaic Fault Detection Technique CNN Deep Learning

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