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Integrating ChatGPT into the ELEVATE-XR Adaptive Instructional Framework 6th

Integrating ChatGPT into the ELEVATE-XR Adaptive Instruction...

引用

6th International Conference on Adaptive Instructional Systems (AIS) Held as Part of the 26th International Conference on Human-computer Interaction (HCII)

作者： McDermott, Ashley F. Stager, Sarah J. Hilltown Engn Chesterfield MA 01012 USA Penn State Univ Coll Informat Sci & Technol University Pk PA 16801 USA

ISBN: (纸本)9783031606083;9783031606090

With the fast and radical transformation of how both students and instructors can access information brought on by the development of generative AI, it is critical to develop best practices around how generative AI is used to support instruction and learning rather than being a detriment. In this paper, we examine how generative AI could be integrated into the Exercisable Learning-theory and EVidence-based Andragogy for Training Effectiveness (ELEVATE) framework developed by Stanney, Skinner, and Hughes [1] to inform adaptive approaches to instruction. Originally developed for designing eXtended Reality (XR) training experiences, the ELEVATE framework incorporates learning theories from behaviorism, cognitivism, and constructivism into a cohesive framework based on the Dreyfus and Dreyfus [2] skill acquisition model and Bloom's Revised Taxonomy [3]. The ELEVATE framework offers guidance for developing appropriate expectations and forms of instruction for students at 5 proficiency levels: novice, advanced beginner, competent, proficient, expert. The ELEVATE framework identifies language for appropriate learning objectives and types of learning activities that would be appropriate for students of different proficiency levels.

关键词： Generative AI adaptive learning adaptive instruction

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Exploring Item Difficulty Prediction: Data Driven Approach for Item Difficulty Estimation 20th

Exploring Item Difficulty Prediction: Data Driven Approach f...

引用

20th International Conference on Intelligent Tutoring Systems (ITS)

作者： Lamgarraj, Mohamed Joiron, Celine Parant, Aymeric Dequen, Gilles Picardie Jules Verne Univ Lab Modlisat Informat & Syst MIS F-80000 Amiens France Picardie Jules Verne Univ CRP CPO F-80000 Amiens France

ISBN: (纸本)9783031630279;9783031630286

This paper presents a comprehensive study of learning assessment, delving into the concept of item difficulty and learner perception. It addresses two critical dimensions: the methodologies employed, particularly data-driven approaches, and the necessary data for this analysis. Traditional difficulty estimation methods focus on question content or student performance. Recent studies suggest using machine learning and natural language processing to predict question difficulty. These models are subject-specific and often overlook individual student differences, limiting their wider application. The work aims to examine data of real-world testing scenarii, so that assembling and building a rich and diverse dataset. It offers valuable insights into the factors influencing item difficulty by giving the maximum amount of information considering the test and the student. It presents experiments to build and train predictive machine learning models for difficulty prediction. At the end, thanks to experiments, we can show a nuanced understanding of the assessment challenge and lay the groundwork for incorporating psychological factors into difficulty estimation as a subsequent phase.

关键词： computer Human Learning Environments Education Assessments Item Difficulty Machine Learning

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Interaction Between Environment and Embodiment Using a Biped Robot

Interaction Between Environment and Embodiment Using a Biped...

引用

Conference on Human Interface and the Management of Information Thematic Area (HIMI) Held as Part of the 26th International Conference on Human-computer Interaction (HCII)

作者： Kobayashi, Tomowa Takeba, Ryo Mori, Hirohiko Tokyo City Univ Setagaya City Japan

ISBN: (纸本)9783031601064;9783031601071

Recent research has claimed that incorporating bodily functions added to physical sensors, such as touching, smelling, and tasting will create AI that is able to classify and think based on its multisensory information. Using an apple as an example, AI recognizes an apple as a symbol, while humans recognize it based on multiple factors such as color, texture, and smell. Based on the idea that human body enables grasping the concept of things in detail, current studies have indicated that a physical body is essential for the establishment of advanced intelligence. This paper identifies differences between AI and human cognitive functions and discusses necessary means of recognizing AI. We reproduce the cognition of things by having the robot perform reinforcement learning of bipedal walking. In the experiment, the two robots reproduced object recognition by performing reinforcement learning of bipedal walking. By having virtual robots of the same mass and size as the actual robots learn to walk, we examine how their learning process, and the results differ between the robots with physical substance and simulators without it. Comparing physical and simulated robots allows us to examine the effects of robot's physicality. We determine the environmental factors (friction, vibration, etc.) that vary the learning process and results, and suggest human-like cognitive functions the robots need to acquire.

关键词： Embodiment Robot Reinforcement Learning

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A Large Language Model Agent Based Legal Assistant for Governance Applications 23rd

A Large Language Model Agent Based Legal Assistant for Gover...

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23rd International Conference on Electronic Government (EGOV)

作者： Mamalis, Marios Evangelos Kalampokis, Evangelos Fitsilis, Fotios Theodorakopoulos, Georgios Tarabanis, Konstantinos Univ Macedonia Informat Syst Lab Thessaloniki 54636 Greece Hellen Parliament Dept Sci Documentat & Supervis Athens Greece Hellen State Legal Council Athens Greece

ISBN: (纸本)9783031702730;9783031702747

Large Language Models (LLMs) have gained significant traction, primarily due to their potential disruptive influence across industries reliant on natural language processing. Governance stands out as one such sector. Notably, there has been a surge in research activity surrounding the implications of LLMs in deciphering complex legal corpora. This research offers substantial assistance to various stakeholders, including decision-makers, administrators, and citizens. This article focuses on the design and implementation of an LLM-based legal assistant tailored for interacting with legal resources. To achieve this, a real-world scenario has been chosen, incorporating models GPT3.5 and GPT4 as the LLMs, a well-defined legal corpus comprising European Union (EU) legislation and case law concerning the General Data Protection Regulation (GDPR), alongside a series of reference legal queries of varying complexity. Retrieval Augmented Generation (RAG) as well as agent methodologies are employed to seamlessly integrate the LLMs' functionalities with the customized dataset. The results appear to be promising, as the system managed to correctly address the majority of the legal queries, though with variable precision. Expectantly, the complexity of the queries severely impacted the quality of the outcome.

关键词： Artificial intelligence Legal assistant Large language model GDPR Policy making Law making Public administration

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Short and Long Term Vessel Movement Prediction for Maritime Traffic 1

引用

18th International Conference on Critical Information Infrastructures Security (CRITIS)

作者： Farahnakian, Farshad Farahnakian, Fahimeh Sheikh, Javad Nevalainen, Paavo Heikkonen, Jukka Univ Turku Dept Comp Turku 20500 Finland

ISBN: (数字)9783031621390

ISBN: (纸本)9783031621383;9783031621390

In maritime traffic management, the precise prediction of vessel trajectories is paramount, given the industry's substantial dependence on vessel transportation for the transport of commodities, passengers, and energy resources. This study proposes two innovative prediction methodologies (short-term and long-term) for vessel movements. Furthermore, we introduce a novel evaluation metric designed to quantitatively assess the efficacy of the proposed short-term prediction method in forecasting vessel trajectories. The presented methodologies were empirically tested, employing two-month Automatic Identification System (AIS) data collected from the Baltic Sea to examine their performance. Preliminary experimental outcomes indicate a superior level of accuracy embodied in the short-term prediction method. On the other hand, the long-term prediction method demonstrated enhanced performance metrics in the context of computational speed and memory utilization. These observations underscore the potential of the proposed methodologies to amplify efficiency and augment safety standards in marine traffic management.

关键词： Maritime Traffic Vessel Movement Prediction Intelligent Transportation System Machine Learning Neural Networks

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SWARM-SLR - Streamlined Workflow Automation for Machine-Actionable Systematic Literature Reviews 28th

SWARM-SLR - Streamlined Workflow Automation for Machine-Acti...

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28th International Conference on Linking Theory and Practice of Digital Libraries (TPDL)

作者： Wittenborg, Tim Karras, Oliver Auer, Soren Leibniz Univ Hannover L3S Res Ctr Hannover Germany Tech Univ Carolo Wilhelmina Braunschweig Cluster Excellence SE2A Sustainable & Energy Effi Braunschweig Germany TIB Leibniz Informat Ctr Sci & Technol Hannover Germany

ISBN: (纸本)9783031724367;9783031724374

Authoring survey or review articles still requires significant tedious manual effort, despite many advancements in research knowledge management having the potential to improve efficiency, reproducibility, and reuse. However, these advancements bring forth an increasing number of approaches, tools, and systems, which often cover only specific stages and lack a comprehensive workflow utilizing their task-specific strengths. We propose the Streamlined Workflow Automation for Machine-actionable Systematic Literature Reviews (SWARM-SLR) to crowdsource the improvement of SLR efficiency while maintaining scientific integrity in a state-of-the-art knowledge discovery and distribution process. The workflow aims to domain-independently support researchers in collaboratively and sustainably managing the rising scholarly knowledge corpus. By synthesizing guidelines from the literature, we have composed a set of 65 requirements, spanning from planning to reporting a review. Existing tools were assessed against these requirements and synthesized into the SWARM-SLR workflow prototype, a ready-for-operation software support tool. The SWARM-SLR was evaluated via two online surveys, which largely confirmed the validity of the 65 requirements and situated 11 tools to the different life-cycle stages. The SWARM-SLR workflow was similarly evaluated and found to be supporting almost the entire span of an SLR, excelling specifically in search and retrieval, information extraction, knowledge synthesis, and distribution. Our SWARM-SLR requirements and workflow support tool streamlines the SLR support for researchers, allowing sustainable collaboration by linking individual efficiency improvements to crowdsourced knowledge management. If these efforts are continued, we expect the increasing number of tools to be manageable and usable inside fully structured, (semi-)automated literature review workflows.

关键词： Systematic Literature Review Workflow Automation Requirement Software Tool Crowdsourcing

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A Generative Approach for Proactive Assistance Forecasting in Intelligent Tutoring Environments 20th

A Generative Approach for Proactive Assistance Forecasting i...

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20th International Conference on Intelligent Tutoring Systems (ITS)

作者： Wu, Yuyan Arevalillo-Herraez, Miguel Solera-Monforte, Sergi Univ Valencia Dept Informat Valencia 46100 Spain

ISBN: (纸本)9783031630279;9783031630286

Adaptive user feedback facilitates the delivery of personalized assistance to students struggling with self-learning and enhances their overall learning effectiveness. However, numerous studies on student behavior have revealed that they may not consistently utilize helpseeking functions. Deciding when a system should assist students during the dynamic learning process poses a challenge. We propose a new approach called Transformer4HELP, which enables the system to proactively assist students in their learning process interactions in a generative way. We employ an auto-regressive masking strategy to train a decoder-based transformer for prediction, assessing the necessity of providing help at each time step based on the likelihood that intervention may benefit the user's actions. To evaluate this approach, we used real behavioral data from students engaged in solving arithmetic mathematical problems. The experimental results demonstrate the effectiveness of the proposed method, reaching an AUC of 0.84 when predicting whether the student needs help.

关键词： Intelligent Tutoring Systems assistance dilemma proactive hints problem solving transformer

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Business Continuity Management- Building Block of Dynamic Resilience 1

引用

18th International Conference on Critical Information Infrastructures Security (CRITIS)

作者： Eveliina, Hytonen Harri, Ruoslahti Laurea Univ Appl Sci Ratatie 22 Vantaa 01300 Finland

ISBN: (数字)9783031621390

ISBN: (纸本)9783031621383;9783031621390

Today's organizations face almost constant exigencies and disruptive events such as natural or manmade disasters, technological innovations, public relations crises, and cyber-attacks, which have led many of them to reconsider their approaches to their business continuity management processes and practices. Organizations may lack resilience and lose critical functions or interrupt operations if they encounter a disruption. Adverse events causing loss of functionalities may also affect stakeholders and society. Therefore, business continuity management is essential for enhancing dynamic resilience. This case study research uses qualitative methods to collect and analyze the data. The data were collected by conducting 28 interviews of Finnish continuity management practitioners and experts. Then a cross-case analysis of the data was conducted. The results of the study show that business continuity principles are recognized and utilized in the organizations' security management work to a varying extent. Emphasis is put on dynamic continuity planning, including continuous risk assessment and exercises and open communication. By following these principles flexibly and by adapting to the changing environment, the organizations may be able to build and enhance dynamic resilience.

关键词： Dynamic Resilience Business Continuity Management Disruptive Events

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A Digitalized Approach to Discourse Production and Reception from the Perspective of Proximization Theory 8th

A Digitalized Approach to Discourse Production and Reception...

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8th International Conference on Emerging Technologies for Education (SETE)

作者： Pan, Chengcheng Shanghai Int Studies Univ Inst Corpus Studies & Applicat Shanghai Peoples R China

ISBN: (纸本)9789819742424;9789819742431

Previous research on Proximization Theory has mainly focused on the perspective of discourse production. This study attempts to compare the differences between discourse spaces of production and reception, specifically examining the differences in theme distribution in the two spaces, as well as discourse production and reception strategies from the perspective of Proximization Theory. Through thematic analysis and close reading, this study analyzes reports and comments on the incident of "Nuclear Wastewater Discharge from Fukushima Nuclear Power Plant in Japan" on the news aggregation website Reddit. The findings are as follows: 1) The themes in the discourse space of reception show significant expansion and exhibit an attitude of resistant reading;2) The original report text, in order to deconstruct the legitimacy of Japan's wastewater discharge, employs spatial, temporal, and axiological proximization strategies, with spatial proximization being predominant;3) Readers in the discourse space of reception employ five discourse strategies.

关键词： Proximization Theory Discourse Production Discourse Reception Discourse Strategies

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Finding Homometric Multiplets 9th

Finding Homometric Multiplets

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9th International Conference on Mathematics and Computation in Music (MCM)

作者： Jedrzejewski, Franck CEA Paris Saclay Univ Saclay France

ISBN: (纸本)9783031606373;9783031606380

In the article On Extended Z-triples (1981), David Lewin proved that Z-sets introduced by Allen Forte, which are neither transposed nor inverted forms and which have the same interval vector are not necessarily pairs. In a N = 16 degrees equal temperament, he exhibited triples of pcsets which are Z-associated. In this paper, we give a general formula for all homometric triples of pentachords, and some new methods to construct homometric multiplet.

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