Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer interaction.Thus,this paper aims to help s...Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer interaction.Thus,this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback,visibility,affordance,consistency,and constraints.It also compares these methods by the number of iterations and time required to display the result.This study helps students learn these methods using interactive learning tools instead of relying on traditional teaching methods.The tool is implemented using the MATLAB app and is evaluated through usability testing with two groups of users that are categorized by their level of experience with root-finding.Users with no knowledge in root-finding confirmed that they understood the root-finding concept when interacting with the designed tool.The positive results of the user evaluation showed that the tool can be recommended to other users.展开更多
As the 21st century brings in a revolutionary change in the way students study at schools and universities, technology continues to play a crucial role in helping students achieve more conceptual and practical knowled...As the 21st century brings in a revolutionary change in the way students study at schools and universities, technology continues to play a crucial role in helping students achieve more conceptual and practical knowledge of topics taught in classrooms. Students with special needs too are now able to study in a general classroom setting, access relevant technologies and use them for higher cognitive development, helping them integrate with their surroundings. However, existing literature shows that though multiple learning tools exist that do enhance learning in special needs students, they either cater to specific areas of development such as Mathematics and English, or that are targeted towards a specified category of studentswith special needs such as autism and cerebral palsy. Furthermore, despite multiple laws and regulations supporting the right to education launched by the UAE （United Arab Emirates） government for special needs students, there seems to exist a need to provide classrooms across the country with educational applications that have a universal approach particularly in the UAE in order to include students with almost any special needs. This paper looks closely at the existing literature and highlights this gap, especially in the UAE and proposes to develop such a tool based on existing learning concepts.展开更多
Our research was focused on the identification of features, which was essential for educational digital products and the determination of their quality. The introductory analytical part of our research is focused on t...Our research was focused on the identification of features, which was essential for educational digital products and the determination of their quality. The introductory analytical part of our research is focused on the analysis of existing sources of information related to the problems of research, production, appropriate use and evaluation of educational software environments. Consequently, we have divided the existing software products into three basic groups according to our main distinguishing feature. Second part of our paper is focused on various aspects, which are to be considered when assessing the quality of software solutions. The final part contains the presentation of results of our findings related to the most important features expected and required from digital learning tools by professional experts and specialists in given field.展开更多
Recently,tool learning with large language models(LLMs)has emerged as a promising paradigm for augmenting the capabilities of LLMs to tackle highly complex problems.Despite growing attention and rapid advancements in ...Recently,tool learning with large language models(LLMs)has emerged as a promising paradigm for augmenting the capabilities of LLMs to tackle highly complex problems.Despite growing attention and rapid advancements in this field,the existing literature remains fragmented and lacks systematic organization,posing barriers to entry for newcomers.This gap motivates us to conduct a comprehensive survey of existing works on tool learning with LLMs.In this survey,we focus on reviewing existing literature from the two primary aspects(1)why tool learning is beneficial and(2)how tool learning is implemented,enabling a comprehensive understanding of tool learning with LLMs.We first explore the“why”by reviewing both the benefits of tool integration and the inherent benefits of the tool learning paradigm from six specific aspects.In terms of“how”,we systematically review the literature according to a taxonomy of four key stages in the tool learning workflow:task planning,tool selection,tool calling,and response generation.Additionally,we provide a detailed summary of existing benchmarks and evaluation methods,categorizing them according to their relevance to different stages.Finally,we discuss current challenges and outline potential future directions,aiming to inspire both researchers and industrial developers to further explore this emerging and promising area.展开更多
Software systems are present all around us and playing their vital roles in our daily life.The correct functioning of these systems is of prime concern.In addition to classical testing techniques,formal techniques lik...Software systems are present all around us and playing their vital roles in our daily life.The correct functioning of these systems is of prime concern.In addition to classical testing techniques,formal techniques like model checking are used to reinforce the quality and reliability of software systems.However,obtaining of behavior model,which is essential for model-based techniques,of unknown software systems is a challenging task.To mitigate this problem,an emerging black-box analysis technique,called Model Learning,can be applied.It complements existing model-based testing and verification approaches by providing behavior models of blackbox systems fully automatically.This paper surveys the model learning technique,which recently has attracted much attention from researchers,especially from the domains of testing and verification.First,we review the background and foundations of model learning,which form the basis of subsequent sections.Second,we present some well-known model learning tools and provide their merits and shortcomings in the form of a comparison table.Third,we describe the successful applications of model learning in multidisciplinary fields,current challenges along with possible future works,and concluding remarks.展开更多
文摘Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer interaction.Thus,this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback,visibility,affordance,consistency,and constraints.It also compares these methods by the number of iterations and time required to display the result.This study helps students learn these methods using interactive learning tools instead of relying on traditional teaching methods.The tool is implemented using the MATLAB app and is evaluated through usability testing with two groups of users that are categorized by their level of experience with root-finding.Users with no knowledge in root-finding confirmed that they understood the root-finding concept when interacting with the designed tool.The positive results of the user evaluation showed that the tool can be recommended to other users.
文摘As the 21st century brings in a revolutionary change in the way students study at schools and universities, technology continues to play a crucial role in helping students achieve more conceptual and practical knowledge of topics taught in classrooms. Students with special needs too are now able to study in a general classroom setting, access relevant technologies and use them for higher cognitive development, helping them integrate with their surroundings. However, existing literature shows that though multiple learning tools exist that do enhance learning in special needs students, they either cater to specific areas of development such as Mathematics and English, or that are targeted towards a specified category of studentswith special needs such as autism and cerebral palsy. Furthermore, despite multiple laws and regulations supporting the right to education launched by the UAE （United Arab Emirates） government for special needs students, there seems to exist a need to provide classrooms across the country with educational applications that have a universal approach particularly in the UAE in order to include students with almost any special needs. This paper looks closely at the existing literature and highlights this gap, especially in the UAE and proposes to develop such a tool based on existing learning concepts.
基金supported by the Slovak Research and Development Agency under the contract No.APVV-0266-11.
文摘Our research was focused on the identification of features, which was essential for educational digital products and the determination of their quality. The introductory analytical part of our research is focused on the analysis of existing sources of information related to the problems of research, production, appropriate use and evaluation of educational software environments. Consequently, we have divided the existing software products into three basic groups according to our main distinguishing feature. Second part of our paper is focused on various aspects, which are to be considered when assessing the quality of software solutions. The final part contains the presentation of results of our findings related to the most important features expected and required from digital learning tools by professional experts and specialists in given field.
基金funded by the National Key R&D Program of China(2023YFA1008704),the National Natural Science Foundation of China(Grant No.62377044)Beijing Key Laboratory of Big Data Management and Analysis Methods,Major Innovation&Planning Interdisciplinary Platform for the“Double-First Class”Initiative,funds for building world-class universities(disciplines)of Renmin University of China,and PCC@RUC.The authors would like to extend their sincere gratitude to Yankai Lin for his constructive feedback throughout the development of this work.
文摘Recently,tool learning with large language models(LLMs)has emerged as a promising paradigm for augmenting the capabilities of LLMs to tackle highly complex problems.Despite growing attention and rapid advancements in this field,the existing literature remains fragmented and lacks systematic organization,posing barriers to entry for newcomers.This gap motivates us to conduct a comprehensive survey of existing works on tool learning with LLMs.In this survey,we focus on reviewing existing literature from the two primary aspects(1)why tool learning is beneficial and(2)how tool learning is implemented,enabling a comprehensive understanding of tool learning with LLMs.We first explore the“why”by reviewing both the benefits of tool integration and the inherent benefits of the tool learning paradigm from six specific aspects.In terms of“how”,we systematically review the literature according to a taxonomy of four key stages in the tool learning workflow:task planning,tool selection,tool calling,and response generation.Additionally,we provide a detailed summary of existing benchmarks and evaluation methods,categorizing them according to their relevance to different stages.Finally,we discuss current challenges and outline potential future directions,aiming to inspire both researchers and industrial developers to further explore this emerging and promising area.
基金the National Natural Science Foundation of China(NSFC)(Grant Nos.61872016,61932007 and 61972013).
文摘Software systems are present all around us and playing their vital roles in our daily life.The correct functioning of these systems is of prime concern.In addition to classical testing techniques,formal techniques like model checking are used to reinforce the quality and reliability of software systems.However,obtaining of behavior model,which is essential for model-based techniques,of unknown software systems is a challenging task.To mitigate this problem,an emerging black-box analysis technique,called Model Learning,can be applied.It complements existing model-based testing and verification approaches by providing behavior models of blackbox systems fully automatically.This paper surveys the model learning technique,which recently has attracted much attention from researchers,especially from the domains of testing and verification.First,we review the background and foundations of model learning,which form the basis of subsequent sections.Second,we present some well-known model learning tools and provide their merits and shortcomings in the form of a comparison table.Third,we describe the successful applications of model learning in multidisciplinary fields,current challenges along with possible future works,and concluding remarks.
