Tanja Käser

Daniel L. Schwartz

International Journal of Artificial Intelligence in Education

IJAIED 发表有关人工智能在教育中的应用的论文。它旨在帮助开发基于计算机的学习系统的设计原则。其前提是，这些原则涉及在实施之前或执行期间对知识相关方面的建模和表示，因此需要应用人工智能技术和概念。 IJAIED 对人工智能和“基于计算机的学习系统”的范围有一个非常广泛的概念，正如以下被认为在 IJAIED 范围内的主题列表所示：自适应和智能多媒体和超媒体系统基于代理的学习环境AIED和教师教育 AIED 系统的架构 学习成果的评估和测试 AIED 系统的创作系统和外壳 贝叶斯和统计方法 基于案例的系统 认知发展 解决问题的认知模型 用于学习的认知工具 计算机辅助语言学习 计算机支持的协作学习 对话（争论、解释、谈判等）发现环境和微观世界分布式学习环境教育机器人嵌入式培训系统为学习环境设计提供信息的实证研究支持编程学习的环境 AIED 系统的评估 AIED 系统组件的正式模型帮助和建议系统人为因素和界面设计教学设计原则教学规划互联网上的智能代理基于计算机的培训的智能课件智能辅导系统知识和技能获取教学的知识表示建模元认知技能建模教学交互动机教学系统的自然语言界面网络化学习和教学系统神经模型应用于 AIED 系统绩效支持系统实际的、真实的世界AIED 系统的应用定性推理在模拟中的应用情景学习和认知学徒学习的社会和文化方面学生建模和认知诊断支持知识建设社区支持网络通信学习和概念改变理论管理和课程整合工具引导探索信息资源

The International Journal of Artificial Intelligence in Education publishes research papers on the application of artificial intelligence in education, aiming to assist in the development of design principles for computer-based learning systems. These principles involve modeling and representing knowledge-related aspects before implementation or during execution, thus necessitating the application of artificial intelligence technologies and concepts. The journal has a broad definition of the scope of artificial intelligence and 'computer-based learning systems', with the following topics considered within its scope: adaptive and intelligent multimedia and hypermedia systems, agent-based learning environments, AIED and teacher education, architecture of AIED systems, assessment and testing of learning outcomes, creation systems and shells for AIED systems, Bayesian and statistical methods, case-based systems, cognitive development, cognitive models for problem-solving, cognitive tools for learning, computer-assisted language learning, computer-supported collaborative learning, dialogue (debate, explanation, negotiation, etc.), discovery environments and micro-worlds, distributed learning environments, educational robotics, embedded training systems, empirical research providing information for the design of learning environments, environments supporting programming learning, evaluation of AIED systems, formal models of AIED system components, help and advice systems, human factors and interface design, instructional design principles, instructional planning, intelligent agents on the internet, intelligent courseware for computer-based training, intelligent tutoring systems, knowledge and skill acquisition, knowledge representation for instruction, modeling metacognitive skills, instructional interaction motivation, natural language interfaces for instructional systems, networked learning and teaching systems, application of neural models in AIED systems, performance support systems, applications of real-world AIED systems, qualitative reasoning in simulations, situational learning and cognition, social and cultural aspects of apprenticeship learning, student modeling and cognitive diagnosis, support for knowledge construction, community support, networked communication learning and conceptual change theory, management and curriculum integration tools, and guided exploration of information resources.

《International Journal of Artificial Intelligence in Education》发表关于人工智能在教育中应用的研究论文，旨在帮助开发基于计算机的学习系统的设计原则。这些原则涉及在实施前或执行过程中对知识相关方面的建模和表示，因此需要应用人工智能技术和概念。该期刊对人工智能和“基于计算机的学习系统”的范围有着广泛的定义，以下主题被认为在其范围之内：自适应和智能多媒体与超媒体系统、基于代理的学习环境、AIED与教师教育、AIED系统架构、学习成果的评估与测试、AIED系统的创作系统与外壳、贝叶斯与统计方法、基于案例的系统、认知发展、解决问题的认知模型、用于学习的认知工具、计算机辅助语言学习、计算机支持的协作学习、对话（争论、解释、谈判等）、发现环境与微观世界、分布式学习环境、教育机器人、嵌入式培训系统、为学习环境设计提供信息的实证研究、支持编程学习的环境、AIED系统的评估、AIED系统组件的正式模型、帮助与建议系统、人为因素与界面设计、教学设计原则、教学规划、互联网上的智能代理、基于计算机的培训的智能课件、智能辅导系统、知识与技能获取、教学的知识表示、建模元认知技能、教学交互动机、教学系统的自然语言界面、网络化学习与教学系统、神经模型在AIED系统中的应用、绩效支持系统、实际的真实世界AIED系统的应用、定性推理在模拟中的应用、情景学习与认知、学徒学习的社会与文化方面、学生建模与认知诊断、支持知识建设、社区支持、网络通信学习与概念改变理论、管理与课程整合工具、引导探索信息资源。

Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

It is demonstrated that students’ inquiry strategies indeed influence the learning outcome, and students” inquiry strategies also seem to be predictive for their academic achievement, and the use of a probabilistic model jointly representing student knowledge and strategies is proposed.

Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

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Journal Info

Category	Quartile
COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS	1