About this Research Topic
Systems that combine artificial intelligence (AI) and human intelligence are referred to as augmented intelligence. As opposed to Artificial Intelligence, which seeks to replace human agents in tasks that can be automated, Augmented Intelligence strives to improve human perception and assist humans in decision-making, learning, or planning. As such, Augmented Intelligence can be applied to educational settings to further improve the precision of predictive models created by Artificial Intelligence algorithms that are responsible to make decisions about students in eLearning software. With the help of educational data, new knowledge is expected to be generated about educational practices using Augmented Intelligence methods. This knowledge can be enriched with human pedagogical knowledge. As such, hybrid knowledge as handled by the computer and enriched by humans is offered to support educational systems.
The purpose of this Research Topic is to highlight the most recent innovations in the area of Augmented Intelligence in Education to facilitate the proposal of innovative services and models that contribute to increasingly enhanced knowledge. Also, the goal of the Research Topic is to establish a design pattern for a human-centered partnership model of people and artificial intelligence working together to enhance cognitive performance, including learning, decision making, and new experiences in educational settings. To conclude, the problem that this Research Topic will try to address is the limit of knowledge of machines in education systems. This can be achieved by uniting the strength of humans and machines when prospecting value from data. Namely, the Editors seek to explore ways to augment human instinct with smart algorithms that provide fast, data-driven predictive insights in papers of this Research Topic.
This Research Topic seeks papers that present a conceptualization of artificial intelligence that focuses on its assistive role, emphasizing that its design enhances human intelligence rather than replaces it. The authors can explore Augmented Intelligence to improve human decision-making in education by processing vast amounts of educational data that would be overwhelming for a human decision-maker and by removing elements like bias, tiredness, and attention that might taint or misinterpret data, This Research Topic will offer a forum for the constructive interaction and prolific exchange of ideas among scientists and practitioners on a range of state-of-the-art research fields.
Pertaining to education, topics will include, but are not limited to:
• Augmented intelligence in education
• Personalized software in education
• Educational Data Mining
• Recommender systems
• Cognitive Systems in education
• Machine learning
• Applied Natural Language Processing
• Formal modeling
• Ontologies and Metadata tagging
• Fuzzy logic
• Artificial Neural Networks
• Genetic Algorithms
• Knowledge graphs
The purpose of this Research Topic is to highlight the most recent innovations in the area of Augmented Intelligence in Education to facilitate the proposal of innovative services and models that contribute to increasingly enhanced knowledge. Also, the goal of the Research Topic is to establish a design pattern for a human-centered partnership model of people and artificial intelligence working together to enhance cognitive performance, including learning, decision making, and new experiences in educational settings. To conclude, the problem that this Research Topic will try to address is the limit of knowledge of machines in education systems. This can be achieved by uniting the strength of humans and machines when prospecting value from data. Namely, the Editors seek to explore ways to augment human instinct with smart algorithms that provide fast, data-driven predictive insights in papers of this Research Topic.
This Research Topic seeks papers that present a conceptualization of artificial intelligence that focuses on its assistive role, emphasizing that its design enhances human intelligence rather than replaces it. The authors can explore Augmented Intelligence to improve human decision-making in education by processing vast amounts of educational data that would be overwhelming for a human decision-maker and by removing elements like bias, tiredness, and attention that might taint or misinterpret data, This Research Topic will offer a forum for the constructive interaction and prolific exchange of ideas among scientists and practitioners on a range of state-of-the-art research fields.
Pertaining to education, topics will include, but are not limited to:
• Augmented intelligence in education
• Personalized software in education
• Educational Data Mining
• Recommender systems
• Cognitive Systems in education
• Machine learning
• Applied Natural Language Processing
• Formal modeling
• Ontologies and Metadata tagging
• Fuzzy logic
• Artificial Neural Networks
• Genetic Algorithms
• Knowledge graphs
Keywords: Augmented Intelligence, Adaptive and Personalized educational software, Artificial Intelligence, Data Mining, Intelligent Tutoring Systems
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
