Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Didactics --- Intelligent tutoring systems --- Military education --- Army schools --- Education, Military --- Military art and science --- Military schools --- Military training --- Schools, Military --- Education --- ICAI (Computer-assisted instruction) --- Intelligent computer-assisted instruction --- ITS (Computer-assisted instruction) --- Knowledge-based tutoring systems --- Tutoring systems, Intelligent --- Computer-assisted instruction --- Expert systems (Computer science) --- Congresses --- Automation&delete& --- Study and teaching --- Automation --- intelligent tutoring system --- Artificial intelligence --- Computer Aided Education

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The aim of this book is to present and discuss new advances in serious games to show how they could enhance the effectiveness and outreach of education, advertising, social awareness, health, policies, etc. We present their use in structured learning activities, not only with a focus on game-based learning, but also on the use of game elements and game design techniques to gamify the learning process. The published contributions really demonstrate the wide scope of application of game-based approaches in terms of purpose, target groups, technologies and domains and one aspect they have in common is that they provide evidence of how effective serious games, game-based learning and gamification can be.

Humanities --- Education --- serious game --- gamification --- game-based learning --- programming teaching --- sustainability teaching --- mobile app --- asynchronous learning --- COVID-19 --- dental education --- distance learning --- game analytics --- integrative review --- remote learning --- serious games --- reading comprehension --- strategy training --- intelligent tutoring system --- feedback --- diabetes self-management --- RAD methodology --- game-design-based --- Software Usability Scale --- OMD --- eye-tracking --- training --- vision impairment --- rehabilitation --- vision teachers --- edutainment --- virtual reality --- traffic safety --- rollover simulator --- seat belt --- awareness --- digital game-based learning --- media in education --- multiplication game --- digital games usefulness --- computational thinking --- Swift Playgrounds --- 12-year Basic Education --- Bebras --- programming --- emotions --- emotional intelligence --- apps --- augmented reality --- usability --- primary school --- physics --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The aim of this book is to present and discuss new advances in serious games to show how they could enhance the effectiveness and outreach of education, advertising, social awareness, health, policies, etc. We present their use in structured learning activities, not only with a focus on game-based learning, but also on the use of game elements and game design techniques to gamify the learning process. The published contributions really demonstrate the wide scope of application of game-based approaches in terms of purpose, target groups, technologies and domains and one aspect they have in common is that they provide evidence of how effective serious games, game-based learning and gamification can be.

Humanities --- Education --- serious game --- gamification --- game-based learning --- programming teaching --- sustainability teaching --- mobile app --- asynchronous learning --- COVID-19 --- dental education --- distance learning --- game analytics --- integrative review --- remote learning --- serious games --- reading comprehension --- strategy training --- intelligent tutoring system --- feedback --- diabetes self-management --- RAD methodology --- game-design-based --- Software Usability Scale --- OMD --- eye-tracking --- training --- vision impairment --- rehabilitation --- vision teachers --- edutainment --- virtual reality --- traffic safety --- rollover simulator --- seat belt --- awareness --- digital game-based learning --- media in education --- multiplication game --- digital games usefulness --- computational thinking --- Swift Playgrounds --- 12-year Basic Education --- Bebras --- programming --- emotions --- emotional intelligence --- apps --- augmented reality --- usability --- primary school --- physics

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.

fintech --- financial technology --- blockchain --- deep learning --- regtech --- environment --- social sciences --- machine learning --- learning analytics --- student field forecasting --- imbalanced datasets --- explainable machine learning --- intelligent tutoring system --- adversarial machine learning --- transfer learning --- cognitive bias --- stock market --- behavioural finance --- investor’s profile --- Teheran Stock Exchange --- unsupervised learning --- clustering --- big data frameworks --- fault tolerance --- stream processing systems --- distributed frameworks --- Spark --- Hadoop --- Storm --- Samza --- Flink --- comparative analysis --- a survey --- data science --- educational data mining --- supervised learning --- secondary education --- academic performance --- text-to-SQL --- natural language processing --- database --- machine translation --- medical image segmentation --- convolutional neural networks --- SE block --- U-net --- DeepLabV3plus --- cyber-security --- medical services --- cyber-attacks --- data communication --- distributed ledger --- identity management --- RAFT --- HL7 --- electronic health record --- Hyperledger Composer --- cybersecurity --- password security --- browser security --- social media --- ANOVA --- SPSS --- internet of things --- cloud computing --- computational models --- metaheuristics --- phishing detection --- website phishing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.

fintech --- financial technology --- blockchain --- deep learning --- regtech --- environment --- social sciences --- machine learning --- learning analytics --- student field forecasting --- imbalanced datasets --- explainable machine learning --- intelligent tutoring system --- adversarial machine learning --- transfer learning --- cognitive bias --- stock market --- behavioural finance --- investor’s profile --- Teheran Stock Exchange --- unsupervised learning --- clustering --- big data frameworks --- fault tolerance --- stream processing systems --- distributed frameworks --- Spark --- Hadoop --- Storm --- Samza --- Flink --- comparative analysis --- a survey --- data science --- educational data mining --- supervised learning --- secondary education --- academic performance --- text-to-SQL --- natural language processing --- database --- machine translation --- medical image segmentation --- convolutional neural networks --- SE block --- U-net --- DeepLabV3plus --- cyber-security --- medical services --- cyber-attacks --- data communication --- distributed ledger --- identity management --- RAFT --- HL7 --- electronic health record --- Hyperledger Composer --- cybersecurity --- password security --- browser security --- social media --- ANOVA --- SPSS --- internet of things --- cloud computing --- computational models --- metaheuristics --- phishing detection --- website phishing