Recently, the way we transfer knowledge has changed tremendously, from face-to-face classes to online learning using conference technology. Inevitably, education technology should be extended more and more to help transfer knowledge, particularly for the next generation. The intelligence of education should be extended using Artificial Intelligence (AI) technology with algorithm implementation such as data mining, machine learning, and deep learning to reach and apply the state of the art of AI as how to think like a human.

Considering the variance of data in education which includes structured data and unstructured data such as text, voice, image, and video, computational intelligence needs to particularly deal with unstructured data which needs to be transformed into structured data for easier deduction of patterns or rules. Structured data in education is easy to deal with on a daily basis using some AI technologies such as data mining, machine learning, and deep learning. Unstructured data text in education, such as questioning answers in an essay or discussion in a forum, needs to be exercised in order to analyze the sentiment of data using some semantic search technology such as Information Retrieval (IR), Text Mining, or Natural Language Processing. Moreover, unstructured data such as voice, image, and video can be processed with computational intelligence techniques such as machine learning or deep learning, which recognize the feature extraction as a transformation from unstructured data to structured data, learn, and find the resulting pattern.

This Special Issue aims to encourage and report on the implementation of computational intelligence technology in education. We seek papers that apply any algorithm in education as part of Artificial Intelligence, such as data mining, machine learning, deep learning, sentiment analysis, Information retrieval, text mining, and Natural Language Processing using structured and unstructured data such as text, voice, image, and video. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Intelligent tutoring systems
• Algorithm implementation in education
• Data mining implementation in education
• Machine learning implementation in education
• Deep learning implementation in education
• Pattern recognition implementation in education
• Computer science implementation in education
• Computational intelligence in Massive Online Open Courses
• Computational intelligence in e-learning, online learning, and blended learning
• Computational intelligence in homeschooling
• Computational intelligence in computer-based and computer-aided instruction
• Computational intelligence in computer-aided design
• Computational intelligence in simulation in education