Synopsis

The application of artificial intelligence and learning theory in Education is one of the promising research domains. AI can be used in the following studies e.g., pedagogy selection, effective student engagement determination, stress measurement, attention measurement, personalized teaching, and factors of effective teaching in tertiary-level education. Smartphones and IoT devices can also be used in intelligence-assisted learning e.g., learning pronunciations of Bengali or Arabic Alphabets. Therefore, big data analysis and deep learning methods can be applied in selecting effective pedagogy, and interactivity, and analyzing the learning behaviors of students of different courses and levels.

Relevance of the Topic

The topic is relevant to computer science, computer engineering, and data science students who are enthusiasts in big-data-analysis, data science, and natural processing.

Future Research/Scope

The Global Market Insights Inc. predicts that the AI education market could have a market value of $20 billion by 2027.

Skills Learned

After completion of this research students will learn to use data science approaches in education research and projects.

Relevant courses to the topic

• Artificial Intelligence, Neural Networks and Deep Learning, Machine Learning, Data Science, and Big-data Analytics

Reading List

• Srinivasan V. AI & learning: A preferred future. Computers and Education: Artificial Intelligence. 2022 Mar 18:100062.
• Chen X, Xie H, Zou D, Hwang GJ. Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence. 2020 Jan 1;1:100002.
• Medeiros RP, Ramalho GL, Falcão TP. A systematic literature review on teaching and learning introductory programming in higher education. IEEE Transactions on Education. 2018 Aug 27;62(2):77-90.
• Lee J, Lee CH, Kim DW, Kang BY. Smartphone-assisted pronunciation learning technique for ambient intelligence. IEEE Access. 2016 Dec 19;5:312-25.
• Kanagarajan S, Ramakrishnan S. Ubiquitous and ambient intelligence assisted learning environment infrastructures development-a review. Education and Information Technologies. 2018 Jan;23(1):569-98.
• Hwang GJ, Sung HY, Chang SC, Huang XC. A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors. Computers and Education: Artificial Intelligence. 2020 Jan 1;1:100003.