A Study on the Efficiency Enhancement of Self-Directed Learning and Online Lecture Using Emotional Factor Control

  • Dong Hwa Kim
Keywords: Emotion control, Self-directed learning, Education, Online education


The 4th industrial revolution, AI, and ChatGPT have been advancing up as key topics in industrial areas and educational systems. This paper deals with the effective teaching method for the effective nurturing of manpower including the ChatGPT. ChatGPT and AI are highly impacting on educational systems as well as many industrial areas because ChatGPT can be easily used by everyone to ask questions and get responses about any field. However, online teaching cannot catch up their teaching results because they cannot see directly. Therefore, they have to develop on how they can see the results of their lecture.

This paper considers methods to see the results using emotional factors. During online lecture, when students have a satisfaction with lecturer’s lecture results, students will express happiness, enjoyment, sadness, fear, anger, disgust, surprise, and embarrassment depending on their satisfaction level. Basically, whenever they have emotional feeling, they can show their faces status such as happiness, enjoyment, sadness, fear, anger, disgust, surprise, and embarrassment.

This paper suggests the method that lecture can adjust or control lecture style through emotional factor measurement and expression.


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How to Cite
Kim, D. H. (2023). A Study on the Efficiency Enhancement of Self-Directed Learning and Online Lecture Using Emotional Factor Control. European Journal of Science, Innovation and Technology, 3(6), 294-304. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/338