Emotion Wheel: Getting Feedback through Mobile Application after Children Reading Books

Emotions experienced by learners play a significant role in both their cognitive and affective learning gains, and thus, the comprehension and measurement of emotions in technology-rich learning environments (TREs) are essential aspects of 21st-century education. This study aims to design an application interface that can measure the topic emotions and epistemic emotions experienced by children after reading books. The application flow and interface design are presented, featuring emotion wheels for both topic and epistemic emotions. Data collected with this application can further be used to explore the correlation and causation between the folksonomy topic structure and emotion categories by analyzing the data. The data could potentially help in training machine learning models for sentiment analysis in future studies.

I. Introduction

In 21st-century education, technology-rich learning environments (TREs) have become crucial for effective learning. Emotions experienced by learners in these environments play a significant role in both their cognitive and affective learning gains. The comprehension and measurement of emotions in TREs are also considered essential aspects. "Emotions are the experiential glue of 21st-century learning" as noted by Arthur Graesser [1]. In line with this, Richard Mayer's commentary emphasizes three core areas to focus on, including identifying which emotions matter, determining how to measure them accurately, and exploring their connection to learning in TREs.