Mental stress analysis by measuring heart rate variability during learning programming: Comparison of visual- and text-based languages

Abstract

Visual-based programming languages that facilitate block-based coding have gained popularity as introductory methods for learning programming. Conversely, programming experts typically use text-based programming languages like C and Java. Nevertheless, a seamless method for transitioning from a visual- to text-based language has yet to be developed. Therefore, our research project aims to develop a methodology that facilitates this transition by bridging the gap between the two languages and verifying the variations in the biometric information of learners of both languages. In this study, we measured the participants’ heart rate variability (HRV) and evaluated variations in mental stress experienced while learning visual- and text-based languages. The experimental results confirmed that participants proficient in text-based languages experienced lower HRV (indicating higher stress levels) when learning visual-based languages. Conversely, those poorly proficient in text-based languages exhibited higher HRVs (indicating more favorable stress levels) while learning text-based languages. This study successfully observed differences in stress levels while learning both language types using experimental methods. These findings serve as a preliminary step toward clarifying the impact of stress experienced during learning outcomes and identifying the factors that constitute beneficial stress. This study establishes a foundation for an intermediate language that can enhance transitions between the two types of languages.