From Formulas to Figures: How Visual Elements Impact User Interactions in Educational Videos

TL;DR

This study investigates how the visual complexity of educational videos, especially in STEM fields, influences user interaction behaviors like pausing, rewinding, and dropping out, based on real-world data analysis.

Contribution

It introduces a detailed taxonomy of visual objects and examines their impact on user behavior, filling a gap in understanding real-world interactions with educational videos.

Findings

Higher visual complexity correlates with increased pauses and rewinds.

Textual visual elements significantly influence user interaction patterns.

Insights can guide the design of more effective educational videos.

Abstract

Educational videos have become increasingly relevant in today's learning environments. While prior research in laboratory studies has provided valuable insights, analyzing real-world interaction data can enhance our understanding of authentic user behavior. Previous studies have investigated technical aspects, such as the influence of cuts on pausing behavior, but the impact of visual complexity remains understudied. In this paper, we address this gap and propose a novel approach centered on visual complexity, defined as the number of visually distinguishable and meaningful elements in a video frame, such as mathematical equations, chemical formulas, or graphical representations. Our study introduces a fine-grained taxonomy of visual objects in educational videos, expanding on previous classifications. Applying this taxonomy to 25 videos from physics and chemistry, we examine the relationship between visual complexity and user behavior, including pauses, in-video navigation, and session dropouts. The results indicate that increased visual complexity, especially of textual elements, correlates with more frequent pauses, rewinds, and dropouts. The results offer a deeper understanding of how video design affects user behavior in real-world scenarios. Our work has implications for optimizing educational videos, particularly in STEM fields. We make our code publicly available (https://github.com/TIBHannover/from_formulas_to_figures).