International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Cognitive Load-Aware Visualization Design |
|---|---|
| ABSTRACT | Data visualizations are widely used for communication and learning, yet we still lack a clear understanding of what makes them easy or difficult to interpret. Cognitive Load Theory (CLT), which explains how mental effort affects learning, may help guide better visualization design. This paper simplifies and adapts findings from recent work exploring how CLT applies to data visualization. The study compared two presentation styles—compact and segmented—when showing climate-related visualizations. While segmentation did not significantly reduce overall mental effort, participants reported that more readable visualizations required less extraneous cognitive load. Most users also preferred segmented designs because they felt more guided. Overall, the findings suggest that cognitive-load-aware design can support better visualization comprehension, but further research is needed to refine methods and understand moderating factors. |
| AUTHOR | SHANUSHREE RAUT, TANUJA DEVKAR, SWAYAM PARPALLIWAR, SAMRUDDHI GAVHANE, PRATIKSHA BENDBHAR, SHIVANI MOURYA, PROF. SACHIN SHINDE |
| VOLUME | 176 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1311093 |
| pdf/93_Cognitive Load-Aware Visualization Design.pdf | |
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