Designing Scaffolded Interfaces for Enhanced Learning and Performance in Professional Software
May 17, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yimeng Liu, Misha Sra
arXiv ID
2505.12101
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Professional software offers immense power but also presents significant learning challenges. Its complex interfaces, as well as insufficient built-in structured guidance and unfamiliar terminology, often make newcomers struggle with task completion. To address these challenges, we introduce ScaffoldUI, a method for scaffolded interface design to reduce interface complexity, provide structured guidance, and enhance software learnability. The scaffolded interface presents task-relevant tools, progressively discloses tool complexity, and organizes tools based on domain concepts, aiming to assist task performance and software learning. To evaluate the feasibility of our interface design method, we present a technical pipeline for scaffolded interface implementation in professional 3D software, i.e., Blender, and conduct user studies with beginners (N=32) and experts (N=8). Study results demonstrate that our scaffolded interfaces significantly reduce perceived task load caused by interface complexity, support task performance through structured guidance, and augment learning by clearly connecting concepts and tools within the taskflow context. Based on a discussion of the user study findings, we offer insights for future research on designing scaffolded interfaces to support instruction, productivity, creativity, and cross-software workflows.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted