"My toxic trait is thinking I'll remember this": gaps in the learner experience of video tutorials for feature-rich software
April 10, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ian Drosos, Advait Sarkar, Andrew D. Gordon
arXiv ID
2404.07114
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Video tutorials are a popular medium for informal and formal learning. However, when learners attempt to view and follow along with these tutorials, they encounter what we call gaps, that is, issues that can prevent learning. We examine the gaps encountered by users of video tutorials for feature-rich software, such as spreadsheets. We develop a theory and taxonomy of such gaps, identifying how they act as barriers to learning, by collecting and analyzing 360 viewer comments from 90 Microsoft Excel video tutorials published by 43 creators across YouTube, TikTok, and Instagram. We conducted contextual interviews with 8 highly influential tutorial creators to investigate the gaps their viewers experience and how they address them. Further, we obtain insights into their creative process and frustrations when creating video tutorials. Finally, we present creators with two designs that aim to address gaps identified in the comment analysis for feedback and alternative design ideas.
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