English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Machine Learning (ML) is becoming more prevalent in the systems we use daily.Yet designers of these systems are under-equipped to design with thesetechnologies. Recently, interactive visualizations have been used to present MLconcepts to non-experts. However, little research exists evaluating howdesigners build an understanding of ML in these environments or how to insteaddesign interfaces that guide their learning. In a user study (n=21), we observehow designers interact with our interactive visualizer, \textit{QUBE}, focusingon visualizing Q-Learning through a game metaphor. We analyze how designersapproach interactive visualizations and game metaphors to form an understandingof ML concepts and the challenges they face along the way. We found theinteractive visualization significantly improved participants' high-levelunderstanding of ML concepts. However, it did not support their ability todesign with these concepts. We present themes on the challenges ourparticipants faced when learning an ML concept and their self-guided learningbehaviors. Our findings suggest design recommendations for supporting anunderstanding of ML concepts through guided learning interfaces and gamemetaphors.

A Game-Based Approach for Helping Designers Learn Machine Learning Concepts