Blogs (1) >>
VL/HCC 2020
Tue 11 - Fri 14 August 2020 Dunedin, New Zealand
Thu 13 Aug 2020 07:15 - 07:30 at Zoom Room - Supports for Human Learning Chair(s): Michelle Ichinco

Online step-by-step text and video tutorials play an integral role in learning feature-rich software applications. However, when searching, users can find it difficult to assess whether a tutorial is designed for their level of software expertise. Novice users can struggle when a tutorial is out of their reach, whereas more advanced users can end up wasting time with overly simple, first-principles instruction. To assist users in selecting tutorials, we investigate the feasibility of using machine-learning techniques to automatically assess a tutorial’s difficulty. Using Photoshop as our primary testbed, we develop a set of distinguishable tutorial features, and use these features to train a classifier that can label a tutorial as either Beginner or Advanced with 85% accuracy. To illustrate a potential application, we developed a tutorial browsing interface called TutVis. Our initial user evaluation provides insight into TutVis’s ability to support users in a range of tutorial selection scenarios.

Thu 13 Aug
Times are displayed in time zone: Pacific Time (US & Canada) change

07:00 - 07:37: Supports for Human LearningResearch Papers at Zoom Room
Chair(s): Michelle IchincoUniversity of Massachusetts Lowell
07:00 - 07:15
Talk
“I Would Just Ask Someone”: Learning Feature-Rich Design Software in the Modern WorkplaceFull paper
Research Papers
Kimia KianiSimon Fraser University, Parmit ChilanaSimon Fraser University, Andrea BuntUniversity of Manitoba, Tovi GrossmanUniversity of Toronto, George FitzmauriceAutodesk Research
Authorizer link
07:15 - 07:30
Talk
An Automated Approach to Assessing an Application Tutorial’s DifficultyFull paper
Research Papers
Shahed Anzarus SababUniversity of Manitoba, Adnan KhanUniversity of Manitoba, Parmit ChilanaSimon Fraser University, Joanna McGrenereUniversity of British Columbia, Andrea BuntUniversity of Manitoba
Authorizer link
07:30 - 07:37
Talk
Using Bugs in Student Code to Predict Need for HelpShort paper
Research Papers
Yana MalyshevaWashington University in St. Louis, Caitlin KelleherWashington University in St. Louis
Authorizer link