Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Hypertext 2016


Published on

This poster is presented at Hypertext 2016. The paper available here:

Published in: Data & Analytics
  • Be the first to comment

  • Be the first to like this

Hypertext 2016

  1. 1. A Comparative Study of Visual Cues for Annotation-Based Navigation Support in Adaptive Educational Hypermedia Roya Hosseini & Peter Brusilovsky {roh38,peterb} Visual Cues in Past Work Annotation Design Choices The Study Findings A2 A3 Knowledge-based Annotation Recommendations C1A1 C1A2 C1A3 C2A1 C2A2 C2A3 Task 1: Finding Least/Most Known Lines + Task 3: Finding Recommended Lines + Visual Cues Were Perceptually Different User Preference Changed in Task Context B1A1 B1A2 B1A3 B2A1 B2A2 B2A3 History-based Annotation NavEx: Fillable Shape Progressor: Red-to-Green Gradient Mastery Grids: Green Color Intensities WebEx: Check Mark Annotation The plots show that the percent of subjects favoring a design changed before and after performing Task 1, Task 2, and Task 3. …. 3 3.5 4 4.5 5 A1 A2 A3 3.5 4 4.5 5 B1 B2 3.5 4 4.5 5 C1 C2 20 40 60 80 Before After -- A1 A2 A3 20 40 60 80 100 Before After B1 B2 C1 C2 The plots show predictive margins of designs’ preference score with 95% CI, for 30 subjects. Design A1, B2, and C2 received significantly higher preference scores compared to other designs in their group. Preference score was calculated by aggregating responses over all questions in each questionnaire. The top designs A1– B2–C2 identified in out- of-context evaluation increased their standing above other designs during in- context evaluation. Task 2: Finding Clicked Lines + A1 Most Efficient Design Most Efficient Design Most Efficient Design