1. Real-time interactions between attention and behavior in multimedia learning environments Susan Letourneau Postdoctoral Fellow, CREATE Lab NYU & CUNY Graduate Center LearnLab Summer Workshop August 4, 2012

2. How can multimedia technology be made more effective for learning? CREATE Lab research includes: Systematic investigation of design principles that may support learning Iterative development of educational games and simulations

3. Interactivity and Engagement Students interact and “engage” with multimedia materials in different ways: –By acting and doing –By looking and thinking –By reacting and feeling How can we capture attention, cognition, emotion, in addition to behavioral activity? Multiple measures: –Activity logs –Eye-tracking –Physiological responses

4. Eye-tracking measures of visual attention Benefits –Remote, noninvasive –Objective –Continuous recording Measures include: –Location of gaze –Duration of fixations –Fixation Sequences

5. Integrating Activity Logs & Eye-tracking Synchronized recordings of behavior and attention using common timestamp Data analysis approaches: –Behaviors as individual events –Behaviors as markers or dividers to parse eye- tracking data –Sequences of gaze and behavior over time

6. Study 1: Gaze and Activity in a Chemistry Simulation 26 high school students Measures: –Eye-tracking, activity logs –Pre/post-tests of chemistry knowledge

7. Gaze transitions between multiple representations correlated with learning outcomes –Controllers-Axes:  =.54, t(20)=2.88, p=.01, Container-Graph:  =.46, t(20)=2.38, p=.02 Students often looked to these key areas immediately after changing a variable in the simulation

8. Study 2: Using visual scaffolds to guide attention 28 high school students, using simulation with or without scaffolds Examined gaze patterns following interactions with the controllers

9. Scanpaths follow the path of the scaffolds. Students with more transitions show higher learning outcomes [Controllers-Axes, r=.56, p<.01]

10. Study 3: Attention during experimentation. 32 high school students planned and executed experiments in a chemistry simulation Activity logs used to divide eye-tracking data into three types of activities: o Adjusting variables (planning experiment) o Watching ongoing experiment o Experiment completed

11. Students directed attention to different parts of the simulation during different activities. Attention to the graph area specifically while students planned an experiment was correlated with post-test scores [  =0.49, t(22)=2.51, p=.02].

12. Planning WatchingEnd of Experiment

13. Ongoing work: Physiological measures of cognitive and affective responses Cognition: –Eye-tracking –EEG Emotion: –Skin conductance –Heart rate

14. Triangulating multiple measures Physiological measurements can be synchronized with eye-tracking and behavioral recordings. Measurements can be time-locked with any channel of information.

15. Current Research Directions Controlled comparisons of responses to tasks Behaviorally Engaging Cognitively Engaging Affectively Engaging

16. Acknowledgments CREATE Lab PIs: Jan Plass, Bruce Homer, Catherine Milne Lizzie Hayward, Ruth Schwartz Institute of Education Sciences, IPORT Fellowship