Real-time interactions between attention and behavior in multimedia learning environments

Real-time interactions between attention and behavior in multimedia learning environments

Susan LetourneauPostdoctoral Fellow, CREATE LabNYU & CUNY Graduate Center

LearnLab Summer WorkshopAugust 4, 2012

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

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

Eye-tracking measures of visual attention

• Benefits– Remote, noninvasive– Objective– Continuous recording

• Measures include:– Location of gaze– Duration of fixations– Fixation Sequences

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

Study 1: Gaze and Activity in a Chemistry Simulation

• 26 high school students• Measures:

– Eye-tracking, activity logs– Pre/post-tests of

chemistry knowledge

• 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

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

• Scanpaths follow the path of the scaffolds. • Students with more transitions show higher learning outcomes

[Controllers-Axes, r=.56, p<.01]

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 experimento Experiment completed

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].

Planning Watching End of Experiment

Ongoing work: Physiological measures of cognitive and affective responses

• Cognition: – Eye-tracking– EEG

• Emotion: – Skin conductance– Heart rate

Triangulating multiple measures

Physiological measurements can be synchronized with eye-tracking and behavioral recordings.

Measurements can be time-locked with any channel of information.

Current Research Directions

• Controlled comparisons of responses to tasks

Behaviorally Engaging Cognitively EngagingAffectively Engaging

Acknowledgments

• CREATE Lab• PIs: Jan Plass, Bruce Homer, Catherine Milne• Lizzie Hayward, Ruth Schwartz

• Institute of Education Sciences, IPORT Fellowship