Light-Bulb Moment?: Towards Adaptive Presentation of Feedback based on Students' Affective State

Affective states play a significant role in students' learning behaviour. Positive affective states can enhance learning, whilst negative affective states can inhibit it. This paper describes a Wizard-of-Oz study which investigates whether the way feedback is presented should change according to the affective state of a student, in order to encourage affect change if that state is negative. We presented 'high-interruptive' feedback in the form of pop-up windows in which messages were immediately viewable; or 'low-interruptive' feedback, a glowing light bulb which students needed to click in order to access the messages. Our results show that when students are confused or frustrated high-interruptive feedback is more effective, but when students are enjoying their activity, there is no difference. Based on the results, we present guidelines for adaptively tailoring the presentation of feedback based on students' affective states when interacting with learning environments.

[1]  R. Pekrun.  The Control-Value Theory of Achievement Emotions: Assumptions, Corollaries, and Implications for Educational Research and Practice , 2006 .

[2]  Manolis Mavrikis,et al.  Diagnosing and acting on student affect: the tutor’s perspective , 2008, User Modeling and User-Adapted Interaction.

[3]  Rosalind W. Picard,et al.  An affective model of interplay between emotions and learning: reengineering educational pedagogy-building a learning companion , 2001, Proceedings IEEE International Conference on Advanced Learning Technologies.

[4]  J. Read,et al.  Endurability, Engagement and Expectations: Measuring Children’s Fun , 2002 .

[5]  Manolis Mavrikis,et al.  Design requirements, student perception indicators and validation metrics for intelligent exploratory learning environments , 2013, Personal and Ubiquitous Computing.

[6]  Ralph L. Rosnow,et al.  Essentials of Behavioral Research: Methods and Data Analysis , 1984 .

[7]  Manolis Mavrikis,et al.  Not all wizards are from Oz: Iterative design of intelligent learning environments by communication capacity tapering , 2010, Comput. Educ..

[8]  Peter Brusilovsky,et al.  Adaptive visualization for exploratory information retrieval , 2013, Inf. Process. Manag..

[9]  Rebecca Eynon,et al.  Supporting older adults in using technology for lifelong learning: the methodological and conceptual value of Wizard of Oz simulations , 2012 .

[10]  C. Izard.  The Many Meanings/Aspects of Emotion: Definitions, Functions, Activation, and Regulation , 2010 .

[11]  John Sweller,et al.  Cognitive Load Theory and the Use of Educational Technology. , 2008 .

[12]  P. Ekman.  An argument for basic emotions , 1992 .

[13]  F. Paas,et al.  Cognitive Architecture and Instructional Design , 1998 .

[14]  Manolis Mavrikis,et al.  Exploring the Potential of Speech Recognition to Support Problem Solving and Reflection - Wizards Go to School in the Elementary Maths Classroom , 2014, EC-TEL.

[15]  Beverly Park Woolf,et al.  Affect-aware tutors: recognising and responding to student affect , 2009, Int. J. Learn. Technol..

[16]  Richard Cox,et al.  Graphical Data Displays and Database Queries: Helping Users Select the Right Display for the Task , 2005, Smart Graphics.

[17]  Zhen Wen,et al.  Behavior-driven visualization recommendation , 2009, IUI.

[18]  Cristina Conati,et al.  Highlighting interventions and user differences: informing adaptive information visualization support , 2014, CHI.