Appraising Computing Self-Efficacy Emotions across a 5-Week Multimedia Authoring Project


  •  C. A. DeCoursey    
  •  C. Bernal Sati    

Abstract

Emotion is a key aspect of how non-specialists learn computing. The emotions included in Computing Self-Efficacy (CSE) research were identified prior to the emergence of recent models of emotion. There has been no attempt to inventory attitudes elicited while learning computing, using contemporary psycholinguistic models of subjectivity. This study of 58 medical students in Saudi Arabia used Appraisal analysis of weekly written personal responses to gain a comprehensive overview of emotions elicited during five weeks’ instruction on website-building. A Before-After Survey identified gains made in reported frequency of tasks performed outside class. A Weekly Attitude Survey identified the strength of 6 previously-identified CSE emotions, framed as positive-negative pairs. Participant journals showed that many emotions included in previous CSE emotions are not frequently-realised, and attitudes are changeable across the learning process. Overall, most positive-negative pairs do not behave correlatively, some persist where others progress, and incidence is a better guide than polarity to an attitude’s significance. Capacity and confidence suggest three stages in learning a computing task.



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