Advancing Development of Intercultural Competence through Supporting Predictions in Narrative Video

  • Authors:

  • Amy Ogan;Vincent Aleven;Christopher Jones

  • Affiliations:

  • Human Computer Interaction Institute;Human Computer Interaction Institute;Modern Languages Department Carnegie Mellon University, Pittsburgh, PA 15213, USA. E-mail: aeo@andrew.cmu.edu, aleven@cs.cmu.edu, cjones@andrew.cmu.edu

  • Venue:
  • International Journal of Artificial Intelligence in Education
  • Year:
  • 2009

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Abstract

Most successes in intelligent tutoring systems have come in well-defined domains like algebra or physics. We investigate how to support students in acquiring ill-defined skills of intercultural competence using an online environment that employs clips of feature films from a target culture. To test the effectiveness of a set of attention-focusing techniques (pause-predict-ponder) we created ICCAT, a simple tutor that enhances an existing classroom model for the development of intercultural competence. We ran a study in two French Online classrooms with 34 participants, comparing ICCAT versions with and without these techniques. We found that the addition of pause-predict-ponder seemed to guide students in acquiring cultural knowledge and significantly increased students' ability to reason from an intercultural perspective. Further analysis of the posttest and the post-video viewing discussion found that students in the experimental condition were significantly assisted by the prediction, and were able to maintain a high quality of discussion over time. The research thus establishes that a simple model for intercultural competence activities, enhanced with the novel pause-predict-ponder techniques, is a viable approach to creating tutors in an ill-defined domain, and possibly better suited to the demands of the domain than the standard problem-solving approach embedded in intelligent tutoring systems.