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      • HARVEST
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      Supporting students in the analysis of case studies for professional ethics education

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      SHARIPOVA-DISSERTATION.pdf (4.551Mb)
      Date
      2015-02-13
      Author
      Sharipova, Mayya
      Type
      Thesis
      Degree Level
      Doctoral
      Metadata
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      Abstract
      Intelligent tutoring systems and computer-supported collaborative environments have been designed to enhance human learning in various domains. While a number of solid techniques have been developed in the Artificial Intelligence in Education (AIED) field to foster human learning in fundamental science domains, there is still a lack of evidence about how to support learning in so-called ill-defined domains that are characterized by the absence of formal domain theories, uncertainty about best solution strategies and teaching practices, and learners' answers represented through text and argumentation. This dissertation investigates how to support students' learning in the ill-defined domain of professional ethics through a computer-based learning system. More specifically, it examines how to support students in the analysis of case studies, which is a common pedagogical practice in the ethics domain. This dissertation describes our design considerations and a resulting system called Umka. In Umka learners analyze case studies individually and collaboratively that pose some ethical or professional dilemmas. Umka provides various types of support to learners in the analysis task. In the individual analysis it provides various kinds of feedback to arguments of learners based on predefined system knowledge. In the collaborative analysis Umka fosters learners' interactions and self-reflection through system suggestions and a specifically designed visualization. The system suggestions offer learners the chance to consider certain helpful arguments of their peers, or to interact with certain helpful peers. The visualization highlights similarities and differences between the learners' positions, and illustrates the learners' level of acceptance of each other's positions. This dissertation reports on a series of experiments in which we evaluated the effectiveness of Umka's support features, and suggests several research contributions. Through this work, it is shown that despite the ill-definedness of the ethics domain, and the consequent complications of text processing and domain modelling, it is possible to build effective tutoring systems for supporting students' learning in this domain. Moreover, the techniques developed through this research for the ethics domain can be readily expanded to other ill-defined domains, where argument, qualitative analysis, metacognition and interaction over case studies are key pedagogical practices.
      Degree
      Doctor of Philosophy (Ph.D.)
      Department
      Computer Science
      Program
      Computer Science
      Supervisor
      McCalla, Gordon
      Committee
      Dutchyn, Christopher; O’Hagan, Emer; Greer, Jim; Vassileva, Julita; Nkambou, Roger
      Copyright Date
      January 2015
      URI
      http://hdl.handle.net/10388/ETD-2015-01-1929
      Subject
      intelligent tutoring systems
      ill-defined domains
      case studies
      latent semantic analysis
      ethics education
      collaboration
      visualization
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