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      CourseWare: Advanced Technical Training System  

      AI controlled Socratic Dialog

      Pedagogical framework and didactic tools:

      The basic principle is based on the Aristotelian Philosophy of Dialogue and Discourse (and in its practical implementation, the Socratic Dialogue). Rather than providing pre- defined static content elements (frontal delivery of facts) to the student, learners are guided in dialogs of dynamically generated adaptive content to discover knowledge and further understanding. The dialogue combines background information with embedded questions to measure comprehension but also facilitate knowledge discovery and understanding from the learners. This changes the perception towards empowerment of the learner and engenders ownership of the information (discovered rather than received by the student) replacing an unconditional acceptance of authoritative delivery with participatory knowledge discovery. The role of the (simulated, rule-based expert system) tutor is to maintain and adapt the dialogue (the sequence and detail of content and questions) to the students\u2019 comprehension and knowledge, by continuously analyzing student behavior and response. Student response includes

      • the time spent on individual units (pages) in the course delivery;
      • the time used and correctness of the answers to the multiple-choice questions;
      • answers to embedded simple questions;
      • answers generated by using the linked model tools as on-line laboratory experimentation;
      • the evolving performance history, activity patterns
      • active participation in the discussion forum.
      • explicit questions and comments submitted by the student including the feedback on individuakl lectures.

      For each individual lecture unit, but also a course (set of related, interdependent lectures) as a whole, learning performance can be measured by comparing the results of a test (set of questions) given before and after the lecture, combining formative and summative evaluation concepts. The hypothesis to be tested here is that the test results after the lecture should be better (higher score) than the test results from the test given before the lecture, together with, on average a faster response. This provides easily embedded performance measures for automated monitoring and also formative evaluation feedback to improve the teaching program itself. The adaptive tutor will be innovative in employing the latest applied research and teaching practices from the field of artificial intelligence and education, and from distance, networked learning. The expert system based tutor supports individual dialogue about the particular learning tasks, (e.g. after use of a simulation, or after watching a video or reading about a topic), and adapt to the needs of the individual learner with a personalized customized delivery of dynamically generated content. The adaptive tutor will also engage in a dialogue with the learner about the learning experience and support individual reflection on that experience. Reflection through dialogue creates meaning from experience (Scardamalia & Bereiter 2008). By supporting learning through reflection on experience, the adaptive tutor not only supports learning but also facilitates knowledge creation, as it extends understanding of the area and enhances the potential for transfer of that knowledge to another context. Distance learning and collaborative activity enables the sharing of activities and discussion on activity leading to the creation of new knowledge and learner created resources. In order to assist learning and collaboration, discussion fora such as phpBB, can provide support for peer and vicarious learning where learners can discuss their course, task or project and where learner generated material can potentially be a valuable learning resource, as well as enhancing motivation. This collaborative activity can also benefit the organization through the sharing and reuse of learner created knowledge.

      The basic concepts: dialogue, discourse:

      The concept of dialogue in teaching is a few thousand years old (viz. Plato, Aristoteles, Socrates, Xenophon, Boethius, and a few more classics. Recent treatment (again more than numerous include Kneziü (2007, The Socratic Dialogue in Teacher Training), and it is not beyond being re-invented at regular intervals, e.g., Isaacs W. (1999) Dialogue and the Art of Thinking together: A pioneering Approach of Communication in Business and Life [the universe and everything], N.Y., Currency. The basics, however, are comparatively simple: The "Socratic method" does not look for specific answers and the (rote) learning of facts, but seeks to broaden students' views by helping them see multiple aspects involved in answering a question, which fits very well with the basic tenets of multi-attribute theory (e.g., Bell et al., 1978). As a somewhat more modern, yet also more controversial notion, discourse is "an entity of sequences of signs in that they are enouncements (enonc├ęs)" (Foucault, 1972, Archaeology of Knowledge. New York: Pantheon). An enouncement (or "statement") enables signs to designate specific and (within a discourse) fixed relations to objects, subjects and other enouncements. Discourse constitutes sequences of such relations to objects, subjects and other enouncements. A discursive formation describes the regularities, patterns and rules that produce such discourses. Foucault used the concept of discursive formation in relation to his analysis of large and diverse bodies of knowledge, such as political economy and natural history. Here we use it to describe the technology assisted teaching of environmental management. Discourse can be observed in (and used as a conceptual framework to describe) spoken, written and signed language and, in the case of CourseWare, multimodal and multimedia forms of communication, which includes any teaching applications of structured (rule driven patterns) forms of language via the Internet and mobile communication.

      From Aristoteles and Socrates to expert systems:

      The implementation of these basic concepts in a man-machine dialog is somewhat more restricted, yet the principle aspirations are the same: to guide the student or learner to self-discovery by a mixture of factual statements and (somewhat leading) questions, adapted to the students responses. These observations of the student reception and understanding of the course content offered, her responses to questions and tasks drives an adaptive, context sensitive and machine-learning delivery mechanism to get closer to a human student - teacher dialogue. The third dimension or component is the communication channel, here represented by both the Internet and a web browser, and mobile phones and tablet PCs, the modern equivalent of the Greek Gymnasium.

      References:

        Bell, D.E., Keeney, R.L., Raiffa, H. (1978) Conflicting Objectives in Decisions. International Series on Applied Systems Analysis. 442 pp., Johm Wiley & Sons, Chichester.
        Geurts, J., Bocconi, S., and Van Ossenbruggen, L. (2003) Towards ontology-driven discourse: From semantic graphs to multimedia presentations Lecture notes in Computer Science, 2003 - Springer
        MacKnight, C. B. (2000). Teaching critical thinking through online discussions. Educause Quarterly, 23(4), 38-41. Retrieved May 4, 2007, from http://www.educause.edu/ir/library/pdf/EQM0048.pdf
        Morse, J. M. (1998), Socratic questioning for the twenty-first century. Inquiry: Critical Thinking Across the Disciplines, 18 (2), 9-23.
        Paraskevas, A., & Wickens, E. (2003, October), Androgogy and the Socratic method: The adult learner perspective. Journal of Hospitality, Leisure, Sport and Tourism Education, 2(2), 4- 14. Retrieved May 4, 2007, from http://www.hlst.heacademy.ac.uk/Johlste/vol2no2/academic/0020.html
        Scardamalia, M. & Bereiter, C. (2008) Pedagogical biases in Educational Technologies. Educational Technology, May/June 2008.


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