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Characterization of Human Knowledge for Intelligent Tutoring

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 563))

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Abstract

Seismic data interpretation and subsurface mapping are key skills to analyze subsurface geology. They form the basis for the decision concerning hydrocarbons exploration and extraction. Interpreting a seismic graph, with perfection, needs expert knowledge. The knowledge of seismic data interpretation used in exploration industry is largely individualistic, with each human expert using his/her own set of mental database of interpretation rules developed over years of experience. For the lack of appropriate structure and formalization, this essential body of knowledge is unable to smoothly percolate to the next generation of seismologists, who are expected to deliver reasonable accuracy in their interpretations, almost immediate to their induction. Characterization of human knowledge is the process of structuring, formalizing and transforming the nature of the knowledge from tacit form to explicit form. Current work presents design and development of intelligent system to characterize this knowledge and deliver it using tutoring strategy exclusively devised as per the learner adjudged learning preference. This prototype additionally also measures learner’s performance and facilitates learning gain. The system has been tested with 16 participants, and the resultant performance is recorded.

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Acknowledgements

The author thankfully acknowledges the management of University of Petroleum and Energy Studies (UPES), Dehradun, India, for supporting and granting permission to publish this work.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Centre for Information Technology, University of Petroleum and Energy Studies, Dehradun, India

    Neelu Jyothi Ahuja

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  1. Neelu Jyothi Ahuja
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Correspondence to Neelu Jyothi Ahuja .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Białystok University of Technology, Białystok, Poland

    Khalid Saeed

  2. Department of Computer Science and Engineering, University of Calcutta, Kolkata, India

    Nabendu Chaki

  3. C.V. Raman College of Engineering, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  4. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Sambit Bakshi

  5. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Durga Prasad Mohapatra

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Jyothi Ahuja, N. (2018). Characterization of Human Knowledge for Intelligent Tutoring. In: Saeed, K., Chaki, N., Pati, B., Bakshi, S., Mohapatra, D. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 563. Springer, Singapore. https://doi.org/10.1007/978-981-10-6872-0_34

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  • DOI: https://doi.org/10.1007/978-981-10-6872-0_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6871-3

  • Online ISBN: 978-981-10-6872-0

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