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A Comprehensive Model for Augmented Confidence Based Learning (ACBL)

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Learning in the Age of Digital and Green Transition (ICL 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 634))

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Abstract

Confidence Based Learning (CBL) is a state-of-the art method of Teaching and Learning System (TLS), where the customized content is delivered to a typical learner based on his lacunas in terms of knowledge level as well as the level of confidence in that knowledge. This system is of immense importance in imparting training to the workforce where the performance of the personnel is dependent to human live and properties and in case of deviation in the performance it may lead to a catastrophic event. The CBL based system mainly consists of three phases namely diagnose, prescribe and learning. The system prior to delivery of any content identifies the lacunas in terms of knowledge and level of confidence. Once the gaps in knowledge and confidence level are identified, a customized prescription of learning plan is provided to an individual learner. The learner learns using the customized content and takes the assessment for obtaining mastery. However, in context to this, there is a lack of an enhance and comprehensive framework for CBL based system, which will provide a blueprint for development of applications related to this new TLS. The authors in this research have identified the voids and propose a comprehensive framework which is compared to the existing available solutions which shows considerable improvement with respect to methodology and practical implications.

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Acknowledgement

The authors of this manuscript acknowledge the support provided by the members of faculty and staff at NITTTR, Kolkata and University of Kalyani, Kalyani, India.

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Authors and Affiliations

  1. National Institute of Technical Teachers’ Training and Research, Kolkata, India

    Rajeev Chatterjee

  2. University of Kalyani, Kalyani, West Bengal, India

    Jyotsna Kumar Mandal & Sadhu Prasad Kar

Authors
  1. Rajeev Chatterjee
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  2. Jyotsna Kumar Mandal
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  3. Sadhu Prasad Kar
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Corresponding author

Correspondence to Rajeev Chatterjee .

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Editors and Affiliations

  1. CTI Global, Frankfurt/Main, Germany

    Michael E. Auer

  2. Federal Ministry of Education, Science and Research, Vienna, Austria

    Wolfgang Pachatz

  3. Tallinn University of Technology, Tallinn, Estonia

    Tiia Rüütmann

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Chatterjee, R., Mandal, J.K., Kar, S.P. (2023). A Comprehensive Model for Augmented Confidence Based Learning (ACBL). In: Auer, M.E., Pachatz, W., Rüütmann, T. (eds) Learning in the Age of Digital and Green Transition. ICL 2022. Lecture Notes in Networks and Systems, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-031-26190-9_6

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