An Adaptive Web Based Educational System Using HMM Approach for C Programming

  • Aditya KhampariaEmail author
  • Babita Pandey
  • Aman Singh
  • Shrasti Tiwari
  • Parampreet Kaur
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 955)


The usage of web enabled e-learning systems has been increased for education in recent years. In present study, a Hidden Markov Model (HMM) driven approach is used to predict the future lecture topics or paths of C programming those has been accessed by students in an adaptive web enabled educational system. Data has been preprocessed and collected from e-learning system then HMM parameters were adjusted and used modified algorithm to train the data. This system help faculty to identified the student’s problems and provide assistance to them as per their need. The experiment result shows the accuracy of prediction in proposed system is 80.23% which is better than neural network multilayer perceptron model whose accuracy rate is 78.15%.


Prediction E-learning HMM Perceptron Questionnaire 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Aditya Khamparia
    • 1
  • Babita Pandey
    • 1
  • Aman Singh
    • 1
  • Shrasti Tiwari
    • 1
  • Parampreet Kaur
    • 1
  1. 1.Lovely Professional UniversityPhagwaraIndia

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