Enhancing Object-Oriented Programming Pedagogy with an Adaptive Intelligent Tutoring System

  • Methembe Dlamini
  • Wai Sze LeungEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 963)


Challenges to teaching programming include a lack of structured teaching methodologies that are tailored for programming subjects while the benefits of providing programming students with individual attention are not easily addressed due to high student-to-teacher ratios. This paper describes how adaptive intelligent tutoring systems may represent a potential solution assisting teachers in delivering individualized attention to their students while also helping them to discover effective ways of teaching a core programming concept such as object-oriented programming. This paper investigates how adaptability in traditional intelligent tutoring systems are achieved, presenting an adaptive pedagogical model that uses machine learning techniques to discover effective teaching strategies suitable for a particular student. The results of a prototype of the proposed model demonstrate the model’s ability to classify the student models according to their learning style correctly. The knowledge obtained can be applied by educators to make better-informed choices in the formulation of lesson plans that are more appropriate to their students.


Intelligent tutoring systems Pedagogical decision-making Adaptability Artificial intelligence Machine learning 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Academy of Computer Science and Software EngineeringUniversity of JohannesburgJohannesburgSouth Africa

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