SMART CLASSROOM: TAXONOMY OF FEATURES, EXISTING TECHNIQUES, CHALLENGES AND RESEARCH OPPORTUNITIES

Timothy Moses; Shamsiya Sadiq

doi:10.4314/njt.2026.3911

Authors

Timothy Moses Department of Computer Science, Faculty of Computing, Federal University of Lafia, NIGERIA.
Shamsiya Sadiq Department of Computer Science, Faculty of Computing, Federal University of Lafia, NIGERIA.

DOI:

https://doi.org/10.4314/njt.2026.3911

Keywords:

Smart classroom, smart classroom taxonomy, challenges in smart classroom, e-learning, information communication technologies

Abstract

Recent years have seen the publication of a sizable quantity of research on smart classrooms. The aftermath of COVID 19 experience has introduced diverse smart classroom platforms with students, instructors, and administrators more engaged and empowered. However, the introduction of smart classrooms still lacks the necessary technological elements and characteristics to compete with the conventional face-to-face teaching methods. Piecemeal adoption will not create the ideal smart classroom environment. This paper, therefore, looked at the taxonomy of features/components that make up an ideal smart classroom environment. A thematic analysis of various existing literatures was used to understand and enumerate the essential tools needed for an ideal smart classroom, present existing works on smart classroom implementation and identify challenges and research opportunities for an ideal smart classroom environment. Findings from this study showed that more robust smart classrooms with a variety of pedagogical methods and adaptive learning are required to fulfil the unique requirements of students; formative assessment will be a useful strategy, helping students transition from being passive to being active learners; the smart learning environment must integrate formal and informal learning to create an autonomous learning environment that supports individual learners; more so from a technological than a pedagogical standpoint, emphasis should be placed on the applications of analytics to teaching and learning.

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