Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Coupling TPACK Instructional Model With Computing Artificial Intelligence Techniques to Determine Technical and Vocational Education Teacher’s Computer and ICT Tools Competence

Version 1 : Received: 26 February 2022 / Approved: 2 March 2022 / Online: 2 March 2022 (12:28:53 CET)
Version 2 : Received: 21 March 2022 / Approved: 22 March 2022 / Online: 22 March 2022 (12:30:20 CET)

How to cite: Kanbul, S.; Adamu, I.; Usman, A.G.; Abba, S.I. Coupling TPACK Instructional Model With Computing Artificial Intelligence Techniques to Determine Technical and Vocational Education Teacher’s Computer and ICT Tools Competence. Preprints 2022, 2022030048 (doi: 10.20944/preprints202203.0048.v1). Kanbul, S.; Adamu, I.; Usman, A.G.; Abba, S.I. Coupling TPACK Instructional Model With Computing Artificial Intelligence Techniques to Determine Technical and Vocational Education Teacher’s Computer and ICT Tools Competence. Preprints 2022, 2022030048 (doi: 10.20944/preprints202203.0048.v1).

Abstract

Nowadays, emerging technologies have changed the places of work through computers and ICT tools, which have revolutionized teaching and learning environments in different ways. In spite of the fact that computers as ICT tools have become part and progressively instrument for instructors used in teaching and learning, most educators can't incorporate them into their teaching and learning process, which results in students being ill-equipped or lacking some necessary skills in the world of work, which leads to low performance and poor production. To tackle this issue, it is essential to develop the tech-nical and vocational education and training (TVET) system by determining the quality of TVE. In this paper, the literature concerning the competence required by TVET teachers towards computer-related instructional technology for classroom teaching and learning was examined through the technological pedagogical content knowledge (TPACK) model. Sixty (60) questionnaires were administered to TVE teachers within six technical colleges of education in north-eastern Nigeria. The data was quantitatively analyzed using tradi-tional linear models, namely multilinear regression (MLR) and artificial intelligence (AI) models, namely artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS), which were developed using MATLAB 9.3 (R2019a), while the classical linear MLR model was developed using SPSS software. The results from our classical study indicated that TVE teachers are competent in computer and some instructional technology usage and show a high correlation between competence and teaching experi-ence and a lower correlation between competence and gender. The goodness of fit shows a good fit of the model. Future studies should examine the application of other linear and non-linear AI techniques.

Keywords

artificial intelligence; TPACK; teachers; competence; computer; TVE

Subject

SOCIAL SCIENCES, Education Studies

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