Predictors of Economics Students’ Behavioural Intention to Use Tablets: A Two-Staged Structural Equation Modelling–Artificial Neural Network Approach

Abstract

The government of Ghana, as part of its digitisation agenda, intends to provide all senior high school students in Ghana with tablets that are loaded with textbooks and other educational materials for their studies. This initiative is flaunted as one of the game-changing development that is yet to happen in the country. This study employed a modified unified theory of acceptance and use of technology model to examine Economics students’ behavioural intention to use tablets for learning. The study was quantitative research with a focus on a descriptive cross-sectional survey design. A total of 354 senior high school Economics students were selected for the study. A five-point Likert scale instrument was adapted as the data collection instrument for the study. A two-staged partial least square structural equation modelling–artificial neural network approach was used to analyse the data. The results revealed that effort expectancy, facilitating condition, social influence, and hedonic motivation had a significant positive influence on Economics students’ behavioural intention to use tablets for learning. However, habit and performance expectancy had no significant influence on Economics students’ behavioural intentions. Therefore, it was recommended that the implementation of the student-tablet policy should be hinged on social influence, effort expectancy, facilitating condition, and hedonic motivation (the student’s motivation) to use tablets due to internal satisfaction.

Profiling Differences in Burnout Among Senior High School Teachers in Ghana Based on Their Demographic Characteristics

“…The study used a descriptive cross-sectional survey design, enabling researchers to collect data at a specific point in time without the necessity of manipulating variables or conducting data collection over an extended duration, as highlighted in previous research [46][47][48].…”

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“…The study used a descriptive cross-sectional survey design, enabling researchers to collect data at a specific point in time without the necessity of manipulating variables or conducting data collection over an extended duration, as highlighted in previous research [46][47][48].…”