Understanding student sentiments towards an automated awarding DApp: a mixed method approach

Purpose Blockchain (BC) has recently gained attention from educational organizations as a reliable and trustworthy technology for storing crucial data. This study aims to explore the factors that influence the students’ intention to use BC to host an automated reward system that is based on objective criteria of students’ performance and activities. Predefined smart contracts would guarantee unbiased judgements and fair rewards. Design/methodology/approach A mixed method approach is used. Based on an iterative rounds of Delphi approach along with a comprehensive literature review, this research proposed an extended Unified Theory of Acceptance and Use of Technology model. The model hypotheses relate performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), perceived innovativeness (PI), trust (TR), perceived security and privacy (S&P), complexity (CX) and enjoyment (EN) to students behavioural intention to use the reward system. The study tests the hypotheses using survey data from 138 students who are familiar with BC technology and its applications. The data analysis is performed using partial least squares-structural equation modelling method. Findings The analysis revealed that PE, EE, PI, TR and EN positively affect students’ intention to use the BC rewarding system, while CX negatively impacts it. Conversely, FC and, interestingly, S&P, which showed a significant influence on trust, were found to be insignificant in influencing students’ intention to use the system. Originality/value This study significantly contributes to the educational technology field by addressing research gaps regarding the adoption and acceptance of BC technology in academia. Firstly, it proposes a basic form of a student reward system. Secondly, it introduces an empirically validated model of students’ adoption, pinpointing factors influencing their readiness to embrace a BC reward system and providing practical implementation insights.