Smartphones today are ubiquitous and are influencing our everyday life and have unsettled many age-old tasks, activities, devices, gadgets, tools and technologies with their redefined usage and definitions. They have relatively strong computing capabilities built into small sizes that offer versatile communication possibilities and are equipped with intuitive operating systems, smart sensors and applications. They have a great potential to be used as learning devices owing to their connectivity and versatility to suit various learning styles and learner preferences. The understanding of parameters which govern the customised integration of smartphones is the key to a successful acceptance and assimilation of these devices as learning tools. Technology acceptance models are used in studies aimed at predicting and explaining the user’s behaviour towards the acceptance and usage of new technologies. This study adopted the Unified Theory of Acceptance and Use of Technology (UTAUT2) model along with educational context, gender and educational level as moderators. This study at the outset hypothesised that the educational context plays a key role as a moderator in the acceptance of smartphones as learning tools and hence will influence the variables in the UTAUT2 model. Context based mobile learning also assures learners that learning content can be matched, adapted or selected according to their current learning situation and contextual educational environment. To understand smartphone technology integration, this research compared the two context groups, one from the College of Engineering (CX1) and the other from the College of Education (CX2), both from the same university cohort. They were chosen according to the contrasting differences in their programs, curriculum, pedagogy, student aptitudes and required skills. The two groups were sampled from a university in New Zealand. This research terms these two groups as two different “contexts” of education. The survey instrument was designed and developed after conducting Pilot studies. The final survey questionnaire was distributed and about 310 were collected from the university students. This study then adopted a two-step confirmatory factor analysis technique. In the first step, it extracted the best items using the Principal Component Analysis factor extraction method. In the second stage, the structure model was developed to assess the four set hypotheses of this research. The results from the data analysis of this research strongly confirm the influence of educational context as a moderator in the acceptance of smartphones as mobile learning tools. The major contributions of this research are that the UTAUT2 model was found to be a significant predictor of the student's behaviour intention to use smartphones as mobile learning tools. The other key contribution of this research was redefining the two original UTAUT2 constructs, Social Influence and Facilitating Conditions. The Social Influence construct was redefined as the influence of peers, classmates and teaching faculty to use smartphones for learning. Facilitating Conditions was redefined as receiving educational help and support through smartphone connectivity and communication. Researchers typically assess the effect of moderators on technology acceptance by considering effects across disciplines/courses. This research focussed on multilevel moderator comparisons (inter and intra groups) to assess the effects of the educational context moderator on acceptance, current models of predictors of acceptance and the moderating influences of gender and educational level. Such inter and intra comparisons should inform our understanding of how a highly personalised device such as the smartphone can be integrated contextually for students as a learning tool. The findings highlight the potential factors that may enable the acceptance of smartphone-based mobile learning within a university environment.