Data Analytics in an Undergraduate Accountancy Programme: The Spaced Retrieval Method

The accountancy profession is now challenged by the pace of technological advancement and the ubiquitous digitalization leading to data explosion and advanced analytics. Digital technology is also replacing mundane tasks and manual work which accountants undertook in the past. Besides data analytics skills, accountants now need to possess critical thinking skills, knowledge of data science tools and communication skills. Consequently, equipping accounting professionals with data analytics skills is critical. Professional accounting bodies address this need by emphasizing continuing professional education and developing guidelines for data analytics. At the same time, higher education institutions are taking the initiative to integrate data analytics into their accounting curricula. However, given the numerous professional accreditation requirements that higher education institutions must fulfill, a big challenge remains for any institution to insert rigorous data analytics training into their existing curriculum. This chapter describes the development of a data analytics roadmap for undergraduate accountancy education—from reviewing our academic and industry data analytics curricula and evaluating existing modules that could be integrated with relevant data analytics topics, to seeking feedback from industry partners regarding the curriculum model we had developed. In delivering our curricula across the levels of study, a spaced retrieval teaching technique was opted to ensure that students could progressively develop data analytics competencies.