Today’s accountants find themselves performing more and more tasks that require data analytics skills. Accounting fields such as audit, tax, financial and managerial accounting all use big data to find patterns that impact decision making and organizational strategy. Data analytics can help accountants and management better understand their organizations from an external and internal perspective. Data analytics helps answer what’s happened (descriptive analysis), why it happened (diagnostic) what the future may look like (predictive) and what direction should be taken next (prescriptive). Accountants are accustomed to looking at problems that need recommendations or solutions. Data Analytic skills enhance the accountant’s ability to quickly determine trends or irregularities in order to more rapidly identify potential problems and find solutions.
Markus and I feel it is important for students to develop data analytic competencies early in their educational coursework as well as reinforcing or “stepping up” these competencies throughout the curriculum. So, the question we often hear is, “How do we get started incorporating data analytics into our courses and curriculum”?
Markus and I have created a “step-up” approach to data analytics that can help. This approach has worked well with our students. We have found that integrating data analytics into our courses has increased synergy, engagement, collaboration, attendance, as well as student interest in the potential of data analytics. Additionally, this approach helps us prepare graduates with the required 21st-century skills.
Since Markus and I teach at different institutions and in different parts of the country, we believe our approach to incorporating data analytics is seamless and has a pedagogical purpose that can be replicated into many accounting courses, by any instructor. The first step in this model is to introduce students to Big Data concepts and problems looking for solutions. Next students interpret already prepared data visualization reports from Power BI and/or Tableau. This gives students the opportunity to see the results of data analytics before they work with any raw data. After students understand the big picture of data analytics, they begin working with data visualization modeling using Power BI (https://powerbi.microsoft.com/en-us/downloads/) and/or Tableau (https://www.tableau.com/). Finally, students are introduced to coding exercises. The Hour of Code (https://hourofcode.com/us, and Code Academy (https://www.codecademy.com/), both offer free coding tutorials that expose students to the world of coding. Introducing students to coding is not intended to replace information systems courses or create proficient coders. The goal of this activity is to expose students to the basic concepts of coding in order to increase student interest and a desire to learn more about coding on their own. Ultimately, we have found that this approach improves critical thinking skills as it pushes students into higher levels of Bloom’s Taxonomy.
Technology and education are continuously evolving. Integrating data analytics into accounting courses across the curriculum allow faculty and students to stay current with industry and educational trends. In addition, data analytics integration allows us to address AAA/AICPA Pathways, AACSB Accreditation Standards and AICPA Technology and Tools Competencies.
To learn more about getting started with integrating Data Analytics into your courses, visit our February 2019 blog at https://teachingandlearningtoolbox.wordpress.com/2019/02/28/integrating-data-analytics-into-your-accounting-courses/.
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