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In recent years professional accountancy bodies (e.g., CPA), accreditation institutions (e.g., AACSB) and employers have steadily raised, and continue to raise expectations regarding the need for accounting graduates to demonstrate skills in data analytics. One of the obstacles accounting instructors face in seeking to implement data analytics, however, is that they need access to ample teaching materials. Unfortunately, there are few such resources available for advanced programming languages such as R. While skills in commonly used applications such as Excel are no doubt needed, employers often take these for granted and incremental value is only added if graduates can demonstrate knowledge in using more advanced data analytics tools for decision-making such as coding in programming languages. This, together with the current dearth of resources available to accounting instructors to teach advanced programming languages is what drives motivation for this chapter. Specifically, we develop an intuitive, two-dimensional framework for incorporating R (a widely used open-source analytics tool with a powerful embedded programming language) into the accounting curriculum. Our model uses complexity as an integrating theme. We incorporate complexity into this framework at the dataset level (simple and complex datasets) and at the analytics task level (simple and complex tasks). We demonstrate two-dimensional framework by drawing on authentic simple and complex datasets as well as simple and complex tasks that could readily be incorporated into the accounting curriculum and ultimately add value to businesses. R script programming code are provided for all our illustrations.

This chapter provides preliminary evidence to show that financial accounting students would use generative artificial intelligence (AI) tools to improve their learning if given the opportunity to do so by their instructors. Most students who completed the exercises we used in the study did so diligently and modified their answers after using a generative AI tool in a manner that suggests beneficial effects. It appears that the more prior knowledge a student had about the subject matter, the more beneficial was the experience. Pitfalls still exist, however. For example, students without knowledge of the subject matter struggled with crafting queries and judging the efficacy of their answers. Moreover, although a minority, some students tended to duplicate their original answers without utilizing the responses generated by the generative AI tool. Additionally, certain students merely copied the answers generated by the AI tool without providing any additional critique or analysis. Implications for teaching and learning and opportunities for future research are discussed.

With recent increases in cybersecurity incidents, it is imperative to supplement current accounting curriculum, equip accounting graduates with sufficient knowledge and skills to assess cybersecurity risk, and learn about controls to mitigate such risks. In this chapter, the authors describe 10 teaching modules, supported by 10 professionally produced video series. The authors developed these videos for educating students on cybersecurity and the videos are available free to instructors from other institutions who wish to use them. The videos are filled with insights and advice from our two experts – one a former hacker and the other an experienced cybersecurity professional. This dialogue between two different sides provides a rich discussion that leads to answering many questions that people often have about cybersecurity. Further, in Exhibit 1, this chapter offers a framework for characterizing and analyzing some recent publicized data-breach cases, which can supplement discussion on cybersecurity modules. Instructors can add more cases to this source overtime. Finally, the authors share the analysis of feedback from students who went through the series. The results suggest that the students show interest in the topic, and videos helped them better understand the complexity of cybersecurity risk and controls.