Artificial intelligence (AI) has become a tool used in class. The integration of technology into education has always been progressive (Holmes, Bialik and Fadel 2019). Some educators do not have training to effectively use AI in class, which can limit the capacity to design courses based on AI (Amado-Salvatierra et al. 2024). In addition, the lack of understanding of how the use of AI can be applied pedagogically can potentially dissuade the integration of AI (AFZAL et al. 2024). The objective of this article is to share examples of IA entry prompts to generate case studies as a learning tool to help students learn about the subjects of the course and learning results.
Case studies offer students the possibility of learning and / or strengthening what they have already learned. When using AI to create case studies, it is important to use correct prompts to obtain an appropriate outing. For example, only one invite asking the AI to give five cases out of five different subjects may not provide sufficient details. However, the incitement of the AI to generate a case study on a subject will potentially generate a more appropriate case. Using so many details in the initial prompt helps to provide a better outing. An example of an IA prompt could be: “Suppose the role of a teacher teacher an introductory accounting course. Generate a case study for students to use to learn the very basic format of a balance sheet. Make sure the case study is relevant in the real world. The role, the declared course and subject can be adapted to adapt to an appropriate class. The case study generated must be examined to verify alignment with specific subjects (s) and learning results.
The cases must be generated in a format that allows a measurable assessment of student learning. The specification of this detail in an AI prompt when generating a case study will help ensure that AI output is measurable. An example of an additional AI prompt to include with the previous example could be: “The case study is to include an assignment part which allows teachers to measure the performance of the student”. A careful assessment of the outlet of this prompt must be carried out to guarantee the alignment of the subject.
Once an appropriate case study has been developed, AI can provide a rating section for the case study generated by AI by encouraging AI to generate a section. An example of an AI prompt to generate a classification section is: “Providing a classification section that aligns with this case study”. An examination of the use of the classification section to measure subjects and appropriate learning is recommended.
At any time in this process, AI can be used to change the output. For example, an appropriate AI prompt to modify something in a case study could be: “Update the case study generated above to include 5 assets, 3 liabilities and 2 equity accounts. At any time of revision, the assessment of the exit generated previously (for example, the section) may have to be regenerated. It is recommended to note the invites of AI which generate an acceptable exit so that these prompts can be reused for future case studies generated by AI.
Another outing of the case study could be a response sheet to use teachers and share with students thereafter to allow performance self-assessment. An example of IA prompt could be: “Provide the response sheet for this case study. Make sure to include the details of all the calculations and definitions of the key terms.
To add additional depth to the use of AI in class, teachers may want to create two case studies on the same subject: one to be carried out by the student without the use of AI, and one with the use of AI. This two -case study method could allow students to learn to use AI appropriately. A list of AI entry prompts appropriate to students to use would help students design appropriate AI prompts. This effort would help students because research indicates that they have a decrease in the feeling of preparation when they have insufficient exposure to the AI application (HSIAO and HAN 2023).
An example of an AI prompt to produce a two -case study with and without the use of AI is: “Suppose the role of an accounting teacher teacher an introductory chalter. Generate a case study so that students can use the very basic format of a balance sheet without the use of AI. In addition, generate a second case study with the same format as the first case study that students can use to learn the very basic format of a balance sheet with the use of AI. Make sure the case study is relevant in the real world. The case study is to include an assignment portion that allows teachers to measure the student’s performance.
Using this method in two cases, teachers can measure changes in students’ performance, allowing students and teachers to see how AI use can help understand the subject of case study. Providing students’ response sheets will allow them to compare their performance and critically analyze the release of AI.
A precious measure to assess would be the time spent by the student in each case. A line element on the case study can be added by AI by including an invite such as: “Provide an element at the end of the case to allow students to report the time they spent for each case studies”.
In addition to the non-AI case and the AI user’s user, students can also carry out conceptual assessments. Such evaluations can be qualitative, allowing the student to critically assess how AI helps efficiency and precision on the subject. Another objective could be qualitative assessments on how AI can be used in their future career depending on the subject specified in the case study. For example, a conceptual question could explain how someone in their profession would benefit from AI to help them perform better in their future career. If these cases are created to be used throughout a course term, students can have a clearer image of how AI could be applied to their class experience.
In conclusion, teachers can use AI to create tools, such as case studies focused on specific subjects, to expose students to real world scenarios and strengthen students’ learning. It is very important, because teachers and students use AI, to recognize that current AI outputs are not always accurate. Professors and students must assess the accuracy of the output generated by AI and adjust if necessary. Experimenting with various AI entries will allow teachers to become more comfortable with the use of AI. Recognition of the role of AI in class does not replace teachers, but it can help provide excellent learning opportunities to students and to demonstrate how AI can be used effectively.
Rhonda Gilreath is an associate professor of accounting at Tiffin University in northwestern Ohio. She likes to explore new opportunities to implement in class to improve educational approaches to prepare her students for preparation for career.
References
AFZAAL, M., Shanshan, X., Yan, D. and Younas, M. 2024. “Cartography of the integration of artificial intelligence in education: a decade of innovation and impact (2013-2023) – A bibliometric analysis.” IEEE access 12: 113275–113299. https://doi.org/10.1109/access.2024.3443313.
Amado-Salvatierra, HR, Morales-Chan, M., Hernandez-Rizzardini, R., and Rosales, M. 2024. “Exploration of educators’ perceptions: integration of artificial intelligence in higher education.” In 2024 IEEE World Engineering Education Conference (EDUNINE)1–5. https://doi.org/10.1109/edunine60625.2024.10500578.
Holmes, W., Bialik, M. and Fadel, C. 2019. Artificial intelligence in education: promises and implications for teaching and learning. Boston: Curriculum overhaul center.
Hsiao, D. and Han, L. 2023. “The impact of data analysis and artificial intelligence on the future accounting profession: prospects of accounting students.” Journal of Theoretical Accounting Research 19 (1): 70–100.