Abstract:

With the arrival of generative artificial intelligence (GenAI), lecturers must reconsider traditional tasks, instructions and criteria to reinvent their assessment practices to promote creativity and integrity in higher education. Lecturers need to do this to ensure that they are assessing students and not GenAI. Students should be required to demonstrate creativity in their work, drawing upon their own ideas and competencies rather than replicating the work of others or having it generated by GenAI. This paper introduces the AICAI model (Academic Integrity and Creativity in the Age of Artificial Intelligence), which emphasizes the use of authentic assessments designed to foster creativity, integrity, and the demonstration of individual authorship.

The model proposes to show how to reinvent assessments tasks by critically examining each component of the model through the lens of academic honesty. Key considerations include:
- professional characteristics of the lecturer such as teaching philosophy and values.
- desired objectives and learning outcomes for the assignments.
- types of assessment that are appropriate for students’ needs.

The model also guides lecturers when considering the role of GenAI with the following factors.
- When is it relevant for students to use GenAI and when does it become cognitive offloading which can be detrimental to learning?
- What constitutes an authentic, real-world task, and how can it be designed to be meaningful and relevant to engage students to do the work and not farm it out to GenAI?
- Are instructions and assessment criteria communicated in various ways, clearly and frequently to ensure that all students can understand the task required of them?

Using this model to design assessments that cultivate student engagement should diminish the temptation to plagiarize and lead to better learning outcomes for students. By combining pedagogical theory and research, the AICAI model proposed in this paper brings out the challenges for teachers assess with new tools but also the opportunities to promote academic integrity in higher education.

Keywords:

Higher education, generative artificial intelligence, assessment, academic integrity, evaluation.