Challenge
The Centre for Teaching and Learning (CTL) at Durham College in Oshawa, Ontario, seconded two professors on a part-time basis from the Faculty of Business to be advocates, models and instructors for other faculty on the educational use and capabilities of Generative Artificial Intelligence (GenAI). Professor Jonathan Carrigan is Program Coordinator in Marketing and Professor Corey Gill is the Program Coordinator in Human Resources. They were early adopters and continue to expand their GenAI applications in the classroom and share their expertise with their colleagues.
The Centre for Teaching and Learning provides faculty training in all aspects of GenAI, as well as access to an extensive range of tools, resources and statements on ethics, privacy and security on its web site, Generative GenAI | CTL.
Professor Carrigan continually develops, evaluates and adopts new uses of GenAI that he integrates in all his classes, course materials, assignments and activities. He teaches students the core concepts of GenAI and how best to leverage its capacities. Through in-class practice and additional assignments, students develop critical awareness and the skills to use GenAI most effectively for their learning and eventual careers. His motivation stems from his belief that in the workplaces of today and the future, those who are most effective in their use of GenAI are most likely to succeed.
In working with other faculty in his role with the CTL, Professor Carrigan presents his experience as a self-described “guinea pig” in testing and revising GenAI innovations, sharing his successes and challenges with his colleagues as guides to enhance their teaching effectiveness and the success of their students.
Experimentation
Each of the courses Professor Carrigan teaches in the Marketing program is developed, delivered and assessed through carefully structured and constantly evaluated interaction with GenAI. Student development of the skills for quality applications of GenAI and critical awareness of its capacities and limitations are essential learning outcomes for each course.
Course Development: Professor Carrigan creates Custom GPTs - course specific applications of ChatGPT – instructing it how to assist with specific course tasks. For each course, he uploads course outlines, goals and outcomes, resources, instructional design guides, assignments, and other material. Through ongoing prompts, revisions, feedback and questions with GenAI, he develops the Custom GPT as a Subject Matter Expert (SME) on a specific course. He can then work with the Custom GPT asking it to review the uploaded material and offer suggestions for course and class structure, for alternatives for new assignments, and perform other tasks of course development and revision. All these tasks require his prompting and assessment. He constantly updates documents in the Custom GPT to keep courses fresh and engaging. Professor Carrigan no longer uses textbooks but instructs GenAI to produce quality and specific content that he monitors for accuracy and completeness.
Learning Coach: To support students in their learning, he creates a learning coach for students by uploading the course outline, learning objectives, assignment instructions and resources to a Custom GPT. Students can use this tool for personalized, always available support. They can request summaries of content, ask questions, attempt previous tests with access to answers and take advantage of a translation function to request information in their own languages. As an additional aid for students, Professor Carrigan uses GenAI to create a 15-minute podcast summarizing a three-hour class, to complement other resources in the Custom GPT.
Activities: One of Professor Carrigan’s goals is that students learn to engage with GenAI in a style that recognizes the parallels between people management and GenAI management. Similar to when they are collaborating with colleagues, students who use clear communication with GenAI on their expectations enhance the likelihood of quality results. Professor Carrigan intends that students use GenAI, not like a Google search engine, but as a remote Subject Matter Expert with a voice in the process. Students go beyond prompting GenAI for specified output to interacting with it like a work partner, asking if it has questions and comments beyond simply providing information. GenAI provides suggestions that students assess and then respond to GenAI with feedback and detailed requests for improved output. This interaction between the students and GenAI emphasizes collaboration rather than a one-time ‘ask and receive’ relationship, fostering professional skills transferrable to a work environment.
A Specific Application: For a course on Market Research, Professor Carrigan uses GenAI to offer students experience in qualitative research through an exercise in gathering data through interviews. Rather than have the students do mock interviews with each other, GenAI performs as interview subjects. Students first receive instruction on using GenAI for this type of application, as well as detailed instructions and grading criteria for the assignment. Working in small groups, they receive a short business case scenario, from which they determine the business challenge, the research objective and three research questions. Professor Carrigan sets up three interview subjects through prompting GenAI about the character of each interviewee and clear directions for their roles. The GenAI Interview subjects do not know what questions the students will ask but use the uploaded information to create responses. Students submit their research questions, record the interactions and responses, analyze the results and offer a proposal for a solution for the business problem. GenAI does not aid the students in the analysis of the interviews and development of solution. Professor Carrigan has GenAI assess the assignment, including the interview transcripts, according to his instructions and criteria, but reviews this GenAI output in detail. This activity takes place in class, lasting about an hour. At a later point in the course, students on an individual basis, use their experience with GenAI to develop a full research plan for an organizational issue which Professor Carrigan assesses as part of the student’s final grade.
Results
During in-class activities involving GenAI, all students are working with the same resources. They submit their work which is immediately and anonymously graded by GenAI. As GenAI posts the grades, wide discrepancies become evident. The class then discusses the grades and how those with the best results used GenAI more effectively. A common issue is generic input producing generic results, leading to recognition of need for specificity and how to achieve it. Students recognize what GenAI can achieve, given clear and specific prompts and continued revision.
Classroom use and discussion of GenAI underline how students are accountable for their results as GenAI follows directions and can make mistakes. This learning supports the development of professionalism in students, recognizing expectations for behaviour in their careers.
Students have responded positively to the integration of GenAI throughout the course as they recognize they are learning skills they need and that offer them advantages in the workplace. They are also able to produce improved assignments for grading in the courses, access additional study materials and effectively search for their own resources.
Next Improvement Steps
In the first class at the start of each course, Professor Carrigan acknowledges that students could probably use GenAI to cheat their way through the course, and possibly their entire program. He then explains and illustrates the consequences of this behaviour - they will fail to acquire the judgement and skills necessary for professional and creative use of GenAI. After graduation, the cheaters will find themselves accountable for the quality and accuracy of GenAI in professional settings but without the skills to accomplish this. Their more successful colleagues will be those who have learned how to work effectively with GenAI.
Professor Carrigan discusses the issue of accountability with students, emphasizing that GenAI is a flawed tool that lies convincingly and that they are responsible for the quality and reliability of its output. The students determine the intent, purpose, standards, level of detail, tone of voice, and most importantly, the accuracy of what GenAI produces. They are responsible for reviewing, revising, and prompting GenAI until the output is ready to be used. Convincing students of this is a challenge, but course-based experience reinforces the necessity of acquiring the skills and accepting the accountability.
The preparation time devoted to the development of GenAI prompts, guides and resources can be extensive. On the other hand, a properly created GenAI guide for grading, or class assignments or resources can save time during delivery and assessment while providing quality tools for students.
Potential
In working with faculty at Durham College, Professor Carrigan stresses that they are the experts at their job and their content. At the same time, GenAI offers potential benefits and threats to education. To counter some of the threats and to benefit from its capacities, professors’ proactive engagement with GenAI can improve the value and impact of their courses. In addition, students who are taught with GenAI integrated into classes and assignments can come to recognize how well-structured interaction with GenAI improves their learning, academic results and career opportunities.
Professor Carrigan proposes that if educators become active in defining the role of GenAI in education, they can retain control of and enhance their roles. Governments and educational institutions need to develop a better sense of what is coming and create strategies for involvement in developments and reactions to changes.
For Further Information
Jonathan Carrigan
Professor and Program Coordinator
Marketing
School of Business
GenAI Consultant
Centre for Teaching and Learning
Durham College
Oshawa, Ontario
[email protected]
