Tag: AI

When I asked Melissa to tell me a bit about how she came to teach at Camosun, she called herself ‘the accidental teacher,’ saying, “I worked for Tourism Victoria for 22 years, finishing my time there as the senior VP of Marketing and Communications. Then I went into consulting and wandered around the world for a while. But something haunted me in the back of my mind. Back in the late 1980s, I had taught part time at Camosun in what was then the new certificate in tourism management. And I loved it. So, when Marina Jaffey called me to say they were looking for someone to teach their media communications course, I jumped at the chance. I taught on a term basis for awhile, and then they couldn’t get rid of me.”

Right now, Melissa teaches Global Business Strategies, Services Marketing, Marketing Communications Portfolio, and her new love, Current Trends in Marketing (MARK 485). MARK 485 is a new course (taught for the first time in Winter 2024) designed to cover a topic that marketing is influenced by and/or that marketing can influence, for example climate change or Artificial Intelligence (AI), and the topic is meant to change every few years. When I asked my students in Fall 2023 what topic we should cover they almost unanimously said AI.” And it is the story of MARK 485 that Melissa shared with me.

But before we talked about this new course and how it worked, I asked Melissa what she enjoys most about teaching. “I confess when I taught in the 80s, I was the sage on the stage. I loved moving from one end of the stage to the other and delivering stories with great anecdotes. But while that was well received back then, when I returned to teaching, students didn’t seem to respond in the same way, so, I started to introduce activities into my teaching. Even if I have to deliver a lecture (to set the tone for example,) I try to make it interactive, and I get the most amazing adrenaline rush from seeing a group of students engaging and thinking out loud. And when I walk out of a class and say to myself, well, I learned something new today too, I love that!”

In the MARK 485 course, Melissa took student engagement even further turning almost everything over to the students. There were 25 students in the first offering, and Marketing and AI was the topic. “It was a risk for me because AI is changing constantly. I had done some Scheduled Development the summer before to prepare, but so much had changed by the time I taught the course that I knew this would truly be a collaboration between me and the students.” To support the students in co-creating the course as it moved along, Melissa walked the students through Bloom’s taxonomy. “I showed them how their four years in the program progressed, from first-year courses where they were asked to write multiple-choice exams that tested their recall and worked my way up to the most exciting part of taxonomy, explaining how they were now analyzing, creating, and using their critical thinking skills. Then I introduced them to the BOPPPS model for lesson planning. No one had heard of it, although no doubt they had seen a host of instructors model it for them in past courses.” The final piece was talking to students about how to read and analyze the journal articles Melissa had chosen to support possible class-led session topics. Pulling from an activity she had encountered in a class she took in an MEd class at Simon Fraser University, Melissa picked a 12-page article and handed it out to students. Students looked horrified, but she walked them through how to read a journal article, how to analyze it, and how to look for three quotes in the article that resonated the most with them. “I also had them write a guided reflection (for a 2% grade) on each article before class so they would come prepared for the student led class sessions. If they hadn’t read the articles, I didn’t grade them harshly because I knew that reading the articles themselves was just the first step, and hopefully they would learn a lot more from their peers during these student-led sessions.”

With the foundation for the student-led class sessions laid, student teams then picked their topics from Melissa’s suggested list. “The first group’s class session topic focused on AI, marketing, and stakeholder relationships. This team modeled the BOPPPS approach brilliantly and the session was very interactive. The team leading the class session appeared confident and engaged, setting a high bar for the rest of the class-led sessions.”

About halfway through the class, Melissa raised the topic of AI and the students’ future. “I asked how many of them would be graduating that term and planning to go directly into marketing jobs. Then I told them that there would be a good chance they would be hired in part because of how current their AI education is, including their newly gained knowledge about the impact of AI on marketing (and vice versa.) Helping students see how AI likely will fit into their careers and how they likely will take an early leadership role in making significant recommendations to their employers, perhaps even proposing how a company should go about rolling out an AI strategy integrated with their marketing plan, made this course all the more practical and significant to this first class of MARK 485 students.”

Melissa also had students write critical reflections three times during the term. “For the first one, they could pick any topic related to AI and marketing.  Many of the students wrote about being worried whether they were going to have a long-term career in marketing, or if AI would take it away from them, and I, in turn, was worried that I had sparked this anxiety. But by the second reflection, I started to see a different theme: that AI is just another tool in their marketing toolkit. The evolution from anxiety, through to ‘I think I’ve got it,’ to their final reflection where AI was not seen as a significant threat to their long-term marketing careers, was very gratifying.”

Melissa based the final class assignment on an article written by a marketing professor about an experiment he conducted on himself. “He’d given himself 30 minutes to engage with an AI tool to write a marketing plan, from the initial gathering of research, evaluating the external market and finding what separates you from your competitors, identifying your target markets, developing the marketing mix, all the way to determining conclusions and recommendations for action. So, I replicated this experiment and had students work on it in teams. Each student had 30 minutes to explore one or more AI tools. Their team then had to pick a company, and hand the controls over to one or more the AI tools to “write” a marketing plan for the company. After seeing the results of the experiment, student teams wrote a paper describing the experience, including analyzing how effective the AI tools they used were in producing an effective marketing plan. Finally, I asked them to make three to five recommendations for a senior marketing director in an organization about how someone in this role should move forward with AI.” Melissa gave them class time to work on the assignment and watched them work. “I loved seeing the playfulness of their experimentation, their curiosity, and their critical analysis.” On presentation day, students reported that while certain AI tools collect and report secondary research with an impressive depth and level of accuracy, the AI tools used currently fall down when it comes to creativity. “One team had AI write a marketing plan for Crocs, but when they tried to direct AI to create a print ad, the results were comical. The Crocs pictured in one of their ads had toes sticking out through the holes, another had extra toes on the side. We laughed, but they presented a mature analysis concluding that the number one thing they need to learn as marketers is how to communicate with AI tools effectively so these tools can help deliver desired results.” Overall students proposed practical, well reasoned recommendations for themselves moving forward as soon-to-be marketing professionals and for the advice and guidance they can provide for their employers.

I wondered what was next for this course. “The curriculum for MARK 485 was designed by Joan Yates (retired faculty member) who observed that even though the course would be student led, instructor preparation is enormous, meaning that a topic should be taught at least twice.” So, this winter, AI will once again be the focus of the course, although Melissa wonders how much it will have changed by then. She also worries a bit that the next offering might not be as successful as this first one was. “Numerous students have told me it was their favorite class, and I also looked forward to coming to class every time. But sometimes those magical experiences don’t repeat. Since students are becoming more knowledgeable about AI now and the course doesn’t run again until Winter 2025, I wonder: will I have the same success with this approach?”

Regardless of what may happen by Winter 2025, Melissa is sure AI will still be an important and relevant topic. “I say to my students, when I was a young marketer, it was so much easier for me. There were a few daily newspapers that were seen by consumers as “the authority,” the 6:00 pm news, only three American TV networks, CBC, and CTV. So, when you set out to write a promotional plan, that was all what you had to draw on. But today you can’t keep up with the number of for-marketing communications options that have been popping up over the past 10-plus years, so I empathize with them finding their way through this more complex marketing landscape, now compounded with the addition of AI for marketing. But at the same time, I tell them how excited I am watching them at the start of this AI era in marketing, because I was there for the first consumer websites, the first live e-commerce sites, the first social media platforms – and we had to decide which ones to focus on for our work. And now they will be the ones deciding which AI tools to recommend for and use in their own workplaces.”

Over the past few months, CETL educational developers have been working with faculty across the college exploring the advantages and disadvantages of Generative Artificial Intelligence (GenAI) in teaching and learning.  As we talked to more and more faculty, we discovered several who were already working GenAI into their assessments and talking about its implications with their students and I wanted to share some of their stories with you.  So here is the first of these interviews focused on using GenAI in the classroom with Tim, a full-time Instructor in the School of Business at Camosun who teaches everything from International Management to Marketing Research to Workplace Professionalism.

When I asked Tim how he is integrating GenAI into his teaching, he told me “I’d been teaching about AI for the last ten years or so when it became apparent that something like GenAI was imminent.  Up until recently, I’ve taught it in a very general way and stayed abreast of its development.  But with the rise of ChatGPT over the past year, I was asked, along with three other Instructors in the School of Business, if I would be willing to put some Professional Development time into figuring out what a good response to AI might be.  We were starting to see people misusing it from an academic honesty perspective.”

Tim spent quite a bit of time over summer 2023 keeping an eye on the various AIs releases (at one point there were about a dozen new English language AIs released every day of the week) and by the end of August, he had built a list categorizing about 80 in an Excel sheet that anyone can access.

As Tim explored, he concluded that “It’s a mistake to be afraid of AI. What I tell students, is: You’ve been told that AI is coming for your job. It’s not. Somebody who knows how to use AI is coming for your job. That means you had better get out ahead of the curve and learn how to use it effectively.”

Tim explained that his approach is to turn artificial intelligence into a Research Assistant. “When I went to college and grad school, the Internet as we know it didn’t exist. Instead, we spent time going to the library, digging through card catalogs, and writing notes on cue cards.  Took forever. The Internet changed all that. But while it’s become easy to find information, it’s hard to sift through because there’s so much out there. I think AI is most useful in an academic world as a Research Assistant because it can find information and put ideas together for you in minutes rather than in hours or more. That said, we still have to teach students how to determine what information is valid.”

In other words, Tim encourages students to use GenAI tools to find ideas but to personally review the sources and websites where the ideas come from.  “You have to be careful because AIs sometimes make things up. For example, I asked an AI tool to create a timeline of Camosun College history, and it did in two minutes. Beautifully presented. All the key events were there, but they were placed in the wrong years, and some were out by ten or more years. The AI had done the research, found the events, but when it couldn’t figure out when these events happened relevant to each other, it made things up and presented them as fact.  If I didn’t know Camosun’s history, I’d have believed it.” Lesson learned: “Use AI to do the initial research and collect basic information, but then go dig and make sure that the information was used correctly.”

I wondered how Tim supports with students as they work with AI tools in class and for assessments, and aside from warning them about plagiarism and checking original sources, he works with them to ensure they understand what they are presenting (in Tim’s classes, students present their papers live).  “I come from government where if the Minister of Advanced Education has a question in the middle of your presentation, she doesn’t wait until the end to ask.  So, to replicate real-world experiences, I interrupt students in the middle of their presentations and pepper them with questions to make sure they understand what they are presenting.  Demonstrating comprehension is critically important. It’s also important they understand that while AI will do the writing for them, if fail to develop their ability to write, they will harm their professional and personal development.” “In a very real sense, learning to write is learning to think.”

Tim also teaches his students how to use various AI tools in his 400-level class.  “I teach them how to use ChatGPT and the one built into Bing which is the easiest to use, as well as how to get the tool to show you the original sources and provide APA citations.” “In my 400-level course, student teams do an hour-long group-presentation on a particular topic each week. I give them a Backgrounder on their topic, and their job is to boil it down to something that can be explained in an hour to people who know nothing about it. For example, for a recent presentation on Fake News, I had the student team use the Gamma AI tool to build a PowerPoint-like website.  It does the research, but also allows you to edit the results.”  Tim sees Gamma AI and other GenAI tools as the next step up from the Internet and says, “If we don’t get on board and learn how to use them, we will be left behind by those who do.”

In his lower-level classes, Tim’s approach to students using AI is a bit different.  “In the Market Research class students take after completing Intro level Statistics, AI can’t really help. Student teams conduct Primary Research, interviewing real clients from the community, design a survey, obtain ethics approval, collect data, and analyze it using Excel. Then we do Boardroom Simulations in the last two weeks of class where they present their Findings, Conclusions, the Options, and Recommendations to the Board, of which I am the Chair.  It’s great fun!”

In Tim’s Workplace Professionalism course, “students complete a series of short presentations on various topics, and AI can be very helpful in conducting secondary research.  I check their comprehension in real-time by asking questions during their presentations.  I think in the future academic research skills are likely to change much as they did when we learned to use the Internet.  This means we have to focus on comprehension and application.”

When I asked how students are reacting to AI, Tim said “They’re not afraid of it at all. They live on their screens, and this is just another way of getting something done. The industrious ones will use AI to build a framework and then they will do the deep dive themselves because they’re curious. The ones who are looking for shortcuts will not do the deep dive and just pretend they understand. That’s why it’s on us to check for comprehension.”

I wondered how Tim’s colleagues have been reacting to all of this.  “It depends on what you’re teaching. If I was still teaching Statistics, AI wouldn’t bother me at all because there are already thousands of videos online students can watch until they understand the concepts.  It’s when students must engage in research that it becomes dangerous. In fact, some of my colleagues are playing with the idea of accepting only peer-reviewed sources because it is more challenging for AI to work behind paywalls (although there are ways around this).”

As we reached the end of our conversation, I asked Tim what is in the future for GenAI and his classes, and he indicated he would still be teaching GenAI tools to his 400-level courses but said “we’ll see when I review their final papers this term whether I will have to begin checking for comprehension even more now.”

As for GenAI itself, Tim says “It’s not clear to me where AI is going to end up. On November 1, 50 countries (including Canada) – countries who recognize that AI has unintended consequences for economies – met at Bletchley Park and signed a declaration about how to regulate AI going forward. But regulations or not, we’re rapidly reaching the stage where you either use GenAI or get replaced by someone who knows how to use it. That’s why I’m teaching it.”