Generative AI is having a significant impact on how students learn and solve problems. In this wave of generative AI technology, professors may be considering which teaching methods can best contribute to student growth. Are there already professors using generative AI in their classes? In which courses and for what assignments have students used generative AI? What do students think about these classes? This Teaching Tip focuses on the results of a survey conducted over seven days, from June 3 (Monday) to June 10 (Monday), 2024, specifically analyzing the section on "Experiences with Classes Using Generative AI." We hope this analysis of the current use of generative AI in classes and the students' reactions will provide helpful insights as you plan your courses for the next semester.

1. Have you ever taken a course that uses generative AI in the classroom?

  To the question of whether they have ever taken a course that uses generative AI, 29.3% of the 423 respondents, or 124 students, said yes. Meanwhile, 70.7%, or 299 students, said they had not had such an experience. Among the 124 students who reported having taken a course that uses generative AI, 110 provided the specific names of the courses. Based on their responses, the most common courses using generative AI included "Basics and Applications of AI," "Creative Convergence Design," and "Creative Writing.“

  When categorizing the courses specified by students, it was evident that courses related to Artificial Intelligence (AI) & Coding, and data were the ones that most frequently applied generative AI. Notably, our university offers Data Science (DS) courses, and among these, "Basics and Applications of AI," "Computational Thinking and Software Coding," and "Problem Solving and Algorithms" were mentioned the most. Students reported using generative AI in these courses to conduct practical exercises and complete assignments. Additionally, students noted using generative AI for tasks like coding and image generation in other AI-related courses, such as "Unstructured Accounting Data Analysis through Deep Learning," "Intelligent Information Society and AI Ethics," "Application of AI Technology in Classes," and "Planning and Production of Content Using AI." Notably, a significant finding is the application of generative AI in subjects that require creativity. Examples include "Creative Convergence Design" and "Creative Writing," which are mandatory courses for first-year students at our university.

  Additionally, there were responses indicating the application of generative AI in several courses within the fields of Business and Economics. Specific courses included "Management Information Systems," "Internet and Management," "Introduction to Business," "Business Statistics," "Digital Platform Management," and "Big Data and Economic Data Analysis." Additionally, there are also courses in the arts field, such as "Arts and Big Data," "Arts and the Fourth Industrial Revolution," and "Cultural Industry and Data Analysis," where generative AI is used in digital/information convergence subjects that align with the needs of future society.

  Interestingly, even in subjects seemingly distant from generative AI, such as Philosophy/History, Language, Humanities, Chemistry, and Education, there were responses indicating AI usage. In the Philosophy/History field, courses included "Civilization of Humans and Land," "Economic History," and "Introduction to East Asian Philosophy." In the Language field, "Introduction to Linguistics" was mentioned, while the Humanities course "Humanities and Cultural Management" also applied AI. In Chemistry, "Organic Chemistry" and "Inorganic Chemistry" were noted, and in Education, "Understanding Educational Technology" was identified as a course utilizing generative AI.

  To the question, “Which generative AI did you use in the course?” an overwhelming number of students reported using ChatGPT, regardless of the field or subject. A total of 91 students stated they used ChatGPT, representing a high percentage of 82.7% among the 119 students who responded that they used generative AI in their classes. On the other hand, besides ChatGPT, although not as frequently used, students utilized a wide variety of other generative AIs. Some general-purpose generative AIs similar to ChatGPT included Wrtn, Copilot, Gemini, and Claude. Additionally, as shown in the table below, students also reported using specialized generative AIs for specific functions, such as image generation, presentation creation, music creation, comic or webtoon creation, and video generation.

2. For what activities or assignments did you use generative AI?

  To the question, "What activities or assignments did you use generative AI for in the course?" the analysis of open-ended responses revealed the following key points: First, the most common use of generative AI was for generating creative ideas, with 20 students mentioning this purpose. Students used generative AI as a brainstorming tool to generate ideas required for class, to create various ideas for solving social issues, or to find ideas that fit specific constraints or limitations. Some students also mentioned using generative AI to generate ideas for assignments that connect their major with creativity or to explore how to phrase questions to ChatGPT to receive better answers. While using generative AI in class activities that require divergent thinking allows for quick and easy idea generation, it may reduce students' efforts in independent thinking, potentially misaligning with the course's learning objectives. This is a point for professors to consider when designing their courses.

  Second, many students used generative AI for coding or statistical purposes. Most of these students were in programming and data analysis courses, using AI for coding assignments. Relevant courses included "Computational Thinking and Software Coding," "C++ Programming Practice," "Management Information Systems," and "Cultural Industry and Data Analysis." Some students also used generative AI for app development and NLP projects. Given that students actively use AI for coding, clear guidance on how much AI can be used in coding and data analysis tasks in the coursework is essential.

  Third, generative AI was used for content creation. Among these, image generation was the most commonly used, with 7 out of 14 respondents indicating they used generative AI for this purpose. For example, some students reported using generative AI for image generation assignments in the "Basics and Applications of AI" course or creating virtual human images in the "Planning and Production of Content Using AI" course. Additionally, in the "Intelligent Information Society and AI Ethics" course, students generated images depicting future scenarios. Some students also used generative AI to create video scripts, assist in video production, or make webtoons. Furthermore, some students utilized generative AI for content automation tasks, such as blogging and video production. This shows that many students actively used various generative AIs for content creation, and some courses fully embraced and allowed these tools.

  Other Activities included initial hands-on practice with generative AI to get familiar with it and using AI for writing reports or essays. In the writing category, two students specifically mentioned using generative AI for English writing. Overall, students used generative AI in their courses for various purposes, including generating creative ideas, coding, content creation, practice exercises, and report writing.

3. What are students' opinions on classes that use generative AI?

In this survey, students were asked about their experiences using generative AI in classes, specifically regarding their satisfaction, perception of its usefulness, and whether clear guidelines from professors were provided. Overall, the students’ reactions to courses that utilized generative AI were quite positive.

Regarding satisfaction, the highest number of students, 57 (47.1%), rated their experience with a score of 4, followed by 42 students (34.7%) who gave a score of 5. This means that 81.8% (99 students) of respondents were satisfied with their experience using generative AI in classes. On the other hand, only 1 student (0.8%) rated their satisfaction as 1, and 4 students (3.3%) rated it as 2.

  Students also rated the usefulness of their experience with generative AI positively. When asked if their experience using generative AI in class was beneficial, the largest group of students, 52 (42.1%), rated it with a score of 4, and the second largest group, 46 students (38.0%), gave a score of 5. Conversely, only 1 student (0.8%) gave a score of 1, and 8 students (6.6%) rated it with a score of 2. Overall, 80.1% (97 students) responded that their experience using generative AI was beneficial, a percentage similar to the satisfaction rate of students who had used generative AI.

  Students were also asked whether professors provided clear guidelines for using generative AI in class. This question used a 5-point scale and included examples of specific guidelines such as the introduction of generative AI, prompt creation, and the scope of use (which activities are permitted and which are restricted).

Among the responses, the most common score was 4, given by 44 students (36.7%), followed by a score of 5 from 28 students (23.3%). In contrast, only 8 students (6.7%) rated it with a score of 1, which was the lowest response rate.

Overall, 60% of students responded positively, indicating that professors provided clear guidelines. However, this percentage is lower compared to the high levels of satisfaction and perceived usefulness of using generative AI in classes.

 In this Teaching Tip, we examined the current status of classes using generative AI and students' perceptions of them. The responses from students were positive, highlighting the potential for generative AI to be used across various academic fields. Notably, it was found to be useful not only in AI, coding, and data-related courses but also in creativity-related subjects, as well as in diverse areas such as arts, business, and humanities.

  From the generative AI survey results shared in Teaching Tips issues 42, 43, and 44 conducted last June,It is clear that our university has established a foundation for students to experience enriched and diverse learning opportunities by integrating generative AI into various academic disciplines. TOf course, to achieve this, it is essential to design course activities and adjust evaluation methods to ensure that the use of generative AI does not hinder students' independent thinking abilities. Clearly defining the scope of generative AI tools and providing more opportunities for students to think and explore on their own should be prioritized.

  With the start of the second semester just about three weeks away, it's likely that professors are seeking ideas for course planning. We hope that the last three Teaching Tips will help in creating classes that encourage students to think more creatively, learn independently, and develop the skills to solve complex problems. Additionally, We also hope that these tips will help professors consider how the use of generative AI as a learning tool can be effectively integrated into professor’s teaching.

Sang-eun Lee, Min-young Ku, Ye-jin Kim (2024), I Attended a Class Utilizing Generative AI Last Semester (CTL Teaching Tips #44). Seoul: Sungkyunkwan University, Center for Teaching and Learning Innovation.