The generative artificial intelligence (AI) tool ChatGPT introduced in November 2022 triggered a discussion on the relevance of traditional memorizing-based learning activities in higher education (Lim et al., 2023). Atlas (2023) described how generative AI might be able to write assignment papers for students. The thinking is that generative AI tools can be detrimental to students’ learning in behaviorist1 assignments. However, generative AI tools could also help sport management instructors teach effectively because young people often enjoy using technology during their studies (Manning et al., 2017). This recent trend of using AI in generating assignment texts relates to at least some parts of sport management courses being taught online (Rayner & Webb, 2021). The use of technology in teaching indicates that ChatGPT and other generative AI tools could improve learning instead of only providing an unethical way to rapidly produce assignments (see Zhai, 2022). This essay aims to present an experiential learning-based project assignment in which ChatGPT could support the efficiency of students’ learning processes and improve their learning experiences.
Experiential Learning
A sport management instructor might benefit from an experiential approach where the students create parts of the course experience by familiarizing themselves with an experiential object (Kolb & Kolb, 2017). Many sport management students are inspired by sporting heroes, who could provide a relevant object to experience via interviews (see Spearman, 2022). For example, the process involved in an athlete becoming a businessperson after a professional sports career could be a topic to work on in an experiential sport management class (cf., Diacin, 2018). Wladimir Klitschko’s success as a venture creator is such an example. ChatGPT and other generative AI tools can help identify information for a project that considers such an athlete hero (Dergaa et al., 2023) both from factual sources, such as case studies (e.g., Groysberg et al., 2020) and popular literature (e.g., Klitschko & Bilen, 2018). Such an assignment might aim to coach students to develop a narrative on their athlete hero (see Rinehart, 2005) focusing on business concepts, albeit the result is likely to be partially fictional (see Ratten & Jones, 2023).
Generative AI
In conjunction with an experiential learning method, generative AI could expedite students’ background research for their assignments (Al Afnan et al., 2023). An assignment type that would highlight the benefits of generative AI would be the kind that does not intend to test the skill of remembering details of theory in a behaviorist manner in multiple-choice exams, for example (Young, 2018). In contrast, the learning outcomes of an assignment benefiting from generative AI might include constructing a deeper interpretation of what the theories mean in practice via experiential learning (see Dees & Hall, 2012; Spearman, 2022). In traditional class teaching, such experiential learning focuses on social interactions between student and instructor instead of an instructor’s lecture materials alone (Kolb & Kolb, 2017). However, because students often use online tools to prepare academic assignments, they could benefit from using ChatGPT as a supplementary information source (Ratten & Jones, 2023). As an online facilitator of efficient information searches guided by an instructor, ChatGPT could promote positive learning experiences. An additional benefit is that students are likely to already have incorporated online courses and tools into their lifestyles (Shreffler et al., 2019). Irrespective of whether a course is delivered in-person or remotely, the purpose of an AI tool used in preparing an assignment is to aid information collection as a “co-creator” of knowledge (Makarius et al., 2020, p. 265).
Example Project Aiming to Improve Student Learning Experiences
Experiential learning techniques applying technology are not new in sports education (Hills & Thomas, 2019). For example, López-Carril et al. (2022) explored using social media tools (e.g., LinkedIn) to achieve interaction-based learning outcomes, and Manning et al. (2017) investigated how Socrative and Twitter could be applied to improve class engagement. However, research does not offer examples of which assignment types could be supported by generative AI tools, such as ChatGPT in a way that AI would support achieving the learning outcomes and improve students’ learning experiences with strong academic integrity. This essay provides an example of such an assignment and its content. Table 1 offers content for an example project, highlighting social interaction with proactive and autonomous dimensions of entrepreneurial orientation (EO) theory (Lumpkin & Dess, 1996). The application of EO in the sport business field includes insights into how athlete entrepreneurs might be innovative in their sport business tasks (Kauppinen, 2022). Those athlete entrepreneurs’ sport business tasks include developing products and services innovatively by applying their physical and emotional experiences in using such products and services during their sports careers (Ratten, 2015).
A Proactive Autonomous Project Assignment for Sport Management Courses Applying ChatGPT in Support of Learning
| Step | In-class activities to be initiated by the course instructor | ChatGPT’s support of students’ learning experience |
|---|---|---|
| 1. Team formation | Ask students to form teams. Inform the participants that they may change teams during the assignment. This permission corresponds to the autonomy dimension in entrepreneurial orientation theory, where a businessperson can determine project development details (Lumpkin & Dess, 1996). | Students could use ChatGPT to benchmark the business team types relevant to sports organizations when forming teams. Using ChatGPT might be a particularly efficient way to unearth information on real sports organizations and sport business professionals (Ratten & Jones, 2023). |
| 2. Athlete selection | Instruct students to select an athlete who has started a business after their sports career and whom the students would be interested in working with. Tell the students to select an athlete they believe has made a positive social impact in their communities (i.e., the operative component of experiential learning; Spence et al., 2009). Advise the students that they will interview that ex-athlete and prepare interview questions with them. | Although engagingly recalling lecture concepts in class can improve the learning experience (Manning et al., 2017), using ChatGPT to identify an athlete contributing to their community could expedite the search. A faster search for athletes in large towns near the school could be beneficial because connecting the course theories to industry practices is the key instead of wasting time finding an interviewee (cf., Spearman, 2022). |
| 3. Material search | Encourage students to use academic references to ensure the information they use is reliable. For example, a team working on Wladimir Klitschko could use case studies (e.g., Groysberg et al., 2020) and popular books on Klitschko (e.g., Klitschko & Bilen, 2018). This information collection aims to include the cognitive component of experiential learning in the students’ project (Spence et al., 2009). | The students should be encouraged to use traditional references (e.g., books, case studies, and journal articles) and other online sources (e.g., ChatGPT) to research what the athlete of their selection has done in business. Acquiring initial insights, perhaps from published interviews (e.g., Ehlen et al., 2018), should be accelerated asking ChatGPT to specify information sources (Ratten & Jones, 2023). Using existing interviews might offer context-specific details on students’ projects (e.g., Spearman, 2022) in addition to using general theories and news. |
| 4. Evaluation criteria preparation | Ask the students to work with the instructor to specify how they would like their assignment to be evaluated so that the evaluation follows the course’s learning outcomes. This task could be done by listing the elements that would be part of their assignment grading. Discuss this list of details with students and formulate evaluation criteria. The instructor’s input to the evaluation criteria should highlight trustworthiness. Make sure that the evaluation criteria include both written and oral elements. Tell the students they will be allowed to revise their assignment paper and give their presentation again after the deadline if they decide to take that option. | Typically, a student follows the evaluation criteria set up by the instructor. For example, a student might interview a facility manager to understand how sport management course concepts could benefit practitioners (Diacin, 2018). If students are involved in setting the evaluation criteria (e.g., by using ChatGPT to find out what other sport management courses’ evaluation criteria look like), they might not only agree on the instructor’s expectations but could also pass on other sport management instructors’ evaluation practices. Consequently, the students’ use of ChatGPT could benefit the course instructor who wants to improve the course’s learning outcomes. |
| 5. New feature ideation | In conjunction with preparing the students’ information search and evaluation criteria, advise students to start investigating the business concept used by their chosen subject. Encourage the students to ideate new product or service features and prepare them to ask about those development ideas in their interviews. Those self-initiated product and service upgrades relate to the proactive approach many innovations require (Lumpkin & Dess, 1996). | Proactiveness in outlining new features is the key for an entrepreneurial person (e.g., an athlete entrepreneur) in the sports industry (Ratten, 2015). Using ChatGPT can enhance the student’s ability to suggest new features for their interviewee’s business, similar to an entrepreneur who takes care of one’s venture (see Ratten & Jones, 2023). An important element in this project step is the students ideating nonexisting features for a selected athlete’s offering instead of only analyzing and evaluating it (see Diacin, 2018). |
| 6. Interviewing the selected athlete | Send students to interview the selected athlete. Before they go, ask them to submit an assignment text outlining their ideas on the athlete’s upgraded business, based on their insights from the interview. The deadline set should impose some time pressure to replicate the time constraints typical of the sports business environment (see Emery et al., 2012). Remind the students that they will have to present the results in class. | Compared to a situation where students would research existing interviews (e.g., Spearman, 2022), meeting a real athlete entrepreneur would require that the student team prepare a set of interview questions.2 ChatGPT could identify example interview questions regarding business development (cf., Diacin, 2018). A relevant set of interview questions can guide the student team’s attempts to convince an athlete to agree to an interview. |
| 7. Presenting in the class | Once the students submit their assignment,3 invite them to present their assignment paper in class. Ask deliberately challenging questions of the type typical in oral examinations (see Susnjak, 2022). When challenging the students (see Lumpkin, 2019) to trigger a potential revision process, the instructor should assume the persona of the athlete interviewed (see Pierce & Middendorf, 2008). In that way, the students experience a realistic feeling of feedback from an athlete in a role-play learning environment (Huq & Gilbert, 2017), not from the behaviorist instructor, following a constructivist logic of offering learning experiences (Kalpana, 2014). Invite the remainder of the class to contribute to the discussion on the presentation. | Although preparing a presentation and giving it in class are typical assessment procedures in sport management education, the student teams could find it more beneficial for their learning experience to focus on the communicational aspects of presenting instead of its technical preparation. ChatGPT is a tool that can collect information from the Internet (Burger et al., 2023). Those who present in the given class and listen could use ChatGPT during a presentation (while listening) to build counterarguments to those presented so that the class discussion could be as challenging for the presenting team as possible. A solid pedagogical reason for students using ChatGPT’s reports instead of their own thinking as feedback is that the instructor could advise how to interpret ChatGPT’s reports critically, especially when the tool is used under time constraints. |
| 8. Presentation evaluation with feedback | Evaluate the assignment paper and presentation according to the evaluation criteria developed in Step 4 in a meeting with the team. Ask students to contribute to the discussion. Record this feedback discussion and share the recording with students. | When using generative AI in teaching, learning soft skills (e.g., communicating answers to a sport management instructor’s questions) might be a more important learning outcome than technical skills. In fact, generative artificial intelligence can provide strong examples in technical tasks, such as preparing information slides. While ChatGPT could contribute some presentation content, the students must learn how to use such materials in the particular context of their assignment (Ratten & Jones, 2023). |
| 9. Trustworthiness improvements | Offer the students an opportunity to revise their work in accordance with the feedback. Highlight that the revised version will be their final submission and promise to award more points than originally awarded for a productive revision. Tell the team that their revised assignment and presentation should compare how the team’s suggestions differ in terms of trustworthiness from those in predatory journals. | The presenting team should be challenged to update their presentation. The target is to make the students understand ChatGPT’s disadvantages (see Ratten & Jones, 2023). For example, the currently unknown amount of untrustworthy information in ChatGPT’s reports (Burger et al., 2023) is a concern that student teams must address to obtain the maximum possible points in this autonomously proactive project. |
| 10. Representing and re-evaluating | Repeat the presenting and evaluation procedure (Step 7) if the students decide to revise their assignment paper and presentation. Re-evaluate their performance and offer them a written feedback file, following the same evaluation criteria outlined in Step 4. | In contrast to Step 8, an instructor could share the revised presentation feedback using social media. The target of using social media in sharing the second feedback is to remind that ChatGPT is a tool to find information (Ratten & Jones, 2023), and other tools can be more relevant for communication (cf., López-Carril et al., 2022; Manning et al., 2017). |
| 11. Learning journal writing | Organize an additional learning journal assignment where the students reflect on how they felt (i.e., the affective component of experiential learning) about their interviewee’s story as a businessperson (see Spence et al., 2009). The critical topics to be presented in the learning journal are the student team’s feelings about their interviewee’s attempts at developing the business (insights from the interview in Step 6) as well as their own feelings about presenting their business development ideas in the front of the demanding class (the Steps 7 and 10). | A learning diary writing (cf., Diacin, 2018; Spearman, 2022) could make the students reflect feelings instead of facts (see Ratten & Jones, 2023). For example, the students’ learning diary could consider demanding and contradictory topics, such as why the athlete they interviewed might emotionally struggle in developing products or services (e.g., because the athlete loves the current content of their offering).4 Reflecting on such feelings would be an important affective learning outcome because ChatGPT struggles with feelings and emotions (Burger et al., 2023). |
As presented in Table 1, an important element of academic integrity in proactive autonomous projects is that such projects could challenge students’ thoughts against well-justified theories (e.g., material not published in predatory journals), which ChatGPT might struggle to work on (Burger et al., 2023). An assignment presented in Table 1 would require an intensive information search before interviewing an experiential object. Such an interviewing task is a traditional sport management assignment discussed by Diacin (2018) and Spearman (2022); an activity that might be made more efficient by utilizing ChatGPT (Ratten & Jones, 2023). Therefore, the pedagogical purpose of such a project-based assignment originates from learning to understand the advantages and disadvantages of generative AI tools. Consequently, the students’ learning should not solely be based on recalling information but to guide them to build a context-specific understanding of the sports industry part of their selection (Spearman, 2022). A behaviorism-based alternative to using these proactive autonomous projects as assignments would be to ban the use of ChatGPT (Lim et al., 2023). However, banning ChatGPT and other generative AI tools might be suboptimal because many sport management students realize technology might help them learn effectively (Manning et al., 2017; Zhai, 2022). Therefore, the proactive autonomous project approach might contribute to students’ perceived return on their investment (i.e., tuition fees and time spent in education).
Conclusions
Compared with existing teaching methods in sport management education, the proactive autonomous projects presented in this essay might improve students’ theory-driven insights (e.g., entrepreneurial orientation [EO]) in their assignments. For example, Diacin’s (2018) assignment to make sense of course concepts by interviewing a facility manager can offer practical insights. Such an interview assignment from which content originates in concepts presented in the class could help build the bridge between the theory and practice of sport management (see Spearman, 2022). However, this essay suggests that encouraging students to use generative AI in conjunction with challenging them to apply theories (e.g., EO) in interview-based assignments might make their learning processes more efficient and improve their learning experience. More specifically, it could be that in such AI-supported learning processes, the students could focus on solving fine-grained and context-specific challenges innovatively. For example, the students could conceptualize why it can be emotionally challenging for their interviewee to develop products and services (i.e., an application of EO; cf., Manning et al., 2017). With AI-supported learning processes, students could also learn important academic skills such as conducting research with strong academic integrity and supporting their results in social communication (cf., López-Carril et al., 2022). Such appropriate research skills might be particularly important for sport business professionals in the era where AI can conduct technical tasks (see Ratten & Jones, 2023). As part of their other experiential teaching practices, sport management instructors might find it beneficial to apply proactive autonomous assignments that aim to support the development of those research skills among their students.
Notes
A relevant learning context for a behaviorist approach could be in language learning where the behaviorist instructor’s target (i.e., changing the students’ behavior) would be achieved by helping students change their ways of communicating in a foreign language (Devaki, 2021).
The intention is that the students would interview an athlete who contributes to their community to learn context-specific details (Spearman, 2022). Learning context-specific details is a learning outcome of which use might overcome the challenge that the students apply AI tools to find answers to general level questions (Ratten & Jones, 2023).
Run a Turnitin or similar plagiarism check on the students’ assignment text (see Lim et al., 2023). If the text scores high in its similarity score, ask the team to explore the implications of that high score for their work (e.g., a lack of sufficient depth of understanding and own interpretation). Share insights on why plagiarism matters in the context of their assignment and presentation (Chan & Tsi, 2023).
Such an emotional struggle could be identified in a situation where an athlete entrepreneur prefers to keep producing their offering without making changes that could serve their customers’ needs. For example, a reason why an athlete entrepreneur might not prefer changes can originate in a feeling that their offering must be superior, because its content was designed as a result of applying that athlete entrepreneur’s personal sports career experiences (see Klitschko & Bilen, 2018).
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