Portrait of António Azevedo

Gamification in Public Relations Strategies

School of Communication and Media Studies - Polytechnic University of Lisbon

AI was integrated into the course as a creative and research support tool across several practical exercises and project development stages. Students used AI tools mainly for ideation, research, and structuring communication strategies within the gaming and esports ecosystem. The primary goal was to help students explore ideas faster while learning to critically evaluate and refine AI-generated outputs. A distinctive element was the combination of hands-on creative tasks — campaign ideation, customised campaign song commercials, and mind mapping — with structured reflection on the limitations and responsible use of AI.

The strongest ideas consistently originated from the students themselves, with AI mainly serving as a tool to expand, refine, and deepen those initial concepts.

António Azevedo

A distinctive element was the combination of hands-on creative tasks — campaign ideation, customised campaign song commercials, and mind mapping — with structured reflection on the limitations and responsible use of AI.

António Azevedo

Learning outcomes

  1. Describe the cultural relevance and economic impact of the gaming and esports industries.
  2. Identify communication challenges and opportunities for brands in gaming environments.
  3. Evaluate communication platforms, channels, and content formats used in gaming.
  4. Design strategic communication plans adapted to gaming communities.
  5. Create campaign proposals for endemic and non-endemic brands within the gaming ecosystem.
  6. Analyse esports as a professional communication and branding environment.
  7. Investigate emerging trends in gaming and assess their implications for brand strategies.

Assessment

AI usage was included as part of continuous assessment through in-class exercises. Where the use of AI was required, evaluation focused less on the final output and more on how students used the tools. Students were assessed on the depth of their interaction with AI, the quality of their prompts, and their ability to critically evaluate and refine AI-generated suggestions.

Evaluation

At the beginning of the course, students completed a pre-survey to assess their prior knowledge and usage of AI tools. At the end of the semester, a post-survey was conducted to understand how their perceptions and practices had evolved. Additionally, a focus group was organised with students from several courses participating in the pilot programme. Feedback was also collected informally throughout the semester.

  • KPIs tracked: No
  • Formal institutional evaluation: No

Risk management

Most AI usage took place during in-class exercises, which allowed the lecturer to monitor how students interacted with the tools and ensure that AI supported learning rather than replacing critical thinking. Students were asked to share and discuss their prompts and interaction process, so assessment focused on how AI was used rather than only on the final outcome. Conducting AI-supported activities in a supervised classroom setting proved effective in maintaining engagement and preventing misuse of the tools.

Challenges

Students inputting the assignment brief directly into AI tools and asking them to generate complete solutions, leading to similar prompts producing similar responses across students
These situations were addressed directly with students, using them as examples to explain why this approach limited learning outcomes. The strategy was continuous reinforcement of proper AI usage, emphasising that the tools should support ideation and exploration rather than replace student effort. Individual feedback and class discussions encouraged deeper prompting and greater personalisation.

Scalability

AI is already a reality in basically all professional fields and can be relevant to a wide range of academic disciplines. One important requirement would be the development of institutional guidelines for responsible AI use. Additionally, as AI adoption grows, institutions could support integration by providing access to selected AI tools through institutional licences or educational partnerships, ensuring equitable access to platforms that may otherwise have limitations in their free versions.