BCM212 Portfolio – Opinion Piece

Higher education is a transformative journey that empowers students to explore their passions, acquire knowledge, and develop the skills necessary for their future careers. It is a time of growth and self-discovery, where individuals embark on a path towards personal and professional fulfilment. However, in an ever-advancing world, the rapid progress and unprecedented nature of Artificial Intelligence (AI) has introduced a new layer of complexity, stirring both excitement and anxiety among current students.

The research project I undertook aimed to investigate BCM212 students’ perceptions of Artificial Intelligence and examine whether the recent advancements in AI technologies have affected their learning attitudes and career ambitions.

My research methodology involved surveying BCM212 students and analysing their responses. 

Throughout this research, I made it a priority to uphold ethical standards and ensure a responsible approach. I wanted to gather information in a manner that respected the rights and well-being of the participants. To achieve this, I ensured participants were provided with clear information about the research and obtained their informed consent. I included a question in the survey asking participants if they had read the participant information and consent, indicating that their responses would be used in a research project on student perceptions of AI technologies. I also outlined the fact that they could withdraw their involvement at any time.

THE SURVEY

The survey aimed to gather data on participants’ levels of concern about AI technologies and their impact on career ambitions across different majors. Additionally, it sought to understand the range of emotions evoked by an image depicting AI entities engaged in creative tasks traditionally associated with humans.

Based on the survey answers, I identified a few trends that can be observed regarding the link between majors/career ambitions and the degree of anxiety surrounding AI. To illustrate these findings, I decided to create the following graphs to document these statistics and define the link. 

Using this information, I interpreted the data in the following ways:

• Participants with majors in Visual Communication Design and Digital and Social Media expressed higher levels of anxiety regarding the impact of AI technologies on their future job prospects. These majors are closely associated with creative industries where individuals rely on their artistic and communication skills. The potential threat of AI technologies replacing human creativity and job roles in these fields may contribute to higher levels of anxiety. 

• Varied Responses in Other Majors: Participants who major in Marketing Communication and Advertising, as well as Screen Media Production exhibited a range of emotions, including happiness, hopefulness, and concern. Some participants expressed slight levels of anxiety, while others appeared more optimistic about the potential benefits and ethical considerations surrounding AI technologies. This suggests that attitudes and anxiety levels can vary even within the same major, indicating the influence of individual perspectives and experiences.

• There is a general agreement across all participants with the statement that universities should do more to address students’ anxieties and concerns about the impact of AI technologies on their future job prospects.

These findings suggest a call to action for decision-makers within the University of Wollongong (and relevant faculties) to acknowledge and address the anxieties and concerns that students have about the impact of AI technologies on their future job prospects. 

Despite the varied responses, the results provide student insights that could inform curriculum design, specifically in creative majors such as Visual Communication Design and Digital and Social Media, where participants expressed typically higher levels of anxiety. This could be achieved through the development of support programs, curriculum enhancements, and initiatives to equip students with the necessary skills to thrive in an AI-driven job market. By integrating AI technologies into the curriculum, student anxiety could potentially be reduced by gaining practical exposure and developing the skills necessary to thrive in an increasingly AI-centred world.

In an article published by The Australia Today, academics from universities in Sydney and Hong Kong (Danny Liu, Adam Bridgeman, and Cecilia Ka Yuk Chan) support this suggestion through a discussion on the growing demand for universities to incorporate AI technology into education. They highlight student desire to acquire AI-related skills and knowledge that are increasingly relevant in various industries and emphasise the need for institutions to include AI education in the curriculum to enhance students’ learning experiences and provide them with valuable skills in a rapidly evolving technological landscape (Liu, Bridgeman & Ka Yuk Chan 2023).

The findings of my research also align with existing research papers on the topic, demonstrating a similarity in concerns expressed by students across various disciplines. The findings of a similar study, ‘What drives students’ AI learning behaviour: a perspective of AI anxiety’, emphasise the importance of addressing student anxieties and equipping them with the necessary skills to navigate the evolving job market.

“Efforts to reduce learning anxiety could be instrumental in improving students’ perception of AI”

(Wang et al. 2022)

The findings of the study further reinforce the importance of a proposed redesign to the BCM curriculum in order to reduce student AI anxiety.

“Anxiety caused by AI job replacement will have a far greater impact on the rewards of learning AI-related skills than the pleasure of learning itself.”

(Wang et al. 2022)

Although my findings are consistent with existing knowledge on the topic, it is essential to recognise the limitations of the research. 

Firstly, the sample size is very small (13 participant answers), which limits the accuracy of the findings in a broader context. Furthermore, the range of participants was skewed with nearly 50% being Marketing Communication and Advertising students. As a result, the analysis based on majors can only provide a rough interpretation due to the disproportionate representation. To enhance the reliability and validity, future studies could include a larger and more diverse sample of participants.

Additionally, another limitation of my research was that it primarily relied on quantitative data obtained through survey responses. While this approach provides valuable insights into participants’ perceptions and emotions, it does not offer in-depth information that can be captured through qualitative research methods. As such, future studies could incorporate more qualitative research methods, such as interviews or focus groups, to obtain a more comprehensive understanding of student perceptions.

In conclusion, whilst the findings of my research provide valuable insights around the diverse emotions and perspectives surrounding AI, it is important to recognise and consider the limitations of my research when interpreting and applying the results. Overall, the findings highlight the need to address students’ concerns about AI and improve support in preparation for the changing job market to reduce student anxiety.

RESEARCH NARRATIVE

Throughout the Semester, I engaged in various activities to gather data and ensure ethical practices were followed for my research project.

To begin, I brainstormed research ideas based on topics that were timely and relevant. After receiving advice and feedback from my peers, I then narrowed down my three key questions (available here) to choose my topic: “Has the emergence of AI technologies impacted the career ambitions and anxieties of students in creative industries”. 

I then created a Research Proposal (available here) and conducted further research into this idea, exploring relevant academic sources and articles to obtain a strong foundation of knowledge to understand the existing research landscape. 

Moving onto Task 2, I completed the ‘Project and Design Management Template’, which involved outlining the aims and significance of my research, how I will conduct ethical research practice, my method and justification, and risk and time management planning. Based on the positive feedback I received from this assessment, I was confident going into the data collection phase of this project.

I then designed an online survey questionnaire to collect data from BCM212 students and distributed the link to prospective participants via Twitter (#BCM212), as well as in-class and through a class spreadsheet.

The survey included questions aimed at assessing BCM212 students’ perceptions of AI, their career ambitions, and their levels of anxiety related to AI technologies. The 12 questions consisted of quantitative and qualitative research methods, including open and close-ended questions, demographic questions, and rating scales. I took careful steps to ensure the clarity and reliability of the questions, making them easily understandable and relevant to the research objectives. 

I ensured participants were provided with clear information about the research and obtained their informed consent. I included a question in the survey asking participants if they had read the participant information and consent, indicating that their responses would be used in a research project on student perceptions of AI technologies. I also outlined the fact that all reported data would remain anonymous and that they could withdraw their involvement at any time.

Upon the completion of the data collection phase, I carefully analysed the survey results, taking note of any patterns or trends that emerged. I then graphed the data to interpret it and identify significant relationships between variables, such as the level of anxiety and participants’ majors/career ambitions. The qualitative data provided deeper insights into participants’ perceptions, supporting the conclusions of my report.

Available here: Survey results

However, it’s important to recognise the limitations of this project. Due to time and resource constraints, the findings should be interpreted with caution. Further research is needed to validate the results and gain a broader understanding of the topic.

BIBLIOGRAPHY

Sources cited in opinion piece:

• Kalpokiene, J & Kalpokas, I 2023, ‘Creative encounters of a posthuman kind – anthropocentric law, artificial intelligence, and art’, Technology in Society, vol. 72, p. 102197.
• Liu, D, Bridgeman, A & Ka Yuk Chan, C 2023, Students want universities to teach them how to use AI in education – The Australia Today, The Australia Today, viewed 5 June 2023, <https://www.theaustraliatoday.com.au/students-want-universities-to-teach-them-how-to-use-ai-in-education/>.
• Wang, Y-M, Wei, C-L, Lin, H-H, Wang, S-C & Wang, Y-S 2022, ‘What drives students’ AI learning behavior: a perspective of AI anxiety’, Interactive Learning Environments, pp. 1–17.
• Linnik, I 2022, Will AI Take Over the World? 5 Jobs That AI Will Replace in the Future and 5 Jobs That AI Won’t Be Able to Handle, Softteco.

Resources used throughout research:

• Wang, Y-Y & Wang, Y-S 2019, ‘Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior’, Interactive Learning Environments, pp. 1–16, viewed 10 February 2020, <https://www.tandfonline.com/doi/full/10.1080/10494820.2019.1674887>.
• EtQ, Inc. 2014, Risk Assessment: Creating a Risk Matrix.
• O’Donnell, J 2011, How to make a simple Gantt chart, The Research Whisperer.
• Science Daily 2021, Artificial Intelligence News, ScienceDaily.
• Gong, B, Nugent, JP, Guest, W, Parker, W, Chang, PJ, Khosa, F & Nicolaou, S 2019, ‘Influence of Artificial Intelligence on Canadian Medical Students’ Preference for Radiology Specialty: A National Survey Study’, Academic Radiology, vol. 26, no. 4, pp. 566–577, viewed 25 March 2021, <https://www.sciencedirect.com/science/article/pii/S1076633218304719>.
• Media, Entertainment & Arts Alliance 2023, MEAA Journalist Code of Ethics, MEAA.
• National Health and Medical Research Council 2018, Human Research Ethics Committees | NHMRC, Nhmrc.gov.au.
• Harvard University 2007, TIP SHEET ON QUESTION WORDING, 17 November.
• Qualtrics n.d., Convenience sampling method: How and when to use it? // Qualtrics, Qualtrics.
• Brake, D, Gammelby, A, Heise, N, Henriksen, A, Hongladarom, S, Jobin, A, Kinder-Kurlanda, K, Lim, S, Locatelli, E, Markham, A, Reilly, P & Tiidenberg, K 2019, Internet research: ethical guidelines 3.0 association of Internet researchers.
• Pollfish 2019, Qualitative vs Quantitative Survey Questions | Pollfish, Pollfish Resources.

Acknowledgement of any writing AI used:

I used ChatGBT to provide a brief outline that I used to summarise the article: Students want universities to teach them how to use AI in education (Liu, Bridgeman & Ka Yuk Chan 2023). After reading the article, I was unsure how to break the information down into key areas, therefore, I used ChatGBT to do this for me. Using the information it generated, I double-checked its relevancy/accuracy and composed a paragraph.