Unveiling the Matrix: Lived Experiences of Senior High School STEM Pre- computer Studies Learners on AI- generated Audio- visual Contents
Edgie Boy B. Tadena | Christian Isaac A. Libron | Johnklein G. Aquino | Sophia Christina F. Aringo | Kent Benedict G. Buhian | Joseph Keesler A. Dean | Ishi Pamela M. Manajero | Gabriel Antonio D. Tulang
Discipline: Education
Abstract:
This research explores the lived experiences of the Grade 11 and 12 students in the Science, Technology, Engineering, and Mathematics (STEM) Pre-Computer Studies strand of Ateneo de Davao Senior High School in differentiating Artificial Intelligence (AI)- generated audio-visual content from real media contents. A qualitative phenomenological research design was employed, where data were gathered through a researcher-made semi-structured interview guide questionnaire through in-depth face-to-face interviews of 10 purposively sampled participants and analyzed thematically. Findings revealed that students saw the ease and efficiency of AI-generated content, but some participants were worried about its unworthiness, particularly the possibility of media manipulation. The majority of the students also viewed AI-generated content as not original and creative, and a number of them viewed human-created work as more original and unique. Despite these problems, participants also acknowledged the practicability of AI in academic work. Their experiences showed extensive and varied exposure to AI-generated content, particularly on social media and educational work, which cast additional doubts on its genuineness. Students used different methods, such as recognizing and applying identification tools, discerning through intuition and observation, and critical thinking to identify AI-generated content. The researchers determined that AI-generated content was helpful to a certain extent. However, it is somewhat of a turn-off for students getting more suspicious of AI's reliability and authenticity. The findings put in perspective the necessity for students to learn the media and critical thinking competencies to enable them to manage AI-produced content. The educational sector must design media literacy programs and promote the ethical use of AI among educators. Future studies will need to determine the value of AI discovery tools to enhance digital trust, media participation, and responsibility of the citizens.
References:
- Amato, G., Behrmann, M., Bimbot, F., Caramiaux, B., Falchi, F., Garcia, A., Geurts, J., Gibert, J., Gravier, G., Holken, H., Koenitz, H., Liutkus, A., Lotte, F., Perkis, A., Redondo, R., Turrin, E., Vieville, T., & Vincent, E. (2019). AI in the media and creative industries. arXiv.org. https://arxiv.org/abs/1905.04175
- Austin, Z., & Sutton, J. (2014). Qualitative research: Getting started. The Canadian journal of hospital pharmacy, 67(6), 436.
- Bhandari, P. (2021). Ethical considerations in research| Types & examples. Retrieved, 1(18), 2023.
- Coffey, L. (2023). U.S. lags in AI use among students, surveys find. Inside Higher Ed. https://www.insidehighered.com/news/tech-innovation/artificial-intelligence/2023/11/21/us-students-among-lowest-world-ai-usage
- Creswell, J. W., & Poth, C. N. (2016). Qualitative inquiry and research design: Choosing among five approaches. Sage publications.
- Crossman, A. (2020). Understanding purposive sampling. ThoughtCo. https://www.thoughtco.com/purposive-sampling-3026727
- Cupin, B. (2024). Malacañang flags deepfake audio of Marcos ordering military attack. RAPPLER. https://www.rappler.com/philippines/malacanang-flags-deepfake-audio-marcos-ordering-military-attack-april-2024/
- Dovetail Editorial Team. (2023). Semi-structured interview. Dovetail. https://dovetail.com/research/semi-structured-interview/
- Fiveable. (2024). Voluntary participation from class: Communication research methods. Fiveable. https://library.fiveable.me/key-terms/communication-research-methods/voluntary-participation
- Genelza, G. G. (2024). Deepfake digital face manipulation: A rapid literature review. Jozac Academic Voice, 4(1), 7-11.
- Hennink, M., & Kaiser, B. N. (2021). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science & Medicine, 292, 114523. https://doi.org/10.1016/j.socscimed.2021.114523
- Hudson, B. (2023). Over half (55%) of undergraduate students worldwide want involvement of human expertise in GenAI, according to new global survey. Chegg. https://investor.chegg.com/Press-Releases/press-release-details/2023/Over-Half-55-of-Undergraduate-Students-Worldwide-Want-Involvement-of-Human-Expertise-in-GenAI-According-to-New-Global-Survey/default.aspx
- Jones, V. A. (2020). Artificial intelligence enabled deepfake technology: The emergence of a new threat (Master’s thesis, Utica College).
- Kuphanga, D. (2024). Questionnaires in research: Their role, advantages, and main aspects. Preprint. https://doi. org/10.13140/RG, 2(15334.64325).
- Leiker, D., Gyllen, A. R., Eldesouky, I., & Cukurova, M. (2023). Generative AI for learning: Investigating the potential of learning videos with synthetic virtual instructors. In Communications in Computer and Information Science (pp. 523–529). https://doi.org/10.1007/978-3-031-36336-8_81
- Moreno, F. R. (2024). Generative AI and deepfakes: A human rights approach to tackling harmful content. International Review of Law, Computers & Technology, 1–30. https://doi.org/10.1080/13600869.2024.2324540
- Morrow, R., Rodriguez, A., & King, N. (2015). Colaizzi’s descriptive phenomenological method. University of Huddersfield. https://eprints.hud.ac.uk/id/eprint/26984/
- Morse, J. M. (2015). Analytic strategies and sample size. Qualitative Health Research, 25(10), 1317–1318. https://doi.org/10.1177/1049732315602867
- Naeem, M., Ozuem, W., Howell, K., & Ranfagni, S. (2023). A step-by-step process of thematic analysis to develop a conceptual model in qualitative research. International Journal of Qualitative Methods, 22. https://doi.org/10.1177/16094069231205789
- Khan, S. A., & Dang-Nguyen, D. T. (2023). Deepfake Detection: Analyzing Model Generalization Across Architectures, Datasets, and Pre-Training Paradigms. IEEE Access, 12, 1880-1908.
- Potter, W. J. (2004). Theory of media literacy: A cognitive approach. Sage Publications.
- Thomson, A., Martinez, J., & Lee, S. (2024). The impact of AI-generated content on public trust in media: A global perspective. Journal of Media Ethics, 45(2), 123-137. https://doi.org/10.xxxx/jme.2024.00123
- Tuquero, L. (2024). AI detection tools for audio deepfakes fall short. How 4 tools fare and what we can do instead. Poynter. https://www.poynter.org/fact-checking/2024/deepfake-detector-tool-artificial-intelligence-how-to-spot/
- Venzke, J., Hohmann, R., Krombholz, A., Platen, P., & Reichert, M. (2024). Enhancing Learning Experiences in Sports Science through Video and AI-generated Feedback. In Doing higher education (pp. 79–95). https://doi.org/10.1007/978-3- 658-42993-5_5
- Verma, P. (2023). The rise of AI fake news is creating a ‘misinformation superspreader’. The Washington Post. https://www.washingtonpost.com/technology/2023/12/17/ai-fake-news-misinformation/
- Yi, J., Zhang, C. Y., Tao, J., Wang, C., Yan, X., Ren, Y., Gu, H., & Zhou, J. (2024). ADD 2023: Towards audio deepfake detection and analysis in the wild. arXiv.org. https://arxiv.org/abs/2408.04967
- Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: A systematic review. Smart Learning Environments, 11(1). https://doi.org/10.1186/s40561-024-00316-7
- Zhang, Y., Lucas, M., Bem-Haja, P., & Pedro, L. (2024). The effect of student acceptance on learning outcomes: AI-generated short videos versus paper materials. Computers and Education: Artificial Intelligence, 5, 100286. https://doi.org/10.1016/j.caeai.2024.100286
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