Research Article
BibTex RIS Cite

İletişim Fakültesi Öğrencilerinin Algoritma Okuryazarlığı ve Algoritmik Karar Verme Konusundaki Algılarının İncelenmesi

Year 2025, Issue: 50, 195 - 214

Abstract

Günümüz dijital ortamı algoritma teknolojisi tarafından yönetilmektedir. Bazı çalışmalar, algoritmaların bu dijital dünyada insan çıkarlarını ve kararlarını haksız bir şekilde etkilediğini öne sürerken, öğrenciler arasında algoritma okuryazarlığına ve algoritmaların karar vermedeki rolüne odaklanan araştırmalar nispeten azdır. Bu nedenle, bu çalışma öğrencilerin algoritmalarla ilgili bilgi ve deneyimlerinin yanı sıra algoritmaların karar verme biçimleri üzerindeki rolünü değerlendirmek için algoritma okuryazarlıklarını ortaya çıkarmayı amaçlamaktadır. Çalışmada, algoritmaların adil olmadığı ve algoritmaya dayalı sistemlerde uygulanan veri kümelerinin ve modellerinin gerçekliğin tarafsız temsillerini sağlamadığı hipotezlerinden yola çıkılarak odak grup görüşmeleri gerçekleştirilmiştir. Bu çalışmaya toplam 32 iletişim fakültesi öğrencisi katılmış ve algoritmaların karar verme sürecindeki rolüne ilişkin algılarını aktarmışlardır. Araştırma ayrıca öğrencilerin algoritma okuryazarlığı ile ilgili deneyimlerini ve kararlarının algoritmaların sunduklarının ötesine geçip geçmediğini de incelemiştir. Tematik olarak analiz edilen bulgular, algoritmaların karar vermede hem faydalar hem de zorluklar sunan çifte bir rol oynadığını ve algoritmaların, özellikle tecimsel çıkarlar söz konusu olduğunda, yeniden önyargı sergilediğini ve kullanıcıları manipüle ettiğini göstermektedir. Özellikle, öğrencilerin algoritmaların reklamların ve medyanın doğasının etkisi altında belirli bir içerik türünü önceliklendirerek kullanıcıların seçimlerini sınırlayabileceğini ve böylece haksız bir önyargı yaratabileceğini düşündükleri tespit edilmiştir. Bu nedenle, gelecekteki araştırmalar, şeffaflıklarını artırmak ve sosyal manipülasyon risklerini azaltmak için algoritmaların tasarımına ve düzenlenmesine odaklanmalıdır.

References

  • Abrams, L. R., McBride, C. M., Hooker, G. W., Cappella, J. N., & Koehly, L. M. (2015). The Many Facets of Genetic Literacy: Assessing the Scalability of Multiple Measures for Broad Use in Survey Research. PLOS ONE, 10(10), e0141532. https://doi.org/10.1371/journal.pone.0141532
  • Airoldi, M., & Rokka, J. (2022). Algorithmic consumer culture. Consumption Markets & Culture, 25(5), 411–428. https://doi.org/10.1080/10253866.2022.2084726
  • Archambault, S., Ramachandran, S., Acosta, E., & Fu, S. (2024). Ethical dimensions of algorithmic literacy for college students: Case studies and cross-disciplinary connections. The Journal of Academic Librarianship, 50(3).
  • Beck, L. C., Trombetta, W. L., & Share, S. (1986). Using focus group sessions before decisions are made. North Carolina Medical Journal, 47(2), 73–74.
  • Brkan, M. (2019). Do algorithms rule the world? Algorithmic decision-making and data protection in the framework of the GDPR and beyond. International Journal of Law and Information Technology, 27(2), 91–121. https://doi.org/10.1093/ijlit/eay017
  • Burton, J. W., Stein, M., & Jensen, T. B. (2020). A systematic review of algorithm aversion in augmented decision making. Journal of Behavioral Decision Making, 33(2), 220–239. https://doi.org/10.1002/bdm.2155
  • Chouldechova, A., Benavides-Prado, D., Fialko, O., & Vaithianathan, R. (2018). A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. In Conference on Fairness, Accountability and Transparency. PMLR, 134–148.
  • Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., & Huq, A. (2017). Algorithmic Decision Making and the Cost of Fairness. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 797–806. https://doi.org/10.1145/3097983.3098095
  • DeVito, M. A. (2021). Adaptive Folk Theorization as a Path to Algorithmic Literacy on Changing Platforms. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 1–38. https://doi.org/10.1145/3476080
  • Dogruel, L. (2021). What is Algorithm Literacy?: A Conceptualization and Challenges Regarding its Empirical Measurement (M. Taddicken & C. Schumann, Eds.). Freie Universität Berlin. https://doi.org/10.48541/DCR.V9.3
  • Dogruel, L., Facciorusso, D., & Stark, B. (2022). ‘I’m still the master of the machine.’ Internet users’ awareness of algorithmic decision-making and their perception of its effect on their autonomy. Information, Communication & Society, 25(9), 1311–1332. https://doi.org/10.1080/1369118X.2020.1863999
  • Dogruel, L., Masur, P., & Joeckel, S. (2022). Development and Validation of an Algorithm Literacy Scale for Internet Users. Communication Methods and Measures, 16(2), 115–133. https://doi.org/10.1080/19312458.2021.1968361
  • Elish, M. C., & Boyd, D. (2018). Situating methods in the magic of Big Data and AI. Communication Monographs, 85(1), 57–80. https://doi.org/10.1080/03637751.2017.1375130
  • Estrela, M., Semedo, G., Roque, F., Ferreira, P. L., & Herdeiro, M. T. (2023). Sociodemographic determinants of digital health literacy: A systematic review and meta-analysis. International Journal of Medical Informatics, 177, 105124. https://doi.org/10.1016/j.ijmedinf.2023.105124
  • Evren, M., & Koyuncu, A. A. (2024). Algorithm Domination As A New Surveillance System. Yeni Medya Dergisi. https://doi.org/10.55609/yenimedya.1528528
  • Gran, A. B., Booth, P., & Bucher, T. (2021). To be or not to be algorithm aware: A question of a new digital divide? Information, Communication & Society, 24(12), 1779–1796. https://doi.org/10.1080/1369118X.2020.1736124
  • Hobbs, R. (2020). Propaganda in an Age of Algorithmic Personalization: Expanding Literacy Research and Practice. Reading Research Quarterly, 55(3), 521–533. https://doi.org/10.1002/rrq.301
  • Jansen, S. C. (2022). What Was Artificial Intelligence? (1st ed., Vol. 1). mediastudies.press. https://doi.org/10.32376/3f8575cb.0cc62523
  • Kalır, H. (2023). Siyah Veri, Beyaz Algoritmalar : Veri Sömürgecisinin Dünya Modelini Reddetmek ve Veriyi Sömürgesizleştirmek Mümkün Mü ? Mülkiye Dergisi, 47(6), 1469- 1504.
  • Karakoç Keskin, E. (2024). Dijital Medya Ortamında Rızanın Algoritmik İnşası: Eleştirel Algoritma Çalışmaları Perspektifinde Bir Tartışma. Yeni Medya, (16), 329-353.
  • Karakoç Keskin, E. & Demirel, E. S. (2025). Algoritmik Medya İçeriği Farkındalık Ölçeğinin (AMCA-scale) Türkçe Uyarlaması ve Ölçek Faktörleri Arasındaki İlişkilerin Analizi. Journal of Akdeniz University Faculty of Communication/Akdeniz Iletişim, (48).
  • Karaman, M. K., & Yiğit, İ. (2024). Yeni Medya Bölümü Öğrencilerinin Algoritma Okuryazarlıkları Üzerine Bir Araştırma. Erciyes İletişim Dergisi, 11(1), 155-180.
  • Katamba, M. (2023). Book Review: Understanding Risks and Crises Through the Media. (15), 351-354.
  • Katamba, M., & Kayıhan, B. (2024). A Descriptive Analysis for the Future of Journalism Studies in Emerging Artificial Intelligence (AI) and the Case of NewsGPT platform. Yeni Medya Dergisi. https://doi.org/10.55609/yenimedya.1427421
  • Kayihan, B., Nari̇n, B., Firat, D., & Firat, F. (2021). Algoritmalar, Yapay Zeka ve Makine Öğrenimi Ekseninde Gazetecilik Etiği: Uluslararası Akademik Dergilere Yönelik Bir İnceleme. TRT Akademi, 6(12), 296–327. https://doi.org/10.37679/trta.900086
  • Köchling, A., & Wehner, M. C. (2020). Discriminated by an algorithm: A systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. Business Research, 13(3), 795–848. https://doi.org/10.1007/s40685-020-00134-w
  • Latzer, M., & Festic, N. (2019). A guideline for understanding and measuring algorithmic governance in everyday life. Internet Policy Review, 8(2). https://doi.org/10.14763/2019.2.1415
  • Latzer, M., Hollnbuchner, K., Just, N., & Saurwein, F. (2016). The economics of algorithmic selection on the Internet. In J. M. Bauer & M. Latzer (Eds.), Handbook on the Economics of the Internet. Edward Elgar Publishing. https://doi.org/10.4337/9780857939852.00028
  • Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), 2053951718756684. https://doi.org/10.1177/2053951718756684
  • Lepri, B., Oliver, N., Letouzé, E., Pentland, A., & Vinck, P. (2018). Fair, Transparent, and Accountable Algorithmic Decision-making Processes: The Premise, the Proposed Solutions, and the Open Challenges. Philosophy & Technology, 31(4), 611–627. https://doi.org/10.1007/s13347-017-0279-x
  • Lomborg, S., & Kapsch, P. H. (2020). Decoding algorithms. Media, Culture & Society, 42(5), 745–761. https://doi.org/10.1177/0163443719855301
  • Longhofer, W., & Winchester, D. (Eds.). (2023). Social theory re-wired: New connections to classical and contemporary perspectives (Third edition). Routledge, Taylor & Francis Group.
  • Low, B., Ehret, C., & Hagh, A. (2025). Algorithmic imaginings and critical digital literacy on #BookTok. New Media & Society, 27(4), 2336–2353. https://doi.org/10.1177/14614448231206466
  • Lutkevich, B., & Gillis, A. S. (2024). What is a bot? TechTarget. https://www.techtarget.com/whatis/definition/bot-robo
  • Mahmud, H., Islam, A. K. M. N., Ahmed, S. I., & Smolander, K. (2022). What influences algorithmic decision-making? A systematic literature review on algorithm aversion. Technological Forecasting and Social Change, 175, 121390. https://doi.org/10.1016/j.techfore.2021.121390
  • Marmolejo-Ramos, F., Marrone, R., Korolkiewicz, M., Gabriel, F., Siemens, G., Joksimovic, S., Yamada, Y., Mori, Y., Rahwan, T., Sahakyan, M., Sonna, B., Meirmanov, A., Bolatov, A., Som, B., Ndukaihe, I., Arinze, N. C., Kundrát, J., Skanderová, L., Ngo, V.-G., … Tejada, J. (2025). Factors influencing trust in algorithmic decision-making: An indirect scenario-based experiment. Frontiers in Artificial Intelligence, 7, 1465605. https://doi.org/10.3389/frai.2024.1465605
  • Möhlmann, M., & Zalmanson, L. (2017). Hands on the wheel: Navigating algorithmic management and Uber drivers’ autonomy, proceedings of the International Conference on Information Systems.
  • Moylan, R., & Code, J. (2024). Algorithmic futures: An analysis of teacher professional digital competence frameworks through an algorithm literacy lens. Teachers and Teaching, 30(4), 452–470. https://doi.org/10.1080/13540602.2023.2263732
  • Oeldorf-Hirsch, A., & Neubaum, G. (2023). Attitudinal and behavioral correlates of algorithmic awareness among German and U.S. social media users. Journal of Computer-Mediated Communication, 28(5), zmad035. https://doi.org/10.1093/jcmc/zmad035
  • Oeldorf-Hirsch, A., & Neubaum, G. (2025). What do we know about algorithmic literacy? The status quo and a research agenda for a growing field. New Media & Society, 27(2), 681–701. https://doi.org/10.1177/14614448231182662
  • Park, Y. J. (2013). Digital Literacy and Privacy Behavior Online. Communication Research, 40(2), 215–236. https://doi.org/10.1177/0093650211418338
  • Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.
  • Şenyüz, B. (2023). Algoritma okuryazarlığı. In Yapay Zeka ve İletişim. Kriter Yayınları.
  • Shin, D. (2020). How do users interact with algorithm recommender systems? The interaction of users, algorithms, and performance. Computers in Human Behavior, 109, 106344. https://doi.org/10.1016/j.chb.2020.106344
  • Tsuei, H.-J., Tsai, W.-H., Pan, F.-T., & Tzeng, G.-H. (2020). Improving search engine optimization (SEO) by using hybrid modified MCDM models. Artificial Intelligence Review, 53(1), 1–16. https://doi.org/10.1007/s10462-018-9644-0
  • Tucker, C. (2018). Privacy, algorithms, and artificial intelligence. In The economics of artificial intelligence: An agenda (pp. 423-437.).
  • Wegner, P. (1997). Why interaction is more powerful than algorithms. Communications of the ACM, 40(5), 80–91. https://doi.org/10.1145/253769.253801
  • Wilkinson, S. (1998). Focus group methodology: A review. International Journal of Social Research Methodology, 1(3), 181–203. https://doi.org/10.1080/13645579.1998.10846874
  • Woods, S. A., Ahmed, S., Nikolaou, I., Costa, A. C., & Anderson, N. R. (2020). Personnel selection in the digital age: A review of validity and applicant reactions, and future research challenges. European Journal of Work and Organizational Psychology, 29(1), 64–77. https://doi.org/10.1080/1359432X.2019.1681401
  • Yalcin, G., Lim, S., Puntoni, S., & Van Osselaer, S. M. J. (2022). Thumbs Up or Down: Consumer Reactions to Decisions by Algorithms Versus Humans. Journal of Marketing Research, 59(4), 696–717. https://doi.org/10.1177/00222437211070016
  • Yin, H. (2021). Role of Artificial Intelligence Machine Learning in Deepening the Internet Plus Social Work Service. Mathematical Problems in Engineering, 2021, 1–10. https://doi.org/10.1155/2021/6915568

Examining the Perceptions of Communication Faculty Students on Algorithm Literacy and Algorithmic Decision Making

Year 2025, Issue: 50, 195 - 214

Abstract

The current digital environment is governed by algorithmic technology. While some studies suggest that algorithms unfairly influence human interests and decisions within this digital world, research focusing on algorithm literacy among students and the role of algorithms in decision-making remains relatively scarce. Therefore, this study seeks to reveal students' algorithm literacy to assess their knowledge and experience with algorithms, as well as the influence of algorithms on their decision-making manners. Focus group interviews were conducted, grounded in theories hypothesizing that algorithms are unfair and that the datasets and models applied in algorithmic systems do not provide unbiased representations of reality. A total of 32 communication students participated in this study, sharing their perceptions on the role of algorithms in decision-making. The research also examined students' experiences with algorithm literacy and whether their decisions extend beyond what algorithms offer. The thematically analyzed findings indicate that algorithms play a double role in decision-making, offering both benefits and challenges, and it is clear that algorithms repeatedly exhibit bias and manipulate users, particularly in position with commercial interests. Notably, it was found that students perceived that algorithms can sometimes limit users' choices by prioritising a particular type of content under the influence of adverts and the nature of the media, thereby creating an unfair bias. Therefore, future research should focus on the design and regulation of algorithms to improve their transparency and mitigate the risks of social manipulation.

References

  • Abrams, L. R., McBride, C. M., Hooker, G. W., Cappella, J. N., & Koehly, L. M. (2015). The Many Facets of Genetic Literacy: Assessing the Scalability of Multiple Measures for Broad Use in Survey Research. PLOS ONE, 10(10), e0141532. https://doi.org/10.1371/journal.pone.0141532
  • Airoldi, M., & Rokka, J. (2022). Algorithmic consumer culture. Consumption Markets & Culture, 25(5), 411–428. https://doi.org/10.1080/10253866.2022.2084726
  • Archambault, S., Ramachandran, S., Acosta, E., & Fu, S. (2024). Ethical dimensions of algorithmic literacy for college students: Case studies and cross-disciplinary connections. The Journal of Academic Librarianship, 50(3).
  • Beck, L. C., Trombetta, W. L., & Share, S. (1986). Using focus group sessions before decisions are made. North Carolina Medical Journal, 47(2), 73–74.
  • Brkan, M. (2019). Do algorithms rule the world? Algorithmic decision-making and data protection in the framework of the GDPR and beyond. International Journal of Law and Information Technology, 27(2), 91–121. https://doi.org/10.1093/ijlit/eay017
  • Burton, J. W., Stein, M., & Jensen, T. B. (2020). A systematic review of algorithm aversion in augmented decision making. Journal of Behavioral Decision Making, 33(2), 220–239. https://doi.org/10.1002/bdm.2155
  • Chouldechova, A., Benavides-Prado, D., Fialko, O., & Vaithianathan, R. (2018). A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. In Conference on Fairness, Accountability and Transparency. PMLR, 134–148.
  • Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., & Huq, A. (2017). Algorithmic Decision Making and the Cost of Fairness. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 797–806. https://doi.org/10.1145/3097983.3098095
  • DeVito, M. A. (2021). Adaptive Folk Theorization as a Path to Algorithmic Literacy on Changing Platforms. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 1–38. https://doi.org/10.1145/3476080
  • Dogruel, L. (2021). What is Algorithm Literacy?: A Conceptualization and Challenges Regarding its Empirical Measurement (M. Taddicken & C. Schumann, Eds.). Freie Universität Berlin. https://doi.org/10.48541/DCR.V9.3
  • Dogruel, L., Facciorusso, D., & Stark, B. (2022). ‘I’m still the master of the machine.’ Internet users’ awareness of algorithmic decision-making and their perception of its effect on their autonomy. Information, Communication & Society, 25(9), 1311–1332. https://doi.org/10.1080/1369118X.2020.1863999
  • Dogruel, L., Masur, P., & Joeckel, S. (2022). Development and Validation of an Algorithm Literacy Scale for Internet Users. Communication Methods and Measures, 16(2), 115–133. https://doi.org/10.1080/19312458.2021.1968361
  • Elish, M. C., & Boyd, D. (2018). Situating methods in the magic of Big Data and AI. Communication Monographs, 85(1), 57–80. https://doi.org/10.1080/03637751.2017.1375130
  • Estrela, M., Semedo, G., Roque, F., Ferreira, P. L., & Herdeiro, M. T. (2023). Sociodemographic determinants of digital health literacy: A systematic review and meta-analysis. International Journal of Medical Informatics, 177, 105124. https://doi.org/10.1016/j.ijmedinf.2023.105124
  • Evren, M., & Koyuncu, A. A. (2024). Algorithm Domination As A New Surveillance System. Yeni Medya Dergisi. https://doi.org/10.55609/yenimedya.1528528
  • Gran, A. B., Booth, P., & Bucher, T. (2021). To be or not to be algorithm aware: A question of a new digital divide? Information, Communication & Society, 24(12), 1779–1796. https://doi.org/10.1080/1369118X.2020.1736124
  • Hobbs, R. (2020). Propaganda in an Age of Algorithmic Personalization: Expanding Literacy Research and Practice. Reading Research Quarterly, 55(3), 521–533. https://doi.org/10.1002/rrq.301
  • Jansen, S. C. (2022). What Was Artificial Intelligence? (1st ed., Vol. 1). mediastudies.press. https://doi.org/10.32376/3f8575cb.0cc62523
  • Kalır, H. (2023). Siyah Veri, Beyaz Algoritmalar : Veri Sömürgecisinin Dünya Modelini Reddetmek ve Veriyi Sömürgesizleştirmek Mümkün Mü ? Mülkiye Dergisi, 47(6), 1469- 1504.
  • Karakoç Keskin, E. (2024). Dijital Medya Ortamında Rızanın Algoritmik İnşası: Eleştirel Algoritma Çalışmaları Perspektifinde Bir Tartışma. Yeni Medya, (16), 329-353.
  • Karakoç Keskin, E. & Demirel, E. S. (2025). Algoritmik Medya İçeriği Farkındalık Ölçeğinin (AMCA-scale) Türkçe Uyarlaması ve Ölçek Faktörleri Arasındaki İlişkilerin Analizi. Journal of Akdeniz University Faculty of Communication/Akdeniz Iletişim, (48).
  • Karaman, M. K., & Yiğit, İ. (2024). Yeni Medya Bölümü Öğrencilerinin Algoritma Okuryazarlıkları Üzerine Bir Araştırma. Erciyes İletişim Dergisi, 11(1), 155-180.
  • Katamba, M. (2023). Book Review: Understanding Risks and Crises Through the Media. (15), 351-354.
  • Katamba, M., & Kayıhan, B. (2024). A Descriptive Analysis for the Future of Journalism Studies in Emerging Artificial Intelligence (AI) and the Case of NewsGPT platform. Yeni Medya Dergisi. https://doi.org/10.55609/yenimedya.1427421
  • Kayihan, B., Nari̇n, B., Firat, D., & Firat, F. (2021). Algoritmalar, Yapay Zeka ve Makine Öğrenimi Ekseninde Gazetecilik Etiği: Uluslararası Akademik Dergilere Yönelik Bir İnceleme. TRT Akademi, 6(12), 296–327. https://doi.org/10.37679/trta.900086
  • Köchling, A., & Wehner, M. C. (2020). Discriminated by an algorithm: A systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. Business Research, 13(3), 795–848. https://doi.org/10.1007/s40685-020-00134-w
  • Latzer, M., & Festic, N. (2019). A guideline for understanding and measuring algorithmic governance in everyday life. Internet Policy Review, 8(2). https://doi.org/10.14763/2019.2.1415
  • Latzer, M., Hollnbuchner, K., Just, N., & Saurwein, F. (2016). The economics of algorithmic selection on the Internet. In J. M. Bauer & M. Latzer (Eds.), Handbook on the Economics of the Internet. Edward Elgar Publishing. https://doi.org/10.4337/9780857939852.00028
  • Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), 2053951718756684. https://doi.org/10.1177/2053951718756684
  • Lepri, B., Oliver, N., Letouzé, E., Pentland, A., & Vinck, P. (2018). Fair, Transparent, and Accountable Algorithmic Decision-making Processes: The Premise, the Proposed Solutions, and the Open Challenges. Philosophy & Technology, 31(4), 611–627. https://doi.org/10.1007/s13347-017-0279-x
  • Lomborg, S., & Kapsch, P. H. (2020). Decoding algorithms. Media, Culture & Society, 42(5), 745–761. https://doi.org/10.1177/0163443719855301
  • Longhofer, W., & Winchester, D. (Eds.). (2023). Social theory re-wired: New connections to classical and contemporary perspectives (Third edition). Routledge, Taylor & Francis Group.
  • Low, B., Ehret, C., & Hagh, A. (2025). Algorithmic imaginings and critical digital literacy on #BookTok. New Media & Society, 27(4), 2336–2353. https://doi.org/10.1177/14614448231206466
  • Lutkevich, B., & Gillis, A. S. (2024). What is a bot? TechTarget. https://www.techtarget.com/whatis/definition/bot-robo
  • Mahmud, H., Islam, A. K. M. N., Ahmed, S. I., & Smolander, K. (2022). What influences algorithmic decision-making? A systematic literature review on algorithm aversion. Technological Forecasting and Social Change, 175, 121390. https://doi.org/10.1016/j.techfore.2021.121390
  • Marmolejo-Ramos, F., Marrone, R., Korolkiewicz, M., Gabriel, F., Siemens, G., Joksimovic, S., Yamada, Y., Mori, Y., Rahwan, T., Sahakyan, M., Sonna, B., Meirmanov, A., Bolatov, A., Som, B., Ndukaihe, I., Arinze, N. C., Kundrát, J., Skanderová, L., Ngo, V.-G., … Tejada, J. (2025). Factors influencing trust in algorithmic decision-making: An indirect scenario-based experiment. Frontiers in Artificial Intelligence, 7, 1465605. https://doi.org/10.3389/frai.2024.1465605
  • Möhlmann, M., & Zalmanson, L. (2017). Hands on the wheel: Navigating algorithmic management and Uber drivers’ autonomy, proceedings of the International Conference on Information Systems.
  • Moylan, R., & Code, J. (2024). Algorithmic futures: An analysis of teacher professional digital competence frameworks through an algorithm literacy lens. Teachers and Teaching, 30(4), 452–470. https://doi.org/10.1080/13540602.2023.2263732
  • Oeldorf-Hirsch, A., & Neubaum, G. (2023). Attitudinal and behavioral correlates of algorithmic awareness among German and U.S. social media users. Journal of Computer-Mediated Communication, 28(5), zmad035. https://doi.org/10.1093/jcmc/zmad035
  • Oeldorf-Hirsch, A., & Neubaum, G. (2025). What do we know about algorithmic literacy? The status quo and a research agenda for a growing field. New Media & Society, 27(2), 681–701. https://doi.org/10.1177/14614448231182662
  • Park, Y. J. (2013). Digital Literacy and Privacy Behavior Online. Communication Research, 40(2), 215–236. https://doi.org/10.1177/0093650211418338
  • Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.
  • Şenyüz, B. (2023). Algoritma okuryazarlığı. In Yapay Zeka ve İletişim. Kriter Yayınları.
  • Shin, D. (2020). How do users interact with algorithm recommender systems? The interaction of users, algorithms, and performance. Computers in Human Behavior, 109, 106344. https://doi.org/10.1016/j.chb.2020.106344
  • Tsuei, H.-J., Tsai, W.-H., Pan, F.-T., & Tzeng, G.-H. (2020). Improving search engine optimization (SEO) by using hybrid modified MCDM models. Artificial Intelligence Review, 53(1), 1–16. https://doi.org/10.1007/s10462-018-9644-0
  • Tucker, C. (2018). Privacy, algorithms, and artificial intelligence. In The economics of artificial intelligence: An agenda (pp. 423-437.).
  • Wegner, P. (1997). Why interaction is more powerful than algorithms. Communications of the ACM, 40(5), 80–91. https://doi.org/10.1145/253769.253801
  • Wilkinson, S. (1998). Focus group methodology: A review. International Journal of Social Research Methodology, 1(3), 181–203. https://doi.org/10.1080/13645579.1998.10846874
  • Woods, S. A., Ahmed, S., Nikolaou, I., Costa, A. C., & Anderson, N. R. (2020). Personnel selection in the digital age: A review of validity and applicant reactions, and future research challenges. European Journal of Work and Organizational Psychology, 29(1), 64–77. https://doi.org/10.1080/1359432X.2019.1681401
  • Yalcin, G., Lim, S., Puntoni, S., & Van Osselaer, S. M. J. (2022). Thumbs Up or Down: Consumer Reactions to Decisions by Algorithms Versus Humans. Journal of Marketing Research, 59(4), 696–717. https://doi.org/10.1177/00222437211070016
  • Yin, H. (2021). Role of Artificial Intelligence Machine Learning in Deepening the Internet Plus Social Work Service. Mathematical Problems in Engineering, 2021, 1–10. https://doi.org/10.1155/2021/6915568
There are 51 citations in total.

Details

Primary Language English
Subjects Journalism
Journal Section Research Article
Authors

Bahar Kayıhan 0000-0001-5196-4350

Muzafalu Katamba 0000-0002-9000-2303

Early Pub Date October 13, 2025
Publication Date October 17, 2025
Submission Date May 24, 2025
Acceptance Date September 2, 2025
Published in Issue Year 2025 Issue: 50

Cite

APA Kayıhan, B., & Katamba, M. (2025). Examining the Perceptions of Communication Faculty Students on Algorithm Literacy and Algorithmic Decision Making. Akdeniz Üniversitesi İletişim Fakültesi Dergisi(50), 195-214.

3328033281

Journal of Akdeniz University Faculty of Communication is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC-BY-NC).