Evaluating Artificial Intelligence Anxiety Among Pre-Service Teachers in University Teacher Education Programs

Oluwanife Falebita

doi:10.58421/misro.v4i1.309

DOI:

https://doi.org/10.58421/misro.v4i1.309

Authors

Oluwanife Falebita University of Zululand https://orcid.org/0000-0002-8287-4005

Keywords:

artificial intelligence, undergraduates, AI Anxiety, Gender, Mathematics, Science and Technology Education, Undergraduates

Abstract

Adopting artificial intelligence (AI) in education for various purposes has become prominent and has raised many user concerns. The concerns, apprehension, or fear that comes with the use of AI are referred to as Artificial Intelligence Anxiety (AI anxiety). Undergraduates are the most frequent users of AI in higher education. This study assessed AI anxiety among pre-service teachers. A survey conducted online was used for data collection. A sample of 1067 pre-service teachers in mathematics, science, and technology teacher education programs were purposefully selected for the study. A questionnaire was used to collect data regarding the pre-service teachers' AI-Anxiety in six dimensions: technology intimidation, societal impact, job displacement, technological dependence, technological dread, and ethical concerns. The instrument was hosted online through Google Forms, and the data gathered was analyzed descriptively (percentage, mean, and standard deviation) and inferentially (ANOVA and regression analysis). This study reveals a moderate level of AI anxiety among pre-service teachers. Levels of AI anxiety vary across the six dimensions, with five found to be high while only one was found to be at moderate level. It also found significant variations in the level of AI anxiety among pre-service teachers based on their area of speciality. Also, the study identified no significant influences of demographic characteristics on the level of AI anxiety among pre-service teachers, emphasizing gender. Thus, educators and institutions should urgently embark on AI literacy to improve the ethical use of AI technologies among pre-service teachers and ameliorate AI anxiety.

Downloads

Download data is not yet available.

References

C. Surugiu, C. Gradinaru, and M.-R. Surugiu, “Artificial Intelligence in Business Education: Benefits and Tools,” Amfiteatru Economic, vol. 26, no. 65, p. 241, Feb. 2024, doi: 10.24818/EA/2024/65/241.

S. Aravantinos, K. Lavidas, I. Voulgari, S. Papadakis, T. Karalis, and V. Komis, “Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus,” Educ Sci (Basel), vol. 14, no. 7, p. 744, Jul. 2024, doi: 10.3390/educsci14070744.

F. Ouyang and P. Jiao, “Artificial intelligence in education: The three paradigms,” Computers and Education: Artificial Intelligence, vol. 2, p. 100020, 2021, doi: 10.1016/j.caeai.2021.100020.

M. A. Ayanwale, I. T. Sanusi, O. P. Adelana, K. D. Aruleba, and S. S. Oyelere, “Teachers’ readiness and intention to teach artificial intelligence in schools,” Computers and Education: Artificial Intelligence, vol. 3, p. 100099, 2022, doi: 10.1016/j.caeai.2022.100099.

J. Dunlosky, K. A. Rawson, E. J. Marsh, M. J. Nathan, and D. T. Willingham, “Improving Students’ Learning With Effective Learning Techniques,” Psychological Science in the Public Interest, vol. 14, no. 1, pp. 4–58, Jan. 2013, doi: 10.1177/1529100612453266.

S. Hennessy et al., “Technology Use for Teacher Professional Development in Low- and Middle-Income Countries: A systematic review,” Computers and Education Open, vol. 3, p. 100080, Dec. 2022, doi: 10.1016/j.caeo.2022.100080.

P. Rodway and A. Schepman, “The impact of adopting AI educational technologies on projected course satisfaction in university students,” Computers and Education: Artificial Intelligence, vol. 5, p. 100150, 2023, doi: 10.1016/j.caeai.2023.100150.

J. Anderson and L. Rainie, “Artificial Intelligence and the Future of Humans,” https://www.pewresearch.org/internet/2018/12/10/artificial-intelligence-and-the-future-of-humans/.

F. Kaya, F. Aydin, A. Schepman, P. Rodway, O. Yetişensoy, and M. Demir Kaya, “The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence,” Int J Hum Comput Interact, vol. 40, no. 2, pp. 497–514, Jan. 2024, doi: 10.1080/10447318.2022.2151730.

D. B. Abrams et al., “Anxiety and Its Measurement,” in Encyclopedia of Behavioral Medicine, New York, NY: Springer New York, 2013, pp. 111–117. doi: 10.1007/978-1-4419-1005-9_938.

M. M. Antony, “Assessment of Anxiety and the Anxiety Disorders: An Overview,” in Practitioner’s Guide to Empirically Based Measures of Anxiety, Boston: Kluwer Academic Publishers, 2001, pp. 9–17. doi: 10.1007/0-306-47628-2_2.

Y.-M. Wang, C.-L. Wei, H.-H. Lin, S.-C. Wang, and Y.-S. Wang, “What drives students’ AI learning behavior: a perspective of AI anxiety,” Interactive Learning Environments, pp. 1–17, Dec. 2022, doi: 10.1080/10494820.2022.2153147.

O. S. Falebita and P. J. Kok, “Artificial Intelligence Tools Usage: A Structural Equation Modeling of Undergraduates’ Technological Readiness, Self-Efficacy and Attitudes,” J STEM Educ Res, Sep. 2024, doi: 10.1007/s41979-024-00132-1.

O. S. Falebita and P. J. Kok, “Strategic goals for artificial intelligence integration among STEM academics and undergraduates in African higher education: a systematic review,” Discover Education, vol. 3, no. 1, p. 151, Sep. 2024, doi: 10.1007/s44217-024-00252-1.

O. S. Falebita, “Assessing the relationship between anxiety and the adoption of Artificial Intelligence tools among mathematics pre-service teachers,” Interdisciplinary Journal of Education Research, vol. 6, pp. 1–13, Jun. 2024, doi: 10.38140/ijer-2024.vol6.20.

D. Ayduğ and H. Altınpulluk, Investigation of Pre-service Teachers’ Artificial Intelligence Anxiety Levels. 2023.

J. von Garrel and J. Mayer, “Artificial Intelligence in studies—use of ChatGPT and AI-based tools among students in Germany,” Humanit Soc Sci Commun, vol. 10, no. 1, p. 799, Nov. 2023, doi: 10.1057/s41599-023-02304-7.

Y. Fu, “A research of the impact of ChatGPT on education,” Applied and Computational Engineering, vol. 35, no. 1, pp. 26–31, Feb. 2024, doi: 10.54254/2755-2721/35/20230354.

D. J. Lemay, R. B. Basnet, and T. Doleck, “Fearing the Robot Apocalypse: Correlates of AI Anxiety,” International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI), vol. 2, no. 2, p. 24, Aug. 2020, doi: 10.3991/ijai.v2i2.16759.

G. Özbek Güven, Ş. Yilmaz, and F. Inceoğlu, “Determining medical students’ anxiety and readiness levels about artificial intelligence,” Heliyon, vol. 10, no. 4, p. e25894, Feb. 2024, doi: 10.1016/j.heliyon.2024.e25894.

O. S. Falebita, “Assessing the relationship between anxiety and the adoption of Artificial Intelligence tools among mathematics pre-service teachers,” Interdisciplinary Journal of Education Research, vol. 6, pp. 1–13, Jun. 2024, doi: 10.38140/ijer-2024.vol6.20.

S. Banerjee and B. Banerjee, “College Teachers’ Anxiety Towards Artificial Intelligence: A Comparative Study,” RESEARCH REVIEW International Journal of Multidisciplinary, vol. 8, no. 5, pp. 36–43, May 2023, doi: 10.31305/rrijm.2023.v08.n05.005.

R. Terzi, “An adaptation of artificial intelligence anxiety scale into Turkish: Reliability and validity study,” vol. 7, pp. 1501–1515, Oct. 2020.

C. McGrath, T. Cerratto Pargman, N. Juth, and P. J. Palmgren, “University teachers’ perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study,” Computers and Education: Artificial Intelligence, vol. 4, p. 100139, 2023, doi: 10.1016/j.caeai.2023.100139.

B. Eyüp and S. Kayhan, “Pre-Service Turkish Language Teachers’ Anxiety and Attitudes Toward Artificial Intelligence,” International Journal of Education and Literacy Studies, vol. 11, no. 4, pp. 43–56, Oct. 2023, doi: 10.7575/aiac.ijels.v.11n.4p.43.

J. Mangundu, “The effects of technostress on academic commitment among first-year undergraduate students at an institution of higher education in South Africa,” in Proceedings of the 4th African Human Computer Interaction Conference, New York, NY, USA: ACM, Nov. 2023, pp. 106–117. doi: 10.1145/3628096.3629044.

C. Brod, “Book Reviews : Technostress: The Human Cost of the Computer Revolution Craig Brod Publisher: Addison-Wesley Publishing Company, Reading, MA Year of Publication: 1984 Materials: 242 pages. Price: $16.95 Intended Audience: Lay; social science Usefulness: Low Clarity: Good Difficulty: Novice,” Social Science Microcomputer Review, vol. 4, no. 4, pp. 553–556, Dec. 1986, doi: 10.1177/089443938600400428.

N. Yao and Q. Wang, “Technostress from Smartphone Use and Its Impact on University Students’ Sleep Quality and Academic Performance,” The Asia-Pacific Education Researcher, vol. 32, no. 3, pp. 317–326, Jun. 2023, doi: 10.1007/s40299-022-00654-5.

C. Zhang, J. Schießl, L. Plößl, F. Hofmann, and M. Gläser-Zikuda, “Acceptance of artificial intelligence among pre-service teachers: a multigroup analysis,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, p. 49, Sep. 2023, doi: 10.1186/s41239-023-00420-7.

P. K. Butakor, “Exploring Pre-Service Teachers’ Beliefs About The Role of Artificial Intelligence in Higher Education in Ghana,” International Journal of Innovative Technologies in Social Science, no. 3(39), Sep. 2023, doi: 10.31435/rsglobal_ijitss/30092023/8057.

C. Zhang, J. Schießl, L. Plößl, F. Hofmann, and M. Gläser-Zikuda, “Acceptance of artificial intelligence among pre-service teachers: a multigroup analysis,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, p. 49, Sep. 2023, doi: 10.1186/s41239-023-00420-7.

K. Lavidas et al., “Determinants of Humanities and Social Sciences Students’ Intentions to Use Artificial Intelligence Applications for Academic Purposes,” Information, vol. 15, no. 6, p. 314, May 2024, doi: 10.3390/info15060314.

P. K. Butakor, “Exploring Pre-Service Teachers’ Beliefs About The Role of Artificial Intelligence in Higher Education in Ghana,” International Journal of Innovative Technologies in Social Science, no. 3(39), Sep. 2023, doi: 10.31435/rsglobal_ijitss/30092023/8057.

F. J. Fowler, Survey Research Methods. London: SAGE Publication inc, 2009.

M. P. Osiesi et al., “Psychosocial factors as predictors of aggressive behaviors among primary school learners,” Aggress Behav, vol. 49, no. 6, pp. 602–615, Nov. 2023, doi: 10.1002/ab.22098.

I. Etikan, “Comparison of Convenience Sampling and Purposive Sampling,” American Journal of Theoretical and Applied Statistics, vol. 5, no. 1, p. 1, 2016, doi: 10.11648/j.ajtas.20160501.11.

Y.-Y. Wang and Y.-S. Wang, “Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior,” Interactive Learning Environments, vol. 30, no. 4, pp. 619–634, Apr. 2022, doi: 10.1080/10494820.2019.1674887.

L. J. Julian, “Measures of anxiety: State‐Trait Anxiety Inventory (STAI), Beck Anxiety Inventory (BAI), and Hospital Anxiety and Depression Scale‐Anxiety (HADS‐A),” Arthritis Care Res (Hoboken), vol. 63, no. S11, Nov. 2011, doi: 10.1002/acr.20561.

F. Baier, A.-T. Decker, T. Voss, T. Kleickmann, U. Klusmann, and M. Kunter, “What makes a good teacher? The relative importance of mathematics teachers’ cognitive ability, personality, knowledge, beliefs, and motivation for instructional quality,” British Journal of Educational Psychology, vol. 89, no. 4, pp. 767–786, 2019, doi: 10.1111/bjep.12256.

A. M. Flanagan, D. C. Cormier, and O. Bulut, “Achievement may be rooted in teacher expectations: examining the differential influences of ethnicity, years of teaching, and classroom behaviour,” Social Psychology of Education, vol. 23, pp. 1429–1448, 2020, doi: 10.1007/s11218-020-09590-y.

J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate Data Analysis. Edinburg: Pearson Education Limited, 2014.

L. Terzi, Educational justice for students with intellectual disabilities. academic.oup.com, 2018. [Online]. Available: https://academic.oup.com/edited-volume/28141/chapter/212926107

C. McGrath, T. Cerratto Pargman, N. Juth, and P. J. Palmgren, “University teachers’ perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study,” Computers and Education: Artificial Intelligence, vol. 4, p. 100139, 2023, doi: 10.1016/j.caeai.2023.100139.