Gendered Dimensions of AI Integration in Language Learning: A Review in the Context of Art and Digitalization
##plugins.themes.bootstrap3.article.sidebar##
##plugins.themes.bootstrap3.article.main##
Resum
This review examines the integration of artificial intelligence (AI) in education, particularly its impact on language learning and gender perceptions. It examines AI’s transformative potential in enhancing educational outcomes and addresses gender biases in AI interactions. Emphasizing the importance of ethical AI practices, the study highlights the need for a nuanced understanding of how gender influences interactions with AI systems in educational contexts. By exploring these dynamics, it sheds light on the complexities of technology adoption and its implications for gender equity in education.
Descàrregues
##plugins.themes.bootstrap3.article.details##
Referències
Ahn, Jungyong; Kim, Jungwon, & Sung, Yongjun. (2022). The effect of gender stereotypes on artificial intelligence recommendations. Journal of Business Research, 141, 50-59. https://doi.org/10.1016/j.jbusres.2021.12.007
Aldahwan, Nouf S., & Alsaeed, Norah Ibraheem. (2020). Use of Artificial Intelligent in Learning Management System (LMS): A Systematic Literature Review. International Journal of Computer Applications, 175(13), 16-26. https://doi.org/10.5120/ijca2020920611
Alzamil, Lima A. (2020). Uncovering Gender Differences in Saudi EFL Learners’ Attitudes Towards the Use of Instagram as a Language Learning Tool. International Journal of Linguistics, 12(5), 17. https://doi.org/10.5296/ijl.v12i5.17486
Ashiyan, Zahra, & Salehi, Hadi. (2016). A comparison of male and female learners’ English collocation learning through using WhatsApp. International Journal of Research Studies in Educational Technology, 6(1). https://doi.org/10.5861/ijrset.2016.1615
Aspray, William. (1991). Creating the Computer: Government, Industry, and High Technology. By Kenneth Flamm. Washington, DC: Brookings Institution, 1988. pp. XI, 282. $28.95, Cloth; $10.95, paper. The Journal of Economic History, 51(3), 739-740. https://doi.org/10.1017/s0022050700039863
Bernotat, Jasmin; Eyssel, Friederike, & Sachse, Janik. (2019). The (Fe)Male Robot: How Robot Body Shape Impacts First Impressions and Trust Towards Robots. International Journal of Social Robotics, 13(3), 477-489. https://doi.org/10.1007/s12369-019-00562-7
Borau, Sylvie; Otterbring, Tobias; Laporte, Sandra, & Fosso Wamba, Sanuel. (2021). The most human bot: Female gendering increases humanness perceptions of bots and acceptance of ai. Psychology & Marketing, 38(7), 1052-1068. https://doi.org/10.1002/mar.21480
Bozkurt, Aras. (2019). Intellectual roots of distance education: a progressive knowledge domain analysis. Distance Education, 40(4), 497-514. https://doi.org/10.1080/01587919.2019.1681894
Bradac, Vladimir, & Walek, Bogdan. (2017). A comprehensive adaptive system for e-learning of foreign languages. Expert Systems with Applications, 90, 414-426. https://doi.org/10.1016/j.eswa.2017.08.019
Brahnam, Sheryl, & De Angeli, Antonella. (2012). Gender affordances of conversational agents. Interacting with Computers, 24(3), 139-153. https://doi.org/10.1016/j.intcom.2012.05.001
Cairns, Len, & Malloch, Margaret. (2017). Computers in Education: The Impact on Schools and Classrooms. Education in the Asia-Pacific Region: Issues, Concerns and Prospects, 603-617. https://doi.org/10.1007/978-981-10-3654-5_36
Cercas Curry, Amanda; Robertson, Judy, & Rieser, Verena. (2020). Conversational Assistants and Gender Stereotypes: Public Perceptions and Desiderata for Voice Personas in Costa-jussà, Marta R.; Hardeimer, Christian; Radford, Will, & Webster, Kellie (Eds.), Proceedings of the Second Workshop on Gender Bias in Natural Language Processing (pp. 72-78). Association for Computational Linguistics.
Charles Sturt University. (2024, August 11). Literature Review: Systematic literature reviews. https://libguides.csu.edu.au/review/Systematic
Chassignol, Maud; Khoroshavin, Aleksandr; Klimova, Alexandra, & Bilyatdinova, Anna. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16-24. https://doi.org/10.1016/j.procs.2018.08.233
Dang, Yongy M.; Zhang, Yang G.; Ravindran, Sury, & Osmonbekov, Talai. (2016). Examining Student Satisfaction and Gender Differences in Technology-Supported, Blended Learning. Journal of Information Systems Education, 27(2), 119.
Deloitte China. (2019, November 12). Global development of AI-Based Education. https://www2.deloitte.com/cn/en/pages/technology-media-and-telecommunications/articles/development-of-ai-based-education-in-china.html
Djalev, Liubomir, & Bogdanov, Stansislav. (2019). Age and Gender Differences in Evaluating the Pedagogical Usability of E-learning Materials. English Studies at NBU, 5(2), 169-189. https://doi.org/10.33919/esnbu.19.2.0
Dogoriti, Evriklea; Pange, Jenny, & S. Anderson, Gregory. (2014). The use of social networking and learning management systems in English language teaching in higher education. Campus-Wide Information Systems, 31(4), 254-263. https://doi.org/10.1108/cwis-11-2013-0062
Dufour, Florian, & Ehrwein Nihan, Celine. (2016). Do Robots Need to Be Stereotyped? Technical Characteristics as a Moderator of Gender Stereotyping. Social Sciences, 5(3), 27. https://doi.org/10.3390/socsci5030027
El Alfy, Shahira; Marx Gómez, Jorge, & Dani, Anita. (2019). Exploring the benefits and challenges of learning analytics in Higher Education Institutions: A systematic literature review. Information Discovery and Delivery, 47(1), 25-34. https://doi.org/10.1108/idd-06-2018-0018
Enríquez, Javier Julián. (2018. November 15-17). 2018 International Joint Symposium on Artificial Intelligence and Natural Language Processing (Isai-NLP). Pattaya, Thailand. https://doi.org/10.1109/isai-nlp45051.2018
Ernst, Clause-Peter, & Herm-Stapelberg, Nils. (2020). Gender Stereotyping’s Influence on the Perceived Competence of Siri and Co. Proceedings of the Annual Hawaii International Conference on System Sciences. https://doi.org/10.24251/hicss.2020.544
Eryilmaz, Ali, & Yeşilyurt, Yusuf Emre. (2022). Foreign Language Writing as a Developmental Process (Foundation, Expansion, Development, and Completion): The FEDcom Model. International Journal of Contemporary Educational Research, 7(2), 307-334. https://doi.org/10.33200/ijcer.768768
Ferrando, Ferrando. (2014). Is the post-human a post-woman? Cyborgs, robots, artificial intelligence and the futures of gender: a case study. European Journal of Futures Research, 2(1). https://doi.org/10.1007/s40309-014-0043-8
Gong, Xiaoyan; Zhao, Liang; Tang, RenHao; Guo, YaNa; Liu, Xiwei; He, Jien; Wang, Fei-Yue; Tang, Ying; Shi, Wanruo; Niu, Xiaojie, & Wang, Xinzhu. (2019). AI educational system for primary and Secondary Schools. 2019 ASEE Annual Conference & Exposition Proceedings. https://doi.org/10.18260/1-2--32050
Gulz, Agneta, & Haake, Magnus. (2008). Challenging Gender Stereotypes Using Virtual Pedagogical Characters. Advances in Social Networking and Online Communities, 113-132. https://doi.org/10.4018/978-1-61520-813-5.ch007
Guo, Yiting; Yin, Ximing; Liu, De, & Xu, Sean Xin. (2021). Effect of Ai Chatbots’ Gender in the Business Context: Empirical Evidence from Debt Collection. Academy of Management Proceedings, 2021(1), 15449. https://doi.org/10.5465/ambpp.2021.15449abstract
Gustavsson, Eva. (2005). Virtual Servants: Stereotyping Female Front‐Office Employees on the Internet. Gender, Work & Organization, 12(5), 400-419. https://doi.org/10.1111/j.1468-0432.2005.00281.x
Guzman, Andrea L., & Lewis, Seth C. Lewis. (2019). Artificial Intelligence and Communication: A Human-Machine Communication Research Agenda. New Media & Society, 22(1), 70-86. https://doi.org/10.1177/1461444819858691
Herbert; Laksono Putro, Budi; Putra, Rizky Rachman, & Fitriasari, Novi Sofia. (2019). Learning Management System (LMS) model based on machine learning supports 21st century learning as the implementation of curriculum 2013. Journal of Physics: Conference Series, 1280(3), 032032. https://doi.org/10.1088/1742-6596/1280/3/032032
Iwaniec, Jania. (2019). Language learning motivation and gender: The case of Poland. International Journal of Applied Linguistics, 29(1), 130-143. https://doi.org/10.1111/ijal.12251
Kahraman, H. Tolga; Sagiroglu, Seref, & Colak, Ilhami. (2010, October 12-14). Development of adaptive and intelligent web-based educational systems. 4th International Conference on Application of Information and Communication Technologies, Uzbekistan, Tashkent. https://doi.org/10.1109/icaict.2010.5612054
Khaled, Dr. (2014). Natural Language Processing and Its Use in Education. International Journal of Advanced Computer Science and Applications, 5(12). https://doi.org/10.14569/ijacsa.2014.051210
Kim, Ahyeon; Cho, MA Minha; Ahn, Jungyong, & Sung, Yongjun. (2019). Effects of Gender and Relationship Type on the Response to Artificial Intelligence. Cyberpsychology, Behavior, and Social Networking, 22(4), 249-253. https://doi.org/10.1089/cyber.2018.0581
Lasekan, Olusiji. (2018). Gender Differences in English Proficiency among Early, Middle and Late Immersion Undergraduate Students: The Role of Individual Difference Factors. Global Journal of Foreign Language Teaching, 8(1), 29-42. https://doi.org/10.18844/gjflt.v8i1.3433
Lee, Youngseok, & Cho, Jungwon. (2020). Design of a Foreign Language Conversation Learning System Using Machine Learning. Int’l Journal of Innovation, Creativity and Change, 13(4), 235-247.
Li, Ruolin. (2020). Using artificial intelligence in learning English as a foreign language: An examination of IELTS LIULISHUO as an online platform. Journal of Higher Education Research, 1(2). https://doi.org/10.32629/jher.v1i2.178
Li, Xiaomeng. (2022). The Effectiveness of Mobile-Assisted Language Learning (MALL) Applications on the Spoken English Assessments in China’s Universities. Advances in Social Science, Education and Humanities Research. 10.2991/assehr.k.220105.137
Lousado, J. P.; Costa, C. M. M., Oliveira, I. P., & Roberto, M. T. (2019, June 19-22). 2019 14th Iberian conference on information systems and technologies (CISTI). 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). https://doi.org/10.23919/cisti.2019.8760734
McDonnell, Marian, & Baxter, David. (2019). Chatbots and gender stereotyping. Interacting with Computers, 31(2), 116-121. https://doi.org/10.1093/iwc/iwz007
Mezei, Peter. (2020). From Leonardo to the Next Rembrandt – The Need for AI-Pessimism in the Age of Algorithms. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3592187
Mikropoulos, Tassos A., & Natsis, Antonis. (2011). Educational Virtual Environments: A Ten-Year Review of Empirical Research (1999-2009). Computers & Education, 56(3), 769-780. https://doi.org/10.1016/j.compedu.2010.10.020
Morales Ríos, Sandra, & Ferreira Cabrera, Anita. (2008). La efectividad de un modelo de aprendizaje combinado para la enseñanza del inglés como lengua extranjera: estudio empírico. RLA. Revista de Lingüística Teórica y Aplicada, 46(2). https://doi.org/10.4067/s0718-48832008000200006
Nag, Procheta, & Yalçın, Özge Nilay. (2020). Gender Stereotypes in Virtual Agents. Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents. https://doi.org/10.1145/3383652.3423876
Nass, Clifford; Moon, Youngme, & Green, Nancy. (1997). Are Machines Gender Neutral? Gender-Stereotypic Responses to Computers with Voices. Journal of Applied Social Psychology, 27(10), 864-876. https://doi.org/10.1111/j.1559-1816.1997.tb00275.x
Otterbacher, Jahna, & Talias, Michael. (2017). S/he’s too warm/agentic! in Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction (pp. 214-223). Association for Computing Machinery. https://doi.org/10.1145/2909824.3020220
Oz, Huseyin. (2015). An Investigation of Preservice English Teachers’ Perceptions of Mobile Assisted Language Learning. English Language Teaching, 8(2). https://doi.org/10.5539/elt.v8n2p22
Pak, Richard; McLaughlin, Anne Collins, & Bass, Brock. (2014). A multi-level analysis of the effects of age and gender stereotypes on trust in anthropomorphic technology by younger and older adults. Ergonomics, 57(9), 1277-1289. https://doi.org/10.1080/00140139.2014.928750
Peredo, Ruben; Canales, Alejandro; Menchaca, Alain, & Peredo, Ivan. (2011). Intelligent Web-based education system for adaptive learning. Expert Systems with Applications, 38(12), 14690-14702. https://doi.org/10.1016/j.eswa.2011.05.013
Petrova, Marina Georgievna, & Khalil, Mohsen. (2020). Artificial Intelligence in adaptive teaching a foreign language. PROCEEDINGS of the 12th All-Russian Research and Methodological Conference with International Participation, Moscow, Institute of Foreign Languages, RUDN University, March 27th, 2020. https://doi.org/10.22363/09835-2020-294-304
Pfeuffer, Nicolas; Benlian, Alexander; Gimpel, Henner, & Hinz, Oliver. (2019). Anthropomorphic Information Systems. Business & Information Systems Engineering, 61(4), 523-533. https://doi.org/10.1007/s12599-019-00599-y
Pokrivcakova, Silvia. (2019). Preparing teachers for the application of AI-powered technologies in Foreign Language Education. Journal of Language and Cultural Education, 7(3), 135-153. https://doi.org/10.2478/jolace-2019-0025
Prisma. (n.d.). Welcome to the NEW Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) website. http://www.prisma-statement.org/
Putra, I Dewa Gede Rat Dwiyana; Saukah, Ali; Basthomi, Yazid, & Irawati, Enny. (2020). The acceptance of the English Language Learning Mobile Application hello English across gender and experience differences. International Journal of Emerging Technologies in Learning (iJET), 15(15), 219. https://doi.org/10.3991/ijet.v15i15.11077
Reich-Stiebert, Natalia, & Eyssel, Friederike. (2017). (IR)relevance of gender? Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. https://doi.org/10.1145/2909824.3020242
Roberts, Nancy. (2019). How artificial intelligence works. Nursing Management, 3(10).
Rus, Vasile; D’Mello, Sidney; Hu, Xiangen, & Graesser, Arthur C. (2013). Recent advances in conversational intelligent tutoring systems. AI Magazine, 34(3), 42-54. https://doi.org/10.1609/aimag.v34i3.2485
Song-Nichols, Kallyn, & Young, Andrew. (2020). Gendered Robots Can Change Children’s Gender Stereotyping. CogSci.
Teo, Timothy; Fan, Xitao, & Du, Jianxia. (2015). Technology acceptance among pre-service teachers: Does gender matter? Australasian Journal of Educational Technology, 31(3). https://doi.org/10.14742/ajet.1672
Timms, Michael J. (2016). Letting Artificial Intelligence in education out of the box: Educational Cobots and smart classrooms. International Journal of Artificial Intelligence in Education, 26(2), 701-712. https://doi.org/10.1007/s40593-016-0095-y
Townsend, David M., & Hunt, Richard A. (2019). Entrepreneurial action, creativity, & judgment in the age of artificial intelligence. Journal of Business Venturing Insights, 11. https://doi.org/10.1016/j.jbvi.2019.e00126
Tumskiy, Stanislav. (2019). The use of learning management systems in the teaching of English to high-level learners at tertiary level. INTED2019 Proceedings. https://doi.org/10.21125/inted.2019.0915
UNESCO. (2023, April 20). How can artificial intelligence enhance education? https://www.unesco.org/en/articles/how-can-artificial-intelligence-enhance-education
Vega, Adrian; Ramírez-Benavides, Kryscia; Guerrero, Luis A., & López, Gustavo. (2019). Evaluating the Nao Robot in the role of personal assistant: The effect of gender in Robot Performance Evaluation. 13th International Conference on Ubiquitous Computing and Ambient . https://doi.org/10.3390/proceedings2019031020Intelligence UCAmI 2019
Veletsianos, George; Scharber, Cassandra, & Doering, Aaron. (2008). When sex, drugs, and violence enter the classroom: Conversations between adolescents and a female pedagogical agent. Interacting with Computers, 20(3), 292-301. https://doi.org/10.1016/j.intcom.2008.02.007
Villegas-Ch, William; Román-Cañizares, Milton, & Palacios-Pacheco, Xavier. (2020). Improvement of an online education model with the integration of machine learning and Data Analysis in an LMS. Applied Sciences, 10(15), 5371. https://doi.org/10.3390/app10155371
Wartman, Steven A., & Combs, Combs Donald. (2018). Medical Education Must Move from the Information Age to the Age of Artificial Intelligence. Academic Medicine, 93(8), 1107-1109. https://doi.org/10.1097/acm.0000000000002044
Watkins, Heather, & Pak, Richard. (2020). Investigating User Perceptions and Stereotypic Responses to Gender and Age of Voice Assistants. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 64(1), 1800-1804. https://doi.org/10.1177/1071181320641434
Whitby, Blay. (2008). Artificial Intelligence: A beginner’s guide. Oneworld Pub.
Woinaroschy, Alexandru. (2020). Personal considerations about creativity and Artificial Intelligence. Journal of Engineering Sciences and Innovation, 5(1), 63-68. https://doi.org/10.56958/jesi.2020.5.1.7
Xodabande, Ismail. (2018). Iranian EFL Learners’ Preferences of Different Digital Technologies for Language Learning beyond the Classroom. International Journal of Education and Literacy Studies, 6(3), 20.
Zhang, Xinyan. (2020). The Application Research of Artificial Intelligence and Big Data Analysis Technology in University Foreign Language Teaching. Journal of Physics: Conference Series, 1684(1), 012022. https://doi.org/10.1088/1742-6596/1684/1/012022
Zheng, Jianbo; Zhang, Qieshi; Xu, Shihao; Peng, Hong, & Wu, Qieshi. (2018). Cognition-Based Context-Aware Coud Computing for Intelligent Robotic Systems in Mobile Education. IEEE Access, 6, 49103-49111. https://doi.org/10.1109/access.2018.2867880