Document Type : Research Paper
Authors
- mehdi mohammadi 1
- reza naserijahromi 2
- ensiyeh esnaashari 3
- majid kowsari 4
- solmaz khademi 2
- sedigheh shadi 5
- hadis noorani zadeh 6
1 Faculty Member, Department of Educational Management and Planning, Faculty of Educational Sciences and Psychology, Shiraz University, Shiraz, Iran
2 PhD in Curriculum Planning, Shiraz University, Shiraz, Iran
3 M.A, executive management, Payam Noor Sari University, Sari city, Iran
4 Member of the academic staff, Department of Management and Curriculum Planning, Farhangian University, Shiraz, Iran
5 M.A., student of Curriculum Development Shiraz University, Shiraz, Iran.
6 M.A Student, Curriculum Planning, Shiraz University, Shiraz, Iran
Abstract
Purpose: It was an evaluative review of the use of artificial intelligence in general education.
Method and tools: This is a qualitative research of the synthesis type, which was carried out with an evaluative review method based on the five-step methodological framework of Amali and Arxi. The synthesis research team consisted of three lesson planning specialists, one person proficient in the synthesis research method, and one expert in searching databases. 52 research sources related to acceptance criteria, including articles on the systematic review of artificial intelligence in education, how artificial intelligence plays a role in production, strengthening education and learning in the present and future, and the impact of artificial intelligence in facilitating and accelerating education and learning, were used as the basis of analysis
Findings: The result is the extraction of three themes organizing the role of artificial intelligence in learning, the role of artificial intelligence in teaching and the role of artificial intelligence in educational evaluation. The validity of the data was confirmed by using the three techniques of reliability, transferability and alignment of data and trust in data by carefully guiding the flow of information collection and alignment of researchers.
Results: In general, the findings of this article showed that artificial intelligence, if used correctly and responsibly, with the advantage of being data-oriented and creating a vast and unlimited field of education, causes effective learning. It also outlines the potential path of human-machine dialogue systems in the future and shows a deep insight into future educational and
Keywords
مختاری، سیدعلی محمد و رضوانی، ریحانه.(1401). کاربرد هوش مصنوعی در آموزش تاریخ. پژوهش در آموزش تاریخ، 3(4). 20.1001.1.28211014.1401.3.4.5.9
اشتری ماهینی، مریم وکلارستاقی، منوچهر.(1395). هوش مصنوعی در فرایند یاددهی-یادگیری. اولین همایش ملی فناوری در مهندسی کاربردی باشگاه پژوهشگران جوان و نخبگان دانشگاه آزاد اسلامی واحد تهران غرب.
انصاری, سراجی و یوسف زاده. (1400). چیستی، چرایی و چگونگی آموزش سواد رسانهای در دورهی ابتدایی. فصلنامه فن آوری اطلاعات و ارتباطات در علوم تربیتی، 11(4)، 127-174.
فهیمیراد، مهرناز و کوتمجانی، صدیقه. (1397). مروری بر کاربرد هوش مصنوعی در آموزش و یادگیری در زمینه های آموزشی. مجله بین المللی یادگیری و توسعه، 8(4)، 106-118. DOI:10.5296/ijld.v8i4.14057
اصغریان، فاطمه و راجی، محسن. (1402). یک سیستم تشخیص نفوذ مبتنی بر یادگیری عمیق برای CAN Bus. مجله فناوری اطلاعات و ارتباطات، 57(57)، 20. 20.1001.1.27170411.1402.15.57.2.7
منافی بوجوشین، صفا، مقسمی، حمیدرضا و وصلی، الهام. (1397). طبقه بندی تصاویر ضبط شده از راه دور با استفاده از الگوریتم یادگیری عمیق CNN.
سلطانی، مریم، خاتمی فیروزآبادی، سید محمدعلی، امیری، مقصود و حاجیان حیدری، مجتبی. (2023). رویکرد ترکیبی پیشبینی تقاضای کانال همهجانبۀ یکپارچه، با استفاده از یادگیری ماشین-خوشهبندی سریهای زمانی با الگوریتم پیچش زمانی پویا و شبکههای عصبی مصنوعی. مدیریت تولید و عملیات، 14(1)، 121-140. 10.22108/POM.2023.136202.1485
شیخیوند، سبحان، موسوی، زهره، یوسفی رضایی، توحید، و اعلایی، شعله. (1401). تشخیص هیجانات القاشده با تحریک شنوایی از سیگنالهای EEG براساس شبکههای یادگیری عمیق. هوش محاسباتی در مهندسی برق، 13(1)، 1-18. 10.22108/ISEE.2020.122304.1357
کردآبادی مجتبی، منصوری زاده، محرم و ختن لو، حسن. (1398). روشی ترکیبی و نیمه نظارتی مبتنی بر گراف برای برچسب زنی خودکار تصاویر.
مهرپارسا، سحر. (1399). هوش مصنوعی و کاربرد آن در آموزش. مطالعات مدیریت و کار آفرینی, 33(6).
Fahimirad, M., & Kotamjani, S. (2017). An overview of the use of artificial intelligence in teaching and learning in educational fields. International Journal of Learning and Development, 8(4), 106-118. DOI:10.5296/ijld.v8i4.14057 [In persian]
Fan, X., & Zhong, X. (2022). Artificial intelligence-based creative thinking skill analysis model using human–computer interaction in art design teaching. Computers and Electrical Engineering, 100, 107957, https://doi.org/10.1016/j.compeleceng.2022.107957
Flogie, A., & Krabonja, M. V. (2023, June). Artificial intelligence in education: developing competencies and supporting teachers in implementing AI in school learning environments. In 2023 12th Mediterranean Conference on Embedded Computing (MECO).IEEE, DOI: 10.1109/MECO58584.2023.10155054
Foltynek, T., Bjelobaba, S., Glendinning, I., Khan, Z. R., Santos, R., Pavletic, P., & Kravjar, J. (2023). ENAI Recommendations on the ethical use of Artificial Intelligence in Education. International Journal for Educational Integrity, 19(1), 12.
George, M. P. (2022). An Innovative Cloud Based Digital Health Application integrated with Artificial Intelligence Modules for User Oriented Medical Nutrition Therapy, http://hdl.handle.net/20.500.14146/10622
Gregory, S., Gregory, B., Reiners, T., Fardinpour, A., Hillier, M., Lee, M., ... & Larson, I. (2013). Virtual worlds in Australian and New Zealand higher education: Remembering the past, understanding the present and imagining the future. In Electric Dreams-ascilite 2013 Conference Proceedings Sydney. Macquarie University.
Gu, R., Xi, Z., Lin, B., & Ji, Y. (2022, March). Teacher-guided Autonomous Learning Enabled by Artificial Intelligence Empowered Remote Experiment Platform. In 2022 IEEE Global Engineering Education Conference (EDUCON). IEEE, DOI: 10.1109/EDUCON52537.2022.9766531
Hamid, O. H., Smith, N. L., & Barzanji, A. (2017, July). Automation, per se, is not job elimination: How artificial intelligence forwards cooperative human-machine coexistence. In 2017 IEEE 15th International Conference on Industrial Informatics (INDIN) (pp. 899-904). IEEE, DOI: 10.1109/INDIN.2017.8104891
Holmes, W., Bialik, M., & Fadel, C. (2023). Artificial intelligence in education. Globethics Publications,
Holmes, W., Persson, J., Chounta, I. A., Wasson, B., & Dimitrova, V. (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe.
Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial intelligence for assessment and feedback to enhance student success in higher education. Mathematical Problems in Engineering, 2022, https://doi.org/10.1155/2022/5215722
Huang, X. (2021). Aims for cultivating students’ key competencies based on artificial intelligence education in China. Education and Information Technologies, 26.
Huang, X., & Qiao, C. (2022). Enhancing computational thinking skills through artificial intelligence education at a STEAM high school. Science & Education.
Jokhan, A., Chand, A. A., Singh, V., & Mamun, K. A. (2022). Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance. Sustainability, 14(4), 2377, https://doi.org/10.3390/su14042377
Justice, L. M., Ahn, W. Y., & Logan, J. A. (2019). Identifying children with clinical language disorder: an application of machine-learning classification. Journal of Learning Disabilities, 52(5), 351-365. https://doi.org/10.1177/0022219419845070
Kassymova, G. K., Malinichev, D. M., Lavrinenko, S. V., Panichkina, M. V., Koptyaeva, S. V., & Arpentieva, M. R. (2023). Ethical Problems of Digitalization and Artificial Intelligence in Education: A Global Perspective. Journal of Pharmaceutical Negative Results, https://doi.org/10.47750/pnr.2023.14.S02.254
Khalifa, N. E., Loey, M., & Mirjalili, S. (2022). A comprehensive survey of recent trends in deep learning for digital images augmentation. Artificial Intelligence Review.
Kharbat, F. F., Alshawabkeh, A., & Woolsey, M. L. (2021). Identifying gaps in using artificial intelligence to support students with intellectual disabilities from education and health perspectives. Aslib Journal of Information Management, 73(1), 101-128. https://doi.org/10.1108/AJIM-02-2020-0054
Kordabadi, M., Mansourizadeh, M., & Khatanlu, H. (2018). A hybrid and semi-supervised graph-based method for automatic image labeling. [In persian]
Kuo-Hung, C., Kuo-En, C., Chung-Hsien, L., Kinshuk, & Yao-Ting, S. (2016). Integration of mobile AR technology in performance assessment. Journal of Educational Technology & Society, 19(4).
Lesia Viktorivna, K., Andrii Oleksandrovych, V., Iryna Oleksandrivna, K., & Nadia Oleksandrivna, K. (2022). Artificial Intelligence in Language Learning: What Are We Afraid Of. Arab World English Journal.
Leung, C. H., Deng, J. J., & Li, Y. (2022, December). Enhanced Human-Machine Interactive Learning for Multimodal Emotion Recognition in Dialogue System. In Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence (pp. 1-7).
Limna, P., Jakwatanatham, S., Siripipattanakul, S., Kaewpuang, P., & Sriboonruang, P. (2022). A review of artificial intelligence (AI) in education during the digital era. Advance Knowledge for Executives, 1(1).
Lin, S., Döngül, E. S., Uygun, S. V., Öztürk, M. B., Huy, D. T. N., & Tuan, P. V. (2022). Exploring the relationship between abusive management, self-efficacy and organizational performance in the context of human–machine interaction technology and artificial intelligence with the effect of ergonomics. Sustainability, 14(4), 1949, https://doi.org/10.3390/su14041949
Liu, X., & Huang, X. (2022). Design of artificial intelligence-based english network teaching (AI-ENT) system. Mathematical Problems in Engineering, 2022, https://doi.org/10.1155/2022/1849430
Liu, X., & Li, Y. (2022, February). Redefining Teacher Qualification in the Artificial Intelligence Era: A Professional Capital Perspective. In Proceedings of the 5th International Conference on Big Data and Education, https://doi.org/10.1145/3524383.3524405
Luckin, R., Cukurova, M., Kent, C., & du Boulay, B. (2022). Empowering educators to be AI-ready. Computers and Education: Artificial Intelligence, 3, 100076. https://doi.org/10.1016/j.caeai.2022.100076
Lutz, É., & Coradi, P. C. (2022). Applications of new technologies for monitoring and predicting grains quality stored: Sensors, internet of things, and artificial intelligence. Measurement, 188, 110609. https://doi.org/10.1016/j.measurement.2021.110609
Malinka, K., Peresíni, M., Firc, A., Hujnak, O., & Janus, F. (2023, June). On the educational impact of ChatGPT: Is Artificial Intelligence ready to obtain a university degree?. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1, https://doi.org/10.1145/3587102.3588827
Manafi Bujushin, S., Moqsemi, H., & Vasli, E. (2017). Classification of remotely sensed images using CNN deep learning algorithm. [In persian]
Mays, N., Roberts, E. and Popay, J. (2001) Synthesising research evidence. In N. Fulop, P. Allen, A. Clarke and N. Black (eds) Studying the Organisation and Delivery of Health Services: Research Methods (London: Routledge).
Megahed, N. A., Abdel-Kader, R. F., & Soliman, H. Y. (2022, April). Post-pandemic education strategy: framework for artificial intelligence-empowered education in engineering (AIEd-Eng) for lifelong learning. In International Conference on Advanced Machine Learning Technologies and Applications. Cham: Springer International Publishing.
Mehrparsa, Sahar (2019). Artificial intelligence and its application in education. Management and Entrepreneurship Studies, 33(6). [In persian]
Mokhtari, S. A.M., & Rezvani, R. (2022). The use of artificial intelligence in history education. Research in history education, 3(4). 20.1001.1.28211014.1401.3.4.5.9 [In persian]
Murtarelli, G., Gregory, A., & Romenti, S. (2021). A conversation-based perspective for shaping ethical human–machine interactions: The particular challenge of chatbots. Journal of Business Research, 129, https://doi.org/10.1016/j.jbusres.2020.09.018
Nazaretsky, T., Bar, C., Walter, M., & Alexandron, G. (2022, March). Empowering teachers with AI: Co-designing a learning analytics tool for personalized instruction in the science classroom. In LAK22: 12th International Learning Analytics and Knowledge Conference, https://doi.org/10.1145/3506860.3506861
Nemorin, S., Vlachidis, A., Ayerakwa, H. M., & Andriotis, P. (2023). AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development. Learning, Media and Technology, 48(1), 38-51. https://doi.org/10.1080/17439884.2022.2095568
Newbronner, E., & Hare, P. (2002). Services to support carers of people with mental health problems: Consultation report. Social Policy Research Unit, University of York, York.
Osamy, W., Khedr, A. M., Salim, A., AlAli, A. I., & El-Sawy, A. A. (2022). Recent studies utilizing artificial intelligence techniques for solving data collection, aggregation and dissemination challenges in wireless sensor networks: a review. Electronics, 11(3), https://doi.org/10.3390/electronics11030313.
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(6).
Pallathadka, H., Sonia, B., Sanchez, D. T., De Vera, J. V., Godinez, J. A. T., & Pepito, M. T. (2022). Investigating the impact of artificial intelligence in education sector by predicting student performance. Materials Today: Proceedings, 51, https://doi.org/10.1016/j.matpr.2021.11.395
Park, S. B., Park, J. H., & Jung, S. (2023). Comparative aesthetic assessment of machine learning and human judgment for building wall designs. Architectural Science Review, 1-11. https://doi.org/10.1080/00038628.2023.2278500
Pawson, R. (2002) Evidence-based policy: in search of a method. Evaluation, 8, 2, https://doi.org/10.1177/1358902002008002512
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development.
Pham, S. T., & Sampson, P. M. (2022). The development of artificial intelligence in education: A review in context. Journal of Computer Assisted Learning, 38(5), https://doi.org/10.1111/jcal.12687
Prahani, B. K., Rizki, I. A., Jatmiko, B., Suprapto, N., & Amelia, T. (2022). Artificial Intelligence in Education Research During the Last Ten Years: A Review and Bibliometric Study. International Journal of Emerging Technologies in Learning.
Randhawa, G. K., & Jackson, M. (2020, January). The role of artificial intelligence in learning and professional development for healthcare professionals. In Healthcare management forum (Vol. 33, No. 1). Sage CA: Los Angeles, CA: SAGE Publications. https://doi.org/10.1177/0840470419869032
Rangel-de Lázaro, G., & Duart, J. M. (2023). You Can Handle, You Can Teach It: Systematic Review on the Use of Extended Reality and Artificial Intelligence Technologies for Online Higher Education. Sustainability, 15(4), 3507. https://doi.org/10.3390/su15043507
Ribino, P. (2023). The role of politeness in human–machine interactions: a systematic literature review and future perspectives. Artificial Intelligence Review.
Rice, M. F., & Dunn, S. (2023). The use of artificial intelligence with students with identified disabilities: A systematic review with critique. Computers in the Schools, 40(4), 370-390. https://doi.org/10.1080/07380569.2023.2244935
Ringwood, J. V., & Galvin, G. (2002). Computer-aided learning in artificial neural networks. IEEE Transactions on Education, 45(4), 10.1109/TE.2002.804401
Ritchie, J., & Spencer, L. (2002). Qualitative data analysis for applied policy research. In Analyzing qualitative data. Routledge.
Rodríguez-García, J. D., Moreno-León, J., Román-González, M., & Robles, G. (2021, March). Evaluation of an online intervention to teach artificial intelligence with learningml to 10-16-year-old students. In Proceedings of the 52nd ACM technical symposium on computer science education, https://doi.org/10.1145/3408877.3432393
Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26.
Ruiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023). Empowering Education with Generative Artificial Intelligence Tools: Approach with an Instructional Design Matrix. Sustainability, 15(15), 11524. https://doi.org/10.3390/su151511524
Salas-Pilco, S. Z., Xiao, K., & Hu, X. (2022). Artificial intelligence and learning analytics in teacher education: A systematic review. Education Sciences, 12(8), https://doi.org/10.3390/educsci12080569
Sanders, K., Kriz, R., Liu, A., & Van Durme, B. (2022). Ambiguous images with human judgments for robust visual event classification. Advances in Neural Information Processing Systems, 35, 2637-2650. https://doi.org/10.48550/arXiv.2210.03102
Sanusi, I. T., Olaleye, S. A., Agbo, F. J., & Chiu, T. K. (2022). The role of learners’ competencies in artificial intelligence education. Computers and Education: Artificial Intelligence, 3, 100098. https://doi.org/10.1016/j.caeai.2022.100098, https://doi.org/10.1016/j.caeai.2022.100098
Sanusi, I. T., Olaleye, S. A., Agbo, F. J., & Chiu, T. K. (2022). The role of learners’ competencies in artificial intelligence education. Computers and Education: Artificial Intelligence, 3, 100098. https://doi.org/10.1016/j.caeai.2022.100098
Sanusi, I. T., Olaleye, S. A., Oyelere, S. S., & Dixon, R. A. (2022). Investigating learners’ competencies for artificial intelligence education in an African K-12 setting. Computers and Education Open, 3, 100083. https://doi.org/10.1016/j.caeo.2022.100083
SAVAŞ, S. (2021). Artificial intelligence and innovative applications in education: the case of Turkey. Journal of Information Systems and Management Research, 3(1).
Shang, H., & Sivaparthipan, C. B. (2022). Interactive teaching using human-machine interaction for higher education systems. Computers and Electrical Engineering, 100, 107811. https://doi.org/10.1016/j.compeleceng.2022.107811
Sheikhi-vand, S., Mousavi, Z., Yousefi Rezaei, T., & Alaei, S. (2023). Detection of emotions induced by auditory stimulation from EEG signals based on deep learning networks. Computational Intelligence in Electrical Engineering, 13(1), 1-18. 10.22108/ISEE.2020.122304.1357 [In persian]
Soltani, M., Khatami Firouzabadi, S. M. A., Amiri, M., & Hajian Heydari, M. (2023). A hybrid approach to integrated omnidirectional channel demand forecasting using machine learning-time series clustering with dynamic time convolution algorithm and artificial neural networks. Production and Operations Management, 14(1), 121-140. 10.22108/POM.2023.136202.1485 [In persian]
Su, J., & Zhong, Y. (2022). Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions. Computers and Education: Artificial Intelligence, 3, 100072. https://doi.org/10.1016/j.caeai.2022.100072
Su, J., Ng, D. T. K., & Chu, S. K. W. (2023). Artificial intelligence (AI) literacy in early childhood education: The challenges and opportunities. Computers and Education: Artificial Intelligence, 4, 100124. https://doi.org/10.1016/j.caeai.2023.100124
Susnjak, T. (2022). ChatGPT: The end of online exam integrity?. arXiv preprint arXiv:2212.09292. https://doi.org/10.48550/arXiv.2212.09292
Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial Intelligence in Education: AIEd for Personalised Learning Pathways. Electronic Journal of e-Learning, 20(5).
Wang, H., Guo, B., Zeng, Y., Ding, Y., Qiu, C., Zhang, Y., ... & Yu, Z. (2022). Enabling Harmonious Human-Machine Interaction with Visual-Context Augmented Dialogue System: A Review. arXiv preprint arXiv:2207.00782.
https://doi.org/10.48550/arXiv.2207.00782
https://doi.org/10.48550/arXiv.2207.00782
Wang, S., Sun, Z., & Chen, Y. (2023). Effects of higher education institutes’ artificial intelligence capability on students' self-efficacy, creativity and learning performance. Education and Information Technologies, 28(5).
Wong, G. K., Ma, X., Dillenbourg, P., & Huan, J. (2020). Broadening artificial intelligence education in K-12: where to start?. ACM Inroads, 11(1), https://doi.org/10.1145/3381884
Xia, Q., Chiu, T. K., Lee, M., Sanusi, I. T., Dai, Y., & Chai, C. S. (2022). A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education. Computers & Education, 189, 104582.
Xia, Q., Chiu, T. K., Zhou, X., Chai, C. S., & Cheng, M. (2022). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 100118.
Xue, Y., & Wang, Y. (2022). Artificial intelligence for education and teaching. Wireless Communications and Mobile Computing, 2022, https://doi.org/10.1155/2022/4750018
Yau, K. W., Chai, C. S., Chiu, T. K., Meng, H., King, I., & Yam, Y. (2023). A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools. Education and Information Technologies, 28(1).
Zhan, Z., Tong, Y., Lan, X., & Zhong, B. (2022). A systematic literature review of game-based learning in Artificial Intelligence education. Interactive Learning Environments, https://doi.org/10.1080/10494820.2022.2115077
Zioga, I., Harrison, P. M., Pearce, M. T., Bhattacharya, J., & Luft, C. D. B. (2020). From learning to creativity: Identifying the behavioural and neural correlates of learning to predict human judgements of musical creativity. NeuroImage, 206, 116311. https://doi.org/10.1016/j.neuroimage.2019.116311
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