دور تطبيقات الذكاء الاصطناعي في تعزيز الاستراتيجيات التعليمية في التعليم المدرسي (مراجعة الأدبيات)
الشريط الجانبي للمقالة
محتوى المقالة الرئيسي
الملخص
يستعرض هذا المقال الأدبيات المتعلقة بدور الذكاء الاصطناعي (AI) وتصور المعلمين لهذا الدور افي مجال الذكاء الاصطناعي في التعليم (AIED).
الخلفية: يتزايد دور الذكاء الاصطناعي في التعليم بسرعة، كما تنتشر المراجعات والتحليلات الوصفية في الأدبيات التربوية حول هذا الموضوع.
هدف الدراسة: تهدف الدراسة إلى مراجعة الأدبيات المتعلقة بدور تطبيقات الذكاء الاصطناعي في تعزيز الاستراتيجيات التعليمية في التعليم المدرسي. وقد تم تحليل 30 مقالا منشورا، لتحديد الأدوار المنوطة بالذكاء الاصطناعي فيما يتعلق بالمتعلمين، والمعلمين، والمعرفة، والبيئة الصفية عمومًا، مثل: دعم التحفيز أو تقديم تغذية راجعة مخصصة، بهدف تعزيز العملية التعليمية في التعليم المدرسي. تشير النتائج إلى وجود تداخل كبير بين دور المعلمين وما يتم تطوير الذكاء الاصطناعي لتحقيقه في مجال AIED. وعلى الرغم من أن أتمتة دور المعلمين بشكل كامل قد تبدو غير ممكنة في المستقبل المنظور، إلا أن طموح الأبحاث في هذا المجال يسير نحو أتمتة عدد متزايد من أدوار المعلمين.
تصميم الدراسة: اعتمدت الدراسة على منهجية المراجعة المنهجية، من خلال تحليل المحتوى لعدد من الدراسات السابقة (30 دراسة) التي تناولت توظيف الذكاء الاصطناعي في تعزيز الاستراتيجيات التعليمية في التعليم المدرسي، والتحديات المرتبطة بذلك. وتوصلت الدراسة إلى عدد من النتائج، من أبرزها: مساهمة تطبيقات الذكاء الاصطناعي في تعزيز دور المعلمين وجعله أكثر شمولا وتكاملا، كما تساعد على إثارة دافعية الطلبة، وتحفيزهم على استمرارية التعلم، وتوظيف استراتيجيات التعليم المختلفة بفعالية وكفاءة، وتساهم في رقمنه المناهج وتوفير تعليم افتراضي ملائم لمستويات الطلبة كافة، كما تمكن من الكشف عن جوانب القوة والضعف لدى الطلبة، مما يسمح بتقديم التوجيه المناسب لقدرات كل طالب، وبالتالي تنمية مهاراتهم المتنوعة.
This article reviews the literature on the role of Artificial Intelligence (AI) and how teachers’ roles are preceived within the field of Artificial Intelligence in Education (AIED).
Background: The role of AI in education is rapidly expanding, and reviews are descriptive analysis are alsom increasingly prevalent in the educational literarture.
Objective of the Study: The study aims to review existing literature on the role of AI applications in enhancing instructional strategies in school education. A total of 30 published articles were analyzed to identify the roles assigned to AI in relation to learners, teachers, knowledge, and the classroom environment as a whole—such as supporting motivation or providing personalized feedback—with the goal of improving the educational process in school settings. The findings reveal a significant overlap between teachers’ roles and what AI is being developed to achieve within the field of AIED. Although fully automating teachers’ roles may not be feasible in the foreseeable future, the ambition of research in this area appears to be the automation of an increasing number of educational functions traditionally performed by teachers.
Study Design: A systematic review approach was adopted, using content analysis of 30 prior studies focused on the employment of AI in enhancing educational strategies in school education, as well as the challenges associated with this enhancement. The study reached several key findings, most notably:
* AI applications contribute to enhancing and expanding the teacher's role, making it more comprehensive and integrated.
* They help stimulate student motivation and encourage continued learning.
* They support the effective and efficient use of various teaching strategies.
* They contribute to curriculum digitization and provide appropriate virtual learning for students of all levels.
* They enable the identification of students’ strengths and weaknesses, thus allowing for personalized guidance tailored to each learner’s capabilities, which in turn fosters the development of various student skills.
المقاييس
تفاصيل المقالة
هذا العمل مرخص بموجب Creative Commons Attribution-NonCommercial 4.0 International License.
المراجع
Arabic References:
Abdul Majid, Q. (2009). The use of artificial intelligence in electrical engineering applications (Unpublished master's thesis). Arab Academy in Denmark.
Abu Shamaila, R. (2013). The effectiveness of an artificial intelligence-based program in developing inferential thinking and academic achievement in the subject of information technology among eleventh-grade female students in Gaza (Unpublished master's thesis). Faculty of Education, Islamic University.
Al-Abbasi, A. H. (2013). Introduction to artificial neural networks and their applications in social sciences using SPSS. Institute of Statistical Studies and Research, Cairo.
Al-Barai, A. (2022). Applications of artificial intelligence and robotics from the perspective of Islamic jurisprudence. Dar Al-Iftaa Egyptian Journal, 14(48), 12–159.
Al-Ghamdi, S., & Al-Furani, L. A. (2020). The reality of using artificial intelligence applications in special education schools in Jeddah from the perspective of female teachers and their attitudes toward it. International Journal of Educational and Psychological Studies, 8(1), 57–76.
Link: http://search.shamaa.org/FullRecord?ID=288590
Gaza, Palestine.
Al-Mahmoudi, M. S. A. (2019). Scientific research methodologies (3rd ed.). Sana'a: Dar Al-Kutub.
Al-Mutairi, A. (2019). Artificial intelligence as an approach to developing educational decision-making in the Ministry of Education in Kuwait. Journal of Scientific Research in Education, Ain Shams University, 11(10), 573–588.
Al-Saud, S. (2016). Educational applications of artificial intelligence in social studies. Slook Journal, 3(4), 133–163.
Al-Sharqawi, A. M. (2011). Artificial intelligence and neural networks (2nd ed.). Imam University Publications, Baghdad, Iraq.
Al-Sumaida'i, I. (2009). Artificial intelligence and expert systems. Dar Al-Jame'ah Publishing, Cairo, Egypt.
Al-Talhi, M. D., & Al-Omairi, F. A. Kh. (2023). Designing a proposed educational program based on artificial intelligence applications and measuring its effectiveness in developing spatial thinking skills and future geographic decision-making among talented high school students in Saudi Arabia. Islamic University Journal for Educational and Psychological Studies, 31(2), 472–503.
Badawi, M. A. H. (2022). Applications of artificial intelligence in education: Challenges and future prospects. Scientific Journal of the Egyptian Society for Educational Computers, 10(2), 93–108.
Bekkari, M. (2022). Challenges of artificial intelligence and its applications in education. Al-Muntada Journal for Economic Studies and Research, 6(1), 286–305.
Ibrahim, A. (2015). The impact of building a web-based expert system for student teachers to develop problem-solving skills and decision-making ability. Egyptian Society for Educational Technology.
Mahmoud, A. R. (2020). Applications of artificial intelligence: An approach to developing education amid the challenges of the COVID-19 pandemic. International Journal of Research in Educational Sciences, 3(4), 171–224.
Meera, A. K. (Ed.). (2019). Applications of artificial intelligence in education from the perspective of university faculty members. Proceedings of the First International Scientific Conference on Human Studies (Intelligence and Abilities), Journal of Psychological Sciences, University of Baghdad, Special Issue, 293–316.
Saad Allah, A., & Chetouh, W. (2019). The importance of artificial intelligence in developing education: AI applications as a modern trend to enhance business organizations’ competitiveness. Arab Democratic Center for Strategic, Political, and Economic Studies.
Shaaban, A. A. (2021). Artificial intelligence and its applications in higher education. Faculty of Education, Educational Journal, 1(84), 1–21.
UNESCO. (2021). Artificial Intelligence and Education: Guidance for Policy-makers. Paris, France.
UNICEF. (2021). Policy guidance on artificial intelligence for children. New York: Office of Global Insight and Policy.
Yassin, S. (2005). E-Management and the prospects of its Arab applications. Center of Research for Publishing and Distribution, Riyadh.
English References:
Adlawan, D. (2024). Top 8 AI Tools for Teachers That Will Save You Time in 2024 (Updated). https://www.classpoint.io/blog/a
Aldosari, S. A. M. (2020). The future of higher education in the light of artificial intelligence transformations. International Journal of Higher Education, 9(3), 145–151.
Ally, M. (2019). Competency profile of the digital and online teacher in future education. International Review of Research in Open and Distributed Learning, 20(2).
Benhadj, Y., El Messaoudi, M., & Nfissi, A. (2019). Artificial intelligence in education: Integrating serious gaming into the language class. IAES International Journal of Artificial Intelligence, 8(4), 382.
Beyaz, S. (2020). A brief history of artificial intelligence and robotic surgery in orthopedics & traumatology and future expectations. Joint Diseases and Related Surgery, 31(3), 653–655.
Bozkurt, A., & Goksel, N. (2018). Technology renovates itself: Key concepts on intelligent personal assistants (IPAs). Paper presented at the EDULEARN18. 10th International Conference on Education and New Learning Technology (Palma, July 2–4, 2018).
Büscher, C. (2020). Scaling up qualitative mathematics education research through artificial intelligence methods. For the Learning of Mathematics, 40(2), 2–7.
Cao, A., Xue, C., & Zhu, W. (2020). Application of big data in the management system of "Second Classroom Education" platform in universities. Journal of Physics: Conference Series, 93, 279–289.
Cukurova, M., Luckin, R., & Kent, C. (2019). Impact of an artificial intelligence research frame on the perceived credibility of educational research evidence. International Journal of Artificial Intelligence in Education, 1–31.
European Commission. (2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. European Union Publications Office.
Fryer, L. K. P., Nakao, K., & Thompson, A. (2019). Chatbot learning.
Grønmo, S. (2019). Social research methods: Qualitative, quantitative and mixed methods approach. SAGE Publications Limited.
Guan, C., Mou, J., & Jiang, Z. (2020). Artificial intelligence innovation in education: A twenty-year data-driven historical analysis. International Journal of Innovation Studies, 4(4), 134–147.
Kairu, C. (2020). Students’ attitude towards the use of artificial intelligence and machine learning to measure classroom engagement activities. Paper presented at EdMedia + Innovate Learning.
Loftus, M., & Madden, M. G. (2020). A pedagogy of data and artificial intelligence for student subjectification. Teaching in Higher Education, 25(4), 456–475.
Lv, Z., & Song, S. (2020). Integration of artificial intelligence plus industry and sports industry: A research on the innovation and development strategy of sports industry. Paper presented at the 2020 International Conference on Sports Sciences, Physical Education and Health (ICSSPEH 2020).
Meikleham, A., & Hugo, R. (2020). Understanding informal feedback to improve online course design. European Journal of Engineering Education, 45(1), 21–44.
Michaeli, T., Romeike, R., & Seegerer, S. (2023). What students can learn about artificial intelligence: Recommendations for K–12 computing education. In Proceedings of IFIP WCCE 2022: World Conference on Computers in Education, Hiroshima, 1–13.
Naidoo, J., & Singh-Pillay, A. (2020). Exploring mathematics teachers’ professional development: Embracing the Fourth Industrial Revolution. Universal Journal of Educational Research, 8(6), 2501–2508.
OIRA, M. (2018). Use of modern assistive technology and its effects on educational achievement of students with visual impairment at Kibos Special Secondary School, Kisumu County, Kenya (Doctoral dissertation, Kenyatta University).
Paiva, R., de Holanda, J. F. S., Peixoto, M. D., & Vieira, J. P. (2019). Augmenting teachers with data science powers: Joining human and artificial intelligence to assist students. Paper presented at the Brazilian Symposium on Computers in Education (SBIE).
Pence, H. E. (2019). Artificial intelligence in higher education: new wine in old wineskins? Journal of Educational Technology Systems, 48(1), 5–13.
Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 22.
Rienties, B., Køhler Simonsen, H., & Herodotou, C. (2020). Defining the boundaries between artificial intelligence in education, computer-supported collaborative learning, educational data mining, and learning analytics: A need for coherence. Paper presented at Frontiers in Education.
Sammut, C. (2013). The child machine vs the world brain. Informatica, 37.
Sapci, A. H., & Sapci, H. A. (2020). Artificial intelligence education and tools for medical and health informatics students: Systematic review. JMIR Medical Education, 6(1), e19285.
Sourani, M. (2020). Artificial intelligence: A prospective or real option for education? Al Jinan, 11(1), 121–139.
Timms, M. 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.
Touretzky, D. S., & McCune, C. G. (2022). Artificial intelligence thinking in K–12. In S.-C. Kong & H. Abelson (Eds.), Computational Thinking Education in K–12: Artificial Intelligence Literacy and Physical Computing (Chap. 8). Cambridge, MA: The MIT Press.
UNESCO. (2022). K–12 AI curricula: A mapping of government-endorsed AI curricula. Paris, France.
Wartman, S. A., & Combs, C. D. (2018). Medical education must move from the information age to the age of artificial intelligence. Academic Medicine, 93(8), 1107–1109.
Zain, F. M., & Sailin, S. N. (2020). Students' experience with flipped learning approach in higher education. Universal Journal of Educational Research, 8(10), 4946–4958.