بررسی استفاده از سیستم‌های هوش مصنوعی برای تشخیص و تصحیح خطاهای محتوای آموزشی در یادگیری الکترونیکی

نوع مقاله : مروری

نویسندگان

1 استادیار، فناوری اطلاعات، دانشگاه پیام نور، تهران

2 گروه علوم پایه، دانشکده پزشکی، دانشگاه علوم پزشکی اردبیل، اردبیل، ایران.

چکیده

مقاله حاضر به بررسی اهمیت تشخیص و تصحیح خطاهای محتوای آموزشی در یادگیری الکترونیکی و نقش سیستم‌های هوش مصنوعی در بهبود کیفیت آموزش و یادگیری می‌پردازد. با رشد سریع پلتفرم‌های یادگیری آنلاین، تقاضا برای محتوای آموزشی با کیفیت بالا افزایش یافته است، اما اشتباهات و نادرستی‌ها در محتوای آموزشی می‌توانند تأثیرات جدی بر تجربه یادگیری دانش‌آموزان داشته باشند. در این راستا، سیستم‌های هوش مصنوعی به عنوان راه‌حلی امیدوارکننده برای شناسایی و اصلاح اشتباهات در محتوای آموزشی ظهور کرده‌اند. این سیستم‌ها توانایی تجزیه‌وتحلیل حجم وسیعی از داده‌ها و شناسایی خطاها و ناسازگاری‌ها را دارند و می‌توانند بهبود قابل توجهی در کیفیت آموزش و یادگیری ایجاد کنند. پیاده‌سازی سیستم‌های هوش مصنوعی به عنوان ابزاری مؤثر برای ارتقاء تجربه یادگیری دانش‌آموزان و افزایش بهره‌وری مربیان در فرآیند آموزش هستند. این مقاله به بررسی نقش اساسی سیستم‌های هوش مصنوعی در ارتقاء تجربه یادگیری می‌پردازد و نشان می‌دهد که چگونه این سیستم‌ها می‌توانند بهبود قابل توجهی در تشخیص و اصلاح خطاهای محتوای آموزشی و بهبود کیفیت آموزش و یادگیری ایجاد کنند. در نهایت، این مقاله به عنوان یک منبع ارزشمند برای محققان و متخصصان حوزه یادگیری الکترونیکی معرفی شده و نقش اساسی سیستم‌های هوش مصنوعی در تحول و بهبود در حوزه یادگیری الکترونیکی را برجسته می‌کند

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Investigating the Use of Artificial Intelligence Systems to Detect and Correct Educational Content Errors in E-Learning

نویسندگان [English]

  • Mohammad Mohsen sadr 1
  • mohsen khani 2
1 Assistant Professor, Information Technology, Payam Noor University, Tehran
2 Ph.D. Department of Basic Science, School of Medicine, Ardabil University of Medical Science, Ardabil, Iran
چکیده [English]

This article examines the importance of identifying and correcting errors in educational content in e-learning and the role of artificial intelligence systems in improving the quality of education and learning. With the rapid growth of online learning platforms, there has been an increased demand for high-quality educational content. However, mistakes and inaccuracies in educational content can have serious effects on students' learning experiences. In this regard, artificial intelligence systems have emerged as a promising solution for identifying and correcting errors in educational content. These systems can analyze large volumes of data and identify errors and inconsistencies, significantly improving the quality of education and learning. Implementing artificial intelligence systems is an effective tool for enhancing students' learning experiences and increasing the efficiency of educators in the teaching process. This article examines the fundamental role of artificial intelligence systems in enhancing the learning experience and demonstrates how these systems can significantly improve the detection and correction of errors in educational content, ultimately leading to improved quality of education and learning. Finally, this article is introduced as a valuable resource for researchers and experts in the field of e-learning, highlighting the essential role of artificial intelligence systems in transforming and improving e-learning

کلیدواژه‌ها [English]

  • Artificial Intelligence
  • Error Detection
  • Educational Content
  • Error Correction

مراجع

Alam, A. (2022). Employing adaptive learning and intelligent tutoring robots for virtual classrooms and smart campuses: reforming education in the age of artificial intelligence. In Advanced Computing and Intelligent Technologies: Proceedings of ICACIT 2022 (pp. 395-406). Springer.
Alam, A., & Mohanty, A. (2022). Business models, business strategies, and innovations in EdTech companies: integration of learning analytics and artificial intelligence in higher education. 2022 IEEE 6th Conference on Information and Communication Technology (CICT)
Ali, O., Abdelbaki, W., Shrestha, A., Elbasi, E., Alryalat, M. A. A., & Dwivedi, Y. K. (2023). A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities. Journal of Innovation & Knowledge, 8(1), 100333.
Alrikabi, H. T. S., Jasim, N. A., Majeed, B. H., Abass, A. Z., & ALRubee, I. R. N. (2022). Smart learning based on Moodle E-learning platform and digital skills for University students. International Journal of Recent Contributions from Engineering, Science & IT (iJES), 10(01), 109-120
Bencherif, F. (2022). Investigating Learners’ Lexical Errors on Writing Process A Case Study of Third Year Pupils at SAIB BOULREBAH High School in SIDI OKBA-BISKRA.
Bharadiya, J. P. (2023). A Comparative Study of Business Intelligence and Artificial Intelligence with Big Data Analytics. American Journal of Artificial Intelligence, 7(1), 24.
Birhane, A., Isaac, W., Prabhakaran, V., Diaz, M., Elish, M. C., Gabriel, I., & Mohamed, S. (2022). Power to the people? opportunities and challenges for participatory AI. Equity and Access in Algorithms, Mechanisms, and Optimization, 1-8.
Chaudhry, M. A., & Kazim, E. (2022). Artificial Intelligence in Education (AIEd): A high-level academic and industry note 2021. AI and Ethics, 1-9.
Huang, A. Y., Lu, O. H., & Yang, S. J. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684.
Jan, Z., Ahamed, F., Mayer, W., Patel, N., Grossmann, G., Stumptner, M., & Kuusk, A. (2023). Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities. Expert Systems with Applications, 216, 119456.
Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022). Artificial intelligence applications for industry 4.0: A literature-based study. Journal of Industrial Integration and Management, (01)7, 83-111.
Jayakumar, S., Sounderajah, V., Normahani, P., Harling, L., Markar, S. R., Ashrafian, H., & Darzi, A. (2022). Quality assessment standards in artificial intelligence diagnostic accuracy systematic reviews: a meta-research study. NPJ Digital Medicine, 5(1), 11.
Khani, M., Sadr, M. M., & Jamali, S. (2024). Deep reinforcement learning‐based resource allocation in multi‐access edge computing. Concurrency and Computation: Practice and Experience, e7995.
Lee, H. (2023). The rise of ChatGPT: Exploring its potential in medical education. Anatomical Sciences Education.
McIntosh, T. R., Liu, T., Susnjak, T., Watters, P., Ng, A., & Halgamuge, M. N. (2023). A culturally sensitive test to evaluate nuanced gpt hallucination. IEEE Transactions on Artificial Intelligence.
Meera, S., & Geerthik, S. (2022). Natural language processing. Artificial Intelligent Techniques for Wireless Communication and Networking, 139-153.
Munir, H., Vogel, B., & Jacobsson, A. (2022). Artificial intelligence and machine learning approaches in digital education: a systematic revision. Information, 13(4), 203.
Naik, N., Hameed, B., Shetty, D. K., Swain, D., Shah, M., Paul, R., Aggarwal, K., Ibrahim, S., Patil, V., & Smriti, K. (2022). Legal and ethical consideration in artificial intelligence in healthcare: who takes responsibility? Frontiers in surgery, 9, 266.
Paiva, J. C., Leal, J. P., & Figueira, Á. (2022). Automated assessment in computer science education: A state-of-the-art review. ACM Transactions on Computing Education (TOCE), 22(3), 1-40.
Pandey, A. (2023). E-Learning and Education 4.0: Revolution in Education of 21st Century. International Conference on Digital Technologies and Applications,
Pratama, M. P., Sampelolo, R., & Lura, H. (2023). Revolutionizing Education: Harnessing the Power of Artificial Intelligence for Personalized Learning. Klasikal: Journal of Education, Language Teaching and Science, 5(2), 350-357.
Rusmiyanto, R., Huriati, N., Fitriani, N., Tyas, N. K., Rofi’i, A., & Sari, M. N. (2023). The Role of Artificial Intelligence (AI) In Developing English Language Learner's Communication Skills. Journal on Education, 6(1), 750-757.
Srinivasa, K., Kurni, M., & Saritha, K. (2022). Harnessing the Power of AI to Education. In Learning, Teaching, and Assessment Methods for Contemporary Learners: Pedagogy for the Digital Generation (pp. 311-342). Springer.
Tulaskar, R., & Turunen, M. (2022). What students want? Experiences, challenges, and engagement during Emergency Remote Learning amidst COVID-19 crisis. Education and information technologies, 27(1), 551-587.
Wang, H., Wang, D., Liu, H., & Tang, G. (2022). A predictive sliding local outlier correction method with adaptive state change rate determining for bearing remaining useful life estimation. Reliability Engineering & System Safety, 225, 108601.
Wilianto, D., & Girsang, A. S. (2023). Automatic Short Answer Grading on High School's E-Learning Using Semantic Similarity Methods. TEM Journal, 12(1).
Xu, H., Wang, H., Zhang, Z., Tu, H., Xiong, J., Xiang, X., Wei, C., & Mishra, Y. K. (2023). High efficiency Al-based multicomponent composites for low-temperature hydrogen production and its hydrolysis mechanism. International Journal of Hydrogen Energy.
Zare, Hossein; Abdullahi, Mohammad Hossein and Azad, Esfandiar (2022). Virtual reality Applications in neurological and psychological interventions, Arjmand Publication
Zare, Hossein, Haddadi, Samaneh. (2023). Virtual reality, augmented reality and artificial intelligence in special education: a practical guide to supporting students with learning differences, Arjmand Publication
فصلنامه علمی پژوهش در یادگیری آموزشگاهی و مجازی
دوره 11، شماره 4 - شماره پیاپی 44
اردیبهشت 1403
صفحه 81-91

فایل ها

هم رسانی

ارجاع به این مقاله

آمار