Araştırma Makalesi
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Use of Internet of Things Tools in Distance Education: A Systematic Literature Review

Yıl 2023, Cilt: 19 Sayı: 3, 394 - 414, 29.12.2023
https://doi.org/10.17860/mersinefd.1291873

Öz

: In this study, the descriptive features and research trends of distance education studies using Internet of Things (IoT) tools were examined. Within the scope of the study, 319 articles in the Web of Science (WOS) database were reviewed, and 42 of them that met the research criteria were analyzed by content analysis method. The results show that there has been an increase in the number of studies on IoT over the years. Especially after the COVID-19 pandemic, there has been an increase in the use of IoT devices in distance education. Most of the studies examined were carried out in Asian countries such as China, Taiwan, and Japan. Studies on improving the learning environment, developing remote experiment systems, monitoring student behaviors, and developing smart learning environments come to the fore. Internet of Things tools offer many opportunities that can be used in distance education learning environments. These tools can be used to improve learners’ experience, help teachers track student progress, and increase the efficiency of educational institutions. The articles highlight the advantages of using IoT technologies in education and reveal their important role in improving the learning experience.

Kaynakça

  • Ahmad, I., Khusro, S., Alam, I., Khan, I., & Niazi, B. (2022). Towards a low-cost teacher orchestration using ubiquitous computing devices for detecting student’s engagement. Wireless Communications and Mobile Computing, 2022, 1-21. https://doi.org/10.1155/2022/7979766
  • Alrashidi, M. (2023). Synergistic integration between internet of things and augmented reality technologies for deaf persons in e-learning platform. The Journal of Supercomputing, 79(10), 10747–10773. https://doi.org/10.1007/s11227-022-04952-z
  • Altınpulluk, H., & Kilinc, H. (2022). The opinions of field experts on the usability of ınternet-of-things technology in open and distance learning environments. International Journal of Information and Communication Technology Education (IJICTE), 18(1), 1-17.
  • Altman, D. G. (1990). Practical statistics for medical research. CRC press.
  • Bao, Y. F. (2016). Analysis of the learning evaluation of distance education based on the Internet of Things. World Transactions on Engineering and Technology Education, 14(1), 168-172.
  • Bauer, M. W. (2000). Classical content analysis: A review. In M. W. Bauer & G. Gaskell (Eds.), Qualitative researching with text, image and sound (pp. 131-151). Sage.
  • Chen, D. (2022). Application of Iot-oriented online education platform in English teaching. Mathematical Problems in Engineering, 2022, 1-9. https://doi.org/10.1155/2023/9763061
  • Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological measurement, 20(1), 37-46.
  • Dai, Z., Zhang, Q., Zhu, X., & Zhao, L. (2021). A comparative study of Chinese and foreign research on the internet of things in education: Bibliometric analysis and visualization. IEEE Access, 9, 130127-130140.
  • dos Santos, F. R., & Notargiacomo, P. (2018). Intelligent educational assistant based on multiagent system and context-aware computing. International Journal of Advanced Computer Science and Applications, 9(4), 236-243.
  • Farhan, M., Jabbar, S., Aslam, M., Hammoudeh, M., Ahmad, M., Khalid, S., . . . Han, K. (2018). IoT-based students interaction framework using attention-scoring assessment in eLearning. Future Generation Computer Systems, 79(3), 909-919.
  • García-Loro, F., Baizán, P., Blázquez-Merino, M., Plaza, P., Aroca, A. M., Orduña, P., . . . Castro, M. (2019). Spreading remote laboratory scope through a federation of nodes: VISIR case. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 14(4), 107-116.
  • Giannakas, F., Troussas, C., Krouska, A., Voyiatzis, I., & Sgouropoulou, C. (2022). Blending cybersecurity education with IoT devices: A u-Learning scenario for introducing the man-in-the-middle attack. Information Security Journal: A Global Perspective, 32(5), 371-382. https://doi.org/10.1080/19393555.2022.2100297
  • Guo, J., Dai, Y., Wang, C., Wu, H., Xu, T., & Lin, K. (2020). A physiological data‐driven model for learners' cognitive load detection using HRV‐PRV feature fusion and optimized XGBoost classification. Software: Practice and Experience, 50(11), 2046-2064.
  • Ikuesan, A. R., Razak, S. A., Venter, H. S., & Salleh, M. (2019). Polychronicity tendency-based online behavioral signature. International Journal of Machine Learning and Cybernetics, 10, 2103-2118.
  • ITU. (2005). The internet of things. Retrieved from https://www.itu.int/net/wsis/tunis/ newsroom/stats/The-Internet-of-Things-2005.pdf
  • Kong, X. T., Chen, G. W., Huang, G. Q., & Luo, H. (2017). Ubiquitous auction learning system with TELD (Teaching by Examples and Learning by Doing) approach: A quasi-experimental study. Computers & Education, 111, 144-157.
  • Kumar, J. A. (2021). Educational chatbots for project-based learning: investigating learning outcomes for a team-based design course. International Journal of Educational Technology in Higher Education, 18(1), 1-28.
  • Lian, J., Zhou, Y., Han, L., & Yu, Z. (2022). Virtual reality and ınternet of things-based music online learning via the graph neural network. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/3316886
  • Mershad, K., Damaj, A., Wakim, P., & Hamieh, A. (2020). LearnSmart: A framework for integrating internet of things functionalities in learning management systems. Education and Information Technologies, 25, 2699-2732.
  • Miglino, O., Di Ferdinando, A., Di Fuccio, R., Rega, A., & Ricci, C. (2014). Bridging digital and physical educational games using RFID/NFC technologies. Journal of e-Learning and Knowledge Society, 10(3), 89-106.
  • Oda, T., Matsuo, K., Barolli, L., Yamada, M., & Liu, Y. (2017). Design and implementation of an IoT-based e-learning testbed. International Journal of Web and Grid Services, 13(2), 228-241.
  • Pappas, M. A., Demertzi, E., Papagerasimou, Y., Koukianakis, L., Voukelatos, N., & Drigas, A. (2019). Cognitive-based E-learning design for older adults. Social Sciences, 8(1). https://doi.org/10.3390/socsci8010006
  • Pecori, R. (2018). A virtual learning architecture enhanced by fog computing and big data streams. Future Internet, 10(1). https://doi.org/10.3390/fi10010004
  • Rahmani, A. M., Ali Naqvi, R., Hussain Malik, M., Malik, T. S., Sadrishojaei, M., Hosseinzadeh, M., & Al-Musawi, A. (2021). E-learning development based on internet of things and blockchain technology during COVID-19 pandemic. Mathematics, 9(24), 3151.
  • Rahmani, A. M., Ehsani, A., Mohammadi, M., Mohammed, A. H., Karim, S. H. T., & Hosseinzadeh, M. (2022). A new model for analyzing the role of new ICT-based technologies on the success of employees' learning programs. Kybernetes, 51(6), 2156-2171.
  • Ramlowat, D. D., & Pattanayak, B. K. (2019). Exploring the internet of things (IoT) in education: a review. Information Systems Design and Intelligent Applications, 2, 245-255.
  • Robles-Gómez, A., Tobarra, L., Pastor-Vargas, R., Hernández, R., & Cano, J. (2020). Emulating and evaluating virtual remote laboratories for cybersecurity. Sensors, 20(11). https://doi.org/10.3390/s20113011
  • Robles-Gómez, A., Tobarra, L., Pastor-Vargas, R., Hernández, R., & Haut, J. M. (2021). Analyzing the users’ acceptance of an IoT cloud platform using the UTAUT/TAM model. IEEE Access, 9, 150004-150020.
  • Said, O., & Albagory, Y. (2017). Internet of things-based free learning system: performance evaluation and communication perspective. IETE Journal of Research, 63(1), 31-44.
  • Setiawan, R., Devadass, M. M. V., Rajan, R., Sharma, D. K., Singh, N. P., Amarendra, K., . . . Sengan, S. (2022). IoT based virtual E-learning system for sustainable development of smart cities. Journal of Grid Computing, 20(3), 24.
  • Shen, Y. (2022). Application of internet of things in online teaching of adult education based on android voice assistant. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/8915889
  • Silva, B. N., Khan, M., & Han, K. (2018). Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society, 38, 697-713.
  • Simić, K., Despotovic-Zrakic, M., Bojovic, Z., Jovanic, B., & Knezevic, D. (2016). A platform for a smart learning environment. Electronics and Energetics, 29(3), 407-417. https://doi.org/10.2298/FUEE1603407S
  • Stojanović, D., Bogdanović, Z., Petrović, L., Mitrović, S., & Labus, A. (2020). Empowering learning process in secondary education using pervasive technologies. Interactive Learning Environments, 31(2), 779-792. https://doi.org/10.1080/10494820.2020.1806886
  • Sun, L. H., Ge, X. L., & Chen, Z. J. (2017). Application prospect of technology in higher education in the future–based on the analysis of horizon report 2017 (higher education edition). Audio-Visual Education Research, 38, 121-128.
  • Taamallah, A., & Khemaja, M. (2015). Providing pervasive Learning eXperiences by Combining Internet of Things and e-Learning standards. Education in the Knowledge Society, 16(4), 98-117.
  • Valencia de Almeida, F., Hayashi, V. T., Arakaki, R., Midorikawa, E., Canovas, S. d. M., Cugnasca, P. S., & Corrêa, P. L. P. (2022). Teaching digital electronics during the covıd-19 pandemic via a remote lab. Sensors, 22(18), 6944.
  • Wang, J., Chen, X., & Gao, X. (2020). Economic management teaching mode based on mobile learning and collaborative learning. IEEE Access, 8, 200589-200596.
  • Wang, X., Fang, Z., & Sun, X. (2016). Usage patterns of scholarly articles on Web of Science: a study on Web of Science usage count. Scientometrics, 109(2), 917-926.
  • Wang, Y. (November, 2010). English interactive teaching model which based upon Internet of Things. Paper presented at International Conference on Computer Application and System Modeling (ICCASM), Taiyuan. Retrieved from https://ieeexplore.ieee.org/document/5622914
  • Wang, Y. (2022). Design of cloud video distance education system based on internet of things. IETE Journal of Research, 1-10. https://doi.org/10.1080/03772063.2021.2021826
  • Wong, W.-K., Chen, K.-P., & Lin, J.-W. (2020). Real-time data logging and online curve fitting using raspberry pi in physics laboratories. International Journal of Distance Education Technologies (IJDET), 18(3), 57-77.
  • Xie, C., Li, C., Sung, S., & Jiang, R. (2022). Engaging students in distance learning of science with remote labs 2.0. IEEE Transactions on Learning Technologies, 15(1), 15-31.
  • Yamada, M., Cuka, M., Liu, Y., Oda, T., Matsuo, K., & Barolli, L. (2017). Evaluation of an IoT-based e-learning testbed: performance of OLSR protocol in a NLoS environment and mean-shift clustering approach considering electroencephalogram data. International Journal of Web Information Systems, 13(1), 2-13.
  • Yang, Y., & Yu, K. (2016). Construction of distance education classroom in architecture specialty based on internet of things technology. International Journal of Emerging Technologies in Learning, 11(5), 56-61.
  • Yu, P.-J., & Xiong, M.-Z. (2022). Remote vocal singing course design based on embedded system and ınternet of things. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/8712081 Zhen, C., & Hu, K. (2022). Design of edge computing online classroom based on college english teaching. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/7068923
  • Zhong, R. Y., & Huang, G. Q. (2014). RFID-enabled learning supply chain: A smart pedagogical environment for TELD. International Journal of Engineering Education, 30(2), 471-482.

Nesnelerin İnterneti Araçlarının Uzaktan Eğitimde Kullanımı: Sistematik Alan Yazın Taraması

Yıl 2023, Cilt: 19 Sayı: 3, 394 - 414, 29.12.2023
https://doi.org/10.17860/mersinefd.1291873

Öz

Bu çalışmada nesnelerin interneti (IoT) araçlarının kullanıldığı uzaktan eğitim çalışmalarının betimsel özellikleri ve araştırma eğilimleri incelenmiştir. Çalışma kapsamında Web of Science (WOS) veri tabanında yer alan 319 makale ele alınmış, bunlardan araştırma kriterlerine uyan 42 tanesi içerik analizi yöntemiyle incelenmiştir. Elde edilen sonuçlar yıllar içerisinde IoT ile ilgili çalışmaların sayısında artış olduğunu göstermektedir. Özellikle COVID-19 pandemisi sonrası IoT’nin uzaktan eğitimde kullanımında artış olmuştur. Araştırma kapsamında incelenen çalışmaların büyük kısmı Çin, Tayvan, Japonya gibi Asya ülkelerinde gerçekleştirilmiştir. Yapılan çalışmalarda öğrenme ortamını iyileştirmek, uzaktan deney sistemleri geliştirmek, öğrenci davranışlarının takip edilmesi ve akıllı öğrenme ortamlarının geliştirilmesi ile ilgili çalışmalar öne çıkmaktadır. Nesnelerin interneti araçları, uzaktan eğitim ortamlarında kullanılabilecek birçok fırsat sunmaktadır. Bu araçlar, öğrencilerin öğrenme deneyimini iyileştirmek, öğretmenlerin öğrenci ilerlemesini takip etmelerine yardımcı olmak ve eğitim kurumlarının verimliliğini artırmak için kullanılabilir. Makaleler, IoT teknolojilerinin eğitimde kullanımının avantajlarını vurgulamakta ve öğrencilerin öğrenme deneyimini geliştirmede önemli bir rol oynadığını ortaya koymaktadır.

Kaynakça

  • Ahmad, I., Khusro, S., Alam, I., Khan, I., & Niazi, B. (2022). Towards a low-cost teacher orchestration using ubiquitous computing devices for detecting student’s engagement. Wireless Communications and Mobile Computing, 2022, 1-21. https://doi.org/10.1155/2022/7979766
  • Alrashidi, M. (2023). Synergistic integration between internet of things and augmented reality technologies for deaf persons in e-learning platform. The Journal of Supercomputing, 79(10), 10747–10773. https://doi.org/10.1007/s11227-022-04952-z
  • Altınpulluk, H., & Kilinc, H. (2022). The opinions of field experts on the usability of ınternet-of-things technology in open and distance learning environments. International Journal of Information and Communication Technology Education (IJICTE), 18(1), 1-17.
  • Altman, D. G. (1990). Practical statistics for medical research. CRC press.
  • Bao, Y. F. (2016). Analysis of the learning evaluation of distance education based on the Internet of Things. World Transactions on Engineering and Technology Education, 14(1), 168-172.
  • Bauer, M. W. (2000). Classical content analysis: A review. In M. W. Bauer & G. Gaskell (Eds.), Qualitative researching with text, image and sound (pp. 131-151). Sage.
  • Chen, D. (2022). Application of Iot-oriented online education platform in English teaching. Mathematical Problems in Engineering, 2022, 1-9. https://doi.org/10.1155/2023/9763061
  • Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological measurement, 20(1), 37-46.
  • Dai, Z., Zhang, Q., Zhu, X., & Zhao, L. (2021). A comparative study of Chinese and foreign research on the internet of things in education: Bibliometric analysis and visualization. IEEE Access, 9, 130127-130140.
  • dos Santos, F. R., & Notargiacomo, P. (2018). Intelligent educational assistant based on multiagent system and context-aware computing. International Journal of Advanced Computer Science and Applications, 9(4), 236-243.
  • Farhan, M., Jabbar, S., Aslam, M., Hammoudeh, M., Ahmad, M., Khalid, S., . . . Han, K. (2018). IoT-based students interaction framework using attention-scoring assessment in eLearning. Future Generation Computer Systems, 79(3), 909-919.
  • García-Loro, F., Baizán, P., Blázquez-Merino, M., Plaza, P., Aroca, A. M., Orduña, P., . . . Castro, M. (2019). Spreading remote laboratory scope through a federation of nodes: VISIR case. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 14(4), 107-116.
  • Giannakas, F., Troussas, C., Krouska, A., Voyiatzis, I., & Sgouropoulou, C. (2022). Blending cybersecurity education with IoT devices: A u-Learning scenario for introducing the man-in-the-middle attack. Information Security Journal: A Global Perspective, 32(5), 371-382. https://doi.org/10.1080/19393555.2022.2100297
  • Guo, J., Dai, Y., Wang, C., Wu, H., Xu, T., & Lin, K. (2020). A physiological data‐driven model for learners' cognitive load detection using HRV‐PRV feature fusion and optimized XGBoost classification. Software: Practice and Experience, 50(11), 2046-2064.
  • Ikuesan, A. R., Razak, S. A., Venter, H. S., & Salleh, M. (2019). Polychronicity tendency-based online behavioral signature. International Journal of Machine Learning and Cybernetics, 10, 2103-2118.
  • ITU. (2005). The internet of things. Retrieved from https://www.itu.int/net/wsis/tunis/ newsroom/stats/The-Internet-of-Things-2005.pdf
  • Kong, X. T., Chen, G. W., Huang, G. Q., & Luo, H. (2017). Ubiquitous auction learning system with TELD (Teaching by Examples and Learning by Doing) approach: A quasi-experimental study. Computers & Education, 111, 144-157.
  • Kumar, J. A. (2021). Educational chatbots for project-based learning: investigating learning outcomes for a team-based design course. International Journal of Educational Technology in Higher Education, 18(1), 1-28.
  • Lian, J., Zhou, Y., Han, L., & Yu, Z. (2022). Virtual reality and ınternet of things-based music online learning via the graph neural network. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/3316886
  • Mershad, K., Damaj, A., Wakim, P., & Hamieh, A. (2020). LearnSmart: A framework for integrating internet of things functionalities in learning management systems. Education and Information Technologies, 25, 2699-2732.
  • Miglino, O., Di Ferdinando, A., Di Fuccio, R., Rega, A., & Ricci, C. (2014). Bridging digital and physical educational games using RFID/NFC technologies. Journal of e-Learning and Knowledge Society, 10(3), 89-106.
  • Oda, T., Matsuo, K., Barolli, L., Yamada, M., & Liu, Y. (2017). Design and implementation of an IoT-based e-learning testbed. International Journal of Web and Grid Services, 13(2), 228-241.
  • Pappas, M. A., Demertzi, E., Papagerasimou, Y., Koukianakis, L., Voukelatos, N., & Drigas, A. (2019). Cognitive-based E-learning design for older adults. Social Sciences, 8(1). https://doi.org/10.3390/socsci8010006
  • Pecori, R. (2018). A virtual learning architecture enhanced by fog computing and big data streams. Future Internet, 10(1). https://doi.org/10.3390/fi10010004
  • Rahmani, A. M., Ali Naqvi, R., Hussain Malik, M., Malik, T. S., Sadrishojaei, M., Hosseinzadeh, M., & Al-Musawi, A. (2021). E-learning development based on internet of things and blockchain technology during COVID-19 pandemic. Mathematics, 9(24), 3151.
  • Rahmani, A. M., Ehsani, A., Mohammadi, M., Mohammed, A. H., Karim, S. H. T., & Hosseinzadeh, M. (2022). A new model for analyzing the role of new ICT-based technologies on the success of employees' learning programs. Kybernetes, 51(6), 2156-2171.
  • Ramlowat, D. D., & Pattanayak, B. K. (2019). Exploring the internet of things (IoT) in education: a review. Information Systems Design and Intelligent Applications, 2, 245-255.
  • Robles-Gómez, A., Tobarra, L., Pastor-Vargas, R., Hernández, R., & Cano, J. (2020). Emulating and evaluating virtual remote laboratories for cybersecurity. Sensors, 20(11). https://doi.org/10.3390/s20113011
  • Robles-Gómez, A., Tobarra, L., Pastor-Vargas, R., Hernández, R., & Haut, J. M. (2021). Analyzing the users’ acceptance of an IoT cloud platform using the UTAUT/TAM model. IEEE Access, 9, 150004-150020.
  • Said, O., & Albagory, Y. (2017). Internet of things-based free learning system: performance evaluation and communication perspective. IETE Journal of Research, 63(1), 31-44.
  • Setiawan, R., Devadass, M. M. V., Rajan, R., Sharma, D. K., Singh, N. P., Amarendra, K., . . . Sengan, S. (2022). IoT based virtual E-learning system for sustainable development of smart cities. Journal of Grid Computing, 20(3), 24.
  • Shen, Y. (2022). Application of internet of things in online teaching of adult education based on android voice assistant. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/8915889
  • Silva, B. N., Khan, M., & Han, K. (2018). Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society, 38, 697-713.
  • Simić, K., Despotovic-Zrakic, M., Bojovic, Z., Jovanic, B., & Knezevic, D. (2016). A platform for a smart learning environment. Electronics and Energetics, 29(3), 407-417. https://doi.org/10.2298/FUEE1603407S
  • Stojanović, D., Bogdanović, Z., Petrović, L., Mitrović, S., & Labus, A. (2020). Empowering learning process in secondary education using pervasive technologies. Interactive Learning Environments, 31(2), 779-792. https://doi.org/10.1080/10494820.2020.1806886
  • Sun, L. H., Ge, X. L., & Chen, Z. J. (2017). Application prospect of technology in higher education in the future–based on the analysis of horizon report 2017 (higher education edition). Audio-Visual Education Research, 38, 121-128.
  • Taamallah, A., & Khemaja, M. (2015). Providing pervasive Learning eXperiences by Combining Internet of Things and e-Learning standards. Education in the Knowledge Society, 16(4), 98-117.
  • Valencia de Almeida, F., Hayashi, V. T., Arakaki, R., Midorikawa, E., Canovas, S. d. M., Cugnasca, P. S., & Corrêa, P. L. P. (2022). Teaching digital electronics during the covıd-19 pandemic via a remote lab. Sensors, 22(18), 6944.
  • Wang, J., Chen, X., & Gao, X. (2020). Economic management teaching mode based on mobile learning and collaborative learning. IEEE Access, 8, 200589-200596.
  • Wang, X., Fang, Z., & Sun, X. (2016). Usage patterns of scholarly articles on Web of Science: a study on Web of Science usage count. Scientometrics, 109(2), 917-926.
  • Wang, Y. (November, 2010). English interactive teaching model which based upon Internet of Things. Paper presented at International Conference on Computer Application and System Modeling (ICCASM), Taiyuan. Retrieved from https://ieeexplore.ieee.org/document/5622914
  • Wang, Y. (2022). Design of cloud video distance education system based on internet of things. IETE Journal of Research, 1-10. https://doi.org/10.1080/03772063.2021.2021826
  • Wong, W.-K., Chen, K.-P., & Lin, J.-W. (2020). Real-time data logging and online curve fitting using raspberry pi in physics laboratories. International Journal of Distance Education Technologies (IJDET), 18(3), 57-77.
  • Xie, C., Li, C., Sung, S., & Jiang, R. (2022). Engaging students in distance learning of science with remote labs 2.0. IEEE Transactions on Learning Technologies, 15(1), 15-31.
  • Yamada, M., Cuka, M., Liu, Y., Oda, T., Matsuo, K., & Barolli, L. (2017). Evaluation of an IoT-based e-learning testbed: performance of OLSR protocol in a NLoS environment and mean-shift clustering approach considering electroencephalogram data. International Journal of Web Information Systems, 13(1), 2-13.
  • Yang, Y., & Yu, K. (2016). Construction of distance education classroom in architecture specialty based on internet of things technology. International Journal of Emerging Technologies in Learning, 11(5), 56-61.
  • Yu, P.-J., & Xiong, M.-Z. (2022). Remote vocal singing course design based on embedded system and ınternet of things. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/8712081 Zhen, C., & Hu, K. (2022). Design of edge computing online classroom based on college english teaching. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/7068923
  • Zhong, R. Y., & Huang, G. Q. (2014). RFID-enabled learning supply chain: A smart pedagogical environment for TELD. International Journal of Engineering Education, 30(2), 471-482.
Toplam 48 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Alan Eğitimleri, Eğitim Teknolojisi ve Bilgi İşlem
Bölüm Makaleler
Yazarlar

Fahri Yılmaz 0000-0002-8290-9079

Doç. Dr. Selçuk Özdemir 0000-0002-6627-3381

Yayımlanma Tarihi 29 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 19 Sayı: 3

Kaynak Göster

APA Yılmaz, F., & Özdemir, D. D. S. (2023). Nesnelerin İnterneti Araçlarının Uzaktan Eğitimde Kullanımı: Sistematik Alan Yazın Taraması. Mersin Üniversitesi Eğitim Fakültesi Dergisi, 19(3), 394-414. https://doi.org/10.17860/mersinefd.1291873

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