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Öğrenme Analitikleri ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme

Year 2021, Volume: 10 Issue: 2, - , 31.12.2021

Abstract

Bu çalışmada öz-düzenlemeli öğrenme ve öğrenme analitikleri alanında yazılmış makaleler sistematik olarak incelenmiştir. Web of Science veri tabanından erişilen 72 makale belli ölçütlere göre analiz edilmiştir. Makalelerin yayınlandığı yıllar, yöntemleri, anahtar kelimeleri, yapıldığı ülkeler, veri toplama araçları, katılımcı düzeyleri, öğrenme alanları incelenmiş ve eğilimler belirlenmiştir. Araştırma konusuyla ilgili makalelerin son yıllarda artış gösterdiği görülmüştür. Makalelerde en fazla deneysel yöntemlerin tercih edildiği sonucuna ulaşılmıştır. Öğrenme alanlarına bakıldığında ise çeşitli alanlara rastlanmış ancak matematik ve mühendislik alanında yapılan çalışmaların sayısı ilk sıralarda yer almaktadır. Avustralya, ABD ve Avrupa ülkelerinin öne çıktığı araştırmada çevrimiçi öğrenme alanlarının gelişmesinde ülkelerin gelişmişlik düzeyinin ve coğrafi şartlarının etkili olduğu düşünülmektedir. Makalelerde yazarların daha çok öğrenci başarılarına ve öğrenme süreçlerine yönelik sonuçlara ulaştığı söylenebilir. Katılımcı olarak başta lisans düzeyi olmak üzere büyük oranda öğrenciler tercih edilmiştir. Öğrenmede büyük rolü olan eğitimcilere yönelik daha fazla çalışma yapılması tavsiye edilmektedir. Bu alanda ihtiyaç duyulan çalışmaların belirlenmesi ve gelecek çalışmalarda uygulayıcılara yol göstermesi açısından mevcut çalışmanın katkı sağlayacağı düşünülmektedir.

References

  • Aguilar, S. J., Karabenick, S. A., Teasley, S. D., & Baek, C. (2021). Associations between learning analytics dashboard exposure and motivation and self-regulated learning. Computers and Education, 162, 104085. https://doi.org/10.1016/j.compedu.2020.104085
  • Ahmad Uzir, N.A., Gasevic, D., Matcha, W., Jovanovic, J., & Pardo, A. (2020). Analytics of time management strategies in a flipped classroom. Journal of Computer Assisted Learning,36(1), 70-88https://doi.org/10.1111/jcal.12392
  • Bahçeci, F. (2015). Öğrenme yönetim sistemlerinde kullanılan öğrenme analitikleri araçlarının incelenmesi. Turkish Journal of Educational Studies, 2(1), 41–58. http://dergi.firat.edu.tr/index.php/turk-jes/article/download/56/31
  • Bozkurt, A. (2016). Öğrenme analitiği : e-öğrenme , büyük veri ve bireyselleştirilmiş öğrenme. Açıköğretim Uygulamaları ve Araştırma Dergisi, 2(4), 55–81. https://dergipark.org.tr/en/pub/auad/issue/34066/377071
  • Campbell, B. J. P., DeBlois, P. B., & Oblinger, diana G. (2007). Academic analytics: A new tool for a new era. EDUCAUSE Review, 51(2), 41–57. https://doi.org/10.1038/scientificamerican08201881-118
  • Cha, H., & Park, T. (2019). Applying and evaluating visualization design guidelines for a MOOC dashboard to facilitate self-regulated learning based on learning analytics. KSII Transactions on Internet & Information Systems, 13(6), 2799–2823. https://doi.org/10.3837/tiis.2019.06.002
  • Clow, D. (2012). The learning analytics cycle: closing the loop effectively. In Proceedings of the 2nd International conference on learning analytics and knowledge (pp. 134-138). https://doi.org/10.1145/2330601.2330636
  • Sáiz Manzanares, M. C., Marticorena Sánchez, R., García Osorio, C. I., & Díez-Pastor, J. F. (2017). How do B-learning and learning patterns influence learning outcomes?. Frontiers in Psychology, 8, 745. https://doi.org/10.3389/fpsyg.2017.00745
  • Drachsler, H., & Kalz, M. (2016). The MOOC and learning analytics innovation cycle (MOLAC): A reflective summary of ongoing research and its challenges. Journal of Computer Assisted Learning, 32(3), 281–290. https://doi.org/10.1111/jcal.12135
  • Erdemci, H. (2019). Öğrenme analitiklerinin öğrenenlerin öz düzenlemeli öğrenmelerine etkisini incelemesi.Doktora tezi, Trabzon Üniversitesi, Trabzon.
  • Gasevic, D., Mirriahi, N., Dawson, S., & Joksimovic, S. (2017). Effects of instructional conditions and experience on the adoption of a learning tool. Computers in Human Behavior, 67, 207-220. https://doi.org/10.1016/j.chb.2016.10.026
  • Gelan, A., Fastre, G., Verjans, M., Martin, N., Jansenswillen, N., Creemers, G., Lieben, M., & Micheal, T. (2018). Article affordances and limitations of learning analytics for computer-assisted language learning : A case study of the VITAL project. Computer Assisted Language Learning, 31(3) 294–319. https://doi.org/10.1080/09588221.2017.1418382
  • Gülcüoğlu, E., Karaoğlan Yılmaz, F. G., & Gökkaya, G. (2021). Öğrenme analitikleri kapsamında 2016-2019 yıllar arasında web of science veritabanında yayınlanan makalelerin betimsel analizi. Bilgi ve İletişim Teknolojileri Dergisi, 3(1), 42-76. https://dergipark.org.tr/en/pub/bited/issue/63346/876562
  • Howell, J., Roberts, L. D., & Mancini, V. O. (2018). Learning analytics messages: Impact of grade, sender, comparative information and message style on student affect and academic resilience. Computers in Human Behavior, 89, 8-15. https://doi.org/10.1016/j.chb.2018.07.021
  • Ifenthaler, D., Gibson, D., Prasse, D., Shimada, A., & Yamada, M. (2021). Putting learning back into learning analytics: Actions for policy makers, researchers, and practitioners. Educational Technology Research and Development, 69, 2131–2150. .https://doi.org/10.1007/s11423-020-09909-8
  • Jivet, I., Scheffel, M., Schmitz, M., Robbers, S., Specht, M., & Drachsler, H. (2020). From students with love: An empirical study on learner goals, self-regulated learning and sense-making of learning analytics in higher education. Internet and Higher Education, 47, 100758. https://doi.org/10.1016/j.iheduc.2020.100758
  • Karaoğlan Yılmaz, F. G.(2020). Öğrenme analitiği geribildirimleri ile desteklenmiş ters-yüz öğrenme ortamının çeşitli değişkenler açısından modellenmesi. Bilgi ve İletişim Teknolojileri Dergisi/Journal of Information and Communication Technologies, 1(2), 78–94. https://dergipark.org.tr/en/pub/bited/issue/54128/693779
  • Karaoglan Yilmaz, F. G., & Yilmaz, R. (2020). Student opinions about personalized recommendation and feedback based on learning analytics. Technology, Knowledge and Learning, 25(4), 753-768. https://doi.org/10.1007/s10758-020-09460-8
  • Karaoglan Yilmaz, F. G., & Yilmaz, R. (2021). Learning analytics as a metacognitive tool to influence learner transactional distance and motivation in online learning environments. Innovations in Education and Teaching International, 58(5), 575-585. https://doi.org/10.1080/14703297.2020.1794928
  • Kim, D., Yoon, M., Jo, I., & Branch, R. M. (2018). Learning analytics to support self-regulated learning in asynchronous online courses: A case study at a women’s university in South Korea. Computers & Education, 127, 233-251.https://doi.org/10.1016/j.compedu.2018.08.023
  • Kizilcec, R. F., Pérez-sanagustín, M., & Maldonado, J. J. (2016). Self-regulated learning strategies predict learner behavior and goal attainment in massive open online courses. Computers & Education, 104, 18-33.https://doi.org/10.1016/j.compedu.2016.10.001
  • Li, S., Du, H., Xing, W., Zheng, J., Chen, G., & Xie, C. (2020). Examining temporal dynamics of self-regulated learning behaviors in STEM learning : A network approach. Computers & Education, 158, 103987. https://doi.org/10.1016/j.compedu.2020.103987
  • Lim, L., & Dawson, S. (2020). Students sense-making of personalised feedback based on learning analytics. Australasian Journal of Educational Technology, 36(6), 15–33. https://doi.org/10.14742/ajet.6370
  • Long, P. D., & Siemens, G. (2014). Penetrating the fog: analytics in learning and education. Italian Journal of Educational Technology, 22(3), 132–137. https://ijet.itd.cnr.it/article/view/195
  • Lu, O. H. T., Huang, J. C. H., Huang, A. Y. Q., Yang, S. J. H. (2017). Applying learning analytics for improving students engagement and learning outcomes in an MOOCs enabled collaborative programming course. Interactive Learning Environments, 25(2), 220-234. https://doi.org/10.1080/10494820.2016.1278391
  • Mangaroska, K., & Giannakos, M. (2019). Learning analytics for learning design: a systematic literature review of analytics-driven design to enhance learning. IEEE Transactions on Learning Technologies, 12(4), 516–534. https://doi.org/10.1109/TLT.2018.2868673
  • Matcha, W., Gaˇ, D., Pardo, A., Lim, L., Maldonado-mahauad, J., Gentili, S., & Mar, P. (2020). Analytics of learning strategies : Role of course design and delivery modality. Journal of Learning Analytics, 7(2), 45–71. https://doi.org/10.18608/jla.2020.72.3
  • Montgomery, A. P., Mousavi, A., Carbonaro, M., Hayward, D. V, & Dunn, W. (2017). Using learning analytics to explore self-regulated learning in flipped blended learning music teacher education. British Journal of Educational Technology, 50(1), 114-127.https://doi.org/10.1111/bjet.12590
  • Namoun, A., & Alshanqiti, A. (2021). Predicting student performance using data mining and learning analytics techniques: A systematic literature review. Applied Sciences, 11(1), 237. https://doi.org/10.3390/app11010237
  • Pérez-álvarez, R., Maldonado-mahauad, J., & Pérez-sanagustín, M. (2018). Design of a tool to support self-regulated learning strategies in MOOCs. Journal of Universal Computer Science, 24(8), 1090–1109. https://doi.org/10.3217/jucs-024-08-1090
  • Pintrich, P. R. (1995). Understanding self-regulated learning. New Directions for Teaching and Learning, 1995(63), 3–12. https://doi.org/10.1002/tl.37219956304
  • Roberts, L. D., Howell, J. A., & Seaman, K. (2017). Give me a customizable dashboard : personalized learning analytics dashboards in higher education. Technology, Knowledge and Learning, 22(3), 317–333. https://doi.org/10.1007/s10758-017-9316-1
  • Silva, J. C., Erik, Z., Rodrigo Lins, R., Jorge Luis, C. R., & Fernando da Fonseca de, S. (2018). Effects of learning analytics on students ’ self-regulated learning in flipped classroom. International Journal of Information and Communication Technology Education, 14(3), 91–107. https://doi.org/10.4018/IJICTE.2018070108
  • Tabuenca, B., Kalz, M., Drachsler, H., & Specht, M. (2015). Time Will Tell: The role of mobile learning analytics in self-regulated learning Bernardo. Computers & Education, 89, 53-74.https://doi.org/10.1016/j.compedu.2015.08.004
  • Tang, H. (2021). Person-centered analysis of self-regulated learner profiles in MOOCs : A cultural perspective. Educational Technology Research and Development, 69(2), 1247-1269. https://doi.org/10.1007/s11423-021-09939-w
  • Tsai, Y., Rates, D., Moreno-marcos, P. M., Muñoz-merino, P. J., Jivet, I., Scheffel, M., Drachsler, H., Delgado, C., & Gašević, D. (2020). Learning analytics in European higher education -Trends and barriers. Computers & Education, 155(May), 103933. https://doi.org/10.1016/j.compedu.2020.103933
  • Valenzuela, C. G., González, C. G., Rojas, A., & Tagle, M. (2021). Learning analytics in higher education : a preponderance of analytics but very little learning ? International Journal of Educational Technology in Higher Education, 18(1), 1-19. https://doi.org/10.1186/s41239-021-00258-x
  • Valiente, J. A. R., Merino, P. J. M., Member, S., Kloos, C. D., Member, S., Niemann, K., Scheffel, M., & Wolpers, M. (2016). Analyzing the impact of using optional activities in self - regulated learning. IEEE Transactions on Learning Technologies, 9(3), 231-243.https://doi.org/10.1109/TLT.2016.2518172
  • Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98–110. https://doi.org/10.1016/j.chb.2018.07.027
  • Yilmaz, R., Karaoglan Yilmaz, F. G., & Kilic Cakmak, E. (2017). The impact of transactive memory system and interaction platform in collaborative knowledge construction on social presence and self-regulation. Interactive Learning Environments, 25(8), 949-969. https://doi.org/10.1080/10494820.2016.1224905
  • You, J. W. (2016). Identifying significant indicators using LMS data to predict course achievement in online learning. The Internet and Higher Education, 29, 23-30. https://doi.org/10.1016/j.iheduc.2015.11.003
  • Yu, X., Xiaoxue, C., & Michael, W. J. (2020). Factors that impact social networking in online self ‑ regulated learning activities. Educational Technology Research and Development, 68(6), 3077–3095. https://doi.org/10.1007/s11423-020-09843-9
  • Zheng, J., Xing, W., Zhu, G., Chen, G., & Zhao, H. (2020). Profiling self-regulation behaviors in STEM learning of engineering design. Computers & Education, 143, 103669. https://doi.org/10.1016/j.compedu.2019.103669
Year 2021, Volume: 10 Issue: 2, - , 31.12.2021

Abstract

References

  • Aguilar, S. J., Karabenick, S. A., Teasley, S. D., & Baek, C. (2021). Associations between learning analytics dashboard exposure and motivation and self-regulated learning. Computers and Education, 162, 104085. https://doi.org/10.1016/j.compedu.2020.104085
  • Ahmad Uzir, N.A., Gasevic, D., Matcha, W., Jovanovic, J., & Pardo, A. (2020). Analytics of time management strategies in a flipped classroom. Journal of Computer Assisted Learning,36(1), 70-88https://doi.org/10.1111/jcal.12392
  • Bahçeci, F. (2015). Öğrenme yönetim sistemlerinde kullanılan öğrenme analitikleri araçlarının incelenmesi. Turkish Journal of Educational Studies, 2(1), 41–58. http://dergi.firat.edu.tr/index.php/turk-jes/article/download/56/31
  • Bozkurt, A. (2016). Öğrenme analitiği : e-öğrenme , büyük veri ve bireyselleştirilmiş öğrenme. Açıköğretim Uygulamaları ve Araştırma Dergisi, 2(4), 55–81. https://dergipark.org.tr/en/pub/auad/issue/34066/377071
  • Campbell, B. J. P., DeBlois, P. B., & Oblinger, diana G. (2007). Academic analytics: A new tool for a new era. EDUCAUSE Review, 51(2), 41–57. https://doi.org/10.1038/scientificamerican08201881-118
  • Cha, H., & Park, T. (2019). Applying and evaluating visualization design guidelines for a MOOC dashboard to facilitate self-regulated learning based on learning analytics. KSII Transactions on Internet & Information Systems, 13(6), 2799–2823. https://doi.org/10.3837/tiis.2019.06.002
  • Clow, D. (2012). The learning analytics cycle: closing the loop effectively. In Proceedings of the 2nd International conference on learning analytics and knowledge (pp. 134-138). https://doi.org/10.1145/2330601.2330636
  • Sáiz Manzanares, M. C., Marticorena Sánchez, R., García Osorio, C. I., & Díez-Pastor, J. F. (2017). How do B-learning and learning patterns influence learning outcomes?. Frontiers in Psychology, 8, 745. https://doi.org/10.3389/fpsyg.2017.00745
  • Drachsler, H., & Kalz, M. (2016). The MOOC and learning analytics innovation cycle (MOLAC): A reflective summary of ongoing research and its challenges. Journal of Computer Assisted Learning, 32(3), 281–290. https://doi.org/10.1111/jcal.12135
  • Erdemci, H. (2019). Öğrenme analitiklerinin öğrenenlerin öz düzenlemeli öğrenmelerine etkisini incelemesi.Doktora tezi, Trabzon Üniversitesi, Trabzon.
  • Gasevic, D., Mirriahi, N., Dawson, S., & Joksimovic, S. (2017). Effects of instructional conditions and experience on the adoption of a learning tool. Computers in Human Behavior, 67, 207-220. https://doi.org/10.1016/j.chb.2016.10.026
  • Gelan, A., Fastre, G., Verjans, M., Martin, N., Jansenswillen, N., Creemers, G., Lieben, M., & Micheal, T. (2018). Article affordances and limitations of learning analytics for computer-assisted language learning : A case study of the VITAL project. Computer Assisted Language Learning, 31(3) 294–319. https://doi.org/10.1080/09588221.2017.1418382
  • Gülcüoğlu, E., Karaoğlan Yılmaz, F. G., & Gökkaya, G. (2021). Öğrenme analitikleri kapsamında 2016-2019 yıllar arasında web of science veritabanında yayınlanan makalelerin betimsel analizi. Bilgi ve İletişim Teknolojileri Dergisi, 3(1), 42-76. https://dergipark.org.tr/en/pub/bited/issue/63346/876562
  • Howell, J., Roberts, L. D., & Mancini, V. O. (2018). Learning analytics messages: Impact of grade, sender, comparative information and message style on student affect and academic resilience. Computers in Human Behavior, 89, 8-15. https://doi.org/10.1016/j.chb.2018.07.021
  • Ifenthaler, D., Gibson, D., Prasse, D., Shimada, A., & Yamada, M. (2021). Putting learning back into learning analytics: Actions for policy makers, researchers, and practitioners. Educational Technology Research and Development, 69, 2131–2150. .https://doi.org/10.1007/s11423-020-09909-8
  • Jivet, I., Scheffel, M., Schmitz, M., Robbers, S., Specht, M., & Drachsler, H. (2020). From students with love: An empirical study on learner goals, self-regulated learning and sense-making of learning analytics in higher education. Internet and Higher Education, 47, 100758. https://doi.org/10.1016/j.iheduc.2020.100758
  • Karaoğlan Yılmaz, F. G.(2020). Öğrenme analitiği geribildirimleri ile desteklenmiş ters-yüz öğrenme ortamının çeşitli değişkenler açısından modellenmesi. Bilgi ve İletişim Teknolojileri Dergisi/Journal of Information and Communication Technologies, 1(2), 78–94. https://dergipark.org.tr/en/pub/bited/issue/54128/693779
  • Karaoglan Yilmaz, F. G., & Yilmaz, R. (2020). Student opinions about personalized recommendation and feedback based on learning analytics. Technology, Knowledge and Learning, 25(4), 753-768. https://doi.org/10.1007/s10758-020-09460-8
  • Karaoglan Yilmaz, F. G., & Yilmaz, R. (2021). Learning analytics as a metacognitive tool to influence learner transactional distance and motivation in online learning environments. Innovations in Education and Teaching International, 58(5), 575-585. https://doi.org/10.1080/14703297.2020.1794928
  • Kim, D., Yoon, M., Jo, I., & Branch, R. M. (2018). Learning analytics to support self-regulated learning in asynchronous online courses: A case study at a women’s university in South Korea. Computers & Education, 127, 233-251.https://doi.org/10.1016/j.compedu.2018.08.023
  • Kizilcec, R. F., Pérez-sanagustín, M., & Maldonado, J. J. (2016). Self-regulated learning strategies predict learner behavior and goal attainment in massive open online courses. Computers & Education, 104, 18-33.https://doi.org/10.1016/j.compedu.2016.10.001
  • Li, S., Du, H., Xing, W., Zheng, J., Chen, G., & Xie, C. (2020). Examining temporal dynamics of self-regulated learning behaviors in STEM learning : A network approach. Computers & Education, 158, 103987. https://doi.org/10.1016/j.compedu.2020.103987
  • Lim, L., & Dawson, S. (2020). Students sense-making of personalised feedback based on learning analytics. Australasian Journal of Educational Technology, 36(6), 15–33. https://doi.org/10.14742/ajet.6370
  • Long, P. D., & Siemens, G. (2014). Penetrating the fog: analytics in learning and education. Italian Journal of Educational Technology, 22(3), 132–137. https://ijet.itd.cnr.it/article/view/195
  • Lu, O. H. T., Huang, J. C. H., Huang, A. Y. Q., Yang, S. J. H. (2017). Applying learning analytics for improving students engagement and learning outcomes in an MOOCs enabled collaborative programming course. Interactive Learning Environments, 25(2), 220-234. https://doi.org/10.1080/10494820.2016.1278391
  • Mangaroska, K., & Giannakos, M. (2019). Learning analytics for learning design: a systematic literature review of analytics-driven design to enhance learning. IEEE Transactions on Learning Technologies, 12(4), 516–534. https://doi.org/10.1109/TLT.2018.2868673
  • Matcha, W., Gaˇ, D., Pardo, A., Lim, L., Maldonado-mahauad, J., Gentili, S., & Mar, P. (2020). Analytics of learning strategies : Role of course design and delivery modality. Journal of Learning Analytics, 7(2), 45–71. https://doi.org/10.18608/jla.2020.72.3
  • Montgomery, A. P., Mousavi, A., Carbonaro, M., Hayward, D. V, & Dunn, W. (2017). Using learning analytics to explore self-regulated learning in flipped blended learning music teacher education. British Journal of Educational Technology, 50(1), 114-127.https://doi.org/10.1111/bjet.12590
  • Namoun, A., & Alshanqiti, A. (2021). Predicting student performance using data mining and learning analytics techniques: A systematic literature review. Applied Sciences, 11(1), 237. https://doi.org/10.3390/app11010237
  • Pérez-álvarez, R., Maldonado-mahauad, J., & Pérez-sanagustín, M. (2018). Design of a tool to support self-regulated learning strategies in MOOCs. Journal of Universal Computer Science, 24(8), 1090–1109. https://doi.org/10.3217/jucs-024-08-1090
  • Pintrich, P. R. (1995). Understanding self-regulated learning. New Directions for Teaching and Learning, 1995(63), 3–12. https://doi.org/10.1002/tl.37219956304
  • Roberts, L. D., Howell, J. A., & Seaman, K. (2017). Give me a customizable dashboard : personalized learning analytics dashboards in higher education. Technology, Knowledge and Learning, 22(3), 317–333. https://doi.org/10.1007/s10758-017-9316-1
  • Silva, J. C., Erik, Z., Rodrigo Lins, R., Jorge Luis, C. R., & Fernando da Fonseca de, S. (2018). Effects of learning analytics on students ’ self-regulated learning in flipped classroom. International Journal of Information and Communication Technology Education, 14(3), 91–107. https://doi.org/10.4018/IJICTE.2018070108
  • Tabuenca, B., Kalz, M., Drachsler, H., & Specht, M. (2015). Time Will Tell: The role of mobile learning analytics in self-regulated learning Bernardo. Computers & Education, 89, 53-74.https://doi.org/10.1016/j.compedu.2015.08.004
  • Tang, H. (2021). Person-centered analysis of self-regulated learner profiles in MOOCs : A cultural perspective. Educational Technology Research and Development, 69(2), 1247-1269. https://doi.org/10.1007/s11423-021-09939-w
  • Tsai, Y., Rates, D., Moreno-marcos, P. M., Muñoz-merino, P. J., Jivet, I., Scheffel, M., Drachsler, H., Delgado, C., & Gašević, D. (2020). Learning analytics in European higher education -Trends and barriers. Computers & Education, 155(May), 103933. https://doi.org/10.1016/j.compedu.2020.103933
  • Valenzuela, C. G., González, C. G., Rojas, A., & Tagle, M. (2021). Learning analytics in higher education : a preponderance of analytics but very little learning ? International Journal of Educational Technology in Higher Education, 18(1), 1-19. https://doi.org/10.1186/s41239-021-00258-x
  • Valiente, J. A. R., Merino, P. J. M., Member, S., Kloos, C. D., Member, S., Niemann, K., Scheffel, M., & Wolpers, M. (2016). Analyzing the impact of using optional activities in self - regulated learning. IEEE Transactions on Learning Technologies, 9(3), 231-243.https://doi.org/10.1109/TLT.2016.2518172
  • Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98–110. https://doi.org/10.1016/j.chb.2018.07.027
  • Yilmaz, R., Karaoglan Yilmaz, F. G., & Kilic Cakmak, E. (2017). The impact of transactive memory system and interaction platform in collaborative knowledge construction on social presence and self-regulation. Interactive Learning Environments, 25(8), 949-969. https://doi.org/10.1080/10494820.2016.1224905
  • You, J. W. (2016). Identifying significant indicators using LMS data to predict course achievement in online learning. The Internet and Higher Education, 29, 23-30. https://doi.org/10.1016/j.iheduc.2015.11.003
  • Yu, X., Xiaoxue, C., & Michael, W. J. (2020). Factors that impact social networking in online self ‑ regulated learning activities. Educational Technology Research and Development, 68(6), 3077–3095. https://doi.org/10.1007/s11423-020-09843-9
  • Zheng, J., Xing, W., Zhu, G., Chen, G., & Zhao, H. (2020). Profiling self-regulation behaviors in STEM learning of engineering design. Computers & Education, 143, 103669. https://doi.org/10.1016/j.compedu.2019.103669
There are 43 citations in total.

Details

Primary Language Turkish
Subjects Studies on Education
Journal Section Makaleler
Authors

Gülay Çetintav 0000-0002-1042-7660

Fatma Gizem Karaoğlan Yılmaz 0000-0003-4963-8083

Publication Date December 31, 2021
Published in Issue Year 2021 Volume: 10 Issue: 2

Cite

APA Çetintav, G., & Karaoğlan Yılmaz, F. G. (2021). Öğrenme Analitikleri ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme. Amasya Üniversitesi Eğitim Fakültesi Dergisi, 10(2). https://doi.org/10.17539/amauefd.1036352
AMA Çetintav G, Karaoğlan Yılmaz FG. Öğrenme Analitikleri ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme. Amasya Üniversitesi Eğitim Fakültesi Dergisi. December 2021;10(2). doi:10.17539/amauefd.1036352
Chicago Çetintav, Gülay, and Fatma Gizem Karaoğlan Yılmaz. “Öğrenme Analitikleri Ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme”. Amasya Üniversitesi Eğitim Fakültesi Dergisi 10, no. 2 (December 2021). https://doi.org/10.17539/amauefd.1036352.
EndNote Çetintav G, Karaoğlan Yılmaz FG (December 1, 2021) Öğrenme Analitikleri ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme. Amasya Üniversitesi Eğitim Fakültesi Dergisi 10 2
IEEE G. Çetintav and F. G. Karaoğlan Yılmaz, “Öğrenme Analitikleri ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme”, Amasya Üniversitesi Eğitim Fakültesi Dergisi, vol. 10, no. 2, 2021, doi: 10.17539/amauefd.1036352.
ISNAD Çetintav, Gülay - Karaoğlan Yılmaz, Fatma Gizem. “Öğrenme Analitikleri Ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme”. Amasya Üniversitesi Eğitim Fakültesi Dergisi 10/2 (December 2021). https://doi.org/10.17539/amauefd.1036352.
JAMA Çetintav G, Karaoğlan Yılmaz FG. Öğrenme Analitikleri ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme. Amasya Üniversitesi Eğitim Fakültesi Dergisi. 2021;10. doi:10.17539/amauefd.1036352.
MLA Çetintav, Gülay and Fatma Gizem Karaoğlan Yılmaz. “Öğrenme Analitikleri Ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme”. Amasya Üniversitesi Eğitim Fakültesi Dergisi, vol. 10, no. 2, 2021, doi:10.17539/amauefd.1036352.
Vancouver Çetintav G, Karaoğlan Yılmaz FG. Öğrenme Analitikleri ve Öz-Düzenlemeli Öğrenme Üzerine Araştırma Eğilimlerinin İncelenmesi: Sistematik Bir İnceleme. Amasya Üniversitesi Eğitim Fakültesi Dergisi. 2021;10(2).

Amasya Üniversitesi Eğitim Fakültesi Dergisi (Amasya Education Journal)