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E-Öğrenme Ortamları ve Öğrenme Analitikleri

Year 2021, , 327 - 336, 31.07.2021
https://doi.org/10.17671/gazibtd.709798

Abstract

2020 yılı Horizon raporunda da vurgulandığı üzere, son yıllarda etkili öğrenme ortamları tasarlamak için ele alınan kavramlardan biri de öğrenme analitikleridir. Öğretim teknolojileri alanında, öğrenme analitiklerinin 10 yıllık bir geçmişi olmasına rağmen henüz gelişiminin erken aşamalarında olduğu düşünülmektedir. Öğrenme analitiklerinin kullanılabilmesi için eğitim bilimleri, istatistik, matematik, makine öğrenmesi ve yazılım geliştirme gibi disiplinler arası pek çok bilgi ve beceriye ihtiyaç duyulmaktadır. Bu çalışmanın amacı, öğrenme analitiklerinin e-öğrenme ortamları açısından potansiyelini ortaya koyarak öğretim tasarımcıları ve uygulayıcılar tarafından daha fazla tanınmasını sağlamaktır. Bu bağlamda, öğrenme analitiklerinin kapsamı, uygulama alanları ve aşamaları açıklanmaktadır. Ayrıca, öğrenme analitiklerinde kullanılan göstergeler, veri kaynakları, araç ve sistemler sunulmaktadır. Öğrenme analitiği süreç modeli ile öğrenme analitiği sunan öğrenme panellerinin kullanımı özetlenmektedir. Son olarak, bu konudaki güvenlik, etik ve standartlaşma kavramları ile ilgili çalışmalardaki sınırlıklar tartışılmaktadır.

Supporting Institution

TUBİTAK

Project Number

117R050

Thanks

Bu çalışma TÜBİTAK 117R050 nolu projenin sağladığı destekle tamamlanmıştır.

References

  • P. Long, G. Siemens, “Penetrating the fog: analytics in learning and education”, Italian Journal of Educational Technology, 22(3), 132-137, 2014.
  • M. Brown, M. McCormack, J. Reeves, D. C. Brook, S. Grajek, B. Alexander, K. Gannon, 2020 Educause Horizon Report Teaching and Learning Edition, 2-58, EDUCAUSE, 2020.
  • R. Ferguson, A. Brasher, D. Clow, A. Cooper, G. Hillaire, J. Mittelmeier, R. Vuorikari, Research evidence on the use of learning analytics: Implications for education policy, 2016.
  • A. Bozkurt, “Öğrenme analitiği: e-öğrenme, büyük veri ve bireyselleştirilmiş öğrenme”, Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 2(4), 55-81, 2016.
  • J. W. Ahn, P. Brusilovsky, “Adaptive visualization for exploratory information retrieval”, Information Processing & Management, 49(5), 1139-1164, 2013.
  • J. Gwizdka, I. Spence, “Implicit measures of lostness and success in web navigation”, Interacting with Computers, 19(3), 357-369, 2007.
  • R. Azevedo, “Understanding the complex nature of self-regulatory processes in learning with computer-based learning environments: An introduction”, Metacognition and Learning, 2(2-3), 57-65, 2007.
  • S. K. D’mello, S. D. Craig, A. Witherspoon, B. Mcdaniel, A. Graesser “Automatic detection of learner’s affect from conversational cues”, User modeling and user-adapted interaction, 18(1-2), 45-80, 2008.
  • L. Bol, J. K. Garner “Challenges in supporting self-regulation in distance education environments”, Journal of Computing in Higher Education, 23(2-3), 104-123, 2011.
  • D. Jeske, J. Backhaus, C. Stamov Roßnagel, “Self‐regulation during e‐learning: using behavioural evidence from navigation log files”, Journal of Computer Assisted Learning, 30(3), 272-284, 2014.
  • T. Güyer, A. Çebi, “Türkiye’deki uyarlanabilir eğitsel hiper ortam çalışmalarına yönelik içerik analizi”, Eğitim ve Bilim, 40(178), 2015.
  • S. Somyürek, H. İ. Yalın, “Adaptive learning systems: Supporting navigation with customized suggestions”, Journal of Human Sciences, 11(1), 55-77, 2014.
  • M. Fırat, “Eğitim teknolojileri araştırmalarında yeni bir alan: öğrenme analitikleri”, Mersin Üniversitesi Eğitim Fakültesi Dergisi, 11(3), 2015.
  • R. Baker, G. Siemens, Learning analytics and educational data mining, Cambridge Handbook of the Learning Sciences (2nd ed). Cambridge Univ. Press: New York, NY, 253-272, 2014.
  • K. R. Koedinger, R. S. Baker, K. Cunningham, A. Skogsholm, B. Leber, J. Stamper, “A data repository for the EDM community: The PSLC DataShop”, Handbook of educational data mining, 43, 43-56, 2010.
  • J. P. Campbell, P. B. DeBlois, D. G. Oblinger, “Academic analytics: A new tool for a new era”, EDUCAUSE review, 42(4), 40, 2007.
  • P. Lal, “Designing online learning strategies through analytics”, In Online Tutor 2.0: Methodologies and Case Studies for Successful Learning, 1-15, IGI Global, 2014.
  • M. Bienkowski, M. Feng, B. Means, “Enhancing teaching and learning through educational data mining and learning analytics: An issue brief”, US Department of Education, Office of Educational Technology, 1, 1-57, 2012.
  • A. L. Dyckhoff, D. Zielke, M. Bültmann, M. A. Chatti, U. Schroeder, “Design and implementation of a learning analytics toolkit for teachers”, Journal of Educational Technology & Society, 15(3), 58-76, 2012.
  • M. Scheffel, H. Drachsler, S. Stoyanov, M. Specht, “Quality Indicators for Learning Analytics”, Educational Technology & Society, 17 (4), 117–132, 2014.
  • J. A. Ruipérez-Valiente, P. J. Muñoz-Merino, D. Leony, C. Kloos, “ALAS-KA: A learning analytics extension for better understanding the learning process in the Khan Academy platform” Computers in Human Behavior, 47, 139-148, 2015.
  • A. L. Dyckhoff, V. Lukarov, A. Muslim, M. A. Chatti, U. Schroeder, “Supporting action research with learning analytics”, Third International Conference on Learning Analytics and Knowledge, 220-229, Nisan 2013.
  • T. Güyer, S. Somyürek, B. Atasoy, H. Yurdugül, M. Ünal, Ş. Aydoğdu, “Öğrenme Analitiği Göstergelerinin Sınıflandırılması”, 6th International Instructional Technologies & Teacher Education Symposium (ITTES 2018), Edirne, Türkiye, 12-14 Eylül 2018.
  • R. Bodily, K. Verbert, “Trends and issues in student-facing learning analytics reporting systems research”, Seventh international learning analytics & knowledge conference, 309-318, Mart, 2017.
  • D. Prasad, R. Totaram, T. Usagawa, “A framework for open textbooks analytics system”, TechTrends, 60(4), 344-349, 2016.
  • T. Richter, J. Naumann, S. Noller, “LOGPAT: A semi-automatic way to analyze hypertext navigation behavior”, Swiss Journal of Psychology/Schweizerische Zeitschrift für Psychologie/Revue Suisse de Psychologie, 62(2), 113, 2003.
  • K. Kitto, A. Bakharia, M. Lupton, D. Mallet, J. Banks, P, Bruza, ... G. Siemens, “The connected learning analytics toolkit”, Sixth International Conference on Learning Analytics & Knowledge, 548-549, Nisan 2016.
  • K. Verbert, E. Duval, J. Klerkx, S. Govaerts, J. L. Santos, “Learning analytics dashboard applications”, American Behavioral Scientist, 57(10), 1500-1509, 2013.
  • B. A. Schwendimann, M. J. Rodriguez-Triana, A. Vozniuk, L. P. Prieto, M. S. Boroujeni, A. Holzer, ... P. Dillenbourg, “Perceiving learning at a glance: A systematic literature review of learning dashboard research”, IEEE Transactions on Learning Technologies, 10(1), 30-41, 2016.
  • K. Börner, D. E. Polley, Visual insights: A practical guide to making sense of data, MIT Press, 2014.
  • B. M. Baker, A conceptual framework for making knowledge actionable through capital formation, Doktora Tezi, University of Maryland University College, 2007.
  • I. Jivet, M. Scheffel, M. Specht, H. Drachsler, “License to evaluate: Preparing learning analytics dashboards for educational practice”, 8th International Conference on Learning Analytics and Knowledge, 31-40, Mart, 2018.
  • Y. S. Tsai, V. Kovanović, D. Gašević, “Connecting the dots: An exploratory study on learning analytics adoption factors, experience, and priorities”, The Internet and Higher Education, 50, 100794, 2021.
  • D. Tzimas, S. Demetriadis, “Ethical issues in learning analytics: a review of the field”, Educational Technology Research and Development, 69, 1101-1133, 2021.
  • M. Wolpers, J. Najjar, K. Verbert, E. Duval, “Tracking actual usage: the attention metadata approach”, Educational Technology and Society, 10(3), 106-121, 2007.
  • R. Ferguson, “Learning analytics: drivers, developments and challenges”, International Journal of Technology Enhanced Learning, 4(5/6), 304-317, 2012.
  • Internet: Family Educational Rights and Privacy Act (FERPA), https://www2.ed.gov/policy/gen/guid/fpco/ferpa/index.html, 06.01.2020.
  • S. Slade, A. Tait, Global guidelines: Ethics in learning analytics, 2019.
  • Z. Papamitsiou, A. A. Economides, “Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence”, Journal of Educational Technology & Society, 17(4), 49-64, 2014.
  • J. Samuelsen, W. Chen, B. Wasson, “Integrating multiple data sources for learning analytics—review of literature”, Research and Practice in Technology Enhanced Learning, 14(1), 11, 2019.
  • A. Nguyen, T. Tuunanen, L. Gardner, D. Sheridan, “Design principles for learning analytics information systems in higher education”, European Journal of Information Systems, 1-28, 2020.
  • C. Schumacher, D. Ifenthaler, “Investigating prompts for supporting students' self-regulation–A remaining challenge for learning analytics approaches?”, The Internet and Higher Education, 49, 100791, 2021.
  • A. A. Mubarak, H. Cao, S. A. Ahmed, “Predictive learning analytics using deep learning model in MOOCs’ courses videos”, Education and Information Technologies, 26(1), 371-392, 2021.
  • M. A. Chatti, A. L. Dyckhoff, U. Schroeder, U H. Thüs, “A reference model for learning analytics”, International Journal of Technology Enhanced Learning, 4(5-6), 318-331, 2013.
  • S. Slade, P. Prinsloo, “Learning analytics: Ethical issues and dilemmas”, American Behavioral Scientist, 57(10), 1510-1529, 2013.
  • S. Dawson, S. Joksimovic, O. Poquet, G. Siemens, "Increasing the impact of learning analytics", 9th international conference on learning analytics & knowledge, 446-455, 2019.
  • S. D. Teasley, “Learning analytics: where information science and the learning sciences meet”, Information and Learning Sciences, 120(1/2), 59-73, 2019.
  • S. El Alfy, J. M. Gómez, A. Dani, “Exploring the benefits and challenges of learning analytics in higher education institutions: a systematic literature review”, Information Discovery and Delivery, 2019.
  • Y. Gülbahar, H. Ilgaz, “Premise of learning analytics for educational context: Through concept to practice”, Bilişim Teknolojileri Dergisi, 7(3), 20, 2014.
  • E. Tutsun, “Öğrenme analitikleri ve yükseköğretimdeki uygulama alanları”, Bilişim Teknolojileri Dergisi, 13(3), 243-254, 2020.

E-Learning Environments and Learning Analytics

Year 2021, , 327 - 336, 31.07.2021
https://doi.org/10.17671/gazibtd.709798

Abstract

As highlighted in the 2020 Horizon report, one of the concepts that have been handled to design effective learning environments is learning analytics. Although learning analytics has only a decade of history in the field of instructional technologies, it is thought to be at an early stage of development. Many interdisciplinary knowledge and skills such as educational sciences, statistics, mathematics, machine learning, and software engineering needed to use learning analytics. This study aims to reveal the potential of learning analytics in terms of e-learning environments and trying to ensure greater recognition by instructional designers and practitioners. In this context, the scope of learning analytics, its application areas and stages are explained. Additionally, indicators, data sources and some tools and systems are presented. The learning analytics process model and the learning panels that offer learning analytics are summarized. Finally the concepts of security, ethics, and standardization around learning analytics and the limitations in the relevant studies are discussed.

Project Number

117R050

References

  • P. Long, G. Siemens, “Penetrating the fog: analytics in learning and education”, Italian Journal of Educational Technology, 22(3), 132-137, 2014.
  • M. Brown, M. McCormack, J. Reeves, D. C. Brook, S. Grajek, B. Alexander, K. Gannon, 2020 Educause Horizon Report Teaching and Learning Edition, 2-58, EDUCAUSE, 2020.
  • R. Ferguson, A. Brasher, D. Clow, A. Cooper, G. Hillaire, J. Mittelmeier, R. Vuorikari, Research evidence on the use of learning analytics: Implications for education policy, 2016.
  • A. Bozkurt, “Öğrenme analitiği: e-öğrenme, büyük veri ve bireyselleştirilmiş öğrenme”, Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 2(4), 55-81, 2016.
  • J. W. Ahn, P. Brusilovsky, “Adaptive visualization for exploratory information retrieval”, Information Processing & Management, 49(5), 1139-1164, 2013.
  • J. Gwizdka, I. Spence, “Implicit measures of lostness and success in web navigation”, Interacting with Computers, 19(3), 357-369, 2007.
  • R. Azevedo, “Understanding the complex nature of self-regulatory processes in learning with computer-based learning environments: An introduction”, Metacognition and Learning, 2(2-3), 57-65, 2007.
  • S. K. D’mello, S. D. Craig, A. Witherspoon, B. Mcdaniel, A. Graesser “Automatic detection of learner’s affect from conversational cues”, User modeling and user-adapted interaction, 18(1-2), 45-80, 2008.
  • L. Bol, J. K. Garner “Challenges in supporting self-regulation in distance education environments”, Journal of Computing in Higher Education, 23(2-3), 104-123, 2011.
  • D. Jeske, J. Backhaus, C. Stamov Roßnagel, “Self‐regulation during e‐learning: using behavioural evidence from navigation log files”, Journal of Computer Assisted Learning, 30(3), 272-284, 2014.
  • T. Güyer, A. Çebi, “Türkiye’deki uyarlanabilir eğitsel hiper ortam çalışmalarına yönelik içerik analizi”, Eğitim ve Bilim, 40(178), 2015.
  • S. Somyürek, H. İ. Yalın, “Adaptive learning systems: Supporting navigation with customized suggestions”, Journal of Human Sciences, 11(1), 55-77, 2014.
  • M. Fırat, “Eğitim teknolojileri araştırmalarında yeni bir alan: öğrenme analitikleri”, Mersin Üniversitesi Eğitim Fakültesi Dergisi, 11(3), 2015.
  • R. Baker, G. Siemens, Learning analytics and educational data mining, Cambridge Handbook of the Learning Sciences (2nd ed). Cambridge Univ. Press: New York, NY, 253-272, 2014.
  • K. R. Koedinger, R. S. Baker, K. Cunningham, A. Skogsholm, B. Leber, J. Stamper, “A data repository for the EDM community: The PSLC DataShop”, Handbook of educational data mining, 43, 43-56, 2010.
  • J. P. Campbell, P. B. DeBlois, D. G. Oblinger, “Academic analytics: A new tool for a new era”, EDUCAUSE review, 42(4), 40, 2007.
  • P. Lal, “Designing online learning strategies through analytics”, In Online Tutor 2.0: Methodologies and Case Studies for Successful Learning, 1-15, IGI Global, 2014.
  • M. Bienkowski, M. Feng, B. Means, “Enhancing teaching and learning through educational data mining and learning analytics: An issue brief”, US Department of Education, Office of Educational Technology, 1, 1-57, 2012.
  • A. L. Dyckhoff, D. Zielke, M. Bültmann, M. A. Chatti, U. Schroeder, “Design and implementation of a learning analytics toolkit for teachers”, Journal of Educational Technology & Society, 15(3), 58-76, 2012.
  • M. Scheffel, H. Drachsler, S. Stoyanov, M. Specht, “Quality Indicators for Learning Analytics”, Educational Technology & Society, 17 (4), 117–132, 2014.
  • J. A. Ruipérez-Valiente, P. J. Muñoz-Merino, D. Leony, C. Kloos, “ALAS-KA: A learning analytics extension for better understanding the learning process in the Khan Academy platform” Computers in Human Behavior, 47, 139-148, 2015.
  • A. L. Dyckhoff, V. Lukarov, A. Muslim, M. A. Chatti, U. Schroeder, “Supporting action research with learning analytics”, Third International Conference on Learning Analytics and Knowledge, 220-229, Nisan 2013.
  • T. Güyer, S. Somyürek, B. Atasoy, H. Yurdugül, M. Ünal, Ş. Aydoğdu, “Öğrenme Analitiği Göstergelerinin Sınıflandırılması”, 6th International Instructional Technologies & Teacher Education Symposium (ITTES 2018), Edirne, Türkiye, 12-14 Eylül 2018.
  • R. Bodily, K. Verbert, “Trends and issues in student-facing learning analytics reporting systems research”, Seventh international learning analytics & knowledge conference, 309-318, Mart, 2017.
  • D. Prasad, R. Totaram, T. Usagawa, “A framework for open textbooks analytics system”, TechTrends, 60(4), 344-349, 2016.
  • T. Richter, J. Naumann, S. Noller, “LOGPAT: A semi-automatic way to analyze hypertext navigation behavior”, Swiss Journal of Psychology/Schweizerische Zeitschrift für Psychologie/Revue Suisse de Psychologie, 62(2), 113, 2003.
  • K. Kitto, A. Bakharia, M. Lupton, D. Mallet, J. Banks, P, Bruza, ... G. Siemens, “The connected learning analytics toolkit”, Sixth International Conference on Learning Analytics & Knowledge, 548-549, Nisan 2016.
  • K. Verbert, E. Duval, J. Klerkx, S. Govaerts, J. L. Santos, “Learning analytics dashboard applications”, American Behavioral Scientist, 57(10), 1500-1509, 2013.
  • B. A. Schwendimann, M. J. Rodriguez-Triana, A. Vozniuk, L. P. Prieto, M. S. Boroujeni, A. Holzer, ... P. Dillenbourg, “Perceiving learning at a glance: A systematic literature review of learning dashboard research”, IEEE Transactions on Learning Technologies, 10(1), 30-41, 2016.
  • K. Börner, D. E. Polley, Visual insights: A practical guide to making sense of data, MIT Press, 2014.
  • B. M. Baker, A conceptual framework for making knowledge actionable through capital formation, Doktora Tezi, University of Maryland University College, 2007.
  • I. Jivet, M. Scheffel, M. Specht, H. Drachsler, “License to evaluate: Preparing learning analytics dashboards for educational practice”, 8th International Conference on Learning Analytics and Knowledge, 31-40, Mart, 2018.
  • Y. S. Tsai, V. Kovanović, D. Gašević, “Connecting the dots: An exploratory study on learning analytics adoption factors, experience, and priorities”, The Internet and Higher Education, 50, 100794, 2021.
  • D. Tzimas, S. Demetriadis, “Ethical issues in learning analytics: a review of the field”, Educational Technology Research and Development, 69, 1101-1133, 2021.
  • M. Wolpers, J. Najjar, K. Verbert, E. Duval, “Tracking actual usage: the attention metadata approach”, Educational Technology and Society, 10(3), 106-121, 2007.
  • R. Ferguson, “Learning analytics: drivers, developments and challenges”, International Journal of Technology Enhanced Learning, 4(5/6), 304-317, 2012.
  • Internet: Family Educational Rights and Privacy Act (FERPA), https://www2.ed.gov/policy/gen/guid/fpco/ferpa/index.html, 06.01.2020.
  • S. Slade, A. Tait, Global guidelines: Ethics in learning analytics, 2019.
  • Z. Papamitsiou, A. A. Economides, “Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence”, Journal of Educational Technology & Society, 17(4), 49-64, 2014.
  • J. Samuelsen, W. Chen, B. Wasson, “Integrating multiple data sources for learning analytics—review of literature”, Research and Practice in Technology Enhanced Learning, 14(1), 11, 2019.
  • A. Nguyen, T. Tuunanen, L. Gardner, D. Sheridan, “Design principles for learning analytics information systems in higher education”, European Journal of Information Systems, 1-28, 2020.
  • C. Schumacher, D. Ifenthaler, “Investigating prompts for supporting students' self-regulation–A remaining challenge for learning analytics approaches?”, The Internet and Higher Education, 49, 100791, 2021.
  • A. A. Mubarak, H. Cao, S. A. Ahmed, “Predictive learning analytics using deep learning model in MOOCs’ courses videos”, Education and Information Technologies, 26(1), 371-392, 2021.
  • M. A. Chatti, A. L. Dyckhoff, U. Schroeder, U H. Thüs, “A reference model for learning analytics”, International Journal of Technology Enhanced Learning, 4(5-6), 318-331, 2013.
  • S. Slade, P. Prinsloo, “Learning analytics: Ethical issues and dilemmas”, American Behavioral Scientist, 57(10), 1510-1529, 2013.
  • S. Dawson, S. Joksimovic, O. Poquet, G. Siemens, "Increasing the impact of learning analytics", 9th international conference on learning analytics & knowledge, 446-455, 2019.
  • S. D. Teasley, “Learning analytics: where information science and the learning sciences meet”, Information and Learning Sciences, 120(1/2), 59-73, 2019.
  • S. El Alfy, J. M. Gómez, A. Dani, “Exploring the benefits and challenges of learning analytics in higher education institutions: a systematic literature review”, Information Discovery and Delivery, 2019.
  • Y. Gülbahar, H. Ilgaz, “Premise of learning analytics for educational context: Through concept to practice”, Bilişim Teknolojileri Dergisi, 7(3), 20, 2014.
  • E. Tutsun, “Öğrenme analitikleri ve yükseköğretimdeki uygulama alanları”, Bilişim Teknolojileri Dergisi, 13(3), 243-254, 2020.
There are 50 citations in total.

Details

Primary Language Turkish
Subjects Computer Software
Journal Section Articles
Authors

Sibel Somyürek

Tolga Güyer

Bilal Atasoy This is me

Mertcan Ünal

Project Number 117R050
Publication Date July 31, 2021
Submission Date March 26, 2020
Published in Issue Year 2021

Cite

APA Somyürek, S., Güyer, T., Atasoy, B., Ünal, M. (2021). E-Öğrenme Ortamları ve Öğrenme Analitikleri. Bilişim Teknolojileri Dergisi, 14(3), 327-336. https://doi.org/10.17671/gazibtd.709798