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• Ethical Considerations in the Practical Application of the Unisa Socio-Critical Model of Student Success

  Fynn, A. (2016). Ethical Considerations in the Practical Application of the Unisa Socio-Critical Model of Student Success. The International Review of Research in Open and Distributed Learning, 17(6),. Athabasca University Press.

• Are Computer Adaptive Tests suitable for assessment in MOOCs

  Rossano, V., Pesare, E. & Roselli, T. (2017). Are Computer Adaptive Tests suitable for assessment in MOOCs. Journal of e-Learning and Knowledge Society, 13(3),. Italian e-Learning Association.

• Innovating Pedagogy 2017

  Ferguson, R., Barzilai, S., Ben-Zvi, D., Chinn, C.A., Herodotou, C., Hod, Y., Kali, Y., Kukulska-Hulme, A., Kupermintz, H., McAndrews, P., Rienties, B., Sagy, O., Scanlon, E., Sharples, M., Weller, M. & Whitelock, D. (2017). Innovating Pedagogy 2017. The Open University.

• NMC Horizon Report: 2017 Library Edition

  Adams Becker, S., Cummins, M., Davis, A., Freeman, A., Hall Giesinger, C., Ananthanarayanan, V., Langley, K. & Wolfson, N. (2017). NMC Horizon Report: 2017 Library Edition. Austin, Texas: The New Media Consortium.

• NMC Horizon Report: 2016 Museum Edition

  Freeman, A., Adams Becker, S., Cummins, M., McKelroy, E., Giesinger, C. & Yuhnke, B. (2016). NMC Horizon Report: 2016 Museum Edition. Austin, Texas: The New Media Consortium.

• South Africa’s Quest for Smart Cities: Privacy Concerns of Digital Natives of Cape Town, South Africa

  Tanner, M. & Tshiani, V. (2018). South Africa’s Quest for Smart Cities: Privacy Concerns of Digital Natives of Cape Town, South Africa. Interdisciplinary Journal of E-Learning and Learning Objects, 14(1), 55-76. Informing Science Institute.

• Construction of a Prediction Model of the Shortest Annual Graduation by Machine Learning Using Learning Environment Data

  Hirose, H., Ozaki, T., Kawate, K., Yamamoto, Y. & Ichikawa, H. (2018). Construction of a Prediction Model of the Shortest Annual Graduation by Machine Learning Using Learning Environment Data. In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 510-515). Las Vegas, NV, United States: Association for the Advancement of Computing in Education (AACE).

• Learning Analytics of Postgraduate Sociology Students of Indira Gandhi National Open University

  Khare, P. Learning Analytics of Postgraduate Sociology Students of Indira Gandhi National Open University. Asian Journal of Distance Education, 12(1), 4-16.

• Adaptive Learning: A Stabilizing Influence across Disciplines and Universities

  Dziuban, C., Moskal, P., Parker, L., Campbell, M., Howlin, C. & Johnson, C. (2018). Adaptive Learning: A Stabilizing Influence across Disciplines and Universities. Online Learning, 22(3), 7-39.

• Cognitive Analysis of Meaning and Acquired Mental Representations as an Alternative Measurement Method Technique to Innovate E-Assessment

  Morales-Martinez, G.E., Lopez-Ramirez, E.O., Castro-Campos, C., Villarreal-Treviño, M.G. & Gonzales-Trujillo, C.J. (2017). Cognitive Analysis of Meaning and Acquired Mental Representations as an Alternative Measurement Method Technique to Innovate E-Assessment. European Journal of Educational Research, 6(4), 455-464.

• Implementation of Flipped Education into Turkish EFL Teaching Context

  Boyraz, S. & Ocak, G. (2017). Implementation of Flipped Education into Turkish EFL Teaching Context. Journal of Language and Linguistic Studies, 3(2), 426-439.

• The Flipped MOOC: Using Gamification and Learning Analytics in MOOC Design--A Conceptual Approach

  Klemke, R., Eradze, M. & Antonaci, A. (2018). The Flipped MOOC: Using Gamification and Learning Analytics in MOOC Design--A Conceptual Approach. Education Sciences, 8(1),.

• Assessment of Learning in Digital Interactive Social Networks: A Learning Analytics Approach

  Wilson, M., Gochyyev, P. & Scalise, K. (2016). Assessment of Learning in Digital Interactive Social Networks: A Learning Analytics Approach. Journal of Asynchronous Learning Networks, 20(2), 97-119.

• Planning for Online Education: A Systems Model

  Picciano, A.G. (2015). Planning for Online Education: A Systems Model. Journal of Asynchronous Learning Networks, 19(5), 142-158.

• The Ethics of Using Learning Analytics to Categorize Students on Risk

  Scholes, V. (2016). The Ethics of Using Learning Analytics to Categorize Students on Risk. Educational Technology Research and Development, 64(5), 939-955.

• Students’ Perceptions of Benefits and Drawbacks of Facebook-Connections with Teachers

  Hershkovitz, A. & Baruch, A. (2019). Students’ Perceptions of Benefits and Drawbacks of Facebook-Connections with Teachers. Interdisciplinary Journal of E-Learning and Learning Objects, 15(1), 1-20. Informing Science Institute.

• Integrating Character Education on Physics Courses with Schoology Based E-learning

  Hilyana, F. & Hakim, M. (2018). Integrating Character Education on Physics Courses with Schoology Based E-learning. Journal of Information Technology Education: Research, 17(1), 577-593. Informing Science Institute.

• Open Praxis vol. 11 issue 1

  Gil-Jaurena, v. (2019). Open Praxis vol. 11 issue 1. Open Praxis, 11(1), 1-116. International Council for Open and Distance Education.

• Global Guidelines: Ethics in Learning Analytics

  Slade, S., Tait, A.,. (2019). Global Guidelines: Ethics in Learning Analytics.

• An Instructional Design Model for Blended Higher Education

  Hack, G. (2016). An Instructional Design Model for Blended Higher Education. Journal of Learning and Teaching in Digital Age, 1(2), 2-9. Mehmet Akif Ocak, PhD.