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• Understand learning style by eye tracking in slide video learning

  Cao, J. & Nishihara, A. (2012). Understand learning style by eye tracking in slide video learning. Journal of Educational Multimedia and Hypermedia, 21(4), 335-358. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE).

• Improving the Workspace Awareness of Authors in Asynchronous Collaborative Authoring of Learning Designs

  Nurjanah, D. & Davis, H.C. (2012). Improving the Workspace Awareness of Authors in Asynchronous Collaborative Authoring of Learning Designs. In T. Amiel & B. Wilson (Eds.), Proceedings of EdMedia 2012--World Conference on Educational Media and Technology (pp. 1366-1376). Denver, Colorado, USA: Association for the Advancement of Computing in Education (AACE).

• Searching for and positioning of contextualized learning objects

  Baldiris Navarro, S., Graf, S., Fabregat, R. & Duque Méndez, N. (2012). Searching for and positioning of contextualized learning objects. The International Review of Research in Open and Distributed Learning, 13(5), 76-101. Athabasca University Press.

• The Expertise Reversal Effect: Cognitive Load and Motivational Explanations

  Rey, G.D. & Buchwald, F. (2011). The Expertise Reversal Effect: Cognitive Load and Motivational Explanations. Journal of Experimental Psychology: Applied, 17(1), 33-48.

• The Impact of E-Learning on Medical Education in Russia

  Trukhacheva, N., Tchernysheva, S. & Krjaklina, T. (2011). The Impact of E-Learning on Medical Education in Russia. E-Learning and Digital Media, 8(1), 31-35.

• Learners' Perceptions and Illusions of Adaptivity in Computer-Based Learning Environments

  Vandewaetere, M., Vandercruysse, S. & Clarebout, G. (2012). Learners' Perceptions and Illusions of Adaptivity in Computer-Based Learning Environments. Educational Technology Research and Development, 60(2), 307-324.

• A New Approach to Personalization: Integrating E-Learning and M-Learning

  Nedungadi, P. & Raman, R. (2012). A New Approach to Personalization: Integrating E-Learning and M-Learning. Educational Technology Research and Development, 60(4), 659-678.

• Towards an Ontological Learnersâ?? Modelling Approach for Personalised e-Learning

  Hosseini, S., Tawil, A.R., Jahankhani, H. & Yarandi, M. (2013). Towards an Ontological Learnersâ?? Modelling Approach for Personalised e-Learning. International Journal of Emerging Technologies in Learning (iJET), 8(2), 4-10. Kassel, Germany: International Journal of Emerging Technology in Learning.

• The Expertise Reversal Effect Concerning Instructional Explanations

  Rey, G.D. & Fischer, A. (2013). The Expertise Reversal Effect Concerning Instructional Explanations. Instructional Science: An International Journal of the Learning Sciences, 41(2), 407-429.

• Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles

  Yang, T.C., Hwang, G.J. & Yang, S.J.H. (2013). Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles. Journal of Educational Technology & Society, 16(4), 185-200.

• Adaptation criteria for the personalised delivery of learning materials: A multi-stage empirical investigation

  Thalmann, S. (2014). Adaptation criteria for the personalised delivery of learning materials: A multi-stage empirical investigation. Australasian Journal of Educational Technology, 30(1),. Australasian Society for Computers in Learning in Tertiary Education.

• Evaluation of an adaptive online learning system

  Griff, E.R. & Matter, S.F. (2013). Evaluation of an adaptive online learning system. British Journal of Educational Technology, 44(1), 170-176. Wiley.

• Learning and Academic Analytics in the Realizeit System

  Howlin, C. & Lynch, D. (2014). Learning and Academic Analytics in the Realizeit System. In T. Bastiaens (Ed.), Proceedings of World Conference on E-Learning (pp. 862-872). New Orleans, LA, USA: Association for the Advancement of Computing in Education (AACE).

• Distributed Learning 3.0: Past to Future

  Yacci, M. (2015). Distributed Learning 3.0: Past to Future. In Proceedings of Global Learn Berlin 2015: Global Conference on Learning and Technology (pp. 681-686). Berlin, Germany: Association for the Advancement of Computing in Education (AACE).

• Adaptemy – Building the Next Generation Classroom

  Ghergulescu, I., Flynn, C. & O'Sullivan, C. (2015). Adaptemy – Building the Next Generation Classroom. In S. Carliner, C. Fulford & N. Ostashewski (Eds.), Proceedings of EdMedia 2015--World Conference on Educational Media and Technology (pp. 86-95). Montreal, Quebec, Canada: Association for the Advancement of Computing in Education (AACE).

• Innovating Randomized Effectiveness Trials: The Case of an Adaptive Learning Engine for E-Learning in High Schools

  Homer, B. & Plass, J. (2015). Innovating Randomized Effectiveness Trials: The Case of an Adaptive Learning Engine for E-Learning in High Schools. In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1105-1114). Kona, Hawaii, United States: Association for the Advancement of Computing in Education (AACE).

• Online Homework Put to the Test: A Report on the Impact of Two Online Learning Systems on Student Performance in General Chemistry

  Eichler, J.F. & Peeples, J. (2013). Online Homework Put to the Test: A Report on the Impact of Two Online Learning Systems on Student Performance in General Chemistry. Journal of Chemical Education, 90(9), 1137-1143.

• Adaptation Criteria for the Personalised Delivery of Learning Materials: A Multi-Stage Empirical Investigation

  Thalmann, S. (2014). Adaptation Criteria for the Personalised Delivery of Learning Materials: A Multi-Stage Empirical Investigation. Australasian Journal of Educational Technology, 30(1), 45-60.

• CC-LR: Providing Interactive, Challenging and Attractive Collaborative Complex Learning Resources

  Caballé, S., Mora, N., Feidakis, M., Gañán, D., Conesa, J., Daradoumis, T. & Prieto, J. (2014). CC-LR: Providing Interactive, Challenging and Attractive Collaborative Complex Learning Resources. Journal of Computer Assisted Learning, 30(1), 51-67.

• Adaptive E-Learning Environments: Research Dimensions and Technological Approaches

  Di Bitonto, P., Roselli, T., Rossano, V. & Sinatra, M. (2013). Adaptive E-Learning Environments: Research Dimensions and Technological Approaches. International Journal of Distance Education Technologies, 11(3), 1-11. IGI Global.