MOOCOLAB - A Customized Collaboration Framework in Massive Open Online Courses

  • Ana Carla A. HolandaEmail author
  • Patrícia Azevedo TedescoEmail author
  • Elaine Harada T. OliveiraEmail author
  • Tancicleide C. S. GomesEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12149)


[Context] The use of MOOCs has generated an increasing amount of data that, if properly explored, can provide an understanding of how students interact throughout their learning, in addition to identifying strategies that can be used in the process of building environments. that enhance the construction of knowledge in a shared way. [Objective] The objective of this article is to propose a Conceptual Collaborative Framework (MOOColab), based on Learning Analytics mechanisms and Recommendation Systems to improve collaborative learning in the environment. [Methodology] For the development of the Framework, the Design Science Research model was used for the analysis, development and evaluation of MOOColab. [Results] An experiment was carried out with two samples: a control group (which did not use the Framework) and an experimental group (which went through the same course using MOOColab). [Conclusion] From the results obtained in the research, it is evident that the implementation of Framework identifying the individualities of each student with the discovery of behavioral patterns and their respective skills to adapt the environment with the recommendation of peers, in order to improve the mutual exchange of information between students involved in the learning process.


MOOC Collaboration Recommendation Systems Learning Analytics 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Federal University of PernambucoRecifeBrazil
  2. 2.Federal Institute of AcreRio BrancoBrazil
  3. 3.Federal University of AmazonasManausBrazil

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