LAK’16 Conference Paper Preparation

So, Back again!

Time is so tight! Deadline is on 31 October 2015. Have only 8 days left.

  • Update: Already submitted. Hopefully, it will be accepted.
  • Update2: Paper was rejected in spite of some nice reviews. No problem, scientific life is like this.. Here are the reviews:

Review 1:

  • This paper is relevant to the community and nicely summarises some of the key methodological trends.

Review 2:

  • The paper present a survey of the different methods used in the learning analytics community from 2013 to 2015.

    The main goals of the study are to help learning analytics researchers to indentify common methods, to determines methods that are highly cited and to assists to understand the on-going current vision.

    The authors describe how the relevant papers were chosen. The main methods categories are presented and in each category the most used techniques and the corresponding goals are described : Data mining techniques, statistics and mathematics, text mining & semantics & linguistic analysis, Visualization, social networks, qualitative analysis and gamification.

    Google scholar was used to check methods’ popularity and then to define the prominent methods and discuss the results.

    the paper is well-written and easy to understand. The paper aims are not fully achieved because it is an on-going study.

Review 3:

  • This paper surveys publications from LAK conference from 2013 to 2015. Learning analytics methods are classified and Google scholar citations analysed. It is a very interesting and useful subject to guide researchers in the field for their future work directions. The paper is well structured in general, except that the reader expects to have a typical conclusion separated section.
    The survey is very interesting; it could be good to present it next year as a full paper with more detailed analysis of each method application and including LA methods published out of LAK.

    In Sec. 4, the number of publications per method should be given in average per article, because methods do not have the same number of articles.

 

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