In this paper, the authors aim to provide a systematic survey of recommender systems in e-learning environments. They cite more than 150 papers published between the years 2001 and 2015.

After a short overview, the paper presents (1) a discussion of requirements and challenges in designing recommender systems for e-learning environments; (2) matrix and tensor factorization-, collaborative filtering-, content-, and association rule mining-based recommendation techniques for e-learning environments; (3) collaborative tagging systems and folksonomies; and (4) the application of tag-based systems to e-learning including some possible extensions. The conclusion section of the paper also provides some future research pointers. The authors aim for comprehensive coverage of the related topics; however, a discussion of testing and evaluation of such systems is missing.

The paper contains long paragraphs. Some of them clearly contain more than one topic. Furthermore, the paper contains several sentences with grammatical errors. On the other hand, it does not contain sufficient intuitive figures and tables that one would like to see in such a survey paper. It is possible to find sentences that refer to a section as a chapter; I speculate that this comes from the fact that some text comes from the PhD thesis of one of the coauthors, which is cited in the references.

Overall, the paper can be useful due to its coverage. However, to me, it is a “good” example of poor presentation and poor editorial work.