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Facilitating research through serendipity of recommendations

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Abstract

Recommender systems are used to suggest items that are useful to users. The recommendations can be surprising and may be categorized as serendipitous recommendations. One of the limitations with serendipitous recommendations is that the user interface of such a recommender system rarely supports the user to switch from accuracy orientation to serendipity facilitations. Using serendipitous recommendations can be challenging. This is because the user might not fully benefit from and understand the serendipitous recommendations. One main advantage of this type of system is that a serendipity-oriented recommender system can be used for the supervision of research students. It can help them to find a novel topic in the area of their research interests. This paper reports on a novel user interface design for facilitating serendipitous recommendations generation in educational environments. The user interface of this recommender system provides students with user controls and visualization in order to explore research articles. This research comprises user experience experiments conducted in an academic environment and evaluated by means of a user centered design evaluation. It involves research articles recommender system named JabRef. The recommender systems were used by students at the undergraduate level. Users reported an enhanced user experience while using the user controls and visualization and serendipitous resource discovery. It was found that user interface design can facilitate a serendipity recommender system in the learning environment. University professors supervising students during the research can also benefit from the recommender system.

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Authors and Affiliations

  1. Centre for Excellence in Information Technology, Institute of Management Sciences, Peshawar, Pakistan

    Ahmad Hassan Afridi

  2. Transportation Research Institute, IMOB, Hasselt University, Hasselt, Belgium

    Ansar Yasar

  3. Acadia University, Wolfville, Canada

    Elhadi M. Shakshuki

Authors
  1. Ahmad Hassan Afridi
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  2. Ansar Yasar
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  3. Elhadi M. Shakshuki
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Correspondence to Ahmad Hassan Afridi.

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Appendix

Appendix

Comments from various students (users)

Appreciated work, good design

Quite productive and good quality work

1. It is highly recommended to install this recommender in universities, this will allow students to select a variety of topics for research with ease

2. The recommender should recommend the latest topics for research in which work is already in process

The recommender takes more time to load comparatively. It only shows the research paper while in BS, only research papers should not be recommended. Along with such papers previous projects and related course in order to build that project should be shown

1. Must tell me about the no of individuals who are working/selecting same research topic e.g. which area/field is very popular

2. Suggestions after selecting research topic e.g. scope of it

3. should also show visualization through paragraph about paper popularity or area/field scope for coming areas

1. Show more graph for the better understanding and for showing more details of particular selected topic

2. Create section for comparing topic related to selected topic

3. Create separate section for different other related topics

4. Provide specific and looking good interface for the author name

5. It is very helpful recommender system

1. Helpful

2. System is slow

A very powerful and helpful software if used correctly

It is a very useful and helpful product which can help every student for their educational work. I only have one problem with the product and that is the interface. It should be more visible and easy to understand

System’s functionality of recommending some different papers is not necessary i guess

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Afridi, A.H., Yasar, A. & Shakshuki, E.M. Facilitating research through serendipity of recommendations. J Ambient Intell Human Comput 11, 2263–2275 (2020). https://doi.org/10.1007/s12652-019-01354-7

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