
 
to users’ point of view regarding the exploitation of 
the knowledge produced. HMI methods are mainly 
used to ensure that systems are useful, usable and 
acceptable. The information architecture is used to 
ensure that knowledge presented in KMS follows 
structures that make the most sense for users and 
their organizational context.  
We implemented our approach in SCP and as a 
result we obtained a prototype, ALEX +. ALEX + 
was evaluated by a panel of users. It shows that 
collaborators are generally satisfied with the 
proposals that were made in the final system and 
will tend more to use it. We can however identify a 
couple of limitations in our approach. Firstly, the 
limited number of participants in the workgroup 
allows us to only have the viewpoints of a small part 
of the actual user population; an assessment of a 
larger amount of people in SCP and also in other 
companies would help us have a better insight of the 
impact of our methodology on the KMS use in the 
company. Secondly, an ideal experimental approach 
would be to do a comparative evaluation of our 
methodology with others proposed by literature in 
the domain of design of corporate KMS. These 
points are planned for future work.   
More generally, with our approach, we can just have 
an overview of the users’ intentions but not of the 
effective use. Our method is not robust enough to 
ensure effective use; it focuses on initial acceptance 
of the system but not on his continuous use. A KMS 
is really useful if users effectively consult or add 
new content, discuss or comment updates, which 
happens when they master the system. This form of 
capitalization, which we call sustainable, requires 
implementation of other features in the system. This 
stage corresponds to the sensory design stage which 
we did not particularly emphasize in our approach. 
We believe that metacognitive assistance features 
like indicators of awareness may be useful (Marty & 
Carron, 2011). Indeed, by proposing activity 
indicators, we can promote a reflexive dynamic of 
learning by user self-regulation processes (George, 
Michel, & Ollagnier-Beldame, 2013). For example, 
users by visualizing the impact of their contribution 
on other actors in the company may be more 
motivated to use the system. Conversely, by 
identifying the comments that were made on 
experience sheets related to their professional field, 
they may become aware of new procedures or 
changes in business practices and thus increase the 
credit given to the developed tool. As such, 
comments could be seen as a recommendation to 
consult. We plan to implement these new features by 
analysing traces of activity (Karray, Chebel-Morello, 
& Zerhouni, 2014). These traces provide much more 
diagnostic of use by sector and functionality. Our 
future work will therefore seek to identify, still with 
an incremental approach, which indicators and 
interaction modalities may be most suitable. Phases 
4 and 5 of our method are mainly concerned; the 
design that affects the sensory and user experiences. 
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