## 7 Conclusions and Outlook  
In this paper, we introduced a smart object gamification platform for museums. The system exploits a combination of semantic web and Internet of Things technologies in order to craft appealing and memorable museum experiences. We have detailed the process by which questions are automatically generated based on a set of templates. Then, we described the interaction of visitors with the museum environment by means of QR codes and a smartphone application that provides advanced visualization and information about the exhibits of interest. The app also offers visitors the opportunity to play the questions that have been generated, thus gamifying their experience. Finally, the prototype of the designed platform was implemented and evaluated in _[PERSON]_ Telecommunications Museum.  
The experimentation performed shows that the platform is easy to use as well as interactive. Both factors contribute to higher levels of cognitive engagement. Visitors' increased cognitive engagement when using the platform enhance learning outcomes and their satisfaction with the visit. This, in turn, contributes towards a higher likelihood for visitors to return to the telecommunications museum. These results encourage the use of the gamification platform in the telecommunications museum. It therefore appears to be a promising work that could be extrapolated and adapted to other kinds of museums or cultural heritage institutions.  
As future work, several lines could be explored. For instance, instead of only providing textual information on the scanned object, the platform could also offer an audio-based description of the exhibit's documentation. Another line of work is to train a machine learning model to classify keywords contained in objects' descriptions. This will allow to extract more relevant concepts from exhibits' descriptions. The approach could help overcome problems that arise from data availability issues in Linked Data knowledge graphs, which affect the quantity and quality of the produced questions.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Hypothesis** & **Path** & **Path Coefficient** & **T-Statistics** & **Decision** \\ \hline H1 & Ease of Use \(\rightarrow\) Interactivity & 0.199 & 0.984 & Not Supported \\ H2 & Ease of Use \(\rightarrow\) Cognitive Engagement & 0.361 & 2.220 & Supported \\ H3 & Interactivity \(\rightarrow\) Cognitive Engagement & 0.391 & 2.465 & Supported \\ H4 & Interactivity \(\rightarrow\) User Satisfaction & 0.129 & 0.882 & Not Supported \\ H5 & Cognitive Engagement \(\rightarrow\) Learning Outcomes & 0.485 & 4.185 & Supported \\ H6 & Cognitive Engagement \(\rightarrow\) User Satisfaction & 0.570 & 4.505 & Supported \\ H7 & User Satisfaction \(\rightarrow\) Revisit Intention & 0.495 & 4.048 & Supported \\ \hline \hline \end{tabular}
\end{table}
Table 6: Hypothesis validation.  
**Author Contributions:** Conceptualisation, C.A.I. and A.L.-M.; methodology, C.A.I. and A.L.-M.; software, A.L.-M.; supervision, C.A.I and A.C.; validation, A.L.-M.; writing-original draft preparation, A.L.-M.; writing-review and editing, A.C. and C.A.I. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Acknowledgments:** The authors express their gratitude to the Library of _Escuela Tecnica Superior de Ingenieros de Telecomunicacion, Universidad Politecnica de Madrid_ for approving the development of the designed system prototype in _[PERSON]_ Telecommunications Museum and for printing hard cardboards containing QR codes.  
**Conflicts of Interest:** The authors declare no conflict of interest.