By Rudra Kumar, Deakin University

As of now, the video games industry has risen to be a giant in the entertainment sector overtaking the movie industry. This sudden growth has made many realise the potential impact that interactive experiences can have on human emotions and thinking. Ushering in the need to understand how specific designs affect player response/strategies they use to overcome game obstacles. This has further opened up another area of study concerning player behaviour and incentivising them to get the intended response [1].

This trend is being quickly adopted by entertainment giants like Ubisoft to further tweak their existing designs according to the feedback they infer from the collected data. Ubisoft recently conducted data collection via gameplay and feedback forms; which they fed into a machine learning algorithm, which taught itself to predict player motivations according to a physiological model with 97 per cent accuracy [2].

Game Analytics has proved to be paramount in the field of serious games, more and more studies and experiments are being performed in the education, support and other sectors. This knowledge can be potentially translated to the rising field of Augmented Reality (AR). As AR is also proving to have a big impact on visitor interaction at historical locations and other places of interest, as demonstrated by Pokémon Go [4], the practice of analytics provides an excellent opportunity to discover more about human behaviour from a unique perspective.

All the while, AR technology has been advancing at an astonishing rate leading to widespread adoption and consequently piquing interest from the world of academia and commerce alike. As AR enhanced experiences is a relatively new body of research we have tried to evaluate an escape room experience enhanced by augmented reality, to determine play strategies, presenting a window into player engagement and design perceptions. This also  kindled the motivation to establish a pipeline to facilitate the collection, filtration and analysis of gameplay data reliably and efficiently, to allow further advancements in understanding play strategies and human behaviour.


  1. Medler, B. and Magerko, B., 2011. Analytics of play: Using information visualization and gameplay practices for visualizing video game data. Parsons Journal for Information Mapping, 3(1), pp. 1-12.
  2. Alessandro Canossa, Feb 14, 2019, How Data Science and Machine Learning can help create better games, Massive Entertainment, retrieved on 18th Feb 2019, Link
  3. Loh, C.S., Sheng, Y. and Ifenthaler, D., 2015. Serious Games Analytics. Edited by Christian Sebastian Loh, Yanyan Sheng, and Dirk Ifenthaler. Cham: Springer International Publishing. doi, 10, pp. 978-3

Oleksy, T. and A. Wnuk (2017). “Catch them all and increase your place attachment! The role of location-based augmented reality games in changing people – place relations.” Computers in Human Behavior 76: 3-8. Link.


Rudra Kumar was a recipient of a 2018/19 AMSI Vacation Research Scholarship.

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