LOTE: Analytics Engine
Visit LOTE: Analytics Engine(opens in a new tab)2022-2023
Stack: C#, Unity, Snowflake
Life on The Edge (LOTE) is an award winning educational game for biology first year undergrads. The player controls a cell and its organelles to survive microbial attacks.
I built an analytics engine for the game. I designed it to capture key game moments (see 2nd screenshot) as analytics events fired from the game to Unity Gaming Services (UGS)'s cloud in Snowflake.
From this data, researchers were able to analyze player behaviour and gauge their learning.
Life on the Edge is a tower-defense game for the first-year biology undergraduate student to learn about the immune system.
I was a graduate student in the department of Education at Concordia University, and my professor Dr. Ji Yae Bong was running a study exploring the efficacy of game-based learning.
At the time, I was researching educational games (my main research area for my Master's until I pivoted to digital research) and so for this project I designed and developed an analytics engine to capture play-through stats over time to reproduce player behaviour and gauge player learning.
The way a player played the game, we hypothesized, was reflective of how well they understood the topic. I defined events that would be fired at various stages during the play-through and their corresponding data elements. This included data points such as win state at the end of a stage, duration, if they sought help from the encyclopedia, and the configuration of the cell.
The game was built with Unity and developed the engine with C#. This data was fired from the client to the Unity Gaming Services cloud which was then ingested into their data warehouse and accessible via Snowflake.
This enabled us to capture and reproduce the essential elements of how a player played each play-through and then corroborate their knowledge with an assessment for a SSHRC study that ran at MacEwan University, Edmonton, Alberta.