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Learning analytics for location based serious games

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EDUCON 2018, April 17-20, Santa Cruz de Tenerife, Spain

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Learning analytics for location based serious games

  1. 1. LEARNING ANALYTICS FOR LOCATION-BAS ED SERIOUS GAMES Victor M. Perez-Colado, Dan Cristian Rotaru, Manuel Freire, Ivan Martinez-Ortiz, Baltasar Fernandez-Manjon
  2. 2. INDEX 1. PROBLEM AND OBJECTIVES 2. PERVASIVE GAMES 3. xAPI 4. LOCATION-BASED xAPI 5. ANALYSIS 6. VISUALIZATIONS 7. ASSESSMENT 8. CONCLUSIONS & FUTURE WORK
  3. 3. PROBLEM ● Growth in Pervasive Gaming ● Serious Games can benefit from location-based mechanics ● No location-based Standard to Track and Analyze data ● Player movement ● Player interactions with and outdoor area ● Entering and exiting areas ● Looking at and following directions
  4. 4. MAIN RESEARCH OBJECTIVES ● Fostering a tool ecosystem ● Creating tools that are meaningful to teachers ● Adopt a “simply works” (but customizable) approach for our analytics platform.
  5. 5. LOCATION-BASED GAMES Player: The character represented by an oriented avatar or symbol. Augmented Map: A real world map that is augmented with the game model. The model is mainly divided in: - Areas/Regions: Real world region that can be accessed or exited (i.e. parks, cities, districts) - Points of interest: A real world element that can be looked (i.e. monuments, buildings). - Virtual elements: Objects that exist only in the game and can be interacted (i.e. monsters, characters, portals) Navigation: Indications to interesting game elements. Points of Interest Virtual Elements Regions Midoki GO Deliver Pokémon GO Ingress
  6. 6. COLLECT DATA ● Actions happen in real-time and everywhere ● The game can have a diverse range of interactions including location-based, serious-game based or game-specific ● Data has to be gathered and presented by analyzing different types of data Player entered park (Area) Player looked at fountain (POI) Player interacted with dragon (VE) Player followed indications
  7. 7. EXPERIENCE API (xAPI) xAPI is Generic and Extensible The model allows tracking of all in-game interactions as xAPI traces (statements). It also simplifies data sharing. To use the Profile, several open-source tracker implementations are available. Experience API (xAPI) for Serious Games Profile: standard interactions model implemented in xAPI with ADL.
  8. 8. LOCATION-BASED xAPI Extensions (to append in any action): ● Location: where the action happens (coordinates). ● Orientation: of the actor’s view (degrees) ● Guide: that the player is following (steps) Targets (to identify augmented map elements): ● Area: subtypes building, urban-area, green-zone, water. ● POI: to identify points of interest. ● Direction: to follow. Verbs (to perform actions with): ● Moved: when an actor changes its position ● Entered/Exited: to access or leave zones. ● Looked: to detect sightseeing ● Followed: when directions are followed.
  9. 9. TRACES The most common actions in location-based games can be created by combining the previous elements. Action Noun Verb Target Extensions Moving Player Move Areas (*) Location Entering place Player Enter Areas (*) Location Exiting place Player Exit Areas (*) Location Looking at place Player Look Areas (*), especially POIs Location Orientation Following navigation indications Player Follow Direction Location Guide
  10. 10. ANALYSIS Traces generated are sent to a LA server that analyzes the traces and generates both visualizations and metrics. There are two types of analysis + alerts: ● Default: is provided by the system and therefore generic for all location-based games. ● Custom: specific visualizations that requires programming to extract game-specific insigth ● Rule -based alerts. Simply enough to be created by instructors ⇒ Simple, but yet powerful, customization
  11. 11. VISUALIZATIONS Analysis outcomes are presented in an easy to understand way: ● Default: Are provided in the LA system for the given events. ○ Default visualization for location-based include: movement in the game environment, area/POI interactions (enter, exit, look), directions followed, etc. ● Custom: Can be created to represent game-specific metrics. ○ For traces with location extension when position is relevant: ■ Heatmaps ■ Route maps (when order matters) ○ For traces without location or when position is not relevant (i.e. distance, angle) ■ Bars, lines, metrics, averages, etc.
  12. 12. ASSESSMENT ▸ Complements the analysis ▸ Offers insights not just a score ▸ Offers a qualitative view of the students’ learning ▸ Assessment can combine location-based data with additional time-related information to assess the behavior over time of the students ▸ Relevant to detect misconceptions and allow the use of targeted feedback to improve the learning experience
  13. 13. CONCLUSIONS ▸ xAPI location-based profile is extended for pervasive experiences ▸ (Limitation) teachers are responsible of extracting meaning from the insights if no additional layer of customization is provided to link inputs to actual learning ▸ The solution provides a simple location-based assessment model that can aid and support traditional assessment methods
  14. 14. THANK YOU! Any questions Ivan Martinez-Ortiz imartinez@fdi.ucm.es www.e-ucm.es github.com/e-ucm/

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