Sunday, February 17, 2008

Playing Saving Adryanee

Saving Adryanee is a learning game by Dr Sebastian Loh of Southern Illinois University Collaboraty for Interactive Learning Research (CILR). It is a playable module for Neverwinter Nights made with the Aurora Toolset.

I was lucky to have the opportunity to play this game which is not yet released as it is still under development. I won't give too much detail because it is not the final version and I wouldn't want to bias any trials.

Adryanee is sick and to save her, you need to discover some nutrition facts and collect some medicines. It is a quest game like World of Warcraft where information and items are 'dropped' by NPC's (Non Player Characters).

The game took me around 2 hours but I could now re-run it in 10 minutes. Embedded in the game are 3 nutrition based facts associated with a general idea of poor nutrition causing diseases. The game could be played without processing this information because it was not actually necessary to recall the information. Once you had 'learnt' the fact, your avatar 'knew' the fact and this altered NPC interactions. There was never a dialogue choice that depended on correct recall or application of a fact. There was also a theme of problem solving being research based and not about superstitious learning. Facts should be tested.

Nevertheless my attention was focused on these facts because I expected that they would be relevant in solving the game.

The learning content was well integrated into the game, in the sense of endogenous fantasy (Malone and Lepper)

In terms of playability and engagement, I found the game too hard and not rewarding. Detailed searching of NPC's and objects is not my idea of fun though it may well suit other playing styles. It should be noted that it is a game under development and that it will no doubt be modified as a result of further playability trials. What was absent was the ability to match the level of difficulty to the players ability. Also missing were interim rewards.

Consider the learning on these criteria:
Declarative knowledge
I can recall all three disorders and their cures because I was engaged but recall was not necessary to play the game. My recall is enhanced because I already knew these 3 facts. 3 facts in 2 hours is not a high information density.

Procedural knowledge
At no stage was I required to use the declarative knowledge. If, later in the game, I was required to correctly diagnose and treat NPC's, the knowledge would cease to be 'inert' knowledge and be better retained. Though my avatar assembled and evaluated data with a scientific method, the player was not required to evaluate. It was scientific method by example not by practice.

Problem solving
Have my problem solving skills been improved? What do I take away that might allow me to do evidence based research. Might my skills at solving infectious disease or forensic medicine problems be enhanced? I was shown by example, causality, evidence, evaluation of evidence but I was not ever problem solving in this domain. I was doing a lot of problem solving in the game domain. I knew I needed to get into the inn and I knew what items I needed. I was second guessing the game designer and drawing on my experience in playing similar games.

Watch this space. Its early days for learning games. The Aurora Toolset has a lot of potential for the cost effective creation of content. Purpose built modules like this can have inbuilt audit trails, see Loh, Designing Online Games Assessment as “Information Trails”

A big thank you to Dr Sebastian Loh for making this game available despite power outages and deep snow at that time. A dwarf walked up to me and gave me advice, it took a sentence of dialogue or two to be sure it wasnt a NPC, It was Sebastian, thanks!

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