Nzoia WeShareIt Situation Awareness Dataset
datasetposted on 01.06.2018 by Abby Muricho Onencan, B. (Bert) Enserink, B. (Bartel) van de Walle
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
The data consists of three separate datasets: 1. Detailed responses from 35 respondents to a pre-game and post-game questionnaire using the 10-dimensional subjective rating scale for situation awareness. The scale is known as Situation Awareness Rating Technique (SART). In this dataset are also the detailed calculations of the three aspects of situation awareness (1) the demand on attentional resources (D); (2) the supply of attentional resources (S); and (3) the understanding of the situation (U). The final part of the dataset calculates situation awareness using the following equation: SA=U-(D-S). U represents the summed understanding. D represents the summed demand and S represents the summed supply. 2. The refined situation awareness data that is divided into seven variables. First, Gender where the respondents are divided into males and females. Second, familiarity, where the data is divided in two groups, 1 for low familiarity (pre-game) and 2 for high familiarity (post-game). Low familiarity refers to the normality stage where the respondents have not been exposed to climate change induced disasters. High familiarity refers to the post disaster exposure stage where the respondents are more aware of the climate change risks. Third, the data is divided into seven teams. There were seven game sessions and each game session had five players. The teams are grouped from 1 (first game session) to 7 (last game session). The fourth variable is the summed demand score for each of the respondents for the pre-game and post-game sessions. The fifth variable is the summed supply score for each of the respondents for the pre-game and post-game sessions. The sixth variable is the summed understanding score for each of the respondents for the pre-game and post-game sessions. The seventh and last variable is the situation awareness score for each of the respondents for the pre-game and post-game sessions. 3. The in-game data for the results (number of smileys) for each of the respondents, in all the seven game sessions during every successive round (6 rounds per session). Smileys are calculated differently for each county government. The smiley score is a sum of the food, environment and investment in public service smileys. The game design and calculation of the scores are detailed in the Game Design report that can be accessed in the TU Delft repository.