September 25, 2001	Key Drivers for C2 Performance: Data Mining SCUDHunt Experiment Data Data Dictionary
	2009 Cantata Court *Vienna, VA 22182 * 703-281-5694

1.0 Introduction

The Information Superiority JWCA Task Force, in conjunction with US Joint Forces Command, are developing an operational concept, operational architecture, and implementation roadmap for JTF C2 to enable the JROC to shape the future Joint C2 Joint Mission Area (JMA) and to realize the full potential of JV2020 warfighting capabilities. In support of this effort, the Joint C4ISR Decision Support Center is working to define the conditions that affect C2 performance and to develop distinct, divergent alternatives for future C2 concepts. To do this, the Task Force must identify and understand the key C2 drivers and corresponding metrics.

Measuring C2’s effectiveness and its relationship to battlefield success, shared situational awareness, and decision-making is a challenging problem. In the past, most of this analysis has been subjective and has not taken a rigorous statistical approach. Under a task funded by the Defense Advanced Research Projects Agency (DARPA), ThoughtLink, Inc., together with the Center for Naval Analyses (CNA), conducted an experiment that measured the effect of different modes of communication and visualization on a distributed team's shared situational awareness (SSA). These variables in C2 were analyzed and measured with data collected from distributed teams playing an on-line game, SCUDHunt.

The SCUDHunt experiment collected a vast amount of data; further analysis of this data provides insights and associations in a number of C2 variables including factors contributing to the quality and timeliness of decisions. To this end, ThoughtLink is supporting OSD’s Joint C4ISR Decision Support Center (DSC) – mining the existing SCUDHunt experiment data to identify these C2 factors.

This document outlines the data dictionary for DSC’s project, providing an organized listing of all the data elements that are pertinent to the analysis, with detailed definitions to provide a common understanding. The first section provides definitions (for instance the calculation used for SSA and the different information assets). The following section describes each of the data elements contained in the Microsoft Access database and Microsoft Excel files. The Access database is data generated from the on-line, distributed game and the Excel files were generated by hand from participant questionnaires.

2.0 Overview of the 2000 SCUDHunt Experiment

2.1 Overview

In 2000, ThoughtLink, together with CNA, conducted an experiment that measured the effect of different modes of communication and visualization on a distributed team's SSA. The study was done for DARPA’s Wargaming the Asymmetric Environment (WAE) program.

The approach we took was to develop an experiment in which teams would play an online game. The game we developed, SCUDHunt, was designed with the following factors in mind:

1. Team members had to share information to do well

2. Their decisions could be directly and easily recorded

3. The measure of their decisions would describe the degree of shared situational awareness of the team.

The experiment included 6 teams composed of 4 people on each team. Each team played 6 different versions of the game - each version used a different combination of communication and visualization tools. The results of this study showed that communication and visualization play an important role in how distributed teams build their shared situational awareness. It also exposed some interesting facets associated with distributed teams, their processes, and social dynamics and relationships.

In addition to these findings, the experiment showed that the use of simple games, designed to target specific experiment goals, is a promising technique for continued research in this rich and complex field. Further studies in this area will contribute to our understanding of what helps and hinders distributed teams' SSA; what parameters we can, and should, measure; how to measure the effect of those parameters; and how to apply lessons learned to larger more complex situations (e.g., Coalition Operations) and to less understood adversaries (e.g., Asymmetric Warfare).

2.2 Game Description

SCUDHunt is a simple, short, abstract game of command, control, communications, intelligence, surveillance and reconnaissance (C3ISR) played by a team of 4 players. The game requires group decision-making and allocation of scarce resources under conditions of time pressure and uncertainty.

The goal of the game is for team members to correctly determine where three Scud launchers are located, on a 5 by 5 grid. The grid represents the fictional country of Korona. Korona is divided into 25 grid squares identified by columns numbered from 1 to 5 and rows lettered from A to E. Row E is the coastline of the Gulf of Sabani. Grid C3 is the capital city, Koronabad, the only “terrain” on the map. Each of the three targets randomly deploys in a different grid square at the start of play. All targets are stationary.

Each team member controls a different sensor, and team members must share their sensor results in order to identify the launcher locations. In each turn, team members decide, typically in a collaborative process, where to locate each sensor. The results for a sensor are returned to the team member controlling it. Results include: X - launcher found; O - no launcher in the square; ? - not sure. Some sensors can also be killed or temporarily disabled on a turn.

At the end of each turn, based on the search results to date, each team member nominates at least three grid squares in which the launchers might be located. The overlap among the nominations reflects the team's shared situational awareness. If there is no overlap, every team member will vote for a different set of grid squares. If there is complete shared situational awareness, each member will vote for the same set of grid squares.

2.3 Definition of SSA

We measured SSA as: the total number of nominated squares divided by the number of unique grid squares nominated. Team SSA scores vary from 1 to the number of team members. As an example, given 4 team members each of whom nominates three squares, if there is minimal SSA, each member will nominate different sets of squares. Then the total number of nominated squares is 12 (4 members x 3 squares/member) and the number of unique grid squares is also 12 (there is no overlap), and the team's SSA score is 1. If the same team has complete SSA and each member votes for the same set of grid squares, then their team score will be 4: 12 squares nominated overall divided by 3 unique nominations.

Two important properties of this measurement of SSA are 1) it directly measures SSA and 2) it does so in the natural context of the game, thus it does not depend on the person's subjective assessment or description of their mental model.

More information on SCUDHunt is available at http://www.scudhunt.com.

Figure 1. Sample SCUDHunt Game Board, with COMINT position on left and shared visualization on right, displaying results returned from all sensor assets.

2.4 SSA Experiment and Results

The experiment was designed to evaluate the effects of different modes of communications and visualization on a distributed team's ability to develop shared situational awareness.

The 3 communications modes were:

• none
• text chat
• voice teleconference.

The 2 visualization modes were:

• none
• shared view of the results of each turn (i.e., for each sensor, the result returned was shown: 0, X, or ?. However, team members could not see from the visualization which asset had generated which result.)

We used a Latin Square design, with six teams playing six games each. Each team played all six combinations of the communications and visualization modes; each team played those games in a different order.

There were four players on each team, so we recruited 24 players altogether for the experiment. During game play, the players were distributed, playing over the Internet from different physical locations. In two of the six teams, players knew each other beforehand; on the other four teams, players did not know each other before the experiment began.

Data collected in the experiment included:

• online game data: each player's moves for every turn for each game and their estimates of target locations at the end of each turn
• recordings of all teleconferences
• archives of the text chat sessions
• pre-experiment questionnaires about each player's background in computers and games
• post-game questionnaires, filled out by most players.

We used standard analysis of variance techniques to determine whether the SSA results showed statistically significant differences:

• Among the teams
• Resulting from the sequence in which the teams played the games
• As a result of the different combinations of communications and visualization modes.

The full results are available in the report "Gaming and Shared Situation Awareness" ; in a simplified form, the results of our hypothesis tests are:

• Do communications and shared visualization affect building a shared picture? YES
• Do communications matter? YES
• Does mode of communications matter? NO
• Does shared visualization matter? YES
• Is there interaction between communications and shared visualization? PROBABLY

The least anticipated result was that the mode of communications, text chat or voice teleconference, was not associated with statistically significant differences in team shared situational awareness. We had thought that, because voice communications are richer in contextual information, games with teleconferences would have higher SSA results than games with text chat. This was not the case.

At least two and normally three project members observed each of the 24 games and we collected some interesting observations about game play. These are discussed further in the final report “Gaming and Shared Situation Awareness”.

• Playing a game appeared to promote bonding and trust. Team members bonded quickly and tightly.
• Teams that established a specific process for using their assets and covering the game board appeared to have better shared awareness. This could compensate, to some degree, for degraded communications or visualization.
• Teams that started with the no-communications game seemed to take longer to achieve higher scores in subsequent games.
• Some female team members appeared to be more concerned about achieving consensus than other team members.

Related Publications

• “Gaming and Shared Situation Awareness”, Peter P. Perla, Michael Markowitz, Albert Nofi, Christopher Weuve: Center for Naval Analyses and Julia Loughran, Marcy Stahl: ThoughtLink Incorporated, CRM D0002722.A2/Final, November, 2000. Available through CNA Document Control and Distribution Section at 703/824-2943 or online at http://www.thoughtlink.com/publications/GamingSSA00Abstract.htm
• “Defining and Measuring Shared Situational Awareness”, Albert A. Nofi, CRM D0002895.A1/Final, November, 2000. Available through CNA Document Control and Distribution Section at 703/824-2943 or online at http://www.thoughtlink.com/publications/DefiningSSA00Abstract.htm

3.0 Definitions

This section provides some definitions, including our definition of shared situational awareness (as used in our original experiment for DARPA). It also defines the information assets used in the SCUDHunt game. The Asset briefs provided to the players and the probability tables (used by the game to generate the results) are provided as Appendixes to this document.

3.1 SSA Definition

SCUDHunt was originally designed to measure and assess Shared Situational Awareness (SSA) in distributed teams. It specifically looked at the effect of using different modes of communication (text chat, teleconferencing, and no communications) and the effect of having a shared visualization environment or no shared visualization environment.

The method used for computing SSA in the game is described below:

As our primary data for analysis, we collect the situational awareness of each individual team member's (defined as their mental model of the location of the SCUDs) by asking the team members to provide individual recommended target locations (strike plans). At the conclusion of each turn, we ask them to submit the fewest number of possible squares that they believe might contain a valid target. We then compare these individual lists and calculate a measure of overlap. This calculation is the ratio of the total number of target squares designated by the players in the team, divided by the total number of distinct squares designated. For example, if each of the 4 players designates 3 squares as their recommended targets, the total number of squares is 12.

Suppose those players choose the following target squares:

Player 1: A1, A2, A3

Player 2: A1, B1, B3

Player 3: A1, B2, B5

Player 4: A1, A3, B4.

Of the total of 12 squares, 8 of them are unique (for example, square A1 is counted only once even though it appears on all four target lists.) This team's score for that turn would thus be 12/8 = 1.5. Using this measure, perfect shared situational awareness would equal the number of players, or 4 for the example shown above. The poorest score would have no shared targets and so there would be as many unique squares as there are total target squares. The resulting score would be 1. Thus, our measure of shared situational awareness will range between 1 and 4, the number of players on each team in the SCUDHunt experiment.

3.2 SCUDHunt Asset and Player Role Definitions

This section provides descriptions of the various information assets and player roles in SCUDHunt. These are specific data values used in the Microsoft Access database and in the Excel files are described in the following section of this report.

There are 9 tables in the Access database and 5 Excel files. See Section 5.0 for a listing of the Access tables and their fields, and the Excel files and their fields.

There are seven assets in the game, controlled by four players. See table below for a mapping of player roles to assets.

Player Role	Asset(s) Controlled
Air Asset Manager	Manned AC, UAV
Intel Manager	COMINT, HUMINT
Space Manager	Satellite
Spec Ops Manager	Navy Seals, Joint Spec Ops Team

The various information assets and player roles are described below.

Name:	AIR ASSET MANAGER
Aliases:	none
Where used:	MS Access DB: Game Players Table; Roles Table
Description:	One of the 4 game roles. This player controls the two air assets: the Manned Aircraft and UAV. This combines functions of JFACC, DARO, CINC J-2, etc.

Name:	COMINT
Aliases:	none
Where used:	MS Access DB: Assets Table; Turn Results Table
Description:	One of the 7 information assets. Intelligence asset controlled by the Intelligence Manager. Searches any grid square. Detects vehicles with fair (.5) reliability. In the game, COMINT represents focused attention by skilled analysts, rather than any specific collection platform or capability.

Name:	HUMINT
Aliases:	The Spy
Where used:	MS Access DB: Assets Table; Turn Results Table
Description:	One of the 7 information assets. Intelligence asset controlled by the Intelligence Manager. Searches any grid square with high (.8) detection reliability. The agent has limited mobility, after initial placement in grid C3 he may either remain in the same square or move to any adjacent grid square. If the agent moves he cannot report in the same turn (the program displays an “S” for “silent.”) Each turn the agent is on the board there is a 10% chance he will be caught and detained. This risk rises to 20% in grid squares containing a target. If the spy is killed he is not available for the rest of the game.

Name:	INTEL MANAGER
Aliases:	none
Where used:	MS Access DB: Game Players Table; Roles Table
Description:	One of the 4 game positions. This player controls COMINT and HUMINT assets (roughly equivalent to DCI, DIA and DIRNSA)

Name:	JOINT SPEC OPS
Aliases:	Special Ops
Where used:	MS Access DB: Assets Table; Turn Results Table
Description:	One of the 7 information assets. Intelligence asset controlled by the SpecOps Manager. May be inserted to search any grid square with high (.9) detection reliability. Can move to any adjacent grid square after initial placement. Each turn that a Spec Ops team is in play, there is a 10% chance the team will be compromised, and forced to perform an emergency extraction. If extracted, the team will be unavailable for 1 day to rest and refit. In grid squares containing a target there is a 20% chance of forced extraction.

Name:	MANNED AIRCRAFT
Aliases:	none
Where used:	MS Access DB: Assets Table; Turn Results Table
Description:	One of the 7 information assets. The Air Asset Manager controls this asset. The aircraft may only fly along board edges (Rows A and E, Columns 1 and 5) outside Koronan airspace; either over water or over notional friendly countries bordering Korona. It searches with high (.8) detection reliability. The manned aircraft must “rest” one turn between flights due to crew fatigue and maintenance requirements. Korona may not intercept or engage the manned aircraft. Although the Manned Aircraft is represented by a U-2 icon, it abstracts capabilities of U-2, EP-3, Rivet Joint, J-STARS, ARL, and other platforms.

Name:	NAVY SEALS
Aliases:	none
Where used:	MS Access DB: Assets Table; Turn Results Table
Description:	One of the 7 information assets, it is controlled by the SpecOps Manager. May be inserted to search any grid square with high (.9) detection reliability. Must start insertion along coastal grid squares. Can move to any adjacent grid square after initial placement. Each turn that a Spec Ops team is in play, there is a 10% chance the team will be compromised, and forced to perform an emergency extraction. If extracted, the team will be unavailable for 1 day to rest and refit. In grid squares containing a target there is a 20% chance of forced extraction.

Name:	SATELLITE
Aliases:	none
Where used:	MS Access DB: Assets Table; Turn Results Table
Description:	One of the 7 information assets, it is controlled by the Space Manager. The satellite searches one entire column each turn. It has a good (.7) probability of detecting the presence of vehicles.

Name:	SPACE MANAGER
Aliases:	none
Where used:	MS Access DB: Game Players Table; Roles Table
Description:	One of the 4 game positions. This player controls the reconnaissance satellite (in the real world this is a committee).

Name:	SPEC OPS MANAGER
Aliases:	none
Where used:	MS Access DB: Game Players Table; Roles Table
Description:	One of the 4 game positions in SCUDHunt. This player controls Special Operations teams including the Navy Seals and the Joint SpecOps team. This asset is roughly equivalent to Unified Command SOC commander, under NCA tasking approval constraints.

Name:	UAV
Aliases:	Unmanned air vehicle
Where used:	MS Access DB: Assets Table; Turn Results Table
Description:	One of the 7 information assets, it is controlled by the Space Manager. The UAV may enter Koronan airspace to search any five contiguous grid squares (column, row, diagonal or combination). There is a 10% chance that the UAV can positively identify a target; this represents an unusually favorable conjunction of lighting, view angle and flaws in enemy concealment and deception. For each grid square it enters, there is a 10% chance that a UAV will crash or be shot down, which aborts any further search on that turn. In grid squares that contain a target, or over the city of Koronabad (C3) this probability is increased to 20%. A lost UAV will be replaced automatically on the next turn.

4.0 SCUDHunt Data

The SCUDHunt game was originally developed to support research for DARPA. The experiment required a great deal of data to be collected. Some of this data was automatically generated by the on-line game and stored in a Microsoft Access database. Additional data was collected in the form of participant questionnaires and subjective observations recorded by the executors of the experiment. The questionnaires are provided as Appendixes to this document. Each team played two games using telephone as the communication and these conversations were recorded. Parts of the conversations were transcribed and stored in a Microsoft Excel file. The following sections describe the data elements in the Microsoft Access database and the various Microsoft Excel files that have been created.

4.1 SCUDHunt Database

The data elements defined here are a combination of the Microsoft Access database and the various Microsoft Excel files generated for this data mining experiment.

Name:	ACCURACY OF RESULTS
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	For each turn, this measures the degree to which a player shared correct information, with the other team members, about the results returned by their information asset(s).
Values:	Since different assets search different numbers of squares (ranging from 1 to 5) each turn and players have one or two assets, the number of search results returned to a player might be as low as 2 or as high as 10. This percentage is computed by dividing the number of search results a player accurately shared with team mates by the total number of search results shared (which might be less than the total number returned – see COMPLETENESS OF RESULTS for an associated measure). Accuracy is computed on a per player/per game/per turn basis.

Name:	AGE
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s age (in years).
Values:	2 digit number. Valid ranges for this experiment include: 13-59.

Name:	AGGREGATE
Aliases:	Visualization Type (Shared or No Vis)
Where used:	MS Access DB: Games Table
Description:	Designates the type of visualization used in a game.
Values:	There are two values: check mark = shared visualization; no check mark (null) = no shared visualization.

Name:	AGREEMENT?
Aliases:	Team Agreement
Where used:	MS Excel Files: Team Data – PostGameQ-ByGame Worksheet
Description:	Subjective score assigned by team members on the extent that the participant and the others agreed.
Values:	Used a scale of 1- 5 (1=None/Very Little and 5=A Lot/Very Much)

Name:	ASSET ID
Aliases:	none
Where used:	MS Access DB: Assets Table; Turn Results Table MS Excel Files: Players
Description:	The ID associated with the various information assets except in the Turn Results table, where the name is used.
Values:	A value of 1-7; Each Asset ID corresponds to a different information asset. Asset 1 = Satellite; Asset 2 = Manned Aircraft; Asset 3 = UAV; Asset 4 = Navy Seals; Asset 5 = Joint Spec Ops; Asset 6 = COMINT; Asset 7 = HUMINT

Name:	ASSET NAME
Aliases:	none
Where used:	MS Access DB: Assets Table
Description:	The names associated with the 7 different information assets.
Values:	Asset values include: Satellite; Manned Aircraft; UAV (unmanned air vehicle); Navy Seals; Joint Spec Ops (joint special operations); COMINT (communication intelligence); HUMINT (human intelligence)

Name:	ASSET PLCMENT COMPLIANCE
Aliases:	Asset placement compliance
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player complies by placing their asset(s) where other players have instructed them.
Values:	Possible values are: 0 (did not comply for any asset),1 (complied with one asset) or 2 (complied for both assets, where applicable).

Name:	ASSET PLCMENT COMPLIANCE COMMENT
Aliases:	Asset placement compliance comment
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows compliance with other players in regards to their asset placement.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	ASSET PLCMENT W/O NEGOTIATION
Aliases:	Asset placement without negotiation
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player played their asset(s) without negotiating.
Values:	A whole number.

Name:	ASSET PLCMENT W/O NEGOTIATION COMMENT
Aliases:	Asset placement without negotiation comment
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows no negotiation of where to place an asset.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	ASSET PLCMENT W/NEGOTIATION
Aliases:	Asset placement with negotiation
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player negotiated with other players on where he/she should place his/her asset(s).
Values:	A whole number.

Name:	ASSET PLCMENT W/NEGOTIATION COMMENT
Aliases:	Asset placement with negotiation
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows negotiation of where to place an asset.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	CHANGE OF LEADER OVER TIME?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring if there was a change in leaders over the session of games.
Values:	Free text. Mostly yes or no, but occasionally players included comments.

Name:	CITY
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The city where the players live.
Values:	Free text.

Name:	COL
Aliases:	Column
Where used:	MS Access DB: Turn Results Table; Strike Turns Table
Description:	On the Turn Results Table, this represents the column on the SCUDHunt game board where assets have returned results. It is paired with a game board Row and is associated with an information assets finding per game/per turn. On the Strike Turns Table, this represents the column on the SCUDHunt game board where a player has placed a strike on a per game/per turn.
Values:	There are 5 columns. Values are: 1,2,3,4, or 5.

Name:	COMM
Aliases:	Mode of Communication
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Describes the mode of communication used in a particular game.
Values:	Values are No (for no communication), text chat, and voice.

Name:	COMM ABILITY?
Aliases:	Communication Ability
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Subjective score assigned by each player on how well they were able to communicate with their teammates for each game.
Values:	Used a scale of 1- 5 (1=Poor and 5=Excellent)

Name:	COMPLETENESS OF RESULTS
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	For each turn, the percentage of search results that a player shared with their team mates.
Values:	Since different assets search different numbers of squares (ranging from 1 to 5) each turn and players have one or two assets, the number of search results returned to a player might be as low as 2 or as high as 10. This percentage is computed by dividing the number of search results a player shared with team mates by the total number of search results returned from all of their assets. This is computed on a per player/per game/per turn basis.

Name:	COMPUTER EXPERIENCE
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A player’s self-assessment of how much computer experience they have. Values were: Low: Seldom use computers; Moderate: Use computers often and are comfortable with them; High: Use computers a lot and feel very confident about your abilities
Values:	Values include: low, seldom, and high.

Name:	CONTROL INSTRUCTIONS
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice from control providing game instructions to the players.
Values:	Either the actual text typed by control or an observer, or a transcription of their voice comment.

Name:	COUNTRY
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The country where the players live.
Values:	Free text.

Name:	DATE PLAYED
Aliases:	none
Where used:	MS Access DB: Games Table
Description:	The starting date and time for each game
Values:	The format is M/DD/YY h:mm:ss PM or AM. For the purposes of this experiment, valid date ranges fell between 09/24/00 – 10/16/00.

Name:	DATE Q COMPLETED
Aliases:	Date Questionnaire Completed
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	The date players completed their Post Game Questionnaire
Values:	The format is MM/DD/YY. For the purposes of this experiment, valid date ranges fell between 09/28/00 – 11/08/00.

Name:	DESCR OF WORKING DISTR
Aliases:	Description of working as a member of a distributed team within their own organization
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s description of their experience working as a member of a distributed team within their own organization.
Values:	Free text

Name:	DESCR OF WORKING DISTR OUTSIDE ORG
Aliases:	Description of working as a member of a distributed team outside their own organization
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s description of their experience working as a member of a distributed team outside their own organization.
Values:	Free text

Name:	DIRECTING OTHERS ASSET PLCMENT
Aliases:	Directing others asset placement
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player directs another player’s asset placement.
Values:	A whole number.

Name:	DIRECTING OTHERS ASSET PLCMENT COMMENT
Aliases:	Directing others asset comment
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment directing another player’s asset placement.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	DIRECTING OTHERS STRIKE PLAN
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player directs another player’s strike plan.
Values:	A whole number.

Name:	DIRECTING OTHERS STRIKE PLAN COMMENT
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment directing another player’s strike plan.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	DIRECTIVE RE: GAME PROCESS
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player directs players to change the way (the process) of how they are playing the game.
Values:	A whole number.

Name:	DIRECTIVE RE: GAME PROCESS COMMENT
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment directing another player or players in a process for playing the game.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	EASIEST GAME?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring what the easiest game was during a particular session.
Values:	Free text. Usually the Game’s number – but occasionally the type of game (e.g., Voice and visual).

Name:	EMAIL
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s work or home e-mail address.
Values:	Text or numbers representing a player’s e-mail. (user name@domain name)

Name:	EMAIL EVER USED?
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player has ever used e-mail.
Values:	Yes, No. All values in the experiment data were Yes.

Name:	EMAIL FREQ?
Aliases:	Email frequency
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asking how often a player uses email. Values were: Often: Weekly or more; Frequently: Monthly or more; Rarely: Yearly or less.
Values:	Often, frequently, rarely.

Name:	EQUALS?
Aliases:	Team equality
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Subjective score assigned by each player on the extent that they and the other team members were equals.
Values:	Used a scale of 1- 5 (1=None/Very Little and 5=A Lot/Very Much)

Name:	FREQ OF GAME PLAY?
Aliases:	Frequency of computer game play
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine the frequency of player’s computer game play. Values were: Often: Weekly or more; Frequently: Monthly or more; Rarely: Yearly or less.
Values:	Often, frequently, rarely.

Name:	FUN?
Aliases:	Was the game fun?
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Subjective score assigned by each player on how fun a particular game was.
Values:	Used a scale of 1- 5 (1=Not Fun At All and 5=Very Much Fun)

Name:	GAME COMMENTS
Aliases:	none
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Free text elaborating on overall comments for a particular game.
Values:	Any text typed by the participants.

Name:	GAME ID
Aliases:	none
Where used:	MS Access DB: Game Players Table; Games Table; Strike Turns Table; Text Chat Table; Turn Results Table MS Excel Files: Team Data– PostGameQ-ByGame Worksheet; SSA Details; Text Chat-Voice;
Description:	Numeric game identifier. The Game ID is automatically and sequentially generated after the creation of each game.
Values:	Any whole number. For the purposes of this experiment, Game IDs ranged from 65 to 119.

Name:	HARDEST GAME?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring what the hardest game was during a particular session.
Values:	Free text. Usually the Game’s number – but occasionally the type of game (e.g., no communication).

Name:	HIGHEST EDU
Aliases:	Highest education completed
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The highest level of education a player has completed.
Values:	Values include: Jr. High, High school, bachelors, masters, and doctorate.

Name:	HOME #
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s home telephone number.
Values:	10 digit number in the following format: 222-222-2222.

Name:	IF LAUNCHER CONSENSUS – TENSION?
Aliases:	none
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	A subjective question for each game where participants are asked if their team tried to come to consensus, was there tension between them and the other team members.
Values:	Used a scale of 1- 5 (1=None/Very Little and 5=A Lot/Very Much)

Name:	IF LEADER WHO?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring who on the team (if anyone) was the leader
Values:	One or more of the player’s names written in free text. Some people also included comments in this field.

Name:	KNEW PLAYERS?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring if the player knew any of the other players on their team.
Values:	Do not know them, slightly, well, and very well

Name:	LAUNCHER CONSENSUS COMMENTS
Aliases:	none
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Free text elaborating on the question associated with whether their team tried to come to consensus on launcher locations.
Values:	Any text typed by the participants.

Name:	LAUNCHER CONSENSUS?
Aliases:	none
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	A subjective question for each game where participants are asked if their team tried to come to consensus on decisions on launcher locations.
Values:	Valid values are Yes or No

Name:	LEADER COMMENTS
Aliases:	none
Where used:	MS Excel Files: Leader Data
Description:	Free text elaborating on the question associated with whether there was a leader during a particular session of games.
Values:	Any text typed by the participants.

Name:	LEADER TODAY?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring if there was a leader of the session games.
Values:	Free text. Most players answered yes or no.

Name:	LIKE PLAYING GAMES?
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player likes playing games.
Values:	Yes, No.

Name:	LIST OF MIL ORG
Aliases:	Military/Defense experience
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A list of a player’s military organization and/or service.
Values:	Free text.

Name:	MB TYPE
Aliases:	Myers-Briggs Personality Type Indicator (MBTI)
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s Myers-Briggs Personality Type (if known).
Values:	Four characters representing the 16 different MBTI personality types. These include: ISTJ, ISFJ, INFJ, INTJ, ISTP, ISFP, INFP, INTP, ESTP, ESFP, ENFP, ENTP, ESTJ, ESFJ, ENFJ, ENTJ.

Name:	MESSAGE
Aliases:	Text Chat Messages
Where used:	MS Access DB: Text Chat Table
Description:	The actual text typed in the text chat window during a game where the text chat option was the games mode of communication. Each entry in this table is linked to a particular player and a particular sequence.
Values:	Any free text typed by a player.

Name:	MIL/DEF EXPERIENCE
Aliases:	Military/Defense experience
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question to determine if a player has military/defense experience.
Values:	Yes, No.

Name:	MULTI-PLAYER WEB GAMES BEFORE?
Aliases:	Played computer games before
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player has played multi-player, web-based games before.
Values:	Yes, No.

Name:	MULTI-PL WEB GAME FREQ?
Aliases:	Multi-player web-based game play frequency
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine the frequency of a player’s multi-player, web-based game play. Values were: Often: Weekly or more; Frequently: Monthly or more; Rarely: Yearly or less.
Values:	Often, frequently, rarely.

Name:	NON-GAME COMMENTS
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player makes a non-game related comment.
Values:	A whole number.

Name:	NON-GAME COMMENTS COMMENT
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows a player’s comment not related to the play of the game.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	NUM TURNS
Aliases:	None
Where used:	MS Access DB: Games Table
Description:	A number that is associated with each SCUDHunt game and signifies the number of turns that were established by Control when the game was initiated.
Values:	Any number between 1 and 7. In the SCUDHunt experiment, the number of turns was always set to 5.

Name:	ORGANIZATION
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The organization (or school) where the players work or attend school.
Values:	Free text.

Name:	OWN VIS ABILITY?
Aliases:	Ability to visualize
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Subjective score assigned by each player on how well they were able to visualize where the SCUDs were on the game board on a per game basis.
Values:	Used a scale of 1- 5 (1=Poor and 5=Excellent)

Name:	PLAYED GAMES BEFORE?
Aliases:	Played computer games before
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player has played computer games before.
Values:	Yes, No.

Name:	PLAYER ID
Aliases:	None
Where used:	MS Access DB: Game Players Table; Players Table; Strike Turns; Text Chat Table; MS Excel Files: Text Chat-Voice
Description:	Either a number associated with a player or the player’s first name.
Values:	On the Players Table, the Player ID is a sequentially assigned number associated with each player’s name. The values for the experiment are the numbers 20 – 43. In the other tables cited above, the Player ID is equal to the Player’s first name. There were 24 participants in the SCUDHunt experiment and each had unique first names.

Name:	PLAYER NAME
Aliases:	None
Where used:	MS Access DB: Players Table MS Excel Files: Players; Team Data– PostGameQ-ByGame Worksheet; Team Data-PostGameQ-General Worksheet; Text Chat/Voice Table; Leader ; Team Data-PlayerBackground Worksheet
Description:	SCUDHunt experiment player’s first name.
Values:	There were 24 participants in the SCUDHunt experiment and each had unique first names.

Name:	PLAYER ORG
Aliases:	None
Where used:	MS Access DB: Players Table
Description:	SCUDHunt experiment player’s organization affiliation
Values:	There were 24 participants in the SCUDHunt experiment and they came from a variety of organizations. Two teams were junior and senior high school students. The senior high school students (Team 1) were from Thomas Jefferson High School in Alexandria, VA. The junior high school team was from Albright Middle School in Houston, TX.

Name:	PLAYERS ROLES?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring what others’ roles were in the games (if any). Some suggested values included: leader, brainstormer, facilitator, keep track of details.
Values:	Free text describing other players on the team and what roles they played on the team.

Name:	PL WEB-BASED GAMES BEFORE?
Aliases:	Played web-based games before
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player has played web-based games before.
Values:	Yes, No.

Name:	POST-GAME QUESTIONNAIRE
Aliases:	none
Where used:	MS Excel Files: Players
Description:	Lists whether the player filled out a post-game questionnaire(s). This questionnaire was given to participants after playing each session of 1 or more games.
Values:	There are two values for Post-Game Questionnaire field in the Players Table: X = we have the questionnaire and BLANK means no questionnaire was filled out.

Name:	PWD
Aliases:	Password
Where used:	MS Access DB: Players Table
Description:	SCUDHunt participant’s password for logging in to SCUDHunt.
Values:	This can be any text string created by the Controller. The convention for the SCUDHunt experiment was to use the first name as the login and the first initial of the participant’s last name as the password.

Name:	QUESTIONING OTHERS ASSET PLACEMENT
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player questions the placement of a player’s asset.
Values:	A whole number.

Name:	QUESTIONING OTHERS ASSET PLACEMENT COMMENT
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows a player questioning another player on their decision to place an asset.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	QUESTIONING OTHERS STRIKE PLANS
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player questions the strike plan of another player.
Values:	A whole number.

Name:	QUESTIONING OTHERS STRIKE PLANS COMMENT
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows a player questioning another player’s strike plan.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	QUESTIONNAIRE INFO
Aliases:	none
Where used:	MS Excel Files: Players
Description:	Lists whether a player filled out a pre-game questionnaire. This questionnaire was given to participants before playing the games and captured a lot of background information.
Values:	There are two values for Questionnaire Info in the Players Table: X = we have the questionnaire and BLANK means the player did not fill out a pre-game questionnaire.

Name:	QUESTIONS RE: GAME PROCESS
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player questions the way (the process) of how they are playing the game.
Values:	A whole number.

Name:	QUESTIONS RE: GAME PROCESS COMMENT
Aliases:	none
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment questioning the way (the process) of how they are playing the game.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	RECIPIENT ID
Aliases:	Text chat recipient
Where used:	MS Access DB: Text Chat Table
Description:	Used to specify the person to whom a text chat message was sent to directly. In most instances, text chat went to all players and Control. Players had the ability to send private messages to an individual or Control.
Values:	Possible values are: 0, meaning the chat message was sent to everyone in the game (as well as observers and Control); Control; or the first name of a specific player or observer.

Name:	ROLE ID
Aliases:	none
Where used:	MS Access DB: Roles Table
Description:	A number associated with the various Asset Manager roles used in the game. Each number is associated with a different asset manager.
Values:	Values of 1-5; Each Role ID corresponds to a different player role. Role 1 = Satellite; Role 2 = Air; Role 3 = Spec Ops; Role 4 = Intel; Role 5 = Demo

Name:	ROLE NAME
Aliases:	none
Where used:	MS Access DB: Roles Table MS Excel Files: Players
Description:	The names associated with the 4 player roles and the role of demo for when the game is in demonstration mode.
Values:	Role name values include: Satellite, Air, Spec Ops, Intel, and Demo.

Name:	ROW
Aliases:	none
Where used:	MS Access DB: Turn Results Table; Strike Turns Table
Description:	On the Turn Results Table, this represents the row on the SCUDHunt game board where assets have returned results. It is paired with a game board Column (COL) and is associated the result returned by an asset per game/per turn. On the Strike Turns Table, this represents the row on the SCUDHunt game board where a player has placed a strike per game/per turn.
Values:	There are 5 rows. Values are 1,2,3,4, and 5.

Name:	SCUD1 COL
Aliases:	none
Where used:	MS Access DB: Games Table
Description:	This represents the column location of the first hidden SCUD. It corresponds to the value in SCUD1 ROW to provide the hidden SCUDs location.
Values:	There are 5 columns. Values are 1,2,3,4, and 5.

Name:	SCUD2 COL
Aliases:	none
Where used:	MS Access DB: Games Table
Description:	This represents the column location of the second hidden SCUD. It corresponds to the value in SCUD2 ROW to provide the hidden SCUDs location.
Values:	There are 5 columns. Values are 1,2,3,4, and 5.

Name:	SCUD3 COL
Aliases:	none
Where used:	MS Access DB: Games Table
Description:	This represents the column location of the third hidden SCUD. It corresponds to the value in SCUD3 ROW to provide the hidden SCUDs location.
Values:	There are 5 columns. Values are 1,2,3,4, and 5.

Name:	SCUD1 ROW
Aliases:	none
Where used:	MS Access DB: Games Table
Description:	This represents the row location of the first hidden SCUD. It corresponds to the value in SCUD1 COL to provide the hidden SCUDs location.
Values:	There are 5 rows. Values are A, B, C, D, and E.

Name:	SCUD2 ROW
Aliases:	none
Where used:	MS Access DB: Games Table
Description:	This represents the row location of the second hidden SCUD. It corresponds to the value in SCUD2 COL to provide the hidden SCUDs location.
Values:	There are 5 rows. Values are A, B, C, D, and E.

Name:	SCUD3 ROW
Aliases:	none
Where used:	MS Access DB: Games Table
Description:	This represents the row location of the third hidden SCUD. It corresponds to the value in SCUD3 COL to provide the hidden SCUDs location.
Values:	There are 5 rows. Values are A, B, C, D, and E.

Name:	SEARCH RESULT ID
Aliases:	none
Where used:	MS Access DB: Search Results Table
Description:	A number associated with the different search results returned on a per turn/per asset basis.
Values:	Values of 1-6; Each Search Result ID corresponds to a different result. Search Result 1 = Nothing to Report; Search Result 2 = Unidentified Vehicle; Search Result 3 = Suspected Launcher; Search Result 4 = Killed in Action; Search Result 5 = Spy Not Captured; Search Result 6 = Team Extracted.

Name:	SEARCH RESULT NAME
Aliases:	none
Where used:	MS Access DB: Search Results Table
Description:	The search result associated with a particular asset on a particular turn.
Values:	Search result values include: Nothing to Report, Unidentified Vehicle, Suspected Launcher, Killed in Action, Spy Not Captured, Team Extracted.

Name:	SENSOR PLCMNT COMMENTS
Aliases:	Sensor Placement Comments
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Free text elaborating on the question associated with whether their team tried to come to consensus on sensor placement.
Values:	Any text typed by the participants.

Name:	SENSOR PLCMNT CONSENSUS?
Aliases:	Sensor Placement Consensus
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	A subjective question for each game where participants are asked if their team tried to come to consensus on decisions on sensor placement.
Values:	Valid values are Yes or No

Name:	SEQUENCE
Aliases:	none
Where used:	MS Access DB: Text Chat
Description:	Numeric text chat identifier. Sequence is automatically and sequentially generated after each text chat submission, across all games.
Values:	Any whole number. For the purposes of this experiment, Sequence for text chat ranged from Sequence #402 – 3134.

Name:	SESSION
Aliases:	none
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet; Team Data-PostGameQ-General Worksheet
Description:	Numeric identifier for the block of time a team played a game. Most of the SCUDHunt teams played the 6 games over 2 separate sessions.
Values:	Session values include: 1, 2.

Name:	SIGN-UP INFO
Aliases:	none
Where used:	MS Excel Files: Players
Description:	A file identifying if we have player contact info. The sign-up form was on the SCUDHunt web site (www.scudhunt.com)
Values:	There are two values for Sign-up Info in the Players Table: X = we have the sign-up info and BLANK – we are missing the sign-up info.

Name:	SSA SCORE
Aliases:	none
Where used:	MS Excel Files: SSA Details
Description:	A per turn, per game calculation computed by dividing the total number of squares nominated by all players in that turn’s strike plan by the number of unique squares nominated in that turn’s strike plan
Values:	The range of SSA Scores for a 4person team is 1-4, with 1 representing no SSA and 4 representing perfect SSA.

Name:	STATE/PROVINCE
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The State or Province where the players live.
Values:	Free text.

Name:	STREET
Aliases:	Street Address
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s street address
Values:	Free text.

Name:	STRIKE PLAN W/O NEGOTIATION
Aliases:	Submitting a Strike Plan without negotiation
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player submitted a strike plan without first negotiating the nominated squares with other team members.
Values:	A whole number.

Name:	STRIKE PLAN W/O NEGOTIATION COMMENT
Aliases:	Asset placement without negotiation comment
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows no negotiation in making a Strike Plan.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	STRIKE PLAN W/NEGOTIATION
Aliases:	Submitting a Strike Plan with negotiation
Where used:	MS Excel Files: Text Chat-Voice
Description:	Counts the times (per game/per turn) a player negotiated with others about the Strike Plan.
Values:	A whole number.

Name:	STRIKE PLAN W/NEGOTIATION COMMENT
Aliases:	Asset placement with negotiation
Where used:	MS Excel Files: Text Chat-Voice
Description:	The actual text chat or voice comment that shows negotiation of a Strike Plan.
Values:	Either the actual text typed by a participant or a transcription of their voice comment.

Name:	TEAM
Aliases:	none
Where used:	MS Excel Files: Player; Team Data– PostGameQ-ByGame Worksheet; Team Data-PostGameQ-General Worksheet; Text Chat-Voice; Leader ; Team Data-PlayerBackground Worksheet
Description:	Number representing a specific team.
Values:	Values for teams are 1-6.

Name:	TEXT CHAT
Aliases:	none
Where used:	MS Access DB: Games Table MS Excel Files: SSA Details
Description:	Designates the type of communication used in a game.
Values:	There are two values in the Games Table: check mark = text chat; no check mark (null) = either telephone or no comms.; The values in the SSA Details file are either True (meaning there was text chat) or False (meaning there was no text chat).

Name:	TEXT CHAT USED?
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player’s ever used text chat.
Values:	Yes, No.

Name:	TEXT CHAT FREQ?
Aliases:	Text chat frequency
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player’s text chat frequency. Values were: Often: Weekly or more; Frequently: Monthly or more; Rarely: Yearly or less.
Values:	Often, frequently, rarely.

Name:	TM PICTURE SHARED?
Aliases:	Team’s shared picture
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet
Description:	Subjective assessment, by each player, of their team’s shared picture of where the SCUDs were at the end of each game.
Values:	Used a scale of 1- 5 (1=Poor and 5=Excellent)

Name:	TOTAL VOTES
Aliases:	none
Where used:	MS Excel Files: SSA Details
Description:	The total number of votes from all the players associated with a Strike Plan on a per game, per turn basis.
Values:	Any number between 12 (the minimum number of votes for all 12 players) and 75 (all players voting for all squares). The actual values ranged between 12 and 36.

Name:	TURN
Aliases:	none
Where used:	MS Access DB: Strike Turns Table; Turn Results Table MS Excel Files: SSA Details; Text Chat-Voice
Description:	Number representing a specific turn for a specific game.
Values:	Values for game turns are 1-5.

Name:	TURN RESULT ID
Aliases:	none
Where used:	MS Access DB: Turn Results Table
Description:	The search result associated with a particular asset on a particular turn.
Values:	Same values as those used in Search Result Name field. Values include: Nothing to Report, Unidentified Vehicle, Suspected Launcher, Killed in Action, Spy Not Captured, Team Extracted.

Name:	UNIQUE VOTES
Aliases:	none
Where used:	MS Excel Files: SSA Details
Description:	The total number of unique squares nominated for strikes, for a given team, on a per game, per turn basis.
Values:	Any number between 3(all players vote for the same squares, where 3 is the minimum number of squares that had to be included in any strike plan) and 25 (players nominate all possible squares). The actual values ranged between 3and 23.

Name:	VISUALIZATION
Aliases:	Type of visualization
Where used:	MS Excel Files: Team Data– PostGameQ-ByGame Worksheet; SSA Details; Text Chat-Voice
Description:	Describes the type of visualization used in a particular game.
Values:	Values in the Team Data – PostGameQ-ByGame Worksheet are No (for no shared visualization), and shared (for shared visualization).Values in the SSA Details file are True (for shared visualization) and False (for no shared visualization). Values in the Text Chat-Voice are NSV (for no shared visualization) and SV (for shared visualization).

Name:	VTC USED?
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player’s ever used VTC (video teleconferencing).
Values:	Yes, No.

Name:	VTC FREQ?
Aliases:	Text chat frequency
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player’s VTC frequency. Values were: Often: Weekly or more; Frequently: Monthly or more; Rarely: Yearly or less.
Values:	Often, frequently, rarely.

Name:	WEB-BAS. GAME FREQ?
Aliases:	Web-based game play frequency
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine the frequency of player’s web-based game play. Values were: Often: Weekly or more; Frequently: Monthly or more; Rarely: Yearly or less.
Values:	Often, frequently, rarely.

Name:	WEB BROWSER USED?
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if the player has ever used a web browser.
Values:	Yes, No. All values in the experiment data were Yes.

Name:	WEB BROWSER FREQ?
Aliases:	Web browser frequency
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine the player’s web browser use frequency. Values were: Often: Weekly or more; Frequently: Monthly or more; Rarely: Yearly or less.
Values:	Often, frequently, rarely.

Name:	WHY EASIEST GAME?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring why a game was the easiest in a particular session.
Values:	Free text.

Name:	WHY HARDEST GAME?
Aliases:	none
Where used:	MS Excel Files: Team Data-PostGameQ-General Worksheet
Description:	Post Game Questionnaire question inquiring why a game was the hardest in a particular session.
Values:	Free text.

Name:	WORKED DISTR OUTSIDE ORG?
Aliases:	Worked as a member of a distributed team outside your own organization.
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if a player has worked as a member of a distributed team outside of their own organization.
Values:	Yes, No.

Name:	WORKED DISTR OUTSIDE ORG FREQ
Aliases:	Worked as a member of a distributed team outside your own organization frequency.
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine the frequency that a player has worked as a member of a distributed team outside their own organization. Values are: Often: Weekly or more; Frequently: Multiple times a year; Rarely: Once or twice; Never.
Values:	Often, frequently, rarely.

Name:	WORKED DISTR W/IN OWN ORG?
Aliases:	Worked as a member of a distributed team within your own organization.
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine if a player has worked as a member of a distributed team within their own organization.
Values:	Yes, No.

Name:	WORKED DISTR W/IN OWN ORG FREQ
Aliases:	Worked as a member of a distributed team within your own organization frequency.
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	A question asked to determine the frequency that a player has worked as a member of a distributed team within their own organization. Values are: Often: Weekly or more; Frequently: Multiple times a year; Rarely: Once or twice; Never.
Values:	Often, frequently, rarely.

Name:	WORK #
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The player’s work telephone number.
Values:	10 digit number in the following format: 222-222-2222.

Name:	ZIP CODE
Aliases:	none
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The Zip code for where the players live.
Values:	A 5-string number.

Name:	# VOTES AS LEADER
Aliases:	none
Where used:	MS Excel Files: Leader Data
Description:	From the post-game questionnaire, the number of teammates who listed a player as having been a leader during a game. No entries are made for players who received no votes as a leader.
Values:	Values are numbers ranging from 1 – 4.

Name:	# YRS SERVED
Aliases:	# of years served in the military or defense-related occupation.
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The number of years and sometimes a description of a player’s military/defense-related history.
Values:	Free text.

Name:	#1 MOST OFTEN PL GAME?
Aliases:	#1 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The first game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#2 GAME?
Aliases:	#2 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The second game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#3 GAME?
Aliases:	#3 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The third game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#4 GAME?
Aliases:	#4 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The fourth game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#5 GAME?
Aliases:	#5 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The fifth game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#6 GAME?
Aliases:	#6 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The sixth game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#7 GAME?
Aliases:	#7 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The seventh game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#8 GAME?
Aliases:	#8 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The eighth game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#9 GAME?
Aliases:	#9 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The ninth game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

Name:	#10 GAME?
Aliases:	#10 Most often played game
Where used:	MS Excel Files: Team Data-PlayerBackground Worksheet
Description:	The tenth game mentioned in a list of a player’s most frequently played games.
Values:	Free text. The name of a computer or web-based game.

5.0 SCUDHunt Microsoft Access Tables and Excel Files

This section provides an alphabetical listing of all of the tables and files comprising the SCUDHunt database. For each Microsoft Access database table and each Excel file, the data values are listed. These can be cross-referenced with section 4.0 of this report for details for each data element.

5.1 MS Access Database Tables & Fields

Assets Table: Asset ID, Asset Name

Game Players Table: Game ID, Player ID, Role

Games Table: Game ID, Date Played, Scud1 Row, Scud1 Col, Scud2 Row, Scud2 Col, Scud3 Row, Scud3 Col, Num Turns, Aggregate, Text Chat

Players Table: Player ID, Player Name, Player Org, Pwd

Roles Table: Role ID, Role Name

Search Results Table: Search Result ID, Search Result Name

Strike Turns Table: Game ID, Turn, Player ID, Row, Col

Text Chat Table: Sequence, Game ID, Player ID, Message, Recipient ID

Turn Results Table: Game ID, Turn, Asset ID, Row, Col, Result ID

5.2 MS Excel Files & Fields

Leader Data:

Team, Player Name, Session, # votes as leader, Comments

Players:

Name, Team, Asset, Sign-up Info, Questionnaire Info, Post-game Questionnaire

SSA Details:

Game ID, Visualization, Text Chat, Turn, Total Votes, Unique Votes, SSA Score

Team Data -PostGameQ-General Worksheet:

Team, Player, Session, Date Q completed, Knew players?, Leader today?, If leader, who?, Change of Leader over time?, Player Roles?, Easiest game?, Why?, Hardest game?, Why?

Team Data -PostGameQ-ByGame Worksheet:

Team, Player, Session, Game #, Comm, Visualization, Fun?, Tm shared pic?, Own vis ability?, Comm ability?, Sensor plcmt consensus?, Comments, Launcher consensus?, Comments, If consensus: tension?, Agreement?, Equals?, Comments

Team Data – PlayerBackground:

Team, Player, Street, City, State/Province, Zip code, Country, Email, Work #, Home #, Organization, MB Type, Age, Highest Edu, Computer Experience, Email ever used?, Email Freq, Web browser used, Web browser freq, Text chat used, Text chat freq, VTC used, VTC freq, Like playing games?, Played games before?, Freq of game play, Pl. web -based games before?, Web-bas game freq, Multi-player web games before?, Multipl web game freq, #1 most often pl game, #2 game, #3 game, #4 game, #5 game, #6 game, #7 game, #8 game, #9 game, #10 game, Mil/def experience?, list of mil org, #yrs served, Worked distr w/in own org?, Worked distr w/in own org freq, Descr of working distr, Worked distr outside org?, Worked distr outside org freq , Descr of working distr outside org

TextChat-Voice:

Team, Game, Visualization, Player, Turn, Asset plcmnt w/ negotiation, Comment, Asset plcmnt w/o negotiation, Comment, Asset placmnt compliance, Comment, Directing others asset plcmnt, Comment, Questioning others asset placement, Comment, Accuracy of results, Completeness of results, Strike plan w/ negotiation, Comment, Strike plan w/o negotiation, Comment, Directing others strike plans, Comment, Questioning others strikeplans, Comment, Non-game comments, Comment, Directive re: game process, Comment, Questions re: game process, Comment, Control Instructions

Appendix A – SSA Ruminations

(includes excerpts from “Gaming and Shared Situation Awareness”)

There is no agreement yet on the definition of situation awareness or shared situation awareness (SSA); different communities think of it in different ways. We spent quite a long time reviewing SSA research and formulating our own definition. For an extensive discussion of situation awareness - both individual and shared - see “Defining and Measuring Shared Situational Awareness” by CNA team member Albert Nofi.

We characterize situational awareness as a dynamic mental model of our operating environment and our place in it. We build this model through a process we call situation assessment, which consists of four interwoven subprocesses: perception, comprehension, projection, and prediction.

For our purposes, the best description of the process of situation assessment is the one described by Mica Endsley in a 1995 paper as:

the perception of the elements in the environment within a volume of space and time, the comprehension of their meaning, the projection of their status into the near future, and the prediction of how various actions will affect the fulfillment of one's goals.

Note: In the paper, this is Endsley's definition of situational awareness. In a later email, she then refers to it as situation assessment.

So the critical factors in the process of situation assessment are:

1. Perception-acquiring the available facts

2. Comprehension-understanding the facts in relation to our own knowledge of such situations

3. Projection-envisioning how the situation is likely to develop in the future, provided it is not acted upon by any outside force

4. Prediction-evaluating how outside forces may act upon the situation to affect our projections.

It's important to note that these four stages form a dynamic tapestry of interwoven threads rather than a static sequence followed like a flow chart. In developing our situation assessment, we don't necessarily follow the neat flow from perception, through comprehension, then projection, and finally prediction. These stages occur virtually simultaneously, given the speed with which our minds work. As we perceive the information, we are already processing it for comprehension and its implications for our purposes. And this process goes on continuously, so that our situational awareness evolves continuously as well.

We then use the results of our situation assessment to develop a mental model and that mental model represents our situational awareness. A mental model is a "psychological representation of the environment and its expected behavior." The purpose of a mental model is "to provide conceptual framework for describing, explaining, and predicting future system states."

The mental model is inherently subjective, based on integrating acquired information with our own personal structural and situational factors. Structural factors include: training, experience, culture, personality, interests, and skill level. Situational factors include things such as mood, fatigue, stress, time pressure, and the complexity and ambiguity of the situation.

The quality of our situational awareness may be characterized by the degree to which our mental model- our situational awareness-"accurately" reflects objective reality. Measuring the "goodness of fit" between reality and SA is not an easy task, however, we were able to neatly capture this in the game construct, described below.

So what is shared situational awareness? Is it that we understand we are in a common, or shared, situation? Or does it mean that we have a common understanding of a particular situation?

For our purposes, we defined shared situational awareness the degree of overlap in the situational awareness of team members.

There are three elements in the development of a team's shared situational awareness.

1. Build individual situational awareness.

2. Share individual situational awareness. This is probably the most critical factor in creating shared awareness. It depends on effectively communicating each person's awareness, in order to build a shared mental model from the individual mental models.

3. Develop the group's shared situational awareness. This is the integration of the different individual mental models of the situation. Note that there need not be a single "team mental model." Multiple mental models can exist among team members but the models must overlap sufficiently to make it possible to perform the mission.

Appendix B – Probability Tables

Probability calculations are performed by the program. Players do not know exact probabilities; only their own asset’s general system reliability, detection phenomenology, accuracy of information, and timeliness of information. See Appendix C for player handouts.

Key
0	nothing to report
?	unidentified vehicles
X	confirmed launcher
N	UAV crashed
N	Spy captured
C	Team must extract
N	Team destroyed

Satellite

Die roll	Empty	Lchr
0	0	0
1	0	0
2	0	0
3	0	0
4	0	0
5	0	?
6	0	?
7	?	?
8	?	X
9	?	X

Manned Aircraft

Die roll	Empty	Lchr
0	0	0
1	0	0
2	0	0
3	0	0
4	0	?
5	0	?
6	0	?
7	0	?
8	?	X
9	X	X

UAV

Die roll	Empty	Lchr
0	0N	0 N
1	0	0 N
2	0	0
3	0	0
4	0	?
5	0	?
6	0	?
7	0	?
8	?	X
9	?	X

COMINT

Die roll	Empty	Lchr
0	0	0
1	0	0
2	0	0
3	0	0
4	0	0
5	0	?
6	0	?
7	0	X
8	?	X
9	X	X

SpecOps

Die roll	Empty	Lchr
0	0C	? N
1	0	X C
2	0	X C
3	0	X
4	0	X
5	0	X
6	0	X
7	0	X
8	0	X
9	?	X

HUMINT

Die roll	Empty	Lchr
0	0 N	0 N
1	0	? N
2	0	X
3	0	X
4	0	X
5	0	X
6	0	X
7	0	X
8	?	X
9	?	X

Appendix C – Asset Briefs

Space Asset Manager

Player Briefing

Your Job

As Space Asset Manager, you control tasking for one imagery reconnaissance satellite.

Where The Asset Can Travel

The satellite can make one pass over one column of Korona’s air space each day. You must decide which vertical column of grid squares will be searched (1,2,3,4 or 5).

Characteristics and/or Limitations

The satellite is invulnerable: it cannot be shot down or disabled by anything in Korona’s arsenal.

Search Results

Imagery, returned at the end of each turn, is good but not perfect. You will receive a good indication if a grid square is empty, and a good indication if the launcher or civilian vehicles are present.

At the end of each Turn you will receive a summary of the imagery analysis for each grid square in the column you selected:

0 – nothing significant to report (grid square seems empty)

? – vehicles detected (may be launchers, decoys, or routine civilian traffic)

X – launchers confirmed (real) unless result came from COMINT or Manned Air search

Air Asset Manager

Player Briefing

Your Job

As Air Asset Manager, you control the manned aircraft and the unmanned aerial vehicles (reconnaissance “drones”).

Where The Assets Can Travel

The manned aircraft may only fly around the edges of the game board either over bodies of water or friendly countries bordering Korona.

The UAV may fly any path of 5 grid squares, horizontally, vertically, diagonally or in combination. For example it could fly along any row,

column or diagonal. The mission must begin and end in an edge square.

Characteristics and/or Limitations

The manned aircraft is required to “rest” between turns because of crew fatigue, refueling, etc. and can therefore only fly every other turn.

The UAV is vulnerable to Koronan ground fire and technical malfunctions. When the UAV enters a grid square there is a small chance that it will crash, ending the mission. If the UAV overflies a target this risk is increased. Any imagery obtained prior to the crash is transmitted back to base in real time, and will be available for analysis. If a UAV is lost, it will be replaced at the start of the following turn.

Search Results

The manned aircraft’s sensors give an excellent indication if a grid square is empty, and a good indication if vehicles are present, but cannot reliably distinguish between civilian truck convoys and SCUD launchers.

The UAV’s sensor’s imagery is good but not perfect. You receive an excellent indication if a grid square is empty, and a good indication if civilian vehicles are present. There is a low chance of confirming the presence of a launcher.

At the end of each Turn you will receive a summary of the search results for each grid square in the column you selected:

0 – nothing significant to report (grid square seems empty)

? – vehicles detected (may be launchers, decoys, or routine civilian traffic)

X – launchers confirmed (real) unless result came from COMINT or Manned Air search

N – UAV crashed

Intelligence Manager

Player Briefing

Your Job

As Intelligence Manager, you control COMINT and HUMINT. As COMINT Manager you control electronic intelligence assets that monitor Koronan civil, military and government communications. As HUMINT Manager you control one well-placed covert agent inside Korona.

Where The Asset Can Travel

One COMINT intercept analysis may be conducted each turn. You may choose any grid square.

The covert agent begins inside Koronabad (grid square C3). He can move to any adjacent grid squares for each turn.

Characteristics and/or Limitations

COMINT can move to any square and it is impervious to destruction.

The agent must remain in a grid square for one whole turn before he can report the findings for that square. If the agent moves, he cannot report that turn. On any turn that the agent reports there is a small chance that he will be caught and executed. He cannot be replaced. If the agent goes underground (skips a turn) he cannot report or be captured. He can be activated on any subsequent turn.

Search Results

COMINT has a fair chance of detecting any target that is present. Note that the Koronan decoy unit is trained and equipped to simulate the communications traffic of a real launch unit.

Agent reports are excellent if a launcher is present. However, there is a low chance that the agent may misinterpret civilian traffic as the launcher.

At the end of each Turn you will receive a summary of the imagery analysis for each grid square in the column you selected:

0 – nothing significant to report (grid square seems empty)

? – vehicles detected (may be launchers, decoys, school bus or routine civilian traffic)

X – launchers confirmed (real) unless result came from COMINT or Manned Air search

S – “silent” (spy has moved and cannot report)

N – Spy captured and executed

SEAL Team Joint SPECOPS Team

SpecOps Manager

Player Briefing

Your Job

As SpecOps Manager, you control one Navy SEAL team and one Joint Special Operations team.

Where The Asset Can Travel

You may “insert” the SEAL team into any coastal grid square (Row E). You may insert the Joint team into any grid square. Once inserted, a team may remain in place and report, move to any adjacent grid square and report, or call for extraction (skip turn).

Characteristics and/or Limitations

For each turn, in each square that it searches, there is a small chance that a team will be located by Koronan Security and forced to perform an emergency extraction. There is a small chance that it will be caught and destroyed before it can be extracted. In a grid square that contains a launcher or in Koronabad (grid C3) this risk increases. An extracted team will need time to rest and refit before it becomes available for duty again (rest one turn). A destroyed team cannot be replaced.

Search Results

Spec Ops and Navy Seal team reports are excellent. They have an excellent ability to positively identify a target. Teams have a fair chance of being extracted or killed if a launcher is present.

At the end of each Turn you will receive a summary of the SpecOps report, for any grid squares that were searched:

0 – nothing significant to report (grid square seems empty)

? – vehicles detected (may be launchers, decoys, or routine civilian traffic)

X – launchers confirmed (real) unless result came from COMINT or Manned Air search

Thumbs-up icon – get from legend – team emergency extraction (returns after variable refit delay)

N – team destroyed (cannot be replaced)

Appendix D – Pre-Game Questionnaire

SCUDHunt Player Questionnaire

This survey is being given to all SCUDHunt participants as part of a study supporting DARPA’s Wargaming the Asymmetric Environment Program.

The purpose of the survey is to determine your background with computers, collaboration tools, computer games and the military.

This information will be kept confidential. This information may be used in two ways.

1. It may be aggregated in order to characterize the different SCUDHunt teams.
2. Individual answers may be used as quotes in the study’s final briefing. If so, they will be presented as anonymous quotes and the individual will not be identified.

1. Name (first, last):

2. Organization:

3. E-mail address:

4. Please assess your overall level of computer expertise:

- Low: Seldom use computers

- Moderate: Use computers often and are comfortable with them

- High: Use computers a lot and feel very confident about your abilities

5. How you ever used any of the following collaboration tools:

5a. E-mail: Yes No

If Yes, how often:

- Often: Weekly or more

- Frequently: Monthly or more

- Rarely: Yearly or less

5b. Web browsers: Yes No

If Yes, how often:

- Often: Weekly or more

- Frequently: Monthly or more

- Rarely: Yearly or less

5c. Text Chat: Yes No

If Yes, how often:

- Often: Weekly or more

- Frequently: Monthly or more

- Rarely: Yearly or less

-

5d. Video Teleconferencing: Yes No

If Yes, how often:

- Often: Weekly or more

- Frequently: Monthly or more

- Rarely: Yearly or less

6. Do you like playing games: Yes No

7. Have you played computer games before? Yes No

If Yes, how often:

- Often: Weekly or more

- Frequently: Monthly or more

- Rarely: Yearly or less

8. Have you played web-based computer games before? Yes No

If Yes, how often:

- Often: Weekly or more

- Frequently: Monthly or more

- Rarely: Yearly or less

9. Have you played multi-player web-based games before? Yes No

If Yes, how often:

- Often: Weekly or more

- Frequently: Monthly or more

- Rarely: Yearly or less

Please list the games you most often play (up to 10):

10. Do you have military or defense-related experience? Yes No

If Yes, list organizations and or service:

How many years:

11. Have you ever worked with people from your organization who are geographically separated from where you work? Yes No

If Yes, how often:

Often: Weekly or more

Frequently: Multiple times a year

Rarely: Once or twice

Never:

Describe some of your experiences working as a member of a distributed team and the tools that you used to communicate?

12. Have you ever worked as part of a team composed of people outside your organization? Yes No

If Yes, how often:

Often: Weekly or more

Frequently: Multiple times a year

Rarely: Once or twice

Never:

Describe some of your experiences working as a member of a distributed team and the tools that you used to communicate?

Appendix E – Post-Session Questionnaire

Note: This is a Sample from Team 1. For the other teams, the game types would have been paired with the order in which that particular team played the games.

***********************************************************************

Please email to mstahl@thoughtlink.com or loughran@thoughtlink.com or FAX to 703/319-8196

SCUDHunt Post-Game Questionnaire – Team 1

Name: __________________________

Date: __________________________

Your Myers-Briggs type (if you know it and if you don’t mind sharing it) ______

(To determine this, you can take an online test at http://www.onlinepsych.com/public/Mind_Games/ptt/pttframe.htm or http://www.keirsey.com/cgi-bin/keirsey/newkts.cgi )

How well did you know the other team members prior to today’s session?

do not know them_

slightly_____

well_____

very well_____

During the games in today’s session,

- was there a leader? (Yes/No)______________

- if so, who? ____________________________

- did it change over time?______________________________________________

- did team members take on roles? (e.g., leader, brainstormer, facilitator, kept track of details,…) ___________________________________________________

_____________________________________________________________

Which game (or set of communication/visualization conditions) was easiest and why?

_____________________________________________________________

_____________________________________________________________

Which game was hardest and why?_________________________________

_____________________________________________________________

Game 1: Voice, shared visualization (ALREADY PLAYED)

On a scale of 1-5 (1=Not At All and 5=Very Much), was this game fun? _____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your team’s shared picture of where the SCUDs were at the end of the game? _____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to visualize where the SCUDs were on the game board? _____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to communicate with your teammates? ____

Did your team try to come to consensus on decisions on sensor placement?

(Yes/No)__________________________________________________

Did your team try to come to consensus on decisions on launcher locations?

(Yes/No)__________________________________________________

If your team tried to come to consensus, on a scale of 1-5 ( 1=None/Very Little and 5=A Lot/Very Much)

-- to what extent was there tension between you and other team members? _____

-- to what extent did you and the others agree? _____

-- to what extent did you feel that you and the other team members were equals? _____

What are your overall comments about Game 1:

________________________________________________________________________

Game 2: Text chat, no shared visualization (ALREADY PLAYED)

On a scale of 1-5 (1=Not At All and 5=Very Much), was this game fun? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your team’s shared picture of where the SCUDs were at the end of the game? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to visualize where the SCUDs were on the game board? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to communicate with your teammates? ___

Did your team try to come to consensus on decisions on sensor placement?

(Yes/No)___________________________________________________

Did your team try to come to consensus on decisions on launcher locations?

(Yes/No)__________________________________________________

If your team tried to come to consensus, on a scale of 1-5 ( 1=None/Very Little and 5=A Lot/Very Much)

-- to what extent was there tension between you and other team members? _____

-- to what extent did you and the others agree? _____

-- to what extent did you feel that you and the other team members were equals? _____

What are your overall comments about Game 2:

________________________________________________________________________

Game 3: No comms, shared visualization

On a scale of 1-5 (1=Not At All and 5=Very Much), was this game fun? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your team’s shared picture of where the SCUDs were at the end of the game? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to visualize where the SCUDs were on the game board? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to communicate with your teammates? ____

Did your team try to come to consensus on decisions on sensor placement?

(Yes/No)_____________________________________________

Did your team try to come to consensus on decisions on launcher locations?

(Yes/No)_______________________________________________

If your team tried to come to consensus, on a scale of 1-5 ( 1=None/Very Little and 5=A Lot/Very Much)

-- to what extent was there tension between you and other team members? ____

-- to what extent did you and the others agree? ___

-- to what extent did you feel that you and the other team members were equals? ____

What are your overall comments about Game 3:

________________________________________________________________________

Game 4: Text chat, shared visualization

On a scale of 1-5 (1=Not At All and 5=Very Much), was this game fun? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your team’s shared picture of where the SCUDs were at the end of the game? ___

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to visualize where the SCUDs were on the game board? ___

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to communicate with your teammates? ____

Did your team try to come to consensus on decisions on sensor placement?

(Yes/No)________________________________________________

Did your team try to come to consensus on decisions on launcher locations?

(Yes/No)_______________________________________________

If your team tried to come to consensus, on a scale of 1-5 ( 1=None/Very Little and 5=A Lot/Very Much)

-- to what extent was there tension between you and other team members? ___

-- to what extent did you and the others agree? ____

-- to what extent did you feel that you and the other team members were equals? ____

What are your overall comments about Game 4:

________________________________________________________________________

Game 5: No comms, no shared visualization

On a scale of 1-5 (1=Not At All and 5=Very Much), was this game fun? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your team’s shared picture of where the SCUDs were at the end of the game? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to visualize where the SCUDs were on the game board? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to communicate with your teammates? ____

Did your team try to come to consensus on decisions on sensor placement?

(Yes/No)_______________________________________________

Did your team try to come to consensus on decisions on launcher locations?

(Yes/No)_________________________________________________

If your team tried to come to consensus, on a scale of 1-5 ( 1=None/Very Little and 5=A Lot/Very Much)

-- to what extent was there tension between you and other team members? ____

-- to what extent did you and the others agree? ____

-- to what extent did you feel that you and the other team members were equals? ____

What are your overall comments about Game 5:

________________________________________________________________________

Game 6: Voice, no shared visualization

On a scale of 1-5 (1=Not At All and 5=Very Much), was this game fun? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your team’s shared picture of where the SCUDs were at the end of the game? ___

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to visualize where the SCUDs were on the game board? ____

On a scale of 1-5 (1 = Poor and 5 = Excellent), how would you grade your ability to communicate with your teammates? ___

Did your team try to come to consensus on decisions on sensor placement?

(Yes/No)_____________________________

Did your team try to come to consensus on decisions on launcher locations?

(Yes/No)_______________________________

If your team tried to come to consensus, on a scale of 1-5 ( 1=None/Very Little and 5=A Lot/Very Much)

-- to what extent was there tension between you and other team members? _____

-- to what extent did you and the others agree? _____

-- to what extent did you feel that you and the other team members were equals? _____

What are your overall comments about Game 6:

________________________________________________________________________

General Comments:

________________________________________________________________________

________________________________________________________________________

________________________________________________________________________