What are these games?
These games help students learn by doing. Players analyze scenarios, work with incomplete information, make explicit decisions, and receive feedback through structured scoring.
Teach and learn software estimation through interactive games.
A curated set of educational games , including questionnaires, manuals, and direct downloads, designed for courses in software project management.
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SimSE international community
Funding acknowledgement
What do students actually do?
- Perform early sizing and connect it to estimation decisions
- Reason about productivity and effort impact
- Revise estimates using observed project data
- Interpret uncertainty and model outputs
- Analyze risk and contingency choices
Datasets and statistical calculations are prepared externally (e.g., Website, Excel). The game captures decisions and evaluates outcomes.
How to use
Each game page provides an overview, a questionnaire, manuals, and direct downloads. Use the games in lectures, labs, or as individual or team assignments.
In-class activity
Short guided sessions to introduce estimation concepts.
Lab session
Hands-on practice with scenarios and decision points.
Assignment
Questionnaires support graded evaluation and reflection.
Self-paced
Students explore independently with immediate feedback.
Available games
Click a card to open the game page. Each game includes its questionnaire, manuals, resources, and downloads.
Game A
Estimation planning: staff selection & sequence of statistical steps
Teach students how to plan a software estimation effort by selecting team members with the appropriate skills in software sizing and linear regression statistics, and by ordering the correct analytical steps to build a valid size-effort model from historical project data.
Estimation planningLinear regressionTeam skills
Game B
Early sizing of the software requirements & management issues
Teach students how staffing decisions in estimation influence early sizing performance in terms of measurement accuracy, speed, and sizing budget management. The game demonstrates the combined effect of measurer profiles, expertise levels, documentation quality, and tool usage on the outcome of an early software sizing effort.
Early sizingCOSMICSizing budget management
Game C
Evaluation of size-effort statistical models – linear regression
Teach students how to interpret the statistical parameters of a linear regression model (sample size, R², outliers, and MMRE) across 10 different ISBSG data subsets, by answering four structured questions per scenario.
Statistical modelISBSG dataRegression
Game D
Identification of an Effort Estimation Range based on NFR Requirements
Teach students how a set of non-functional requirements (NFRs) impacts the selection of an effort estimation range when using a linear regression model.
NFR
Effort Estimation
Regression Model
Game E
Adjustment to the estimation range using a set of 10 project constraints
Teach students how to adjust a previously established effort estimation range by incorporating project contraints as additional independent variables, building upon initial estimates derived from functional size and non-functional requirements.
AdjustmentProject ConstraintsCOCOMO
Game F
Using information on risks and opportunities to select a budget and a contingency reserve
Applies risk thinking to estimation decisions: contingency, impacts, and rational choices under uncertainty.
ContingencyImpactsDecisions