Software Estimation Educational Games
COSMIC Chaire philanthropique ETS

Game D • An effort estimation range

Identification of an Effort Estimation Range based on NFR Requirements

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Recommended: read “How it works” first

Learning objective

Teach students how a set of non-functional requirements (NFRs) impacts the selection of an effort estimation range when using a linear regression model.

What the player sees

  • A graph showing project data and the linear regression model
  • The full red line representing the regression equation
  • The upper and lower dashed red lines representing equation ± MMRE
  • Ten NFR scenarios, each with different levels of non-functional requirements

MMRE = Mean Magnitude of Relative Error.

What the player does

  1. Open the next available NFR scenario.
  2. Assess how the NFR levels increase or decrease expected project effort.
  3. Select the most appropriate effort estimation range from the graph (data, regression equation and ±MMRE).
  4. Enter a number from 1 to 5 (one answer per scenario).

Each scenario is answered once and cannot be revisited in the game flow.

Answer options (enter a number from 1 to 5)

For each NFR scenario, the player answers the following question: “Among the five options below, which one would you choose to perform the effort estimation for this software project?”

1
Above +MMRE
The effort range above the +MMRE bound.
2
Equation to +MMRE
The effort range from the equation line up to +MMRE.
3
On the equation
Effort exactly on the equation line.
4
Equation to -MMRE
The effort range from the equation line down to -MMRE.
5
Below -MMRE
The effort range below the -MMRE bound.

Teaching notes

This game is useful to train students to reason about uncertainty and to understand how NFRs may shift effort estimates above or below a regression baseline.

Suggested use in class

  • Start with a short recap: regression line as baseline + ±MMRE as uncertainty bounds
  • Have students justify their choice (why option 1 vs 2 vs 3, etc.)
  • Compare answers across scenarios to highlight systematic NFR effects
  • Emphasize that the player selects a range, not a single-point estimate

What to evaluate

  • Consistency of reasoning across scenarios
  • Ability to link NFR intensity to effort shift direction
  • Understanding that estimates can be ranges, not single points

Downloads & documentation

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Questionnaire: game-d-questionnaire.html

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