Summary of "Uji N-Gain Score ➡️ Cara Mengitung N Gain dengan SPSS"

Main ideas / lessons conveyed

Purpose of N-gain score: To determine the effectiveness of a method or treatment.
Core concept: Compute N-gain using the difference between posttest and pretest scores relative to the maximum possible (ideal) improvement.
Formulas and parameters:
- N-gain is calculated as the normalized gain from pretest to posttest.
- The ideal score is treated as the maximum possible score, given as 100 in the example.
Categorization (by N-gain value):
- High if N-gain > 0.7
- Medium if 0.3 ≤ N-gain ≤ 0.7
- Low if N-gain < 0.3
Effectiveness interpretation (by percentage):
- Not effective if < 40%
- Less effective if 40–55%
- Quite effective if 56–75%
- Effective if > 76%
How to compute in SPSS (version 23): Use Transform → Compute Variable to create:
- posttest − pretest
- ideal score − pretest
- N-gain score
- N-gain percent
How to interpret results in SPSS:
- Use Analyze → Descriptive Statistics → Descriptives
- Interpret primarily the mean (average) of:
  - N-gain score (mean) for the category (high/medium/low)
  - N-gain percent (mean) for effectiveness level

N-gain = (posttest − pretest) / (ideal − pretest) Ideal score = maximum possible score (example uses 100)

Assuming the dataset already contains variables named pretest and posttest:

Menu: Transform → Compute Variable
Target Variable: posttest_minus_pretest (name described as “posttest minus pretest”)
Numeric Expression: posttest - pretest
Click OK

Menu: Transform → Compute Variable
Target Variable: ideal_minus_pretest (described as “ideal score minus pretest”)
Ideal score used: 100
Numeric Expression: 100 - pretest
Click OK

Menu: Analyze → Descriptive Statistics → Descriptives
Move the variables into the variable(s) box:
- N_gain_score
- N_gain_percent
Click OK
Interpret the mean values:
- Mean N-gain score:
  - 0.7 ⇒ High
- Mean N-gain percent:
  - 76% ⇒ Effective

Mean N-gain score: 0.7620
- Since 0.7620 > 0.7, category = High effectiveness
Mean N-gain percent: 76.2032
- Since 76.2032% > 76%, interpretation = Effective

Single speaker/instructor: The person presenting the tutorial (no name provided).
Tool/software referenced: IBM SPSS Statistics version 23 (used in the demonstration).
No other external sources or speakers mentioned.