Skip to main content

Advertisement

Table 3 Summary of the logistic regression analysis for academic achievement in physics

From: Assessing prior knowledge types as predictors of academic achievement in the introductory phase of biology and physics study programmes using logistic regression

  Model A Model B Model C Model D
Parameter B (SE) OR [95% CI] B (SE) OR [95% CI] B (SE) OR [95% CI] B (SE) OR [95% CI]
Intercept − 0.852 (0.312) 0.43 − 1.958 (0.581) 0.14 − 1.816 (0.540) 0.16 − 1.775 (0.530) 0.17
HS GPA 1.282 (0.365) 3.60*** [1.8, 7.4] 0.513 (0.534) 1.67 [0.6, 4.8] 0.477 (0.505) 1.61 [0.6, 4.3] − 0.450 (0.440) 1.77 [0.7, 4.6]
Knowledge of facts 0.704 (0.503) 2.02 [0.8, 5.4] 0.754 (0.496) 2.11 [0.8, 5.6]
Knowledge of meaning 1.035 (0.530) 2.82ǂ [1.0, 8.0] 1.232 (0.507) 3.43* [1.3, 9.3] 1.475 (0.477) 4.37** [1.7, 11.1]
Integration of knowledge 0.556 (0.521) 1.74 [0.6, 4.8]
Application of knowledge 1.259 (0.592) 3.52* [1.1, 11.2] 1.300 (0.576) 3.67* [1.2, 11.3] 1.553 (0.555) 4.73** [1.6, 14.0]
Correctly classified cases 71.2% 84.9 % 82.2 % 82.2 %
Nadelkerke’s R2 .287 .627 .615 .590
Chi-square Tests 17.29*** 45.15*** 43.98*** 41.55***
  1. Chi-square tests test the deviance of the fitted model against the null model. Not significant predictors were excluded in the following model. Dependent variable = academic achievement (1 = passed all subject-specific courses)
  2. OR odds ratio
  3. ǂp < .10
  4. *p < .05
  5. **p < .01
  6. ***p < .001