TABLE 3.
Multiple regression analyses for achievement goals as predictors of emotions.
| Model 1: Enjoyment | Model 2: Pride | Model 3: Anger | Model 4: Anxiety | Model 5: Shame | Model 6: Boredom | |
| Achievement goals | ||||||
| Learning approach | 0.11 (0.06) | 0.09 (0.07) | −0.18 (0.07) | 0.08 (0.07) | 0.05 (0.08) | −0.16 (0.07) |
| Learning avoidance | −0.05(0.06) | 0.01 (0.07) | 0.17 (0.06) | 0.05 (0.07) | −0.08(0.08) | 0.04 (0.07) |
| Task approach | 0.10 (0.06) | 0.06 (0.07) | −0.07(0.07) | −0.05(0.07) | −0.05(0.07) | −0.03(0.07) |
| Task avoidance | 0.04 (0.06) | 0.03 (0.08) | −0.05(0.07) | −0.07(0.06) | 0.04 (0.08) | −0.04(0.07) |
| Appearance approach | −0.07(0.06) | 0.13 (0.06) | 0.06 (0.06) | −0.02(0.07) | 0.02 (0.08) | −0.01(0.07) |
| Appearance avoidance | 0.05 (0.07) | 0.02 (0.07) | −0.09(0.08) | 0.21 (0.09) | 0.24 (0.10) | −0.06(0.09) |
| Normative approach | 0.01 (0.07) | 0.05 (0.06) | 0.04 (0.06) | 0.05 (0.06) | −0.07(0.07) | 0.03 (0.07) |
| Normative avoidance | 0.05 (0.08) | −0.07(0.08) | 0.03 (0.07) | −0.08(0.08) | −0.11(0.09) | −0.03(0.09) |
| Relational | 0.05 (0.05) | 0.04 (0.05) | −0.02(0.06) | 0.04 (0.05) | 0.13 (0.05) | 0.10 (0.05) |
| Work avoidance | −0.13 (0.06) | −0.02(0.06) | −0.08(0.06) | 0.03 (0.06) | 0.11 (0.06) | 0.15 (0.05) |
| Control variables | ||||||
| Age | 0.08 (0.08) | −0.01(0.06) | −0.06(0.07) | −0.20 (0.08) | −0.10(0.08) | −0.20 (0.07) |
| Full professor (1 = yes, 0 = no) | 0.05 (0.06) | 0.04 (0.06) | 0.10 (0.06) | 0.11 (0.07) | −0.02(0.07) | −0.07(0.07) |
| Ph.D. (1 = yes, 0 = no) | −0.03(0.07) | < 0.01(0.06) | 0.01 (0.06) | 0.14 (0.06) | 0.02 (0.07) | 0.05 (0.06) |
| Gender (1 = ♂, 2 = ♀) | 0.06 (0.05) | 0.03 (0.05) | −0.01(0.05) | 0.17 (0.05) | 0.04 (0.06) | −0.10 (0.05) |
| R2 | 0.09 | 0.06 | 0.05 | 0.15 | 0.10 | 0.17 |
Reported are the standardized regression coefficients with their standard errors in parentheses. Running the model without age, academic rank, and gender as controls yielded no significant differences in parameter estimates. Statistically significant coefficients (p < 0.05) are displayed in boldface. All models were fully saturated and yielded a perfect fit to the data.