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Rasa Nedzinskait˙ e-Mači¯ unien˙ e and Antonios Kafa

                Table 2.2  Moderating Effect of escs on the Relation between Instructional
                         Leadership and Students’ Science Scores in pisa 2022
                Predictors            β (se)      t           ()           ()
                instlead        –. (.)  –.** [–., –.] [–., –.]
                escs             . (.)  .**  [., .]  [., .]
                Interaction      . (.)  .  [–., .]  [–., .]
                notes  95 confidence interval: (1) low limit, upper limit, (2) boot low limit, boot
                          2
                upper limit. R = 0.56, F =23.34**, N = 60. *Correlation is significant at the 0.05 level
                (2-tailed). **Correlation is significant at the 0.01 level (2-tailed).

                  Instructional leadership had a significant negative effect on science
                scores (β = –33.26, p = 0.01). Meanwhile, escs had a significant positive
                effect on science scores (β = 56.32, p < 0.001), suggesting that students
                from higher socioeconomic backgrounds perform better in science. The
                interaction effect between instructional leadership and escs was not
                statistically significant (β =9.96, p = 0.62), indicating that escs does
                notmoderatetherelationshipbetweeninstructional leadershipand sci-
                ence scores (see Figure 2.4).
                  The Bootstrap confidence intervals for instructional leadership ([–
                58.72, –15.10]) confirm that its negative impact on science achievement
                is robust, as the ci does not include zero. The interaction effect’s con-
                fidence interval ([–18.24, 52.83]) contains zero, reinforcing the conclu-
                sion that moderation is not significant. Therefore, Hypothesis 6 – escs
                moderates the relationship between instructional leadership and sci-
                ence achievement – is not supported.
                  The moderating role of escs in the relationship between School Au-
                tonomy (schauto) and science achievement was also examined (see
                Table 2.3).
                  The model explains 56 of the variance in science achievement (R 2
                = 0.56), indicating strong explanatory power. The overall model is sta-
                tistically significant F (3,56) = 23.67, p < 0.001), meaning the predictors
                (schauto, escs, and their interaction) contribute significantly to ex-



                                       instlead
                Figure 2.4                              –33.26**
                Moderating Effect                      56.32**
                of escs between          escs                    science
                Instructional
                Leadership                               9.96
                                    instlead × escs
                and Science Scores

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