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Table 3 Multilevel analysis of students’ self-regulation, learning situations, and emotional states

From: Emotional states during learning situations and students’ self-regulation: process-oriented analysis of person-situation interactions in the vocational classroom

Effect

Estimate

SE

p

95 % CI

LB

UB

Fixed effects

Intercept

.189

.106

.078

–.021

.400

Age

.142

.070

.047

.002

.281

Students’ self-regulationa [= 0]

–.338

.140

.018

–.617

–.059

Student centring—Teacher instruction (Sc–Ti)

.018

.026

.491

–.033

.070

Learning new contents—Repetition (Lnc–R)

.003

.024

.904

–.044

.050

Self-regulation ↓ × Sc–Tib

.036

.026

.159

–.014

.087

Self-regulation ↓ × Lnc–Rc

.023

.024

.327

–.023

.069

Self-regulation ↓ × Sc–Ti × Lnc–R

–.001

.022

.970

–.043

.042

Self-regulation ↑ × Sc–Ti × Lnc–R

.015

.023

.508

–.030

.060

Random effects

Random intercept variance (person)

.426

.066

<.001

.314

.577

Random intercept variance (situation)

.041

.007

<.001

.030

.056

Repeated measures effect

AR1 diagonal

.499

.011

<.001

.477

.521

–2LL (2-level model/null model)

9827.192/10,039.848

AIC (2-level model/null model)

9835.192/10,045.848

BIC (2-level model/null model)

9860.670/10,065.006

McFadden-Pseudo-R2

.021

Analysis of deviance (χ2-test)

Δ–2LL = 212.656, Δdf = 9, p < .001

  1. Depended variable Students’ emotional states
  2. aSelf-regulation ↓ = 0, self-regulation ↑ = 1, self-regulation ↑ [= 1] as reference
  3. b[Self-regulation ↑ × Sc–Ti] as reference
  4. c[Self-regulation ↑ × Lnc–R] as reference