Page 115 - Empowering pre-service teachers through inquiry - Lidewij van Katwijk
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                                Relationship among quality of inquiry, quality of teaching and perceptions toward inquiry
 Supervisors’ ratings of teaching are prone to be inaccurate and unreliable
(Praetorius, Pauli, Reusser, Rakoczy, & Klieme, 2014). Because these pre-service
teachers were assessed by supervising teachers of the school, who were not
specifically trained to assess teaching quality, a bias caused by confounding factors
(e.g., halo effects) could easily occur (Creemers, Kyriakides & Antoniou, 2012). For
example, the relationship (good or bad) between the supervising teacher and the pre-
service teacher could have influenced the assessment score. To avoid this bias and
increase reliability, we measured the teaching quality of 80 pre-service teachers in the
final internship with the validated International Comparative Analysis of Learning
and Teaching (ICALT) instrument (Van der Lans, Van de Grift & Van Veen, 2018).
The correlation between the ICALT scores and the assessment scores for the final
internship was significant (r = .334, p = .003; two-tailed; see Van Katwijk & Van der 5 Lans, 2016). We deemed this as a fair indication for the use of the assessment scores as
 measures of teaching quality for the complete sample of 650 students.
Quality of pre-service teacher inquiry
We measured the quality of pre-service teacher inquiry by the scores (between 5.5 and 10, as noted previously) on the pre-service teacher inquiry project, assessed by an inquiry report (N = 650). The assessment consists of three main aspects: (1) content (weight 60%), including problem analysis, theoretical framework, research question, research design, results, conclusions and discussion; (2) form (weight 20%), including structure, language, academic writing, use of correct APA style and layout; and (3) process (weight 20%), including description of the inquiry process, participation in inquiry team and reflection on professional development.
Data analysis
For the first research question, we used descriptive statistics, using SPSS 25 to determine the mean scores and standard deviations on the four scales of the questionnaire. Two researchers independently analysed the open-end question about the perceived most important learning outcome inductively. We compared the categories that emerged, discussed the few differences and came to consensus by applying previous research findings (Van Katwijk et al., 2019b). In 18 of the 194 cases, the pre-service teachers had mentioned two ‘most important learning outcomes’ instead of one. We decided to split those cases and use both expressions as most important learning outcomes. An independent third researcher analysed the answers once more, deductively with the determined categories. The interrater agreement was high, over 95% (Miles, Huberman & Saldana, 2014).

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