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                                Pre-service teacher inquiry; an international comparison
 we applied a “value” code when direct quotes explicitly mentioned value, as well as to answers to the question “What do you think about pre-service teacher research?” or perceptions not directly related to the purpose or learning outcome, such as the following excerpt: “It was a way to connect on a professional level and she [the mentor teacher] was able to see what kind of a learner I am and what I am interested in” (PST AU1).
For the cross-case analysis, we used a replication strategy (Yin, 2014), beginning
with two Dutch cases from the same institute; one case with pre-service teachers
and one with teacher educators. Then we examined the other six cases to look for 4 similar and different patterns in perceptions of purposes, learner outcomes, and
value of pre-service teacher research, ultimately ending with a list of codes related to
one or more of the cases. In the second cycle, we refined our pattern codes by using
the code co-occurrence tool and various codes from primary document tables in
Atlas.ti (Friese, 2014) to look for similarities and differences and address the research
questions. Subsequently, to connect our data with prior literature, we moved from an
inductive case-oriented approach to a more deductive, variable-oriented approach
(Miles et al., 2014), using the four aspects related to pre-service teacher research:
(1) research knowledge, (2) inquiry habit of mind, (3) applying research in practice,
and (4) conducting research. We analysed the qualitative data from the focus
groups and quantified them to a certain extent, to be able to “discern and to show
regularities or peculiarities in the qualitative data we might not otherwise see, or to
determine patterns or idiosyncrasy” (Sandelowski, 2009, p. 210). We calculated the
relative frequencies of the codes referring to purposes within the cases, to specify
the distribution of attention to various purposes of pre-service teacher research
in the focus groups. We acknowledge the limitations of these “quasi-statistics”
(Becker, 1990) but regard such quantitative information as a necessary complement
to the qualitative information gathered from the data (Maxwell, 2010). First, the
quantitative information about percentages of code frequencies increases internal generalizability and comparability between the focus groups with different numbers
of participants; second, with these quantitative data, we can identify and characterize
diverse perceptions in the groups/cases studied; and third, we can show that we were
not “cherry-picking our data for instances that support our interpretations” (Maxwell,
2010, p. 478). Finally, we analysed similarities across all cases and sought to explain the
differences, using quotes from the participants, the case contexts, and our theoretical

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