Writing-to-learn in biology and mathematics teacher education: promoting students’ topic knowledge and insight

Abstract

In the present study, effects of Genre Writing instruction added with planning and revising activities (GWPR) are investigated in teacher education. This type of instruction was considered promising because it appeared to lead to positive effects on topic knowledge and insight in previous studies conducted in secondary education. Researchers’ expectation was that writing-to-learn activities by means of GWPR support teacher candidates in acquiring topic knowledge and insight into subject matter. Two studies were undertaken, one in biology and one in mathematics teacher education, each comprising a quasi-experiment and a think-aloud study. Both studies were embedded in regular courses. Researchers co-created writing-to-learn tasks with the teacher educators involved. Both experiments showed positive effects on learning. Results of the think-aloud studies provided evidence for specific indicators (students’ reflections) of the process of writing-to-learn, in which experimental teacher candidates differed from the control group. Finally, we discuss the impact of the results for the theory, follow-up studies and teaching practice.

Full text

Frontiers in Education 01 frontiersin.org
Writing-to-learn in biology and
mathematics teacher education:
promoting students’ topic
knowledge and insight
AartjeVan Dijk
1
*, AmosVanGelderen
1† and FolkertKuiken
2†
1 Research Centre for Urban Talent, Rotterdam University of Applied Sciences, Rotterdam, Netherlands,
2 Faculty of Humanities, Amsterdam Center for Language and Communication, University of
Amsterdam, Amsterdam, Netherlands
In the present study, eects of Genre Writing instruction added with planning
and revising activities (GWPR) are investigated in teacher education. This type
of instruction was considered promising because it appeared to lead to positive
eects on topic knowledge and insight in previous studies conducted in secondary
education. Researchers’ expectation was that writing-to-learn activities by means
of GWPR support teacher candidates in acquiring topic knowledge and insight
into subject matter. Two studies were undertaken, one in biology and one in
mathematics teacher education, each comprising a quasi-experiment and a
think-aloud study. Both studies were embedded in regular courses. Researchers
co-created writing-to-learn tasks with the teacher educators involved. Both
experiments showed positive eects on learning. Results of the think-aloud
studies provided evidence for specific indicators (students’ reflections) of the
process of writing-to-learn, in which experimental teacher candidates diered
from the control group. Finally, we discuss the impact of the results for the theory,
follow-up studies and teaching practice.
KEYWORDS
writing-to-learn, genre writing instruction in learning, teaching cognitive strategies,
reflection on own learning, co-creating a writing task
1. Introduction
Students in higher education oen have diculty understanding the contents of their
textbooks and their teacher educators’ explanations of subject matter (Hunter and Tse, 2013).
Consequently, they cannot acquire the topic knowledge and insight a course is aimed at.
Students’ unfamiliarity with discipline specic language in academic genres is seen as an
important cause of their diculties with learning (Hunter and Tse, 2013).
Several studies emphasize the importance of supporting students in acquiring the desired
topic knowledge and insight (Sampson and Phelps Walker, 2012; Hunter and Tse, 2013;
Finkenstaedt-Quinn etal., 2017). By topic knowledge wemean basic factual knowledge in the
context of academic courses. By insight wemean the ability to relate new concepts to students’
prior knowledge. Insight is viewed as the ultimate aim of academic courses, because it is the
manifestation of a higher order understanding of concepts (Boscolo and Carotti, 2003; Hand
etal., 2009; Klein and Rose, 2010; Kenney etal., 2014).
Teachers have dierent means at their disposal for providing support, for instance by
teaching task-oriented reading, taking into account students’ limited genre specic vocabulary
and grammar knowledge, or by stimulating students’ reection about subject matter. Another
OPEN ACCESS
EDITED BY
Cheryl J. Craig,
Texas A and M University, UnitedStates
REVIEWED BY
Abdullah Kaldırım,
Dumlupinar University, Türkiye
Jesse R. Sparks,
Educational Testing Service, UnitedStates
*CORRESPONDENCE
Aartje Van Dijk
a.c.van.dijk@hr.nl
†These authors share senior authorship
RECEIVED 09 November 2022
ACCEPTED 15 June 2023
PUBLISHED 07 July 2023
CITATION
Van Dijk A, Van Gelderen A and Kuiken F (2023)
Writing-to-learn in biology and mathematics
teacher education: promoting students’ topic
knowledge and insight.
Front. Educ. 8:1094156.
doi: 10.3389/feduc.2023.1094156
COPYRIGHT
© 2023 Van Dijk, Van Gelderen and Kuiken.
This is an open-access article distributed under
the terms of the Creative Commons Attribution
License (CC BY). The use, distribution or
reproduction in other forums is permitted,
provided the original author(s) and the
copyright owner(s) are credited and that the
original publication in this journal is cited, in
accordance with accepted academic practice.
No use, distribution or reproduction is
permitted which does not comply with these
terms.
TYPE Original Research
PUBLISHED 07 July 2023
DOI 10.3389/feduc.2023.1094156

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 02 frontiersin.org
way of supporting students is using writing as a tool for learning. is
means, that students carry out writing tasks that are intended to
stimulate reection on their writing resulting in new topic knowledge
and insight, better known as writing-to-learn (Bereiter and
Scardamalia, 1987; Galbraith, 2009). Examples of writing-to-learn
tasks are writing a learning journal for reection on subject matter or
writing about discipline specic concepts adapted to a lay audience.
Writing is considered an important medium for learning, because
externalizing reection in a written text enables writers to retain their
thoughts and allows them to reread and develop their ideas further
(Nückles etal., 2009). is may lead to new topic knowledge and
insight into disciplinary concepts (Emig, 1977; Klein and Boscolo,
2016; Graham etal., 2020).
e present study aims in the rst place at the co-construction of
instructional materials and assessment of the eects of a method for
writing-to-learn directed at students in higher education. e method
is based upon previous research in instruction on writing-to-learn. A
second aim is nding characteristics of the process of writing-to-learn
for a better understanding of how it operates.
1.1. Research into instruction in
writing-to-learn
Although writing-to-learn has been studied for several decades
and has shown positive eects on learning, it is not much used by
teachers (Klein and Boscolo, 2016). One oen-mentioned reason is
that many teachers do not know how to implement writing-to-learn
in their curriculum (Akkus and Hand, 2011; Eaton and Wade, 2014;
Kenney etal., 2014). Research into promising approaches for writing-
to-learn has given ground for recommendations for teaching practice.
Below, wegive a brief overview.
In the rst meta-analysis on writing-to-learn carried out (48
studies), Bangert-Drowns etal. (2004) concluded that in most studies
involved, writing was not accompanied by specic instruction directed
at writing-to-learn and did not result in signicant learning outcomes.
However, they found a minority of studies in which instruction in
metacognitive writing strategies was provided, which led to positive
results. Bangert-Drowns etal. (2004) speculated that instruction in
cognitive and metacognitive writing strategies is promising for future
research into eects of writing-to-learn, because these types of
instruction stimulate reection on writing products, which may lead
to learning of course contents. Cognitive writing strategies are
understood as organizing strategies, such as goal setting, selecting and
structuring contents (Berthold etal., 2007). Metacognitive writing
strategies are understood as strategies for monitoring own task
performance and evaluating texts (reviewing and revising) (Berthold
etal., 2007).
In their meta-analysis of 56 experiments including 19 studies
examined by Bangert-Drowns etal. (2004), Graham etal. (2020)
analyzed eects of writing-to-learn activities on learning in science,
social studies and mathematics in grades 1–12. ey found a positive
eect with an average eect size of 0.30 (which was larger than the
ndings of Bangert-Drowns etal. (2004), who found an average eect
size of.17). However, there was a wide variability in eect sizes found,
ranging from 1.67 to −0.74. Eighteen percent of the experiments
showed negative eects. e authors could not explain this variability
with any of a large group of variables, such as the type and features of
activities and instruction (including the use of cognitive and
metacognitive strategies), study characteristics, discipline (science,
social studies, or math), grade, duration et cetera. Moderation analyses
using each of these variables showed no signicant results. e authors
concluded that the descriptions of most studies were not suciently
detailed to determine which of the contextual and instructional factors
were actually involved, for instance the details of writing tasks used,
or the type of thinking operations instruction was meant to provoke
(directed at topic knowledge or insight). erefore, Graham etal.
(2020) call for much more detailed descriptions of the contextual and
instructional features of writing-to-learn interventions in
future studies.
Miller etal. (2018) conducted an inductive, systematic literature
review of 43 studies, embedded in regular courses in grades 6–12in
science, social studies and mathematics. ey investigated the state of
research on the use of writing-to-learn tasks in content areas by
focusing on eects of instruction on learning. e researchers
distinguished explicit instruction, inquiry-based instruction of
cognitive and metacognitive strategies, and instruction of self-
reection. Explicit instruction can beprovided by means of a model
or a checklist, or by directly instructing the planning of a writing task.
Inquiry-based instruction stimulates students to nd out how to use
cognitive and metacognitive strategies without guidance by the
teacher. Instruction in self-reection entails journaling requiring
students’ reection on their own learning. Miller et al. (2018)
concluded that both explicit and inquiry-based instruction of
cognitive and metacognitive strategies as well as instruction in self-
reection can beeective in stimulating learning by writing. Overall,
in 46.5% of the reviewed studies, instruction of metacognitive and
cognitive strategies, and self-reection clearly promoted learning.
Van Dijk etal. (2022) reviewed 43 studies (from grade 5 to higher
education) investigating which types of instruction in cognitive and
metacognitive strategies lead to topic knowledge and insight. In this
study, four types of instruction for writing-to-learn were
discriminated. e rst three are based on Klein’s (1999) hypotheses
about the nature of cognitive operations involved in writing-to-learn.
e fourth type emerged from a number of studies. e rst type
called Forward Search, stimulates the use of metacognitive strategies
for reection on contents of a dra. e second type called Backward
Search, requires the use of cognitive as well as metacognitive strategies.
Cognitive strategies are directed at setting goals and planning text
contents, and metacognitive strategies are directed at revising a dra
referring to a previously made planning. e third type was called
Genre Writing consisting of the provision of genre knowledge added
with cognitive and/or metacognitive strategies for planning and
revision. e fourth type was called Planning Only and consists of
cognitive strategies for planning. e review found positive eects on
topic knowledge and insight for all four types in 62% of experimental
comparisons on average. e most empirical support, given the
number of studies, was found for Genre Writing supported with
additional instruction in planning and revision.
Other studies point at elements of instruction that may enlarge
eects of strategy-instruction: the intended audience and genre
knowledge. Prain (2006) suggested requiring students to write for a
lay audience (an audience unfamiliar with the topic). Presumably, this
urges students to reect on formulations matching their audience’s
knowledge, leading to a critical review of their insights. Prain’s (2006)
suggestion was tested in various studies (Hand etal., 2004; Hohenshell

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 03 frontiersin.org
and Hand, 2006; Hand etal., 2007; Finkenstaedt-Quinn etal., 2017)
showing positive results. Newell (1984) emphasized the role of genre
knowledge for writing-to-learn. If students have knowledge of the
requirements of the specic genre, they are supposed to write in, they
may beable to recognize relations between concepts they were not
aware of previously (Newell, 1984). Klein and Kirkpatrick (2010) and
Klein and Samuels (2010) conrmed Newell’s (1984) view on the role
of genre knowledge by showing that the eect of genre writing
instruction on learning may depend on students’ knowledge of the
genre. Klein and Boscolo (2016) noted that genre knowledge may bea
prerequisite for writing-to-learn.
Although most empirical studies mentioned above provide
evidence for positive eects of instruction in genre knowledge,
metacognitive and cognitive strategies, and writing for a lay audience
on learning, evidence is still inconclusive, given that for each type of
instruction null results of experimental comparisons are quite
frequently encountered (Miller etal., 2018: 53.5%, Graham etal., 2020:
19%; Van Dijk etal., 2022: 38%).
1.2. Promising elements of instruction in
writing-to-learn
In this study, the evidence that the elements genre knowledge,
planning and revising (cognitive and metacognitive strategies) and a
lay audience provide positive eects on learning, is followed as a lead.
e combination of these elements is what wecall “Genre Writing
instruction added with Planning and Revising” (GWPR). Studies
using this combination of instructional elements in secondary
education were among the most successful studies (Van Dijk etal.,
2022). is study sets out to nd more conclusive evidence for the
eects of GWPR on disciplinary topic knowledge and insight of
students in higher education.
In the rst place, GWPR instructs genre knowledge in a
preparatory activity (before the actual execution of a writing
assignment) by means of a model text of the genre at stake. Genre
knowledge is dened as knowledge of the genre’s rhetorical goal and
prevalent conceptual relations between text elements to arrive at this
goal (Halliday and Martin, 1993). For instance, the rhetorical goal of
explanatory texts is clarifying a topic, and a prevalent conceptual
relation, for instance “comparing”, shows the disciplinary use of the
genre (e.g., the comparison between ecological niches of dierent
species in biology, or the comparison of numerical equations in
mathematics). Analyzing a model text can make students aware of
these characteristics. e model text should therefore exemplify
various linguistic realizations of the conceptual relation, for instance
the relation “comparing” is realized as “… diers from…”, “more
recently …” or “… is larger than…” (dependent on the specic
disciplinary context). If students are made aware of how the conceptual
relation “comparing” in an explanatory text can berealized, they can
make comparisons in their own writing and reect on the results,
which may lead to new insights into the meaning of these comparisons
(Langer and Applebee, 1987). In addition, in GWPR, the model text
is written in such a way that it is comprehensible to a lay audience.
erefore, no disciplinary jargon is used.
In the second place, planning consists of the cognitive strategies
selecting and organizing contents in preparation of writing. In our
view of GWPR, instruction on planning entails that students can use
pairwise brainstorming aimed at the selection of knowledge elements
from memory and textbook that they nd relevant. For instance, in
case of a text about similarities and dierences between old and
contemporary views, students will have to decide which elements of
these views are relevant for such a comparison. Students are instructed
to represent their selection by means of keywords and to organize
them in a mind map, such that the structure of their dra becomes
visible. ey thereby have to consider the conceptual relations in view
of comprehensibility for their audience and may therefore decide to
include an introduction or a conclusion. While writing their dras
(individually) they are supposed to consult their planning as well as
the model text exemplifying the formulation of central
conceptual relations.
In the third place, in GWPR revising consists of the use of
metacognitive strategies for reformulation based on peer feedback.
Students are instructed to review their peer’s dra focusing on the
conceptual structure as realized in the text and on its comprehensibility
for a lay audience. For instance, if the conceptual structure is based on
making comparisons, peers check the clarity and accuracy of the
comparisons made, and whether they are in accordance with the
writing assignment. In this process, students reect on their peer’s
representation of the conceptual relations in language from the
viewpoint of the intended (lay) audience. Students use their peer’s
feedback for revising their dras individually. In doing so, they have
to reect on their original insights in the conceptual relations and
their original formulation, which may lead to new insights (Bereiter
and Scardamalia, 1987).
In the fourth place, writing for a lay audience is used as intrinsic
in the planning and revising phases of GWPR instruction.
Additionally, a lay audience is an important condition for nding
appropriate sources for model texts. It is dened as an audience that
is not familiar with the disciplinary contents of the course. It may
consist of younger students than the writers or of a general audience.
When planning and revising a text for a lay audience, writers cannot
copy disciplinary jargon from their textbooks. Students therefore must
reect on alternative wordings based on every day or simplied
language. is translation process may lead to new insights about the
conceptual relations at stake (Prain, 2006).
us, GWPR instruction including genre knowledge, a lay
audience, cognitive and metacognitive strategies for planning and
revision necessitates students to reect critically on their original
understanding, stimulating their learning of new topic knowledge and
insights. Additionally, GWPR supports students in understanding
conceptual relations in texts of their academic discipline.
1.3. The process of writing-to-learn
In writing-to-learn research, the cognitive processes involved in
learning while writing are scarcely investigated. erefore, it is not
clear how these processes can beobserved, what they look like and
what are dierences between the processes of students who are
learning while writing and those who are not. Two theories about the
process of writing-to-learn have been proposed in the past decades
and have been used as explanations for results found in empirical
studies directed at newly learned topic knowledge and/or insights.
First, Bereiter and Scardamalia (1987) discriminated a writing
process typical for experienced writers. ey described it as a

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 04 frontiersin.org
recursory process taking place in reviewing and revising the content,
while reecting on the goals. eir theory is that writers seek to
reconcile contents and rhetorical goals, and therefore adjust their text
several times on rhetorical and content aspects. ey call this iterative
process knowledge transformation, because pre-existing knowledge is
transformed into new knowledge during writing.
e second theory is the dual process theory proposed by
Galbraith (2009). is theory distinguishes a knowledge retrieval
process and a knowledge constituting process. Writers use their
knowledge retrieval system, in which explicit knowledge is stored, for
retrieving content taking into account rhetorical goals. While writing,
they use their knowledge constituting system in order to make
connections between concepts, some of which may be new
connections the writer was not aware of previously (implicit
knowledge). ese new connections lead to new insights. e
constitution of relations is a cyclic process in which writers alternately
revise their text and refer to their knowledge constituting system. Both
theories state that learning by writing takes place in a cyclic process
entailing reection on content and rhetorical goals interactively
(Klein, 2004).
Testing of these theories took place in various ways. Bereiter and
Scardamalia (1987) provided planning instruction for students in
grade 6 for writing an opinion essay and an exposition. ey aimed at
investigating how to instruct planning activities such that these lead
to reection. Experimental students were provided with cue cards for
planning in a series of 38 50-min lessons (divided over 19 weeks).
Planning was modelled in several lessons by the researcher and
students, and strategy instruction was provided for reconciliation of
inconsistencies. Results were measured by means of a pre- and post-
test, each requiring students to write an opinion essay and an
exposition, without use of sources. Six students from the control group
and six from the experimental group performed the planning of these
four texts thinking aloud. e protocols were analyzed on the presence
of reective activities because reection was considered as indicating
knowledge transformation. e protocols of the experimental students
showed an increase in reective activities in the post-test, whereas
(business as usual) control students showed a decrease. e dierence
between the two conditions on the post-test was signicant, in favor
of the experimental students. is is considered as evidence that
experimental students progressed in transforming their knowledge
during the planning of their texts in comparison to the control group.
Galbraith (2009) tested his dual process theory by comparing two
types of writers (high self-monitors and low self-monitors) while
writing essays, and measured writers’ learning (that is, topic
knowledge and insight) aerwards. High and low self-monitors dier
in the way they operate when writing, well-considered (high self-
monitors) or intuitively (low self-monitors). High self-monitors
appeared to show larger eects of writing on learning than low self-
monitors, when making notes before writing, whereas low self-
monitors showed larger eects on learning, when being assigned to
write a text without any preparation. Galbraith considered the latter
results as evidence for the existence of knowledge constituting.
Because of their disposition, low self-monitors enter this process
spontaneously without being directly aware of acquiring
new knowledge.
Contrary to Bereiter and Scardamalia (1987), Galbraith (2009) did
not measure the processes involved in writing-to-learn directly.
However, in an experimental study, Baaijen and Galbraith (2018) used
keystroke logging for measuring 78 university students’ writing
processes as described in the dual process theory. Change in insight
was measured by comparing students’ ratings of their insight just
before and just aer writing. Students’ revision of text appeared to
berelated to increased insight.
Based on the theory of Bereiter and Scardamalia (1987) and an
early version of Galbraith’s (1992, 1999) th eor y, Klein (2004) aimed to
identify writing-to-learn processes by conducting an exploratory
think-aloud study with 56 university students. Students performed a
science experiment. ereaer, they explained its outcome. en, they
wrote a note (journal type) about how they arrived at their conclusion,
while thinking aloud. Finally, they explained the outcome again.
Change in insight was measured by comparing students’ explanations
before and aer writing. A regression analysis provided evidence that
students’ reection on goal setting, organizing and generating
(planning) as well as reection on reviewing and revising while
writing promoted insight. us, whereas Bereiter and Scardamalia
(1987) found evidence for reection in planning, and Baaijen and
Galbraith (2018) in reviewing and revising, Klein (2004) found
evidence in planning as well as in rereading and revising contents.
From the above, it follows that reective processes mediating
between rhetorical aspects and text contents, as proposed by Bereiter
and Scardamalia (1987) as well as Galbraith (2009) are promising
candidates for writing-to-learn. In the think-aloud parts of the present
studies, indicators of such reective processes are more specically
dened. ese indicators entail reective activities (cognitive and
metacognitive) performed during goal setting, organizing, generating,
rereading, and revising.
Analysis of indicators of reective processes involved in writing-
to-learn can provide additional evidence for eects of GWPR on
learning. By comparing verbalized writing processes of students from
an experimental and a control group, wemay nd support for the
expectation that GWPR stimulates reective writing, which may lead
to learning.
1.4. The present study
is study investigates whether GWPR instruction has eect on
the learning of topic knowledge and insight in two widely diering
disciplines in teacher education. Additionally, it investigates whether
indicators of the writing-to-learn process can be identied by
comparing think-aloud protocols of experimental and control teacher
candidates at the end of the intervention. Teacher education is an
interesting context, because there are few empirical studies directed at
the eects of writing-to-learn instruction in that context (Van Dijk
etal., 2022). In addition, it was a practical choice, because the rst
author is a teacher educator at the university involved and therefore
well informed of organizational and personal issues that have to
betaken into account.
e study was situated in biology (study 1) and mathematics
(study 2) teacher education. is allowed us to compare results from
two widely dierent disciplines regarding the role that writing plays
in educational practice. In biology, writing is a relatively frequent
activity (e.g., in lab reports), whereas writing in mathematics rarely
occurs (Veel, 1999). e interventions were embedded in regular
courses, as Miller etal. (2018) suggested. As Hunter and Tse (2013)
suggested, the study was carried out in cooperation with the biology

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 05 frontiersin.org
and mathematics teacher educators for organizing, composing, and
embedding the intervention in their regular courses.
Apart from an experimental study directed at eects of GWPR, a
think-aloud part was included in each study. e addition of a process
analysis to the eect study oers the opportunity to investigate
whether the outcomes of the experiment and think-aloud part
complement each other. Our process analysis is intended to nd
empirical support for previous ndings that dierent sorts of
(cognitive and metacognitive) reective activities indicate writing-to-
learn (Bereiter and Scardamalia, 1987; Klein, 2004; Baaijen and
Galbraith, 2018).
We formulated the following two research questions:
1. Does GWPR instruction lead to more topic knowledge and
insight in the context of biology and mathematics teacher
education, in comparison to a control group receiving business
as usual lessons?
2. Does GWPR instruction lead to observable dierences in
processes of writing-to-learn between experimental and
control teacher candidates?
2. Study 1: writing-to-learn in biology
teacher-training
2.1. Materials and methods
2.1.1. Participants
e study took place in a third-year biology teacher education
course at a university. At the start, 53 teacher candidates participated.
However, 15 teacher candidates did not perform the pre-test or post-
test and were therefore excluded. Reasons for dropping out were
illness, study break o, and moving. Consequently, 38 teacher
candidates were le for analysis, 20in the control group and 18in the
experimental condition. Table1 presents age, gender, mother tongue,
and prior education. e latter was a high school degree for 28
students, whereas 10 students had followed higher education prior to
entering biology teacher education.
For the analysis of the process of writing-to-learn, 12 teacher
candidates were randomly selected from the 38 teacher candidates as
participants of a think-aloud study. Six teacher candidates belonged
to the control group and six to the experimental condition. Table2
shows characteristics of the 12 participants.
One biology teacher educator was involved in the study. e
teacher educator had 15 years of experience in higher education and
was the regular teacher educator for both the control and the
experimental group. Due to personal circumstances, hetaught the
control group in the rst four lessons only. A biology colleague
replaced him during the remaining four lessons in the control group.
2.1.2. Design
We used a quasi-experimental, post-test-only design, comparing
a control group with an experimental group. e dependent variables
were topic knowledge and insight into biology subject matter taught.
Prior knowledge of biology and vocabulary knowledge were used as
covariates. e control group received the regular biology lessons
(business as usual), while the experimental group received the lessons
including writing-to-learn tasks. e two groups received their lessons
in two consecutive academic years, respectively 2011–2012 for the
control group and 2012–2013 for the experimental group. In the third
academic year of teacher education, only one class received lessons.
is was the reason why we chose to conduct the study in two
consecutive academic years. Otherwise the sample of participants
would have been too small.
Observations of the control group lessons were organized in order
to get acquainted with the objectives and structure of the regular
course and for designing the experimental course, specically how to
embed writing-to-learn tasks in the lessons.
For analyzing the process of writing-to-learn, a think-aloud
multiple case study was carried out with six experimental and six
control teacher candidates. Utterances were coded and systematically
analyzed in order to investigate dierences between the (reective)
writing processes of experimental and control teacher candidates.
2.1.3. Treatment
e experiment took place in a course aimed at the history of
biology, and scientists’ contributions to biology. Observations of the
lessons for the control group were carried out by the rst author to
describe the proceedings in the business as usual condition and to
prepare replacing parts of the business as usual lessons with the
writing tasks needed in the experimental condition. In preparation of
each lesson in the control group, teacher candidates had to study one
or two chapters from the textbook Zeiss (1999) and answer open-
ended questions about the contents. A pair of teacher candidates
additionally prepared a presentation about next week’s topic including
hands-on activities for their classmates. e lessons consisted of
discussing teacher candidates’ questions about subject matter, and
their answers on the open-ended questions. In the nal part of each
lesson, the two teacher candidates presented next week’s topic.
In preparation of the intervention, the biology teacher educator
and the rst author cooperated in designing model texts, writing tasks
as well as a teacher educator manual, combining their expertise in,
respectively, biology and writing-to-learn. ey discussed how to
embed the writing tasks in the regular lessons and which part of the
TABLE1 Characteristics of participants of biology teacher education.
Experimental group
(N= 18)
Control group
(N= 20)
Age M: 27 (SD: 9.94) M: 24 (SD: 3.73)
Gender Female: 11 Female: 10
Mother tongue Dutch: 16 Dutch: 19
Prior education High school: 15 High school: 13
TABLE2 Characteristics of selected participants of the think-aloud part
in biology teacher education.
Experimental group
(N= 6)
Control group
(N= 6)
Age M: 27 (SD: 9.22) M: 22 (SD: 1.51)
Gender Female: 4 Female: 2
Mother tongue Dutch: 5 Dutch: 6
Prior education High school: 6 High school: 3

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 06 frontiersin.org
lessons would bele out. Furthermore, the rst author proposed
topics from the biology textbook and sources for the model texts and
decided together with the teacher educator which would t best for
the writing tasks. e role of the teacher educator was to secure that
the contents of the writing tasks and the aims of the biology course
matched. erefore, heevaluated the instructions included in the
writing tasks, and whether the writing tasks focused on objectives of
the biology lessons. Additionally, the teacher educator reacted to the
suggestions in the teacher educator manual in order to decide whether
it was suciently clear how he should present the conceptual
relations involved.
e treatment in the experimental group is aimed at writing about
the chapters studied, based on the principles of GWPR. Analysis of
the assignments and texts used in the regular course showed that the
most used conceptual relations were comparison, sequence, and
cause-eect. us, writing tasks in the genre “explanation” would t
well with the objectives of the biology course (Rose, 2008). erefore,
wedeveloped model texts and writing tasks each focusing on one of
these three relations separately. Each of the three writing-to-learn
tasks required teacher candidates to write an explanation directed at
an audience of students in grade 9–10. is audience, with no
knowledge about the topics, was important, because it required a
thorough and simplied explanation from the teacher-candidates in
their writing. is requirement added to the ecological validity of the
writing tasks, because biology teacher education aims at teaching
students in secondary education.
GWPR instruction entails that each writing task is preceded by
an explanation of a model text. Model texts were derived from a
biology textbook directed at the audience (grades 9–10) and
rewritten to t our needs. e topics of each model text and
accessory writing task were related so that the teacher-candidates
could use the model text for their writing. However, in order to avoid
copy-paste strategies, the topics of the model text and the writing
task were not identical (e.g., “dierences between regular medicine
and alternative cure” for the model text, and “a dierence between
Hippocrates’ vision on medicine and the contemporary visions on
alternative cure” for the writing task).
ree model texts were composed, each containing examples of
one conceptual relation. A conceptual relation was expressed in
various ways (for instance the relation “comparing” was represented
by formulations such as “bigger as…”, “compared to…”, “more
important than…”). e purpose of this emphasis on dierent
linguistic realizations of conceptual relations was to provide teacher-
candidates with the instruments to consciously deal with the
conceptual relations at stake in the chapters studied. e teacher
candidates were expected to become aware of the relevance of these
relations for their understanding of studied texts.
e experimental participants were explicitly instructed in each
writing task to use the conceptual relation presented in the model text.
In this way, the experimental participants were stimulated to
transform their own thinking about the topic in order to accommodate
the knowledge gap between themselves and their younger audience.
We assume that such transformation is important for the teacher
candidates to become aware of gaps in their explanation that need to
berepaired in order to beunderstood by their readers (Prain, 2006).
Additionally, the writing tasks consisted of the following parts.
e rst was instruction on planning and entailed pairwise
brainstorming. In their planning, experimental teacher candidates had
to take the requirements into account posed by the given conceptual
relation and the intended audience. e second part was writing a
dra individually. e third part demanded pairs of teacher candidates
to comment on each other’s dra, while referring to the conceptual
relation at stake and the audience, and, if necessary, to ask for
clarication of each other’s feedback. Finally, teacher-candidates had
to revise their dras individually by using their peers’ feedback.
e biology teacher educator used the teacher educator manual
(which was fabricated in cooperation with him) for presenting the
model texts and the writing tasks to the teacher-candidates. It
contained suggestions for explaining the conceptual relation to the
teacher candidates, with the model text projected on a smart board
and selected linguistic realizations of the conceptual relation marked.
e teacher educator also would ask teacher candidates to look for
unmarked examples of the conceptual relation in the model text and
discuss these.
2.1.4. Instruments
2.1.4.1. Prior knowledge tests
In consultation with the teacher educator, the researchers
composed tests of prior knowledge about biology. e tests were based
on the textbook that had been used during the rst two academic
years comprising eight major biological themes varying from plants
to heredity (Reece etal., 2011). e tests consisted of eight multiple
choice (topic knowledge) and eight open-ended questions (insight),
each referring to one of the themes.
e rst author and the teacher educator coded teacher
candidates’ answers on the open-ended questions independently for a
sample of eight cases. e inter-rater reliability was 0.81 (Pearson
Correlation), which is considered acceptable. As can beexpected, the
homogeneity of the items measuring topic knowledge and insight was
low, given that the items represented quite dierent areas of biological
knowledge. Cronbach’s alpha for the eight items on topic knowledge
was 0.001 and for the eight items on insight 0.49. However, Cronbach’s
alpha provides an underestimation of test reliability (Boyle, 1991;
Sijtsma, 2009; Taber, 2018). e tests for prior knowledge might still
explain variance in our posttest measures. erefore, wedecided to
include both measures as covariates in our analysis.
2.1.4.2. Vocabulary test
A vocabulary test of 30 items derived from the Dutch version of
the Peabody picture vocabulary test (Dunn and Dunn, 2005) was
composed. is Dutch version is based on frequencies per one million
words. e words are ranked in 17 sets each aimed at a specic age
group. For the selection of words, weused four sets (nr. 14–17) aimed
at ages above 18. We selected 30 words of which the expected
prociency was between p = 0.36 and p = 0.86. Cronbach’s alpha of the
vocabulary test was 0.83, which is considered acceptable.
2.1.4.3. Topic knowledge and insight in the post-test
e post-test served as nal examination of the biology course
and was designed in consultation with the biology teacher educator.
It consisted of 30 multiple-choice questions (as a measure for topic
knowledge), and nine open-ended questions (as a measure for
insight). e multiple-choice questions as well as the open-ended
questions covered the six periods in history distinguished in teacher
candidates’ textbook. Nine of the multiple-choice items correlated

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 07 frontiersin.org
negatively with the remaining items, and therefore were removed.
Cronbach’s alpha of the remaining 21 items was 0.53.
One open-ended question was excluded from the post-test,
because of an unclear formulation. e researcher and the biology
teacher educator independently coded teacher candidates’ answers on
the remaining open-ended questions of the post-test for a sample of
eight cases. e inter-rater reliability was 0.88 (Pearson Correlation).
Cronbach’s alpha was 0.76 for eight open-ended questions. Although
the items for topic knowledge had a rather low reliability, wedecided
to include both parts of the test in our analysis.
2.1.4.4. Post-test writing task
A nal writing task was assigned to all teacher candidates. is
task required them to read two chapters (one mandatory and one free
choice) of Darwin’s e origin of species, to track down Darwin’s
statements, to look for observations these were derived from, and to
describe them Darwin (2010). e writing task was a regular
instrument used by the teacher educator for testing teacher candidates’
insight into Darwin’s work.
Although the format of this writing task was quite dierent from the
experimental writing-to-learn tasks used during the lessons, weused it in
the think-aloud study for examining the process of writing-to-learn. e
origin of species was not studied during the course. erefore, this writing
task barely measured understanding of course content. However, the task
required teacher candidates’ acquiring knowledge of subject matter by
writing. erefore, weconsidered it an appropriate measure for examining
the process of writing-to-learn.
2.1.5. Procedure
Table3 presents the lesson structure in the control group and in
the experimental group. e business-as-usual lesson structure was as
follows: posing questions about subject matter studied, discussion of
teacher candidates’ answers on the open-ended questions, and nally
a presentation prepared by a pair of teacher candidates. e
experiment comprised nine lessons, one lesson each week. e rst
lesson was used for administration of the prior knowledge and
vocabulary tests; lessons 2–7 were regular lessons; lesson 8 was used
for preparation of the post-test, the last lesson for the post-test and the
nal writing task.
In the experimental condition, the writing-to-learn tasks were
embedded in lessons 2–7 as follows. Each writing task was divided
into two parts in such a way that teacher candidates wrote a dra in
one lesson and revised their text in the next (see experimental
condition in Table3). For securing treatment delity, the rst author
observed whether the teacher educator carried out the lessons as
intended and as described in the teacher educator manual, in all
experimental lessons. No deviations were encountered.
For keeping time on task equal in the control and experimental
conditions, the part in which control teacher candidates were allowed
to pose questions about subject matter was le out in the experimental
condition and replaced by one part of the writing tasks.
In the academic year (2012–2013) aer the control teacher
candidates participated in the biology course, a change in timetabling
of the teacher education institute resulted in longer lesson duration for
the experimental lessons (150 instead of 100 min). A 15 min pause was
inserted, but still the duration of experimental lessons was longer
(some 35 min) than the control lessons. Unfortunately, wetherefore
cannot exclude that this dierence in time-on-task has inuenced the
results of the experiment.
ink aloud procedures can inform about the cognitive processes
involved in task execution of several sorts (Ericsson and Simon, 1993; Van
Someren etal., 1994). For the think-aloud experiment, the sample of 12
teacher candidates carried out their post-test writing task individually in
an empty classroom, in the presence of the rst author. She told them that
she was interested in how they addressed the writing task, and for this
reason, she asked them to think-aloud while writing. She provided an
instruction including a video clip of a student thinking aloud while
writing a paper. Teacher candidates wrote their texts on a computer while
using e origin of species and were free to use their self-made summaries
of the chapters as well. ey had to execute their task in 1 h maximum.
When teacher candidates kept silent for 10 s, the researcher encouraged
them to keep thinking aloud, and used prompts such as: say aloud what
youare thinking. e sessions were video recorded.
2.1.5.1. Coding teacher candidates’ transcribed utterances
Teacher candidates’ verbalizations were transcribed and
represented in protocols as separate utterances in case of verbal
behavior, and separate instances in case of non-verbal behavior (for
instance: “sighing”). An utterance was dened as a phrase containing
a meaningful element of information (Pander Maat, 1994).
e codes were based on Hayes and Flower’s (1980) writing model.
In total, 24 codes were used to describe teacher candidates’ writing and
thinking processes. For instance, the utterance “all claims and observations
have to beselected” was coded as “thinking about task approach”. In
addition, interruptions and utterances not focusing on the writing task
were coded and attributed to two categories: “interruptions” and “other
remarks”. Finally, the resulting coding scheme comprised 29 verbal and
non-verbal activities (see Appendix A).
By means of this coding scheme, the rst author and a trained
research-assistant coded the utterances, one code per utterance or per
instance. For determining inter-rater reliability, two protocols (one
from the experimental and one from the control group) were coded
by two independent raters. ere was agreement for 84% of all
utterances, a fair amount for our purposes. Dierences in coding were
resolved aer discussion.
TABLE3 Lesson structure in control and experimental condition of
biology teacher education.
Control group Experimental group
Business as
usual (lessons
2–7)
First draft
(lessons 2, 4, and
6)
Revision
(lessons 3, 5,
and 7)
• Posing questions
about subject
matter studied
• Class discussion about
students’ answers on
open-ended questions
• Presentation of next
week’s topic by a small
group of students
• Class discussion about
students’ answers on
open-ended questions
• Presentation of next
week’s topic by a small
group of students
• Writing-to-learn task,
part 1:explanation of
model text, planning
and writing a rst
dra (on laptops)
• Writing-to-learn
task, part 2: feedback
and writing nal text
• Class discussion
about students’
answers on open-
ended questions
• Presentation of next
week’s topic by a
small group of
students
Bold text indicates replacement of elements in the control condition by writing-to-learn
tasks.

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 08 frontiersin.org
Reective activities such as reviewing, revising, goal setting,
organizing and generating contents can beregarded as indicators of
writing-to-learn processes, according to previous studies (Bereiter and
Scardamalia, 1987; Klein, 2004; Baaijen and Galbraith, 2018). e
following specic codes from our list can beregarded as indicators for
these reective activities: (1) using knowledge about audience, (2)
thinking about content selection, (3) thinking about formulating, (4)
revising while formulating, (5) revising aer nishing an utterance,
(6) rereading own text, (7) rethinking task approach.
2.1.6. Data analysis
2.1.6.1. Prior knowledge, vocabulary test, and post-test
Two ANOVA’s were used for comparing prior knowledge (insight)
and vocabulary in the two conditions. By means of two ANCOVA’s,
teacher candidates’ post-test scores in the two conditions were compared.
e two dependent variables were the sums of teacher candidates’ scores
on topic knowledge and insight. e sums of teacher candidates’ scores
on prior knowledge (insight) and on vocabulary were used as covariates.
In all statistical tests, alpha level was 0.05.
2.1.6.2. Process analysis
For determining whether utterances that were considered as
indicators for writing-to-learn occurred in a larger frequency in the
experimental than in the control group, the means of each code per
condition were computed. Subsequently, the ratio of the mean
frequency of each code to the total number of utterances in a condition
was computed. Finally, eect-sizes (Cohen’s d) were used to evaluate
dierences between the two groups in proportioned mean frequencies.
As Cohen (1988) suggests, eect sizes below 0.20 are considered as no
eect, the range between 0.20 and 0.50 is considered as a small eect,
the range between 0.50 and 0.80 as a medium eect and ≥ 0.80 as a
large eect.
2.2. Results
Table4 presents the means and standard deviations for the four
variables involved, including the pre-tests for prior insight, prior topic
knowledge, and vocabulary, and the post-tests for insight and
topic knowledge.
2.2.1. Prior knowledge
An ANOVA showed that experimental and control students’
scores on prior insight did not dier signicantly, F(1,36) = 1.712,
p = 0.199, nor did the two groups dier signicantly on prior topic
knowledge, F(1,36) = 0.716, p = 0.198.
2.2.2. Vocabulary
An ANOVA showed no signicant dierences between the
experimental and control teacher candidates’ scores on pre-test
vocabulary: F(1,36) = 0.783, p = 0.382.
2.2.3. Post-tests
Two ANCOVA’s were conducted to compare students’ scores on
post-test insight and post-test topic knowledge in the experimental
and control condition. e scores on prior insight, prior topic
knowledge and on vocabulary served as covariates. e ANCOVA’s
showed that the covariate prior insight signicantly predicted the
scores on post-test insight, F(1,36) = 4. 479, p = 0.042, partial η
2
= 0.120
(medium), as well as on post-test topic knowledge, F(1,36) = 5.997,
p = 0.020, partia l η
2
= 0.154 (large). e covariate prior topic knowledge
did not predict dierences in post-test insight, F(1,36) = 0.218,
p = 0.643, nor in topic knowledge, F(1,36) = 3.393, p = 0.074. e
covariate vocabulary did not predict dierences in insight
F(1,36) = 0.073, p = 0.789, nor on topic knowledge: F(1,36) = 0.774,
p = 385. erefore, in the nal analysis, prior topic knowledge and
vocabulary were not included as covariates, while prior insight was.
is analysis shows that the scores of experimental and control
students on the post-tests of insight and topic knowledge diered
signicantly, F(1,36) = 15.023, p = 0.00, partial η
2
= 0.30 (large) for
insight, and F(1,36) = 13.43, p = 0.001, partial η2 = 0.28 (large) for topic
knowledge. It appears that the experimental students proted from the
intervention consisting of writing-to-learn with GWPR and
outperformed the control students in the business-as-usual condition.
2.2.3.1. Characteristics of writing-to-learn
In Table 5, the rst column comprises seven (of 29) codes
indicating teacher candidates’ verbal behavior. Wepredicted that these
codes indicate reection and therefore writing-to-learn (see
Appendix A for an overview of all 29 codes).
e remaining columns show the proportioned mean frequencies
and standard deviations of codes for the experimental and control
condition and eect size (Cohen’s d) as an estimation of the magnitude
of the dierence between the two groups.
We expected to nd dierences between the (proportioned) mean
frequencies, in favor of the experimental condition.
Table5 shows that dierences in three activities are relatively large
and in the expected direction: revising while formulating (e.g., he
needs a tree…an apple tree to beable to grow), d =0.49 (small eect),
revising aer nishing an utterance (e.g., this happens two … this is…
no no, this has two reasons), d = 0.75 (medium eect), and rereading
own text, d = 0.82 (large eect).
e other four hypothesized activities did not show larger
frequencies for experimental teacher candidates. e rst, using
knowledge about audience, was not applied by the teacher candidates
in both conditions. e second, thinking about content selection, was
TABLE4 Means and standard deviations for prior insight and topic
knowledge, vocabulary knowledge, and post-test scores on insight and
topic knowledge in biology teacher education.
N = 38 Experimental group
(N= 18)
Control group
(N= 20)
Variables Mean (SD) Mean (SD)
Prior insighta3.81 (1.66) 4.50 (1.61)
Prior topic knowledgeb3.83 (1.15) 4.35 (1.27)
Pre-test vocabularyc18.11 (0.40) 19.70 (4.61)
Post-test insightd5.28 (1.66) 3.40 (1.82)
Post-test topic
knowledgee
13.33 (2.64) 10.85 (2.41)
aeoretical maximum score: 15.5.
beoretical maximum score: 8.
ceoretical maximum score: 30.
deoretical maximum score: 13.5.
eeoretical maximum score: 21.

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 09 frontiersin.org
performed more oen by control teacher candidates (d = −0.27). e
third, thinking about formulating, was equally frequent in both
conditions just as the fourth activity, rethinking task approach.
us, it appeared that teacher candidates who had received
GWPR-instruction, showed three out of seven of the hypothesized
activities more oen than the control group.
3. Study 2: writing-to-learn in
mathematics teacher-training
3.1. Materials and methods
3.1.1. Participants
is study took place in a third-year mathematics teacher-training
course at a university. e control group started with 51 teacher
candidates and the experimental group with 38 teacher candidates.
However, 27 teacher candidates were excluded. Reasons were
enrolment for a resit of the nal test only (because of failure in the year
before), or attendance of just a few lectures (teacher candidates’
presence was not obligatory). In the analyses, 62 teacher candidates
were included, 36in the control group and 26in the experimental
condition. Table6 presents age, gender, mother tongue, and prior
education of the participants. Part of the participants (29) possessed a
high school degree only, but most of them (33) had followed higher
education prior to their enrolment in mathematics teacher education.
For answering the second research question concerning the
process of writing-to-learn, 15 mathematics teacher candidates were
randomly selected from the sample of 62 teacher candidates as
participants in the think-aloud study. Seven teacher candidates
belonged to the control group and eight to the experimental condition.
Table 7 presents their characteristics. One mathematics teacher
educator was involved in the study. He had 9 years’ experience in
teacher education and taught both conditions.
3.1.2. Design
e design of this study was the same as Study 1. e lessons and
writing tasks were about topics from mathematics (rows and limits).
Just as in Study 1, the experiment took place in two consecutive
academic years and started 1 year later than Study 1: the control group
in 2012–2013 and the experimental condition in 2013–2014. In the
third academic year of mathematics teacher education only one class
received education. is was the reason why wechose to conduct the
study in two consecutive academic years.
3.1.3. Treatment
e experiment took place in a course aimed at insight into
linking rows and recurrent relations, the use of web graphs for
computing these relations, and computing limits. As in study 1,
observations were carried out by the rst author in order to
describe the proceedings in the business as usual condition (the
control group) and to plan adaptations for the writing tasks in the
experimental condition. In the control group, teacher candidates
studied sections of a chapter from their textbook and completed a
number of accessory sums as their weekly homework. In the
TABLE5 Proportioned means, standard deviations, and eect sizes of indicators of writing-to-learn in experimental (N = 6) and control group (N = 6), in
biology teacher education.
Experimental Control Eect size
Codes Mean Std. deviation Mean Std. deviation Cohen’s d
Planning: generating
Using knowledge about audience 0.00 0.00 0.00 0.00 0.00
Planning: selecting
inking about content selection 0.03 0.04 0.04 0.04 −0.27
Formulating
inking about formulating 0.02 0.02 0.02 0.03 0.00
Revising while formulating 0.03 0.03 0.02 0.01 0.49
Revising aer nishing an utterance 0.03 0.04 0.01 0.01 0.75
Monitoring
Rereading own text 0.08 0.09 0.03 0.03 0.82
Rethinking task approach 0.01 0.01 0.01 0.01 0.00
TABLE6 Characteristics of the participants of mathematics teacher
education.
n = 62 Experimental group
(N = 26)
Control group
(N = 36)
Age M: 26 (SD: 9.64) M: 29 (SD: 11.25)
Gender Female: 14 Female: 18
Mother tongue Dutch: 22 Dutch: 33
Prior education High school: 10 High school 19
TABLE7 Characteristics of the selected participants for the think-aloud
study in mathematics teacher education.
n = 15 Experimental group
(N = 8)
Control group
(N = 7)
Age M: 20 (SD: 1.06) M: 21 (SD: 2.27)
Gender Female: 3 Female: 3
Mother tongue Dutch: 8 Dutch: 6
Prior education High school: 3 High school: 4

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 10 frontiersin.org
lessons, the teacher educator discussed the tasks performed at
home using a whiteboard. Furthermore, new topics
were introduced.
e intervention in the experimental group aimed at elaborating
on the homework and entailed the implementation of the principles
of GWPR. On the basis of the observations in the control group, it was
concluded that the genre explanation would t well with the aims of
the lessons. Analysis of the textbooks and assignments revealed that
the conceptual relations “condition”, “denition” and “sequence”
belonged to the dominant mathematical reasoning and explaining.
erefore, it was decided to make teacher candidates sensitive to these
conceptual relations in the experimental lessons.
e researcher and the teacher cooperated in developing two
writing tasks, two model texts and a teacher educator manual. e
writing tasks required teacher candidates to write an explanation
directed at an audience (grade 10 students) that they taught in their
apprenticeship. erefore, the model texts were based on textbooks
directed at grade 10. An example of a writing task is to write an
explanation of how time and web graphs can beused for visualizing
rows of numbers.
e topics of the model texts were closely related to the topics of
the accessory writing tasks (for instance, “limits” for the model text
and “computing limits” for the writing task). In the model texts, the
conceptual relations were presented in various wordings (for instance
for the relation sequencing: rst…, thereaer…). As usual in texts
about mathematics (Veel, 1999), the model texts comprised graphical
representations, such as a table or formulas in addition to the text.
e way instruction in writing-to-learn was applied, was the same
as in Study 1 (see Section 2.1.3).
3.1.4. Instruments
3.1.4.1. Prior knowledge
e researchers composed the tests of prior knowledge in
consultation with the teacher educator. e tests were based on textbooks
from Bos etal. (2007), which had been used during the rst academic year
in four courses directed at the mathematical eld “analysis” providing
prior knowledge for the course central in the present study. Five themes,
varying from function theory to dierential equation, had been taught.
e tests consisted of eight multiple choice (topic knowledge) and six
open-ended questions (insight), referring to the themes.
e rst author evaluated teacher candidates’ answers on the
open-ended questions in consultation with the teacher educator. Inter-
rater reliability was not computed, because of the unambiguity of the
answers, consisting of denitions of concepts required for three open-
ended questions and solutions for the remaining mathematical tasks.
As can beexpected, the homogeneity of the items measuring topic
knowledge and insight was low, given that the items represented
various themes from the eld of mathematics. For the eight items on
topic knowledge, Cronbach’s alpha indicated a large heterogeneity
(−0.118). e six items on insight were more homogeneous, as
indicated by a Cronbach’s alpha of 0.56. Despite the heterogeneity of
the tests, wedecided to include both measures in our analysis. As
mentioned in study 1, Cronbach’s alpha provides an underestimation
of test reliability (Boyle, 1991; Sijtsma, 2009; Taber, 2018). erefore,
the tests for prior knowledge might still explain variance in our
posttest measures and wedecided to include these tests as covariates
in our analysis.
3.1.4.2. Vocabulary
e vocabulary test consisting of 30 items described in Study 1,
was used in Study 2 as well. One item appeared to correlate negatively
with the rest. erefore, this was removed. Cronbach’s alpha of the test
consisting of 29 items was 0.86, which is considered acceptable.
3.1.4.3. Topic knowledge and insight in the post-test
e post-test consisted of four multiple-choice items and seven
open-ended questions. e homogeneity of the multiple-choice test
was 0.15 (Cronbach’s alpha). Weexplain this low homogeneity by the
small number of items in the test. Because of the low homogeneity, the
results were not included in the analyses.
e seven open-ended questions were mathematical tasks and
belonged to the usual nal test. Wele its evaluation with the teacher’s
expertise. Cronbach’s alpha for the open-ended questions was 0.81,
which is considered acceptable.
3.1.4.4. Post-test writing task
For examining the process of writing-to-learn in the think-aloud
study, a writing task was added to one of the mathematical tasks in the
post-test. First, students were required to carry out one mathematical
task. e subsequent writing task entailed the explanation (in language)
of the way they had calculated their outcome of the mathematical task
by focusing on the theorem they were instructed to apply. ey had to
write their explanation for an audience of grade 10 students.
3.1.5. Procedure
e lesson structure for the control group was as follows: the
teacher educator discussed teacher candidates’ questions about their
homework. ereaer, he lectured teacher candidates about new
theory, while representing this in mathematical symbols and schemes
on a whiteboard. e course lasted 9 weeks: eight lessons lasting
100 min each and a nal examination in the 9th week.
e writing-to-learn tasks for the experimental group were
embedded in four of eight lessons as follows. For each writing task
students wrote a dra in one lesson and a revised text in the next (see
lessons 4–7 in Table 8). For securing treatment delity, the rst
author observed whether the teacher educator carried out the lessons
as intended and as described in the teacher educator manual in all
experimental lessons. No deviations were encountered.
Time on task remained equal for both conditions by replacing
parts of the discussion of students’ questions and the introduction of
new theory by the writing tasks in the experimental lessons. e prior
knowledge and vocabulary tests were administered in the rst lesson
for both conditions. e second, third and eighth lesson were identical
for both conditions. e post-test including the post-test writing task
was administered in the ninth week of the course in both conditions.
For the think-aloud experiment, the sample of 15 students
completed the writing task thinking aloud. erefore, they completed
only the mathematics task during the post-test session and performed
the additional writing task immediately aer the post-test. Students
executed the writing task individually in an empty classroom, in the
presence of the rst author.
e researcher’s behavior was as described in Study 1. Students
wrote their texts on a computer thinking aloud, while having their
computation of the mathematics task at hand. ey had to perform
the writing task in maximally half an hour. e sessions were
video recorded.

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 11 frontiersin.org
3.1.5.1. Coding teacher candidates’ transcribed utterances
In Study 1, weexplained how the coding scheme was composed.
For Study 2, this scheme consisting of 29 codes was used as well (see
Appendix B). e rst author and a trained research-assistant coded
utterances (verbal behavior) and instances (nonverbal). Two complete
protocols (one for each condition) were coded independently by the
two raters. ere was agreement for 85% of all utterances and
instances. Weconsider this a sucient reliability of coding. Dierences
in coding were resolved aer discussion.
From these codes the same selection of (seven) codes as in Study
1 was made as indicating that the process of writing-to-learn is taking
place (cognitive and metacognitive processes).
3.1.6. Data analysis
3.1.6.1. Prior knowledge, vocabulary and post-test
To test for equivalency of groups, three ANOVA’s were used
comparing students’ prior topic knowledge, prior insight and
vocabulary in both conditions. To test for dierences between
students’ insight, we compared the post-test scores (open-ended
questions) of the two conditions by conducting an ANCOVA. Prior
topic knowledge, prior insight and vocabulary were used as covariates.
3.1.6.2. Process analysis
e analysis of the process of writing-to-learn was performed as
in Study 1 (see Section 2.1.6).
3.2. Results
Table 9 shows teacher candidates’ mean scores and standard
deviations on the pre-tests for prior insight, prior topic knowledge and
vocabulary, and the post-test for insight.
3.2.1. Prior knowledge
e dierences between students’ prior insight in the two
conditions were not signicant F(1,60) = 0.414, p = 0.522. e
dierences between students’ prior topic knowledge in the two
conditions were also not signicant F(1,60) = 0.406, p = 0.527.
3.2.2. Vocabulary
ere were no signicant dierences between teacher candidates’
vocabulary in the two conditions F(1,56) = 2.27, p= 0.137.
3.2.3. Post-test
e ANCOVA showed that the covariates prior insight, prior topic
knowledge and vocabulary did not signicantly predict the scores on
insight in the post-test, respectively F(1,56) = 1.829, p = 0.182,
F(1,56) = 0.147, p = 0.703 and F(1,56) = 3.216, p = 0.079. erefore, in
the nal analysis the covariates were not included. An ANOVA
showed that the scores on the post-test insight of control and
experimental students diered signicantly, F(1,60) = 5.829, p = 0.019,
partial η
2
= 0.089 (medium eect). Experimental students
outperformed control students in post-test insight scores.
3.2.4. The process of writing-to-learn
Table10 shows proportioned frequencies of the seven selected
indicators of writing-to-learn (reective activities) for both conditions.
e results for all 29 coded activities of the think-aloud study can
befound in Appendix B. Eect sizes are shown for estimating the
magnitude of dierences in proportioned frequencies between the
two conditions.
It appears that there are dierences in the expected direction for
four activities: using knowledge about audience (e.g., the utterance:
for students Iwould explain it by means of a stable population), d = 0.83
(large eect), thinking about content selection, d = 0.55 (medium
eect), revising while formulating, d = 0.38 (small eect) and rereading
own text, d = 1.27 (large eect).
e remaining three hypothesized indicators of writing-to-learn
did not show dierences between the conditions in favor of the
experimental teacher candidates. e activity thinking about
TABLE8 Lesson structure in control and experimental condition in
mathematics teacher education.
Control
group
Experimental
group
Experimental group
Lessons
2–7
Lessons 2, 3 Lessons 4, 6 Lessons 5, 7
Business as usual First draft Final text
• Discussion of students’ questions
about subject matter studied.
• Discussion of
students’ questions
about subject
matter studied
• Discussion of
students’
questions
about subject
matter studied
• Lecture about new theory. • Writing-to-learn
task, part
1:explanation of
model text,
planning and
writing a rst
dra (by hand)
• Writing-to-
learn task,
part 2:
feedback and
writing
nal dra
• Lecture about
new theory
• Lecture about
new theory
Lessons 1, 2, 3, 8, and 9 were identical for both groups. Bold text indicates replacement of
elements in the control condition by writing-to-learn tasks.
TABLE9 Means, standard deviations for prior insight and topic
knowledge, vocabulary knowledge and post-test scores on insight in
mathematics teacher education.
N = 62 Experimental group
(N= 26)
Control group
(N= 36)
Variables Mean (SD) Mean (SD)
Prior insighta4.27 (2.78) 3.85 (2.37)
Prior topic knowledgeb3.96 (1.18) 4.17 (1.30)
Pre-test vocabularyc,d 14.59 (4.57) 17.11 (6.97)
Post-test insighte28.35 (11.42) 21.22 (11.50)
aeoretical maximum score: 23.
beoretical maximum score: 8.
ceoretical maximum score: 29.
dFour students did not perform the test.
eeoretical maximum score: 49.

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 12 frontiersin.org
TABLE11 Overview of the results of the process analyses in Study 1 and
Study 2.
Indicators of writing-to-
learn
Study 1:
Biology
Cohen’s d
Study 2:
Mathematics
Cohen’s d
Planning
Using knowledge about audience Not used Large
inking about content selection Small negative
eect
Medium
Formulating
inking about formulating No eect Small negative
eect
Revising while formulating Small Small
Revising aer nishing an utterance Medium No eect
Monitoring
Rereading own text Large Large
Rethinking task approach No eect No eect
Not used, not used by both conditions.
formulating was slightly more frequent for the control teacher
candidates, d = −0.25. e second formulating activity revising aer
nishing an utterance was performed just as oen by both conditions,
d = 0.00. e monitoring activity rethinking task approach (e.g., I have
to do it in another way…) was equally frequent in both conditions as
well, d = 0.00. us, in these three cases, the hypothesis was
not conrmed.
4. Discussion
4.1. Conclusion
We expected that GWPR instruction comprising genre
knowledge, planning and revision, and writing for a lay audience,
creates favorable conditions for the process of writing-to-learn. ese
entail teacher candidates’ awareness of characteristic conceptual
relations in the genre at stake, teacher candidates’ reection during
generating and organizing text contents and during rereading and
revising the formulation of the conceptual relations, aiming at
comprehensibility of the text to a lay audience.
e results of both studies showed that GWPR instruction leads
to eects on insight and topic knowledge in biology teacher education
(with large eect sizes), and on insight in mathematics teacher
education (large eect size). Because the post-test for topic knowledge
on mathematics was not reliable, results for topic knowledge could not
beincluded in the analysis.
e aim of the two think-aloud studies was to identify indicators
of the writing-to-learn process. e hypothesis was that reective
activities (cognitive and metacognitive) performed during organizing
and generating contents and reviewing and revising are indicative for
the process of writing-to-learn. erefore, it was expected that
experimental teacher candidates performed reective activities more
oen than control teacher candidates.
For reader’s convenience, Table11 presents the outcome of the
analysis of the process of writing-to-learn for both studies. Eect sizes
are presented for estimation of the magnitude of dierences found
between experimental and control teacher candidates. In biology
teacher education, some evidence for the hypothesis was found.
Experimental teacher candidates executed three of seven reective
activities more oen than control teacher candidates. In mathematics
teacher education, four reective activities were more oen carried
out by teacher candidates who had received GWPR instruction than
by control teacher candidates. Two of these (revising while formulating
and rereading own text) were similar to two indicators of writing-to-
learn in biology teacher education.
is evidence partly conrmed our view on the role of reective
activities in writing-to-learn. Dierences found between the two
studies can beexplained by dierences between the two writing tasks
in biology and mathematics. e outcome of the think-aloud studies
is complementary to the results found for topic knowledge and insight
in the two studies. It provides evidence that GWPR instruction incites
the process of writing-to-learn by teacher candidates’ reection on
conceptual relations and comprehensibility to the intended audience,
TABLE10 Proportioned means, standard deviations, and eect sizes of indicators of writing-to-learn in experimental (N = 8) and control group (N = 7) of
mathematics teacher education.
Experimental Control Eect size
Codes Mean Std. deviation Mean Std. deviation Cohen’s d
Planning: generating
Using knowledge about audience 0.04 0.03 0.02 0.02 0.83
Planning: selecting
inking about content selection 0.03 0.05 0.01 0.01 0.55
Formulating
inking about formulating 0.03 0.02 0.04 0.07 −0.25
Revising while formulating 0.03 0.04 0.01 0.02 0.38
Revising aer nishing an utterance 0.02 0.02 0.02 0.02 0.00
Monitoring
Rereading own text 0.12 0.09 0.04 0.06 1.27
Rethinking task approach 0.01 0.01 0.01 0.02 0.00

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 13 frontiersin.org
leading to more insight and topic knowledge in biology teacher
education and insight in mathematics teacher education.
4.2. Eects of GWPR instruction
In the two studies presented, GWPR instruction appeared to
enhance learning in biology and mathematics teacher education. e
strength of GWPR instruction may bethat it initiates a coherent
writing process by focusing teacher candidates’ attention repeatedly
on genre-specic formulation of conceptual relations and
comprehensibility to a lay audience. erefore, the instructed activities
link up with each other. Weassume that this explains why the process
resulted in new topic knowledge and insight in biology and insight
in mathematics.
To recapitulate, genre writing with planning and revising (GWPR)
starts with discussing a model text. is text has the characteristics of
the genre (e.g., exposition), (lay) audience and topic the teacher
candidates are supposed to write about, but it is designed in such way
that copying contents is prohibited. In addition, in the model text
examples of formulations of a conceptual relation are highlighted and
reected upon in class. Subsequently, teacher candidates are stimulated
to reect on their planning activities in small groups by discussing
selection of content elements and how to clarify the relationships
between these elements in a way that is comprehensible to the lay
audience, taking advantage of examples of linguistic realizations in the
model text. In the context of teacher education, wecould make use of
the fact that it is directed to the teaching of younger teacher candidates.
is provided a good occasion for an ecologically valid audience for
writing. Aer teacher candidates have written a dra on their own,
they are stimulated to provide feedback on each other’s dras in pairs
or small groups with specic attention to the comprehensibility of the
conceptual relations to the audience. Finally, teacher candidates use
this feedback, for revising.
4.3. Teacher candidates’ and teacher
educators’ evaluation of writing-to-learn
Apart from learning effects of GWPR, it is also relevant to
find out how teacher candidates and teacher educators value our
approach to writing-to-learn. Therefore, we asked how they
evaluated the use of GWPR instruction in their classes. Do
teacher candidates believe that they benefit from writing-to-
learn? Do teachers consider writing-to-learn a useful addition to
their teaching repertoire? For answering these questions, teacher
candidates’ and teacher educators’ views were explored in
individual interviews (three biology teacher candidates, three
mathematics teacher candidates and two teacher educators) that
took place after finishing the experiments. In addition, a
questionnaire was administered to experimental teacher
candidates (18 biology and 26 mathematics teacher candidates).
All biology teacher candidates considered writing supportive for
learning and mentioned that they acquired new topic knowledge and
insight. ey were positive about using model texts stating that these
made clear which type of text the teacher educator expected. e
biology teacher educator appreciated the teacher educator manual for
familiarizing him with GWPR instruction, but still felt insecure about
explaining the conceptual relations in the model texts. However, his
intention was to continue using writing-to-learn in his lessons.
Mathematics teacher candidates’ reaction on GWPR instruction
was mixed. e three interviewed mathematics teacher candidates
experienced the writing activities as useful and meaningful. Two
teacher candidates valued peer feedback, because this made them
realize that their texts were not understandable to an audience yet.
However, in their evaluations quite a number (15 of 26) of mathematics
teacher candidates appeared to benot convinced of the usefulness of
writing-to-learn assignments. One mathematics student was afraid
not to beable to write a text as long as the model text.
eir teacher educator did not feel comfortable with teaching
writing-to-learn. Hewondered whether the course “Rows and limits”
was suitable for using writing-to-learn tasks and suggested that a
course requiring teacher candidates to write mathematical proofs
might oer better opportunities for writing-to-learn.
ese reactions reect dierences between the two disciplines.
e disciplines involved in the experiment dier largely regarding the
role of writing. In biology teacher education, teacher candidates are
used to write about subject matter, whereas mathematics teacher
candidates usually do not write texts in math classes. In class, they are
not challenged to express their knowledge of subject matter in their
own words (Skemp, 1987; Veel, 1999), which is an important element
of writing-to-learn. erefore, it is remarkable that mathematics
teacher candidates showed positive eects on learning. Using writing-
to-learn tasks in mathematics teacher education may entail a much
larger pedagogical change than in biology teacher education (Graham
etal., 2020).
4.4. The process of writing-to-learn
e assumption behind the think-aloud studies was that GWPR
instruction stimulates reection on content and rhetorical goals
(Bereiter and Scardamalia, 1987). Seven reective activities were
identied as indicators of this process. e biology as well as the
mathematics experimental teacher candidates performed two of these
activities, namely “revising while formulating” (small eect sizes) and
“rereading own text” (large eect sizes), more frequently than control
teacher candidates. is is in accordance with the discussed theories,
which stress the importance of rereading and revising for learning by
writing (Bereiter and Scardamalia, 1987; Galbraith, 2009).
Additionally, these similarities between the two types of teacher
education provide support for Klein (2004) who showed evidence for
rereading and revising.
Dierences between the two types of teacher education can largely
beexplained by dierences between the writing tasks and teacher
candidates’ familiarity with writing. e mathematics post-test writing
task was similar to the writing-to-learn tasks teacher candidates
performed in the lessons (assignment of genre and a lay audience), but
the biology post-test writing task was not (no assignment of genre and
no lay audience).
In the rst place, the biology writing task contained criteria for
selecting contents (“look for Darwin’s observations and his accessory
explanations”). erefore, it is understandable that experimental biology
teacher candidates did not dier from control teacher candidates on the
indicator “thinking about content selection”, whereas the experimental
mathematics teacher candidates did. In addition, biology teacher

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 14 frontiersin.org
candidates were not instructed to write for an audience, contrary to
mathematics teacher candidates. erefore, it is not surprising that
biology experimental teacher candidates did not dier from control
teacher candidates on the indicator “using knowledge about audience”.
Another dierence concerns experimental mathematics teacher
candidates not showing the indicator “revising aer writing an
utterance” more frequently than control teacher candidates, whereas
experimental biology teacher candidates did. is can beexplained by
the previously mentioned unfamiliarity of mathematics teacher
candidates with writing. erefore, they might have been hesitant to
revise their text, a phenomenon that is oen encountered in
inexperienced writers (Bereiter and Scardamalia, 1987; Beal, 1990;
Van Gelderen, 1997).
e indicator “thinking about formulating” did not show larger
frequencies for biology nor for mathematics experimental teacher
candidates in comparison to control groups. For biology teacher
candidates, this can beexplained by the writing task as well. Both
conditions did not need “thinking about formulating”, because they
disposed of Darwin’s formulation. erefore, the conditions may have
acted in the same way. Mathematics teacher candidates did not like
writing, as previously described. erefore, they probably were not
inclined to spend much eort (and reection) on their
formulation processes.
In biology as well as mathematics teacher education, experimental
teacher candidates did not dier from control teacher candidates on
the indicator “rethinking task approach”. Possibly, teacher candidates
in both studies did not consider reecting on their task approach,
because both writing tasks provided enough structure for them to
follow. In that case, they did not see a reason to critically evaluate
their approach.
5. Suggestions for future research
In the two studies reported, GWPR instruction facilitated
academic learning in two largely diering disciplines in higher
education. Additionally, teacher candidates valued learning by writing,
albeit more in biology than in mathematics. erefore, webelieve that
future research into the eects of GWPR instruction on topic
knowledge and insight is worthwhile in order to determine the
generalizability and stability of these ndings in other educational
contexts. An important issue to concern is the role of teacher attitudes
towards writing-to-learn (see Section 6).
is applies to both higher and secondary education in dierent
disciplines. Relatively, much research on writing-to-learn has already
been conducted in secondary education (Miller etal., 2018; Graham
etal., 2020). In that context, research into eects of GWPR instruction
however is of value since it is still unknown what type of instruction
for writing-to-learn is more eective than others (Graham etal.,
2020). GWPR instruction oers much support in understanding and
producing conceptual relations in writing, which may bebenecial for
learning processes of students in secondary school.
In the present studies in higher education, the numbers of
participants (including teacher educators) were quite small. For
providing stronger evidence, we recommend research on larger
samples. is may berealized in higher education courses teaching
larger numbers of teacher candidates, for example in their rst year of
study. Alternatively, a cooperation of several universities teaching the
same course may be considered. A requirement is that teachers
involved are motivated for working in a team consisting of researchers
and teachers from various universities for cocreating materials and
lessons and aligning their assessments of learning results.
While the present studies did not use randomized samples,
we suggest using a true experimental design for further studying
GWPR instruction, because this can yield stronger evidence. An
example of a true experimental design can befound in Kie etal.
(2006). e researchers assign students randomly to two experimental
conditions, such that each class comprises students from both
conditions. e material is self-instructing, and the lesson structure is
identical for both groups to ensure that the dierences between the
tasks are not noticed by teacher candidates. For GWPR instruction,
this design can beapplied by administering writing tasks with dierent
topics for learning for each of the two experimental conditions. Eects
can bedemonstrated by comparing topic knowledge and insight on
the dierent topics that the teacher candidates were writing about.
e present think-aloud studies were performed with very small
samples. Although the analysis of protocols is very costly and time
consuming, it is recommendable that future studies are carried out
with more sizable samples. For substantiating the hypotheses provided
in our study about the process of writing-to-learn, testing in larger
samples is needed. It would provide more certainty about the issue
whether the dierent types of reection discriminated are indeed
components of the process of writing-to-learn.
e two present studies provided evidence that certain elements
of the (nal) writing tasks have consequences for the process of
writing-to-learn. While the nal mathematics writing task explicitly
dened an audience to write for, this element was missing in the nal
biology writing task. In addition, this task allowed teacher candidates
to copy formulations from an existing text, which probably prevented
them from critically reexamining their formulations. erefore, in
future studies nal writing tasks should at least comply with the
structure of writing tasks that are part of the GWPR instruction,
including both a lay audience to keep in mind and the production of
text that can beregarded as the teacher candidates’ genuinely own text.
6. Pedagogical implications
Although it appears that writing-to-learn can beapplied in many
disciplines, it is not much used in education yet (Klein and Boscolo,
2016). Teachers are hesitant to use writing as a learning tool in class,
as appeared from the interviews held with the teachers in the present
studies. ey felt insecure in designing writing-to-learn tasks and in
selecting (or rather creating) good model texts as examples of the
realization of certain conceptual relations. Additionally, they
considered supporting student writing not as their job. It may seem
self-evident that language teachers readily take on the task to support
their colleagues on using writing-to-learn. However, this cannot
beexpected from them that easily. Aer all, their profession is not
teaching writing-to-learn but learning to write, meaning that they
instruct teacher candidates in how to structure their texts, connect
sentences, use correct grammar and spelling. Most language teachers
have no experience in composing model texts from a genre for
writing-to-learn tasks and how to use these in class.
erefore, wesuggest that language and subject teachers cooperate
gaining experience in developing good writing-to-learn tasks. is

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 15 frontiersin.org
way, all teachers can contribute their own expertise (on discipline
specic knowledge or on writing tasks and instructions) and
determine which genre suits their learning goals. At the same time,
they can use the elements of Genre Writing instruction: a preparatory
activity for explaining the genre at stake, highlighting conceptual
relations as the focus of instruction, followed by instruction on
planning, reviewing and revising activities.
Data availability statement
e raw data supporting the conclusions of this article will
bemade available by the authors, without undue reservation.
Ethics statement
Ethical review and approval was not required for the study on
human participants in accordance with the local legislation and
institutional requirements. Written informed consent for participation
was not required for this study in accordance with the national
legislation and the institutional requirements.
Author contributions
All authors listed have made a substantial, direct, and intellectual
contribution to the work and approved it for publication.
Funding
is research received funding from Rotterdam University of
Applied Sciences.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their aliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
Supplementary material
e Supplementary material for this article can befound online
at: https://www.frontiersin.org/articles/10.3389/feduc.2023.1094156/
full#supplementary-material
References
Akkus, R., and Hand, B. (2011). Examining teachers’ struggles as they attempt to
implement dialogical interaction as part of promoting mathematical reasoning within
their classrooms. Int. J. Sci. Math. Educ. 9, 975–998. doi: 10.1007/s10763-010-9266-8
Baaijen, V. M., and Galbraith, D. (2018). Discovery through writing: relationships with
writing processes and text quality. Cogn. Instr. 36, 199–223. doi:
10.1080/07370008.2018.1456431
Bangert-Drowns, R. L., Hurley, M. M., and Wilkinson, B. (2004). e eects of school-
based writing-to-learn interventions on academic achievement: a meta-analysis. Rev.
Educ. Res. 74, 29–58. doi: 10.3102/00346543074001029
Beal, C. R. (1990). e development of text evaluation and revision skills. Child Dev.
61, 247–258. doi: 10.2307/1131063
Bereiter, C., and Scardamalia, M. (1987). e Psychology of Written Composition.
Hillsdale, NJ: Lawrence Erlbaum Associates.
Berthold, K., Nückles, M., and Renkl, A. (2007). Do learning protocols support
learning strategies and outcomes? e role of cognitive and metacognitive prompts.
Learn. Instr. 17, 564–577. doi: 10.1016/j.learninstruc.2007.09.007
Bos, D., Bouw, J., Brinkman, H., De Bruijn, I., Doekes, W., Van Dijk, B., et al. (2007).
Moderne Wiskunde: Vwo-bovenbouw deel B1, B2, B3, D1, D3. 9e editie. Noordho.
Boscolo, P., and Carotti, L. (2003). Does writing contribute to improving high school
students’ approach to literature? L1-Educ. Stud. Lang. Lit. 3, 197–224. doi:
10.1023/B:ESLL.0000003685.30925.c4
Boyle, G. J. (1991). Does item homogeneity indicate internal consistency or item
redundancy in psychometric scales? Personal. Individ. Dier. 12, 291–294. doi:
10.1016/0191-8869(91)90115-R
Cohen, J. (1988). Statistical power analysis for the behavioural sciences. Lawrence
Erlbaum Associate, Publishers. Academic Press.
Darwin, C. (2010). Het ontstaan van soorten door natuurlijke selectie ofwel het bewaard
blijven van rassen die in het voordeel zijn in de strijd om het bestaan Amstel Uitgevers
(Olympus).
Dunn, L. M., and Dunn, L. M. (2005). Peabody picture vocabulary test-III-NL. L.
Schlichting (Dutch version). Amsterdam: Harcourt Test Publishers.
Eaton, C. D., and Wade, S. (2014). Collaborative learning through formative peer
review with technology. Primus 24, 529–543. doi: 10.1080/10511970.2014.881442
Emig, J. (1977). Writing as a mode of learning. Coll. Compos. Commun. 28, 122–128.
doi: 10.2307/356095
Ericsson, K. A., and Simon, H. A. (1993). Protocol analysis. London: MIT Press.
Finkenstaedt-Quinn, S. A., Halim, A. S., Chambers, T. G., Moon, A., Goldman, R. S.,
Ruggles Gere, A., et al. (2017). Investigation of the inuence of a writing-to-learn
assignment on student understanding of polymer properties. J. Chem. Educ. 94,
1610–1617. doi: 10.1021/acs.jchemed.7b00363
Galbraith, D. (1992). Conditions for discovery through writing. Instr. Sci. 21, 45–71.
doi: 10.1007/BF00119655
Galbraith, D. (1999). “Writing as a knowledge-constituting process” in Knowing what
to write: conceptual processes in text production. eds. M. Torrance and D. Galbraith
(Amsterdam: Amsterdam University Press), 139–159.
Galbraith, D. (2009). Writing as discovery. Br. J. Educ. Psychol., Monograph Series II
6-teaching and learning writing 2, 5–26. doi: 10.1348/978185409x421129
Graham, S., Kiuhara, S. A., and McKay, M. (2020). e eects of writing on learning
in science, social studies, and mathematics: a meta-analysis. Rev. Educ. Res. 90, 179–226.
doi: 10.3102/0034654320914744
Halliday, M. A. K., and Martin, J. R. (1993). Writing science: literacy and discursive
power. London: e Falmer Press.
Hand, B., Gunel, M., and Ulu, C. (2009). Sequencing embedded multimodal
representations in a writing-to-learn approach to the teaching of electricity. J. Res. Sci.
Tea c h . 46, 225–247. doi: 10.1002/tea.20282
Hand, B., Wallace, C. W., and Yang, E. (2004). Using a science writing heuristic to enhance
learning outcomes from laboratory activities in seventh-grade science: quantitative and
qualitative aspects. Int. J. S ci. Educ. 26, 131–149. doi: 10.1080/0950069032000070252
Hand, B., Yang, O. E., and Bruxvoort, C. (2007). Using writing-to-learn science
strategies to improve year 11 students’ understanding of stoichiometry. Int. J. Sci. Math.
Educ. 5, 125–143. doi: 10.1007/s10763-005-9028-1
Hayes, J. R., and Flower, L. S. (1980). “Identifying the organization of writing processes” in
Cognitive processes in writing. eds. L. W. Gregg and E. R. Steinberg (Mahwah: Erlbaum), 3–27.
Hohenshell, L. M., and Hand, B. (2006). Writing-to-learn strategies in secondary
school cell biology: a mixed method study. Int. J. Sci. Educ. 28, 261–289. doi:
10.1080/09500690500336965

Van Dijk et al. 10.3389/feduc.2023.1094156
Frontiers in Education 16 frontiersin.org
Hunter, K., and Tse, H. (2013). Making disciplinary writing and thinking practices an
integral part of academic content teaching. Act. Learn. High. Educ. 14, 227–239. doi:
10.1177/146978741349803
Kenney, R., Shoner, M., and Norris, D. (2014). Reecting on the use of writing to
promote mathematical learning: an examination of preservice mathematics teachers'
perspectives. Teach. Educ. 49, 28–43. doi: 10.1080/08878730.2013.848002
Kie, M., Rijlaarsdam, G., and van den Bergh, H. (2006). Writing as a learning tool:
testing the role of students’ writing strategies. Eur. J. Psychol. Educ. 21, 17–34. doi:
10.1007/BF03173567
Klein, P. D. (1999). Reopening inquiry into cognitive processes in writing-to-learn.
Educ. Psychol. Rev. 11, 203–270. doi: 10.1023/A:1021913217147
Klein, P. D. (2004). Constructing scientic explanations through writing. Instr. Sci. 32,
191–231. doi: 10.1023/B:TRUC.0000024189.74263.bd
Klein, P. D., and Boscolo, P. (2016). Trends in research on writing as a learning activity.
J. Writ. Res. 7, 311–350. doi: 10.17239/jowr-2016.07.3.01
Klein, P. D., and Kirkpatrick, L. C. (2010). A framework for content area writing:
mediators and moderators. J. Writ. Res. 2, 1–46. doi: 10.17239/jowr-2010.02.01.1
Klein, P. D., and Rose, M. A. (2010). Teaching argument and explanation to prepare
junior students for writing-to-learn. Read. Res. Q. 45, 433–461. doi: 10.1598/
RRQ.45.4.4
Klein, P. D., and Samuels, B. (2010). Learning about plate tectonics through argument
writing. Alberta J. Educ. Res. 56, 196–217. doi: 10.11575/ajer.v56i2.55398
Langer, J. A., and Applebee, A. N. (1987). How writing shapes thinking: a study of
teaching and learning NCTE.
Miller, D. M., Scott, C. E., and McTigue, M. (2018). Writing in the secondary level
disciplines: a systematic review of context, cognition and content. Educ. Psychol. Rev. 30,
83–120. doi: 10.1007/s10648-016-9393-z
Newell, G. E. (1984). Learning from writing in two content areas: a case study/protocol
analysis. Res. Teach. Engl. 18, 265–287.
Nückles, M., Hübner, S., and Renkl, A. (2009). Enhancing self-regulated learning by
writing learning protocols. Learn. Instr. 19, 259–271. doi: 10.1016/j.
learninstruc.2008.05.002
Pander Maat, H. (1994). Tekstanalyse: Een pragmatische benadering. Groningen:
Martinus Nijho.
Prain, V. (2006). Learning from writing in secondary science: some theoretical and
practical implications. Int. J. Sci. Educ. 28, 179–201. doi: 10.1080/09500690500336643
Reece, J. B., Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., Jackson, R. B.,
et al. (2011). Campbell Biology. San Francisco, Benjamin Cummings/Pearson.
Rose, D. (2008). “Writing as a linguistic mastery: the development of genre-based
literacy pedagogy” in Handbook of writing development. eds. D. Myhill, D. Beard, M.
Nystrand and J. Riley ousand Oaks: Sage.
Sampson, V., and Phelps Walker, J. (2012). Argument-driven inquiry as a way to help
undergraduate students write to learn by learning to write in chemistry. Int. J. Sci. Educ.
34, 1443–1485. doi: 10.1080/09500693.2012.667581
Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of
Cronbach’s alpha. Psychometrika 74, 107–120. doi: 10.1007/s11336-008-9101-0
Skemp, R. R. (1987). e psychology of learning mathematics. New York and London:
Routledge.
Taber, K. S. (2018). e use of Cronbach’s alpha when developing and reporting
research instruments in science education. Res. Sci. Educ. 48, 1273–1296. doi: 10.1007/
s11165-016-9602-2
Van Dijk, A., Van Gelderen, A., and Kuiken, F. (2022). Which types of instruction in
writing-to-learn lead to insight and topic knowledge in dierent disciplines? A review
of empirical studies. Rev. Educ. 10, 1–41. doi: 10.1002/rev3.3359
Van Gelderen, A. (1997). Elementary students' skills in revising: integrating
quantitative and qualitative analysis. Writ. Commun. 14, 360–397. doi:
10.1177/0741088397014003003
Van Someren, M. W., Barnard, Y. F., and Sandberg, J. A. C. (1994). e think aloud
method: a practical guide to modelling cognitive processes Academic Press Limited.
Veel, R. (1999). “Language, knowledge and authority in school mathematics” in
Pedagogy and the shaping of consciousness: linguistic and social processes. ed. F. Christie
(London: Cassell).
Zeiss, F. (1999). Natuurlijke historiën: Geschiedenis van de biologie van Aristoteles tot
Darwin. Amsterdam: Boom.