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Learning and Instruction 88 (2023) 101810
0959-4752/© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
Domain-specic self-regulated learning interventions for elementary
school students
Minhye Lee
a
,
*
, Sun Young Lee
a
, Ji Eun Kim
b
, Hyun Jae Lee
c
a
Department of Education, Daegu National University of Education, Daegu, South Korea
b
Dorim Elementary School, Daegu, South Korea
c
Nogyang Elementary School, Gyeonggi-do, South Korea
ARTICLE INFO
Keywords:
Self-regulated learning
Classroom intervention
Motivation
Elementary school
Domain specicity
ABSTRACT
Background: Self-regulated learning has been deemed an essential skill that must be explicitly learned and
repeatedly practiced for young students. The need for research on teacher-led self-regulated learning in-
terventions embedded in regular classroom instructions has escalated steadily.
Aims: We aimed to investigate self-regulated learning interventions’ effectiveness led by teachers applicable to
three primary subjects (i.e., writing, mathematics, reading) based on Zimmerman’s cyclical model of self-
regulated learning.
Samples: 214 Korean upper elementary school students participated in a series of three intervention studies
(n
Study1
=70, n
Study2
=69, n
Study3
=75).
Methods: Trained homeroom teachers implemented the interventions—incorporating explicit instructions about
domain-specic strategies in writing (Study 1), mathematics (Study 2), and reading (Study 3)—in Korean
elementary school classrooms. Participants were assigned to one of the three groups: regular classroom in-
struction (REG), domain-specic strategy instruction (STR), and strategy instruction within the framework of
eight-phase self-regulated learning instruction (STR +SRL).
Results: Synthesized results revealed that the STR +SRL group used more self-regulated strategies, performed
better in achievement tests, and was less distracted by task-irrelevant thoughts than the STR and REG groups.
Conclusions: Our interventions are compatible with domain-specic instructions in multiple subjects and can
guide and prompt self-regulatory learning processes in elementary classrooms. Current ndings also reiterate the
importance of the teachers’ role in research-based interventions to increase ecological validity and applicability.
We shed light on the potential mechanism that underlies the relationship between enhanced self-regulated
learning and motivational and cognitive outcomes.
1. Introduction
Self-regulated learning is pivotal in preparing students to be agentic
life-long learners in an unpredictable, dynamic, and ever-changing so-
ciety (Organization for Economic Co-operation and Development,
2018). Considering that self-regulated learning has been deemed an
essential skill that must be explicitly learned and repeatedly practiced
throughout life, early interventions for elementary school lower-grade
students are more effective than later interventions for secondary
school students (Stoeger et al., 2014). In classroom settings,
self-regulated learning can be better developed and transferred by
teachers (Callan et al., 2022). When teachers’ guided instructions and
consistent reminders regarding self-regulatory processes are combined
with subject-specic strategies during class, students easily utilize and
apply self-regulated learning skills in multiple subjects (Dignath &
Veenman, 2021; Zimmerman et al., 1996). In addition, the utilization of
a think-aloud approach by teachers or instructors to model cognitive
self-instruction has been particularly benecial for students struggling
with impulse control (Meichenbaum & Goodman, 1971) and low
achievement (Schunk & Gunn, 1985).
Unfortunately, research on teacher-led interventions embedded in
regular classroom instructions—compared with researcher-led in-
terventions in controlled laboratory environments—is scant owing to
the former’s smaller effect sizes (Dignath & Büttner, 2008). Only a few
* Corresponding author. Department of Education, Daegu National University of Education, 219 Joongang-daero, Nam-gu, Daegu, 42411, Republic of Korea.
E-mail address: minhyelee@dnue.ac.kr (M. Lee).
Contents lists available at ScienceDirect
Learning and Instruction
journal homepage: www.elsevier.com/locate/learninstruc
https://doi.org/10.1016/j.learninstruc.2023.101810
Received 9 February 2023; Received in revised form 8 June 2023; Accepted 23 July 2023
Learning and Instruction 88 (2023) 101810
2
recent studies have included teachers as conductors of self-regulated
learning interventions in their regular subject-domain classes (e.g.,
reading, writing), incorporating domain-specic strategies (e.g., strate-
gies for nding main ideas, mind mapping; Benick et al., 2021; Lau,
2020; Merchie & Van Keer, 2016; Schünemann et al., 2013; Stoeger
et al., 2014). Thus, in the present series of intervention studies, we
developed teacher-led self-regulated learning interventions applicable
to three primary subjects—writing (Study 1), mathematics (Study 2),
and reading (Study 3)—in authentic elementary school classrooms. We
examined the effects of self-regulated learning interventions on
elementary school students’ motivation and performance in comparison
with two control groups, as follows: (1) control intervention groups,
who were taught domain-specic strategies only without instruction
regarding self-regulated learning; and (2) no-treatment groups, who
were exposed to regular classroom instructions.
1.1. Zimmerman’s cyclical model of self-regulated learning
Among several models of self-regulated learning, Zimmerman’s
(1986, 1989, 2000, 2013) cyclical model of self-regulated learning,
which is based on social cognitive theory, has been widely accepted and
considered effective, particularly for elementary school students (Pan-
adero, 2017). The model posits that self-regulated learning is a series of
cognitive, metacognitive, motivational, and behavioral processes to
plan, control, and reect on one’s learning (Zimmerman, 2000). More
precisely, there are three self-regulatory phases as follows: (1) The
forethought phase—to analyze a task along with setting goals, strategic
planning, and preparing oneself with motivational beliefs and
self-diagnosis about one’s current cognitive and motivational state; (2)
the performance control phase—to manage and monitor one’s progress
during task performance based on the goals and plans established in the
forethought phase; and (3) the self-reection phase—to evaluate one’s
outcome and feedback concerning the self-reective information in the
upcoming forethought phase.
Although Zimmerman’s (2000) cyclical model contains multiple
sub-processes within each phase, owing to its complexity, a simplied
version has been adopted for elementary school students (Stoeger et al.,
2014; Stoeger & Ziegler, 2005; Ziegler & Stoeger, 2005). The simplied
version emphasizes cognitive and metacognitive aspects rather than the
motivational aspect, which is, reportedly, more effective for secondary
school students (Dignath & Büttner, 2008). It comprises seven steps: (1)
self-assessment, (2) goal-setting, (3) strategic planning, (4) strategy
implementation, (5) strategy monitoring, (6) strategy adjustment, and
(7) outcome evaluation (Stoeger et al., 2014). The rst three steps
correspond to the forethought phase. In this phase, students practice
setting optimal goals based on the self-assessment of their current
competence. Then, they are guided to plan strategies to narrow the gap
between the set goal and their current level of competence. The subse-
quent three steps correspond to the performance control phase. While
implementing the planned strategies, students continue monitoring and
adjusting their strategy use. The last step corresponds to the
self-reection phase. Students evaluate and reect on their outcomes in
comparison with the goals and strategies set at the beginning. This
seven-step self-regulated learning intervention for elementary school
students has been replicated with independent samples of German
fourth graders in the reading domain (i.e., nding main ideas) (Sontag &
Stoeger, 2015; Stoeger et al., 2014; Stoeger & Ziegler, 2005).
Given the parsimony and replicability of the simplied version for
elementary school students, we adopted the cyclical model version
designed by Stoeger and his colleagues in our intervention programs. A
single minor modication was made to be more coherent with Zim-
merman’s original model by adding an explicit task analysis phase as the
second step. According to Zimmerman (2013), one of the primary pur-
poses of the forethought phase is to have students pause and analyze the
task before starting it. In line with this idea, we provided students with
time to analyze the task complexities and nuances before formulating
goals (i.e., third phase) and developing comprehensive action plans (i.e.,
fourth phase). Finally, an eight-phase cyclical model of self-regulated
learning including self-assessment, task-analysis, goal-setting, strategic
planning, strategy implementation, strategy monitoring, strategy
adjustment, and self-reection, was developed and implemented as the
primary framework of interventions in these studies (Appendix A).
1.2. Domain-specic self-regulated learning interventions
Self-regulated learning should be taught with specic subject matters
or content domains (Alexander, 1995) because students develop cogni-
tive skills, behavioral tactics, and motivational beliefs in a highly
domain- and context-specic manner (Bong, 2001). Students who have
learned about self-regulated learning as decontextualized general stra-
tegies might struggle to transfer and apply the knowledge to specic
subject domains (Boekaerts, 1997). This phenomenon is commonly
witnessed in elementary school students as novice learners unfamiliar
with self-regulatory processes and content knowledge. For this reason,
most extant interventions to boost elementary school students’
self-regulated learning are embedded in a particular subject domain,
such as reading or writing, mathematics, social science, or science
(Dignath et al., 2008).
Additionally, self-regulated learning should be taught with domain-
specic cognitive strategies that students can use during the self-
regulatory processes (Benick et al., 2021; Lau, 2020; Stoeger et al.,
2014). Without sufcient knowledge regarding strategies used in a
particular domain, students might be unable to circulate the
self-regulated learning cycle of planning, implementing, monitoring,
and adjusting strategy phases effectively (Zimmerman, 1989). In this
sense, a few intervention studies expected synergistic effects of
self-regulated learning instruction embracing strategy instruction
(Glaser & Brunstein, 2007; Guthrie et al., 2004; Lau, 2020; Stoeger et al.,
2014). According to these studies, teaching domain-specic strategies
(e.g., underlining, highlighting, and/or mind mapping to nd main
ideas in a text) combined with metacognitive or self-regulatory strate-
gies (e.g., goal setting, planning, monitoring) is more effective than
teaching strategies alone.
Although the cyclical model of self-regulated learning is compatible
with diverse subject domains, there is a lack of research that deals with
two or more subject domains concurrently in self-regulated learning
interventions within a single study. It is important to determine the
effectiveness and compatibility of interventions in various subject areas
because interventions designed for one particular domain may not be
transferable to other domains. From the perspective of Korean elemen-
tary school teachers, who teach a wide range of subjects, excluding
physical education, English as a foreign language, and music, using
heterogeneous self-regulated learning interventions can be challenging.
Thus, in the present study, we targeted contents and strategies of
persuasive writing, solving mathematical word problems, and reading
comprehension, which are covered in the Korean National Elementary
School Curriculum, in a series of three studies. These three domains
were chosen because they are considered fundamental subjects in
elementary school curricula pivotal to students’ academic success
throughout their schooling (Ehm et al., 2014). That is, prociency in
these skills is integral to mastering other applied disciplines, including
social science, science, and history. Most previous research identifying
the benecial effects of self-regulated learning interventions for
elementary school students has studied one of these three subject do-
mains (for a review, see Dignath et al., 2008). We attempted to make the
interventions compatible with regular classroom instructions for three
core subject domains so that teachers feel less burdened when imple-
menting the interventions.
Furthermore, we aimed to investigate the additive effects of self-
regulated learning interventions, embracing domain-specic strategy
instruction in comparison with teacher instruction pertaining only to
cognitive strategies and regular classroom instruction. Thus, three sets
M. Lee et al.
Learning and Instruction 88 (2023) 101810
3
(i.e., writing, mathematics, reading) of three-group quasi-exper-
iments—including a no-intervention regular classroom instruction
group (REG), a strategy-only group (STR), and a strategy plus self-
regulated learning group (STR +SRL)—were designed, as suggested
by previous studies (Benick et al., 2021; Glaser & Brunstein, 2007;
Guthrie et al., 2004; Lau, 2020; Stoeger et al., 2014).
1.3. Teacher-led classroom interventions for elementary school students
Numerous researchers have agreed that classroom interventions
should ideally be designed and implemented by teachers (Callan et al.,
2022; Dignath & Veenman, 2021; Perry & VandeKamp, 2000; Rozendaal
et al., 2005). It is because teachers are the most knowledgeable about
their students and well-positioned to freely adjust details of in-
terventions to their classroom contexts in an ecologically valid manner
(De Corte, 2000). Teacher-led self-regulated learning interventions can
be more effective under the Korean elementary school system wherein
one homeroom teacher stays in the classroom with their students all day
and teaches nearly all subjects except for physical education, science,
English, and music. With this system, teachers can apply the cyclical
model of self-regulated learning to diverse subject matters and
customize it to their students with domain-specic strategies.
Nonetheless, existing meta-analyses have consistently reported that
teacher-led self-regulated learning interventions exhibit weaker effect
sizes than research-led interventions (Dignath & Büttner, 2008; Hatti
et al., 1996). This nding might be attributable to either researchers
lacking experience in classroom contexts when developing interventions
or teachers’ limited knowledge regarding the self-regulated learning
construct’s details and background when implementing interventions
(Dignath et al., 2008). Furthermore, teachers tend to believe that
self-regulated learning is challenging to teach and, therefore, do not feel
condent that they can teach it (Lawson, Vosniadou, VanDeur, Wyra, &
Jeffries, 2019). This phenomenon implies that teachers implementing
self-regulated learning interventions should be trained and taught about
self-regulated learning to change their belief system in advance (Callan
et al., 2022).
Despite the comprehensive training and recognition of teachers on
the importance of self-regulated learning interventions, teachers may
encounter a range of obstacles during the implementation process in
their classrooms (Dignath & Büttner, 2008). Kline et al. (1992) thor-
oughly scrutinized the possible hindrances that prevent teachers from
executing strategy instruction in authentic classroom environments.
They found that teachers who underwent extensive workshops on
strategy instruction seldom applied this instruction in their classrooms
owing to the ensuing factors: “(1) setting factors (e.g., lack of adminis-
trative support and high start-up costs), (2) teacher factors (e.g., a poor
mindset and failure to use critical teaching skills), (3) programmatic
factors (e.g., lack of overall plans that specify how strategy instruction
will be incorporated into ongoing instruction), and (4) instructional
factors (e.g., high rates of interruptions during strategy instruction,
bogging down during the instructional processes, and not ensuring that
students demonstrate mastery and generalization of the strategy)” (Kline
et al., 1992, p. 397). The follow-up studies conducted by the researchers,
which involved providing teachers with comprehensive supporting
materials, organizing regular meetings with support teams, and imple-
menting feedback routines for students, proved to be efcacious in
enhancing teachers’ implementation of strategy instruction.
Therefore, in the present study, to minimize the potential reduced
effects of teacher-led interventions and maximize the accurate imple-
mentation of the interventions, we invited elementary school teachers in
the intervention development stage to be part of a professional devel-
opment program for teachers (Cleary, 2011). During this program,
teachers were provided one-on-one mentoring sessions with a member
of the research team who explained and discussed what self-regulated
learning is and how to teach it to elementary school students in class-
room contexts. The research team established immediate
communication channels (e.g., messengers, phone calls) with teachers
during implementation to encourage them to discuss unexpected events
or conicts that may impede sessions. Furthermore, we followed specic
guidelines to maximize the effects of self-regulated learning in-
terventions in elementary school classrooms based on meta-analytic
results (Dignath et al., 2008); the guidelines suggest that teachers pro-
vide explicit instructions, modeling, and feedback regarding
self-regulatory processes and strategy uses in the context of reading/-
writing or mathematics for their students. Following the guidelines,
teachers explicitly explained what self-regulated learning is and why it is
necessary, demonstrated instilling the self-regulatory processes and
strategy uses as a cycle, and provided verbal feedback about students’
self-regulated learning.
1.4. Cognitive and motivational outcomes of self-regulated learning
interventions
Previous research has indicated that students who received self-
regulated learning interventions had better performance, used self-
regulated strategies more, were more motivated, and focused more on
their tasks than students who did not receive such interventions (for a
review, see Dignath & Büttner, 2008). More precisely, students exposed
to self-regulated learning interventions embedded in reading, writing, or
mathematics reported higher performance scores in reading compre-
hension tests (Sontag & Stoeger, 2015; Sp¨
orer & Schünemann, 2014),
essay writings (Brunstein & Glaser, 2011), or mathematics tests (Teong,
2003) than students not exposed to the interventions. The intervention
groups achieved better academic performance due to the implementa-
tion of interventions that enhanced their motivational and cognitive
processes, as delineated below.
The intervention groups used self-regulated strategies more
frequently than the control groups (Carretti et al., 2014; Leidinger &
Perels, 2012). Self-regulated strategy use refers to the extent of students’
planning, goal setting, monitoring, and evaluation during a particular
task (Shell & Husman, 2008). This construct is consistent with Zim-
merman’s cyclical model of self-regulated learning (2000), which en-
compasses the phases of forethought, performance control, and
self-reection. The intervention programs boost students’ employment
of self-regulated strategies by introducing and reminding them about the
self-regulatory cycle during instructional sessions.
The self-regulated learning interventions also enhanced students’
adaptive motivation (Guthrie et al., 2004; Schünemann et al., 2013;
Souvignier & Mokhlesgerami, 2006). Self-efcacy, as one of the most
prominent forms of adaptive motivation, has been extensively assessed
by self-regulated learning researchers (Bandura, 1977). Self-efcacy for
learning refers to an individual’s subjective beliefs about their capacity
to understand, remember, and analyze tasks to learn and acquire new
knowledge and skills presented in a particular task (Bong et al., 2012;
Schunk, 1996). Building on the work of Zimmerman et al., (1992) who
showed that self-efcacy for self-regulated learning is linked to
self-efcacy in academic domains, the interventions improve
self-efcacy by increasing self-efcacy for self-regulated learning.
Students who underwent the self-regulated learning interventions
were more concentrated on the task than those not exposed to the in-
terventions (Ganda & Boruchovitch, 2018; Grunschel et al., 2018).
Attention or concentration refers to an individual’s capacity to sustain
cognitive focus on a particular task (Weinstein et al., 2016). As an
opposite form of concentration, task-irrelevant thoughts refer to the
degree of student distraction from the task (Linnenbrink et al., 1999).
Student task-irrelevant thoughts can be decreased by having them focus
on the task itself and reminding them of self-regulatory processes, such
as sticking to their goals, monitoring progress, and adjusting malfunc-
tioning strategies.
However, few studies comprehensively assess cognitive and moti-
vational constructs as outcomes of self-regulated learning interventions.
Given that self-regulated learning interventions can positively impact
M. Lee et al.
Learning and Instruction 88 (2023) 101810
4
both motivational and cognitive aspects of learning, assessing all these
outcomes can aid in determining the relative efcacy of interventions. In
the current investigation, therefore, we focused on academic perfor-
mance, self-regulated strategy use, self-efcacy, and task-irrelevant
thoughts to evaluate the effectiveness of our interventions.
1.5. The present studies
Based on a literature review of studies on self-regulated learning
interventions, we raised three research questions. First, to what extent
do teacher-led self-regulated learning interventions cohere with Zim-
merman’s cyclical model of self-regulated learning in elementary school
classrooms? Second, can teacher-led self-regulated learning in-
terventions incorporating cognitive strategy instruction lead to better
learning outcomes than cognitive strategy instruction and regular
classroom instruction? Third, can teacher-led self-regulated learning
interventions be compatible with domain-specic class instruction
across three core subjects (i.e., writing, mathematics, and reading)?
To answer these questions, we rst aimed to develop teacher-led self-
regulated learning interventions—incorporating domain-specic stra-
tegies in writing (Study 1), mathematics (Study 2), and reading (Study
3). We designed and implemented three-group (i.e., REG, STR, and STR
+SRL groups) pre-post quasi-experiments in elementary school class-
rooms to examine group differences in self-regulated strategy use, task-
irrelevant thoughts, self-efcacy, and performance in subject domains
while controlling for the baseline scores. The interventions that we
developed for the STR +SRL groups exhibited three core features as
follows: (1) They were based on the eight-phase cyclical model of self-
regulated learning. (2) They embraced instructions regarding domain-
specic strategies. (3) They were led by teachers who provided
explicit instructions, modeling, and feedback regarding self-regulated
learning. The STR groups were exposed only to explicit instructions
regarding domain-specic strategies, while the REG groups were pro-
vided regular classroom instructions led by their teachers.
2. General methodology
2.1. Participants and procedures
We conducted a priori analyses to dene the sample size using
G*Power (Faul et al., 2007). All participants’ parents or legal guardians
were informed about the details of experiments and gave written
informed consent form approved by the Institutional Review Board. The
STR and STR +SRL groups completed a self-report survey and a writing
task in their classroom twice—once one week prior to the intervention
(pre-test) and once one week after (post-test). Although the REG group
did not receive any interventions, they completed the same survey and
writing task at approximately the same time as the other two interven-
tion groups. The program received approval from the Institutional Re-
view Board and was conducted in compliance with all relevant laws and
institutional guidelines.
2.2. Teacher workshop
All intervention sessions for the STR and STR +SRL groups were
implemented by trained homeroom teachers who voluntarily partici-
pated in the research and mentoring program with a member of the
research team. To be more precise, the research team dispatched an
ofcial document that briey introduced the objectives, procedures, and
contents of the interventions to principals who had expressed interest in
self-regulated learning during the prior workshop for elementary school
administrators. The principals distributed the document to their aca-
demic staff serving as homeroom teachers and instructed interested
teachers to contact the principal investigator (PI) of the research
directly. Schools that met the criteria of having at least three interested
teachers were contacted with priority in line with the three-group
comparison research design. Once the principals had conrmed the
research participation of the teachers and students, the PI scheduled a
Zoom meeting to provide an overview of the research to the teachers and
principals. Given the logistical challenge of aligning schedules for all
participants and principals, we opted to deliver a concise introduction
outlining the research’s objectives and methodology. After the over-
view, the teacher workshop was incorporated into a personalized one-
on-one mentoring program for professional development. This pro-
gram was conducted weekly for a month, with the exibility to
accommodate the schedules of each teacher.
For the teachers of the STR +SRL group, a general introduction to
strategies and self-regulated learning in a target domain (Study 1 for
writing, Study 2 for mathematics, Study 3 for reading) was delivered by
a member of the research team at the rst meeting. In order to pique
teachers’ curiosity and diagnose their understanding of self-regulated
learning, they were prompted at the onset of the rst meeting to ex-
press their agreement or disagreement with ve statements pertaining to
self-regulated learning, which were actually common misconceptions.
Here are ve statements that start with “self-regulated learning is …”:
(1) “… applicable to older students, specically those in at least middle
school who have cognitively developed to some degree,” (2) “… the
same as the use of cognitive strategies, such as elaboration and organi-
zation,” (3) “… naturally transferred to other domains once it is learned
in one area,” (4) “… unable to be taught,” and (5) “… for students who
are smart enough to control their own thinking.” Two of the three
teachers who participated agreed with all ve misconceptions. One of
the teachers agreed with four statements but not the fth one.
After refuting the incorrect statements based on prior research
(Callan & Shim, 2019; Dignath & Büttner, 2008; Lawson et al., 2019),
the research team proceeded to introduce the content of what
self-regulated learning is, why it is important, how its cyclical feature
functions during learning, and why teaching strategies alone would be
less effective than teaching strategies embedded in self-regulated
learning. Details of the content will be explicated in each Study,
describing the intervention program for the STR +SRL group.
In the second meeting, the teacher asked questions regarding the
content of the previous meeting and theoretical and conceptual argu-
ments pertaining to self-regulated learning. A member of the research
team answered the questions based on the ndings of recent studies
developing self-regulated learning interventions. Once the teachers
satised their curiosity regarding self-regulated learning, one of the
researchers introduced the background of the STR +SRL intervention
program’s development. In the third meeting, one of the researchers
explained how to implement the STR +SRL program in their writing
classes with specic lesson plans and student worksheets. After listening
to the explanation and skimming through the lesson plans and work-
sheets, the teachers asked questions and rehearsed the program as if
implementing it to the students. In the last meeting, the teachers prac-
ticed and rehearsed the key instructions regarding introducing self-
regulated learning in a particular domain for their students. Before the
nal meeting ended, the ve misunderstandings about self-regulated
learning introduced in the rst session were reintroduced, and all the
teachers strongly disagreed with them. Over the course of the workshop,
the suggestions (e.g., instructional strategies, appropriate examples for
elementary school students) that the teachers provided were reected
on as much as possible.
The only difference observed in the STR +SRL group was that the
STR group teachers did not receive any information relevant to self-
regulated learning; thus, meetings were held only twice, excluding the
introduction and a question-and-answer session regarding self-regulated
learning. During the rst meeting, a member of the research team
introduced the STR intervention with lesson plans and student work-
sheets while explaining the purpose of the intervention and providing
relevant background information. During the second meeting, the
teachers were asked to rehearse the program implementation. The
teachers of the REG group did not participate in the professional
M. Lee et al.
Learning and Instruction 88 (2023) 101810
5
development program until after the two interventions were over. After
completing the two interventions, the REG group teachers were invited
to—and participated in—the professional development program.
2.3. Intervention programs
This section elucidates the convergent attributes of the three in-
terventions. For a more precise explication of the domain specicity of
each intervention, check the Method section in each study. Appendix B
lists the program contents used for each of the STR and STR +SRL
groups across three studies. All program content was tailored to the
context of each subject domain (i.e., Study 1 for writing, Study 2 for
mathematics, and Study 3 for reading) based on the consultation of two
elementary school teachers. The consulting teachers primarily focused
on the lexical complexity (e.g., self-regulated learning, strategy, evalu-
ation) utilized throughout the entire intervention process, including
lesson plans, activity sheets, and measurements. The teachers also
commented on evaluating and adjusting the difculty level of pre- and
post-achievement tests. They provided advice to reduce the instructional
burden of teachers that may arise from implementing interventions and
enhance the compatibility of the interventions with the national
elementary school curriculum.
For the STR +SRL group, at the commencement of the intervention
program, the teachers provided instruction about self-regulated
learning, the eight-phase cyclical model, and the cyclical features of
the eight phases during the rst three sessions. In Session 1, the STR +
SRL group was taught about what self-regulated learning is and why it is
important in daily life. The teachers started by giving daily life examples
requiring self-regulation, such as when students should resist the
temptation to watch YouTube videos or play computer games instead of
participating in online classes during COVID-19. Once students under-
stood the examples, the teacher asked them to think and talk about
scenarios wherein they failed to regulate themselves while studying.
Based on the students’ scenarios, the teachers emphasized the impor-
tance of self-regulated learning and highlighted the fact that several
students do not know how to regulate their learning by themselves.
Thereafter, the teachers claried what self-regulated learning is and why
it is highly important—particularly for elementary school students,
referring to the neuroscientic ndings about human brain development
in adolescence. Specically, the teachers introduced the brain region,
the dorsolateral prefrontal cortex, which is closely related to self-
regulation and executive functions, and develops slowly until the early
twenties. The teachers stressed the importance of acquiring and prac-
ticing self-regulated learning skills during elementary school and how it
would be benecial to develop their dorsolateral prefrontal cortex.
Moreover, students were provided an acronym for self-regulated
learning in Korean to become accustomed to its meaning.
In Session 2, the teachers provided detailed instruction about the
specics of eight-phase self-regulated learning in the writing domain
using a worksheet developed by the research team and elementary
school teachers. The worksheet contained specic questions reminding
the students of what each phase means in the writing context. More
precisely, for the self-assessment phase, a question asked, “How con-
dent are you about [SUBJECT DOMAIN] and why?” For the task analysis
phase, a question asked, “What does the [SUBJECT DOMAIN] task
require you to think about?” For the goal-setting phase, a question
asked, “What is your goal in this [SUBJECT DOMAIN] task?” For the
strategic planning phase, a question asked, “Which strategy are you
going to use to [SUBJECT DOMAIN]?” For the strategy implementation
phase, a reminder saying, “Stick to the strategy you planned” was pre-
sented instead of a question. For the strategy monitoring phase, a
question asked, “Do you think [SUBJECT DOMAIN] strategy you plan-
ned was appropriate for [SUBJECT DOMAIN] task?” For the strategy
adjustment phase, a question asked, “If you think the strategy does not
t well in the task, why do you not change your strategy?” For the
outcome evaluation phase, a question asked, “Do you think your
[SUBJECT DOMAIN] is satisfactory and why? If you are not satised
with your [SUBJECT DOMAIN], what would you like to revise in your
next [SUBJECT DOMAIN]?”
In Session 3, the teachers explained the cyclical feature of eight-
phase self-regulated learning with examples of hypothetical students
who knew what self-regulated learning was but failed to circulate the
eight-phase model and demonstrated poor outcomes. Additionally, the
teachers modeled how to circulate the eight-phase model during the task
on thinking aloud. For instance, in Study 1 about writing, the teacher
found the sample topic, “Do we need to use smartphones at school?”
Thereafter, she spoke loudly about how condently she could write an
essay about this topic as the rst self-assessment phase of self-regulated
learning. She then showed that she tries to infer why this topic is
argumentative and worth considering as the second task in the analysis
phase. Once she nished the task analysis, she set a goal to convince
readers to agree with the necessity of using smart phones at school to
search and investigate what students are curious about as the third
phase, goal-setting. Then, she selected the “talking with friends” strategy
to elaborate on her idea and listened to the other opinions regarding the
topic as the fourth strategic planning phase. While directing questions
regarding the topic to other classmates and recording what they said, she
organized supporting evidence to refute the opposing opinion as the fth
strategy implementation phase. After talking with classmates, she wrote
the central argumentative sentences and provided supporting evidence.
While writing, she reread her sentences to monitor her writing (i.e., the
sixth strategy monitoring phase) and nd logical aws—such as irrele-
vant supporting evidence to the main idea—as the seventh strategy
adjustment phase. Lastly, she evaluated her writing for coherence,
grammatical errors, and extent of supporting evidence as the outcome
evaluation phase.
The STR groups were exposed to the intervention programs identical
to the STR +SRL group except that the teachers did not explicitly
reference self-regulated learning. The REG groups followed regular
classroom instructions in line with the public elementary school
curriculum.
2.4. Measures
Appendix C presents all self-report survey items used in the pre- and
post-tests and their composite reliabilities. Items were translated into
Korean and back-translated into English by two bilingual researchers.
The translated items were reviewed by three elementary school teach-
ers. Based on the teachers’ comments, we modied some of the items to
reect the domain specicity and the level of elementary school stu-
dents’ literacy to the extent that the modication did not alter the
meaning of the original item. Identical items referring to each domain
were used for pre- and post-tests. Students responded using a 5-point
Likert scale ranging from 1 (not at all true) to 5 (very true).
2.4.1. Pre- and post-test measures
Both pre- and post-tests consisted of three sections and were processed
in order: (1) self-efcacy for learning measure prior to a task to assess
one’s perceived condence in writing/math/reading, (2) writing/math/
reading achievement test, and (3) self-regulated strategy use and task-
irrelevant thought measures referring to the previous test. Our primary
dependent variables, self-regulated strategy use and task-irrelevant
thoughts, were in the third section to increase the accuracy of students’
item responses about the writing task. Self-efcacy for learning was
measured using ve items developed by Bong et al. (2012). Self-regulated
strategy use was measured using eight items developed and used by Shell
and Husman (2008). Students’ task-irrelevant thoughts were assessed
using ve items by Linnenbrink et al. (1999). These measures have been
extensively used and validated in multiple studies conducted within the
education system of South Korea (e.g., Lee & Bong, 2022; Lee et al., 2021;
Shin et al., 2023). The domain-specic pre- and post-achievement tests are
elucidated in the Method sections of each study.
M. Lee et al.
Learning and Instruction 88 (2023) 101810
6
2.4.2. Every-session measures
In Studies 2 and 3, but not in Study 1, one item for each of the task-
irrelevant thoughts (“I thought about things other than solving the word
problem”) and self-efcacy (“I am condent that I can solve the word
problem”) was measured for each session to monitor students’ changes
in attention and motivation across the six intervention sessions. Stu-
dents’ performance was also assessed every session.
2.4.3. Fidelity measures
To assess the delity of program implementation, teachers of the STR
and STR +SRL groups reported in their checklists (1) whether they
covered all material in the student worksheets and (2) delivered in-
structions in the lesson plans after each session. Both items were rated on
a 3-point scale ranging from 0 (not at all) to 2 (completely). Addition-
ally, the teachers personally communicated to a member of the research
team regarding whether their implementations were satisfactory and the
reasons why they felt so. The frequency of this personal communication
was daily, unless the teachers were occupied with other responsibilities.
The teachers were requested to transmit the completed checklist for the
day to the research team during this communication. When the teachers
forgot to complete the checklist, they retrospectively provided answers
during the daily communication, and the research team documented
their responses. The ratings on the checklist completed by the teachers
reveal that the teachers in both groups adhered to the intervention
procedures (M
all
=1.91, SD
all
=0.12; M
STR
=1.90, SD
STR
=0.17; M
STR +
SRL
=1.92, SD
STR +SRL
=0.08). After completing the intervention pro-
grams, student worksheets that guided the sessions were collected.
Based on all the indicators of delity, we concluded that the programs
were implemented as intended.
3. Study 1: self-regulated learning intervention in writing
In Study 1, we developed a self-regulated learning intervention in the
writing domain, specically persuasive writing. Both the STR and STR
+SRL groups were instructed regarding three writing strategies (i.e.,
brainstorming, mind mapping, and having a conversation about the
topic with friends) and how to write a persuasive essay. During the last
week of interventions, they practiced writing persuasive essays daily.
However, two differences existed in the intervention programs between
the two groups. The STR +SRL group was taught the primary features of
self-regulated learning and how to apply self-regulated learning in
writing during the rst three sessions, while the STR group received
regular classroom instructions. Additionally, the STR +SRL group
practiced writing, using three strategies embedded in the eight-phase
model of self-regulated learning (Appendix A), while the STR group
practiced writing with a focus on using the strategies.
3.1. Method
3.1.1. Participants and procedure
We conducted an a priori power analysis to dene the sample size
using G*Power (Faul et al., 2007) with the input parameters—effect size
f =0.22 (effect size of self-regulated learning interventions for
elementary school students on reading/writing performance from
Dignath et al.’s [2008] meta-analysis),
α
=0.05, power (1-β) =0.80,
number of groups =3, correlations between repeated measures =
.50—in a mixed within-between-subject design. The analysis suggested
that 54 participants were needed. Considering the nature of the
quasi-experimental design, 70 fth graders (38 boys, 32 girls; mean age
=10.46) from three classrooms at a public elementary school in the
suburb of Uijeongbu-si, South Korea, participated in the study. Each
class was randomly assigned into one of the REG (n =23), STR (n =24),
and STR +SRL (n =23) groups.
The STR +SRL program’s duration was three weeks (Week 1: Ses-
sions 1–3, Week 2: Sessions 4–7, Week 3: Sessions 8–12); the STR pro-
gram’s duration was two weeks (Week 2: Sessions 4–7, Week 3: Sessions
8–12), because it did not provide a general introduction to self-regulated
learning in Week 1 (see Appendix B, Table B.1). The REG group followed
the regular writing curriculum during the three weeks the interventions
processed.
3.1.2. Intervention programs
Appendix B.1 lists the program contents used for each of the STR and
STR +SRL groups in Study 1. For the STR +SRL group, the intervention
program started three sessions earlier than the STR group to provide the
overall introduction to self-regulated learning during the rst week
(Sessions 1–3). During Session 1, the STR +SRL group was taught what
self-regulated learning is and why it is important in daily life. In Session
2, the teacher provided a detailed instructions about the specics of
eight-phase self-regulated learning in the writing domain using a
worksheet developed by the research team and elementary school
teachers. In Session 3, the teacher explained the cyclical feature of eight-
phase self-regulated learning with examples of hypothetical students
who knew what self-regulated learning was but failed to circulate the
eight-phase model and demonstrated poor writing.
After being introduced to self-regulated learning, students were
taught three writing strategies, including brainstorming, mind mapping,
and conversing about the topic with friends in Sessions 4 and 5. Teachers
introduced these strategies individually and had students practice them
when writing their essays. While writing, students received a worksheet
encouraging them to remember and apply the eight-phase self-regulated
learning in addition to the strategies. The worksheet comprised a simple
gure summary of the eight-phase self-regulated learning principles and
a space to practice brainstorming, mind mapping, and/or talking with
friends about strategies. After the introduction to strategies, students
were instructed regarding the specics of writing an essay during Ses-
sions 6 and 7. The sessions covered logistics and know-how regarding
writing a persuasive essay, including what persuasive essays are, why
they are necessary, what their main features are, their format, and how
to compose one. These factors form part of the regular elementary school
curriculum and the writing textbook. While providing instructions, the
teacher attempted to clarify the connection between three writing
strategies and the eight-phase self-regulated learning model she taught
in previous sessions.
Once all the instructions were delivered, students practiced their
writing daily for 40 min using three writing strategies and the eight-
phase self-regulated learning in Sessions 8–12. Throughout the ve
sessions, students wrote a persuasive essay every day about the
following topics: “Is studying very important in our lives?”; “Are
smartphones benecial to us?”; “Is Simcheong in the traditional fairy
tale a devoted or a selsh daughter?”; “Is it okay to use internet terms in
daily life?”; and “Are exams necessary for us?” All writing topics were
relevant to students’ daily lives and potentially controversial to make
students provide reasonable evidence to support their argument. Stu-
dents received a worksheet to guide the eight-phase self-regulated
learning and strategy uses. The left side of the worksheet visualized the
eight-phase self-regulated learning with a hopscotch pattern and asked
students to write their answers about each phase. The right side was
empty to encourage students to use writing strategies freely. After each
writing practice, the teacher gave verbal feedback on students’ self-
regulated learning (e.g., your goal was too vague to achieve in this
writing task; you appeared to forget the cyclical feature of self-regulated
learning) without commenting on the writing quality per se.
For the STR group, the intervention program started one week later
than the STR +SRL group because they did not receive any explanation
or instruction about self-regulated learning (i.e., Sessions 1–3). In Ses-
sion 4, the teacher focused only on using three writing strategies. During
writing practice, the STR group received a worksheet containing only
empty spaces to facilitate students’ application of the writing strategy.
The teacher did not give any feedback about student writing. For the
REG group, the teacher explained the three writing strategies and how to
write a persuasive essay that the two intervention groups were taught in
M. Lee et al.
Learning and Instruction 88 (2023) 101810
7
line with the public elementary school curriculum. However, the REG
group did not receive everyday writing practices or explicit instructions
about self-regulated learning and strategies reminding them of strategy
uses while writing.
3.1.3. Writing performance measures
Writing topics presented in pre- and post-tests were both retrieved
from Koran National Elementary School Curriculum on Language Art.
Three elementary school teachers rated students’ writing performance
on four dimensions: (1) presence of reasonable evidence (0 =no, 1 =
yes), (2) consistency of writing (0 =inconsistent, 1 =consistent), (3)
clear paragraph division (0 =no, 1 =yes), and (4) composition of
introduction, body, and conclusion (0 =no, 1 =yes). The mean score of
the four dimensions was used as a writing performance indicator. Fleiss’
Kappa coefcient for inter-rater reliability among the three teachers was
0.89.
3.2. Results
3.2.1. Descriptive statistics and randomization check
Table 1 presents the descriptive statistics for all variables measured
at pre- and post-tests in Study 1. As a randomization check, we con-
ducted one-way analyses of variance (ANOVAs) on the pre-test scores.
Task-irrelevant thoughts (p =.26,
η
2
=0.04) and writing performance
(p =.25,
η
2
=0.04) did not show signicant group differences. However,
despite the random assignment of classes, the STR group showed higher
self-regulated strategy use (F[2, 67] =4.51, p =.02,
η
2
=0.12) and self-
efcacy (F[2, 67] =8.08, p <.01,
η
2
=0.19) scores than both the REG
and STR +SRL groups. The REG and STR +SRL groups did not differ in
these scores (ps >.12).
3.2.2. Effects of the intervention program on changes from pre-to post-test
scores
Given the nested data structure and the difference in pre-test scores
in self-regulated strategy use and self-efcacy, we conducted mixed
linear modeling on each dependent variable (i.e., self-regulated strategy
use, performance, task-irrelevant thoughts, and self-efcacy) via SPSS
26.0 Windows Mixed Linear Model interface (Peugh & Enders, 2005).
More precisely, we rst tested the unconditional model for each post-test
score of dependent variables without the time (i.e., pre- and post-test)
and group (i.e., REG, STR, and STR +SRL) variables to assess their
means and the intra- and interindividual variances. With these vari-
ances, intraclass correlation coefcients (ICCs) of dependent variables
were calculated (see Appendix C). Then, we tested conditional models
with xed effects of time, group, and time ×group interaction and a
random effect of participants for each dependent variable. In doing so,
we could consider potential dependences between repeated measures
nested in an individual. Our primary focus was the extent to which the
time ×group interaction would be signicant. The results would imply
that changes in dependent variables from pre-to post-test scores differ by
group.
Parameter estimates from the mixed linear models are presented in
Supplementary Information 1. The results showed that there were sig-
nicant time ×group interactions in self-regulated strategy use, F(2,
69.98) =5.43, p <.01, and writing performance, F(2, 70) =19.21, p <
.01, though not in task-irrelevant thoughts, F(2, 69.55) =0.49, p =.62,
and self-efcacy, F(2, 70) =1.37, p =.26 (see Fig. 1). More specically,
students in the STR +SRL group increased their self-regulated strategy
use, whereas those in the STR group did not (Estimate [Est.] =0.79,
Standard Error [SE] =0.24, t =3.29, p <.01, 95% Condence Interval
[CI] =[0.31, 1.27]). The STR +SRL group also showed enhanced
writing performance from pre-to post-test scores more steeply than the
REG (Est. =0.49, SE =0.09, t =5.58, p <.01, 95% CI =[0.31 0.66]) and
STR (Est. =0.45, SE =0.09, t =5.15, p <.01, 95% CI =[0.27, 0.62])
groups.
4. Study 2: self-regulated learning intervention in mathematics
In Study 2, we developed a self-regulated learning intervention in the
mathematics domain, particularly in solving word problems. A
remarkable change in the intervention program was that instructions
about problem-solving strategies (i.e., drawing a diagram, making a
table, nding a rule) and the cyclical model of self-regulated learning
were integrated within each session across the intervention, rather than
separating them from each other. Thus, problem-solving strategies were
expected to be better absorbed in the self-regulatory processes. The
disparate number of sessions between the STR and STR +SRL groups
was also partially ameliorated in Study 2. One notable difference in
measurement between Studies 1 and 2 was that, in the latter, we addi-
tionally assessed every session for self-efcacy, task-irrelevant thoughts,
and word problem-solving performance. In doing so, we expected to
monitor the students’ gradual changes in primary learning outcomes
over the course of the intervention.
4.1. Method
4.1.1. Participants and procedure
A total of 69 fourth graders (37 boys, 32 girls; mean age =9.78) from
three classrooms at a public elementary school in the suburb of Daegu-si,
South Korea, participated in Study 2. Although the suggested sample
size by G*Power was 15 based on the mean effect size f =0.49 from the
meta-analysis (Dignath et al., 2008), due to the quasi-experimental
design, 69 students participated in the study. Each class was randomly
assigned to one of the REG (n =21), STR (n =22) and STR +SRL (n =
Table 1
Descriptive statistics of pre- and post-test measures by group.
Variable Study 1: Writing (N =70) Study 2: Mathematics (N =69) Study 3: Reading (N =75)
REG (n =23) STR (n =24) STR +SRL
(n =23)
REG (n =21) STR (n =22) STR +SRL
(n =26)
REG (n =25) STR (n =25) STR +SRL
(n =25)
M SD M SD M SD M SD M SD M SD M SD M SD M SD
Pre-test
Self-regulated strategy use 2.89 0.65 3.48 0.70 3.02 0.78 3.36 0.69 3.22 0.71 2.91 0.89 2.83 0.95 2.91 0.90 3.23 0.65
Task-irrelevant thoughts 1.90 0.87 1.62 0.72 1.53 0.73 2.14 0.95 2.24 1.05 2.72 1.17 1.63 0.69 1.78 0.61 1.81 0.80
Self-efcacy 3.28 0.65 4.03 0.65 3.57 0.62 3.53 0.88 3.76 1.20 3.77 0.89 3.61 0.84 3.52 0.76 3.70 0.72
Performance 0.38 0.30 0.28 0.28 0.42 0.31 0.39 0.17 0.52 0.25 0.46 0.23 0.84 0.19 0.86 0.15 0.89 0.13
Post-test
Self-regulated strategy use 2.94 0.58 3.19 0.73 3.52 0.82 3.54 0.78 3.08 0.86 3.68 0.70 2.57 0.97 2.74 0.78 3.23 0.86
Task-irrelevant thoughts 1.84 0.80 1.60 0.70 1.67 0.78 2.12 0.84 1.98 0.88 1.32 0.91 2.17 0.88 2.10 0.77 1.46 0.56
Self-efcacy 3.55 0.71 4.06 0.70 3.59 0.76 3.61 0.80 3.59 1.11 3.48 1.09 3.50 0.95 3.44 0.80 3.75 0.82
Performance 0.35 0.29 0.29 0.23 0.88 0.22 0.41 0.16 0.54 0.22 0.61 0.24 0.78 0.21 0.82 0.19 0.90 0.11
Note. All variables except for performance scores were rated on a 5-point Likert scale. Study 1 writing performance was ranged from 0 to 10. Studies 2 and 3 per-
formance scores ranged from 0 to 1. REG =regular classroom instruction; STR =strategy instruction; STR +SRL =strategy and self-regulated learning instruction.
M. Lee et al.
Learning and Instruction 88 (2023) 101810
8
26) groups. The duration of both intervention programs was three weeks
(Week 1: Sessions 1 & 2, Week 2: Sessions 3 & 4, Week 3: Sessions 5 & 6)
(for detailed program content, see Appendix B; Table B.2).
4.1.2. Intervention programs
Appendix B.2 lists the program content for each of the STR and STR
+SRL groups. We selected three representative strategies, i.e., drawing
a diagram, making a table, and nding a rule, which were known to be
widely used in solving mathematics word problems. Examples and
representative cases provided during the instruction and worksheets
also referred to mathematics word problems. Although almost all the
instructional format and ow was similar to those of Study 1, except for
the domain specicity, a few modications were inevitable given that
understanding, memorizing, and applying the cyclical eight-phase
model via only three consecutive sessions could be overwhelming,
particularly for elementary school students. Thus, intervention
programs used in Study 2 had two primary differences compared to
Study 1: (1) Self-regulated learning instructions for the STR +SRL group
were spread out throughout the session rather than intensively delivered
at the beginning of the intervention, and (2) practice sessions in both the
STR and STR +SRL groups were accompanied by each of the strategy
instructions rather than being consecutively separated as practice-only
sessions. By interleaving self-regulated learning instructions and prac-
tice sessions with strategy instructions, students were expected to
remember the eight-phase self-regulated learning while practicing
strategies and be accustomed to the self-regulated learning and strate-
gies in a more embedded way throughout the sessions.
For the STR +SRL group, the intervention program started with an
introduction to self-regulated learning and the rst strategy−drawing a
diagram−simultaneously. In Session 1, the STR +SRL group was taught
this strategy to solve mathematics word problems. The teacher gave an
instruction about when and how drawing a diagram can be used when
Fig. 1. Study 1: Estimated group means for the pre- and post-test scores of self-regulated strategy use and performance in the writing domain. Note. REG =regular
classroom instruction; STR =strategy instruction; STR +SRL =strategy and self-regulated learning instruction.
Table 2
Descriptive statistics of during session measures by group.
Variable Session Study 2: Math Study 3: Reading
STR (n =22) STR +SRL (n =26) STR (n =25) STR +SRL (n =25)
M SD M SD M SD M SD
Task-irrelevant thoughts Session 1 2.00 1.27 2.20 1.38 1.93 0.73 1.79 0.92
Session 2 2.41 1.30 1.73 1.22 1.69 0.70 1.53 0.77
Session 3 2.48 1.44 1.80 0.96 2.08 1.16 1.72 0.79
Session 4 2.45 1.18 1.44 0.96 2.39 0.89 1.68 0.75
Session 5 2.14 1.31 1.77 1.18 2.46 0.83 1.72 0.79
Session 6 2.14 1.31 1.54 1.03 2.26 0.92 1.58 0.72
Self-efcacy Session 1 3.00 1.23 3.96 1.14 3.57 0.76 3.84 0.76
Session 2 2.73 1.28 3.61 1.39 3.88 0.72 3.89 1.10
Session 3 2.76 1.30 3.04 1.24 3.42 0.51 3.80 1.19
Session 4 2.68 1.13 3.68 1.38 3.35 0.49 4.00 0.91
Session 5 2.86 1.35 3.91 1.09 3.08 0.65 3.80 1.00
Session 6 3.00 1.14 3.92 1.26 3.22 0.85 3.79 0.88
z-Scored Performance Session 1 −0.10 1.00 0.09 1.02 −0.14 1.11 0.14 0.87
Session 2 −0.00 0.95 0.00 1.06 −0.08 0.96 0.09 1.05
Session 3 −0.03 1.02 0.03 1.00 −0.29 1.10 0.27 0.83
Session 4 −0.14 1.07 0.12 0.94 −0.28 1.23 0.26 0.64
Session 5 0.22 0.93 −0.18 1.04 −0.39 1.05 0.38 0.81
Session 6 −0.08 1.05 0.06 0.97 −0.34 1.26 0.32 0.51
Note. REG =regular classroom instruction; STR =strategy instruction; STR +SRL =strategy and self-regulated learning instruction.
M. Lee et al.
Learning and Instruction 88 (2023) 101810
9
students solve mathematical word problems. After a general instruction
about the strategy, the teacher went through the sample word problem
using the drawing of a diagram strategy using a think-aloud method.
After the strategy instruction and modeling, what self-regulated learning
is and why it is important in daily life were taught in a more brief
manner compared to Study 1. Students were also taught about the eight-
phases of self-regulated learning and how they could be applied to
mathematics word problems. The teacher emphasized that drawing a
diagram could be selected as one of the strategies in the fourth pha-
se—planning a strategy. In Session 2, students practiced drawing a di-
agram while solving four math word problems within the framework of
eight-phase self-regulated learning. The teacher provided students with
a worksheet containing four math word problems. For each problem, the
eight-phase self-regulated learning model was presented accordingly.
The teacher reminded the students about each of the eight phases and
encouraged them to monitor their self-regulated learning during each
question. In Session 3, the teacher introduced the second strategy,
making a table, and how the eight phases circulate during problem-
solving. The teacher explained the cyclical nature of eight-phase self-
regulated learning with examples of hypothetical students who knew
what self-regulated learning was, but failed to circulate the eight-phase
self-regulated learning and achieved poor problem-solving. In Session 4,
students solved four word problems using the making-a-table strategy
within the eight-phase self-regulated learning cycle with the worksheet
as they did in Session 2. In Session 5, the last strategy—nding a rule-
—was introduced and practiced within the eight-phase self-regulated
learning cycle. The worksheet was also provided to make students aware
of the self-regulated learning cycle while solving each word problem. In
Session 6, the last session, students solved four word problems and were
asked to choose one of the strategies they had learned. The teacher kept
reminding them of the eight-phase self-regulated learning model and
had them monitor their phase and circulate the phases. In Sessions 4 to
6, the teacher gave individual verbal feedback, focusing on self-
regulated learning based on the student worksheets without
mentioning whether student responses were correct or incorrect.
For the STR group, the teacher introduced and modeled three
problem-solving strategies. Every session, the STR group received a
worksheet with four math word problems similar to the STR +SRL
group, but without the eight-phase model. The teacher focused only on
using the three problem-solving strategies. The teacher did not give any
feedback about students’ problem-solving. For the REG group, the
teacher explained three problem-solving strategies and how to choose
appropriate strategies to solve word problems that the two intervention
groups were taught in line with the public elementary school curricu-
lum. However, the REG group did not receive additional problem-
solving practice or self-regulated learning and strategy instructions
reminding them of strategy uses while solving word problems.
4.1.3. Mathematics performance measures
Students’ performance in math word problems before and after the
interventions were measured using 12 short-answer questions devel-
oped by the school teachers. The difculty level of the pre- and post-test
problems was equivalent as we modied the numerical values of iden-
tical word problems. The mean score of each item accuracy, coded 0 =
incorrect and 1 =correct was used as a math word problem performance
indicator. Throughout six sessions, different sets of four mathematical
word problems were assessed based on which were most effectively
solved using the acquired strategy during that particular session. For
instance, during the session on the “nding-a-rule” strategy, students
were asked to solve four word problems that could be solved best by
utilizing that specic strategy. Although we designed sessions to be
equally difcult, both groups of students showed decreased accuracy
during the fourth session. Thus, the mean score of each item’s accuracy
was standardized to control for difculty.
4.2. Results
4.2.1. Descriptive statistics and randomization check
Table 1 reports the descriptive statistics for all variables measured at
pre- and post-tests, and Table 2 presents the descriptive statistics for
every-session measures in Study 2. One-way ANOVAs on pre-test scores
were conducted for a randomization check. There were no signicant
between-group differences in all measured variables, including self-
regulated strategy use (p =.14,
η
2
=0.06), task-irrelevant thoughts
(p =.14,
η
2
=0.06), self-efcacy (p =.67,
η
2
=0.01), and math per-
formance (p =.17,
η
2
=0.05).
4.2.2. Effects of the intervention program on changes from pre-to post-test
scores
Parameter estimates from the mixed linear models are presented in
Supplementary Information 2. The results showed that there were sig-
nicant time ×group interactions in self-regulated strategy use, F(2,
69) =8.44, p <.01, task-irrelevant thoughts, F(2, 69) =5.35, p <.01,
and math performance, F(2, 69) =6.19, p <.01, although not in self-
efcacy, F(2, 69) =1.84, p =.17 (see Fig. 2). More precisely, students
in the STR +SRL group increased their self-regulated strategy use,
whereas those in the REG (Est. =0.58, SE =0.23, t =2.57, p =.01, 95%
CI =[0.13, 1.04]) and STR (Est. =0.91, SE =0.23, t =4.02, p <.01,
95% CI =[0.46, 1.35]) groups did not. The STR +SRL group showed
reduced task-irrelevant thoughts in comparison with the REG (Est. =
−0.79, SE =0.25, t = − 3.14, p <.01, 95% CI =[−1.29, −0.29]) and STR
groups (Est. = − 0.55, SE =0.25, t = − 2.23, p =.03, 95% CI =[−1.05,
−0.06]). The STR +SRL group also presented enhanced math perfor-
mance from pre-to post-test scores more steeply than the REG (Est. =
0.14, SE =0.05, t =2.97, p <.01, 95% CI =[0.05, 0.23]) and STR (Est.
=0.14, SE =0.05, t =3.03, p <.01, 95% CI =[0.05, 0.23]) groups.
4.2.3. Effects of the intervention program on changes across six sessions
We conducted mixed linear model analyses including xed effects of
time, group, and time ×group interaction and a random effect of par-
ticipants. This analytic approach would examine the potential differ-
ences between the two intervention groups in the changes in self-
efcacy, task-irrelevant thoughts, and performance throughout six
intervention sessions while controlling for potential dependences be-
tween repeated measures nested in an individual. Our primary focus was
the extent to which the main effects of group and session ×group in-
teractions were signicant. The results would imply that the mean
scores across the six sessions and the changes in the six measures differ
by group. In all three models, session ×group interactions were not
statistically signicant (ps ≥.07), whereas the main effects of group
were signicant for self-efcacy, F(1, 48.73) =9.62, p <.01, and task-
irrelevant thoughts, F(1, 47.48) =4.32, p =.04 (see Fig. 3). This
nding indicates that the STR +SRL group (estimated M =3.69, SE =
0.18) showed a higher mean score on six self-efcacy measures than the
STR group (estimated M =2.85, SE =0.20). In contrast, the STR +SRL
group (estimated M =1.75, SE =0.17) showed a lower mean score on
six task-irrelevant thought measures than the STR group (estimated M =
2.26, SE =0.18).
5. Study 3: self-regulated learning intervention in reading
In Study 3, we developed a self-regulated learning intervention in the
reading domain. Even though the overall structure and procedure of the
intervention were identical to Study 2, we attempted to minimize
additional teacher burden by simplifying teacher instruction and
excluding individual feedback.
5.1. Method
5.1.1. Participants and procedure
A total of 75 sixth graders (39 boys, 36 girls; mean age =11.35) from
M. Lee et al.
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three classes at a public elementary school in the suburb of Daegu-si,
South Korea, participated in Study 3. Each class was randomly
assigned to one of the REG (n =25), STR (n =25) and STR +SRL (n =
25) groups. The duration of the STR +SRL intervention was four weeks
(Week 1: Sessions 1 & 2, Week 2: Sessions 3 & 4, Week 3: Sessions 5–7,
Week 4: Session 8), and that of the STR intervention was three weeks
(Week 1: Sessions 1 & 2, Week 2: Sessions 3 & 4, Week 3: Sessions 5–7)
(for detailed program contents, see Appendix B; Table B.3).
5.1.2. Intervention programs
Appendix B.3 lists the program content used for each of the STR and
STR +SRL groups. We selected the Think Before, While, and After
(TWA) reading strategy, which has been widely used in elementary
school children’s reading comprehension (Mason, 2013). It consists of
nine specic strategies, including thinking about “the author’s purpose,”
“what you know,” “what you want to know,” “reading speed,” “linking
knowledge,” “rereading parts,” “the main idea,” “summarizing infor-
mation,” and “what you learned.” These nine strategies have been
deemed independent of each other (Mason, 2013). For this reason, the
TWA strategy has been introduced as an overarching term to motivate
students to utilize one of the nine strategies during the process of reading
(Mason, 2004), as demonstrated in the current study. Examples and
representative cases distributed during the instruction and worksheets
also referred to reading comprehension.
Although almost all the instructional formats and ow were similar
to those of Study 2 except for the domain specicity, a few modications
were necessary to decrease the teachers’ instructional burden. In both
Studies 1 and 2, homeroom teachers took charge of all instructions and
individualized feedback about student worksheets, which could be time-
and labor-intensive in addition to their ordinary tasks. Thus, to alleviate
teacher workload, intervention programs used in Study 3 had two pri-
mary differences compared to Study 2: (1) Teacher instructions were
concisely delivered within 10 min per session, and (2) detailed infor-
mation about self-regulated learning and strategies was presented in
student worksheets. The teachers were expected to remind students of
strategies and self-regulated learning when students read texts and
solved reading comprehension problems presented in the worksheets.
For the STR +SRL group, the intervention program started with an
introduction to the TWA strategy (Mason, 2013). In Session 1, the STR +
SRL group was taught about what the TWA strategy is and why it is
necessary to comprehend a text better. The teacher gave precise in-
structions about when and how the TWA strategy can be used while
students read a text. Students modeled how the teacher used the TWA
strategy while reading a sample text. In Session 2, the teacher provided
instruction about what self-regulated learning is and why it is important
in their daily life in a similar manner to Study 2. Students were also
Fig. 2. Study 2: Estimated group means for the pre- and post-test scores of self-regulated strategy use, task-irrelevant thoughts, and performance in the mathematics
domain.
Note. REG =regular classroom instruction; STR =strategy instruction; STR +SRL =strategy and self-regulated learning instruction.
M. Lee et al.
Learning and Instruction 88 (2023) 101810
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taught about the eight-phases of self-regulated learning and how it could
be applied to reading text. The teacher emphasized that the TWA
strategy could be selected as useful in the fourth phase of the eight-phase
self-regulated learning, planning a strategy. In Session 3, students
practiced the TWA strategy and got used to the eight-phase self--
regulated learning while reading a news article. The teacher provided
students with a worksheet containing seven problems, measuring
reading comprehension of a news article, and a brief diagram of the
eight-phase self-regulated learning model. The teacher briey reminded
each student of the eight phases and encouraged them to monitor their
self-regulated learning phase while reading the news article using the
TWA strategy. In Session 4, the teacher briey explained the cyclical
feature of eight-phase self-regulated learning and provided the same
form of worksheet as that of Session 3. After a brief explanation, students
were asked to read a discussion paper and solve six reading compre-
hension problems using the TWA strategy, focusing on the cyclical
feature of self-regulated learning and maintaining the cycle promptly. In
Session 5, students read a story text and solved six reading compre-
hension problems using the TWA strategy within the eight-phase cycle.
A worksheet was also provided to make students aware of the
self-regulated learning cycle while solving each reading comprehension
problem. In Session 6, students read the other story text and solved eight
reading comprehension problems using the TWA strategy embedded in
the eight-phase self-regulated learning cycle with the worksheet. The
teacher reminded the students that the focus of the practice was to di-
agnose one’s phase accurately and return to the accurate phase. In
Session 7, students read an essay text and solved eight reading
comprehension problems using the TWA strategy within the framework
of the eight-phase model. In Session 8, students read an expository text
and solved nine problems using the TWA strategy embedded in the
eight-phase self-regulated learning model.
For the STR group, the teacher introduced and modeled the TWA
strategy while reading a sample text. During every session, the STR group
received a worksheet with the reading text and comprehension problems
similar to the STR +SRL group, but without the eight-phase self-regulated
learning model. The teacher focused only on using the TWA strategy. For
the REG group, the teacher explained several strategies to read accurately
in line with the public elementary school curriculum, such as underlining
the main idea, mind mapping, and summarizing, but did not explicitly
deal with the TWA strategy. The REG group did not receive additional
reading practice or self-regulated learning and strategy instructions
reminding them of strategy uses while reading.
5.1.3. Reading performance measures
Students’ reading comprehension performance before and after the
interventions were assessed using eight items which were combinations
of multiple-choice and short-answer questions developed by the school
teachers. The reading texts and comprehension questions utilized were
sourced from a test question bank developed for teachers. The mean
score of each item’s accuracy was coded as 0 =incorrect and 1 =correct,
which were used as performance indicators. Students’ reading
Fig. 3. Study 2: Estimated group means of self-efcacy and task-irrelevant
thoughts throughout the six sessions in the mathematics domain. Note. STR
=strategy instruction; STR +SRL =strategy and self-regulated learning
instruction.
Table 3
Average Cohen’s ds of Dependent Variables and 95% Condence Intervals (CIs).
Comparison Dependent variable Average d (SE) p 95% CI z Q df p I
2
STR +SRL vs. REG Self-regulated strategy use 0.56 (0.17) < .01 [0.22 0.90] 3.27 1.63 2 .44 0.00
Task-irrelevant thoughts ¡1.00 (0.40) .01 [-1.78–0.22] −2.52 9.65 2 .01 79.27
Self-efcacy 0.30 (0.17) .08 [-0.03 0.63] 1.76 0.27 2 .87 0.00
Performance 0.96 (0.44) .03 [0.11 1.81] 2.21 11.63 2 <.01 82.80
STR +SRL vs. STR Self-regulated strategy use 0.79 (0.31) .01 [0.18 1.39] 2.56 6.22 2 .05 67.84
Task-irrelevant thoughts ¡0.82 (0.32) .01 [-1.44–0.20] −2.58 6.61 2 .04 69.75
Self-efcacy 0.10 (0.17) .57 [-0.23 0.42] 0.58 0.13 2 .94 0.00
Performance 0.94 (0.49) .05 [-0.01 1.89] 1.93 14.70 2 <.01 86.40
STR vs. REG Self-regulated strategy use 0.33 (0.17) .06 [-0.01 0.66] 1.92 1.07 2 .59 0.00
Task-irrelevant thoughts −0.20 (0.17) .24 [-0.53 0.13] −1.17 0.37 2 .83 0.00
Self-efcacy 0.21 (0.17) .23 [-0.13 0.54] 1.21 0.61 2 .74 0.00
Performance 0.09 (0.17) .61 [-0.25 0.42] 0.51 0.14 2 .94 0.00
Note. Bold fonts are statistically signicant average Cohen’s ds at ps <.10. SE =standard error; CI =condence interval; REG =regular classroom instruction; STR =
strategy instruction; STR +SRL =strategy and self-regulated learning instruction.
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Learning and Instruction 88 (2023) 101810
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performances were assessed every session with 6–9 items testing reading
comprehension. The mean score of each item’s accuracy was standard-
ized to control for difculty.
5.2. Results
5.2.1. Descriptive statistics and randomization check
Table 1 shows the descriptive statistics for all variables measured at
pre- and post-test, and Table 2 presents the descriptive statistics for
every-session measures in Study 3. One-way ANOVAs on pre-test scores
were conducted to check for randomization. There were no signicant
between-group differences in all measured variables, including self-
regulated strategy use (p =.21,
η
2
=0.04), task-irrelevant thoughts
(p =.65,
η
2
=0.01), self-efcacy (p =.69,
η
2
=0.01), and reading
performance (p =.53,
η
2
=0.02).
5.2.2. Effects of intervention programs on changes from pre-to post-test
scores
Parameter estimates from the mixed linear models are presented in
Supplementary Information 3. The results showed that there was a sig-
nicant time ×group interaction in task-irrelevant thoughts, F(2, 75) =
7.31, p <.01, although not in self-regulated strategy use, F(2, 75) =
0.60, p =.55, self-efcacy, F(2, 75) =0.33, p =.72, and reading per-
formance, F(2, 75) =0.94, p =.40 (see Fig. 4). More precisely, students
in the STR +SRL group showed a steeper decrease in task-irrelevant
thoughts than the REG (Est. = − 0.89, SE =0.24, t = − 3.66, p <.01,
95% CI =[−1.37, −0.40]) and STR (Est. = − 0.68, SE =0.24, t = − 2.80,
p <.01, 95% CI =[−1.16–0.20]) groups.
5.2.3. Effects of intervention program on changes across six sessions
We conducted mixed linear model analyses with three dependent
variables (i.e., self-efcacy, task-irrelevant thoughts, performance)
measured across six sessions. In all three models, session ×group in-
teractions were not statistically signicant (ps ≥.13), whereas the main
effects of group were signicant in task-irrelevant thoughts, F(1, 50.86)
=9.78, p <.01, and standardized reading performance, F(1, 53.80) =
6.72, p =.01 (see Fig. 5). These ndings indicate that the STR +SRL
group (estimated M =1.67, SE =0.12) showed a lower mean score of six
task-irrelevant thought measures than the STR group (estimated M =
2.22, SE =0.13). On the contrary, the STR +SRL group (estimated M =
0.23, SE =0.14) showed a higher mean score of six performance mea-
sures than the STR group (estimated M = − 0.27, SE =0.14).
6. Meta-analyses of intervention effects on dependent variables
To synthesize the results from the three studies effectively, we con-
ducted meta-analyses using Comprehensive Meta-Analysis Version 4.0
software (Borenstein, 2022) and reported the integrated standardized
effect sizes (Cohen’s ds) in Table 3. For the dependent variables whose
heterogeneity measures were statistically signicant, the effect sizes
were integrated using a random-effect model. The results indicated that
there were signicant differences between the STR +SRL and REG
groups in the self-regulated strategy use (d =0.56, SE =0.17, 95% CI =
[0.22 0.90], p <.01), task-irrelevant thoughts (d = − 0.96, SE =0.40,
95% CI =[−1.78–0.22], p =.01), and performance (d =0.99, SE =0.46,
95% CI =[0.09 1.89], p =.03). Self-efcacy showed a marginally sig-
nicant difference between the two groups (d =0.30, SE =0.17, 95% CI
=[−0.03 0.63], p =.08). The STR +SRL group also differed from the
STR group in self-regulated strategy use (d =0.79, SE =0.31, 95% CI =
[0.18 1.39], p =.01), task-irrelevant thoughts (d = − 0.82, SE =0.32,
95% CI =[−1.44–0.20], p =.01), and marginally in performance (d =
1.02, SE =0.55, 95% CI =[−0.06, 2.09], p =.06). The STR and REG
groups showed none of the signicant differences in all dependent
variables (|d|s <0.21, ps >.23), except for the self-regulated strategy
Fig. 4. Study 3: Estimated group means for the pre- and post-test scores of task-
irrelevant thoughts in the reading domain.
Note. REG =regular classroom instruction; STR =strategy instruction; STR +
SRL =strategy and self-regulated learning instruction.
Fig. 5. Study 3: Estimated group means of self-efcacy and standardized per-
formance scores throughout the six sessions in the reading domain.
Note. STR =strategy instruction; STR +SRL =strategy and self-regulated
learning instruction.
M. Lee et al.
Learning and Instruction 88 (2023) 101810
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use reporting a marginally signicant group difference (d =0.33, SE =
0.17, 95% CI =[−0.01 0.66], p =.06).
7. Discussion
There has been a continuous effort to boost younger students’ self-
regulated learning by incorporating domain-specic strategies in their
classroom settings (Sontag & Stoeger, 2015; Stoeger et al., 2014). Taking
one step forward, we developed self-regulated learning interventions in
three core academic domains (i.e., writing, mathematics, and reading)
led by teachers in elementary school classrooms and based on Zim-
merman’s cyclical model (2000). By implementing this approach, the
applicability of interventions can be expanded to encompass multiple
subject domains commonly taught and considered core in elementary
school classrooms, unlike a single-domain approach (e.g., Kolovelonis
et al., 2022; Lau, 2020). Throughout the three studies, our interventions
were benecial for elementary school students to enhance their
self-regulated strategy use and task performance, and to diminish
task-irrelevant thoughts during the task.
7.1. Effectiveness of eight-phase self-regulated learning interventions
The integrated results from the meta-analyses with three data sets in
writing (Study 1), math (Study 2), and reading (Study 3) revealed that
our self-regulated learning interventions were more effective than reg-
ular classroom instructions for elementary school students in enhancing
self-regulated strategy use, performance, and marginally, self-efcacy,
(p =.08) and decreasing task-irrelevant thoughts (see Table 3).
Cohen’s ds were larger than 0.50, except for self-efcacy (d =0.30),
implying that the advantages of our interventions were medium to large
in comparison with regular classroom instructions. These ndings were
not surprising because most educational treatments (i.e., learning skill
interventions) were known to be benecial to some extent compared to
regular classroom instructions, which are the same as no treatment
(Hattie et al., 1996). Thus, intervention studies should retain control
groups exposed to control programs containing the same content and
activities of the intervention programs other than the target treatment,
as well as the no-treatment group. In this respect, the STR groups, who
received instructions about domain-specic strategies but not about
self-regulated learning, played a role as control groups. Throughout the
series of studies, we could observe the relative effectiveness of our
self-regulated learning interventions on self-regulated strategy use,
task-irrelevant thoughts, and marginally, performance (p =.06), over
the strategy-only instructions.
Our ndings echo the importance of connecting self-regulated
learning interventions to the specic subject matter. Self-regulated
learning interventions embracing domain-specic strategies would be
more benecial for elementary school students, who might struggle with
transferring skills and strategies between domains (Dignath & Büttner,
2008; Hattie et al., 1996). Most previous studies have also developed a
self-regulated learning intervention within a single domain and exam-
ined its effects on the domain-specic outcome measures, such as
reading performance or mathematics problem-solving (e.g., Brunstein &
Glaser, 2011; Leidinger & Perels, 2012; Stoeger et al., 2014). This
single-domain approach has been widely adopted to promote students’
near transfer from newly acquired self-regulated learning skills within
the domain to the same or similar areas (Perkins & Salomon, 1989). Still,
the ultimate goal of self-regulated learning interventions is to help stu-
dents apply skills to not only a particular subject domain but also other
school subjects freely and appropriately. To achieve this, Hattie et al.
(1996) highlighted that the interventions should be delivered across all
classes or contexts tailored to each specic domain.
From this perspective, we suggest that the cyclical model of self-
regulated learning can function as a generic framework, encompassing
multiple subject instructions dealing with specic strategies. In our
eight-phase cyclical model, four phases—the fourth to seventh—require
students to be aware of planning, implementing, monitoring, and
adjusting appropriate domain-specic strategies. Based on our non-
signicant group differences between the STR and REG groups, the
regular classroom instructions have already covered a lot of domain-
specic strategies regarding how to write an essay, solve math word
problems, and comprehend text materials (see Table 3). The remaining
four phases—self-assessment, task analysis, goal setting, and outcome
evaluation—are not necessarily specic to a particular domain; rather,
they are more like metacognitive processes applicable to diverse con-
texts and domains as a generic framework. That is, once students catch
the domain-general feature of the cyclical model of self-regulated
learning, they can freely choose and switch appropriate strategies
learned in their classes depending on the task, situation, context, and/or
domain within the self-regulated learning cycle. Thus, it would be
benecial to provide students with explicit instructions about the
cyclical model and each phase of self-regulated learning processes, and
encourage them to apply the cyclical model to diverse subject domains
using acquired strategies.
7.2. Multifaceted cognitive and motivational outcomes
One noticeable outcome measure in the present research was task-
irrelevant thoughts, which were remarkably reduced by our self-
regulated learning interventions during task performance. When circu-
lating the eight phases of self-regulated learning, students concentrate
more on the ongoing task and activate task-relevant thoughts, such as
useful strategies or background knowledge. This nding was consistent
with the results from previous self-regulated learning interventions
developed for university students (Ganda & Boruchovitch, 2018;
Grunschel et al., 2018). These studies indicated that college students
who participated in self-regulated learning interventions exhibited
higher concentration on the task than those in the control groups. The
nding hints at the potential mechanism that underlies the effects of
self-regulated learning intervention, which is mediated by concentration
on the task, subsequently leading to increased strategy uses, motiva-
tional beliefs, and academic performance. While inhibiting
task-irrelevant thoughts and concentrating on a task, students could
reserve enough working memory capacity to monitor, control, and
reect on their performance (Lee et al., 2021; Linnenbrink et al., 1999).
Unexpectedly, our interventions did not demonstrate a boosting ef-
fect on students’ self-efcacy in the subject domains in comparison with
regular classroom instruction and strategy-only instruction. This nding
was incongruent with prior research demonstrating the benets of self-
regulated learning interventions on self-efcacy (Guthrie et al., 2004;
Schünemann et al., 2013). According to Zimmerman’s (2013) concep-
tual foundations of self-regulated learning, self-efcacy as a subjective
belief about one’s learning and performance in a particular domain
might play a key role in successful self-regulatory processes. It functions
as a core impetus to initiate and sustain self-regulated learning
throughout the learning processes. Even though we could only nd a
marginally signicant group difference between the STR +SRL and REG
groups in the post-test self-efcacy score, the composite scores of
every-session self-efcacy measures showed that the STR +SRL groups
reported higher self-efcacy scores than the STR groups across the six
sessions in both Study 2 and 3. From this nding, we had to admit that
students’ self-efcacy in a subject domain (i.e., writing, math, or
reading) is difcult to change using our self-regulated interventions.
However, students’ at-the-moment context-specic efcacy belief—-
whether they believe that they can successfully write about a particular
topic, solve a math problem, or comprehend a presented text—can be
enhanced. Another possibility is that students’ self-efcacy for
self-regulated learning might be increased rst and then transferred to
domain-level self-efcacy (Ganda & Boruchovitch, 2018; Zimmerman
et al., 1992). Further research needs to address the role of self-efcacy
for self-regulated learning as an integral outcome of self-regulated
learning interventions.
M. Lee et al.
Learning and Instruction 88 (2023) 101810
14
7.3. Potential practical implications of teacher-led classroom
interventions
It is noteworthy that elementary school teachers were invited at the
beginning of the intervention development with researchers as part of
the teacher professional development program. In accordance with
previous meta-analytic studies, one of the most consistent ndings in
self-regulated learning interventions was that teacher-led interventions
were less effective than researcher-led ones (e.g., Dignath & Büttner,
2008). There could be several reasons, although we focused on the
possibility that the separation between intervention developers, mostly
researchers, and intervention operators, mostly teachers (De Corte,
2000), can minimize experimenter bias threatening the internal validity
of experiments. However, researchers who focus on theoretical and
empirical rigor might easily underestimate the dynamic variability in
classroom settings, such as the principal’s or parents’ interference.
Teachers who focus on implementation without sufcient background
knowledge about the construct and experimental design might under-
estimate the potential effects of subtle changes in the program or dif-
ferences in nuances of their explanation. To prevent this possibility, the
teachers who participated in our studies actively voiced their opinion
about program content and procedures, as well as administrative work
to convince parents and principals. Throughout the interactive discus-
sion between the researchers and teachers, the ecological validity and
replicability of the current interventions could be enhanced in Korean
elementary school contexts.
We could also expect that teachers’ depth of understanding about
self-regulated learning can be boosted by program participation. A few
studies have highlighted that teachers tend to have false beliefs about
self-regulated learning, such that self-regulated learning is likely to be
unteachable (Lawson et al., 2019) or that it is the same as
self-directedness (Callan & Shim, 2019). These conceptual confusions
might make teachers reluctant to offer explicit instructions or guidelines
to students about self-regulatory processes during classes. Moreover,
teachers with false beliefs may disparately emphasize the importance of
self-regulated learning for students who they believe self-regulate their
learning. Nonetheless, once teachers participate in the intensive training
sessions to implement the intervention, they can easily revise their be-
liefs and try to implement the self-regulated learning intervention as
accurately as possible (Steinbach & Stoeger, 2016). Although we could
not assess teachers’ belief changes about self-regulated learning, our
intensive one-on-one mentoring session as part of the teacher profes-
sional development program could be expected to lead them to better
understand and implement the self-regulated learning cycle in their
classes.
7.4. Limitations and future directions
Despite the signicance of this research, we acknowledge that the
generalizability of our ndings may be restricted to Korean elementary
school contexts. In future research, the effectiveness of our intervention
should be replicated in different cultural and educational settings with
appropriate customization (Harackiewicz & Priniski, 2018). To enhance
the applicability of the interventions across diverse cultures, we
recommend emphasizing the pivotal role of teachers who can timely
prompt and remind students about the cyclical feature of self-regulated
learning throughout classes (Callan et al., 2022). At the outset, teachers
may be burdened with several tasks and initial resistance to incorpo-
rating novel teaching techniques, as we witnessed in our teacher
workshops. However, once convinced, they are more apt to apply the
self-regulated learning cycle to the given subject matter based on their
content knowledge than researchers. Acknowledging and mitigating the
burdensome nature of teaching, dispelling teachers’ misconceptions
about self-regulated learning, and providing comprehensive examples
and interactive communication channels with the research team would
facilitate the implementation of self-regulated learning interventions in
subject-specic classes.
Another potential limitation is that for elementary school students, it
may be quite overwhelming to remember the eight phases of the self-
regulated learning cycle when they are rst introduced. Particularly,
for younger students, having enough time to familiarize themselves with
the eight phases is essential before they are required to apply them to
problem-solving contexts. One way to overcome this limitation would be
to give instruction while parceling up the eight phases into three (i.e.,
forethought, performance control, self-reection) or four (i.e., self- and
task-analysis, goal setting and strategic planning, monitoring and
adjustment, outcome evaluation and self-reection) groupings.
Future research must employ a more rigorous longitudinal experi-
mental design to ensure that the amount of instructional length and
presence of teacher feedback are controlled for between the STR and
STR +SRL groups, as these variables could impact the outcomes. The
STR +SRL groups’ extended instructional time dedicated to introducing
and training self-regulated learning could have been balanced by
incorporating other new, neutral skills, such as information-searching or
communication skills for the STR groups. In light of the crucial role that
teacher feedback plays in enhancing student self-regulated learning
(Callan et al., 2022), the presence of teacher feedback can be considered
an additional treatment in future research. It is imperative to examine
the delayed effects of interventions and the underlying psychological
mechanisms by conducting longitudinal studies (Shin et al., 2022).
Future studies can also measure teacher reports about their beliefs
and attitudes about self-regulated learning before and after participating
in the interventions. Based on the expectation that we would not be able
to draw a meaningful conclusion with only nine teachers who partici-
pated in these studies, we did not measure any teacher reports in the
studies except for the delity checklists. We were also concerned about
the possibility that addressing teacher reports would distract the
research focus of developing self-regulated learning interventions in
three academic domains for elementary school students. However, ac-
cording to a previous study (Steinbach & Stoeger, 2016), teachers who
participated in the intervention study might change their beliefs and
attitudes about self-regulated learning and encourage students to use it
in their classrooms. In future research, changes in teachers’ beliefs and
instructional behaviors depending on the participation in intervention
programs must be explored.
The absence of objective delity measures based on classroom ob-
servations is another concern in these studies. The interventions started
in the middle of the COVID-19 pandemic. Under this unexpected
emergency context, schools were extremely sensitive about the spread of
the virus and strictly controlled visitor access. For this reason, teachers’
instructions could not be rated by a third person, although, as comple-
mentary measures, we collected teachers’ self-reported checklists and
students’ activity sheets indicating conrmed delity. For future
research, we suggest including objective delity measures such as a
checklist rated by at least two trained research assistants observing the
intervention sessions (Shin et al., 2019). Following O’Donnell (2008)’s
guidelines, the checklist for assessing the delity of interventions must
be dened a priori with theoretical and operational clarity. It must
measure critical components and processes of both experimental and
comparison conditions with random or complete census sampling.
Through this approach, researchers could screen participants demon-
strating nonadherence to the intervention, which can compromise the
M. Lee et al.
Learning and Instruction 88 (2023) 101810
15
overall efcacy of the intervention (Nagengast et al., 2018). They can
also scrutinize possible challenges to implementing or complying with
the interventions (Brisson et al., 2020; Kline et al., 1992).
8. Conclusion
With an increasing emphasis on life-long education to prepare for the
unpredictable, complex, and rapidly changing society, students are ex-
pected to learn and practice self-regulated learning skills at a young age.
In line with the recent approaches to enhance elementary school stu-
dents’ self-regulated learning, we developed and examined the effects of
three sets of ecologically valid self-regulated learning interventions,
embracing instructions about domain-specic strategies in writing,
mathematics, and reading domains based on Zimmerman’s (2000,
2013) cyclical model. Considered together, the success of our in-
terventions contributes to the current literature in three aspects. Above
all, we found that our eight-phase cyclical model of self-regulated
learning was effective across three different subject domains. It im-
plies that our interventions are compatible with domain-specic in-
structions in multiple subjects by being a generic framework that guides
and prompts self-regulatory learning processes in elementary class-
rooms. Our ndings also reiterate the importance of the teachers’ role in
research-based interventions to increase ecological validity and appli-
cability. Inviting teachers at the beginning of the intervention devel-
opment reduced the possibility of teachers taking a passive and limited
role in implementing the interventions. Teachers’ practical knowledge
about classroom dynamics and administrative procedures should be
welcomed and reected to increase the effectiveness of classroom in-
terventions. We shed light on the potential mechanism that underlies the
relationship between enhanced self-regulated learning and motivational
and cognitive outcomes. The ndings suggest that when focusing on the
self-regulated learning cycle, students are less distracted by
task-irrelevant thoughts, leading to increased performance and
self-regulated strategy use. In future research, our response to the call for
enhancing younger students’ self-regulated learning needs to be repli-
cated and extended in different cultural and educational settings.
Declaration of interest
None.
Funding
This work was supported by the Ministry of Education of the Re-
public of Korea and the National Research Foundation of Korea (NRF-
2021S1A5A8065217).
Data statement
The research data is unavailable to access because it is condential.
CRediT authorship contribution statement
Minhye Lee: Conceptualization, Methodology, Funding acquisition,
Project administration, Supervision, Writing – original draft, Writing –
review & editing. Sun Young Lee: Data curation, Formal analysis,
Investigation, Resources. Ji Eun Kim: Data curation, Formal analysis,
Investigation, Resources. Hyun Jae Lee: Data curation, Formal analysis,
Investigation, Resources.
Appendix A. The Eight-Phase Cyclical Model of Self-Regulated Learning
M. Lee et al.
Learning and Instruction 88 (2023) 101810
16
Appendix B. Program Contents of Intervention Groups
Table B.1
Study 1: Program Contents of Strategy (STR) and Strategy +Self-Regulated Learning (STR +SRL) Intervention Groups in the Writing Domain
Session STR Group STR +SRL Group
1–3 Regular class instruction Introduction to SRL: Teacher instruction about SRL
- What is SRL and why is it important?
- What are the eight phases of SRL?
- How can we use the eight-phase SRL for writing an essay?
- How do the eight phases circulate and interact with each other?
4–5 Practice strategies: Teacher instruction about three writing strategies and practice strategies with a short writing exercise
- Brainstorming
- Drawing a mind map
- Having a conversation about the topic with friends
6–7 How to write a persuasive essay: Teacher instruction about writing a persuasive essay
- What is a persuasive essay and why is it necessary?
- What are the main features of a persuasive essay?
- What is the format and composition of a persuasive essay?
8–12 Writing practice: Write a persuasive essay every day using the three
writing strategies
Writing practice: Write a persuasive essay every day using the three writing strategies and eight
phases of SRL as a whole process
Teacher feedback about student SRL
Table B.2
Study 2: Program Contents of Strategy (STR) and Strategy +Self-Regulated Learning (STR +SRL) Intervention Groups in the Mathematics Domain
Session STR Group STR +SRL Group
1 STR 1 instruction: Overall introduction to the program and teacher instruction
about “drawing a diagram” strategy
STR 1 instruction: Overall introduction to the program and teacher instruction about
“drawing a diagram” strategy
Introduction to SRL: Teacher instruction about SRL
- What is SRL and why is it important?
- What are the eight phases of SRL?
- How can we use the eight-phase SRL for solving math word problems?
2 STR 1 practice: Solve word problems using the “drawing a diagram” strategy STR 1 practice: Solve word problems using “drawing a diagram” strategy
Getting used to the eight-phase SRL: Memorize and get used to the eight phases of SRL
while solving the word problems using STR 1
3 STR 2 instruction: Teacher instruction about the “making a table” strategy STR 2 instruction: Teacher instruction about “making a table” strategy
Introduction to the cyclical model of SRL: Teacher instruction about how the eight phases
circulate and interact with each other
4 STR 2 practice: Solve word problems using “making a table” strategy STR 2 practice: Solve word problems using the “making a table” strategy
Practice SRL cycle I: Practice cyclical SRL while solving the word problems using STR 2
Teacher feedback about student SRL
5 STR 3 instruction & practice: Teacher instruction about “nding a rule”
strategy and student practice
STR 3 instruction & practice: Teacher instruction about “nding a rule” strategy and
student practice
Practice SRL cycle II: Practice cyclical SRL while solving the word problems using STR 3
Teacher feedback about student SRL
6 Solve word problems using the three strategies Solve word problems using three strategies and SRL as a whole process
Teacher feedback about student SRL
Table B.3
Study 3: Program Contents of Strategy and Strategy +Self-Regulated Learning Intervention Groups in the Reading Domain
Session STR Group STR +SRL Group
1 Introduction to TWA strategy: Teacher instruction about the TWA strategy
2 Read a news article using TWA Introduction to SRL: Teacher instruction about SRL
- What is SRL and why is it important?
- What are the eight phases of SRL?
- How can we use the eight-phase SRL for reading a text?
3 Read a discussion paper using the TWA
strategy
Read a news article using TWA strategy
Getting used to the eight-phase SRL: Memorize and get used to the eight phases of SRL while reading a news article
4 Read a story text using the TWA strategy Read a discussion paper using TWA strategy
Introduction to the cyclical model of SRL: Teacher instruction about how the eight phases circulate and interact with each
other
5 Read a story text using the TWA strategy Read a story text using the TWA strategy
Practice SRL cycle I: Practice cyclical SRL while reading a story
6 Read an essay using the TWA strategy Read a story text using the TWA strategy
Practice SRL cycle II: Practice how to diagnose one’s phase accurately and circulate SRL
7 Read an expository text using the TWA
strategy
Read an essay using the TWA strategy
Practice SRL as a whole process while reading an essay using the TWA strategy
8 Regular class instruction Read an expository text using TWA
Practice SRL as a whole process while reading an expository text using the TWA strategy
M. Lee et al.
Learning and Instruction 88 (2023) 101810
17
Appendix C. Items, Composite Reliabilities, and Intraclass Correlation Coefcients of Measures
Variable (Reference) Item Composite reliability
ω
and ICC
Study 1 Study 2 Study 3
Self-regulated strategy use during task (Shell &
Husman, 2008)
During the [SUBJECT] task,
I try to determine the best approach for each problem.
I try to monitor my progress.
I make plans for how I will solve the problems.
I use different ways to organize my thoughts, such as diagrams, charts,
timetables, etc.
I check myself to see how well I am understanding.
I take notes and jot down questions.
I focus on understanding the important ideas.
I set goals for myself which I try to accomplish.
Pretest: 0.77
Posttest:
0.78
ICC: 0.29
Pretest: 0.81
Posttest:
0.86
ICC: 0.36
Pretest: 0.89
Posttest:
0.90
ICC: 0.50
Task-irrelevant thoughts during task (Linnenbrink et al.,
1999)
During the [SUBJECT] task,
*I thought about things other than the task.
I had a hard time concentrating.
I had a hard time working on the task at hand.
I often lost track of what I was thinking.
I had difculty keeping my mind on thing.
Pretest: 0.85
Posttest:
0.84
ICC: 0.59
Pretest: 0.90
Posttest:
0.88
ICC: 0.50
Pretest: 0.86
Posttest:
0.89
ICC: 0.20
Self-efcacy for learning in [SUBJECT] domain (Bong
et al., 2012)
*I’m condent that I can solve [SUBJECT] problems.
I’m condent that I can fully remember the things that I learn in
[SUBJECT] class.
I can understand even the complicated things presented in [SUBJECT]
class.
I can identify the most important ideas in [SUBJECT] content.
I can easily understand the topics taught in [SUBJECT] class.
Pretest: 0.83
Posttest:
0.87
ICC: 0.66
Pretest: 0.92
Posttest:
0.94
ICC: 0.77
Pretest: 0.91
Posttest:
0.94
ICC: 0.62
Domain-specic academic performance Study 1: Teacher-rated four dimensions of writing quality
Study 2: Twelve math word problems
Study 3: Eight reading comprehension problems
Pretest: 0.82
Posttest:
0.90
ICC: 0.32
Pretest: 0.89
Posttest:
0.88
ICC: 0.67
Pretest: 0.86
Posttest:
0.81
ICC: 0.33
Note.
ω
=omega; ICC =intraclass correlation coefcient. * Items used for a single-item measure throughout the sessions in Studies 2 and 3.
Appendix D. Supplementary data
Supplementary data related to this article can be found at https://doi.org/10.1016/j.learninstruc.2023.101810.
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