education

sciences
Article
Young Children’s Self-Regulated Learning Benefited from a
Metacognition-Driven Science Education Intervention for Early
Childhood Teachers
Shiyi Chen 1, * , Rebecca Sermeno 1 , Kathryn (Nikki) Hodge 1 , Sydney Murphy 1 , Ariel Agenbroad 2 ,
Alleah Schweitzer 3 , Ling Ling Tsao 1 and Annie J. Roe 1

1 Margaret Ritchie School of Family and Consumer Sciences, University of Idaho,

Moscow Idaho, ID 83843, USA; serm7353@vandals.uidaho.edu (R.S.); hodg6069@vandals.uidaho.edu (K.H.);
murp5065@vandals.uidaho.edu (S.M.); ltsao@uidaho.edu (L.L.T.); aroe@uidaho.edu (A.J.R.)
2 Community Food Systems & Small Farms, University of Idaho Extension, Boise Idaho, ID 83714, USA;
ariel@uidaho.edu
3 Student Wellness Center, Dartmouth College, Hanover, NH 03755, USA; alleah.e.schweitzer@dartmouth.edu
* Correspondence: shiyic@uidaho.edu

Abstract: The two goals of this study are to examine the impact of an early childhood teacher’s
metacognition-driven, place-based science teaching professional development (PD) intervention
and to explore the association between science teaching and environment quality and children’s
self-regulated learning. A total of 110 children (Mage = 60 months) and 20 teachers from preschools
and kindergartens in rural regions of Idaho, U.S., participated in this mixed-methods study between
August 2022 and May 2023. Children’s and teachers’ pre-test and post-test data were collected
using validated observation tools, surveys, and reflection journals. The results from repeated mea-
sures ANOVA and linear mixed regression show that there were statistically significant increases in
children’s self-regulated learning scores and teachers’ science teaching efficacy and metacognitive
Citation: Chen, S.; Sermeno, R.;
Hodge, K.; Murphy, S.; Agenbroad,
knowledge, but not metacognitive regulation skill scores post-PD. Thematic analysis revealed ev-
A.; Schweitzer, A.; Tsao, L.L.; Roe, A.J. idence about children’s learning interests and inquiry skills, and that science activities supported
Young Children’s Self-Regulated children’s learning in other subjects and developmental domains (e.g., literacy, mathematics, and
Learning Benefited from a social-emotional skills). Our results indicate the potential for supporting young children’s self-
Metacognition-Driven Science regulated learning by training teachers to implement a developmentally appropriate, hands-on
Education Intervention for Early science curriculum that focuses on reflective thinking and a holistic understanding of science con-
Childhood Teachers. Educ. Sci. 2024, cepts and process skills.
14, 565. https://doi.org/10.3390/
educsci14060565
Keywords: early childhood; science education; self-regulated learning; metacognition; professional
Academic Editors: Alice development
Delserieys Pedregosa and
Maria Kampeza

Received: 31 March 2024

1. Introduction
Revised: 6 May 2024
Accepted: 15 May 2024
1.1. Self-Regulated Learning
Published: 24 May 2024 In an age of information technology characterized by an abundance of rapidly evolving
knowledge, cultivating self-regulated learners is becoming increasingly important [1].
Self-regulated learning (SRL) is an umbrella term that includes cognitive, metacognitive,
social–emotional, and motivational aspects of learning [2,3]. Self-regulated learners have
Copyright: © 2024 by the authors. a proactive and adaptive approach to learning, which equips them with the skills and
Licensee MDPI, Basel, Switzerland.
mindset to navigate complex education settings and beyond [4]. Self-regulated learners
This article is an open access article
master their own learning by setting goals, applying effective learning strategies, and
distributed under the terms and
pressing on in the face of challenges [2]. Research has linked self-regulated learning to
conditions of the Creative Commons
school outcomes from childhood to adolescence across several subject areas [5,6].
Attribution (CC BY) license (https://
Early childhood is a prime time window for fostering SRL, given young children’s
creativecommons.org/licenses/by/
rapidly developing cognitive faculties [7,8]. Teachers’ instructional support and learning
4.0/).

Educ. Sci. 2024, 14, 565. https://doi.org/10.3390/educsci14060565 https://www.mdpi.com/journal/education

Educ. Sci. 2024, 14, 565 2 of 23

environment play an important role in nurturing children’s SRL [9]. In particular, teachers’
support during science inquiry learning activities may have great potential to support
children’s SRL [10–12], given that the inquiry learning cycle (i.e., ask, investigate, create,
discuss, reflect) mirrors the SRL model [13,14]. Therefore, this present study aims to
examine the effect of an early science education intervention on children’s SRL.

1.2. Young Children’s SRL and Metacognition

Zimmerman’s theoretical model of SRL [15], although widely adopted, does not ac-
count for young children’s cognitive limitations [16]. Preschool- and kindergarten-aged
children’s SRL is still developing; as a result, they may have challenges in effectively reg-
ulating their learning processes [16]. Some of these challenges include limited cognitive
control, difficulty with goal setting, and limited understanding of one’s cognitive processes,
which could be due to young children’s immature executive functioning (i.e., a collage
of cognitive abilities such as working memory, cognitive flexibility, and inhibitory con-
trol [17]). Therefore, this study adopted a theoretical framing of SRL more suited for young
children, as proposed by Bronson and Bronson [18], and Whitebread and colleagues [19].
This framework includes four categories of SRL: emotional (e.g., regulate one’s emotions,
especially when facing challenges), prosocial (e.g., collaborate with others and being aware
of others’ feelings), cognitive (e.g., aware of oneself and strategies), and motivational (e.g.,
initiative and task persistence).
A defining characteristic of SRL is the ability to regulate one’s own cognition and
motivation during a learning episode [15], and the prerequisite for SRL is metacognition [20].
Metacognition is a cognitive function that involves being aware of and controlling one’s
mental processes [21,22]. Metacognition researchers agree on the three core components
of metacognition [22–25]: metacognitive knowledge (i.e., knowledge about the person,
task, and strategies), monitoring (i.e., gauging one’s cognition during a goal-oriented task),
and control (i.e., using information gathered during metacognitive monitoring to adjust
subsequent actions to facilitate problem solving).
Whether and to what extent young children (e.g., age 3–5 years) can think metacogni-
tively is debatable in the fields of education and psychology [26–29]. Early metacognition
researchers claim that metacognition does not emerge until middle childhood [29]. This no-
tion is partly due to the measurement limitation—many relied heavily on the participants’
language ability to report their mental processes, which young children lack [9,30]. More
recent research has used developmentally appropriate methods to assess young children’s
metacognition, such as play-based observation tools [19,23], interviews [31], and simple
computer tasks [32]. In general, researchers found that young children could reflect on
their own thinking; however, they tend to overestimate their task performance and struggle
with calibrating their decision making based on cognitive monitoring [33]. These results
echoed recent neuroscience findings: the neural correlates of metacognition seem to reside
in the anterior cingulate cortex—a brain region that connects the prefrontal cortex with
the limbic system and plays an important role in motivation, decision making, and error
monitoring but which is far from maturing during early childhood [34,35]. Therefore,
adults’ facilitation and enriched environments are necessary to leverage metacognition and
SRL to promote young children’s learning and development [36,37].

1.3. Foster Young Children’s SRL

SRL can be improved through the direct teaching of learning strategies [38], inter-
actions with others [37], and enriched learning environments [5]. Ample studies have
examined effective SRL strategies that are teachable and applicable in education settings,
such as setting learning goals, concept mapping, reciprocal teaching, and cognitive re-
flection [39–41]. Yet, the majority of these studies are conducted with older children and
adults [42–44]; as a result, many SRL strategies do not apply to the early childhood age
group (i.e., preschool- and kindergarten-aged children). Given young children’s rapidly
evolving mental capabilities, developmental appropriateness is the key when it comes to
Educ. Sci. 2024, 14, 565 3 of 23

supporting their learning and development [16,45,46]. Some commonalities across studies
on pedagogical practices that foster young children’s SRL and metacognition are adults’
dialogic support, modeling, and learning context [20,37,47].

1.3.1. Teachers as Agents and Learners of SRL

Teachers have a dual role in fostering children’s SRL as agents and learners of SRL [48].
First, teachers operate as agents of SRL by providing instructional support to children.
Research studies shed light on ways that early childhood teachers can support young
children’s SRL, such as directly teaching SRL strategies (e.g., setting learning goals and
reflecting on learning experiences), scaffolding, promoting learners’ autonomy, providing
constructive feedback, and creating a learning environment that values explorations and
collaboration [20,49]. These teaching strategies are linked to children’s learning gain and
growth in SRL [47]. However, much less empirical attention is paid to the teachers’ second
role as learners of SRL. To help children develop their SRL, teachers must first become
competent self-regulated learners themselves [50]. The four SRL competence components
are teachers’ SRL knowledge, skills, self-efficacy, and motivation/value [48]. Purposeful
training, such as teachers’ preparation and professional development programs, is pivotal
to enhancing teachers’ SRL competence [51].

1.3.2. SRL and Early Science Learning

SRL can be supported by an array of subject domains in early childhood classrooms,
such as literacy and mathematics [4,49]; however, we argue that early childhood science
activities, with proper support from teachers, provide a prime context to foster young
children’s SRL. Children are born inquisitive and eager to learn through hands-on explo-
ration [52,53]. Science learning activities capitalize on young children’s innate curiosity,
promote autonomy, and foster metacognitive thinking and problem-solving skills, all of
which are essential components of SRL [54]. Additionally, with the absence of standard-
ized testing, early childhood teachers have a higher degree of freedom to pursue science
activities driven by children’s interests as compared to their counterparts in higher grades,
making science learning uniquely suited for early childhood education [55].

1.4. Science Learning in Early Childhood Classrooms

1.4.1. Science Learning Starts Early
Contrary to the notion that science only takes place in laboratories led by highly
trained scientists, young children, as young as infants, possess rudimentary scientific
reasoning skills [53,56,57]. In Walker and colleagues’ study [57], 18–30-month-old children
were capable of discovering the association between sounds and different buttons on a
box through trial and error, indicating that very young children could detect patterns of
conditional probability and exhibited a rudimentary form of causal reasoning. Indeed,
young children possess some domain-general learning skills and are already “experts” in
learning through experimentation—the core of scientific discoveries [58].
Science learning does not only start early; scientific exploration is also developmentally
appropriate for supporting children’s learning [59,60]. During preschool and kindergarten,
children’s symbolic thinking emerges, and abstract reasoning becomes more and more ex-
plicit [28]. This transformation is aided by adults’ support and hands-on learning materials,
which allow children to manipulate and experiment while engaging multiple senses [61].
Science activities often involve experiential learning, and it is through interacting with
hands-on materials that young children form abstract understandings of a scientific concept
from concrete representations [62].

1.4.2. Developmentally Appropriate Early Childhood Science Education

Research findings in neuroscience and cognitive and developmental psychology shed
light on possible reasons that integrative science learning is developmentally appropriate
for young children. Brains process information from different sensory modalities such as
Educ. Sci. 2024, 14, 565 4 of 23

visual, audio, and tactile information in a coordinated manner [63]. Integrative learning,
such as learning mathematics and language while engaging in hands-on science activities,
stimulates various areas of the brain to generate a more comprehensive understanding
of information [64,65]. This is especially important for young children, to whom expe-
riential learning transforms concrete objects into abstract understanding [45,66]. Also,
early childhood is a sensitive period in human development, where children’s brains are
constantly organizing synaptic connections in response to the environment and experiences
(i.e., brain plasticity) [7]. Adults’ support (e.g., asking open-ended questions, activating
prior knowledge) is particularly important for early science learning because it can offset
young children’s cognitive limitations and boost science learning outcomes [46]. There-
fore, providing young children with individualized support and environments enriched
with science learning opportunities is crucial for their knowledge gain as well as for later
development [67].
Early childhood science teaching traditions include various approaches aimed at intro-
ducing young children to scientific concepts and scientific process skills [50]. Examples of
these traditions include outdoor exploration (i.e., observing and interacting with natural
elements in the outdoors), hands-on experiments (i.e., allowing children to test their hy-
potheses by interacting with science materials), storytelling (i.e., learning science concepts
in a narrative format), sensory learning (i.e., engaging children’s senses during science
exploration), child-led inquiry (i.e., giving children opportunities to ask questions and in-
vestigate), and integrative science learning (i.e., incorporating science in everyday activities
like cooking and gardening) [68]. Overall, these traditions prioritize active engagement and
children’s curiosity, promote science concept learning, and foster a sense of appreciation
for science [69].
Research studies on developmentally appropriate early childhood science education
focus on understanding how young children develop general scientific skills, attitudes, and
concepts in specific domains (e.g., weather and seasons; plants and animals; living and non-
living things) [70]. There are several trends in current research on early childhood science
education. There is a notable emphasis on integrating science learning with other subject
areas such as technology, engineering, art, and mathematics (i.e., STEAM) in children’s
daily lives [71]. Moreover, early childhood science education seems to deviate from the
traditional teacher-centered approach to child-centered approaches, such as problem-based
learning and inquiry-based learning [61]. Family and community engagement are also
recognized as a crucial component of early childhood science education [72].

1.4.3. Current State of Science Learning in Early Childhood Education Settings

Despite the multifaceted benefits of early science education, science is a much less
emphasized subject area in early childhood education [62,71]. Research investigating
early childhood teachers’ instructional time allocations found that teachers spent much
less time on science activities than on literacy, language, mathematics, and social study
activities [73,74]. Relatedly, early childhood teachers’ perceived confidence and capacity
in teaching science is lower than in other subject areas, which may lead to fewer science
learning opportunities in the classroom [73,75]. Previous research also indicates that some
early childhood science activities are hands-on but not “minds-on”; in other words, teachers
tend to pay more attention to the pragmatics of the science activity than how children can
make sense of what is being performed [76,77]. Inquiry-based science learning activities,
for example, require learners to propose predictions by drawing on existing knowledge
and form conclusions by comparing hypotheses with evidence gathered during investi-
gations [54]. The cognitive skills involved in inquiry based learning are still developing
in preschool and kindergarten children [16], which may impede their ability to construct
accurate understanding from inquiry learning activities [68]. Young children’s cognitive
limitations underline the importance of teachers’ effective support during science learning
activities via approaches such as questioning and activating prior knowledge [78]. How-
Educ. Sci. 2024, 14, 565 5 of 23

ever, early childhood teachers’ science learning support seems to be sporadic rather than
purposeful [79].
Researchers have identified several challenges that may have hindered early child-
hood teachers’ capacity and willingness to conduct science activities, for instance, the
lack of developmentally appropriate science pedagogical content knowledge [79], poor
resources [80], and classroom management issues [81]. Further, many early childhood cur-
ricula and learning standards emphasize literacy and mathematics more than science [73],
which can partially explain the unbalanced instructional attention [53]. Additionally, early
childhood teachers tend to be anxious about conducting science activities because they
doubt their ability to answer children’s questions [82]. This issue indicates teachers’ belief
that they must have comprehensive knowledge about certain science topics in order to lead
an activity [81]. However, teachers should adopt and model the mindset that science is
a dynamic discovery process; a gap in their understanding is not embarrassing, rather, it
affords an opportunity for learning with children [82].

1.5. Professional Development Programs

To nurture children’s SRL using science activities, teachers must become competent
self-regulated learners who possess the necessary knowledge and positive attitudes towards
science [83]. Well-designed education interventions, such as teachers’ PD programs, can
help teachers become self-regulated learners [68,69]. It is important to note that not all
PD programs are education interventions by default [84]. For a PD program to become an
education intervention, it must have a purposeful education and research design, evidence-
based activities, targeted areas of improvement, and empirical data that can support the
effect of the PD program [85]. A recent meta-analysis on effective education intervention
targeting children’s SRL and metacognition indicates that contrary to popular beliefs,
teacher-administered education interventions yielded a larger effect than researcher-led
ones [86]. This might be because trained classroom teachers, as compared to researchers,
were able to provide more immersive interventions and encouraged the transfer of the
learned skills to other domains [37]. Therefore, training teachers through PD programs
could have a positive downstream effect on their students’ learning.

1.6. Empirical Gaps

First, although the SRL framework reflects the iterative, trial-and-error nature of scien-
tific discovery, there is very limited research on the application of SRL and metacognition
in science learning during early childhood [13,30]. The relation between metacognition
and learning is well established among older children and adult learners [85,87], but more
research is needed to investigate how to use science activities to foster young children’s
metacognition and SRL [30]. The second empirical gap is the lack of research on the features
of effective teachers’ PD programs designed to support teachers’ and children’s metacogni-
tion and SRL [9]. The quality of teachers’ PD programs targeting early science education
varies greatly from one-time online workshops to experiential, systematic training over a
prolonged period of time [67,88,89]. The development of cognitive skills such as SRL and
metacognition require sustained, targeted efforts [90]; however, it is not very clear what
kind of PD design facilitates the transformation of teachers’ pedagogical knowledge to
instructional practices that will eventually benefit children [91,92].

1.7. The Present Study: Aims, Research Questions, and Hypothesis

Informed by the existing literature and empirical gaps, we created a ten-month science
education intervention that focuses on SRL and metacognition—Farm to Early Care and
Education (Farm to ECE). Farm to ECE adopts a progressive online training plus an in-
person coaching model with supplementary curricula that allows teachers to enact their
training in real-world scenarios. The goals of this study are twofold: (1) to examine the
effect of Farm to ECE on children’s SRL and (2) to explore the association between science
Educ. Sci. 2024, 14, 565 6 of 23

instructional environment quality and changes in children’s SRL. The specific research
questions and hypotheses are as follows:
• RQ1: Does the education intervention lead to a significant gain in teacher-level out-
comes, as measured by teachers’ science teaching efficacy and metacognitive aware-
ness? We hypothesize that the teacher-level outcomes will improve after the education
intervention.
• RQ2: Does the education intervention lead to a significant gain in children’s SRL scores?
We hypothesize that children’s SRL will increase after the educationintervention.
• RQ3: To what extent are changes in young children’s SRL related to science teaching
and environment quality? We hypothesize that better science instructional environ-
ment quality is associated with greater improvements in children’s SRL.
• RQ4: What insights can be gained from teachers’ reporting of children’s learning
during the education intervention? We hypothesize that teachers’ reports will provide
authentic information on various aspects of children’s learning experiences.

2. Materials and Methods

This mixed-methods study was approved by the Institutional Review Board (IRB) at
the lead author’s university (IR protocol code 21-233). The data presented in this paper
were collected between August 2022 and May 2023.

2.1. Participants
The targeted sample sizes in this study were based on a priori power analysis con-
ducted using the software Optimal Design. The results indicated that 22 teachers and
132 children were needed to detect a statistical significance with an alpha of .05 and a
power of .80. Eligible participants were preschool and kindergarten teachers and children
(age = 4–6 years, typically developing) within two hours driving distance from the lead
author’s university from rural regions of north Idaho, U.S. Trained research assistants
contacted potential participating teachers via phone calls, emails, and a recruitment event
at a regional child development conference in the summer of 2022. Participating teachers
then distributed parental consent forms to eligible children in their classrooms. For each
teacher, approximately six children were randomly selected for data collection from all the
consented children.
A total of 21 teachers consented but one dropped out due to not having eligible children
in the classroom (Nteacher = 20) (Table 1). On average, the teachers’ age was 36.74 years old
(SD = 10.34, range = 22–57), they were predominately White (75%), 60% had a Bachelor’s
degree and above, and their teaching experiences ranged from 3 to 29 years (SD = 6.69).
The child sample consisted of 110 children and had slightly more boys than girls (Nboy = 62,
Ngirl = 48), with an average age of 60 months (SD = 7.76, range = 44–87).

Table 1. Participants’ demographic information.

N M/Percent
TEACHER
Gender: Male 1 5%
Female 19 95%
Age (yrs.) 20 36.74
Ethnicity/Race: Hispanic 3 15%
Non-Hispanic White 15 75%
Other 2 10%
Grade: Preschool 17 95%
Kindergarten 1 5%
Have a certification 8 40%
Have a CDA 6 30%
Degree: GED 3 15%
HS 2 10%
Educ. Sci. 2024, 14, 565 7 of 23

Table 1. Cont.

N M/Percent
AA 2 10%
BA/BS 12 60%
MA/MS 1 5%
Experience (yrs.) 20 9.35
CHILD
Gender: Boys 62 56%
Girls 48 44%
Age (mo.) 110 60
Ethnicity/Race: Hispanic 8 7.3%
Non-Hispanic White 95 86.4%
Bi- or Multi-racial 7 6.3%
Note. AA = Associate degree, BA/BS = Bachelor’s degree, CDA = Child Development Associate Credential,
GED = General Education Diploma, HS = High School, MA/MS = Master’s degree, mo = month, yrs = years.

2.2. PD Intervention Design and Implementation

This year-long education intervention was in the form of a teachers’ PD program and
was divided into the spring and fall seasonal segments. In Farm to ECE, teachers were not
only learning science background knowledge and developmentally appropriate science
teaching practices (e.g., activating prior knowledge, open-ended questions, and sensory
learning) via an online learning platform (i.e., Canvas) but also receiving monthly curricula
and activity materials (i.e., “Harvest of the Month” toolkit) to facilitate the transformation
of pedagogical knowledge into instructional practices and to enrich their science learning
environment [67,89].
Educ. Sci. 2024, 14, x FOR PEER REVIEW 8 of 24
A typical training module included an introduction video (overview of the curriculum
and teaching strategies introduced in that curriculum), a detailed explanation and demon-
stration of the teaching practices introduced in a given curriculum, and digital resources
prompts)
that was incorporated
complement into each(e.g.,
the curriculum lesson plan.recipe,
song, Teaching practice textboxes were added
dance).
next to each activity with detailed explanations of the learning science behind the teaching
The “Harvest of the Month” toolkit (Figure 1) was distributed to teachers at the
practice. The design of activities was aligned with the Idaho Learning e-Guideline and
beginning of each month. It included seasonal vegetables/grains/fruits (e.g., plums, beets,
was developmentally appropriate for 3-to-6-year-old children. The content of the Farm to
lentils, microgreens) purchased from local farms, a plant-themed children’s book, detailed
ECE curriculum was also aligned with the core components of the National Farm to School
lesson
program.plans, vocabulary cards, and family engagement newsletters.

Figure 1. Harvest
Figure 1. Harvest of
of The
The Month
Month toolkit
toolkit example:
example: March
March microgreen
microgreen curriculum.
curriculum.
Each month’s activities (see Figure 2 for examples) centered on the basic plant science
concepts related to the featured vegetables/grains/fruits while crosscutting several science
teaching traditions such as hands-on experiments, storytelling, sensory learning, and
child-led inquiry learning traditions [43,45]. For example, week 1 activity typically in-
Educ. Sci. 2024, 14, 565 8 of 23

The monthly curriculum included four lesson plans that were supplementary to
teachers’ primary curriculum—this was to avoid adding too much work into teachers’
existing workload. A unique teaching practice (e.g., concept map, scripted reflective
prompts) was incorporated into each lesson plan. Teaching practice textboxes were added
next to each activity with detailed explanations of the learning science behind the teaching
practice. The design of activities was aligned with the Idaho Learning e-Guideline and
was developmentally appropriate for 3-to-6-year-old children. The content of the Farm
to ECE curriculum was also aligned with the core components of the National Farm to
School program.
Each month’s activities (see Figure 2 for examples) centered on the basic plant science
concepts related to the featured vegetables/grains/fruits while crosscutting several science
teaching traditions such as hands-on experiments, storytelling, sensory learning, and child-
led inquiry learning traditions [43,45]. For example, week 1 activity typically included an
introduction, where teachers presented the real vegetables/grains/fruits to children and
encouraged children to explore with all their senses. Week 2 activities usually included
more in-depth investigation using science experiments (e.g., sink-or-float experiments
with apples and pears) and observation (e.g., beans germination). Week 3 activities were
typically shared book reading (e.g., “A Fruit is a Suitcase for Seeds”). The purpose of the
week 4 activity was to review what they had learned in the previous weeks using physical
movements. For instance, in the “Fruit Tree Yoga” activity, children were asked to recall
the lifecycle of a fruit tree and use yoga poses to demonstrate their understanding. The
lesson plan of each week’s activities details the activity materials, procedures, and scripted
open-ended questions that teachers could use to introduce vocabulary words (e.g., beets,
rhubarb, hypothesis, investigate), encourage children to make predictions/hypotheses (e.g.,
“Will the apple sink or float?”), investigate the phenomenon (e.g., “Let us fill the bucket
and find out which one sinks and which one floats.”), observe and collect evidence (e.g.,
teachers will record children’s hypotheses and the experiment results on a large Post-It
Educ. Sci. 2024, 14, x FOR PEER REVIEW 9 of 24 did
easel pad), and discuss the experiment results (e.g., “Take a look at your hypotheses,
you guess it right?”, “Why do you think the apple floats but the pear did not?”).

Figure2.2.Photographs
Figure Photographsofofthe
thePDPDprogram
program implementation.
implementation. Note.
Note.Left to to
Left right: bean
right: germination
bean ger-
experiment, bean germination journal, and visiting a local granary.
mination experiment, bean germination journal, and visiting a local granary.
Metacognitive knowledge
Metacognitive knowledge(i.e.,
(i.e.,knowledge
knowledge about
about thethe
person, teaching
person, teachingstrategies, andand
strategies,
teaching tasks [25]), was incorporated into the PD in various forms
teaching tasks [25]), was incorporated into the PD in various forms based on previous based on previous
research on
research on metacognition
metacognition intervention.
intervention.For Forinstance,
instance, teachers were
teachers required
were requiredto complete
to complete
quarterly self-reflection
quarterly self-reflection journals
journalsandandpre-
pre-and
andpost-PD
post-PDassessments
assessments [86]. Also,
[86]. teachers
Also, teachers
wereexplicitly
were explicitly taught
taught about
aboutmetacognition,
metacognition,SRL, SRL, science
science content knowledge
content knowledge related to the
related to the
curriculum, and
curriculum, and science
scienceteaching
teachingpractices
practices(e.g., problematizing
(e.g., problematizing modeling,
modeling, questioning,
questioning,
concept map)
concept map) using
using monthly
monthlyonline
onlinetraining
trainingmodules
modules [91]. Moreover,
[91]. metacognitive
Moreover, metacognitive skills
skills
(i.e., planning, monitoring, and evaluation) [14] were translated into the
(i.e., planning, monitoring, and evaluation) [14] were translated into the PD as journal PD as journal
reflection, workshop,
reflection, workshop, and andin-person
in-personobservation
observationbyby a trained
a trained research
researchassistant
assistant[93].
[93].
2.3. Procedure
Farm to ECE is a three-year project, and the data presented in this paper were from
the year-1 cohort. The year-1 project spanned from September 2022 to May 2023. At the
beginning of the PD program in August 2022, teachers participated in a two-and-half
hours orientation workshop, led by the first author. The orientation covered topics such
Educ. Sci. 2024, 14, 565 9 of 23

2.3. Procedure
Farm to ECE is a three-year project, and the data presented in this paper were from
the year-1 cohort. The year-1 project spanned from September 2022 to May 2023. At the
beginning of the PD program in August 2022, teachers participated in a two-and-half
hours orientation workshop, led by the first author. The orientation covered topics such as
the Farm to ECE curriculum, PD training syllabus, early science learning, metacognition
and its application in children’s learning, data collection schedule, and Canvas tutorial.
Before and after the PD program (i.e., August 2022 and May 2023), teachers completed a
series of online and in-person assessments for their science teaching efficacy, metacognitive
awareness, science teaching and environment quality, and SRL rating scales. In particular,
teachers were required to complete an SRL rating scale for each of the six randomly selected
children (with parental consent) in their class during pre- and post-test. During the first
week of each month, every teacher received a “Harvest of the Month” toolkit (the toolkit
content is described in a previous section) and was required to complete the monthly online
training module prior to implementing the curriculum activities by reviewing the online
training materials. Teachers’ online engagement statistics (e.g., page viewing frequency and
duration, etc.) were monitored by the research assistants. The fidelity of the implementation
data were collected using an observation tool—Science Teaching and Environment Rating
Scale (STERS, [94], α = .94)—at two different time points in November 2022 and April 2023.
For each STERS data collection session, trained research assistants observed one Farm
to ECE curriculum activity in the classroom and interviewed teachers about their lesson
planning and instructional decision-making process after the observation on the same day.
The observation field notes and interview transcripts were then independently scored by
two trained research assistants using a validated rubric. Upon program completion, each
participating teacher received ninety PD credits and a USD 1500 stipend.

2.4. Measurement Instruments

2.4.1. Children’s SRL
We measured children’s SRL using the Children’s Independent Learning Development
checklist (CHILD; α = .97; [19]; Appendix A). CHILD is a teacher-reported rating scale
that measures children’s SRL behaviors. The instrument contains four subscales: cognitive
(seven items, e.g., the child adopts previously heard language for own purposes), motiva-
tional (five items, e.g., the child plans own tasks, targets, and goals), prosocial (five items,
e.g., the child shares and takes turns independently), and emotional subscale (five items,
e.g., the child can monitor progress and seeks help appropriately). Each subscale uses a
four-point Likert scale ranging from Never (1) to Always (4). Given the time commitment
of the entire teacher- and child-assessment battery, we did not include the Emotional and
Prosocial subscales to avoid overwhelming teachers.

2.4.2. Science Teaching and Environment Quality

Science learning environment quality was measured by the Science Teaching and
Environment Rating Scale (STERS; [94], α = .94; Appendix B). STERS assesses the quality of
science teaching and environment in early childhood classrooms by drawing on classroom
observation and teacher interview data. Trained research assistants observed the classroom
science learning environment and a science learning activity from the Farm to ECE curricu-
lum twice a year in the spring and fall semesters. The research assistants then interviewed
the teachers about their instructional decision making using a structured interview protocol
(Eight questions, e.g., What have you learned about children’s understanding of this topic
up to this point? Do you use this information for planning, if so, how?). In total, there were
40 observation field notes and 40 interview recordings (average length: eight minutes).
Observation field notes and interview transcripts were scored on a 4-point validated
rubric (1 = deficient to 4 = exemplary) across eight indicators: (1) creates a physical en-
vironment for inquiry and learning (e.g., provides access to science learning materials),
(2) facilitates direct experiences to promote conceptual learning (e.g., engages learners and
Educ. Sci. 2024, 14, 565 10 of 23

assists their learning), (3) promotes the use of scientific inquiry (e.g., intentionally facilitates
science process skills), (4) creates a collaborative climate that promotes exploration and
understanding (e.g., fosters a science learning environment where children’s ideas are
valued), (5) provides opportunities for extended conversations (e.g., promotes multi-turn
discussion), (6) builds children’s vocabulary (e.g., introduces new words), (7) plans in-depth
investigations (e.g., provides sufficient time for exploration), and (8) assesses children’s
learning (e.g., uses on-going assessments). Two trained research assistants scored the obser-
vation and interview data independently (κ = .91). Each teacher’s STERS score was derived
from two sets of observations and interviews collected in the fall and spring semesters.
RAs resolved the scoring differences by discussing the scoring results with the lead author.

2.4.3. Teachers’ Science Teaching Efficacy

Teachers’ science teaching efficacy was measured by the Science Teaching Efficacy and
Beliefs (STEB; [95], αSTEB = .90; Appendix C) and Science Teaching Outcome Expectancy
(STOE; αSTOE = .93) subscales in the Elementary Teacher Efficacy and Attitudes toward
STEM Surveys (T-STEM; [95]). STEB and STOE are five-point Likert scales that include
40 items in total. An example of a STEB scale item is “When a student has difficulty under-
standing science concept, I am confident that I know how to help the student understand
it better”. An example of a STOE scale item is “Students’ learning in science is directly
related to their teacher’s effectiveness in science teaching”.

2.4.4. Teachers’ Metacognitive Awareness

The Metacognitive Awareness Inventory for Teachers (MAIT; [96]; Appendix D) was
used to measure teachers’ metacognitive awareness. The MAIT involves 24 items on a
five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). The three
subscales that measure metacognitive knowledge are declarative knowledge (α = .63, e.g., I
am aware of the strengths and weaknesses in my teaching), procedural knowledge (α = .61,
e.g., I try to use teaching techniques that worked in the past), and conditional knowledge
(α = .63, e.g., I use different teaching techniques depending on the situation). The three
subscales that measure metacognitive regulation are planning (α = .73, e.g., I organize my
time to best accomplish my teaching goals), monitoring (α = .71, e.g., I ask myself questions
about how well I am doing while I am teaching), and evaluating (α = .76, e.g., I ask myself
if I could have used different techniques after each teaching experience).

2.4.5. Qualitative Data Collection

For the qualitative data collection, teachers completed four online quarterly reflection
journal entries on Canvas. Each entry included five writing prompts that required teachers
to reflect on and provide examples of children’s activity engagement, things that went well,
challenges they encountered, and teaching strategies or science background knowledge
that they wished they knew more about (e.g., How was children’s engagement? What did
not go as planned and how did you resolve it?).

2.5. Data Analysis

We first conducted descriptive analysis to examine the normality of the data and test
the assumptions for the subsequent analysis. A series of repeated measures analyses of
variance (ANOVA) [97] were used to test the first two hypotheses. Teachers’ and children’s
outcome variables were entered as the dependent variables in each model, respectively.
To test the third hypothesis, we used linear mixed models to account for the data’s nested
structure (i.e., children were clustered in classrooms/teachers). Individual children’s
scores were centered at the group level to improve the results’ interpretability [98]. Fully
unconditional models were run before adding predictors [99]. Intraclass correlation (ICC)
indicated that the common variance shared at the cluster level (ICCcog = .12, ICCmot = .24)
warranted the use of linear mixed modeling [99]. Child-level variables were then entered
Educ. Sci. 2024, 14, 565 11 of 23

at level-1, and teacher-level variables were entered at level-2. Software R (Version 4.3.1)
and R package lme4 [100] were used.
Qualitative data were analyzed using a thematic analysis method to identify recurring
patterns in the data [101]. A trained graduate research assistant combed through teachers’
reflection journal entries and assigned open codes to emerging phenomena. The research
assistant then conducted axial coding by further grouping open codes into larger categories
(i.e., axial codes) and identifying the relations between the axial codes. For the final step,
the leader author and three research assistants held a meeting to discuss axial coding results
and emerging themes. Detailed memos, peer debriefing, and the involvement of multiple
coders enhanced the credibility of the qualitative data analysis [102].

3. Results
In this section, we describe the data analysis results organized by using the research
questions. We first present whether and to what extent the PD program impacted chil-
dren and teachers’ outcomes, and then discuss the relation between science teaching and
environment quality improvement to children’s SRL scores. Finally, we review the qual-
itative evidence of teacher-reported children’s learning and challenges related to the PD
program implementation.

3.1. PD’s Impact on Teachers’ Metacognitive Awareness and Science Teaching Efficacy
A series of repeated measures ANOVA were used to answer RQ1: Does the education
intervention lead to a significant gain in teacher-level outcomes, as measured by science
instructional environment quality, teachers’ science teaching efficacy, and metacognitive
awareness? We did not control any covariates because this study adopted a within-subject
repeated measure experimental design; therefore, potential covariates such as teachers’
degrees and years of teaching experience were already controlled. Although our sample was
slightly smaller than the target sample size, the data analysis results showed some positive
effects of the PD program on teachers’ outcomes (Figure 3), which partially confirmed our
first hypothesis. Specifically, after the PD program, there was an increase in teachers’ science
teaching efficacy beliefs (Fefficacy (1, 19) = 11.12, p = .003, η 2 = .37, average score increase
post-PD: 4.15) and science teaching outcome expectancy (Fexpectancy (1, 19) = 4.33, p = .05,
η 2 = .19; average score increase post-PD: 2.55). Also, teachers’ metacognitive knowledge
awareness showed meaningful improvement after the PD program (Fawawre (1, 19) = 6.90,
p = .02, η 2 = .27, average score increase post-PD: 2.65). Contrary to what was expected,
teachers’ metacognitive regulation skills were not statistically different before and after the
PD (Freg (1, 19) = 1.76, p = .20).

3.2. Children’s SRL

To answer RQ2—Does the education intervention lead to a significant gain in children’s
SRL scores?—we conducted linear mixed modeling with child outcomes at level-1. There
was no predictor added at level-2, which only accounted for the unobserved variance
explained by the class/teacher differences. The cognitive and motivational subscales
showed satisfactory reliability in our sample (αcog = .96, αmot = .90). The results indicate
that there was an increase in teacher-reported children’s cognitive skills (F(1, 109) = 20.08,
p < .001, η 2 = .16), with an average of 1.68 points increase after the PD. There was also
a significant improvement in children’s learning motivation (F(1, 109) = 13.50, p < .001,
η 2 = .11), with an average of .14 points increase post-PD (Figure 3). The data analysis results
confirm our second hypothesis.

3.3. The Association between Science Teaching and Environment Quality and Children’s SRL
To answer RQ3—To what extent are changes in young children’s SRL related to science
teaching and environment quality?—linear mixed modeling was used with children’s
cognitive and motivation gain scores (i.e., post-test scores minus pre-test scores) at level-1
and teachers’ science teaching and environment quality at level-2. Note that the science
 3.1. PD’s Impact on Teachers’ Metacognitive Awareness and Science Teaching Efficacy
A series of repeated measures ANOVA were used to answer RQ1: Does the education
intervention lead to a significant gain in teacher-level outcomes, as measured by science
instructional environment quality, teachers’ science teaching efficacy, and metacognitive
Educ. Sci. 2024, 14, 565 12 of 23
awareness? We did not control any covariates because this study adopted a within-subject
repeated measure experimental design; therefore, potential covariates such as teachers’
degrees and years of teaching experience were already controlled. Although our sample
teaching and smaller
was slightly environment
than thequality scores
target samplewere
size,notthe used
data asanalysis
pre-test results
and post-test
showedscores some
because
positive data
effects were collected
of the in November
PD program 2022outcomes
on teachers’ and April(Figure
2023 for fidelitypartially
3), which monitoring con-
and PD our
firmed coaching purposes. The
first hypothesis. science teaching
Specifically, after the and environment
PD program, therequality
was anscores
increasewere in
derived
teachers’from datateaching
science collectedefficacy
at both beliefs
time points
(Fefficacyin(1,order
19) =to11.12,
betterp represent
= .003, η2 the
= .37,quality
average of
the science
score instructional
increase post-PD:environment. The results
4.15) and science teaching showed
outcomethatexpectancy
gain scores (F inexpectancy
the cognitive
(1, 19) =
(t(14) = 2.33, = .24, p = .02) and motivational (t(14) = 2.16, = .15,
4.33, p = .05, η = .19; average score increase post-PD: 2.55). Also, teachers’ metacognitive
β 2 β p = .03) aspects of
SRL were significantly
knowledge associated
awareness showed with the quality
meaningful improvement of science instructional
after the PD program practices and
(Fawawre (1,
learning environment.
19) = 6.90, p = .02, η2 =In.27,
other words,score
average children tended
increase to have2.65).
post-PD: betterContrary
SRL skillstowhenwhattheir was
teachers
expected, had better science
teachers’ teachingregulation
metacognitive practices and
skills whenweretheir
notclassroom
statisticallyenvironment
different before was
conducive to science learning.
and after the PD (Freg(1, 19) = 1.76, p = .20).

70
*
60 *
*
50 *
*
40 *
* *
30 *
*
20

10

0
T_STEB T_STOE T_MK T_MR C_Cog C_Mot

Pretest Posttest

Figure3.3.Teacher’s
Figure Teacher’sand
andchildren’s
children’spre-test
pre-testand
andpost-test
post-testresults.
results.Note.
Note.* *pp<<.05,
.05,****pp<<.01,
.01,***
***pp<< .001,
.001,
C = child, Cog = cognition, MK = metacognitive knowledge, Mot = motivation, MR
C = child, Cog = cognition, MK = metacognitive knowledge, Mot = motivation, MR = metacognitive= metacognitive
regulation,STEB
regulation, STEB==science
scienceteaching
teachingefficacy
efficacybeliefs,
beliefs,STOE
STOE==science
scienceteaching
teachingoutcome
outcomeexpectancy.
expectancy.

3.4.
3.2.Qualitative Evidence
Children’s SRL
To
Toanswer
answerRQ4—What
RQ2—Doesinsights can be intervention
the education gained from lead teachers’ reporting ofgain
to a significant children’s
in chil-
learning
dren’s SRLduring the education
scores?—we conductedintervention?—we
linear mixed modelingused a with
thematic
childanalysis
outcomes method to
at level-1.
analyze
There wasteachers’ structured
no predictor reflection
added journals.
at level-2, which The results
only are discussed
accounted for the by themes below.
unobserved vari-
ance explained by the class/teacher differences. The cognitive and motivational subscales
3.4.1.
showedChildren’s Learning
satisfactory Interests
reliability and
in our Engagement
sample (αcog = .96, αmot = .90). The results indicate that
thereTeachers’ written reports
was an increase revealed evidence
in teacher-reported of children’s
children’s cognitive strong interests
skills in the
(F(1, 109) curricu-
= 20.08, p<
lum
.001,materials, particularly
η2 = .16), with an averagethose hands-on
of 1.68 pointsactivities
increase (e.g., bean
after the germination
PD. There was alsoexperiment,
a signif-
learning games, and in
icant improvement fruits/vegetables/grains exploration).
children’s learning motivation For example,
(F(1, 109) = 13.50, pa<teacher
.001, η2wrote:
= .11),
“Overall, their engagement was exceptional. Each child had an excitement in the
with an average of .14 points increase post-PD (Figure 3). The data analysis results confirm fruits and veg-
etables being discussed
our second hypothesis. and we were all able to connect over different home/life experiences with
the material and the lesson”. Another teacher reflected: “My preschoolers loved learning about
fruits and vegetables during September and October. . .. having the actual fruits and vegetables to
see, smell, feel, and taste was very fun for them!”. However, several teachers mentioned that
younger preschool children tended to lose interest quicker than older children.

3.4.2. Science Activities Support Learning in Other Subject and Developmental Domains
The Farm to ECE curriculum primarily focused on the teaching of basic plant science
concepts; however, qualitative data analysis showed evidence that this curriculum also
supported children’s learning in other subject domains (e.g., literacy, mathematics) and
developmental domains (e.g., inquiry skills and self-regulation skills). For example, a
teacher reflected on teaching children thinking vocabulary (i.e., predict, observe, compare):
Educ. Sci. 2024, 14, 565 13 of 23

In week one of September, the “thinking vocabulary” was very beneficial for myself and
my students. We explicitly went over each of the vocabulary terms, and then we dove
right into the lesson. During the lesson, I repetitively used the words “predict, observe,
and compare”, and I could tell that my students felt like little scientists, which is exactly
what they were!
A teacher reflected on children’s inquiry and mathematics skills during the bean
germination experiment: “My class enjoyed playing, sorting, and weighing beans. We germinated
them as instructed in plastic bags first then transferred them to bigger containers. We started
measuring and taking notice of how fast or slow each plant grew”. Another teacher wrote about
how children document evidence in the bean germination experiment: “The child loved
to watch the different beans grow and then be able to draw the progress on their journal. They
would always ask to see how much the beans have sprouted!”. The same teacher also reflected
on how children were motivated to initiate new investigations: “The best highlight is the
children asking if we could plant our own seeds from our apples and what other vegetables we could
grow in our garden”. A different teacher described children’s self-regulation skills during a
small-group activity: “The children patiently waited their turn and followed directions well when
we planted their bean plant”.

4. Discussion
The goal of this ongoing three-year study is to examine the effect of a metacognitive-
driven, experiential early science instructional intervention on children’s SRL and to explore
the relation between science instructional environment quality and the improvement in
children’s SRL. Quantitative and qualitative analyses of the year-1 data showed that the
PD program yielded positive impacts on teachers’ and children’s outcomes, such as science
teaching efficacy, metacognitive awareness of teaching, and children’s SRL. We also found a
small but significant correlation between science instructional environment quality and the
children’s improvement in SRL. In this section, we discuss our research findings, limitations,
and future directions.

4.1. Early Science Education and Children’s SRL

As expected, we found a statistically significant increase in both the cognitive and mo-
tivational aspects of young children’s SRL after the PD program (controlling for children’s
age), and this improvement was positively associated with the quality of science teaching
and environment quality. Our quantitative finding was supported by teachers’ qualitative
reports of children’s learning interests and inquiry skills (e.g., observe, document, initiate
new investigation). The connection between children’s SRL skills gains and early science
teaching and environment quality could imply that early science learning promoted young
children’s SRL [55]. The positive association between science teaching environment quality
and children’s SRL in our study, although interesting, did not warrant causation. We en-
courage future researchers to employ a randomized control trial to investigate the potential
causal relation between early childhood science education and SRL, as well as to unpack
why this relation exists.
Despite the benefit of early science learning, science is an overlooked subject area
in early childhood classrooms. For instance, on average, preschool teachers dedicated
only 9% of classroom learning time to science, which is significantly lower than literacy
(30%) and math (19%) [74]. The current state of early science learning could be due to
insufficient teacher training about science pedagogical content knowledge [79] and the lack
of resources [80], in particular the lack of developmentally appropriate science curriculum
that also touches on other subject and developmental domains (e.g., literacy, math, social-
emotional development).
The Farm to ECE curriculum filled the gaps described above by integrating literacy and
mathematics contents in the science curriculum while promoting children’s self-regulation
skills. For example, in the “Peaches & Plums” unit, children not only learned science con-
cepts about fruits (e.g., lifecycles and growing conditions) but also new vocabulary words
Educ. Sci. 2024, 14, 565 14 of 23

(e.g., pit, fuzz, and ripe). In the “Radishes” unit, children gained mathematic competency
by measuring and weighing radishes and exercising their self-regulation skills in a small
group activity where children used scientific tools (e.g., magnifying glasses and scales) to
explore radishes. Moreover, this curriculum uses locally sourced fruits/vegetables/grains
as children’s place-based hands-on learning materials, which were connected with rural
children and teachers’ lived experiences. Our finding is supported by the results from a
recent meta-analysis study: teacher-administered interventions targeting children’s SRL
yielded a bigger effect than those administered by interventionists, possibly due to teachers’
extensive knowledge about their children and the ability to conduct immersive training that
encouraged knowledge transfer [86]. Given the positive impact of early science learning
on children’s SRL, as indicated by our data analysis results, future researchers and early
childhood policymakers should create and fund evidence-based, integrative early science
curricula; such curricula should also be supplemented by teacher training to maximize its
benefit [71].

4.2. The PD’s Impact on Teachers’ Outcomes

As for the teacher-level outcome, our data analysis results showed that the metacognition-
driven early science learning PD meaningfully improved early childhood teachers’ science
teaching efficacy. It is worth noting that we observed an increase not only in teachers’
science teaching efficacy beliefs but also outcome expectancy post-PD. Previous research
has shown that early childhood teachers’ training did not necessarily lead to positive
changes in the outcome expectancy aspect of science teaching efficacy [103]. In other
words, teacher training that focuses on content knowledge and pedagogy may increase
teacher-perceived science teaching ability but not the perceived impact of their teaching. A
plausible explanation is that science teaching outcome expectancy involves many factors
beyond teachers’ control, such as children’s learning interests and contextual factors (e.g.,
resources and behavior management) [104]. We credit the increase in teachers’ science
teaching outcome expectancy in our program to the immersive, hands-on curriculum. The
Farm to ECE PD program uses a year-long supplementary curriculum to accompany the
monthly online training, and this combination possibly aided the translation of pedagogical
content knowledge to classroom teaching practices, therefore leading to increased science
teaching outcome expectancy. Future work is needed to understand the multifaceted
factors that contribute to teachers’ knowledge transformation to classroom practices (e.g.,
PD training regimen, curriculum, teacher attitudes, and class sizes).
Our results also showed an increase in teachers’ metacognitive knowledge about
their teaching practices; however, the PD did not have an effect on their regulation skills
regarding teaching (i.e., planning, monitoring, and evaluation). The Farm to ECE program
adopted several ways to enhance teachers’ metacognitive awareness for teaching. For
instance, we added “Teaching/Classroom Management Strategies Boxes” to each curricu-
lum activity to explain the science behind these evidence-based instructional practices and
how to use them with young children. These practices were explained in greater detail in
teachers’ monthly training videos on the online PD platform. The curriculum activities
allowed teachers to practice using the teaching/classroom management strategies taught in
the PD. In addition, teachers were asked to write quarterly reflections about their classroom
implementations. The Farm to ECE PD design echoed previous successful PDs that aimed
to enhance teachers’ and students’ metacognition [105–107].
As to the null finding on teachers’ metacognitive regulation skills, a possible explana-
tion is the need for more teachers’ autonomy in our program. The current Farm to ECE PD
program was prescribed to teachers—the lesson plan, learning goals, activities, and materi-
als were predetermined in the monthly curriculum. As a result, there was not much room
in the curriculum for teachers to proactively exercise their planning, monitoring, and evalu-
ation skills. Future PD programs could consider using a semi-structured PD framework to
allow teachers to co-design the PD with researchers in order to promote teachers’ autonomy
and metacognitive regulation skills [83]. Another possible explanation for the null finding
Educ. Sci. 2024, 14, 565 15 of 23

is related to measurement. The MAIT explores a teacher’s self-reported measurement and

is not designed for any specific grade level or content area [96]. Therefore, MAIT items may
not accurately reflect early childhood teachers’ metacognition related to science teaching,
and teachers’ responses may be subject to social desirability [108]. Content-specific direct
measurements of teachers’ metacognition are needed in order to provide reliable data on
teachers’ awareness of their content and pedagogical knowledge. Future researchers could
consider developing such measurements using a response-contingent signal detection
approach (i.e., type-2 signal detection). Başokçu and Güzel [109] successfully created this
type of instrument to measure elementary teachers’ mathematics teaching metacognition.
Such a measurement approach could be expanded to other grades and content areas.

4.3. Limitations and Future Directions

In this section, we discuss several limitations and how future research may overcome
these limitations and advance studies on metacognition and early science teaching and
learning. First, the participants in our study were predominately White and from rural
areas of Northern Idaho, and the sample size was slightly underpowered. Therefore, our
sample was homogenous and is not representative of the larger population in the U.S. The
results from this study should be interpreted within their context. Future research should
consider recruiting a larger sample from a more demographically diverse population (e.g.,
urban, inner city). Secondly, a number of measurements used in this study were self-
reported and teacher-reported instruments (e.g., CHILD, STEB, STOE, and MAIT), which
may have introduced social desirability bias and rater’s bias [108]. Future researchers who
are interested in a similar topic should consider using or creating direct measurements of
children’s SRL [110] and teacher’s metacognitive awareness in teaching [109]. Third, the
outcome of the PD was measured immediately after the program, and we do not have data
to demonstrate the long-term impact of this program. Future PD studies should examine
delayed effects as well as acute effects in order to investigate the possible lasting impact
and transfer effects of a PD program. Fourth, the qualitative data collected in this study
(i.e., reflection journals) lacked richness. Additional qualitative data, such as teachers’
interviews, will enable a more in-depth interpretation of results from this mixed-methods
study. Fifth, child-level outcomes were limited to SRL, and measurements that assess
children’s science learning conceptual changes were absent. Future studies should measure
not only changes in children’s learning skills but also knowledge retainment as well. The
sixth limitation is related to the PD design. Although we created curriculum activities
that promote sensory learning and child-directed exploration, there is a lack of immersive
problem-based learning. To improve the current design, we plan to create more open-ended
inquiry learning tasks (e.g., germinating and growing beans, creating compost) to better
instill the idea that science is a dynamic discovery process. Last but not least, we only used
the cognitive and motivational subscales of CHILD. We decided to not include emotional
and prosocial subscales to lessen teachers’ workload, given their existing tasks. Future
work is needed to examine the relation between science learning and all aspects of SRL.

5. Conclusions
Self-regulated learners are competent at setting learning goals, selecting effective
learning strategies, monitoring and evaluating task performances, and persevering despite
challenges [4]. We argue that early science learning might be an overlooked prime context to
supporting children’s self-regulated learning (SRL) because science activities capitalize on
children’s innate curiosity and allow children to exercise the motivational (meta)cognitive
and self-regulation aspects of SRL. Our research findings show the potential of supporting
children’s SRL by training early childhood teachers to conduct science activities using a
combination of professional development and experiential curriculum. Particularly, chil-
dren’s improvement in SRL could in part be attributed to teachers’ skillfulness in leading
science activities (e.g., promoting children’s inquiry learning and sense-making) and the
quality of the science learning environment (e.g., a classroom containing developmentally
Educ. Sci. 2024, 14, 565 16 of 23

appropriate science materials that afford exploration and learning). Overall, the Farm to
ECE program supported children’s SRL, holistic understanding of basic plant science con-
cepts and science process skills, and teachers’ science teaching efficacy and metacognitive
awareness as well.
Our study also has implications regarding the unique challenges and strengths related
to conducting education research with rural populations in the U.S. Idaho ranks 44th of
the 50 states in population density, averaging 22.3 per square mile [111] As a result, we
were only able to enroll 20 childcare centers. The majority of the childcare centers in this
study were located in dispersed rural areas within a 2 h radius from the lead author’s
university, which inevitably increased the cost of delivering PD materials and instructional
coaching. However, the teachers seemed to be very enthusiastic about the PD content, and
only one teacher dropped out due to not having enough eligible children in her classroom.
We attribute our high retention rate to the fact that early childhood teachers, especially
those in remote rural areas, receive very limited financial and training support and are
eager for content-rich PD and curriculum that are related to their lived experiences in
rural areas (i.e., agriculture, gardening). Early childhood teachers in rural areas are one of
the least studied populations, and future researchers should be mindful of the challenges
and strengths associated with conducting research with this population. In particular,
place-based PD (e.g., PD centered on the farm culture) seemed to gain traction among
rural teachers. Future researchers and policymakers should continue to create and support
place-based, experiential PD and curriculum for early childhood teachers and children in
rural communities.

Author Contributions: Conceptualization, S.C., A.A., A.S., L.L.T. and A.J.R.; Methodology, S.C.; Soft-
ware, S.C.; Formal analysis, S.C.; Investigation, S.C., R.S., K.H. and S.M.; Resources, S.C., A.A., A.S.,
L.L.T. and A.J.R.; Data curation, S.C., R.S., K.H. and S.M.; Writing—original draft, S.C.; Writing—review
& editing, R.S., K.H., S.M., A.A., A.S., L.L.T. and A.J.R.; Visualization, S.C.; Supervision, S.C., R.S. and
A.S.; Project administration, S.C., R.S. and K.H.; Funding acquisition, S.C. All authors have read and
agreed to the published version of the manuscript.
Funding: This work is supported by the Professional Development for Agricultural Literacy grant
program, [grant no. 2022-68018-36258/project accession no. 1027835], from the U.S. Department of
Agriculture, National Institute of Food and Agriculture.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki and approved by the Institutional Review Board of University of Idaho (protocol code
21-233, 7 January 2022).
Informed Consent Statement: Informed consent was obtained from all participants involved in the
study.
Data Availability Statement: Data will be made available upon request.
Conflicts of Interest: The authors declare no conflicts of interest.

Appendix A. Children’s Independent Learning Development Checklist

Based on your recent observation of the child in the past two months, this child:

Self-Regulated Learning Skills Always Usually Sometimes Never

Emotional
1. Can speak about own and others’ behavior and Consequences.
2. Tackles new tasks confidently.
3. Can control attention and resist distraction.
4. Monitors progress and seeks help appropriately.
5. Persists in the face of difficulties.
Educ. Sci. 2024, 14, 565 17 of 23

Self-Regulated Learning Skills Always Usually Sometimes Never

Prosocial
1. Negotiates when and how to carry out tasks.
2. Can resolve social problems with peers.
3. Shares and takes turns independently.
4. Engages in independent cooperative activities with peers.
5. Is aware of feelings of others and helps and comforts.
Cognitive
1. Is aware of own strengths and weaknesses.
2. Can speak about how they have done something or what they
have learned.
3. Can speak about future planned activities.
4. Can make reasoned choices and decisions.
5. Asks questions and suggests answers.
6. Uses previously taught strategies.
7. Adopts previously heard language for own purposes.
Motivational
1. Finds own resources without adult help
2. Develops own ways of carrying out tasks
3. Initiates activities
4. Plans own tasks, targets, and goals
5. Enjoys solving problems

Appendix B. Science Teaching and Environment Quality

Note. Only the interview protocol is shown in Appendix B due to the size of the full
instrument and copyright issues. Interested users can contact the Educational Development
Center https://edc.org/ (accessed on 6 May 2024) for the full instrument and training.
Introduction Script
Today is_____________________ (month/day/year), I’m with ________ (teachers’ name), ID
number______. I just observed the ______activity featuring ________ (fruit/veggie/grain).
I have 4 questions about the activity you did today. There are no right or wrong answers,
we are simply interested in your opinion.
Interview Questions
1. Reflect on the activity you did today, how did you prepare for this topic? How did
you introduce the children to this topic?
2. What have you learned about children’s understanding of this topic up to this point?
a. How have you learned this?
b. Do you document learning in any way?
c. How do you keep and use your information about children’s science learning?
“Science” here refers to the food and agriculture knowledge in the Farm to
ECE curriculum.
d. Do you use this information in planning? If so, how?
3. What additional materials and activities do you plan to provide related to this topic
and why?
4. What are the most important strategies you use to support children’s science learn-
ing? “Science” here refers to the food and agriculture knowledge in the Farm to
ECE curriculum.
Educ. Sci. 2024, 14, 565 18 of 23

Appendix
Educ. Sci. 2024, 14, x FOR PEER REVIEW C. Science Teaching Efficacy Beliefs and Outcome Expectancy 20 of 24
Educ. Sci. 2024, 14, x FOR PEER REVIEW There are no right or wrong answers in this list of statements. It is simply a matter
20 of 24
of what is true for you. Read every statement carefully and choose the one that best
describes you.
Strongly disagree Strongly
Disagree (2) Neutral (3) Agree (4)
(1)
Strongly disagree
Strongly
Agree (5)
Strongly
Strongly
 I am aware of the strengths and weak- Disagree
Disagree (1) (2)DisagreeNeutral (3)
(2) Neutral (3)Agree (4) (4)
Agree
Agree (5)
(1) Agree (5)
 nesses
Science Teaching in my
I am aware of the strengths and weak- teaching.
Efficacy Beliefs
I am continually
Inesses try to in use my
improving
teaching
teaching.
my science that
techniques teaching practice.

I know worked
I try theto steps in necessary
use the
teachingpast. techniques
to teach science thateffectively.
I am confident
Iworked use myin strengths
that I can
the past. to
explaincompensate
to students forwhy science
experiments
my work.
weaknesses in my teaching.
 I use my strengths to compensate for
I am confident
I pace
my myself
weaknesses that Iwhilecan
in teach
myI am teaching
science
teaching. in or-
effectively.
I wonder Ider pace toImyself
if have
have enough
the Itime.
necessary
while skills to teach
am teaching in or-science.
 I asktomyself
der have periodically
enough time. if I meet my
I understand science concepts well enough to be effective
teaching
in teaching
I ask myself goals
science. while I amifteaching.
periodically I meet my
GivenIteaching ask myself
a choice,goals how
I would wellI am
while
invite I ahave accom-
teaching.
colleague to evaluate my
science plished
I ask teaching. my teaching
myself how well I have accom- goals once I am fin-
ished.
plished my
I am confident thatteaching
I can answer goalsstudents’
once I am fin-
science Iished. know
questions. what skills are most important
Whenin I aknow orderwhat
student tohasbeskills
a good areteacher.
difficulty understanding
most importanta science
concept, Iinhave I am a confident
specific
order to be a good teacher. that
reason I know how to help the
for choosing
student each understand
teaching ittechnique
better. I use in class.
 I have a specific reason for choosing
WhenIeach teaching
can teaching
motivatescience, I am confident
myself
technique to Iteach
use in
enough
whenclass.I
to welcome
student questions.
 really need to
I can motivate myself to teach when I teach.
I know Ireally what
set my tospecific
need
do to increase
teaching
to teach.
student
goalsinterest
before Iin science.
Science start Teaching
teaching. Outcome Expectancy
 I set my specific teaching goals before I
WhenIstart afind
studentmyself
teaching.
does better than
assessing how usual
usefulin science,
my it is
often because the teacher exerted a little extra effort.
teaching
The inadequacy
I find myself techniques are while I am my
of aassessing
student’s how scienceuseful
background can be
teaching.
teaching
overcome by good teaching. techniques are while I am
 I ask myself if I could have used differ-
Whenteaching. a student’s learning in science is greater than
expected, ent
I asktechniques itmyself
is mostifoften Iafter
could dueeachhave teaching
to theirused expe-
differ-
teacher having
foundent rience. a more effectiveafter
techniques teachingeach approach.
teaching expe-
The teacher Irience. have iscontrol
generally over how well for
responsible I teach.
students’ learning
in science. II am haveaware control of what
over how teaching well techniques
I teach.
If students’ II am use aware
while
learning Iofamin
whatteaching
science
teachingis lesstechniques
than expected, it is
most likely II use due to ineffective
different
use while I am teaching teaching science
techniquesteaching.de-
Students’ pending learning on the
in situation.
I use different teaching techniques de- to their
science is directly related
teacher’s Ipending askeffectiveness
myself on the
in science
questions
situation. about teaching.
the teach-
Whening a low achieving
materials I amchildgoing progresses
to use. more than
expected I askinmyself science,
questions
it is tousually
about
due
the
to the
teach- attention
 Iing check regularly
materials what extent myextrastu-
given by the teacher.I am going to use.
If parents dents
I check comprehend
regularly the topic while I am
comment thatto what
their childextent my stu-
is showing more
interest teaching.
dents comprehend
in science at school, the it topic whiledue
is probably I amto the
performance After
teaching. teaching
of the child’s a point, I ask myself if I'd
teacher.
Minimal teach
After it more
teaching
student effectively
learninga point, nextmyself
I ask
in science time.
can if I'd be
generally
attributed Iteach know what
toittheir I am
teachers. expected
more effectively next time. to teach.
 II knowuse helpful what teaching
I am expected techniques
to teach. auto-
 matically.
I use helpful teaching techniques Appendix auto-D. Metacognitive Awareness Inventory for Teachers
 Imatically.
know when each teaching technique I
There are no right or wrong answers in this list of statements. It is simply a matter
 use
I know willwhen be most each effective.
teaching
 Iuse organize my time
oftechnique
to best accomplish
what is Itrue for you. Read every statement carefully and choose the one that best
will be most effective.
my teaching describes you.
 I organize mygoals.time to best accomplish
 I askteaching
my myself questions
goals. about how well I Strongly Disagree
Neutral (3) Agree (4)
Strongly
Disagree (1) (2) Agree (5)
 Iam askdoingmyself while I am teaching.
questions about how well I
 II ask
am
am awaremyself
doing
of if
while
the strengths
I have
I am considered
and weaknesses in my teaching.
teaching. all pos-
 sible
II ask techniques
try tomyself
use teaching after
if I have teaching
techniques
considered thata worked
point.
all pos-in the past.
sible techniques after teaching a point.
References
References
1. Taranto, D.; Buchanan, M.T. Sustaining lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
1. Educ. 2020,
Taranto, D.;11, 5–15. https://doi.org/10.2478/dcse-2020-0002.
Buchanan, M.T. Sustaining lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
2. Panadero, E. A review
Educ. 2020, 11, 5–15. of self-regulated learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
https://doi.org/10.2478/dcse-2020-0002.
2. https://doi.org/10.3389/fpsyg.2017.00422.
Panadero, E. A review of self-regulated learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
  ent
Iin
After
worked
Idents ask
use techniques
ordermyself
teaching
in
different behow
to the aafter
ateaching
goodwell
point,
past. each
teacher. teaching
IItechniques
have
ask accom-
myself expe-
if I'd
de- I (1) Agree (5)
 Iteaching.
nesses set
ask my
myself specific
comprehend
in my periodically
teaching.teaching
the ifgoals
topic while before
I important
meet my
ImyamIfin- Strongly disagree Strongly

Educ. IIing
Sci. rience.
Iplished
teach
know
am
can
find
pace awarewhat
motivate
myself
myself
materials
2024,it 14,
my
more xof skills
FOR what
teaching myself
assessing
Iwhileam
effectively
are
going
PEER tomost
teaching
I goals
am teach
how techniques
useful
teaching
to
REVIEW
next use.
once when
time.I amin or- 20 of 24
 pending
start
Iteaching.
teaching have
am
use
ask a
aware
my
myself specific
on
teaching.
goalsof
strengths
the
if the
Iwhilereason
couldstrengths
to
situation. for
compensate
have
Iteacher.
am choosing
and
usedthat
teaching. weak-
for
differ- (1) Disagree (2) Neutral (3) Agree (4)
 Ider
in
really
teaching
I try
use
check to
order
towhileuse
need
haveto teaching
be
Itoam
techniques
enough
regularly a good
teach. teaching
to techniques
are
time.
what while
extent I am
my stu- Agree (5)
 ished.
each
IAfter
Inesses
my
Ient
have
know
ask
find
ask
control
teaching
what
in
weaknesses
myself
myself
techniques
myself
teaching how
over
technique
Iteaching.
myquestions amin
assessing
aafter
how
expected
my
well
point, each well
Iteaching
use
Iteaching.
about
Ihow
have
ask to Iin
the
usefulteach.
accom-
myself
class.
teach.
teach-
my
expe-
if I'd
 worked
Iteaching.
dents have
use
am
set
ask my a in
different
aware
myself the
specific
comprehend of past.
periodicallyreason
teaching
the strengths
teaching
the for choosing
techniques
goals
if
topic I and
meet
while weak-
before
my
Ide-
am I
 Iplished
ing
teaching know
am
can
try
use
pace aware
to what
motivate
use
helpful
itmyself
materials xof skills
teachingwhat
myself
teaching
techniquesIwhileamPEER are most
teaching
to teach
Itechniques
goingamtechniques important
techniques
teaching
to use. Iwhen
thatauto-
in or-I Strongly disagree Strongly
Educ.
 Sci. rience.
teach
Ieach
pending
nesses
start
Iteaching.
teaching use
ask
2024,
my 14,
my
inmore
teaching FOR
teaching
strengths
on
teaching.
myself my
goalsthe
if effectively
technique toare
situation.
teaching.
Ipast.
could
while
goals while
REVIEW
amnext
compensate
have once
I use
Iteacher. usedtime.
in
teaching.
am
Iclass.
amforfin-
differ- Disagree (2) Neutral (3) Agree (4) 20 of 24
 in
Imatically.
really
Iworked
der
teaching. order
use
check
have towhile
need
haveto
in
control be
Ito
the am
enough
regularly aover good
teach. teaching
to time.
what
how extent
well my
I teach.
teach. stu- (1) Agree (5)
 Iished.
my know
can
ask what
weaknesses
motivate
myself Iassessing
amin
myself
questions expected
my Iteaching.
to teach
about tothe whenteach-ifI I'd Strongly disagree Strongly
Educ.  Sci. I try
Ient
After
Idents
find
ask
have
use
am
set
know
ask
to
aware
my
my
use
myself
techniques
myself
teaching
a14,
myself
comprehend
565
teaching
specific
different ofhow
strengths
when the
eachaafter
periodically
if I
well
point,
reason
teaching
could
techniques
each
strengths
teaching
to
the
Ihow
ask
for goals
compensate
teaching if
topic
have I
useful
teaching
have accom-
myself
choosing
techniques
and
that
technique
meet
while
used weak-
before
my
expe-
de-
for
my
I
differ-am I Disagree (2) Neutral (3) Agree (4)
 Iteaching
Ireally
ing
worked
rience.
plished
teach
2024,
know
am aware
usematerials
pace what
helpful
myself
itneedin
my
more to
the skills
ofteaching
techniques what
Iwhile
teach.
teaching am going
past.
effectively
are most
teaching
Iare
amtechniques
goals
important
techniques
teaching
to
while
next use.
once I am
time. auto-
in or-
Iclass.
am fin- (1) Agree (5)of 23
19
each
pending
nesses
start
my
use
teaching
teaching.
ent teaching
will in
techniques on
teaching.
weaknessesbemy the
most
goals technique
situation.
teaching.
in
while
after my
effective.
I
each Iteaching
use
teaching.
am in
teaching. expe-
 in
Imatically.
Ider
teaching. amorder
use
set
check
use
have towhile
my
my have
aware to be
Iof
specific
regularly am
enough
strengths
control athe
over good
teaching
teaching
to to teacher.
time.
strengths
what
how goalsand
extent
compensate
well weak-
before
my
I teach.
teach. forstu- I
 ished.
IIrience. know
can
ask what
motivate
myself Iassessing
am
myself
questions expected
to teach to when I I'd Strongly disagree Strongly
I try
After findto
pace
organize
ask
have
use
know
use
myself
myself
myself
teaching
ain myteaching
specific
different
when how while
time well
a reason
point,
teaching
each
to amIabout
Itechniques
teaching Ihow
best have
ask
for
techniques
the
useful
teaching
accomplish
accom-
myself
choosing
technique
teach-
that inmy
ifor-
de- I Disagree (2) Neutral (3) Agree (4)
 nesses
start
Idents
my
Iworked
really
ing ask
know
am
use myself
teaching.
weaknesses
awarewhat
helpful
need
materials in
my
comprehend of
to
the if teaching.
periodically
I
skills
I what
teachingin
could
teach.
am
past.
the
my
are
going most
teaching if
topic
teaching.
have
techniques
to
I meet
while
used
important
techniques
use.
my
I
differ-
auto-am (1) Agree (5)
 teaching
der
my
plished
Iteach
each
pending have toteaching
ithave
teaching mytechniques
more
control
on enough
thegoals.
teaching
effectively
over
technique are
time.
how
situation. goals while
next
wellonce
Iteaching
use Iteach.
Itime.
in am
Iclass.
am fin-
use
Iteaching
teaching.
ent try
find
pace will
to be
use
myself
techniques
myself most
goals
teaching
assessing
while effective.
while
after Iam
Ieacham
techniques
how teaching.
useful
teaching that my
expe-
in or-
 Iin
Imatically.
teaching.
Iished. amorder
use
set
check
use while
aware
my
my
ask aware
know
to be
Iof
specific
regularly
myself am
strengths
what
athe good
periodically
questions
I whatam
teaching
to teacher.
strengths
teaching
what
toteaching
expected about goalsand
extent
compensate
if Ito meet
how weak-
before
my my
wellstu-
forI I I Strongly Strongly
 worked
Iteaching
After
rience.
der
Istart
am
can
ask
have
use
know
motivate
asktomyself
organize
myself
have
a in my of
the how
techniques
teaching enough
specific
different
when
myself
questions
time
past. well
a reason
point,
teaching
each
toareto
best
time.
teaching
teach
Iabout
have
while
Itechniques
ask
for
the Iteach.
techniques
when
accomplish
accom-
myself
choosing am
technique
teach-if I'd
de- I Disagree (1)
Disagree (2) Neutral (3) Agree (4)
Agree (5)
 nesses
Idents
my
teaching
am
Iing
really ask
know
use doing in
teaching.
weaknesses
myself
helpful
while my
comprehend
goals
what while
Itoif
am teaching.
I
skills in
could
while
teaching the
my topic
teaching.
have
areIteaching.
Iteaching
am am
most while
used
teaching.
techniques important I
differ-
auto-am
 my
Iplished
teaching.
teach use
ask
have itneed
materials
teaching
my
myselfmy
more
strengths
control Iteach.
goals.
teaching am
effectively
periodically
over going
to
howgoals to
next
compensate
if
well Iuse.
once Itime.
meet Iclass.
am
teach. forfin-
my
 Ieach
pending
use
teaching.
ent try
find
pace
use
ask teaching
will
to use
myself
techniques
my on
be
myself
myself the
most
teaching
strengths
how technique
while situation.
ifassessing effective.
after
to
have Ieach
am
compensate
well
Iteaching Iteaching
techniques
Ihow use
teaching
have
considered in
useful
for
accom-thatmy
all my
expe-
in or-
weaknesses in
pos-
 Iin
matically.
ished.
my
I
teaching
order
use
set
check
ask
know my
weaknesses
myself
to
different
what
be
specific
regularly
goals ifI
a
questions
I am
good
inteaching
to
could
while my
teacher.
what
expected
I techniques
about goals
extent
teaching.
have
am how
used
to
teaching. before
my de-
well
differ-
teach. stu- II
 Iteaching
worked
After
rience.
der myam
can
ask aware
motivate
myself
organize
teaching.
to in
teaching
have my of
the
techniques
enough what
myself
questions
time
past.
a point, teaching
toareto
time. I teach
about
best while
ask techniques
the when
accomplish
I
myself amteach-if I I'd
 Iplished
sible
pending
start
dents
am
ent
Ireally
have
know
know
pace
a my
techniques
teaching.
askdoing comprehend
what
techniques
myself
teaching
specific
when
on the
while each
skills
after
reason
after the
Iteaching
am are
goals
teaching
teaching
situation.
Ieach
for
topic
teaching.
Imost
once
choosing
while aIpoint.
technique
important
teaching
am I am
expe-
fin-
or-I
 ing
my
teaching.
teach
Iished. use
use
ask
have
myself
helpful
while
itneed
materials
teaching
my
myselfmore
control Itohow
am Iwhile
teaching
teach.
goals.
strengths am
effectively
periodically
over
well
going
to
how
am teaching
have
techniques
to
next
compensate
ifuse
well
accom-
Iuse.
Itime.
meet teach.
in
auto-
for
my
 each
use
Iteaching. ask
find
pace
ask teaching
will
myself be
myself
myself
myself most technique
questions
assessing
while effective.
if aIteaching
have I am I
about
how
teaching
considered thein
usefulin class.
teach-
order
all my
pos- to have
 in
Irience.
der
plished
matically. order
use
set
check
ask to haveto be
my
different
my enough
teaching
specific
regularly questions good
teaching teacher.
time.
goals
toexpected
what once
techniques
about goals
extenthow Imyam
before de-
well fin-
stu- II
my
teaching
Iteaching know
am
can weaknesses
myself
aware goals
what
motivate ofif Iam
IIwhat
skills in
could
while
myself my
are teaching.
have
I best
am
most
teaching
to used
to
teaching.
teach important differ-
teach.
techniques
when I
References
 I
ing
After
sible
Iished. organize
enough
have
ask
know
time.
materials
techniques
a
myself my
techniques
teaching
specific
control
when
time
aam
periodically
over
each point,
after
reasonto
going
are
how I to
while
ask
teaching
teaching forif
wellaccomplish
use. I
myself
choosing
I meet
I am
a point.
teach.
technique my if I'd
 pending
start
dents
am
ent
Iin
really
my
Iteach
teaching. pace
ask
use doing
techniques
order
check helpful
while
itneed
teaching
on
teaching.
comprehend
be
the
towhile
myself
myself Ito
regularly
more how
am while
teachingsituation.
ateach.
goals. good
effectivelywell
to
the
Iteaching
afteramIeach
what
topic
teaching.
amI have
techniques
teacher. extent
next
while
teaching
teachingaccom-
time. my
I
auto-am
expe-
in or-I
stu-
1. each
teaching
use
teaching.
I
Irience.
der
Taranto,
know
am
ask
find
ask
ask teaching
aware
will
myself
myself
myself D.;
goals
what
be
myself Buchanan,
of
most technique
skillswhile
what
questions
assessing
periodically
if Iteaching are I
effective.
have am M.T.
most
teaching I
about
if how
I use
meet
considered Sustaining
thein
teaching.
important
useful
my class.
techniques
teach-
I all my
teaching
pos- lifelong
goals learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 plished
matically.
Idents setto
have
use
ask
know
have
my
awhat
comprehend
myself
enough
teaching
specific
different
my questions
if Iam
IIatime reason
could
time.
teaching
thegoals
about
topic
have
expected once
forgoals
choosing
techniqueshow
while
used
to am
beforeIde-
well
differ-
teach. am fin-
II
References
 in
I
ing
teaching
After
sible
Iished.
each
pending
Educ.
can
ask
order
use
while
have
know
2020,
motivate
myself
while
organizeI am
materials to my11,
be
I how
am
teaching.
techniques
teaching
techniques
askdoing
myself
control
when
teachingon
5–15.
myself
a good
am
periodically
the over
each
well
teaching
point,
after
technique
tohttps://doi.org/10.2478/dcse-2020-0002.
going
are
how
to
I
teaching
situation. I teach
have
teacher.
best to
while
ask
teaching
Iif
well I
myselfwhen
accom-
accomplish
use. am
a class.
I technique
use meet
Iin point.
teach. my if I I'dI
2. start
am
teaching.
Ient use
Panadero,teaching.
techniques
helpful while
E. teaching
A Ireason
afteram
review teaching.
each of teaching
techniquesself-regulated expe-
auto- learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
Ireally
plished
my
teaching.
teach have
use itneed
my
aregularly
different
teaching
check more to
specific teach.
teaching
goals.teaching
effectivelytoare goals
what for once
choosing
techniques
extent
next time.Imyam de- fin-lifelong
stu-
1.
 teaching
I
use
Iished.
After
rience.
Taranto,
I know
am
can
ask
find
ask
ask aware
willmyself
myself
myself D.;
goals
what
be
motivate
myself
teaching
Buchanan,
of
most
how skillswhile
what
questions
if assessing
I a well
have
point, I I am
teaching
effective.
myself to M.T.
mostteach
about
have how
considered
I ask
Sustaining
teaching.
important
techniques
the
usefulwhen
accomplished
myself teach-
all my I
pos-
if I'd my teaching learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
References matically.
Ipending
each
Idents https://doi.org/10.3389/fpsyg.2017.00422.
set my
ask
know specific
teachingon
comprehend
myself
what the
questions
if Iam teaching
IIatechnique
situation.
could the I goals
about
topic
have
expected use howin
while
used
to beforeI amII
class.
well
differ-
teach.
 Iin
really
ing
teaching Educ.
ask
order
use
goals 2020,
myself
while
organize
once
need
materials toImy11,
be
I
amtohow
am
techniques 5–15.
time good
finished.
teach.
am well
teaching
tohttps://doi.org/10.2478/dcse-2020-0002.
going
are I
best have
teacher.to
while accom-
accomplish
use. I am
 sible
Iteach
start have
know techniques
itcontrol
more
when
teaching. over
each after
effectively how teaching
teaching next
well a point.
Itime.
teach.
technique I
2. IIent
am
teaching.
plished
Iteaching.
my
can
ask
use doing
Panadero,
have
use
set
check
what
motivate
myself
techniques
helpful
my
different
teaching
my
while skills
E.teaching
aregularly
specific
myself
questions
Ateaching
goals.
are
Ireason
after
teaching am
review
teaching
tomost
goals
toexpected
what
teach
about
teaching.
each of
for
important
the
teaching
techniques whenteach-
self-regulated
once
choosing
techniques
goals
extent Imyam
beforeexpe-
auto-
de-
Ifin-
stu- learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
I lifelong
1. IIuse
inreally
ing
After
rience.
matically.
Taranto,
know
am
find
know
ask aware
will
order what
need
materials
myself D.;
what
be
to
myself
teaching
Buchanan,
of
most
be I
skills
toif Ia am
what
teach.
I aam are
have
point,
https://doi.org/10.3389/fpsyg.2017.00422.
teaching
effective.
good
assessing most
going M.T.
teacher.
how toSustaining
important
to
considered
I ask use.
myselfteach.
techniques
useful all my
in order
pos-
if I'd to be alearning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
References ished.
each
Ipending
start
dents ask teachingon11,
teaching.
comprehend
myself the
if technique
questions situation.
I5–15.
could the I use
about
topic
have howin class.
while
used well
I amI
differ-
 IIteach
Iteaching
sible Educ.
use
good
have
set
check
have my2020,
helpful
while
organize
teacher.
a myI
regularly
techniques
itcontrol
more amteaching
techniques
specific time teaching
reasonto
teachinghttps://doi.org/10.2478/dcse-2020-0002.
are
toteaching
after
effectively
over what
how
techniques
best while
for
teaching
next
wellaccomplish
I
choosing
goals
extent am auto-
abefore
Itime. my
point.
teach. stu- I
2. Ient
am
teaching. know
can
ask
finddoing when
what
motivate
myself
myself
techniques
Panadero, while each
skills
E.questions
A myself are
Ireview
assessing
afteram tomostteach
about
teaching.
each how
of
technique
important
the
useful
teaching whenteach-
self-regulated my
expe-I I learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1. Imatically.
my
teaching.
each
start
dents use different
teaching
teaching
teaching.
comprehend goals.teaching
technique the techniques
I use
topic in
while Ide-
class. am
 Iuse
in
Ireally
ing
Ipending
teaching
After
rience.
Taranto,
know
am aware
will
order
have a
askmaterials D.;
what
be
to be
specific
need
myself Buchanan,
of
most
to I
techniques
teaching a am
what good
reason
teach.
ifIeach
Iaamhave expected
point, teaching
effective.
for
going M.T.
teacher. to
choosing
to use.
considered
are I while
ask
Sustaining
teach.
techniques
I am
myself each
all ifpos- lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
teaching
I'd
References Ihttps://doi.org/10.3389/fpsyg.2017.00422.
Iteaching. know
ask
findmyself
can
Educ. when
motivate
myself
2020, on the
11,questions
if assessing
5–15. teaching
situation.
Imyself
could about
have
to teach
how technique
how
used
usefulwhen well
differ-
my I II
https://doi.org/10.2478/dcse-2020-0002.
 IIteaching.
sible use
set
check helpful
while
organize
technique
have my a I myI
use
specific
regularly
techniques amteaching
time
in teaching
class.
reasonto
teaching
to how
after what techniques
bestfor
teaching accomplish
choosing
goals
extent auto-
abefore
my
point. stu- I
Iteach have itcontrol
more effectively
over next
well Itime.
teach.
2. Iuse
am
ent
really
teaching
After
Imatically.
my
each
ask will
Panadero,
use
myself
doing
techniques
needbe
teaching
different
teaching
teaching
most
while
E.toquestions
techniques Ateach.
goals.
effective.
Ireview
aafterameach
point,
teaching
technique are about
teaching.
while
Itechniques
ask
of
I use
the
teaching I am
myself teach-
self-regulated
in
expe-
class. if I'd learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
de-
1. start
dents
I Taranto,
ask
know
am teaching.
comprehend
myself
aware D.;
what Buchanan,
ofifI I am
what could the topic
have
expected
teachingM.T. towhile
Sustaining
used I
differ-
teach.
techniques am lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 ing
rience.
Iteaching.
teach
Ient
I organize
can
set motivate
askmaterials
myself
my my
specific
it when
more time
myself
Ieach
Iam
ifeffectively
have toconsidered
to
going
teaching
https://doi.org/10.3389/fpsyg.2017.00422.
know
best
teach
teaching to accomplish
when
use.
goals
next time. I really
all pos-
before
technique I need
References
 pending
Iteaching.
Istart ask
can
find
Educ.
touse myself
motivate
myself
2020,
techniques
helpful
while
teach.
on11,
I
the
questions
am
situation.
myself
assessing
5–15.
after
teaching teaching toabout
teach
how
techniques how
usefulwhen well
my I II
https://doi.org/10.2478/dcse-2020-0002.
each teaching expe-
auto-
 IImy
sible
use
IAfter
am have
ask
know
ask
teaching
check regularly
techniques
control
teaching.
myself
will what
myself
doing be ifgoals.
most
while IA over
Iam
questions
toexpected
after
could what
how
effective. teaching
have
about
extent
well used
tothe
a my
I teach.point.
teach.
differ-
teach-
stu-
2. really
teaching
rience.
Imatically.
ITaranto, Panadero,
use
ask
need
different
myself E.to
techniques
teaching a Ireview
teach. am
point,
teaching
questions
teaching.
are while
Itechniques
of
about how I am
askself-regulated
myself if I'd
de-
well learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1. dents
I
ent find
am comprehend
myself
aware
techniques D.; Buchanan,
of assessing
whatafter the topic
teaching
each M.T.
how while
Sustaining
useful
techniques
teaching ImyamIlifelong
expe- learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 Ihttps://doi.org/10.3389/fpsyg.2017.00422.
ing
Iteaching.
teach
Iam
pending
use
ask
set
have
know
helpful
organize
setmaterials
my
myself
my my
specific
specific
itcontrol
more
when
on the
teaching
time
Iteaching
Ieach
overam
ifeffectively
have going
teaching
how
techniques
toconsidered
best
teaching
situation.
goalsto accomplish
goals
next
well before
use.
Itime. auto-
allI start
before
teach.
technique pos- II teaching.
References teaching.
teaching
I
rience.
matically. Educ.
use doing
2020,
while while
11,
techniques
I am I
5–15. am
teaching teaching.
https://doi.org/10.2478/dcse-2020-0002.
are while I am
 IImy
sible
start
use
IAfter ask
know
am
teaching
check aware
findwill
ask
regularly
techniques
teaching.
myself
what
myself be E. of
goals.
if IIam
ifIeach
most what
questions
toexpected
after
could whatteaching
have
teaching
effective. about
extent
used
to a my
point.
differ-
teach.
techniques
the teach-
stu-
2. Iteaching.
IIent ask
Panadero,
use
have
know
myself
myself
teaching
different
control
when
assessing
A ahave
over point,
review
teaching howhow
teaching ofuseful
considered
Itechniques
ask
well myself my all
self-regulated
I teach.
technique
teaching
pos-
if
de- I'd learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1.
 dents
Isible
ask
Taranto,
find
use myself
comprehend
myself
techniques
helpful
while
organize
techniques D.;
my
questions
Buchanan,
I am
are assessing
time
while after
teaching the
teaching
Itoeach
am about
topic
bestM.T.
how how
while
Sustaining
useful
teaching
techniques
accomplish
teaching. well
ImyamIIlifelong
expe-
auto- learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
ing
teach materials
techniques
it more I am after
effectively
https://doi.org/10.3389/fpsyg.2017.00422. going to
teaching
next use. a
time. point.
References pending
Iuse
am
teaching.
teaching
rience.
askdoing
am
Educ. myself
aware
will
2020, on
be if what
the
of
most
while
11,
techniques
I5–15.
could
situation.
Ieffective. have used
amteaching
teaching. differ-
techniques
https://doi.org/10.2478/dcse-2020-0002.
are while I am
 matically.
IImy use
check
know different
teachingregularly
what goals.teaching
toexpected
what techniques
extent de-
myexpe- stu-
2. Ient
Iteaching.
After asktechniques
ask
use
ask myself
while
organize
myself
Panadero,myself
teaching myif
E. IIA
if Iam
I questions
am aafter
time
could teaching
have
point,
reviewtoeach
have about
best used
considered
I of
ask to
teaching
the teach.
accomplish teach-
different
myself all if
self-regulated pos- techniques
I'd learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1. Ipending
dents have
know
ask
Taranto, control
when
myself on
comprehend
D.; the over
each
questions
Buchanan, how
teaching
situation.
the well
about
topic
M.T. I teach.
technique
how
while
Sustaining well
I amIIlifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.

References Imy
rience.
Iing
sible
teach usematerials
after
use helpful
each teaching
different
teaching
techniques
it more teaching
I
goals. am
teaching
after
effectively
https://doi.org/10.3389/fpsyg.2017.00422. techniques
experience.
going to use.
techniques
teaching
next a
time. auto-
de-
point.
 Iuse
am
teaching. ask
am
ask
Educ. myself
aware
will
myself
doing
2020, be of
while
11,if
most I
what
questions could
Ieffective.
5–15. am have
teaching
about
teaching. used
the differ-
techniques
teach-
https://doi.org/10.2478/dcse-2020-0002.
1. matically.
Ipending have
check
ask
Taranto, control
regularly
myself on the
D.; over
questions how
toexpected
what
situation. well
about extent I teach.
how teach.
my wellstu-Ilifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
2. Ient
Iing
After know
use
ask
Panadero,while
organize
have what
techniques
control
materials
myself
teaching myIBuchanan,
E. amIIA
over
if Iam
timeafter
aam teaching
havehow toeach
going
point,
review best
wellM.T.
to
considered
I of
ask toSustaining
teaching
Iaccomplish
teach.
use.
myself allexpe-
self-regulated pos-
if I'd


IIdents
am know
am
ask
Educ. awarewhen
comprehend
myself
doing
2020, of
while
11, each
what
questions I
5–15. am teaching
the topic
teaching
about
teaching. technique
while
techniques
the I
teach- amI learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
https://doi.org/10.2478/dcse-2020-0002.
References Ihttps://doi.org/10.3389/fpsyg.2017.00422.
rience.
Iteach
my
sible use
use
check helpful
different
teaching
it regularly
techniques
more teaching
goals.teaching
to what
after
effectively techniques
techniques
teachingextent
next a my
time. auto-
de-
point. stu-
2. use
teaching.
Iing use
ask will
while
ammaterials
aware
Panadero,myself be most
ofI if
am
what
IAIam effective.
teaching
have teaching
going totechniques
considered use. I use while
all pos- I
1. matically.
pending
ITaranto,
dents have
ask
know myself onE.the
control
comprehend
D.;
what I over
questions
Buchanan,am
reviewhow
situation.
the
expected
of
well
about
topic
M.T.
self-regulated
to I teach.
how
whileteach.
Sustaining well
I amIlifelong learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 IIAfter amorganize
useteaching
check teaching
different my
regularly time
a after
point,
teaching
to to
whatbest ask accomplish
Itechniques
myself
extent my ifstu-
de- I'd
 Isible
Iteaching.
am know
am
ask
techniques
https://doi.org/10.3389/fpsyg.2017.00422.
awarewhen
myself of each
what
questions I amteaching
teaching
teachingabout the
a
technique point.
techniques
teach- I
References Ipending
my
teach usedoing
Educ. 2020,while
helpful
teaching
it more
11,
onmost
thegoals. 5–15.
teaching
effectively
situation.
teaching.
https://doi.org/10.2478/dcse-2020-0002.
techniques
nextwhile time.auto-
dents
use
Iing use willcomprehend
while be I am the
effective.
teaching topic I am on
2. After
matically.
Iteaching.
use
ask different
materials
Panadero,
ask
myself
teaching
myself E. teaching
if IA Ia
questions
am
have
point,
review techniques
going I to
considered
ask
of
about
use.
myself depending
all if
self-regulated
how
pos- learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
wellI'd Ilifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
1.

References IIteach Taranto,
know
organize
the situation. D.;my
what Buchanan,
I timeam expected
to bestM.T. toSustaining
the teach.
accomplish teach-
 sible
IEduc. use
check
know different
it regularly
techniques
more
when teaching
effectivelyto
after
https://doi.org/10.3389/fpsyg.2017.00422.
each what
teaching techniques
teachingextent
next a
time.
techniquemy de-
point. stu- I
 am
ing
Imy
After doing
2020,
materials
useteaching
helpful
teaching while
11, I am
teaching I
5–15. am goingteaching.
https://doi.org/10.2478/dcse-2020-0002.
point,techniques
asituation. to use.
I ask myself auto-
if I'd
1. pending
dents
Iuse Taranto, comprehend
D.; goals.
onquestions
the
Buchanan, the topic
M.T. while
Sustaining I am lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
2. Iteach I know
askwill
ask myself
Panadero, what
myself be E. ifIeffectively
most AIam have expected
effective.
review about
considered
of theto teach.
teachingall pos-
self-regulated materials I am
References

matically.
I
teaching.
Isible
check
ask
Educ.
use
it regularly
myself
2020,
more
helpful 11,questions
5–15.
teaching
to what about extent
next time.
how my
the teach- wellstu-
https://doi.org/10.2478/dcse-2020-0002.
techniques auto- I learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
organize
going to use.
techniquesmy time after
https://doi.org/10.3389/fpsyg.2017.00422. to best
teaching accomplisha point.
2. dents
Iam
ing
After knowdoingcomprehend
when
what
materials
Panadero, teaching while IIeach
E.goals.Aam aamIreview
am theteaching.
teaching
expected
going
point,
topicto
I of
while
technique
teach.
to self-regulated
ask use.
myself
I amI
if I'd learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1. matically.
my teaching
Taranto, D.; Buchanan, M.T. Sustaining lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 teaching.
use
IIteach use
checkwill
helpfulbe most teaching effective. techniques auto-
References I
ask
check
ask itregularly
myself
myselfmoreif
regularly I to
have
effectively what
to
https://doi.org/10.3389/fpsyg.2017.00422.
know when each
questions teaching
extent
considered
what extent
next
about
mytime.
technique
how
students
all
my pos-
wellstu- II
 After
Idents Educ.
organize
comprehend
matically.
sible 2020,
teaching
techniquesmy11,
the 5–15.
a
time point,
topic
after tohttps://doi.org/10.2478/dcse-2020-0002.
I
best
while ask
teachingI myself
accomplish
am teaching.
a point. if I'd
2. Iuse
am know will
doing
Panadero,
comprehend
what
bewhile
most
E. IAam theteaching.
expected
effective.
Ireview
am topicto
of
whileteach.
self-regulated
I am
learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1. teach
my
ITaranto, know it when
teaching more
D.; effectively
goals.
each
Buchanan, teaching next
M.T. time.
technique
Sustaining I lifelong
 teaching.use
After helpful
organize
teaching my ifteaching
atimepoint,
IIhttps://doi.org/10.3389/fpsyg.2017.00422.
ask myself Iamhave techniques
toIconsidered
best
ask accomplish
myself auto-
ifall
I’d teach
pos- it morelearning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 use know
ask
Educ. will what
myself
2020, benext
most
11, I
questions expected
effective.
5–15. about tohow teach. well
https://doi.org/10.2478/dcse-2020-0002. I
References After
matically.
my
sible teaching
effectively
teaching
techniques a after
time.
goals. point, I ask myself
teaching a point. if I'd
2. Iam
teach use doing
Panadero,helpful
organizeit morewhile
my
E. teaching
Atime Ireview
effectivelyam toteaching.
techniques
best of
nextaccomplish
self-regulated
time. auto- learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1. ITaranto,
know when each teaching technique
how well IIlifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 I ask
know
matically.
myself
what questions
D.; IBuchanan,
am expected
IIhttps://doi.org/10.3389/fpsyg.2017.00422.
ask myself ifgoals.
about
M.T. Sustaining
to teach.
my
use
am know
Educ.
teaching
will
doing what
2020, bewhile
most
11, I Iam have
Ieffective.
5–15. am
considered
expected
teaching. to teach. all pos-
https://doi.org/10.2478/dcse-2020-0002.
References
 Isible
know
ask techniques
whenquestions
myself each after teaching
teachingabout a point.
technique
how well II
2. IPanadero,
use helpful
organize
use helpful
ask myself my
E. ifteaching
time
teaching
A I have
reviewto techniques
best of accomplish
techniques
considered auto-
automatically.
all
self-regulated pos- learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1. use
Taranto,
am will be
doing D.; most
Buchanan,
while Ieffective.
am M.T.
teaching. Sustaining lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
matically.
my
sible teaching
techniques goals. after teaching a point.
https://doi.org/10.3389/fpsyg.2017.00422.
References IEduc.
organize
know
ask 2020,
when
myself my11,
each
if I5–15.
time tohttps://doi.org/10.2478/dcse-2020-0002.
teaching
have besttechnique
considered accomplish allI use
pos- will be
 I know whenquestions
ask effective.
myself each teaching abouttechnique
how well II
2. mymost
Panadero,
sible teaching
techniques E.goals.A reviewafter of self-regulated
teaching a point. lifelong learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1.
References use
Taranto,
am will
doing be
D.; most
Buchanan,
while Ieffective.
am M.T.
teaching. Sustaining learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
 Ihttps://doi.org/10.3389/fpsyg.2017.00422.
ask myself questions about how well I
 IEduc.
organize
organize
ask 2020,
myself my
my 11,time
if I5–15.
time tohttps://doi.org/10.2478/dcse-2020-0002.
to best
have best accomplish
accomplish
considered allmypos- teaching goals.
1. Taranto,
am doingD.; Buchanan,
while M.T. Sustaining lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
References
2. myPanadero,
sible teaching
techniques E.goals.A Ireview am teaching.
after teaching of self-regulated
a point. learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
 Educ.
I ask 2020, questions
ask myself 11,if I5–15. haveabout
Ihttps://doi.org/10.3389/fpsyg.2017.00422.
myself https://doi.org/10.2478/dcse-2020-0002.
how wellall
considered I am
pos- doing while I
1. ITaranto,
ask myself
am teaching. D.; questions
Buchanan, about
M.T. how
Sustaining well I lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
2. Panadero,
sible techniques E. A review after teaching of self-regulated
a point. learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
References am
Educ. doing
2020, while
11, I
5–15. am teaching.
https://doi.org/10.2478/dcse-2020-0002.
https://doi.org/10.3389/fpsyg.2017.00422.
2. I ask
ask myself
IPanadero,myselfE. ififI A have
I have considered
review considered all possible
of self-regulated all pos-techniques learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
1.
References Taranto,
after teaching D.; Buchanan,
a point. M.T. Sustaining lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
sible techniques after teaching a point.
https://doi.org/10.3389/fpsyg.2017.00422.
Educ. 2020, 11, 5–15. https://doi.org/10.2478/dcse-2020-0002.
1. Taranto, D.; Buchanan, M.T. Sustaining lifelong learning: A self-regulated learning (SRL) approach. Discourse Commun. Sustain.
2. Panadero, E. A review of self-regulated learning: Six models and four directions for research. Front. Psychol. 2017, 8, 422.
References References Educ. 2020, 11, 5–15. https://doi.org/10.2478/dcse-2020-0002.
https://doi.org/10.3389/fpsyg.2017.00422.
2. Taranto, Panadero, Buchanan, E. A review of Sustaining self-regulated learning: Six models and fourlearning
directions forapproach.
research. Front. Psychol. 2017, 8, 422.
1.1. Taranto,D.; D.; Buchanan,M.T. M.T. Sustaininglifelong lifelonglearning:
learning:AAself-regulated (SRL) approach.Discourse
self-regulated learning(SRL) DiscourseCommun.
Commun.Sustain.
Sustain.
Educ. https://doi.org/10.3389/fpsyg.2017.00422.
Educ.2020,2020,11, 11,5–15. 5–15.[CrossRef]
https://doi.org/10.2478/dcse-2020-0002.
2.2. Panadero, Panadero,E.E.AAreview reviewofofself-regulated
self-regulatedlearning: learning:Six
Sixmodels
modelsand andfour
fourdirections research.Front.
directionsforforresearch. Front.Psychol. 2017,8,8,422.
Psychol. 2017, 422.
[CrossRef] https://doi.org/10.3389/fpsyg.2017.00422.
3. Zimmerman, B.J. Self-regulated learning and academic achievement: An overview. Educ. Psychol. 1990, 25, 3–17. [CrossRef]
Educ. Sci. 2024, 14, 565 20 of 23

4. Schunk, D.H.; Greene, J.A. Handbook of Self-Regulation of Learning and Performance; Routledge: London, UK, 2017. [CrossRef]
5. Dent, A.L.; Koenka, A.C. The relation between self-regulated learning and academic achievement across childhood and adoles-
cence: A meta-analysis. Educ. Psychol. Rev. 2016, 28, 425–474. [CrossRef]
6. Chu, L.; Li, P.H.; Yu, M.N. The longitudinal effect of children’s self-regulated learning on reading habits and well-being. Int. J.
Educ. Res. 2020, 104, 101673. [CrossRef]
7. Mahatmya, D.; Lohman, B.J.; Matjasko, J.L.; Farb, A.F. Engagement across developmental periods. In Handbook of Research
on Student Engagement, 1st ed.; Christenson, S.L., Reschly, A.L., Wylie, C., Eds.; Springer: Berlin, Germany, 2012; pp. 45–63.
[CrossRef]
8. McLaughlin, K.A.; Sheridan, M.A.; Humphreys, K.L.; Belsky, J.; Ellis, B.J. The value of dimensional models of early experience:
Thinking clearly about concepts and categories. Perspect. Psychol. Sci. 2021, 16, 1463–1472. [CrossRef] [PubMed]
9. Whitebread, D.; Neale, D. Metacognition in early child development. Transl. Issues Psychol. Sci. 2020, 6, 8. [CrossRef]
10. Şen, Ş.; Yılmaz, A.; Geban, Ö. The effects of process oriented guided inquiry learning environment on students’ self-regulated
learning skills. Probl. Educ. 21st Century 2015, 66, 54–66. [CrossRef]
11. Ucan, S.; Webb, M. Social regulation of learning during collaborative inquiry learning in science: How does it emerge and what
are its functions? Int. J. Sci. Educ. 2015, 37, 2503–2532. [CrossRef]
12. Winne, P.H. Modeling self-regulated learning as learners doing learning science: How trace data and learning analytics help
develop skills for self-regulated learning. Metacogn. Learn. 2022, 17, 773–791. [CrossRef]
13. Avargil, S.; Lavi, R.; Dori, Y.J. Students’ metacognition and metacognitive strategies in science education. Cogn. Metacogn. Cult.
STEM Educ. 2018, 24, 33–64. [CrossRef] [PubMed]
14. Zohar, A.; Barzilai, S. A review of research on metacognition in science education: Current and future directions. Stud. Sci. Educ.
2013, 49, 121–169. [CrossRef]
15. Zimmerman, A.; Moylan, B. Handbook of Metacognition in Education; Routledge: London, UK, 2009.
16. Bjorklund, D.F. Children’s Thinking: Cognitive Development and Individual Differences; Sage: Thousand Oaks, CA, USA, 2022.
17. Landis, T.; Hart, C.; Graziano, P. Targeting self-regulation and academic functioning among preschoolers with behavior problems:
Are there incremental benefits to including cognitive training as part of a classroom curriculum? Child Neuropsychol. 2019, 25,
668–704. [CrossRef] [PubMed]
18. Bronson, M.B.; Bronson, M. Self-Regulation in Early Childhood: Nature and Nurture; Guilford Press: New York, NY, USA, 2001.
19. Whitebread, D.; Coltman, P.; Pasternak, D.P.; Sangster, C.; Grau, V.; Bingham, S.; Almeqdad, Q.; Demetriou, D. The development
of two observational tools for assessing metacognition and self-regulated learning in young children. Metacogn. Learn. 2009, 4,
63–85. [CrossRef]
20. Dörr, L.; Perels, F. Improving metacognitive abilities as an important prerequisite for self-regulated learning in preschool children.
Int. Electron. J. Elem. Educ. 2019, 11, 449–459. [CrossRef]
21. Azevedo, R. Reflections on the field of metacognition: Issues, challenges, and opportunities. Metacogn. Learn. 2020, 15, 91–98.
[CrossRef]
22. Flavell, J.H. Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. Am. Psychol. 1979, 34,
906–911. [CrossRef]
23. Marulis, L.M.; Nelson, L.J. Metacognitive processes and associations to executive function and motivation during a problem-
solving task in 3–5 year olds. Metacogn. Learn. 2021, 16, 207–231. [CrossRef]
24. Rouault, M.; McWilliams, A.; Allen, M.G.; Fleming, S.M. Human metacognition across domains: Insights from individual
differences and neuroimaging. Personal. Neurosci. 2018, 1, e17. [CrossRef] [PubMed]
25. Schraw, G.; Moshman, D. Metacognitive theories. Educ. Psychol. Rev. 1995, 7, 351–371. [CrossRef]
26. Escolano-Pérez, E.; Herrero-Nivela, M.L.; Anguera, M.T. Preschool metacognitive skill assessment in order to promote an
educational sensitive response from mixed-methods approach: Complementarity of data analysis. Front. Psychol. 2019, 10,
1298–1309. [CrossRef]
27. Gonzales, C.R.; Merculief, A.; McClelland, M.M.; Ghetti, S. The development of uncertainty monitoring during kindergarten:
Change and longitudinal relations with executive function and vocabulary in children from low-income backgrounds. Child Dev.
2022, 93, 524–539. [CrossRef] [PubMed]
28. Jean, P.; Inhelder, B. The Psychology of the Child; Basic Books: New York, NY, USA, 2008.
29. Wimmer, H.; Perner, J. Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s
understanding of deception. Cognition 1983, 13, 103–128. [CrossRef]
30. Chen, S.; McDunn, B. Metacognition: History, measurements, and the role in early childhood development and education. Learn.
Motiv. 2022, 78, 101786. [CrossRef]
31. Marulis, L.M.; Palincsar, A.S.; Berhenke, A.L.; Whitebread, D. Assessing metacognitive knowledge in 3–5 year olds: The
development of a metacognitive knowledge interview (McKI). Metacogn. Learn. 2016, 11, 339–368. [CrossRef]
32. Kattner, F.; Bryce, D. Attentional control and metacognitive monitoring of the effects of different types of task-irrelevant sound on
serial recall. J. Exp. Psychol. Hum. Percept. Perform. 2022, 48, 139–158. [CrossRef]
33. Roebers, C.M.; van Loon, M.H.; Buehler, F.J.; Bayard, N.S.; Steiner, M.; Aeschlimann, E.A. Exploring psychometric properties of
children’ metacognitive monitoring. Acta Psychol. 2021, 220, 103399. [CrossRef] [PubMed]
Educ. Sci. 2024, 14, 565 21 of 23

34. Fleming, S.; Dolan, R. The neural basis of metacognitive ability. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2012, 367, 1338–1349.
[CrossRef]
35. Metcalfe, J.; Schwartz, B.L. The ghost in the machine: Self-reflective consciousness and the neuroscience of metacognition. In
Oxford Handbook of Metamemory; John, D., Sara, T., Eds.; Oxford University Press: Oxford, UK, 2016; pp. 407–424. [CrossRef]
36. Eberhart, J.; Bryce, D.; Baker, S. Staying Self-Regulated in the Classroom: The Role of Children’s Executive Functions and Situational
Factors; OSF: Peoria, IL, USA, 2023. [CrossRef]
37. Perry, N.E.; VandeKamp, K.O.; Mercer, L.K.; Nordby, C.J. Investigating teacher-student interactions that foster self-regulated
learning. In Using Qualitative Methods to Enrich Understandings of Self-Regulated Learning; Perry, N., Ed.; Routledge: London, UK,
2023; pp. 5–15. [CrossRef]
38. Dignath, C.; Veenman, M.V. The role of direct strategy instruction and indirect activation of self-regulated learning—Evidence
from classroom observation studies. Educ. Psychol. Rev. 2021, 33, 489–533. [CrossRef]
39. Ergen, B.; Kanadli, S. The effect of self-regulated learning strategies on academic achievement: A meta-analysis study. Eurasian J.
Educ. Res. 2017, 17. [CrossRef]
40. Schuster, C.; Stebner, F.; Geukes, S.; Jansen, M.; Leutner, D.; Wirth, J. The effects of direct and indirect training in metacognitive
learning strategies on near and far transfer in self-regulated learning. Learn. Instr. 2023, 83, 101708. [CrossRef]
41. Sukowati, S.; Sartono, E.; Pradewi, G. The effect of self-regulated learning strategies on the primary school students’ independent
learning skill. Psychol. Eval. Technol. Educ. Res. 2020, 2. [CrossRef]
42. Theobald, M. Self-regulated learning training programs enhance university students’ academic performance, self-regulated
learning strategies, and motivation: A meta-analysis. Contemp. Educ. Psychol. 2021, 66, 101976. [CrossRef]
43. Xu, Z.; Zhao, Y.; Zhang, B.; Liew, J.; Kogut, A. A meta-analysis of the efficacy of self-regulated learning interventions on academic
achievement in online and blended environments in K-12 and higher education. Behav. Inf. Technol. 2023, 42, 2911–2931.
[CrossRef]
44. Garcia, R.; Falkner, K.; Vivian, R. Systematic literature review: Self-regulated learning strategies using e-learning tools for
Computer Science. Comput. Educ. 2018, 123, 150–163. [CrossRef]
45. Babakr, Z.; Mohamedamin, P.; Kakamad, K. Piaget’s cognitive developmental theory: Critical review. Educ. Q. Rev. 2019, 2,
517–524. [CrossRef]
46. Vandenbroucke, L.; Spilt, J.; Verschueren, K.; Piccinin, C.; Baeyens, D. The classroom as a developmental context for cognitive
development: A meta-analysis on the importance of teacher-student interactions for children’s executive functions. Rev. Educ.
Res. 2018, 88, 125–164. [CrossRef]
47. Venitz, L.; Perels, F. The promotion of self-regulated learning by kindergarten teachers: Differential effects of an indirect
intervention. Int. Electron. J. Elem. Educ. 2019, 11, 437–448. [CrossRef]
48. Karlen, Y.; Hirt, C.N.; Jud, J.; Rosenthal, A.; Eberli, T.D. Teachers as learners and agents of self-regulated learning: The importance
of different teachers competence aspects for promoting metacognition. Teach. Teach. Educ. 2023, 125, 104055. [CrossRef]
49. Jacob, L.; Benick, M.; Dörrenbächer, S.; Perels, F. Promoting self-regulated learning in preschoolers. J. Child. Educ. Soc. 2020, 1,
116–140. [CrossRef]
50. Oates, S. The importance of autonomous, self-regulated learning in primary initial teacher training. Front. Educ. 2019, 4, 102.
[CrossRef]
51. Sermeno, R. Investigating Head Start Teachers’ Science Teaching Attitudes and Efficacy. Master’s Thesis, University of Idaho,
Moscow, ID, USA, 2022. ProQuest Dissertations & Theses Global.
52. Fusaro, M.; Smith, M.C. Preschoolers’ inquisitiveness and science-relevant problem solving. Early Child. Res. Q. 2018, 42, 119–127.
[CrossRef]
53. Gopnik, A. Childhood as a Solution to Explore–Exploit Tensions. Philos. Trans. R. Soc. 2020, 375, 20190502. [CrossRef]
54. Cremin, T.; Glauert, E.; Craft, A.; Compton, A.; Stylianidou, F. Creative little scientists: Exploring pedagogical synergies between
inquiry-based and creative approaches in early years science. In Creativity and Creative Pedagogies in the Early and Primary Years;
Cremin, R., Ed.; Routledge: London, UK, 2018; pp. 45–60. [CrossRef]
55. Tippett, C.D.; Milford, T.M. Findings from a pre-kindergarten classroom: Making the case for STEM in early childhood education.
Int. J. Sci. Math. Educ. 2017, 15, 67–86. [CrossRef]
56. Shultz, T.R.; Nobandegani, A.S. A computational model of infant learning and reasoning with probabilities. Psychol. Rev. 2022,
129, 1281–1295. [CrossRef]
57. Walker, C.M.; Bridgers, S.; Gopnik, A. The early emergence and puzzling decline of relational reasoning: Effects of knowledge
and search on inferring abstract concepts. Cognition 2016, 156, 30–40. [CrossRef]
58. Helm, J.H.; Katz, L.G.; Wilson, R. Young Investigators: The Project Approach in the Early Years; Teachers College Press: New York, NY,
USA, 2023.
59. Adbo, K.; Vidal Carulla, C. Learning about science in preschool: Play-based activities to support children’s understanding of
chemistry concepts. Int. J. Early Child. 2020, 52, 17–35. [CrossRef]
60. Dilek, H.; Taşdemir, A.; Konca, A.S.; Baltaci, S. Preschool children’s science motivation and process skills during inquiry-based
STEM activities. J. Educ. Sci. Environ. Health 2020, 6, 92–104. [CrossRef]
61. Raven, S.; Wenner, J.A. Science at the center: Meaningful science learning in a preschool classroom. J. Res. Sci. Teach. 2023, 60,
484–514. [CrossRef]
Educ. Sci. 2024, 14, 565 22 of 23

62. O’Connor, G.; Fragkiadaki, G.; Fleer, M.; Rai, P. Early childhood science education from 0 to 6: A literature review. Educ. Sci. 2021,
11, 178. [CrossRef]
63. Cantor, P.; Osher, D.; Berg, J.; Steyer, L.; Rose, T. Malleability, plasticity, and individuality: How children learn and develop in
context. In The Science of Learning and Development; Routledge: London, UK, 2021; pp. 3–54.
64. Aydoner, S.; Bumin, G. The factors associated with school readiness: Sensory processing, motor, and visual perceptual skills, and
executive functions in kindergarten children. Appl. Neuropsychol. Child. 2023, 12, 1–9. [CrossRef] [PubMed]
65. Mavilidi, M.F.; Okely, A.; Chandler, P.; Domazet, S.L.; Paas, F. Immediate and delayed effects of integrating physical activity into
preschool children’s learning of numeracy skills. J. Exp. Child Psychol. 2018, 166, 502–519. [CrossRef]
66. Saxena, A.; Lo, C.K.; Hew, K.F.; Wong, G.K.W. Designing unplugged and plugged activities to cultivate computational thinking:
An exploratory study in early childhood education. Asia-Pac. Educ. Res. 2020, 29, 55–66. [CrossRef]
67. Darling-Hammond, L.; Flook, L.; Cook-Harvey, C.; Barron, B.; Osher, D. Implications for educational practice of the science of
learning and development. Appl. Dev. Sci. 2020, 24, 97–140. [CrossRef]
68. Bjerknes, A.L.; Wilhelmsen, T.; Foyn-Bruun, E. A systematic review of curiosity and wonder in natural science and early childhood
education research. J. Res. Child. Educ. 2024, 38, 50–65. [CrossRef]
69. Ravanis, K. Research trends and development perspectives in Early Childhood Science Education: An overview. Educ. Sci. 2022,
12, 456. [CrossRef]
70. Kastriti, E.; Kalogiannakis, M.; Psycharis, S.; Vavougios, D. The teaching of Natural Sciences in kindergarten based on the
principles of STEM and STEAM approach. Adv. Mob. Learn. Educ. Res. 2022, 2, 268–277. [CrossRef]
71. Larimore, R.A. Preschool science education: A vision for the future. Early Child. Educ. J. 2020, 48, 703–714. [CrossRef]
72. Saçkes, M.; Trundle, K.C.; Bell, R.L.; O’Connell, A.A. The influence of early science experience in kindergarten on children’s
immediate and later science achievement: Evidence from the early childhood longitudinal study. J. Res. Sci. Teach. 2011, 48,
217–235. [CrossRef]
73. Gerde, H.K.; Pierce, S.J.; Lee, K.; Van Egeren, L.A. Early childhood educators’ self-efficacy in science, math, and literacy instruction
and science practice in the classroom. Early Educ. Dev. 2018, 29, 70–90. [CrossRef]
74. Nores, M.; Friedman-Krauss, A.; Figueras-Daniel, A. Activity settings, content, and pedagogical strategies in preschool classrooms:
Do these influence the interactions we observe? Early Child. Res. Q. 2022, 58, 264–277. [CrossRef]
75. Guo, Y.; Piasta, S.B.; Bowles, R.P. Exploring preschool children’s science content knowledge. Early Educ. Dev. 2015, 26, 125–146.
[CrossRef] [PubMed]
76. Ljung-Djärf, A.; Magnusson, A.; Peterson, S. From doing to learning: Changed focus during a pre-school learning study project
on organic decomposition. Int. J. Sci. Educ. 2014, 36, 659–676. [CrossRef]
77. Hamel, E.; Joo, Y.; Hong, S.Y.; Burton, A. Teacher questioning practices in early childhood science activities. Early Child. Educ. J.
2021, 49, 375–384. [CrossRef]
78. Sins, P.; de Leeuw, R.; de Brouwer, J.; Vrieling-Teunter, E. Promoting explicit instruction of strategies for self-regulated learning:
Evaluating a teacher professional development program in primary education. Metacogn. Learn. 2024, 19, 215–247. [CrossRef]
79. Pendergast, E.; Lieberman-Betz, R.G.; Vail, C.O. Attitudes and beliefs of prekindergarten teachers toward teaching science to
young children. Early Child. Educ. J. 2017, 45, 43–52. [CrossRef]
80. Park, M.H.; Dimitrov, D.M.; Patterson, L.G.; Park, D.Y. Early childhood teachers’ beliefs about readiness for teaching science,
technology, engineering, and mathematics. J. Early Child. Res. 2017, 15, 275–291. [CrossRef]
81. Yıldırım, B. Preschool STEM activities: Preschool teachers’ preparation and views. Early Child. Educ. J. 2021, 49, 149–162.
[CrossRef]
82. Dunekacke, S.; Barenthien, J. Research in early childhood teacher domain-specific professional knowledge—A systematic review.
Eur. Early Child. Educ. Res. J. 2021, 29, 633–648. [CrossRef]
83. Kelter, J.; Peel, A.; Bain, C.; Anton, G.; Dabholkar, S.; Horn, M.S.; Wilensky, U. Constructionist co-design: A dual approach to
curriculum and professional development. Br. J. Educ. Technol. 2021, 52, 1043–1059. [CrossRef]
84. Zepeda, S.J. Professional Development: What Works; Routledge: London, UK, 2019. [CrossRef]
85. De Boer, H.; Donker, A.S.; Kostons, D.D.; Van der Werf, G.P. Long-term effects of metacognitive strategy instruction on student
academic performance: A meta-analysis. Educ. Res. Rev. 2018, 24, 98–115. [CrossRef]
86. Eberhart, J.; Schäfer, F.; Bryce, D. Are Metacognition Interventions in School-Aged Children Effective? Evidence from a Series of
Meta-Analyses; OSF: Peoria, IL, USA, 2023. Available online: https://osf.io/preprints/psyarxiv/475br (accessed on 6 May 2024).
87. Donker, A.S.; De Boer, H.; Kostons, D.; Van Ewijk, C.D.; van der Werf, M.P. Effectiveness of learning strategy instruction on
academic performance: A meta-analysis. Educ. Res. Rev. 2014, 11, 1–26. [CrossRef]
88. Philipsen, B.; Tondeur, J.; Pareja Roblin, N.; Vanslambrouck, S.; Zhu, C. Improving teacher professional development for online
and blended learning: A systematic meta-aggregative review. Educ. Technol. Res. Dev. 2019, 67, 1145–1174. [CrossRef]
89. Sims, S.; Fletcher-Wood, H. Identifying the characteristics of effective teacher professional development: A critical review. Sch.
Eff. Sch. Improv. 2021, 32, 47–63. [CrossRef]
90. Kuhn, D. Metacognition matters in many ways. Educ. Psychol. 2022, 57, 73–86. [CrossRef]
91. Zohar, A.; Ben-Ari, G. Teachers’ knowledge and professional development for metacognitive instruction in the context of higher
order thinking. Metacogn. Learn. 2022, 17, 855–895. [CrossRef]
Educ. Sci. 2024, 14, 565 23 of 23

92. Zohar, A.; Lustov, E. Challenges in addressing metacognition in professional development programs in the context of instruction
of higher-order thinking. In Contemporary Pedagogies in Teacher Education and Development; Weinberger, Y., Libman, Z., Eds.;
Springer: Berlin, Germany, 2018; pp. 87–100. [CrossRef]
93. Kraft, M.A.; Blazar, D.; Hogan, D. The effect of teacher coaching on instruction and achievement: A meta-analysis of the causal
evidence. Rev. Educ. Res. 2018, 88, 547–588. [CrossRef]
94. Chalufour, I.; Worth, K.; Clark-Chiarelli, N. Science Teaching Environment Rating Scale (STERS); Education Development Center:
Waltham, MA, USA, 2006.
95. Friday Institute for Educational Innovation. Teacher Efficacy and Attitudes toward STEM (TSTEM) Survey: Development and
Psychometric Properties; North Carolina State University: Raleigh, NC, USA, 2012; Available online: https://www-data.fi.ncsu.edu/
wp-content/uploads/2020/11/01153610/T-STEM_FridayInstitute_DevAndPsychometricProperties_FINAL-1.pdf (accessed on 6
May 2024).
96. Balcikanli, C. Metacognitive Awareness Inventory for Teachers (MAIT). Electron. J. Res. Educ. Psychol. 2011, 9, 1309–1332.
[CrossRef]
97. Keselman, H.J.; Huberty, C.J.; Lix, L.M.; Olejnik, S.; Cribbie, R.A.; Donahue, B.; Kowalchuk, R.; Lowman, L.; Petoskey, M.;
Keselman, J.; et al. Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA, and ANCOVA
analyses. Rev. Educ. Res. 1998, 68, 350–386. [CrossRef]
98. Enders, C.K.; Tofighi, D. Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychol.
Methods 2007, 12, 121–138. [CrossRef] [PubMed]
99. Gelman, A.; Hill, J. Data Analysis Using Regression and Multilevel/Hierarchical Models; Cambridge University Press: Cambridge, UK,
2006.
100. Bates, D.; Mächler, M.; Bolker, B.; Walker, S. Lme4: Linear Mixed-Effects Models Using Eigen and S4. R Package Version 1.1-8.
2015. Available online: http://CRAN.R-project.org/package=lme4 (accessed on 6 May 2024).
101. Braun, V.; Clarke, V. Thematic Analysis; American Psychological Association: Washington, DC, USA, 2012. [CrossRef]
102. Cypress, B.S. Rigor or reliability and validity in qualitative research: Perspectives, strategies, reconceptualization, and recommen-
dations. Dimens. Crit. Care Nurs. 2017, 36, 253–263. [CrossRef] [PubMed]
103. Chen, S.; Geesa, R.; Izci, B.; Song, H. Investigating preservice teachers’ science and mathematics teaching efficacy, challenges, and
support. Teach. Educ. 2022, 57, 304–324. [CrossRef]
104. Anthony, C.J.; Ogg, J. Executive function, learning-related behaviors, and science growth from kindergarten to fourth grade. J.
Educ. Psychol. 2020, 112, 1563–1581. [CrossRef]
105. Hessels-Schlatter, C.; Hessels, M.G.; Godin, H.; Spillmann-Rojas, H. Fostering self-regulated learning: From clinical to whole class
interventions. Educ. Child Psychol. 2017, 34, 110–125. [CrossRef]
106. Ismail, N.M.; Tawalbeh, T.E.I. Effectiveness of a metacognitive reading strategies program for improving low achieving EFL
readers. Int. Educ. Stud. 2015, 8, 71–87. [CrossRef]
107. Zohar, A.; Peled, B. The effects of explicit teaching of metastrategic knowledge on low-and high-achieving students. Learn. Instr.
2008, 18, 337–353. [CrossRef]
108. Dodou, D.; de Winter, J.C. Social desirability is the same in offline, online, and paper surveys: A meta-analysis. Comput. Hum.
Behav. 2014, 36, 487–495. [CrossRef]
109. Başokçu, T.O.; Güzel, M.A. Beyond counting the correct responses: Metacognitive monitoring and score estimations in mathemat-
ics. Psychol. Sch. 2022, 59, 1105–1121. [CrossRef]
110. Arias, J.D.L.F.; Díaz, A.L. Assessing self-regulated learning in early childhood education: Difficulties, needs, and prospects.
Psicothema 2010, 22, 277–283.
111. U.S. Census Bureau. Quick Facts Idaho. 2020. Available online: https://www.census.gov/quickfacts/fact/table/ID/PST045223
(accessed on 6 May 2024).

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual
author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to
people or property resulting from any ideas, methods, instructions or products referred to in the content.