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This survey research, assessed whether novice secondary school teachers knew and understood the effectiveness of empirically-supported learning strategies, namely spaced practice, retrieval practice, interleaved practice, using multimodal representations, elaborative interrogation and worked-out examples. These ‘proven’ strategies can be contrasted with frequently used learning strategies that have been found to be less effective, such as re-reading, taking verbatim notes, highlighting/underlining, summarizing, and cramming. This study broadens previous research on teachers’ knowledge of learning strategies by both refining and extending the methodology used in the scenario studies, and by administering it to a different, previously unexplored population. Novice teachers enrolled in a teacher training program (N = 180) in Flanders, Belgium were presented with a three-part survey, consisting of open-ended questions, learning scenarios and a list of study strategies. The results show that misconceptions about effective study strategies are widespread by novice teachers and suggests that they are unaware of several specific strategies that could benefit student learning and retention. While popular but less effective strategies such as highlighting and summarising were commonly named by them in open-ended questions, this was not the case for proven effective strategies (e.g., studying worked-out examples, interleaving, and using multi-modal representations) which were not or hardly mentioned. We conclude that this study adds to the growing literature that it is not only students, but also novice teachers who make suboptimal metacognitive judgments when it comes to study and learning. Explicit instruction in evidence-informed learning strategies should be stressed and included in both teacher professional development programs and initial teacher training.
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Frontiers in Education 01 frontiersin.org
Novice teachers’ knowledge of
eective study strategies
Tim Surma
1
*, Gino Camp
2, Renate de Groot
2 and
Paul A. Kirschner
1,2
1 Expertise Centre for Education and Learning, Thomas More University of Applied Sciences,
Antwerp, Belgium, 2 Faculty of Educational Sciences, Open University of the Netherlands, Heerlen,
Netherlands
This survey research, assessed whether novice secondary school teachers
knew and understood the eectiveness of empirically-supported learning
strategies, namely spaced practice, retrieval practice, interleaved practice,
using multimodal representations, elaborative interrogation and worked-
out examples. These ‘proven’ strategies can be contrasted with frequently
used learning strategies that have been found to be less eective, such as
re-reading, taking verbatim notes, highlighting/underlining, summarizing, and
cramming. This study broadens previous research on teachers’ knowledge of
learning strategies by both refining and extending the methodology used in the
scenario studies, and by administering it to a dierent, previously unexplored
population. Novice teachers enrolled in a teacher training program (N = 180)
in Flanders, Belgium were presented with a three-part survey, consisting
of open-ended questions, learning scenarios and a list of study strategies.
The results show that misconceptions about eective study strategies are
widespread by novice teachers and suggests that they are unaware of several
specific strategies that could benefit student learning and retention. While
popular but less eective strategies such as highlighting and summarising were
commonly named by them in open-ended questions, this was not the case for
proven eective strategies (e.g., studying worked-out examples, interleaving,
and using multi-modal representations) which were not or hardly mentioned.
Weconclude that this study adds to the growing literature that it is not only
students, but also novice teachers who make suboptimal metacognitive
judgments when it comes to study and learning. Explicit instruction in
evidence-informed learning strategies should be stressed and included in
both teacher professional development programs and initial teacher training.
KEYWORDS
learning strategies, study strategies, teaching, teacher education, memory
Introduction
Educators are oen asked for advice on how to improve their students’ self-study
behavior. is requires teachers to expand their teaching of subject-specic information
with teaching their students how to best process this information (i.e., how to study;
Weinstein and Mayer, 1986). Research into human cognition has provided information on
TYPE Original Research
PUBLISHED 22 November 2022
DOI 10.3389/feduc.2022.996039
OPEN ACCESS
EDITED BY
Ingo Kollar,
University of Augsburg,
Germany
REVIEWED BY
Michael Rochnia,
Universität Wuppertal,
Germany
Katharina Engelmann,
University of Hildesheim,
Germany
*CORRESPONDENCE
Tim Surma
tim.surma@thomasmore.be
SPECIALTY SECTION
This article was submitted to
Teacher Education,
a section of the journal
Frontiers in Education
RECEIVED 16 July 2022
ACCEPTED 02 November 2022
PUBLISHED 22 November 2022
CITATION
Surma T, Camp G, de Groot R and
Kirschner PA (2022) Novice teachers’
knowledge of eective study strategies.
Front. Educ. 7:996039.
doi: 10.3389/feduc.2022.996039
COPYRIGHT
© 2022 Surma, Camp, de Groot and
Kirschner. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The
use, distribution or reproduction in other
forums is permitted, provided the original
author(s) and the copyright owner(s) are
credited and that the original publication in
this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms.
Surma et al. 10.3389/feduc.2022.996039
Frontiers in Education 02 frontiersin.org
concrete learning strategies that support student learning (e.g.,
Dunlosky etal., 2013), but has also shown that many learners have
awed mental models of how they learn, making them more likely
to mismanage their learning (Bjork etal., 2013). Teachers are in
the position to teach students how to optimize their use of study
time to promote ecient and eective learning and better
retention of knowledge and skills in both generic learning to learn
lessons or within their subject-specic classes (Education Council,
2006). Since the beginning of the 21
st
century, learning strategy-
instruction has indeed become part of several national curricula
(Glogger-Frey etal., 2018). e idea is that teachers’ use of the
evidence-base on eective study-strategies when advising students
can improve students’ self-study behavior (see, e.g., Biwer etal.,
2022, for a practical implementation of an evidence-based
program). To move from the evidence into the actual design of
pedagogical practices informed by this best-evidence, it is
necessary to have a deep understanding of what, how, and when
something works in optimal circumstances. To improve students’
study behaviors, it is worth exploiting the most promising
guidelines that have been shown to work for the largest possible
group of pupils. Implementation of a so-called evidence-informed
approach on teaching and learning, based on stable and robust
scientic ndings (best-evidence), then oers the chance to raise
practice (see, e.g., Slavin, 2020). e question is, however, whether
novice teachers have this accurate knowledge of the evidence on
which they can base their practice. Knowledge, acquired during
teacher education, can work as a starting point in their teaching
career upon which the can gain further expertise during their
ensuing professional career (Berliner, 2001). In this survey
research, weassessed whether novice secondary school teachers,
who recently graduated from initial teacher training, in Flanders
(Belgium) have accurate knowledge of the eectiveness and
non-eectiveness of particular study strategies.
Eective strategies for acquiring
knowledge and skills
Research on teachers’ knowledge is multifaced because of the
multiple denitions given to the knowledge itself (Elbaz, 1983;
Shulman, 1986; Darling-Hammond and Bransford, 2005).
Teachers’ knowledge about eective study-strategies is part of
what Lee Shulman termed principles of teachers’ propositional
knowledge (i.e., ‘know that’, principles derived from empirical
research and theory about learning and instruction (Shulman,
1986; Verloop etal., 2001)). Well over a century of laboratory and
applied research in cognitive and educational psychology has
brought us a number of well-established principles: certain
learning strategies promote retention more and lead to more
durable learning than others (Pashler etal., 2007; Dunlosky etal.,
2013; Fiorella and Mayer, 2016). ese strategies can belabeled as
study strategies when students independently employ them to
promote their learning by achieving goal oriented instructional
tasks, oen characterized by tests or exams (Winne and Hadwin,
1998; Dinsmore etal., 2016). Many experiments where learners
are taught or encouraged to apply specic study strategies, such as
rereading, spacing practice, summarizing or highlighting have
been conducted to determine if and how they work and to
determine which lead to longer-lasting learning (as opposed to
achievement on exams). Several key reviews reach converging
ndings (Pashler etal., 2007; Dunlosky etal., 2013; Putnam and
Roediger, 2018; Weinstein etal., 2018). In their extensive review,
Dunlosky etal. (2013) discussed 10 frequently used and researched
strategies: spaced practice, retrieval practice, interleaved practice,
rereading, imagery use for text learning, keyword mnemonic,
highlighting, summarization, self-explanation and elaborative
interrogation. ey assessed the eectiveness of these strategies
for dierent age groups, subject areas, types of learning materials,
study tasks and types of learning. Spaced practice and retrieval
practice were, amongst others, qualied as useful strategies that
promote learning, whereas highlighting, rereading, summarizing
and keyword mnemonics were seen as strategies with low utility.
Similarly, Pashler etal. (2007) identied seven eective learning
and study strategies that overlap considerably with Dunlosky etal.
(2013): spaced practice, studying worked examples, combining
graphics with verbal descriptions, using concrete representations,
retrieval practice and elaborative interrogation. ese ndings has
led the National Council on Teacher Quality (NCTQ) to describe
six learning and study strategies as the core of prospective teachers
knowledge base on eective learning processes, as their
eectiveness is supported by evidence from multiple sources and
replications, ranging from lab-based studies with paired associates
as study materials to real classroom-settings with authentic study
materials (Pomerance etal., 2016; Weinstein et al., 2018). In
Table1 these six strategies are presented and accompanied by an
example of their implementation in students’ self-study.
Distributed or spaced practice (i.e., study sessions of the same
material are distributed across time) usually improves retention of
that material in comparison to massing study of that same material
in one long session, keeping total study time equivalent in both
conditions. In a typical experiment, Nazari and Ebersbach (2019)
compared two groups of secondary school students on learning
mathematical calculations (basic probability) in either spaced
fashion (i.e., three practice sessions of 15 min on three consecutive
days) or massed fashion (i.e., one 45-min session delivered within a
single day). Students in the spaced condition outperformed the
students in the massed condition on post-tests aer 2 and 6 weeks.
Distributing practice extends the total time hypothesis (i.e., people
tend to learn more as a simple function of time spent on the learning
task; Ebbinghaus, 1964) with a timing aspect: introducing spacing
gaps between study sessions enhances long term retention. is
advantage is known as the spacing eect. For recent reviews, see
(Carpenter, 2017; Wiseheart etal., 2019; Latimier etal., 2021).
A related strategy is interleaved practice, where learners alternate
amongst several separate but related topics during one practice
session as compared to blocked practice devoted to a single topic
(Firth etal., 2021). When interleaving (also known as variability of
practice; Van Merriënboer and Kirschner, 2018), practice of each
Surma et al. 10.3389/feduc.2022.996039
Frontiers in Education 03 frontiersin.org
specic topic or task is separated from the next occurrence by the
practicing of other topics or tasks. For example, in study sequence
A-B-C-B-A-C-A-B-C… there are three tasks between the rst and
second instance of A, one between the rst and second instance of
B, and so forth. us, by using interleaved practice, learners also
achieve spacing eects but the reverse is not necessarily true. Simple
spacing (A-A-A-interval-A-A-A) does not lead to interleaving.
Interleaving practice is appropriate when students must learn to
distinguish among concepts or terms, principles or types of
problems that appear to besimilar on the surface, or see deeper level
similarities in concepts that appear on the surface to bedierent
(e.g., when to use the formulae for acceleration, velocity, and
resistance). For recent reviews, see, for example, Firth etal. (2021),
Carvalho and Goldstone (2017), and Kang (2016).
Retention is also enhanced when learners engage in retrieval
practice (practice testing) as a study strategy. Here students retrieve
what they have learned either by testing themselves or by being
tested by others such as peers or the teacher. Simply put, when
students are tested on a particular learning material, they are
required to retrieve it from their long term memory to get the
correct answer. Note, these are no-stakes tests meant to support
learning and not to assess learning (summative testing), to unfold
the study process (formative testing) or as a means for self-
evaluation. Retrieval strategies have been shown to besuperior to
non-retrieval strategies such as restudying, re-reading or copying
the information, a benet known as the testing eect (Adesope
etal., 2017; Sotola and Crede, 2021).
Elaboration entails study strategies that foster conscious and
deliberate/intentional connecting of the to-be-learned material
with pre-existing (i.e., prior) knowledge (Hirshman, 2001). To
take advantage of elaboration, students can, for instance, engage
in what is known as elaborative interrogation (i.e., posing and
answering questions about to-be-learned material). e practice
of asking epistemic questions such as “why,,” “when,” and “how,
can help increase students’ understanding and retention of
concepts (Ohlsson, 1996; Popova et al., 2014). Elaborative
interrogation demands more than just recall of facts requiring
learners to think about information on a deeper level, on such
things as causal mechanisms and comparisons between important
concepts (Pressley etal., 1987).
Learning from multimodal representations of to-be learned
material (i.e., complementing text-based study materials with
explanatory visual information such as graphs, gures and
pictures) facilitates student learning and retention compared to
studying single representations. Verbal and pictorial coding has
additive eects on recall (Paivio, 1986; Camp etal., 2021; May er,
2021). Illustrations are especially helpful when the concept is
complex or involves multiple steps (Eitel and Scheiter, 2015).
Finally, students learn more by alternating between studying
worked-out examples (i.e., studying example problems with their
solution) and solving similar problems on their own than they do
when just given problems to solve on their own (Kalyuga etal.,
2001; Renkl, 2002). Renkl etal., 1998; Kirschner etal., 2006; Van
Gog et al., 2019). Students’ procedural knowledge can
be improved by replacing approximately half the practice
problems with fully-worked-out examples and then removing
steps, one at a time (i.e., partially worked-out examples) until
only the problem remains. A common variation is to combine
worked examples with prompts to allow students to explain the
information to oneself (Bisra etal., 2018). Connecting concrete
examples to more abstract representations also allows students to
apply concepts in new situations (Weinstein etal., 2018).
Popular but less eective study strategies
Teachers’ propositional knowledge about less eective study-
strategies can also be useful; knowing which strategies are less
eective should not be ignored in evidence-informed practice
(Gorard, 2020). Research has shown that students oen employ
suboptimal study-strategies such as re-reading, taking verbatim
notes, highlighting/underlining, and cramming (see, e.g., Morehead
etal., 2016; Anthenien etal., 2018; Dirkx etal., 2019). However, in
order to recognize, identify and evaluate these strategies when used
by their students in order to eventually correct this, it is necessary for
teachers to have an accurate understanding of them. Suboptimal
strategies can bemisleading when it comes to allocating study time
in self-paced learning (Dunlosky etal., 2013).
Re-reading texts, an oen used and suggested study strategy,
is a passive study strategy as it does not require eortful processing
TABLE1 Six eective study strategies applied to students learning.
Study strategy Practical application
Distributed/spaced practice Students can plan to restudy course materials on multiple days before an exam, rather than massing their study on the day and night
before the exam.
Interleaving practice Aer studying negative slopes in graphs, students can switch to studying positive, zero, and undened slopes; next time, students can
study the four in a dierent order, promoting discrimination and selecting appropriate strategies for problem solving.
Retrieval practice When learning about social science, students can practice by recalling answers to questions rather than immediately looking up answers
in a textbook.
Elaborative interrogation When students are studying an expository text of the human circulatory cycle, students can ask and explain themselves why and how
blood ows in a particular order.
Example-based study Students can study worked-out examples to self-explain the procedure to solve quadratic equations.
Multi-modal learning Students combine verbal and pictorial information when learning about the hydrological cycle.
Surma et al. 10.3389/feduc.2022.996039
Frontiers in Education 04 frontiersin.org
of the text (Morehead etal., 2016; Dirkx etal., 2019). Moreover, it
provides students with the false impression of successful learning
due to the increased perceived uency at second reading of the
text (Rawson and Dunlosky, 2002). at is to say, when reading a
text for a second time students recognize the information in the
text but this is quite dierent from being able to remember it. A
similar manifestation of this metacognitive overcondence can
be observed with students copying or rewriting notes or texts
(Kobayashi, 2005). Here students passively engage in oen
verbatim copying of information which does not require a type of
processing of the information that stimulates long-term retention,
such as elaboration or retrieval processes. Highlighting or
underlining is a popular study strategy because of its ease of use
and its assumed potential for assisting the storage for important
sections in text materials (Morehead etal., 2016; Dirkx et al.,
2019). Although there is evidence to suggest that students recall
highlighted information better than the non-highlighted
information, in general, students’ highlighting habits are mostly
ineective as they usually underline unessential information, or
too much or too little information (Ponce etal., 2022). Cramming
is a widely used study strategy where students mass their study
sessions directly prior to exams or tests (Hartwig and Dunlosky,
2012). Massing study sessions, though fruitful for recall at a short
retention interval (i.e., performance on a test), yields sub-standard
recall in the long-term (i.e., learning).
Although summarizing and concept mapping could beseen as
potential examples of active and generative study strategies (Fiorella
and Mayer, 2016), the results of their use are oen disappointing.
Summarizing is the act of concisely stating key ideas from to-be-
learned material using one’s own words and excluding irrelevant or
repetitive material. While summarizing is eective in certain
domains and study tasks (e.g., summarizing short expository texts
for history lessons), research has shown that there are a few
important boundaries (e.g., procedural knowledge in for instance
physics and chemistry is not appropriate for creating a summary as
is vocabulary learning; Dunlosky etal., 2013). Concept mapping
might beconsidered as a form of summarizing where a graphic
organizer is created by identifying key words or ideas, by placing
them in nodes, by drawing lines linking related terms and by writing
about the nature of the relationship along those lines (Schroeder
etal., 2018). Similar to summarizing, boundary conditions of the
strategy have been identied. For instance, Karpicke and Blunt
(2011) found that for studying text passages retrieval practice is more
eective than concept mapping while observing the learning
materials. Studies have also shown that students can struggle to
create summaries or concept maps of sucient quality if they have
only received basic instructions (e.g., capturing the main points and
on excluding unimportant material, see Rinehart etal., 1986; Bednall
and James Kehoe, 2011; Schroeder etal., 2018) or have either not
suciently practiced summarizing or concept mapping so as to
acquire the necessary skills to do it well or lack the necessary prior
knowledge to identify what is important.
However, as noted by Miyatsu et al. (2018), even the
aforementioned more shallow strategies can betweaked into a
more eective approach by enriching or combining them with
eective strategies. For instance, rewriting notes by reorganizing
them elicits elaborative processing and studying one’s summary
followed by trying to reproduce it without the summary being
visible takes advantage of the benets of the testing eect. It is
known that students who solely engage in less eective strategies
(e.g., highlighting without engaging in retrieval practice) tend to
reduce their potential of recall and transfer (Blasiman etal., 2017).
Why do students not know what is
germane to their learning?
e accumulated knowledge from cognitive psychology about
how to study eectively and how to avoid ineective study
strategies does not necessarily lead to improved learning behavior
by students. e majority of self-report questionnaires reveals that
students are oen not aware of the advantages of retrieval practice,
spaced practice, and elaboration strategies and do not oen
implement them in their self-regulated learning. Most students
use strategies, such as repeatedly rereading their learning materials
or massing their study, which hamper, rather than improve, their
eectiveness as learners (see, e.g., Kornell and Bjork, 2007;
Karpicke etal., 2009; McCabe, 2011; Hartwig and Dunlosky, 2012;
Dirkx et al., 2019). is might be partially explained by two
accounts. First, students (and teachers were former students) are
susceptible to – oen false – metacognitive intuitions or beliefs
about learning which inuences their knowledge (for an overview
of biases and classic beliefs in human learning, see, e.g., Koriat,
1997; Bjork etal., 2013). For instance, monitoring judgments of
learning is typically based on cognitive cues that learners consider
to bepredictive for their future memory performance, that is, they
confuse initial performance with learning for long-term
maintenance (Soderstrom and Bjork, 2015). Ineective strategies
such as massed practice (as opposed to spaced practice), blocked
practice (as opposed to interleaved practice), rereading (as
opposed to elaboration and retrieval practice) intuitively seem to
bemore satisfying and uent because the learner makes quicker
gains during initial study. ese quick gains create “illusions of
learning” such as the stability bias which make learners believe
that their future performance will remain as high as during initial
study (Kornell and Bjork, 2009).
Study strategies such as spaced practice, interleaved practice
and retrieval practice reduce this illusion of learning. ey can
begrouped under the overarching concept of desirable diculties,
learning strategies that initially feel dicult in that they do cause
errors and appear to slow down learning, but result in long lasting
learning (Bjork, 1994). Even when learners experience memory
benets from these desirable diculties, earlier research has
shown a lack of awareness of the eectiveness of the strategies
when predicting their own future learning while using spaced
practice (Rawson and Dunlosky, 2011), retrieval practice (e.g.,
Roediger and Karpicke, 2006), and interleaved practice (e.g.,
Kornell and Bjork, 2008; Hartwig etal., 2022).
Surma et al. 10.3389/feduc.2022.996039
Frontiers in Education 05 frontiersin.org
A second reason why students might not use the most eective
study techniques is that students never learned how to study
eectively or having learnt it, have not properly practiced it so as
to make it a part of their repertoire, or struggle to maintain
benecial habits of studying (Fiorella, 2020). One inuential
source of such information is the teacher, who could provide
students with metacognitive instructions (see further). Research
suggests that teachers could improve students’ knowledge about
study strategies by embedding explicit strategy instruction into
their subject-content teaching (Putnam etal., 2016; Rivers, 2021).
However, several surveys indicate that only 20–36% of students
report having been taught about study strategies (Kornell and
Bjork, 2007; Hartwig and Dunlosky, 2012). In large international
assessments, Flemish students self-report that only 55% of their
teachers support their learning processes (OECD, 2019).
The case for explicit strategy instruction
Pintrich (2002) and Muijs and Bokhove (2020) suggest that
explicit instruction of study-strategies should consist of pointing
out the signicance of a strategy (‘know that’, i.e., conceptual or
propositional knowledge), how to employ the strategy in
classroom settings (‘know how’, i.e., prescriptive or procedural
knowledge), and monitoring and evaluating proper use of the
strategy while providing instructional scaolds. For instance,
students in courses with explicit instruction on implementing
retrieval practice in self-study were more likely to use the strategy
compared to the control group who did not receive explicit
instruction (McCabe, 2011). Biwer etal. (2020) compared two
groups of undergraduate students who were randomly assigned to
either a 12-week “Study Smart”-program where they received
explicit instruction on metacognitive knowledge or a control
group. During three sessions students learned about when and
why particular learning strategies were eective; reected on and
discussed their strategy use, motivation, and goal-setting;
experienced ineective versus eective strategies (i.e., highlighting
versus practice testing) and practiced the strategies in subject-
specic courses. Students in the Study-Smart-condition gained
more accurate knowledge of eective study strategies (e.g., rated
methods based on retrieval practice as more eective and
highlighting as less eective) and reported, for instance, an
increased use of practice testing and less usage of ineective study
strategies such as highlighting and rereading.
If teachers do not have the propositional knowledge relating
to eective study strategies, they cannot beexpected to use, model
them or explicitly teach students to use them. Willingham (2017)
describes this as the necessity to “have a mental model of the
learner”: because the teacher can recognize the underlying
mechanisms in instructional methods or study approaches (e.g.,
retrieval processes while using ashcards), they can also transfer
these strategies to novel situations. Teacher knowledge has indeed
been dened as a central element and precursor of teaching
competence (for a full discussion on teacher knowledge for
teaching and learning, see, e.g., Toom, 2017). Understanding the
essential theoretical concepts of the strategies is required to notice,
scaold, and teach strategy-use in generic learning-to-learn
courses or subject-specic courses (Glogger-Frey etal., 2018).
Earlier studies on the use of research evidence nd that teachers
pay limited attention to best-evidence ndings and rarely consult
it to improve their practices (Dagenais etal., 2012; Walker etal.,
2019). In addition, there is some evidence that teachers do not
begin their careers with this foundational knowledge about
eective strategies for learning and study. Research by the National
Council for Teaching Quality in UnitedStates showed that the way
in which essential information on eective learning is covered in
the written study material used in in pre-service teacher education
programs is inadequate (Pomerance etal., 2016). is was partially
replicated by Surma etal. (2018) for Dutch and Flemish teacher
education. ey found that in general, teacher education textbooks
and syllabi do not suciently cover essential learning strategies
from cognitive psychology or, in some cases, do not cover them at
all. For instance, only three teacher education programs (out of
24) provided textbooks and syllabi with a full coverage on spaced
practice and retrieval practice (i.e., conceptual information,
prescriptive information on how to apply the strategy in regular
classrooms, and references to research). Such results indicate that
teacher candidates may beunder-informed, or not informed by
their study materials about eective learning strategies.
In addition to research on the textbooks and syllabi used in
teacher education, survey research is an oen-used method to
gain insight in teachers’ knowledge. McCabe (2018) had academic
support instructors rate a list of 36 study strategies for their
eectiveness on 5-point Likert-scale (from not eective to
extremely eective). Several eective study strategies were
recognized as eective (e.g., retrieval practice, answering
questions, spacing study sessions), whereas some (e.g., multi-
modal learning, interleaved practice) were less recognized.
Ineective study strategies (e.g., rereading, copying notes
verbatim) consistently had lower ratings. McCabe also asked the
instructors to predict the outcomes of four learning scenarios
where two contrasting study strategies were contrasted, each one
describing a ecologically valid/realistic educational situation.
Learning scenarios are a type of vignette-based research, which is
becoming more popular in social science studies because it allows
respondents to react to context-specic cues such as real-life
classroom conditions (Aguinis and Bradley, 2014). e use of
learning scenarios to grasp instructors’ knowledge has since then
been replicated and extended for other populations, such as
pre-service teachers and in-service teachers (Halamish, 2018;
Firth etal., 2021), university instructors (Morehead etal., 2016)
and medical faculty (Piza etal., 2019). e results were mixed,
with some educators capable of both identifying some eective
strategies (e.g., retrieval practice contrasted with the more passive
restudying, Firth et al., 2021) and simultaneously being
unsuccessful in distinguishing an eective strategy from a less
eective one (e.g., interleaved practice versus blocked practice in
all o the aforementioned studies). Table2 provides a summary of
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all the studies on metacognitive judgments of learning strategies
using scenario-methodology.
Broadening the research base on
knowledge of eective study strategies
e current research broadens previous research on teachers
knowledge of eective study strategies by both rening and
extending the methodology used in the earlier scenario studies,
and by administering it to a dierent, previously unexplored
population (i.e., novice teachers). Earlier studies using the
scenario-method had some limitations regarding the number of
study strategies being assessed/rated, the sampling method used,
and the lack of open-ended questions that were presented to
the respondents.
First, most studies only examined a limited number of
learning scenarios where more eective study strategies were
contrasted with less eective ones (Morehead et al., 2016;
Halamish, 2018; Firth etal., 2021). Only spacing, testing, and
interleaving were included in each study, which are all examples
of study strategies within the desirable diculties paradigm (see
Table2). Other study strategies with a robust evidence base, such
as studying worked-out examples, elaboration and using multi-
modal representations were rarely or not assessed by teachers.
Moreover, retrieval practice, for example, has not been assessed in
relation to a non-passive study strategy (such as concept mapping).
Increasing the number of scenarios is particularly interesting
because the study strategies can also beinterpreted as instructional
strategies from the teacher’s perspective. For instance, teachers can
use retrieval practice by integrating regular low stakes quizzes in
their classrooms (Agarwal etal., 2021). As such, the knowledge
about the strategies in the scenarios also provides insight into the
teacher’s pedagogical knowledge. In the present research
weintroduce the participants to seven learning scenario’s which
tackle all the aforementioned limitations.
Second, in previous studies the sample ranged from
pre-service teachers to more experienced teachers (Halamish,
2018; Firth etal., 2021), but did not explicitly gauge the knowledge
of novice teachers (i.e., teachers who very recently graduated from
teacher training institutions; see participants). is is valuable
because novice teachers have not benetted from wide-ranging
practical classroom experience nor professional development
programs, both of which might be inuential to clarify how
human memory works in the classroom. Earlier research did not
nd signicant dierences between pre-serve and in-service
teachers (Halamish, 2018; Firth etal., 2021). is study adds to a
baseline measurement of novice teacher knowledge, which might
contribute to the understanding of the impact of teacher education
on imparting the essential knowledge and skills to start
the profession.
ird, authors of the previous studies indicated that the
sampling of teachers was probably not consistently representative
due to selection bias arising from convenience sampling
(Halamish, 2018; Firth etal., 2021). In Firth’s study Firth etal.
(2021), data were collected from students in one teacher training
college and in-service teachers were sampled using self-selection.
Halamish (2018), recruited respondents by self-selection through
a call in an online teacher discussion group. We used cluster
sampling, where the sample population is selected in groups
(clusters) based on location and timing.
Finally, it is also worth pointing out that earlier survey
research used closed-answer questioning (McCabe, 2011;
Morehead etal., 2016; Blasiman etal., 2017; Halamish, 2018; Firth
et al., 2021) and, thus, did not ask for spontaneous
recommendations on eective study strategies using open-ended
questions (with notable exceptions for McCabe (2018), who asked
academic support-centers to prioritize three learning strategies,
and Glogger-Frey et al. (2018), who limited their research to
comprehension-oriented learning strategies). McCabe (2018)
found limited evidence for the use of terms from cognitive
psychology (such as retrieval practice or metacognition) which
could indicate that the academic support-center heads were not
familiar with the evidence-base in the eld of eective learning
and studying. Open-ended questions examine the respondents’
organization of the knowledge schemes present. If teachers have
sucient in-depth knowledge of eective learning strategies, they
will beable to prioritize and coherently explain why one strategy
TABLE2 Metacognitive judgments of learning strategies using scenario-methodology.
McCabe
(2011)
Morehead
etal. (2016)
Morehead
etal. (2016)
McCabe
(2018)
Halamish
(2018)
Halamish
(2018)
Firth etal.
(2021)
Firth etal.
(2021)
Country respondents US US US US ISR ISR UK UK
respondents Under-graduate Undergraduate University level
Instructors
Academic
Study-advisors
Pre-service
teachers
In-service
teachers
Pre-service
teachers
In-service
teachers
Retrieval vs. restudying 30% 49% 62% 59% 49% 48% 4.82*4.7*
Interleaving vs. blocking 16% 13% 23% 12% 3.18*2.93*
Spacing vs. massing 10% 69% 74% 23% 28% 40% 5.27*4.45*
Dual coding vs. single coding 52%
Generating vs. non generating 80%
Percentages of respondents who preferred the study strategy with empirical support in the scenario. *Scores of respondents on a 7-point Likert scale (1, the evidence-based study strategy
is not eective- 7: the evidence-based study strategy is very eective).
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is preferred to another. It is therefore expected that novice teachers
can access their knowledge about eective learning-strategies
according to the knowledge structures they possess. One would
expect that the most eective learning strategies (such as spaced
practice and retrieval practice) would berecalled rst (Glogger-
Frey etal., 2018). is is especially important because an adequate
knowledge organization is predictive for the accessibility of that
information at a later stage (Prawat, 1989). Open questions should
also be positioned at the beginning of the survey because
measuring this coherent knowledge is more challenging when the
respondents have not already been shown a list of study strategies:
prior knowledge is activated by the list, which can lead to bias in
the assessment.
The current study
Taken together, the results of earlier research on teachers’
knowledge of study strategies indicates that teacher knowledge
might not besucient or even available to equip their students
with eective study strategies. It is hypothesized that, based on
earlier research, novice teachers might not be aware of the
eectiveness of study-strategies such as retrieval practice,
interleaved practice and spaced practice and that spontaneous
study advice might include less eective strategies. Given the
methodological concerns in the particular context of survey
research in the area of teachers’ propositional knowledge of
evidence-based study strategies, more research is needed. e
present study examines knowledge about the eectiveness of study
strategies within novice secondary school teachers and further
examines whether these teachers’ spontaneous study-strategy
advice is underpinned by research into human learning. is
study thereby gives insight into the baseline level of knowledge of
novice teachers and extends the methodology used in previous
research by adding learning scenarios and open-ended questions.
Materials and methods
Participants
Participants were 240 novice teachers who followed an
introductory course for novice teachers in secondary education,
organized in two provinces in Flanders, Belgium from 19 Flemish
teacher education institutions encompassing both bachelor and
master-level teacher education programs. Novice teachers were
dened, based on the theory of stages of expertise development,
as practicing teachers with comparable in-group and between-
group professional experience before they reached the stadium of
advanced beginners, which is reached at approximately 1.5 years
of experience, above which an increased teachers expertise level
can beexpected (see, e.g., Sabers etal., 1991).
e participants were informed about the research and that
the survey data would be used for research purposes. e
participants were then asked to consent to their responses being
used in this research. One participant did not consent and was
excluded from all analyses. Of the remaining 239, 59 participants
indicated they had more than 2 years of teaching experience and
were excluded from the analysis. is resulted in a nal sample of
180 respondents (Median age = 25; SD = 6.5; Mean 25.7; male = 62;
female = 118).
Procedure
e survey was administered to a large population at an
annual kick-o meeting for all novice teachers in two provinces
where 19 teacher education institutions were represented.
Permission from the Flemish pedagogical support network was
asked and obtained to conduct the research. ere was no
response bias, as most teachers attending the meeting were
expected to participate by their school leaders. e pen and pencil
survey, which took approximately 30 min to complete, was
administered live during the meeting. e survey was completed
by the participants anonymously.
e open-ended questions were placed at the start of the
survey in order to identify the study strategies that teachers would
‘spontaneously’ recommend (i.e., recall from their long-term
memory) before being primed by the learning scenarios or lists of
study strategies. Respondents then completed the second part (i.e.,
seven learning scenarios) and the nal part (i.e., study strategy
list) of the survey before providing demographic information (age,
gender, type of teacher education, teacher education institute,
years of teaching experience, subject-domain of teaching).
Respondents were restricted from viewing the remaining parts of
the survey and could not return to earlier answered questions to
limit prior questions inuencing subsequent answers.
Materials
e instrument used in this study consisted of three major
parts: open-ended questions on study strategy advice; learning
scenarios based on the learning scenarios as described by McCabe
(2011, 2018), Morehead etal. (2016), and Halamish (2018); and a
list of study strategies (based on McCabe, 2018) that respondents
had to rate for eectiveness.
Open-ended questions
First, participants were asked to write down three study
strategies they would recommend to their students to help them
pass a subsequent test. ey were instructed to think about
general, not subject-specic study strategies. So as not to inuence
respondents with the direction of their response, no answer
categories were provided. In the second open-ended question,
more context-specic cues were added by articulating that the test
would take place in 3 weeks and the student had already studied
the material once, prompting participants to deliberately consider
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spaced and/or retrieval practice as preferred study strategy. For the
second question, teachers were asked to recommend one single
study strategy to their students.
Following the open design of qualitative studies (Creswell
and Creswell, 2017), the data from the rst open question was
analyzed before moving to the second open question. First, the
rst author read every answer to gain a general overview. As a
second step, the rst author followed a process of mixed coding,
both theoretical (i.e., based on the 15-category coding scheme of
Dirkx etal., 2019, as described below) and in vivo (i.e., based on
the participants’ responses). ird, aer coding 20 questions, the
rst author cleaned the codes, and made a nal lists of codes
with relevant example statements. is process resulted in a
coding scheme consisting of 16 categories. Fourth, data from the
free-response question about the three most recommended
study strategies were then classied into 16 categories. e rst
10 codes in the coding frame by Dirkx etal. (2019) correspond
to the 10 learning strategies discussed by Dunlosky etal. (2013).
e following four codes correspond to strategies that were not
covered by the above-mentioned article but are oen reported as
being used as a study strategy by students. e categories added
by Dirkx and colleagues were copying (i.e., copying of course
materials; see also Blasiman etal., 2017), generating examples
(see Karpicke etal., 2009), cramming (as opposed to spaced
practice), and solving practice problems (i.e., solving problems
provided in students’ learning materials such as textbooks and
electronic learning environments). Another nal category was
added aer the second phase of coding, namely the code in
which recommendations are collected that form the ‘behind-the-
scenes of studying’ and that are not dominated by information-
processing, such as time-management, avoidance of behaviors
counterproductive for learning, concentration, study aids,
attitude, self-discipline, intrinsic or extrinsic motivation (Credé
and Kuncel, 2008). ese constructs are also important in
research on learning and metacognition but go beyond the scope
of this article, which focuses on cognitive learning strategies that
facilitate long-term learning.
Aer the coding process, the percentage of teachers with a
response in each category was calculated. When teachers specied
more study strategies than asked for, the additional strategies were
nevertheless included in the results. For instance, the
recommendation students should test themselves several times
before the test, consists of two study strategies (i.e., retrieval
practice and spaced practice). Two researchers assessed 25% of the
surveys whether the students’ responses were an example of one
of the strategies that would t into the coding frame of Dirkx etal.
(2019). e coders discussed their ndings, and intercoder
reliability was found to be82%, which was satisfactory. When
inconsistencies were uncovered, the researchers re-reviewed the
recommendations until they reached agreement. To establish
intercoder reliability, the researchers reanalyzed the same selection
of responses aer a period of 4 months and obtained a 96% level
of agreement with previous coding results. e rst author coded
the remaining surveys twice.
Learning scenarios
e second part of the survey consisted of seven hypothetical
study scenarios, each describing two students using two dierent
study-strategies, one empirically validated as being eective and
one not. Each scenario was based on a educationally relevant
study that investigated the eectiveness of study strategies (see
Table3). e participants were asked which strategy they would
recommend to their students to achieve long-term learning (i.e.,
better outcomes as measured by delayed-test scores) given a
particular situation.
For example, one scenario contrasting spaced practice and
massed practice presented the following situation: Two students
are preparing for a written test in 3 weeks. ey have to study one
chapter, comprising both theory and practice problems. Student
A spaces their practice and study over the 3 weeks. Student B
studies and practices intensively just prior to the test (i.e., the night
before). All told, they study an equal amount of time. Rate the
eectiveness of both students’ study strategies for long
term retention.
In each scenario, participants used a 5-point Likert-scale to
score each strategy of each student in the scenarios. e use of
separate scores per strategy made it possible to assess both the
absolute perceived eectiveness of each strategy and the dierence
in perceived eectiveness between the strategies. e authentic
context provided in the scenarios was designed to activate prior
knowledge about cognitive learning strategies. e retrieving and
interleaving scenarios were drawn from previous surveys
(McCabe, 2011, 2018; Halamish, 2018) with minor modications
in wording to make the learning scenarios more appropriate for
Flemish respondents. is can beseen as replicating and extending
the evaluation of learning scenarios presented in the
aforementioned studies. e remaining ve scenarios were novel
(spacing vs. massing; worked examples vs. problem solving; dual
coding vs. single coding; elaborative interrogation vs. rereading;
retrieving vs. mind mapping), with similar style and length, and
were reviewed by a team of international experts in cognitive
science and translatory research in order to validate their contents.
Aer an iterative process of three rounds of feedback, full
consensus was reached on the content and wording of the
new scenarios.
TABLE3 Seven learning scenarios.
Comparison of study strategies
(eective versus less eective)
Inspired by
1. Retrieving vs. restudying Roediger and Karpicke (2006)
Experiment 1.
2. Spacing vs. Massing Carpenter etal. (2009)
3. Interleaving vs. blocking Rohrer and Taylor (2007)
4. Worked examples vs. problem solving Sweller and Cooper (1985)
5. Dual coding vs. single coding Mayer and Gallini (1990)
6. Elaborative interrogation vs. rereading Smith etal. (2010)
7. Retrieving vs. mindmapping Karpicke and Blunt (2011)
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Study strategy list
In the nal part of the survey, participants were provided with
a list of 22 specic study strategies (obtained and adapted from
McCabe, 2018) and they were asked to rate on a 5-point Likert
scale, on average, how eective they thought each strategy was for
their students’ learning. e list was slightly rened by adding
some elaborated comments to the initial statements by McCabe.
For example, in the original study strategy list ‘Using pictures’ is
adapted to ‘Search pictures in order to clarify dicult concepts’, as
the rst statement did not describe how pictures should beused.
Statistical analyses
All survey data was analyzed via SPSS. e alpha level was set
to 0.05 for all statistical tests reported. For the analysis of the
learning scenarios, paired samples t-tests were used to compare
the mean ratings given to the empirically validated and
non-empirically validated study strategies for each scenario and
the resulting eect size are reported with Cohen’s d (De Winter
and Dodou, 2010). Positive eect sizes showed eects supporting
the evidence-based study strategy, while negative eect sizes
showed eects supporting the non-evidence-based strategy.
Hinge-points for small, medium or large eects were 0.2, 0.5, and
0.8, respectively. e data from the seven scenarios were combined
to form an overall accuracy score for each participant. For each
scenario question, each individual participant was coded as a 0 if
the non-empirically validated strategy was given a higher rating
than the empirically validated strategy and a 1 if the empirically
validated scenario was given a higher rating than the
non-empirically validated scenario. Accuracy scores ranged from
a minimum score of 0 (zero correct scenario judgments) to a
maximal score of 7 (all scenarios were judged correctly). e
overall accuracy comparing groups (e.g., masters vs. bachelors and
gender) across all scenarios were calculated via chi-square tests.
For the analysis of the study scenarios, descriptive statistics
were calculated. Paired t-tests were used to compare items that
rely on the same strategy (e.g., “test yourself with practice tests”
and “use ashcards to test yourself” both rely on the testing eect).
Results
To identify relevant clustering in the dataset, a number of
exploratory analyses were rst carried out. ere were no
signicant results from analyses comparing correct strategy
endorsements from the learning scenarios among self-reported
teacher education types (collapsing into three categories for
universities, universities of applied sciences or adult education
programs; (χ2 = 6.141; p > 0.05)), nor bachelor/master level
(χ2 = 4.872; p = 0.56) nor were strategy endorsements correlated
with teachers years of experience (i.e., 0 or 1 year teaching
experience; χ2 = 6.244; p = 0.396) nor were strategy endorsements
correlated with age (χ
2
= 154.732; p = 0.256) or gender (χ
2
= 6.620;
p = 0.357). It was not possible to compare the various teacher
education institutions and subject domains due to a limited
number of respondents per teacher education institution or
subject domain. As a result, associations with the demographic
factors mentioned earlier will not beexamined further.
Learning strategy recommendations
For a full overview of the top-three recommendations that
would begiven to students if they were studying for a test, see
Table4. Here, wepresent the most notable results: Summarization
was advised by 95% of the teachers. Less than half suggested
taking a practice test and only 19 (10%) explicitly mentioned that
repeating the subject matter in more than one session (spaced
practice) was advantageous. In contrast, 38 teachers (21%) said
that students should cram the material just before the test. Self-
explanation was a relatively oen suggested strategy (39%),
especially in the context of trying to explain the subject matter to
yourself or explaining it to someone else. Some eective strategies,
such as studying worked examples, interleaving, and using
multimodal representations were not or hardly mentioned.
Less eective study strategies such as copying notes, using
mnemonics or re-reading were given less attention. When
TABLE4 The frequency of recommended study strategies per open
question.
Open question 1
Study advice for a
test (3 answers
per participant
allowed)
Open question 2:
Study advice for a
test in 3 weeks (1
answer per
participant allowed)
Summarizing 172 (95%) 27 (15%)
Practice testing 81 (45%) 15 (8%)
Self-explaining 71 (39%) 7 (4%)
Highlighting 59 (33%) 2 (1%)
Cramming 38 (21%) 5 (3%)
Doing practice problems 34 (19%) 57 (32%)
Rereading 30 (17%) 10 (6%)
Elaborative interrogation 18 (10%) 0 (0%)
Spaced practice 19 (10%) 95 (53%)
Organizational &
practical advice
11 (6%) 26 (14%)
Copying 10 (6%) 0 (0%)
Keyword mnemonics 6 (3%) 0 (0%)
Imagery use –
multimodal coding
4 (2%) 0 (0%)
inking of real-life
examples
4 (2%) 1 (1%)
Interleaved practice 1 (1%) 0 (0%)
3.08 advices per teacher 1.34 advice per teacher
e rst gure in each cell indicates the absolute frequency of how many times a
particular strategy was recommended by a respondent. e second gure indicates the
percentage of respondents who recommended the study strategy.
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Frontiers in Education 10 frontiersin.org
highlighting was mentioned as a recommendation (33%), it was
in combination with another study strategy, such as rereading and
summarizing (e.g., “highlight the most important information
while rereading”; “make a summary using the highlighted text.”).
In the second open question, when it was explicitly stated that
the test would only take place in 3 weeks and students had already
studied once, spacing of study moments was explicitly mentioned
by 53% of the teachers. Taking a practice test, however, was only
suggested by 15 teachers (8%). Note that teachers were only
allowed to provide one study-advice on the second open-ended
question. Less eective study strategies such as copying notes,
highlighting and cramming were hardly mentioned. Similar to
McCabe (2018), there was limited evidence for the use of terms
originating from cognitive or educational psychology in both
open questions; that is, there was no mention of concepts such as
“retrieval,” “metacognition,” “testing eects,” etc.
Learning scenarios
Novice teachers in the current study made predictions about
learning outcomes for scenarios representing seven evidence-
based study strategies. In Table5 the descriptive and inferential
statistics per scenario are presented. In all cases, the responses
ranged from the minimum (1) to the maximum (5). For ve of the
seven scenarios, participants provided mean ratings indicating
their endorsement of the evidence-based strategy. Interleaved
practice and retrieval practice were not seen as being eective in
scenarios when compared with blocked practice and mind
mapping, respectively. Retrieval practice was judged as being
eective in comparison with restudying.
Study strategy list
Ratings of the strategy’s perceived eectiveness (rated on a
5-point scale with 5 indicating highest eectiveness) are found in
Table6. e study strategies that are described in the literature as
the least eective (i.e., copying notes, cramming, rereading …) are
also rated the lowest by novice teachers. Novice teachers consider
study strategies that are based on spaced practice, retrieval
practice, elaboration, multimodal representations, and worked
examples to be eective. Generative study strategies such as
summarizing and mind mapping are also evaluated as being
eective. Items 6 “test yourself with practice tests” and 12 “use
ashcards to test yourself” which both rely on the underlying
mechanism of retrieval practice were not perceived equally
eective (t(179) = 8,85, p < 0.01). A similar pattern I for items
related to spacing (i.e., items 5 and 11; t(179) = 3.10, p < 0.01) and
interleaving (i.e., items X and X; t(179) = 2.420, p < 0.05) and
rereading (i.e., items 5 and 11; t(179) = 3.10, p < 0.01). Items
concerning elaboration (i.e., items 3 and 7; t(179) = 0, p = 1.00) and
marking (i.e., items X and X; t(179) = 0.533, p = 0.594) were
perceived equally eective.
Discussion
is study explored novice teachers’ knowledge of eective
study strategies. e results of a three-part survey in which
participants were asked to provide study advice for their students
(open-ended questions) and assess the eectiveness of given study
strategies (closed questions) were presented. e results showed
that some misconceptions about eective study strategies are
widespread within novice teachers albeit with a dissimilar pattern
compared to previous empirical research. e results were
consistent across demographic factors. For instance, why teachers
who have recently completed a master’s program do not tend to
have a broader knowledge of eective study strategies. is can
be explained by the curriculum used: a master’s program in
teacher education in Flanders does not encapsulate a more
in-depth package of, for instance, educational psychology, but
mainly expands subject-specic learning content. Overall,
wefound two main results. First, there is considerable variability
in the perceived eectiveness of the most eective study strategies
when comparing answers from open questions (i.e., section 1 of
this survey) and closed questions (i.e., sections 2 and 3in this
survey; learning scenarios and study strategy list). Second,
TABLE5 Mean ratings (and standard deviations) for empirically validated learning strategies (EV) and non-empirically validated learning strategies
(non-EV) for the learning scenario questions.
Learning scenario EV Non-EV Comparison % EV
M1 SD M2 SD T Cohens d
Testing (EV) vs. restudying 4.07 0.68 2.27 0.83 20.60*2.37 90
Spacing (EV) vs. Massing 4.44 0.87 2.54 0.87 18.73*2.18 87
Interleaving (EV) vs. blocking 3.51 1.10 3.39 0.91 0.97 0.12 44
Worked examples (EV) vs. problem solving 4.03 0.98 2.98 1.07 8.36*1.02 65
Dual coding (EV) vs. single coding 4.67 0.56 2.46 0.89 26.99*2.97 96
Elaborative interrogation (EV) vs. rereading 4.50 0.64 2.45 0.77 27.54*2.89 96
Testing (EV) vs. mindmapping 3.43 0.93 4.31 0.70 9.81*1.07 13
M, Mean; SD, Standard Deviation; EV, empirically validated learning strategy (EV), Non-EV, non empirically validated learning strategy *p < 0.05. Responses range from 1 = very
ineective to 5 = very eective.
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teachers oen have incomplete knowledge about strategies that do
not tend to produce durable learning; they sometimes prefer
strategies in their study recommendations that have been shown
not to work. In what follows, we elaborate on these
two observations.
Perceived eectiveness of the most
eective strategies
is study contrasts with prior work in that respondents were
asked to answer open-ended questions on eective strategy-use
before assessing learning scenarios contrasting two commonly
used study strategies. ere was considerable variation between
strategy recommendations of highly eective study strategies in
the open-ended questions (requiring recall from long-term
memory) and the endorsement of these strategies in closed
questions (possibly requiring only recognition). Results show that
the respondents very oen- but not always- provided appropriate
judgments (i.e., preferring the strategy which is backed up by
evidence) when they had to weigh two study-strategies against
each other, but the same eective study-strategies were not
recommended spontaneously to their students in the open-ended
questions. Strong endorsements in learning scenarios does not
automatically turn into obvious recommendations. Spaced
practice, for instance, was mentioned as a strategy by less than half
of the teachers aer it was prompted in the second open-ended
question (i.e., that students had already studied for the test once
and that the test would take place within 3 weeks), while the
majority of the respondents identied spaced practice as a more
eective strategy than massed practice in a learning scenario. A
similar tendency was observed in the third section of the survey,
where items referring to the spacing eect (i.e., “study the same
materials several times spaced in time”) were considered highly
eective. Likewise, retrieval practice was assessed as eective when
contrasted with a rather passive study strategy (i.e., rereading) but
was suggested as a strategy by less than half of the teachers in the
rst open-ended question. Interleaved practice, elaboration, using
worked examples, and using multi-modal representations were also
marginally recommended in the open-ended questions. However,
when they were presented in opposition to a less eective study
strategy in the learning scenarios, all except for interleaved
practice were appropriately and almost unanimously identied
as eective.
If novice teachers were presented forced-choice questions, in
many cases they will opt for the right answer, which paints an
relatively optimistic picture. at is, they remember or are capable
of discerning in a paired comparison what works (i.e., they might
possess the tacit knowledge) but cannot freely recall it when only
prompted to do so (i.e., they might not possess deep conceptual
propositional knowledge). is limits the chance that those not
freely recalling the strategy will use the strategy in their teaching
TABLE6 Perceived eectiveness of learning strategies as reported by novice teachers.
Mean Std. Deviation
1. Use concrete examples to explain dicult concepts. 4.39 0.610
2. Search for images to clarify dicult concepts. 4.35 0.672
3. Study by explaining the subject matter to others. 4.32 0.821
4. Make a summary, mind map or outline of the subject matter. 4.29 0.757
5. Study the same material several times spaced in time. 4.28 0.748
6. Test yourself through practice tests. 4.28 0.652
7. Ask yourself who-what-why-how.. questions. 4.18 0.654
8. Find similarities or dierences in the subject matter. 4.18 0.719
9. Use mind maps, summaries or diagrams. 4.14 0.797
10. Practise by answering questions about the subject matter. 4.12 0.617
11. Try to study the same subject repeatedly spaced in time. 4.11 0.781
12. Use ash cards to test yourself. 3.98 0.756
13. Develop mnemonic devices (such as rhymes) while studying 3.97 0.869
14. Study by imagining the material as youstudy 3.87 0.756
15. Use examples that explain how to solve an exercise 3.69 0.749
16. Mix up exercises of dierent types 3.67 0.995
17. Vary the order in which youpractice within one study session 3.49 0.952
18. Underline or highlight the most important elements of the course material 3.42 0.978
19. Revisit the parts youhave underlined or marked 3.39 0.928
20. Read the course material out loud 3.10 1.023
21. Read the course material several times 2.73 0.960
22. Study the subject matter all at once for a longer period of time 2.09 0.777
23. Copy the course material verbatim. 1.72 0.825
Responses range from 1 = very ineective to 5 = very eective.
Surma et al. 10.3389/feduc.2022.996039
Frontiers in Education 12 frontiersin.org
repertoire is probably negligible. Possessing certain propositional
knowledge is known to precede competently handling the
pedagogical skills related to the knowledge areas in real classroom
situations (Munby etal., 2001). In optimal circumstances, they
should also spontaneously recommend the strategy to their
students, which is not entirely the case with strategies such as
spaced practice, retrieval practice, interleaved practice, using
multimodal representations, and using worked examples. is
also conrms the claim for the introduction of open-ended
questions as a methodological improvement for measuring
learners’ knowledge about study strategies: performing well on the
learning scenarios does not necessarily imply that teachers
spontaneously transfer their knowledge to more ecologically
valid settings.
Another noteworthy observation was that even within one
study single study strategy such as retrieval practice, there were
considerable dierences in perceived eectiveness. For instance,
concept mapping, which is essentially a generative strategy, is
considered to bemore eective than retrieval practice in a learning
scenario, while the memory benets of retrieval practice (i.e.,
engaging immediately in trying to remember aer a rst reading)
are more protable over time than merely generating concept
maps from open books (Karpicke and Blunt, 2011; Camerer etal.,
2018). Nevertheless, when contrasted with rereading, retrieval
practice yielded superior results. In the rst open-ended question,
retrieval practice was advised by less than half of the teachers, but
wewere unable to determine from the responses whether retrieval
practice was conceived as merely self-testing (a strategy for self-
evaluation at the very end of the study process) or as a study
strategy to strengthen one’s memory. is suggests that the
respondents might not befully aware of the cognitive principles
supporting strategies such as retrieval practice (Rivers, 2021). is
limits novice teachers’ to generalize the strategies to novel
situations and instructional methods (Willingham, 2017).
Whether teachers’ and learners are aware of the full advantages of
retrieval practice and for explanations why retrieval practice is not
considered a study strategy but merely an self-evaluation strategy,
should betackled by future research (see, e.g., Rivers, 2021).
When novice teachers had to assess the eectiveness from a list
of 36 study strategies, on the whole, the most eective strategies
were more oen rated higher than those with a weaker evidence-
base. A notable exception – again- is interleaving, where both items
were rated low in eectivity (“Mix up exercises of dierent types”;
Alternate the order in which you practice within one study
session”). e lower accuracy of the strategy endorsements related
to mixing up study sequence (i.e., interleaving) is consistent with
earlier research (McCabe, 2018; Firth et al., 2021). Some well
recognized study strategies such as interleaving are counterintuitive
to people as they pose diculties during the initial learning process
(Bjork, 1994; Clark and Bjork, 2014). Metacognitive insight into
desirable diculties may bedierent from that of other eective
strategies and require explicit instruction and practice as some of
the advantages do not appear to beobvious for learners and teachers
at rst sight (Soderstrom and Bjork, 2015). Conditions of retrieval
practice and interleaved practice that oen facilitate long-term
retention may appear unhelpful in the short term as they appear to
impede current performance.
One might suspect that when the information on eective
strategies is presented clearly and in contrast to less eective
strategies, the former will appear obvious in hindsight. However,
this does not explain why Flemish novice teachers assess the study
scenarios using desirable diculties (i.e., spaced practice, retrieval
practice, interleaved practice) dierently than other populations.
Compared to earlier studies with similar scenarios, Flemish novice
teachers seem to benotably more accurate in identifying desirable
diculties than their mostly Anglo-Saxon counterparts. Table2
shows three study scenarios which were replicated for seven
dierent population groups in dierent countries. e explanation
for these dierences may begrounded in the fact that novice
teachers recently graduated from teacher education and topics
regarding memory and cognition are still vivid in their minds. If,
however, that was the case, more-eective strategies should have
been spontaneously mentioned and more subject-specic terms
from cognitive psychology should have been generated in the
open questions. is is also at odds with the ndings of Surma
etal. (2018) on the contents of teacher education textbooks and
their accompanying syllabi. is research therefore also identies
possible geographical and curricular issues in surveys on
respondents’ knowledge: generalization about teachers’ mental
models of learning over countries and related teacher education
curricula do not seem to beself-evident.
Perceived eectiveness of the least
eective strategies
e respondents tended to suggest strategies that have been
shown not to work while avoiding strategies that do work. For
example, the vast majority of novice teachers recommend
summarizing as a principal study strategy while this strategy is
described by Dunlosky etal. (2013) as a low-utility strategy. In the
list of study strategies, however, while summarizing was also seen
as highly eective, highlighting and cramming were listed among
the least eective strategies. Copying notes was not oen
spontaneously mentioned in the open questions, nor was it
strongly appreciated in the study strategies list.
e reasons for this dispersed perception of eectiveness for
summarizing versus copying/ highlighting/cramming may have
several explanations. First, Pressley etal. (1989, p.5) stated that
“summarizing is not one strategy but a family of strategies.” When
a participant notes that summarizing is a robust strategy, it is not
necessarily known what the participant considers to
be summarizing (i.e., declarative knowledge: for one student,
summarizing is perceived as schematizing single words while for
another it might bemaking a verbatim transcription of their
textbook) and the way in which summarizing proceeds (i.e.,
procedural knowledge: do Isummarize with the textbook open or
closed? Do Isummarize aer Ihave already studied the material
Surma et al. 10.3389/feduc.2022.996039
Frontiers in Education 13 frontiersin.org
thoroughly? Do Iuse a summary to review aerwards or to test
myself? Do Isummarize aloud or in writing?). For copying and
highlighting, the conceptual and procedural interpretation
appears to bemore straightforward. In reality, the manifestations
of summarizing as a study strategy are probably more diverse and
prone to individual dierences than the narrow denition that
researchers assign to the concept (Miyatsu etal., 2018). Despite
the fact that teachers do prefer summarizing over retrieval
practice, this choice is unlikely a symptom of their knowledge of
eective studying because learners appear, based on earlier
research, not always fully aware of the boundary conditions of
certain study strategies (Bjork etal., 2013).
A second explanation as to why the novice teachers
spontaneously suggest suboptimal strategies can befound in a
theory-practice gap. Study strategies are oen studied in cognitive
science literature as “singletons,” that is as individual and generic
phenomena, whereas in ecologically valid situations, a given study
strategy is oen sequentially linked within a series of other study
strategies and linked with specic type of learning content. For
instance, a student who rst reads the learning material, rereads
the material while highlighting relevant information, summarizes,
and nishes by testing themselves, uses a number of strategies
labeled as less eective (i.e., rereading, highlighting, summarizing).
As noted earlier by Miyatsu etal. (2018), ineective strategies,
under certain conditions, can bepotent. For example, a strategy
labeled as ineective such as massed or blocked practice will
sometimes result in a good performance on an immediate test
even though it does little for long-term retention and distracts the
learner by providing suboptimal judgments of future learning. So
far, research on learning strategies has been fairly myopic, focusing
on study strategies in isolation but not oen tracing optimal
combinations or study arrangements in holistic ecologically valid
settings (Dirkx etal., 2019). Follow-up research should look at
how learners perceive eective study strategies from a semantic
point of view, which strategies they choose depending on the type
of learning content or subject area, how they combine study
strategies chronologically, and why they do so. A more qualitative
research design may beappropriate for this purpose.
Limitations
One must becareful when interpreting the results of this study,
because multiple factors could have contributed to the discrepancy
between the results of the open-ended and closed questions, and the
lack of consistency regarding the perceived eectiveness of the study
strategies. e limitations with respect to semantics (i.e., do all
respondents interpret the term summarizing identically?), the focus
on individual strategies (i.e., students are likely to use more than one
study strategy during the study process) and the geographical
dierences (i.e., Flemish novice teachers score better on scenarios
that probe desirable diculties than respondents from other
countries) were outlined earlier. e validity of a measurement
instrument is not established in one or two (sets of) studies. For
example, in follow-up studies learning scenarios can beadded that
contrast popular and frequently used strategies such as summarizing
with other generative strategies such as mind mapping to gain a
more ne grained image of novice teachers’ knowledge of study
strategies. A more qualitative approach can beused to determine
how teachers interpret certain (combinations of) study strategies.
Finally, and to state the obvious: Responses are self-reported and
may not reect novice teachers true educational advice given in
real classrooms.
Conclusion
ere remains a noticeable gap between the typical way
learners perceive study strategies and the empirical evidence
regarding their eect on learning, and novice teachers seem to
beno dierent than their peers elsewhere. e results from this
study add to the growing literature that not only students,
experienced teachers, university instructors, and pre-service
teachers can besuboptimal in their judgments (Morehead etal.,
2016; Halamish, 2018; McCabe, 2018; Firth etal., 2021). Overall,
our data suggests that Flemish novice teachers are consistent in
evaluating given study strategies (specically: spaced practice,
multimodal representations, and elaboration), but are less able to
spontaneously formulate study-advices about the same study
strategies. Other aspects of the results are more complex. Novice
teachers appeared to beless consistent in their evaluation of study
strategies that rely on the desirable diculties framework. Indeed,
strategies with the strongest evidence-base, such as spaced practice
and retrieval practice, were not oen spontaneously recommended
in open-ended questions. Since there are large discrepancies
between spontaneously recommended study strategies and the
eectiveness scores of the same strategies in closed questions, it is
possible that that novice teachers do not yet exhibit a coherent
image of the learners cognitive architecture. Student teachers
knowledge of learning strategies has been previously described as
‘knowledge in pieces’ (Glogger-Frey etal., 2018, p.228), and the
same conundrums are found in novice-teachers study strategy
knowledge. Our indications of the lack of sophistication in novice
teachers’ knowledge highlights the need for teaching them about
and training them in the use of evidence-based strategies
(McCabe, 2018).
Teacher learning and their classroom skills should beseen as
and a dynamic process and a continuum rather than an judgment
of teachers’ knowledge at a xed time (Blömeke etal., 2015). From
the perspective of translational research— the amalgam of
processes and activities associated with the use of ndings from
empirical research to incorporate best-evidence guidelines into
everyday practice (see, e.g., Gorard, 2020) – the presented study
oers an opportunity to examine curricula in both teacher
education and continuing professional development whether they
disseminate the most consistent research results regarding
learning processes. Where best-evidence is used as part of initial
teacher education and continuing professional development
Surma et al. 10.3389/feduc.2022.996039
Frontiers in Education 14 frontiersin.org
curricula, teacher performance is found to besuperior (Brown
and Zhang, 2016). Explicit strategy instruction in teacher
education and continuous professional development may thus
provide a tangible solution for this ‘knowledge in pieces’ in novice
teachers. Explicit instruction about the concepts, use and
advantages of employing empirically supported learning strategies
thus might promote teachers’ understanding of the mental model
of the learner (Willingham, 2017). As argued by Lawson etal.
(2019), learning about learning and cognition should perhaps
beseen as a separate knowledge domain so that pre-service and
in-service teachers can transfer that propositional knowledge both
implicitly and explicitly to their students. It is important that all
teachers have deep conceptual knowledge of study strategies as
teachers might beconsidered as ‘memory workers’ who have the
responsibility of teaching their students how learning happens and
how to use eective study strategies to create lasting learning.
Data availability statement
e datasets presented in this article are not readily available
because in the informed consent, it was stated that the dataset
would only beused for this particular research. Requests to access
the datasets should bedirected to tim.surma@thomasmore.be.
Ethics statement
e studies involving human participants were reviewed and
approved by Open University of the Netherlands. e patients/
participants provided their written informed consent to participate
in this study.
Author contributions
TS, GC, PK, and RG contributed to the conception and the
design of the study. TS analyzed the data and wrote, revised, and
reviewed sections of the manuscript. GC, RG, and PK provided
feedback during the writing process. All authors contributed to
the article and approved the submitted version.
Acknowledgments
We would like to thank Peter Verkoeijen, Pedro Debruyckere,
Dominique Sluijsmans, Kristel Vanhoyweghen, Tine Hoof, Eva
Maesen, and Laurie Delnoij for their feedback during various
stages of this study.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their aliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
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... Studies have shown that university instructors frequently promote both lower and higher utility learning strategies and have a moderate understanding of evidence-informed learning strategies (McCabe, 2018;Piza, 2018;Morehead et al., 2016). Previous published research on instructors' recommendations and understanding of learning strategies is limited to surveys of higher education instructors, and there remains a paucity of research evaluating the strategies teachers most commonly promote in schools (see Surma et al. (2022) for an exception; McCabe, 2018;Piza, 2018;Morehead et al., 2016). ...
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... Recent research has delved into various facets of novice teachers' professional development and experiences. For instance, Surma et al. (2022) investigated novice secondary school teachers' knowledge of effective study strategies and found that although they could identify Abu-Alhija & Fresko, 2010). The Israeli Ministry of Education has established a comprehensive support system that includes mentoring by seasoned teachers and participation in internship workshops. ...
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... Recent research has delved into various facets of novice teachers' professional development and experiences. For instance, Surma et al. (2022) investigated novice secondary school teachers' knowledge of effective study strategies and found that although they could identify Abu-Alhija & Fresko, 2010). The Israeli Ministry of Education has established a comprehensive support system that includes mentoring by seasoned teachers and participation in internship workshops. ...
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Recent research shows the importance to teach students the self-regulated use of effective learning strategies at university. However, the effects of such training programs on students’ metacognitive knowledge, use of learning strategies, and academic performance in the longer term are unknown. In the present study, all first-year pharmacology students from one university attended a learning strategy training program, i.e., the ‘Study Smart program’, in their first weeks. The 20% (n = 25) lowest scoring students on the first midterm received further support regarding their learning strategies. Results showed that all students gained accurate metacognitive knowledge about (in)effective learning strategies in the short- and long-term and reported to use less highlighting, less rereading, but more interleaving, elaboration, and distributed practice after the training program. Academic performance was compared to the prior cohort, which had not received the Study Smart program. While in the previous cohort, students in the top, middle, and bottom rank of midterm 1 stayed in these ranks and still differed significantly in the final exam, students in the Study Smart cohort that received the training program improved throughout the year and differences between ranks were significantly reduced. A learning strategy training program including a remediation track for lower performing students can thus support students to study more effectively and enhance equal chances for all students at university.
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