Journal of Curriculum Studies
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tcus20
Lower secondary intended curricula of science
subjects and mathematics: a comparison of the
Czech Republic, Estonia, Poland and Slovenia
Petr Kácovský, Tereza Jedličková, Radim Kuba, Marie Snětinová, Petra
Surynková, Matěj Vrhel & Eva Stratilová Urválková
To cite this article: Petr Kácovský, Tereza Jedličková, Radim Kuba, Marie Snětinová, Petra
Surynková, Matěj Vrhel & Eva Stratilová Urválková (2021): Lower secondary intended curricula
of science subjects and mathematics: a comparison of the Czech Republic, Estonia, Poland and
Slovenia, Journal of Curriculum Studies, DOI: 10.1080/00220272.2021.1978557
To link to this article: https://doi.org/10.1080/00220272.2021.1978557
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JOURNAL OF CURRICULUM STUDIES
https://doi.org/10.1080/00220272.2021.1978557
Lower secondary intended curricula of science subjects and
mathematics: a comparison of the Czech Republic, Estonia,
Poland and Slovenia
Petr Kácovský a, Tereza Jedličková b, Radim Kuba c, Marie Snětinová
Petra Surynková d, Matěj Vrhel e and Eva Stratilová Urválková f
a
,
a
Department of Physics Education, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic;
Institute of Geology and Paleontology, Faculty of Science, Charles University, Prague, Czech Republic; cDepartment
of Teaching and Didactics of Biology, Faculty of Science, Charles University, Prague, Czech Republic; dDepartment
of Mathematics Education, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic;
e
Department of Social Geography and Regional Development, Faculty of Science, Charles University, Prague, Czech
Republic; fDepartment of Teaching and Didactics of Chemistry, Faculty of Science, Charles University, Prague, Czech
Republic
b
ABSTRACT
KEYWORDS
Comparative studies on science curricula provide insights into educational standards worldwide. Accordingly, in this study, we analysed the
intended curricula of mathematics and science subjects of the Czech
Republic, Estonia, Poland and Slovenia by comparing their lower secondary (ISCED 2) National Curriculum Documents on mathematics, physics,
chemistry, biology, geography and geology from the perspective of learning outcomes. By document analysis, we extracted obligatory learning
outcomes from the national curricula, assessing their level of detail and
structure. A team of seven coders also measured cognitive demands of
the learning outcomes using the revised Bloom’s taxonomy. Our results
showed considerable differences in the number of learning outcomes
across countries and in the structure of these outcomes across subjects,
even within national documents. Cognitive demands determined by
learning outcomes were similar across the countries, but metacognitive
knowledge and cognitive processes of higher level (Evaluate and Create)
were mostly overlooked. We also found a lack of learning outcomes
explicitly requiring the use of ICT, experimental or field work or data
analysis. Although these requirements are usually formulated in general
sections of curriculum documents, we recommend explicitly incorporating them into these documents as individual learning outcomes.
Cognitive objectives;
comparative analysis;
curriculum research;
outcomes of education;
secondary education
Introduction
Enhancing educational goals is a key priority of educational policies in every country. For this
purpose, each Ministry of Education sets national curricula or framework educational programmes.
These documents should reflect the shift in the country’s current priorities and educational
demands, focusing on curriculum changes and revisions whilst considering their far-reaching social,
political, economic and mostly educational consequences. In the Czech Republic, we are currently
revising our national curriculum, finally suggesting a major modification after years of minor changes
because the challenges of our modern globalized society have major implications in the design of
CONTACT Eva Stratilová Urválková
urvalkov@natur.cuni.cz
Department of Teaching and Didactics of Chemistry, Faculty
of Science, Charles University, Hlavova 8, Prague 12843, Czech Republic
© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.
0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2
P. KÁCOVSKÝ ET AL.
national curricula. As such, these curricula should be extensively revised to provide students with
ample opportunities for practical activities, thereby developing their ICT skills and technology
proficiency whilst promoting their thinking, organizing and planning (metacognition) abilities,
among others.
When preparing curriculum reforms, national authorities find inspiration in other countries with
success in international testing (e.g. Programme for International Student Assessment (PISA) and
Trends in International Mathematics and Science Study (TIMSS)) or struggling with similar problems. Therefore, we compared our current science subjects curriculum documents (traditionally,
biology, chemistry, physics, geography and geology; and in our conception, mathematics as well)
to those of several other countries. These countries were chosen according to the following
criteria: (1) showing significantly better results in international surveys, such as PISA, and (2)
having a similar cultural and historical background. Among all possible countries from the former
Eastern Bloc, Poland, Slovenia and Estonia, meet these criteria, outperforming the Czech Republic
in previous PISA testing (OECD, 2014, 2016a, 2019). Members of our team have already participated in five separate studies comparing subject-specific content of science and mathematics
education in these four countries. While these partial studies—published in a special issue of the
Scientia in Educatione journal (Janoušková et al., 2019)—addressed the comparison of specific
topics taught in particular countries, in this paper we will focus on prescribed learning outcomes,
their nature, structure and intellectual demands.
Research context
All four post-communist countries share a similar history, that is, they were under communist
governance and a planned economy after World War II, but the Union of Soviet Socialist Republics
(USSR) influenced those countries to varying degrees. Estonia was a member state of the USSR
until 1991, while Poland and the Czech Republic (Czechoslovakia until 1993) maintained their
sovereignty formally, albeit within the Eastern Bloc, both until 1989, and subjected to USSR rule in
practice. In turn, Slovenia was a founding member of the Socialist Federal Republic of Yugoslavia
and was not subjected to the direct influence of the USSR, eventually seceding from Yugoslavia in
1991.
Since their transfer to democratic regimes in the 1990s, all four countries continue to improve
their living standards, which are approaching the average standards of western countries. All of them
have also joined the European Union in 2004, thereby prompting reforms towards implementing
common EU-legislation.
Changes in the education systems of the Czech Republic, Estonia, Poland and Slovenia ran parallel
to their historical events. Before the collapse of the communistic regimes in the 1990s, education in
these countries focused on factual cognition and transmissive teaching methods, failing to address
environmental issues or doing so merely by chance and always under a political ideology (Horváth &
Próbald, 2003).
The political changes that occurred in the early 1990s were the same starting point for the
education reforms in all four countries. The Czech Republic and Poland tried to prepare new
curriculum documents as soon as possible. However, as a result, the content remained almost
unchanged, albeit freed from all ideological issues. Conversely, Estonia began to prepare a completely new curriculum, featuring school curriculum autonomy and defining learning outcomes
directly inspired by the Finnish National Curriculum. The new curriculum was planned as an effective
tool for building an open, democratic, information-based society, geared towards Europe, and for
promoting a market economy. Furthermore, this new curriculum included problem solving, critical
thinking and personal responsibility within its key objectives to simultaneously motivate pupils and
foster their abilities to reflect on and manage their own learning (OECD, 2016b). Within former
Yugoslavia, Slovenia had some autonomy in their own education system planning; however, as in
other communist countries, its curriculum was ideologically driven. For this reason, in the 1990s, the
JOURNAL OF CURRICULUM STUDIES
3
democratic and pro-European independent Slovenian Republic adopted a new education policy,
including a new curriculum. After moderate revisions in 2007, this curriculum was reformed to its
current form from 2008 to 2011 (Vlček et al., 2016).
The governments of these countries have all the interest in succeeding when implementing such
reforms. For this reason, they participate in international surveys and assessments. As mentioned
above, the Czech Republic differs non-significantly from the OECD average while Poland, Slovenia and
Estonia are the only countries from the former Eastern Bloc that regularly rank significantly above the
OECD average in science and mathematics, in PISA testing (OECD, 2014, 2016a, 2019). Therefore,
policy learning may enable us to design strategies towards improving Czech curriculum documents.
Comparing the curricula: theoretical framework
The diverse success rates of pupils from the selected countries measured in international surveys has
led us to reflect on the similarities and differences between the curricula of lower secondary
education (ISCED 2) in these countries.
According to Bray and Thomas (1995), comparative studies on education can be classified using
three-dimensional system. The first dimension is geographical/ locational (countries, districts,
schools and classrooms), the second dimension is based on non-locational demographic variables
(religion, age and gender), and the third dimension encompasses other aspects of education and
society such as curriculum, teaching methods and educational finance, among others. Furthermore,
we only focus on one of the key components in the analysis of educational standards of the selected
countries, that is, their curriculum as defined by their national curriculum documents.
Basically, a curriculum can be regarded as a plan for learning, describing what, why and how pupils
should learn (Taba, 1962). The curriculum model is based on three aspects: the intended curriculum,
the implemented curriculum, and the achieved curriculum (Kridel, 2010). The intended curriculum
defines the expectations and goals in terms of knowledge, skills, values and attitudes, which should be
achieved and developed by pupils during their formal education, also specifying how the outcomes of
the teaching and learning process should be assessed. The implemented curriculum represents
teaching and learning activities used in school practice, and the achieved curriculum indicates the
knowledge and understanding that pupils have achieved during their education. As stated above, in
our research, we only address the intended curriculum, more specifically, the official national curriculum documents and frameworks. These documents should serve as a fundamental vision, a widely
accepted direction for all stakeholders in the education process—including government officials,
textbook authors, teachers, school principals and teacher educators.
Different perspectives on how to best compare these documents stand out in the field-specific
literature. For example, the comparison of curriculum breadth and depth is widely accepted
(Murdock, 2008). Yet, while breadth is usually understood in terms of the number of topics
prescribed, depth is not uniformly defined (Murdock, 2008); similarly, there is no consensus on
whether breadth could be achieved at the expense of only depth and vice versa. Alternatively,
Thijs and van den Akker (2009) propose four parameters of curriculum quality, addressing curriculum relevance, consistency, practicality and effectiveness. Notwithstanding the rationale and
merits of such parameters, in this study, we follow the approach previously applied by other
researcher groups (e.g. Elmas et al., 2020; Lee et al., 2015) comparing intellectual demands of
intended curricula.
Intellectual demands placed on pupils by national curriculum documents directly shape the
implemented curriculum, e.g. by influencing teachers’ decisions on the cognitive processes that should
be supported through instruction and on the methods chosen to do so. To evaluate the intellectual
demands of national curriculum documents, we focused on what these documents prescribe for pupils
to manage at the end of the instruction—depending on the country, these requirements are known as
educational goals, outcomes or objectives. In this paper, we uniformly use the umbrella term
obligatory learning outcomes to express all three concepts, in line with, e.g. Harden (2002).
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P. KÁCOVSKÝ ET AL.
To assess these learning outcomes, we used an analytical framework of cognitive, affective, and
psychomotor knowledge domains (e.g. Wei & Ou, 2019). The cognitive educational objectives1 target
the recall or recognition of knowledge and their taxonomy was originally addressed by Bloom et al.
(1956), who outlined six major categories of cognitive processes (Knowledge, Comprehension,
Application, Analysis, Synthesis, and Evaluation). Educational objectives in the affective domain
refer to interests, desires, feelings, emotions, values, enthusiasm, or attitudes. Lastly, the psychomotor domain is composed of objectives aimed at developing motor and physical abilities and skills. All
three domains are clearly related to each other. As such, these relationships were studied, whilst
revising and modifying the taxonomies as well.
In this study, we only address the cognitive domain, which is the only relevant domain when
assessing the intellectual demands of obligatory learning outcomes.
Revised Bloom’s taxonomy
The frequent use of Bloom’s taxonomy has uncovered its limitations. This taxonomy assumes that
mastering the simpler categories is a prerequisite for mastering the corresponding ‘higher’ categories (Bloom et al., 1956). However, Ormell (1974) highlighted that the order of categories can be
inverted—e.g. specific demands for Knowledge can be more complex than some demands for
Analysis. Furthermore, according to Kreitzer and Madaus (1994), Evaluation is a part of Synthesis
and not the other way around. Lastly, the unidimensionality of the taxonomy has been criticized
because educational objectives typically consist of two components—content (usually noun) and
action (usually verb), thus suggesting two dimensions (Krathwohl, 2002).
These criticisms have led researchers to suggest taxonomies able to suppress unwanted effects.
To cover both dimensions mentioned above, models have been developed based on the categorization of mental processes and on types of knowledge. For example, the Depth of knowledge (DOK)
model developed by Webb (1997) has four major levels (Recall & Reproduction, Basic Application of
Skills/Concepts, Strategic Thinking, and Extended Thinking) and focuses on the complexity of the
content and on the cognitive process simultaneously demanded by the educational objective; DOK
was used, e.g. in PISA 2018. Other taxonomies (New Taxonomy and SOLO Taxonomy) directly use
multiple dimensions (Lee et al., 2017).
Arguably, the most commonly used adaptation of the original Bloom’s model is the revised
Bloom’s taxonomy (RBT) introduced by Anderson et al. (2001). RBT preserves the system with six
categories of cognitive processes, which are renamed in verb form, and the two highest levels are
reversely-ordered—the RBT cognitive processes are Remember, Understand, Apply, Analyse,
Evaluate and Create. In addition, a second dimension is included to differentiate the types of
knowledge as Factual, Conceptual, Procedural and Metacognitive. The authors (Anderson et al.,
2001) provided examples to make it easier to use the taxonomy. Table 1 presents general definitions
and examples of typical verbs linked to cognitive processes. In turn, Table 2 outlines the major types
of knowledge, as well as subtypes and their examples.
Despite these guidelines, distinguishing the Metacognitive type of knowledge (not only from
other types of knowledge but also from the affective domain) is a particularly complex task, which
can be nevertheless facilitated by supplementing the original description of Metacognitive knowledge with other sources and by specifying typical characteristics of metacognition (Anderson et al.,
2001; Cambridge Assessment International Education, 2019; Flavell, 1979; Lokajíčková, 2014).
According to these authors, metacognitive learning outcomes primarily encompass the following
characteristics: interdisciplinary overlap (except when the other discipline is used as a ‘tool’, such as
mathematics in geography), tasks requiring or employing one’s own experience and knowledge of
different situations and cultural norms on the use of different strategies or on learning how to use
different types of information, value, interest beliefs or judgements.
JOURNAL OF CURRICULUM STUDIES
5
Table 1. Cognitive processes of revised Bloom’s taxonomy (based on Anderson et al., 2001).
Cognitive
process
Remember
Definition
The student can recall or remember
the information.
Understand The student can explain ideas or
concepts.
Apply
The student can use the information
in a new way.
Analyse
The student can distinguish between
the different parts.
Evaluate
The student can justify a stand or
decision.
Create
The student can create new product
or point of view.
Examples of typical active verbs involved
Define, duplicate, list, memorize, recall, repeat, reproduce, state
Classify, describe, discuss, explain, identify, locate, paraphrase, recognize,
report, select, translate
Choose, demonstrate, dramatize, employ, illustrate, interpret, operate,
schedule, sketch, solve, use, write
Appraise, compare, contrast, criticize, differentiate, discriminate,
distinguish, examine, experiment, question, test
Appraise, argue, defend,evaluate, judge, select, support, value
Assemble, construct, create, design, develop, formulate, write
Table 2. The major types and subtypes of the knowledge dimension (based on Anderson et al., 2001).
Major types of knowledge
A. Factual: The basic elements students must
know to be acquainted with a discipline or
solve problems in it
B. Conceptual: The interrelationships among
the basic elements within a larger structure
that enable them to function together
Subtypes
AA. Knowledge of terminology
AB. Knowledge of specific details and
elements
BA. Knowledge of classifications and
categories
BB. Knowledge of principles
andgeneralizations
BC. Knowledge of theories,models,
and structures
C. Procedural: How to do something, methods CA. Knowledge of subject-specific
of inquiry, and criteria for using skills,
skills and algorithms
algorithms, techniques, and methods
CB. Knowledge of subject-specific
techniques and methods
CC. Knowledge of criteria for
determining when to use
appropriate procedures
DA. Strategic knowledge
D. Meta-cognitive:
Knowledge of cognition in general as well as
awareness and knowledge of one’s own
cognition
DB. Knowledge about cognitive
tasks, including appropriate
contextual and conditional
knowledge
DC. Self-knowledge
Examples
Unit of rate, unit of force
Some common danger warning
symbols
The nature of force
Energy conservation law
Structure of atom, theory of evolution
Friction calculation
Scientific methods
The criteria used to determine when
to apply Newton’s second law
Knowledge of outlining as a means of
capturing the structure of a unit of
subject matter in a textbook
Knowledge of the cognitive demands
of different tasks
Awareness of one’s own knowledge
level
Notwithstanding its quality, RBT is not a flawless tool. Unsurprisingly, dissenting voices underscore its limitations (Amer, 2006; Tutkun et al., 2012), and revisions of the revised taxonomy have
already been published (Darwazeh & Branch, 2015). Yet, RBT has become a widely reputable tool,
which has proved useful in various research procedures. When analysing official curriculum documents, RBT has been repeatedly used by researchers from various countries, including in Edwards
(2010), Elmas et al. (2020), Lee et al. (2017), Wei and Ou (2019), Wei (2020), and Yaz and Kurnaz (2020),
thus demonstrating its value in different cultural contexts and applications.
Comparative studies in science subjects and mathematics intended curricula
Various comparative cross-national studies of intended curricula have been conducted in different
regions and over various time periods. For instance, Kamens and Benavot (1991) discussed the origin
and spread of mathematics and science education in national elementary and secondary school
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P. KÁCOVSKÝ ET AL.
curricula of world regions. Pawilen and Sumida (2005) published a study on the similarities and
differences of intended science curricula for elementary levels between the Philippines and Japan in
terms of the aims, content and organization of the curricula. More recently, Lee et al. (2015)
compared Korean and Singaporean intended primary science curricula, and in their following and
highly detailed study, Lee et al. (2017) provided further insights into primary science curriculum
standards in mainland China, Hong Kong, Taiwan, Korea, Japan and Singapore. In turn, Wei and Ou
(2019) discussed the similarities and differences of junior high school science curriculum standards
among four Chinese regions.
Among such comparative studies specifically conducted in European countries, the report on the
analysis of curriculum documents for science subjects of the Czech Republic, England, Estonia,
Finland, France, and Poland conducted by Grajkowski et al. (2014) stands out because the authors
compared the Polish science core curriculum at the lower secondary level and the first year of higher
secondary school with the corresponding documents of the other countries. Concurrently, a number
of Czech research studies on comparative education in the international context have described and
compared education systems in different countries. For example, Greger et al., (2006) analysed
education systems in Germany, Great Britain and Sweden. However, to our best knowledge, no
study has directly compared the science subjects and mathematics curriculum of the Czech Republic
to the science subjects and mathematics curriculum of any other country in the context of learning
outcomes at the lower secondary level. Even the study by Elmas et al. (2020), which is the most
similar to our research, only compared chemistry curricula, doing so at a different level of education,
that is, upper secondary school.
Research Questions
Combining our research goals with the theoretical background described above, we formulated the
following research questions (RQ):
(1) How detailed are science subjects and mathematics curricula of the Czech Republic, Estonia,
Poland and Slovenia in terms of learning outcomes?
(2) Is the structure of learning outcomes similar across subjects within a single country?
(3) How do the cognitive demands of these curricula differ across selected countries?
(4) What are the specific features of Czech, Estonian, Polish and Slovenian curricula?
The first RQ aims to determine the number of obligatory learning outcomes, while the second RQ
relates to the internal coherence of national curriculum documents. Cognitive demands (RQ3) of
learning outcomes are measured by RBT.
Methodology
For our research purposes, we employed document analysis as a stand-alone method although this
technique is most often used for triangulation during qualitative research (Denzin, 1970). Document
analysis has several advantages: the documents are non-reactive, unaffected by the research process,
and remain stable and suitable for repeated reviews (Bowen, 2009). In this study, our document
analysis focused on content rather than thematic analysis, with a deductive category application
approach (Mayring, 2000).
Research sample: relevant curriculum documents
All countries compared in this study use a two-level curriculum structure. This curriculum structure
consists of (1) a national framework document, which defines basic requirements for education, and
(2) a school level document, which provides the framework for implementing education in specific
JOURNAL OF CURRICULUM STUDIES
7
schools and which is defined by each school itself. In our research, Czech, Estonian, Polish and
Slovenian national framework documents on lower secondary education (ISCED 2) were the primary
sources of information that provided raw data for our analysis. Hereinafter, we briefly describe these
documents and specify their sections analysed in our study.
The Czech primary and lower secondary systems are mostly single structured and termed basic
education. Therefore, the national core curriculum for lower secondary education in the Czech
Republic (CZC) is found in The Framework Educational Programme for Basic Education (2007). This
document formulates the conception of basic education, its objectives and the key competencies
that should be achieved by pupils. The educational content is divided into educational areas; in this
study, we address the areas Mathematics and Its Application and Humans and Nature, which include
the following educational fields: Physics, Chemistry, Geography and Natural Sciences (Czech designation for Biology at ISCED 2). Since 2005, when FEP BE was established in schools, no extensive
reform has been implemented, and its minor changes lay outside the scope of our research.
The Estonian curriculum (ESTC) came into force in 1996 and was divided into separate frameworks for
lower and upper secondary education in the 2011 revision (Lees, 2016). Estonia also has single structured
education with standards determined by The Estonian national curriculum for basic schools (National
curricula for basic schools, 2017). Its general section specifies core values and objectives of basic education, while appendices contain syllabi of subject areas and compulsory subjects. For our study, we selected
the subject fields Mathematics and Natural Science (i.e. physics, chemistry, biology and geography).
Since the 2017/2018 school year, a single structure education framework covering ISCED 1 and 2 has
been implemented in Poland (Wojniak & Majorek 2018). While the impact of the new curriculum
document has not been reflected in PISA yet, we analysed the curriculum document that was valid
before the reform, i.e. Podstawa Programowa Kształcenia Ogólnego Dla Szkół Podstawowych [Curriculum
for Primary and Secondary Schools] (PLC) (Dziennik Ustaw, 2012), more specifically the requirements in
the subjects Mathematics, Physics, Chemistry, Biology and Geography. Before the reform, compulsory
education included only the primary (ISCED 1) and lower secondary (ISCED 2) levels.
Slovenian education is also single structured, and its current curriculum (SLOC) has been in force
since 2011. The curriculum is available as hypertext and consists of a brief general section followed
by subject curricula (GOV.SI Portal, n.d.) described in separate, detailed documents containing the
definition of the subject, general goals, learning outcomes, knowledge standards and didactic
recommendations. Our study focused on the curricula of Mathematics (grade 6–9), Geography,
Physics, Chemistry and Biology.
In all countries, the current role of the national curriculum is quite similar, primarily shaping
school curriculum documents since learning outcomes must be defined and described in these
documents (see national education acts). In the Czech Republic, Poland and Slovenia, the correspondence between national and school curriculum documents is one of the assessment parameters
used in centralized school inspections; conversely, in Estonia, the self-evaluation of schools plays a
key role in evaluation policy (SICI, 2016).
In Estonia, Poland and Slovenia, pupils undergo an obligatory national examination at the end of
ISCED 2. In addition to providing pupils, schools, parents and other stakeholders with external
assessment metrics, the results of national examinations can serve as criteria for admission to
upper secondary education; however, passing these exams is necessary to graduate from lower
secondary school only in Estonia (National curricula for basic schools, 2017). In Estonia, Poland and
Slovenia, the requirements of the national examination reflect the general framework of the national
curriculum, but the specific content of examinations depends on institutions responsible for preparing them. The situation regarding textbooks is similar—in all four countries, teachers can choose
from different editions of textbooks, which must be approved by officials and in accordance with the
national curriculum. However, this is only a formal requirement in some countries; for example, the
scope of Czech textbooks is much wider than that of the CZC.
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P. KÁCOVSKÝ ET AL.
Research procedure
For each country, we first extracted obligatory learning outcomes from each national curriculum
document, as described above. Learning outcomes are termed expected outcomes in the CZC,
learning objectives in the PLC, operational objectives in the SLC and learning outcomes in the ESTC.
According to literature (Simpson, 1966), we assumed that each learning outcome (unit of analysis)
contains a cognitive component. The learning outcomes were analysed during the multilevel coding
process using RBT. The Metacognitive knowledge was coded in terms of a broader perception, as
detailed in the Theoretical Framework. Therefore, we did not differentiate specific cognitive processes for metacognitive learning outcomes. We did not specify the subtypes of knowledge dimensions presented by Anderson et al. (2001; see Table 2) either to maintain the scope of this paper
focused on its topic.
During the RBT coding process, the team of seven researchers split into six sub-teams of three to
four coders by study subject. The leader of each subject prepared (and, if necessary, translated) the
outcomes for coding; learning outcomes with geological topics were removed from the geographical and biological curriculum and assigned separately to the geological sub-team. The coding was
processed in three levels: (1) the coders in sub-teams coded the learning outcomes on their own and
uploaded their codes into a shared table, (2) one day before the joint meeting, the researchers
checked the codes in the shared table towards reaching a consensus; when the coding was still
inconsistent after the second level, (3) the coding of the learning outcome was discussed during the
joint meeting until reaching an agreement.
Coding rules
The learning outcomes were coded according to the type of knowledge (Factual (F), Conceptual (C),
Procedural (P) and Metacognitive (M)) and to the cognitive process (Remember (RE), Understand
(UN), Apply (AP), Analyse (AN), Evaluate (EV), Create (CR)). The researchers coded the learning
outcomes as they were precisely stated in the document and followed the whole context of the
learning outcome, not only the separate active verb. The latter remark is crucial because context
modifies meaning; therefore, verbs associated with one level of RBT in one context may be
associated with another level in another context (Stanny, 2016). Whenever the outcome was difficult
to code, in the sense of RBT, the researchers’ teaching experience was used to overcome such
problems.
The learning outcomes containing two or more active verbs are termed complex and coded
according to the following criteria: (1) When two or more verbs required the same type of knowledge
but different cognitive process, the higher process is coded.2 (2) When two or more types of
knowledge were identified, each of them was coded with the most demanding level of cognitive
process.3 The rules were used even when the verb was not explicitly written, but semantically
contained,4 or when the verb was used in a transgressive form.
The process of analysis was continuously run thanks to a feedback loop. The coding rules and
examples, precedents, were collected in a coding agenda and continuously updated whilst checking
formerly coded learning outcomes for reliability (Mayring, 2000).
Results
Numbers of learning outcomes
The first parameter on which we focused was the level of detail of the study curricula, which we
simply measured by the number of learning outcomes prescribed by curriculum documents, as
specified in Methodology. The results are summarized in Table 3. This statistics disregards the
complexity of the outcomes (e.g. whether they contain more sub-sections) or their ambitiousness.
JOURNAL OF CURRICULUM STUDIES
9
Table 3 shows that the geology curricula lack learning outcomes considering their relatively low
numbers across the countries. As a result, the use of quantitative measures (percentages or graphs)
can be misleading; henceforth, we will present the data on geology only qualitatively, thereby
avoiding comparisons using graphs or tables.
In terms of the five remaining subjects, CZC is the briefest and SLOC the most extensive; PLC and ESTC
show a generally similar extent (except for mathematics). Across the countries, science subjects account
for a relatively similar percentage of all outcomes analysed per country—21–30% in biology, 11–19% in
chemistry, 19–23% in physics and 16–20% in geography. In mathematics, this interval is considerably
wider, ranging from 8% in Estonia, where the mathematics curriculum is quite short, to 29% in Slovenia,
with more than 260 mathematics learning outcomes; CZC and PLC devote approximately as many
outcomes to mathematics as they do to major science disciplines (e.g. chemistry or geography).
In total, almost 1900 learning outcomes were analysed, as summarized in Table 3. Although we
outline the percentages of learning outcomes instead of their absolute numbers in the following
tables, these data must still be interpreted in the context of Table 3—especially for CZC, where a
single outcome typically accounts for ca. 3% of total outcomes within the subject.
Structures of the learning outcomes
The information outlined in Table 3 can be further analysed by assessing how the learning outcomes
are structured and whether their structure is similar among all subjects in the same country. During
the coding process, we differentiated simple (containing one active verb) from complex (two and
more verbs) outcomes; for complex outcomes, we also considered their ‘gradation’, i.e. whether they
required two or more different types of knowledge (Table 4).
In CZC and ESTC, ca. one third of the learning outcomes are complex, requiring more than one
type of knowledge; in PLC, this ratio is approximately one fourth. Slovenia, whose list of learning
outcomes is by far the most extensive, has only 11% of such outcomes, suggesting that, despite the
high number of outcomes, they are generally semantically simpler and less structured than the
corresponding outcomes of the other curricula.
Especially in CZC and PLC, Table 4 highlights considerable differences in the structure of learning
outcomes across particular subjects; cf. biology and chemistry in CZC or chemistry and mathematics
in PLC. In turn, SLOC shows low percentages of complex learning outcomes across all subjects, which
is the most characteristic feature of the Slovenian curricula.
Table 3. Numbers of obligatory learning outcomes prescribed by national curricula; the percentages between parentheses show
the percentage of specific subjects in the total number of outcomes of the country (which is reported in the last row of the table).
Biology
Chemistry
Geography
Geology
Mathematics
Physics
Total per country
Czech Republic (CZC)
31 (21%)
27 (18%)
29 (19%)
6 (4%)
29 (19%)
29 (19%)
151
Estonia (ESTC)
125 (30%)
62 (15%)
84 (20%)
11 (3%)
35 (8%)
95 (23%)
412
Poland (PLC)
109 (25%)
84 (19%)
69 (16%)
6 (1%)
73 (17%)
95 (22%)
436
Slovenia (SLOC)
187 (21%)
98 (11%)
158 (18%)
10 (1%)
262 (29%)
175 (20%)
890
Table 4. Percentages of complex learning outcomes requiring two or more types of knowledge.
Biology
Chemistry
Geography
Mathematics
Physics
Share per country
Czech Republic (CZC)
16%
52%
31%
28%
31%
30%
Estonia (ESTC)
20%
34%
33%
29%
52%
33%
Poland (PLC)
29%
44%
22%
3%
16%
24%
Slovenia (SLOC)
12%
10%
6%
15%
8%
11%
10
P. KÁCOVSKÝ ET AL.
Cognitive demands of the learning outcomes
The distribution of learning outcomes based on RBT is presented in Table 5. For each country and
subject, the numbers show the percentage of learning outcomes requiring the corresponding
combination of type of knowledge and cognitive process. The sums of the percentages exceed
100% because many learning outcomes include two or more different types of knowledge and/or
cognitive processes.
The highly detailed data presented in Table 5 can be analysed from two perspectives: types of
knowledge and cognitive processes.
Physics
Mathematics
Geology
Geography
Chemistry
Biology
Table 5. Percentages of learning outcomes requiring the corresponding combination of type of knowledge (F, C, P and M) and
cognitive process (RE, UN, AP, AN, EV and CR).
Czech Republic
F
C
P
RE 16 0
0
UN 0 48 3
AP 0
0
3
AN 0 19 10
EV 0
0
0
CR 0
0
0
F
C
P
RE 37 0
0
UN 0 44 4
AP 0
4 22
AN 0
7
0
EV 0 15 0
CR 0
0
0
F
C
P
RE 14 0
0
UN 0
7 10
AP 3
3 14
AN 0 34 0
EV 0 24 0
CR 0
0
3
F
C
P
RE 0
0
0
UN 0 67 17
AP 0
0
0
AN 0 33 0
EV 0
0
0
CR 0
0
0
F
C
P
RE 0
0
0
UN 0 17 3
AP 3
3 52
AN 0
3 14
EV 0
3
3
CR 0 10 7
F
C
P
RE 0
0
0
UN 0 17 0
AP 0 41 38
AN 0 21 3
EV 0
0
0
CR 0
0
3
M
RE
UN
AP
26
AN
EV
CR
M
RE
UN
AP
26
AN
EV
CR
M
RE
UN
AP
21
AN
EV
CR
M
RE
UN
AP
17
AN
EV
CR
M
RE
UN
AP
7
AN
EV
CR
M
RE
UN
AP
7
AN
EV
CR
F
12
0
0
0
0
0
F
19
2
0
0
0
0
F
29
0
0
0
0
0
F
36
0
0
0
0
0
F
0
3
3
0
0
0
F
31
12
0
0
0
0
Estonia
C
P
0
1
34 2
0
3
30 1
5
1
1
4
C
P
3
0
37 0
3 31
21 6
3
0
2
0
C
P
1
5
33 8
12 13
17 4
0
0
1
1
C
P
0
0
36 9
36 9
0
0
0
0
0
0
C
P
0
0
29 6
3 74
0
0
0
0
0
6
C
P
5
0
61 26
1 20
0
8
2
0
7
2
M
RE
UN
AP
29
AN
EV
CR
M
RE
UN
AP
13
AN
EV
CR
M
RE
UN
AP
15
AN
EV
CR
M
RE
UN
AP
18
AN
EV
CR
M
RE
UN
AP
9
AN
EV
CR
M
RE
UN
AP
0
AN
EV
CR
Poland
F
C
P
33 2
0
1 55 1
0
4
2
0 14 1
0
4
0
0
0
0
F
C
P
26 5
0
3 41 2
1
1 19
0
3
8
0
0
0
0
3 13
F
C
P
14 3
0
0 59 6
0
4
6
0
9
1
0
4
0
0
0
4
F
C
P
33 0
0
0 100 0
0
0
0
0
0
0
0
0
0
0
0
0
F
C
P
0
0
0
0
8
3
0 11 75
0
0
5
0
0
0
0
0
0
F
C
P
11 14 0
1 45 3
0
4 13
0
5 11
0
0
2
0
0
7
M
RE
UN
AP
17
AN
EV
CR
M
RE
UN
AP
1
AN
EV
CR
M
RE
UN
AP
12
AN
EV
CR
M
RE
UN
AP
0
AN
EV
CR
M
RE
UN
AP
0
AN
EV
CR
M
RE
UN
AP
0
AN
EV
CR
Slovenia
F
C
P
6 32 3
1 39 1
0
1
5
0
2
1
0
1
1
0
0
1
F
C
P
5
7
2
1 38 2
0
0 22
0
5
2
0
0
0
0
0
1
F
C
P
4
3
0
0 24 1
2 16 2
0 20 1
0 11 0
0
1
0
F
C
P
0 10 0
0 50 0
0
0
0
0
0
0
0
0 10
0
0
0
F
C
P
4
8
4
2 13 2
0
3 65
0
0
5
0
1
1
0
0
6
F
C
P
12 9
1
4 34 3
1
4 17
0
6 13
0
1
0
0
0
3
M
21
M
22
M
22
M
20
M
2
M
1
JOURNAL OF CURRICULUM STUDIES
11
Perspective of types of knowledge
The graphs in Figure 1 show the percentage of learning outcomes requiring a specific type of
knowledge within each subject, regardless of the level of required cognitive process.
In all science disciplines, across the countries compared in this study, Conceptual knowledge
was the most frequently required type of knowledge, accounting for more than 50% of learning
outcomes. In mathematics, Procedural knowledge prevailed (ca. 80%) in all four countries.
Procedurally oriented outcomes are also quite frequent in chemistry and physics curricula (usually
found in 30% of outcomes and more) and the least frequent in biology. Factual knowledge is only
sporadically required in more than 30% of outcomes, namely in biology, in PLC, in chemistry, in
CZC, and in physics, in ESTC; in mathematics, Factual knowledge is virtually not required at all.
Metacognitive knowledge is generally the least emphasized in the learning outcomes of PLC and
almost absent (< 10% of learning outcomes) from the mathematics and physics curricula of all four
countries.
Figure 1. Percentages of learning outcomes requiring different types of knowledge.
12
P. KÁCOVSKÝ ET AL.
Perspective of cognitive processes
The graphs of Figure 2 show the percentages of learning outcomes with specific cognitive processes.
Complex outcomes containing the same cognitive process several times (e.g. requiring both
Conceptual and Procedural knowledge at the Understand level) were included only once in the
graphs.
The two highest levels of cognitive processes, i.e. Evaluate and Create, are very rare (< 10%, most
often even < 5% of learning outcomes) across subjects and countries. In science disciplines, the level
Understand prevails, except in CZC, where Apply and Analyse are the most frequent levels in physics
and geography, respectively. Notably, the numbers of outcomes requiring the level Apply in biology
is generally very low.
Figure 2. Percentages of learning outcomes requiring specific cognitive processes.
JOURNAL OF CURRICULUM STUDIES
13
Specific qualitative features of the curriculum documents
In addition to the quantitative approach used in RBT, we selected some qualitative characteristics of
the national curriculum documents, again focusing on obligatory learning outcomes. However,
many relevant requirements are contained in the general sections of the national curricula (e.g.
common characteristics of specific subjects or educational areas). Therefore, in the next paragraphs,
we will also address these aspects of the intended curricula.
The most specific aspects of science disciplines are experimenting and practical work. In some
subjects, ESTC, PLC and SLOC apply the concept of prescribed experiments that pupils should or
must perform, listing these experiments. All three curricula require that pupils conduct experiments
in physics, ESTC and PLC require performing experiments in chemistry as well, and PLC recommends
them in biology. In biology and chemistry, SLOC also emphasizes more general experimental skills
(e.g. ‘know how to select and use appropriate tools and technology to conduct experiments’). ESTC lists
learning outcomes, often followed by Practical work and use of ICT, a section containing brief tips on
how to incorporate experiments/ICT into the current topic. ESTC and PLC also encourage pupils to
plan experiments (biology in Estonia and physics and chemistry in Poland) or to formulate hypotheses and expectations (biology and physics in Estonia and physics in Poland). In contrast to the
national curriculum documents of other countries, CZC does not specify experiments (except for
three measurements mentioned in physics and one pH measurement in chemistry), although
experimental work is mentioned within the educational area Humans and Nature.
Currently, science subjects and mathematics curriculum documents require working with data,
either collected during experiments or retrieved from external sources. Yet, in ESTC and PLC, only a
few outcomes inherently encourage pupils to work with data (biology and physics in ESTC and
mathematics and physics in PLC), such as recording, processing and interpreting data. In SLOC, this
emphasis on working with data is stronger: all subjects, except geology, include learning outcomes
focused on processing and analysing data from different sources or observations. CZC only explicitly
mentions work with geographical data.
Digital competence is one of the seven Key Competences for Lifelong Learning defined by the
European Parliament and the Council (2006). Presently, being digitally competent means having
competences in all areas defined by The European Digital Competence Framework, also known as
DigComp (Vuorikari et al., 2016). Yet, none of the learning outcomes of all countries analysed in this
study target the development of digital competence in this sense of DigComp. For this reason, we
also assessed whether the learning outcomes promote at least the use of ICT among pupils. Across
countries and subjects, we found that only approximately 10–15 of all 1900 outcomes analysed in
this study explicitly call for the use of ICT (personal computers, laptops and bring your own device
(BYOD), among other technologies) during instruction, almost invariably in mathematics, in ESTC
and SLOC. Furthermore, the extent to which the national curricula focus on ICT varies significantly
across countries. In CZC, the role of ICT is mentioned in two sentences at the level of educational area
Mathematics and Its Applications; for science subjects, a similar note is missing. In PLC and SLOC, the
importance of ICT is emphasized more often and repeatedly, in passages describing general goals of
specific subjects. ESTC is the most specific in offering tips in the sections Practical work and use of ICT
that follow most thematic units into which the learning outcomes are divided in the curricula.
In the context of environmental education, field trips or work are considered powerful educational
methods. However, their implementation in the national curricula varies across the selected countries.
For example, in geography, field trips or work are only mentioned at the level of learning outcomes in
PLC and SLOC. In CZC, field education is stated as one of seven thematic units of geography; nevertheless, the learning outcomes of this unit are formulated vaguely. Lastly, field trips or work are not
mentioned in ESTC at all. Similarly, in the biology curricula of all four countries, some learning outcomes
are often too general as well (e.g. environmental topics or first aid) and fail to clearly state that they aim
to develop practical skills (during field trips, laboratory work, experimenting and practising).
14
P. KÁCOVSKÝ ET AL.
Specifically focusing on geography, the approach to the regional geography varies significantly.
CZC provides a list of the general topics that should be applied to any region. In turn, PLC divides
regional geography into three parts—Poland, Europe, and the rest of the World, while ESTC focuses
only on the regional geography of Estonia and Europe. Regions listed in PLC and ESTC are used as
models for teaching general topics of social and physical geography. SLOC is the most detailed
curriculum in terms of regional geography, mentioning all main regions of the world in individual
topics reflecting specific problems and typical geographical processes.
Our analysis also showed no interdisciplinary overlaps between learning outcomes beyond the
field of natural sciences and mathematics. In all countries, geography is the only subject with
learning outcomes explicitly referring to social sciences (e.g. economy or sociology), which is
unsurprising considering that geography lies at the border between natural and social sciences.
Finally, in all countries, we found excessively widely, even vaguely, formulated learning outcomes,
as clearly observed in several subjects (physics, mathematics and geography, among others) in CZC.
For example, in physics and mathematics, one fourth of the outcomes contain the phrases ‘solving
practical problems‘ or ‘solving real-life problems‘; the teachers select the problems that they address in
class. In SLOC, various outcomes use the active verb ‘spoznajo’ which can be translated into ‘know’ or
‘learn’. Thus, the required cognitive process is not specified. Similarly, outcomes in PLC (in physics
and chemistry) frequently use the general phrasing ‘use the concept of sth.‘, also failing to clearly
identify the cognitive process required for the corresponding learning outcome.
Discussion
Number, structure and nature of learning outcomes
Despite the lack of a general rule for the ‘ideal’ number of learning outcomes within national
documents, some opinions prevail. Popenici and Millar (2015) indicate that an excessive number
of learning outcomes can be a source of confusion for students regarding specific expectations; in
turn, a minimum number of learning outcomes is necessary to ensure adequate information for a
comprehensive assessment of student learning. Although the authors provide these guidelines
primarily for university courses, such guidelines may also apply to national curriculum documents.
In Results, we showed that the curricula differ in the number of learning outcomes prescribed at a
national level. For example, SLOC has the highest number of learning outcomes, which are however
mostly simple (including one active verb). Conversely, CZC has a low number of learning outcomes
across subjects, yet Czech teachers have considerably more autonomy to develop their own syllabi
than their Slovenian counterparts. Hence, in addition to this number of learning outcomes, other
factors, such as their complexity, must also be considered when analysing intended curricula which
provide teachers with a high degree of autonomy.
In fact, the enhanced autonomy that Czech teachers are afforded also comes with its caveats. Lee
et al. (2015) state that, apart from textbooks, most teachers seek guidance in the intended curriculum, and primarily novices and less experienced teachers do so; in line with this argument, Kuiper
and Berkvens (2013) underscore that increasing teacher autonomy can be controversial, especially
when teachers lack professional experience and expertise. Moreover, as shown in a survey conducted by the Czech Ministry of Education, Youth and Sport (MŠMT, 2019), the Czech Republic is
facing a shortage of qualified teachers or even teachers as such, regardless of background. Therefore,
a brief intended curriculum should be adapted to meet the needs of a specific national context by
explicitly defining suitable learning outcomes (Elmas et al., 2020).
The structure of learning outcomes also differed considerably between subjects, even in the same
country—in CZC and PLC, the ratio of complex learning outcomes requiring two or more types of
knowledge ranges from zero to 50%, depending on subject. Focusing on the clarity of learning
outcomes, Kennedy et al. (2007) recommend using only one verb per learning outcome and avoiding
complicated sentences. Popenici and Millar (2015) further propose avoiding statements composed
JOURNAL OF CURRICULUM STUDIES
15
of multiple sentences or including more active verbs in the analysis. Conversely, Kennedy et al. claim
that the list of the outcomes may be too long and elaborate if the learning outcomes are very narrow,
thus suggesting using more sentences to clarify learning outcomes. Hence, experts recommend
using simple rather than complex learning outcomes, but this approach is not always possible. As
such, balancing the complexity and the number of learning outcomes may be the most feasible
strategy.
The conceptual apparatus (set of active words used in a curriculum) significantly varies by subject
in all curricula compared in this study, excluding ESTC. Whether these differences within national
curricula are intentional or merely reflect the lack of a common conception and agreement among
curriculum builders across subjects remain unanswered questions. The latter hypothesis is supported
by studies showing that expert commissions addressing curriculum changes mostly rely on the
experience of their leading members, not on expertise, formal investigations, or systematic research
(Westbury et al., 2016). This strong influence of renowned experts may exacerbate the fragmentation
of common conceptions. Consequently, the inconsistent terminology and structure of learning
outcomes across subjects can mislead and confuse teachers of more than one subject, raising
concerns about whether interdisciplinary overlaps are involved in the design of curricula meaningfully and thoughtfully or only for formal reasons.
Considering these inconsistencies within the same country, the question arises as to whether the
authors of intended curriculum create the documents following any taxonomy, e.g. RBT. Although
this intention is not obvious, the selection of active verbs in all four curricula indicates that the RBT
concepts were used to design most learning outcomes. After all, using RBT to design curriculum
documents at different levels is the standard strategy in some countries, e.g. the United Kingdom
(Council for the Curriculum, Examinations & Assessment, 2019; Uhlenwinkel, 2014).
Cognitive demands
As shown in Results, we found differences in cognitive demands across subjects and countries;
however, they are not systematic enough to enable us to reach extensive conclusions. For example,
we cannot conclude that any of the four national curricula generally demand higher or lower levels
of a required type of knowledge and/or cognitive process than the other. Similarly, our data do not
demonstrate that the disciplines show dramatically different cognitive demands but for two
exceptions.
The first exception is mathematics, which tends to require higher types of knowledge and
cognitive processes due to its focus on applications, regardless of country. The second exception
is biology, whose generally formulated learning outcomes could be related to the lower frequency of
Procedural knowledge, not only in the intended curricula but also in school reality. As a result of
these vague formulations, some topics can be taught mostly theoretically although they offer
numerous opportunities for more appropriate and relevant practical lessons (Kuba et al., 2019;
Wilks & Pendergast, 2017). For instance, the topic of first aid is included in the curricula of all four
countries, and even in more than one subject, albeit without detailing practical guidelines. Thus, the
national curricula of these countries should recommend not only specifying the key first-aid
measures (Bakke et al., 2017) but also training safety procedures and practising assessing consciousness and breathing, simulating resuscitation and calling emergency services, among other exercises
(Greif et al., 2015).
Across all countries and subjects, Metacognitive knowledge is the most neglected type of knowledge in the national curricula. Moreover, mathematics and physics curricula mostly overlook
Metacognitive knowledge in their learning outcomes, in all four countries, despite extensive studies
on metacognition demonstrating its importance for both teaching and learning (Hartman, 2001).
Georghiades (2006) further supports the notion that metacognitive activities enhance the pupils’
ability to use their conceptions of science cross-contextually. Accordingly, the curriculum must be
flexible to allow pupils to practice their metacognitive skills and to help teachers prepare activities
16
P. KÁCOVSKÝ ET AL.
that concurrently develop metacognitive thinking, according to Braund (2017). Therefore,
Metacognitive knowledge should be considered when designing learning outcomes and curriculum
documents (Wei & Ou, 2019).
ICT in learning outcomes
Notes on the use of ICT are rarely included in science subjects and mathematics learning outcomes
based on the findings of our study. Even when the importance of ICT is emphasized, it is done so at
the level of educational areas (CZC) or subjects (PLC, SLOC). We consider the approach applied in
ESTC the most appropriate because the use of ICT is advocated in most thematic units, immediately
following learning outcomes. However, in line with Hennessy et al. (2005), we believe that the
requirements of using ICT and developing digital competences should be formulated directly in clear
guidelines of obligatory subjects specifying learning outcomes considering the field-specific evidence. Several studies have shown that curricula often fail to link digital competences inside and
outside the school (Sefton-Green et al., 2009) and to reflect how everyday experiences can be
challenged in school-based settings. Therefore, relevant obligatory learning outcomes should
directly encourage pupils to process real-life data in spreadsheets or to use their own smart devices
meaningfully (i.e. BYOD) in various ways (Hennessy et al., 2005).
The position of geoscience
During our analysis, we found differences in a few key aspects of teaching geoscience. The first
aspect is the conception of regional geography, which is among the most discussed topics of school
geography in post-communist European countries (Daněk, 2020; Horváth & Próbald, 2003). In the
1990s, regional geography mostly focused on the uniqueness of various regions of the world, often
applying descriptive teaching methods and mainly fostering memorization learning strategies
(Knecht & Hofmann, 2020; Řezníčková, 2009). The curricula analysed in this study brought about
changes in approaches to regional geography, especially in the selection of the regions taught in
class. Yet, based on the number of learning outcomes of these national curriculum documents,
regional geography still prevails, except in CZC. CZC specifies topics of regional geography very
widely and lets schools select the specific regions; nevertheless, most Czech teachers still prefer the
descriptive model from the 1990s (Knecht & Hofmann, 2020). Therefore, when implementing
educational reforms on regional geography, Czech schools should strike a balance between generalizations and specifics, using the concept of New Regional Geography and replacing simple descriptions of regions with regional case studies and analyses (Daněk, 2020; Knecht & Hofmann, 2020; Paasi
et al., 2018).
In geology, CZC similarly interprets individual geological disciplines almost separately, paradoxically covering the widest range of geological topics (among all four countries) and yet defining the
lowest number of learning outcomes. The other curricula cover a narrower scope of geological
topics, directly connecting theoretical knowledge to regional examples. Thus, we deem this arrangement more appropriate because pupils receive complex information about a specific region whilst
learning general geological knowledge through specific examples.
The role of geology among other science disciplines is an even more general topic. At ISCED 2,
geology has been gradually less taught as a separate discipline (Lewis, 2008). More specifically, in
CZC, geological topics are included in biology syllabi, while the other national curricula incorporated
them, each in their own way, in geography. Including geology within other subjects subordinates the
subject (Meléndez et al., 2007). The decreasing ratio of geological topics at ISCED2 raises concerns
within the geology community for the substantial drop in geological contents in secondary and
tertiary education (Arthurs, 2019). Consequently, such a decline will inevitably lower the number of
geology students at universities and adversely affect research and knowledge on Earth (Arthurs,
2019).
JOURNAL OF CURRICULUM STUDIES
17
Conclusions and recommendations
In this study, we analysed science subjects and mathematics national curriculum documents of the
Czech Republic, Estonia, Poland and Slovenia from the perspective of obligatory learning outcomes.
The most conspicuous difference among these curricula is their extent—the highly detailed SLOC
has six times as many learning outcomes as the very brief CZC. A compromise must thus be reached
between these two slightly extreme approaches, that is, between providing teachers with the
necessary autonomy to empower them to develop their own activities and establishing clear
guidelines and orientations. Moreover, research conducted in the Czech Republic (MŠMT, 2019)
has revealed that schools in this country rely on a high number of non-certified teachers. For this
reason, the ongoing school reform should develop a more detailed curriculum with a higher number
of more specific learning outcomes to help teachers to create meaningful and applicable curriculum
documents of their schools.
Within some curricula (PLC, CZC), we found clear differences in the typical structure of learning
outcomes and active verbs used among subjects. These differences may indicate that, for each
subject, requirements were formulated by a different group of people, according to their expertise. A
closer collaboration between such groups could help to create a more uniform document with
further interdisciplinarity. Ideally, learning outcomes should use a single set of semantically unambiguous active verbs across subjects to facilitate the work of teachers who teach more than one if not
several of them.
Our measurement of cognitive demands using RBT found no significant systematic difference
among countries. The most frequent types of knowledge are Conceptual (in science subjects) and
Procedural (in mathematics). In turn, the most prevalent cognitive processes are Understand (in
science subjects) and Apply (in mathematics).
Across the curricula examined in this study, the cognitive processes Evaluate and Create are
underrepresented in all subjects. Since the level Evaluate has the potential to develop the critical
thinking of pupils and the level Create can encourage their independence and responsibility when
conducting a project, these cognitive processes must be strengthened in education reforms. In all
countries, we also recommend supporting metacognition, especially in mathematics and physics,
which almost completely overlook this cognitive process, by integrating it into topics such as Energy
and Environment, Renewable Energy or Financial Literacy. In biology and geosciences, we recommend supporting Procedural knowledge, especially in the form of practical tasks, observation and
field work.
Based on our analysis, the Czech Republic is the only country of the quartet examined in this study
where geological topics are taught in biology. However, the theoretical knowledge on geology
should be connected to regional examples. Therefore, we propose incorporating geological topics
into geography, as in ESTC, PLC and SLOC.
Finally, we strongly recommend explicitly incorporating cross-curricular demands (e.g. using ICT,
working with data and conducting experiments and practical and field work) into each subject whilst
specifying learning outcomes in the new Czech curriculum. Describing these demands and their
importance only in the general sections of national curricula is not enough for teachers or textbook
authors to take them into account in their work. In this context, Slovenian physics and chemistry
curricula, which specify the learning outcomes that should be achieved experimentally, emerge as
paradigmatic examples of good educational guidelines.
Limitations of the study
Among the main limitations of our study, the research method stands out because only exploring
the national curriculum documents precludes a complex examination of the educational reality in
any country. The main issue overlooked in this study due to its methodological approach is how the
autonomy of some schools in preparing school curriculum documents (based on national curricula)
18
P. KÁCOVSKÝ ET AL.
affects learning outcomes in these school documents. In addition, the extent to which national
curriculum documents influence teaching, e.g. how teachers and textbook authors follow curriculum
requirements, is another key question that remains unanswered. Similarly, by analysing only obligatory learning outcomes, we are necessarily disregarding other, often general, sections of national
curriculum documents, which also provide valuable information. Although we doubt that the
general sections of these documents are followed as thoroughly as the specific learning outcomes,
these sections should be analysed in follow-up research, for example, using latent semantic analysis.
In future research, other topics should be addressed in this area—for example, given the increasing
importance of the integrated Science, Technology, Engineering, and Mathematics (STEM) approach,
it could be suitable to analyse the incorporation of STEM in national curricula.
In terms of the coding process, by using a feedback loop (see Methodology), we strove for a
consistent approach across countries and subjects. However, for some outcomes, finding a consensus among the three coders was very difficult, thus preventing us from presenting their final
decision as absolutely unambiguous. This potential source of inconsistency could be eliminated by
automatic text analysis of the learning outcomes. Due to the absence of a coherent text, such an
analysis may have difficulty in following the entire context of the outcomes, which is crucial for
determining the level of RBT. However, it can warn of inconsistency in the coding of the same (or
similar) phrases and characteristic word combinations, thus partially doing the job of our ‘manual’
feedback loop.
As we have already noted, even within a single country we found considerable variation in the way
how intended learning outcomes are formulated across different subjects. Our experience shows that the
curricula of some subjects are easier to assess than others because they more closely match the
terminology and the spirit of RBT. Therefore, the applicability of RBT itself across subject-specific contexts
seems to be another limiting factor of our research framework.
Finally, PLC and SLOC are not available in English and required translation. Although we crosschecked ambiguously translated terms with our foreign colleagues (native researchers) whenever
necessary, we may not have avoided sporadic involuntary misinterpretations. Nevertheless, our RBT
analysis was not based on isolated active words but on the whole context of the learning outcomes,
thereby minimizing this study limitation.
Notwithstanding the aforementioned limitations, we believe that our results provide relevant
insights and highlight clear strategies for curriculum makers to plan and prepare effective education
reforms, not only in the context of the Czech education but also across cultures and education
systems with overlapping issues.
Notes
1. In agreement with the terminology used in taxonomies, we exceptionally use the term educational objective
instead of the above defined term learning outcome in a few following paragraphs dedicated to taxonomies.
2. ‘Explain and compare the functions of the respiratory systems of different vertebrates’ contains Conceptual knowledge at both Understand (‘explain’) and Analyse (‘compare’) level, ultimately coded as Conceptual-Analyse
(C-UN + C-AN = C-AN).
3. ‘Read chemical equations and, employing the Law of Conservation of Mass, calculate the mass of the reactants or
product’ were coded as C-UN and P-AP because of the two knowledge fields (C, P) and the higher cognitive
process (‘read’ = C-RE, ‘employing’ = C-UN, ‘calculate’ = P-AP).
4. ‘Describe Estonia’s geological structure according to drawings, thematic maps and the geochronological scale’ was
coded as C-AP. ‘According to’ in the sense of ‘using’ shifts the cognitive process from Understand to Apply.
Acknowledgments
We would like to thank our dear colleagues Martin Hanus, Tomáš Matějček, Jan Mourek, Dana Řezníčková (Charles
University, Prague), Marta Derek, Alina Awramiuk-Godun (University of Warsaw), Malgorzata Nodzyńska (Pedagogical
University of Krakow) and Saša Ziherl (University of Ljubljana) for their help and valuable consultations. The authors also
thank Carlos V. Melo for editing the manuscript.
JOURNAL OF CURRICULUM STUDIES
19
This work has been supported by Charles University Research Centre No. UNCE/HUM/024 and the project PROGRES
Q17 Teacher preparation and teaching profession in the context of science and research.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This work was supported by the Charles University Research Centre No. UNCE/HUM/024.
Notes on contributors
Petr Kácovský (ORCID ID 0000-0003-0675-6098), PhD, is an assistant professor and educator of pre-service physics
teachers at the Faculty of Mathematics and Physics, Charles University, Czech Republic. He is interested in research on
students’ misconceptions in thermodynamics and the role of experiments in science education, focusing especially on
physics demonstrations and lab work. He is a member of the team of experts for Czech national education curriculum
revisions.
Tereza Jedličková (ORCID ID 0000-0003-0260-9293), PhD, is a researcher of Didactics of Geosciences and educator of
pre-service teachers at Institute of Geology and Paleontology, Faculty of Science, Charles University, Czech Republic.
She is a lower secondary school teacher of biology and chemistry and has practice as assistant professor (didactics of
biology) at Department of Biology and Environmental studies, Faculty of Education, Charles University. She is interested
in research on implementation of digital technologies in biology and geology education in context of students’
motivation and popularization of science education.
Radim Kuba (ORCID ID 0000-0001-9614-9675) is a PhD student of Theoretical and Evolutionary Biology, research
scientist and teacher at Faculty of Science, Charles University, Czech Republic. He also teaches at a public elementary
school. Under the auspices of the Department of Teaching and Didactics of Biology, he focuses on experiential learning,
especially regarding the topics of first aid and crisis communication. He also takes part in projects examining the
learning disposition of students, their success in education and the psychological characteristics related to this (such as
the family environment, siblings, birth order).
Marie Snětinová (ORCID ID 0000-0003-4164-3160), PhD, is an assistant professor and educator of pre-service physics
teachers at the Faculty of Mathematics and Physics, Charles University, Czech Republic. She has Master and PhD degrees
in physics education from the Charles University. She works with students from upper secondary school level to
university level. Among her research interests are problem solving in physics education and students’ understanding
and motivation related to experimental work.
Petra Surynková (ORCID ID 0000-0002-4370-3916), PhD, currently holds the position of Assistant Professor at the
Department of Mathematics Education at Charles University, the Czech Republic. Her major is doing research in the area
of classical and applied geometry, and didactics of mathematics and teaching geometry. She held the position of
Research Assistant in the Institute of Applied Geometry at Johannes Kepler University, Austria in 2015 and 2016. In 2017
she was awarded a Fulbright scholarship and spent one year at Florida Atlantic University as a Fulbright scholar dealing
with the project Classical Geometry and Algorithmic Thinking in Research and Modern Education.
Matěj Vrhel (ORCID ID 0000-0002-9008-3385), is a PhD student and educator of pre-service geography teachers at the
Faculty of Science, Charles University, Czech Republic. He also teaches geography at a public elementary school. He
focuses on research on the quality of geographical education, fieldwork in school geography and the theory of
homeland studies. He is a member of the team of experts for Czech national education curriculum revisions.
Eva Stratilová Urválková (ORCID ID 0000-0002-8629-3582), PhD, is an assistant professor at the Department of Teaching
and Didactics of Chemistry, Faculty of Science, Charles University, Czech Republic, teaching mainly pre-service chemistry teachers (didactics of general chemistry) and she is a guarantor of students’ practice in chemistry at secondary
schools, therefore she is in contact with many chemistry teachers and school reality. She participated in European
projects focused on inquiry based science education, and experiments using probeware in science education.
ORCID
Petr Kácovský
http://orcid.org/0000-0003-0675-6098
Tereza Jedličková
http://orcid.org/0000-0003-0260-9293
20
P. KÁCOVSKÝ ET AL.
Radim Kuba
http://orcid.org/0000-0001-9614-9675
Marie Snětinová
http://orcid.org/0000-0003-4164-3160
Petra Surynková
http://orcid.org/0000-0002-4370-3916
Matěj Vrhel
http://orcid.org/0000-0002-9008-3385
Eva Stratilová Urválková
http://orcid.org/0000-0002-8629-3582
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