Content uploaded by J. Ángel Velázquez-Iturbide
Author content
All content in this area was uploaded by J. Ángel Velázquez-Iturbide on Dec 04, 2019
Content may be subject to copyright.
Report of the Spanish Computing Scientific Society on Computing
Education in Pre-University Stages
J. Ángel Velázquez-Iturbide
Spanish Computing Scientific Society / Universidad Rey Juan Carlos
Madrid, Spain
angel.velazquez@urjc.es
ABSTRACT
In recent years, many developed countries have addressed
computing education in primary or secondary education. Potential
benefits for students in these educational stages and for the society
are great, existing a wide range of approaches to such a computing
education. The Spanish Computing Scientific Society (SCIE), with
the support of the Spanish Board of Deans of Computing Schools
(CODDII) created in September 2017 a working group formed by
experts in either computing or computing education with the goal
of elaborating a report with specific recommendations about this
issue for the Spanish government. The report was issued in July
2018 and recommends, in conformance to Spanish educational
laws, to establish a matter called “Informatics”. This matter would
preferably be implemented as a mandatory course offered from
primary to secondary education. The course contents comprise six
areas: programming, computers and operating systems, networks
and the Internet, data, digital content, and security. The course
would include issues of both digital literacy and computing as a
discipline, with digital literacy contents based on the European
DIGCOMP framework.
CCS CONCEPTS
• Social and professional topics~Computing
education • Social and professional topics~Model
curricula • Social and professional topics~K-12
education • Social and professional topics~Computational
thinking • Social and professional topics~Computing literacy
KEYWORDS
Computing education, K-12 education, computing literacy,
computational thinking
ACM Reference format:
J. Ángel Velázquez-Iturbide. 2018. Report of the Spanish Computing
Scientific Society on Computing Education in Pre-University Stages. In
Proceedings of TEEM conference (TEEM’18). ACM, New York, NY, USA,
2 pages. https://doi.org/10.1145/1234567890
1 Introduction
There are many reasons to introduce the study of computing in
schools and high-schools [15]. The situation in the different
countries of the developed world is heterogeneous (read [3][6] for
overviews of the European current situation).
In Spain, the situation is frustrating. There is no consensus
among the main political parties on an educational policy. In
addition, educational competences are distributed into the different
regions, with the national government only retaining basic
legislative competences. In these conditions, it is difficult to
introduce changes in the education system. The Spanish Computing
Scientific Society (SCIE), concerned with the importance of
computing education, created a working group in September 2017
with the brief of developing a report with specific
recommendations for the Spanish government, and in general for
the Spanish society. The report should not “reinvent the wheel”, but
should adapt to the Spanish legislative framework similar
recommendations. The working group was also supported by the
Spanish Board of Deans of Computing Schools (CODDII). The
final report was approved in June 2018.
The aim of this paper is to present a summary of the working
group report. An executive summary and the complete report can
be found at the web sites of SCIE [14] and CODDII [13]. The
structure of the paper follows. In the following section, we include
some preliminaries. In the third section, we include our proposal in
detail. Finally, we include our conclusions.
2 Preliminaries
Proper understanding of the proposal of the working group requires
a brief overview of some related concepts, and of the current
Spanish legislative situation regarding computing education.
Permission to make digital or hard copies of part or all of this work for personal or
classroom use is granted without fee provided that copies are not made or distributed
for profit or commercial advantage and that copies bear this notice and the full
citation on the first page. Copyrights for third-party components of this work must
be honored. For all other uses, contact the owner/author(s).
TEEM’18, October, 2018, Salamanca, Spain
© 2018 Copyright held by the owner/author(s). 978-1-4503-0000-0/18/06...$15.00
https://doi.org/10.1145/1234567890
TEEM’18, October, 2018, Salamanca, Spain J.Á. Velázquez-Iturbide
2.1 Digital Competence and Computing
It is important to make a sharp distinction between two concepts
that are not always well understood, especially by educational
policy makers, namely digital competence (also known as digital
literacy) and computing.
In 2006, the European Parliament identified eight key
competences of the citizen [12]. These competences were directly
incorporated by the Spanish Ministry of Education in 2015 as the
key competences of the curriculum [4]. According to its original
declaration, “digital competence involves the confident and critical
use of Information Society Technology (IST) for work, leisure and
communication.” There is little doubt about the convenience of
having basic skills in digital competence since primary education.
Thus, according to Informatics Europe and ACM Europe [11]: “All
students should benefit from education in digital literacy, starting
from an early age and mastering the basic concepts by age 12.
Digital literacy education should emphasize not only skills but also
the principles and practices of using them effectively and
ethically.”
On the other hand, computing is a discipline, with its own
fundamentals and body of knowledge. It is at the cross of at least
three cultures, namely mathematics, science and engineering [8].
Computer programming is probably the most popular area of the
computing body of knowledge, and is a relevant part of its core.
However, computing is much more than programming. Thus,
according to 2013 Computing Curricula [1], computing comprises
18 areas, with only some of them being related to programming.
There is a tendency to include programming in high-school , and
even school, curricula (often under the ambiguous term
“computational thinking” [7]). Basic knowledge of computing
fundamentals gives students a broader and deeper perspective to
understand their surroundings. Citing again Informatics Europe and
ACM Europe [11]: “All students should benefit from education in
informatics as an independent scientific subject, studied both for its
intrinsic intellectual and educational value and for its applications
to other disciplines”.
The two cites of ACM Europe and Informatics Europe are a
good summary the working group approach to this concern, as we
will show in section 3.
2.2 Digital Competence
There are different approaches to digital competence. The working
group adhered to the DIGCOMP framework [5][9][16]. There were
two main reasons: it is a well-structured framework and it is used
in Spanish government initiatives (and, more generally, in the
European Union).
The DIGCOMP framework defines digital competence by
means of five “dimensions” [5][9]:
1. Areas defined to be part of the digital competence.
2. Competence descriptors and titles that are pertinent to each
area.
3. Levels of proficiency for each competence.
4. Examples of the knowledge, skills and attitudes applicable to
each competence.
5. Examples of use, on the applicability of the competence to
different purposes. Actually, examples are provided for two
areas of use: employment and learning.
We include the areas and competences defined, updated in
DIGCOMP version 2.0 [16]. For full understanding, the reader
should read their definitions, as some terms have different nuances
than in computer science, e.g. programming or problem solving.
1. Information and data literacy.
1.1. Browsing, searching and filtering data, information and
digital content.
1.2. Evaluating data, information and digital content.
1.3. Managing data, information and digital content.
2. Communication and collaboration.
2.1. Interacting through digital technologies
2.2. Sharing through digital technologies
2.3. Engaging in citizenship through digital technologies
2.4. Collaborating through digital technologies
2.5. Netiquette
2.6. Managing digital identity
3. Digital content creation
3.1. Developing digital content
3.2. Integrating and re-elaborating digital content
3.3. Copyright and licenses
3.4. Programming
4. Safety
4.1. Protecting devices
4.2. Protecting personal data and privacy
4.3. Protecting health and well-being
4.4. Protecting the environment
5. Problem solving
5.1. Solving technical problems
5.2. Identifying needs and technological responses
5.3. Creatively using digital technologies
5.4. Identifying digital competence gaps
The third dimension distinguishes 8 levels of proficiency [5], which
pairwise correspond to foundation, intermediate, advanced and
highly specialized levels of proficiency. Examples for dimensions
4 and 5 can be found in several versions [5][9].
2.3 Computing
As any other discipline, experts in computing have often tried to
identify its constituent characteristics, including its object of study,
and relevant concepts and methods. Outstanding computer
scientists have contributed with different efforts, but the
characterization of computing that has wider acceptance if that
implicitly contained in the Computing Curricula. The last version
dates 2013 [1], but an antecedent, the Denning report [8], is
probably more understandable to novices. According to the
Denning report:
“The discipline is of computing is the systematic study of
algorithmic processes that describe and transform
information: their theory, analysis, design, efficiency,
implementation, and application. The fundamental
SCIE Report on Computing Education in Pre-University Stages WOODSTOCK’18, June, 2018, El Paso, Texas USA
question underlying all of computing is, «What can be
(efficiently) automated?»”
The Denning report acknowledged the core role of
programming in computing, but warned that computing is not
limited to programming. Nine subareas of computing were
identified:
1. Algorithms and data structures.
2. Programming languages.
3. Architecture.
4. Numerical and symbolic computation.
5. Operating systems.
6. Software methodology and engineering.
7. Databases and information retrieval.
8. Artificial intelligence and robotics.
9. Human-computer communication.
Obviously, this definition of computing has evolved since 1989,
giving place to more updated and more complex definitions. Thus,
Computing Curricula 2013 distinguishes 18 subareas.
2.4 Spanish Legislation on Computing in Primary
and Secondary Education
Spanish legislation has a complex structure. The national
Parliament has competences to establish the structure and most of
the contents of the educational system. In addition, regional
parliaments have partial competences on the definition of courses,
their contents and implementation. Finally, educational centers also
have partial autonomy on the implementation of courses.
Four educational stages are identified. Only primary education
and secondary education are mandatory:
‒ Elementary education, for children who are less than 5 years
old.
‒ Primary education, for children who are 5 to 12 years old.
‒ Secondary education, for children who are 12 to 16 years old.
‒ Bachelorship, for youngsters who are16 to 18 years old. Each
student must choose one of three specialties (“modalities”):
Sciences, Social Sciences and the Humanities, or Arts.
In Spanish legislation, each educational stage is characterized
by several elements. Firstly, broad, general learning goals are
given. Secondly, an organization of the stage is given, by
identifying the number of academic years, the courses to study in
each academic year and whether they are mandatory. Thirdly, a
detailed description of each subject matter is given by means of
contents, assessable learning standards and assessment criteria.
Fourthly, complementary considerations or details are dealt with.
As noted above, digital competence is identified as a key
competence for students [4]. However, there is no mandatory
course devoted to either digital competence education or computing
education in any educational stage. There are several optional
courses on digital competence, typically named “Information and
Communication Technologies”. Their offer depends on the
regional governments or the educational centers. Some regional
governments have established mandatory courses, within their
competences, devoted to programming and robotics [10]. However,
no holistic view of computing is given, and programming contents
are limited to “computational thinking” or robotics.
3 A Proposal for Computing Education
The working group elaborated detailed recommendations. The first
two subsections outline the intended requirements of
recommendations and the main elements of the proposal. Then, an
excerpt of the learning outcomes contained in the proposal are
given. Finally, two additional concerns are briefly addressed.
3.1 Requirements
The working group implicitly assumed several requirements:
‒ In alignment with the recommendations of Europe Informatics
and ACM Europe, the proposal should include both digital
competence and computing.
‒ The proposal should guarantee universal education, i.e. it
should guarantee that all students receive a minimum education
in the matter.
‒ The proposal should include realistic learning outcomes, which
were reasonably achievable by “a typical student”.
‒ The proposal should include recommendations adapted to each
educational stage.
‒ The proposal should be detailed enough to be understandable
by both policy makers and teachers. Policy makers should be
(relatively) free to adjust the recommendations to the current
legal format and to practical constraints. Teachers should be
able to acquire a rough but accurate idea of the contents in order
to successfully address their teaching duties.
3.2. Main Elements
After discussion within the working group, the following
conclusions were adopted:
‒ In the Spanish educational system, universality can only be
guaranteed by declaring a new subject matter, whose study
should be mandatory.
‒ The new subject matter would be called “Informatics”, given
the understandability of this term by typical citizens.
‒ The new subject matter should be implemented as a mandatory
course, which would be offered from primary education to
secondary education and bachelorship.
‒ As explained in the requirements section, the new subject
matter would include digital competence and computing. Its
contents were grouped into six areas:
o Programming.
o Computers and operating systems.
o Networks and the Internet.
o Data.
o Digital contents.
o Security.
‒ The detailed recommendation roughly adheres to the following
intents:
TEEM’18, October, 2018, Salamanca, Spain J.Á. Velázquez-Iturbide
o Primary education. It comprises a foundational level of
proficiency of digital competence, and basic
knowledge of programming, computers, networks and
data.
o Secondary education. Proficiency in digital
competence is increased to an intermediate level.
Knowledge of computing, especially of programming,
has a more abstract nature.
o Bachelorship. Deeper knowledge on computing is
acquired, and applications are oriented to the specific
scope of each specialty.
3.3. Detailed Specification
A relatively detailed specification was made of the contents of the
Informatics course in each educational stage. One key decision was
the format adopted for such a specification. Learning outcomes
were specified in a style similar to the learning goals of the revised
Bloom’s taxonomy [2]. An example of learning outcome for
programming in primary education follows: “[The student]
decomposes a problem into simple subproblems that make easier to
program it”.
We decided to specify learning outcomes instead of the
elements used in Spanish laws because we felt that we would not
be intrusive in the legislative labor and it would not be difficult to
make such a translation. For instance, for the learning outcome
given in the previous paragraph, it is not difficult to identify its
underlying contents, to develop assessment criteria, and to develop
learning standards to assess.
We include here the specification for two of the six areas for
primary and secondary education. The first area is programming
(see Table 1), and the second one is computers and operating
systems (see Table 2). An interesting detail is that the former area
was designed so that it only contains computing contents, while the
latter contains outcomes of computing and also of digital
competence. The complete specification of learning outcomes can
be found in the report [13][14].
Note in Table 2 that the two first learning outcomes for primary
education and the first one for secondary education end with a
numeration. This indicates that they are learning outcomes of
digital competence, not of computing. The numeration identifies
the area and competence of DIGCOMP that corresponds to such an
outcome. In this case, they correspond to competences 5.1 (solving
technical problems) and 5.2 (identifying needs and technological
responses).
Table 1. Learning outcomes in primary and secondary education for the area of programming
Primary education Secondary education
− Describes in an orderly and precise way the steps necessary to
solve a simple problem.
− Decomposes a problem into simpler problems that make easier
to program it.
− Understands that a program is edited and run in an electronic
device using a programming language with precise and non-
ambiguous statements.
− Uses a visual block-based programming language.
− Builds programs that makes specific tasks using sequence,
iteration, conditional, parallelism, variables and expressions.
− Uses logical reasoning to predict the behavior of block-based
programs, and detects and fixes bugs.
− Uses the basic elements of a textual programming language,
including data types and functions or procedures.
− In addition to stand-alone desktop programs, she is able to
construct some other kind of programs (e.g. a web application
or a mobile app).
− Understands the basic concepts of programming languages (e.g.
lexicon, syntax, semantics and virtual machine).
− Understands and uses Boolean logic.
− Uses logical reasoning to predict the behavior of textual
programs, and detects and fixes bugs.
− Understands the stages of the programming process: analysis,
design, edition, compilation, testing, debugging, documentation,
incremental development.
− Uses an iterative process to develop programs.
− Explains in a structured way the design of a program and
documents it.
− Applies test cases, previously designed, to check the correct
behavior of programs.
Table 2. Learning outcomes in primary and secondary education for the area of computers and operating systems
Primary education Secondary education
− Knows how to solve simple problems for handling electronic
devices and applications (5.1).
− Knows how to customize an operating system (5.2).
− Knows the difference between different electronic devices (e.g.
computer, smartphone, etc.), and between hardware and
software.
− Knows the components of a computer and understands the role
they play in its working.
− Understands the role of the operating system in an electronic
device.
− Handles units (and their multiples) of storage capacity and of
processing speed.
− Knows the main characteristics and functionality of electronic
devices, selecting the most adequate device or functions for a
given task (5.2).
− Designs simple digital circuits with logic gates.
− Understands the hardware and software components of a
computer, and how they inter-communicate and communicate
with other computers.
− Understands the main functions of operating systems.
− Understands how machine instructions are stored and run in a
computer.
TEEM’18, October, 2018, Salamanca, Spain J.Á. Velázquez-Iturbide
Table 3. Learning outcomes in bachelorship for the area of programming
Specialty of Sciences Specialty of Social Sciences and the
Humanities Specialty of Arts
− Understands some linguistic
fundamentals of programming languages
(e.g. alphabets and languages, regular
and context-free languages).
− Knows lineal data structures (e.g. stacks
and queues).
− Understands some fundamental
algorithms, both from mathematics (e.g.
numeric of matrix algorithms) and
information processing (e.g. sorting or
searching).
− Develops and applies test cases to simple
algorithms.
− Develops programs systematically,
according to a simple life-cycle (analysis,
design, etc.).
− Develops programs for application fields
related to the specialty of Sciences (e.g.
data analysis), orienting them to current
applications (e.g. robotics, artificial
intelligence, virtual or augmented reality,
big data, etc.).
− Develops programs of medium
complexity for several platforms (e.g.
programs for desktop computers,
dynamic web pages or mobile apps).
− Traces the behavior of recursive
programs.
− Uses several criteria to evaluate
algorithms in simple ways (performance,
style, etc.).
− Understands some linguistic
fundamentals of programming
languages (e.g. alphabets and
languages, regular and context-free
languages).
− Knows lineal data structures (e.g.
stacks and queues).
− Understands some fundamental
algorithms, both from mathematics
(e.g. numeric of matrix algorithms) and
information processing (e.g. sorting or
searching).
− Develops and applies test cases to
simple algorithms.
− Develops programs systematically,
according to a simple life-cycle
(analysis, design, etc.).
− Develops programs for application
fields related to the specialty of Social
Sciences and Humanities (e.g. data
analysis), orienting them to current
applications (e.g. artificial intelligence,
big data, etc.).
− Understands some linguistic
fundamentals of programming languages
(e.g. alphabets and languages, regular
and context-free languages).
− Knows lineal data structures (e.g. stacks
and queues).
− Understands some fundamental
algorithms, both from mathematics (e.g.
numeric of matrix algorithms) and
information processing (e.g. sorting or
searching).
− Develops and applies test cases to simple
algorithms.
− Develops programs systematically,
according to a simple life-cycle (analysis,
design, etc.).
− Develops programs for application fields
related to the specialty of Arts (e.g.
artistic creation), orienting them to
current applications (e.g. robotics,
artificial intelligence, virtual or
augmented reality, etc.).
Table 3 shows the learning outcomes for bachelorship in the
area of programming. Given that there are three specialties, they
share a subset of the learning outcomes, with applications oriented
to the specifics of the specialty. However, the Sciences specialty
includes a deeper treatment of some topics. The same guidelines
were used to design Bachelorship competences for the other areas.
3.4 Other Concerns
The working group report stresses the importance of two open
concerns, sketching how they could be addressed in the future.
The first concern is the implementation of our
recommendations. Computing is only of the many disciplines that
students must be educated in. Global scheduling (and legislation)
of education is a political and educational issue that is out from our
scope. However, other issues could be further refined with our
assistance. Thus, the computing science education community has
made available a body of knowledge that allows making more
concrete recommendations on teaching materials, hardware and
software resources, or kinds of exercises. Finally, some issues are
still open and further research is needed, such as the definition of
learning itineraries.
A second concern is teacher training. In Spain, teachers of
primary education receive a general-purpose education, while
teachers of secondary education are graduated in different degrees
and they are later specialized into education. Obviously, training
secondary education teachers with a background on computing or
related degree for computing education tasks is much easier than
training primary teachers. However, this is a problem which also is
found in other countries and can be addressed with adequate long
term policies.
4 Conclusions
We have presented a summary of the report elaborated by the
SCIE/CODDII working group on computing education in pre-
university stages. First, preliminaries were presented, including the
concepts of digital competence and computing (and relevant
frameworks) and some elements of Spanish educational legislation.
Then, the requirements, the main elements and a relatively detailed
description of our recommendations were presented. Other relevant
concerns also were addressed briefly.
The main contribution of the report is a set of founded
recommendations on computing education in pre-university stages.
Given the SCIE/CODDII recommendations, the Spanish
government has available a founded basis to address the education
of future generations in computing. Our recommendations are
TEEM’18, October, 2018, Salamanca, Spain J.Á. Velázquez-Iturbide
based on a rigorous conceptual framework and are aligned with
other international initiatives. There are open issues and challenges
that should be addressed if the recommendations were put into
practice. The current recommendations should be adapted to a
number of political and educational constraints, and its
implementation should be monitored to detect working anomalies.
There are huge challenges for the future. The most obvious if
our capability of diffusing and explaining our recommendations to
the Spanish society.
ACKNOWLEDGMENTS
I want to thank all the members of the working group, who
altruistically contributed with their efforts.
REFERENCES
[1] ACM e IEEE Computing Society, the Joint Task Force on Computing Curricula.
2013. Computer Science Curricula 2013 – Curriculum Guidelines for
Undergraduate Degree Programs in Computer Science,
https://www.acm.org/binaries/content/assets/education/cs2013_web_final.pdf.
[2] L.W. Anderson, D.R. Krathwohl, P.W. Airasian, K.A. Cruikshank, R.E. Mayer,
P.R. Pintrich, R. Raths and M.C. Wittrock. 2001. A Taxonomy for Learning,
Teaching and Assessing – A revision of Bloom’s taxonomy of educational
objectives, Addison-Wesley Longman.
[3] A. Balanskat and K. Engelhardt. 2015. Computing Our Future: Computer
Programming and Coding - Priorities, School Curricula and Initiatives across
Europe, European Schoolnet,
http://fcl.eun.org/documents/10180/14689/Computing+our+future_final.pdf/746
e36b1-e1a6-4bf1-8105-ea27c0d2bbe0.
[4] BOE. 2015. Orden ECD/65/2015, de 21 de enero, por la que se describen las
relaciones entre las competencias, los contenidos y los criterios de evaluación de
la Educación Primaria, la Educación Secundaria Obligatoria y el Bachillerato,
29th January 2015, nº 25, sec. I, pp. 6.986-7.003.
[5] S. Carretero, R. Vuorikari and Y. Punie. 2017. DIGCOMP 2.1: The Digital
Competence Framework for Citizens, report EUR 28558, Institute for Prospective
Technological Studies, Joint Research Centre, European Commission.
[6] The Committee on European Computing Education (CECE), Informatics Europe
and ACM Europe. 2017. Informatics Education in Europe: Are We All in the
Same Boat?, http://www.informatics-
europe.org/component/phocadownload/category/10-
reports.html?download=60:cece-report.
[7] P. J. Denning. 2017. Remaining trouble spots with computational thinking,
Communications of the ACM, 60(6):33-39, DOI 10.1145/2998438.
[8] P. J. Denning, D. E. Comer, D. Gries, M. C. Mulder, A. Tucker, A. J. Turner and
P. R. Young. 1989. Computing as a discipline, Communications of the ACM,
32(1):9-23, enero 1989.
[9] A. Ferrari. 2013. DIGCOMP: A Framework for Developing and Understanding
Digital Competence in Europe, report EUR 26035, Institute for Prospective
Technological Studies, Joint Research Centre, European Commission.
[10] Instituto Nacional de Tecnologías Educativas y Formación del Profesorado,
INTEF. 2018. Programación, robótica y pensamiento computacional en el aula:
Situación en España – enero 2018, http://code.educalab.es/wp-
content/uploads/2017/09/Pensamiento-Computacional-Fase-1-Informe-sobre-la-
situación-en-España.pdf.
[11] Joint Informatics Europe and ACM Europe Working Group on Informatics
Education. 2013. Informatics Education: Europe Cannot Afford to Miss the Boat,
http://europe.acm.org/iereport/ACMandIEreport.pdf.
[12] Official Journal of the European Union. 2006. Recommendation of the European
Parliament and of the Council of 18 December 2006 on key competences for
lifelong learning, 2006/962/EC, 30th December 2006, 394/10-18.
[13] J. Á. Velázquez-Iturbide (coord.). 2018. Informe del grupo de trabajo
SCIE/CODDII sobre la enseñanza preuniversitaria de la informática, CODDII,
http://coddii.org/la-informatica-como-materia-clave-en-las-ensenanzas-
preuniversitarias/.
[14] J. Á. Velázquez-Iturbide (coord.). 2018. Informe del grupo de trabajo
SCIE/CODDII sobre la enseñanza preuniversitaria de la informática, SCIE,
http://www.scie.es/informatica-ensenanza-no-universitaria/.
[15] S. Vogel, R. Santo and D. Ching, 2017. Visions of computer science education:
Unpacking arguments for and projected impacts of CS4All initiatives.
Proceedings of the 2017 SIGCSE Technical Symposium on Computer Science
Education (SIGCSE 2017), ACM DL, pp. 609-614, DOI:
http://dx.doi.org/10.1145/3017680.3017755.
[16] R. Vuorikari, Y. Punie, S. Carretero and L. Van den Brande. 2016. DIGCOMP
2.0: The Digital Competence Framework for Citizens, report EUR 27948,
Institute for Prospective Technological Studies, Joint Research Centre, European
Comission.
