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Plan Ceibal 2020: future scenarios for
technology and education—the case
of the Uruguayan public education system
Matías Mateu
1*
, Cristóbal Cobo
2
and John Moravec
3
Abstract
In the present work, a set of future studies were implemented in order to answer the following question: What will
the future scenarios be within the next 5 years regarding new technologies in the public education sector in
Uruguay? For this purpose, two panels (consisting of 20 participants internal to the programme and 25 international
experts external to the programme) were set up to conduct a Delphi study. In addition, a historical analysis of the use
of Internet resources at schools (traffic and users connected to the network) was developed. This section of the study
brought us the following findings: Primary and middle public school centres have experienced an exponential growth
in Internet use as measured by traffic downloads and uploads, as well as by connections. Traffic doubled every 1.
5 years, and connections had doubled roughly every year in the period from 2011 to 2015.
The study integrated the Delphi results and the analysis of Internet use as a method for prospective scenario planning,
based on which four main possible educational and technological scenarios for 2020 were identified. This approach
allowed us to define the possible technological future for the national education and technology policy.
We found that the key challenges were not technological, but social and cultural factors. Some of the challenges to be
explored are (1) How can we understand the role(s) of teachers better?, (2) can we rethink how technology is being
used, adopted and adapted in learning environments?, and (3) what systemic changes are needed to respond these
possible scenarios better through policy development? The findings suggest that problems and challenges presented
by new technological innovations in education are not solved by more technology.
Finally, we consider an approach such as this could work as a framework to help develop public education and
technology policies in other countries with middle to high incomes that have strong orientations toward public
education, including much of Europe.
Keywords: Education, Technology, Policy Delphi, Future scenarios, Plan Ceibal
Introduction
More than seven decades have passed since B. F. Skinner
postulated his teaching machine to help children with
their education through the paradigm of personalised,
reinforced learning with programmed instructions [1].
Several decades after Skinner’s disruptive idea, Pappert
conceived the idea of one laptop per child for educa-
tional purposes in the 1960s [2]. However, it was not
until the very beginning of the twenty-first century that
the modern idea of one laptop per child arose. Fostered
by the spread of the Internet and the constant decrease
in the cost of devices, Nicholas Negroponte founded a
non-profit organisation called One Laptop per Child in
2005. Only 1 year later, an entire country, Uruguay, was
ready to test the entire paradigm via a public policy
called Plan Ceibal.
Plan Ceibal
Plan Ceibal is a national educational policy in Uruguay
that has the main objective of developing technological
and educational innovations at system level in the public
primary and secondary education system (ANEP). More
than 700,000 students (ranging from five to 18 years of
age), together with more than 40,000 teachers, are bene-
ficiaries of Plan Ceibal.
1
* Correspondence: matmateu@gmail.com
1
Plan Ceibal, Montevideo, Uruguay
Full list of author information is available at the end of the article
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The process of Plan Ceibal can be described in three
stages [3]. The first, from 2006 to 2009, had the main ob-
jective of decreasing the digital divide by granting access
to devices and the Internet to students and teachers across
the entire country [4]. The second stage was characterised
by the integration of technological, educational and social
support for the technological infrastructure [5]. The final
stage, implemented since 2013, has been characterised by
its focus on new educational practices [6].
In 2015, Plan Ceibal founded a study centre
2
called
Ceibal Foundation in order to conduct research and to
cooperate with other research institutions in the field of
technology and education worldwide. The study centre
has allowed Plan Ceibal to begin a prospective research
process in order to provide the policy with foresight
concerning the trends and possible scenarios regarding
new technologies in education and the deployment chal-
lenges thereof in a systematic manner. One of the results
of this process is documented hereafter.
Rethinking K-12 education for the twenty-first century
Today, there is a great debate about emerging paradigms
related to new practices and metrics in the educational
field. For researchers and practitioners, there seems to
be some difficulty when attempting to achieve a consen-
sus concerning the important questions to be asked. For
instance, as international evidence indicates, there is not
a clear correlation between the access or the use of
digital tools and the improvement in student perfor-
mances [7,8]. International studies show that standar-
dised tests are not indicating major changes when
measuring traditional performances. However, an
alternative form of reading these results is that the
measurement of socio-emotional changes in the learn-
ing, self-motivation, self-regulation among other capaci-
ties are very rarely measured or considered in these
types of studies. It is considered necessary to think more
about measuring what is valued instead of valuing that
which is measured [9].
New pedagogies for deep learning and Plan Ceibal
One concrete attempt to address the problem of re-
thinking pedagogies for twenty-first century is Plan
Ceibal’s partnership with the Global Network for Deep
Learning or NPDL (New Pedagogies for Deep Learn-
ing). This is an international initiative integrated by
several countries.
3
Uruguay is the only developing
enation involved in the network. Deep learning is a
conceptual and pedagogical framework where, “stu-
dents develop competencies and capacities that prepare
them to be creative, be connected, be capable of solving
problems in a collaborative way as well as being holistic
and good citizens contributing to the common well and
also creating it”[10].
Presentation of the research problem
The general problem addressed in this research is the
future of education in the Uruguayan context. More
explicitly, how do we rethink educational systems and
educational processes in the era of knowledge and accel-
erated cultural and technological changes? This work
explores the subsequent questions: What possible sce-
narios could emerge in the next 5 to 10 years regarding
technology enhanced education? How do we introduce
future perspectives and studies in Plan Ceibal policy
(and implementation)? More specifically, how do we
apply future studies to the adoption of new technologies
and to meet the challenges of effective integration into
the educational process?
The purpose of this study was to provide a methodo-
logical approach and results that could help policy
makers to be better prepared to answer these questions.
In addition, this could provide an insight into a meth-
odological framework to be used by other countries,
particularly those in Europe that have a tradition of
strong public education systems and policies.
Objective and research questions
In this study, a collection of future research techniques
were implemented in order to construct future scenarios
for the next 5 years with regard to new technologies in
the public education sector in Uruguay.
This general objective was divided into three specific
objectives:
–Objective 1: To analyse the evolution of Plan
Ceibal’s educational network (traffic and
connections) for the period 2011–2015 and to
project its evolution for the period 2016–2019
–Objective 2: To implement a Delphi study to obtain
a ranking of the most relevant new technologies in
the educational field for the period 2016–2020, as
well as a set of most important challenges associated
with the implementation of these new technologies
–Objective 3: To integrate objectives 1 and 2 via the
use of scenario planning techniques in order to
construct possible scenarios for the technological
and educational levels of adoption in the case of the
Uruguayan public education system.
The research questions formulated in order to achieve
these goals were:
1. What has been the “aggregated use”
4
of teachers
and students in the classroom in terms of Internet
traffic and connections?
2. Which new technologies
5
should Plan Ceibal
leverage within the next 5 years and what are the
key challenges
6
associated with these technologies?
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3. What scenarios can we build by means of Plan
Ceibal’s educational technology supply and the
educational system’s demand for the period 2016–
2019?
Methodology
Methodological scheme
In order to accomplish our goals, as well as to answer
the proposed questions, the research was designed
according to three phases, as presented in the methodo-
logical scheme in Fig. 1.
The three phases of the study are then described from
a methodological point of view.
Delphi study
A classical definition of the Delphi method was given by
Linstone and Turoff [11] as follows:
Definition 1 Delphi Method Must be characterised as
a method to give structure to the communication
process of a group. This method will allow the group to
manage a complex problem effectively.
The reviewed literature states that Delphi is a method
that is used to study mid- and long-term futures, al-
though it does not help to predict future events. Instead,
it helps experts in a specific field to achieve consensus
concerning a specific topic [12,13].
In general terms, the Delphi method is an iterative
process, which normally has two to three rounds con-
sisting of a series of questionnaires that are presented
for consideration to the panellists; the questionnaires are
then adjusted based on the panellists’answers and pre-
sented for reconsideration. Between the rounds, the
panellists receive feedback regarding their answers, as
well as feedback from the rest of the panel. In this sense,
it is a qualitative, normative and exploratory method
characterised by being anonymous and controlled debate
and is based on the statistics derived from the answers
of the group [12].
This method has been used extensively in the educa-
tion field in recent decades [14], as well as in medical
science and other fields [15,16]. Examples in the educa-
tion sector are the K-12 Horizon Project
7
from New
Media Consortium [17,18], the doctoral thesis by John
Moravec [19] and the doctoral thesis by Somerville [20].
Selection of the Delphi method
After analysing different techniques used in future stud-
ies, the Delphi method was chosen given an intention to
gather an important group of experts and asked them to
express opinions about and to discuss the proposed
topics. We used the K-12 Horizon Project [17] to gener-
ate the initial list of new technologies and the challenges
to the implementation thereof.
Panels
Two panels were introduced, one consisting of inter-
national experts from outside of Plan Ceibal (external
panel) and the other consisting of experts from within
Plan Ceibal (internal panel).
External panel A preliminary list of 45 invited partici-
pants was prepared, based on the criterion that they would
variously represent each of the four following categories:
academia, education, industry and the government. A per-
sonalised invitation was sent to each invitee. The ages of
participants ranged from 30 to 75 years, with an average of
50 years. Eight panellists came from the academic world,
seven from the academic and industrial sectors at the same
Fig. 1 Methodological scheme of the study
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time, four from education and two from industry. Nine of
the 21 had degrees in teaching. Finally, five were women
and 16 were men. The members of the external panel are
presented in Table 1.
Internal panel The internal panel was composed of 18
people (invited personally by the primary investigator),
who were section chiefs, managers, directors and advisers
from Plan Ceibal. Ten women and eight men participated.
The main criterion for invitation was that they would rep-
resent both education and technology divisions in the or-
ganisation. Also, eight internal panellists had an education
background, eight had an engineering background and
two had an economy background. The average age of the
panellists was 44.
Questionnaires As mentioned previously, the Delphi
process consisted of two rounds, which were answered by
both panels and comprised of online surveys. Each survey
was reviewed and tested prior to its application.
The main objective of the Delphi rounds was twofold:
1. To prioritise new technologies by considering the
importance of adoption and the feasibility thereof
2. To define strategies to counter challenges to the
implementation of these technologies in the case of
Plan Ceibal
Network use analysis
The Delphi study explores the possible future supply of
technology. In this section, we adopt the users’perspec-
tive; in other words, we analyse the users’demands for
technology. We aim to compute a proxy for the demand
for Internet resources and the evolution thereof in class-
rooms for the next 5 years. We will now summarise the
phase 2 of the study, as it is synthesised in [21].
The analysis includes the universe of urban schools in
the primary and secondary education systems. This
includes 1535 schools, each with its own wireless LAN
covering each classroom.
8
The variables tracked were:
–Download Internet traffic
–Upload Internet traffic
–Simultaneous connections
These variables were collected hourly each day, begin-
ning in 2011, via a network monitoring system and were
stored on a database maintained by Plan Ceibal. We
took a sample of each variable at a busy hour
9
to con-
duct our analysis. The data collected were completely
anonymous by nature.
Scenario planning
As stated in [12], and given the fact that we cannot pre-
dict the future with precision, scenario planning allows
us to understand plausible scenarios better. The main
motivation is to explore possible futures and not to
choose a favourite one.
We also consider that these kinds of tools allow us
not only to analyse possible futures but also to work
actively toward a preferred future. This constructive
approach is the basis of l’avenir from the French
Prospective School [22].
There is a wide range of definitions of scenarios in the
visited bibliography [23–25]. The definition adopted for
our purpose is presented in [26]:
Definition 2 Scenario Ascenario is a hypothetical
sequence of events built with the purpose of focusing
attention on causal processes and decision points.
We followed the three basic stages of scenario con-
struction methods, namely the identification of critical
dimensions and key factors (design), the construction of
scenarios (analysis) and visualisation and narration
(results).
Dimensions
The two dimensions for scenario construction were:
Table 1 External panel
Alejandro Maiche (FPSIC-UDELAR, Uruguay)
John Moravec (Education Futures, USA)
Ana Rivoir (FSC-UDELAR, Uruguay)
Laura Motta (ANEP, Uruguay)
Antonio M. Battro (indep., Argentina)
Leticia Britos (Stanford U., USA)
Carlos Petrella (FING-UDELAR, Uruguay)
Luis Garibaldi (CFE-ANEP, Uruguay)
Celsa Puente (CES-ANEP, Uruguay)
Luis Osin (GET, Israel)
Claudio Rama (inclep., Uruguay)
Marcelo Bagnulo (UCRMJETF, Spain)
Cristobal Cobo (Oxford U., UK)
Pablo Brenner (Collokia, Uruguay)
Daniel Kofman (Telecom ParisTech, France)
Pablo Sprechmann (NYU, USA)
Eugenio Severin (indep., Chile)
Rafael Mandressi (CNRS, France)
Fernando da Rosa (Ibirapita, Uruguay)
Raquel Aguilar (CTEP, Uruguay)
Fernando Santamara (U. de la Sabana, Colombia)
Gonzalo Mateos (Rochester U., USA)
Guillermo Spiller (Facebook, USA)
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1. Supply of educational technology: This dimension
was represented by Plan Ceibal’s portfolio of educational
technologies in the educational system.
2. Demand for educational technology: This dimension
represents the level of use and appropriation of the dif-
ferent assets and devices with which Plan Ceibal supplies
the educational system.
In other words, the Delphi study outputs were used as
a proxy for the future supply of educational technology
for the next 4 years, whereas the analysis of the network
use was used to project the future demand for educa-
tional technology by Plan Ceibal’s users.
Scenario construction
By combining the sign of the growth of both dimensions
under analysis, we obtained four possible scenarios,
illustrated in Table 2.
Validation of scenarios
There is no unique way to validate scenarios. In this
work, we adopted a practical approach, namely the
acceptance of the scenarios’construction and visual-
isation on the part of the stakeholders (decision
makers at Plan Ceibal and practitioners from primary
and education). A series of focus groups (one with
decision makers and one with practitioners) were de-
veloped within Plan Ceibal. The Futures Wheel
method [27] was used in order to investigate further
consequences of each scenario presented. This tech-
nique was perceived as very enlightening and encour-
aged profound discussion among participants through
different scenarios, showing their potential and ro-
bustness for exploration.
Analyses
Delphi study
Two rounds were administered during this stage. The
first round was carried out in July, 2015. The external
panel harvested 21 experts’answers, and the internal
one 19. The second round took place during October,
2015. Fourteen external panellists answered the second
quiz, and 17 answers were obtained for the internal sec-
ond round. The minimum number of expected answers
was 10 per panel [28].
New technologies
In order to process the responses, an interquartile range
(IQR) and interquartile deviation (IQD) was computed
for each item:
IQD = IQR/2 (1)
After the first round, each technology was ranked
according to the average score and the degree of consen-
sus was computed. The IQD indicated the dispersion of
answers along a given scale and is used as a proxy for
consensus measurement [15,29]. To calculate IQD, the
IQR is first computed:
IQR = Interquartile range = |P
75%
−P
25%
| (2)
The smaller the value of IQR is, the greater the con-
sensus of the group concerning that item is [30]. With
regard to a 5-point Likert-type scale,
10
a dynamic range
of authors uses 1.00 as the threshold of statistical con-
sensus [19,29].
To generate the ranking of new technologies, we
ordered the items according to the highest and lowest
average scores IQR.
First round
The initial 39 new technologies were ranked, and the
top 20 were selected for the second round.
Second round
In the second round, three different dimensions were
explored:
–Horizon of adoption: 2 to 4 years
–Impact on the learning process: scale 0 to 3; 0 = no
impact and 3 = high impact
–Usability: scale (0)
For the components of impact and usability, a metric
called relevance was generated, which establishes the im-
portance of adoption. In addition, with the dimension of
the horizon of adoption, they were sorted chronologically.
Implementation challenges
First round
Panellists were asked to rank five of the 19 initial items in
terms of their importance. Given the selection frequency
of each item and its order of importance for each panellist,
a ranking was created. The top five implementation chal-
lenges were then analysed in the second round.
Second round
In the second round, two dimensions of the top five
challenges were further evaluated by the panel:
–Implementation difficulty
–Forecast for the year 2020
Panellists were also asked to complete a field with a
justification of the answers and a field with proposed
Table 2 Future scenarios based on supply of and demand for
educational technology
Scenario Demand Supply Paradigm
2020-1 + + New
2020-2 + –Traditional
2020-3 –+ Conflict
2020-4 ––No paradigm
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strategies to leverage the resolution of each implementa-
tion challenge.
Based on implementation difficulty and the forecast
for 2020 dimensions, a metric called feasibility was tabu-
lated, which indicates the extent to which each imple-
mentation challenge could be solved by 2020.
From the textual answers and by using content ana-
lysis techniques [31], two outcomes were obtained:
1. SWOT Analysis (strengths, weaknesses, opportunities
and threats) to solve implementation challenges
2. Typology of strategies to boost the resolution of
principal implementation challenges
Network use analysis
The network analysis focuses on patterns, cycles and
seasonal effects, as shown in Fig. 2. We present two
charts. The first, aggregated into quarters, shows a con-
sistent increase in the traffic demand from quarter to
quarter. In the second chart, the aggregation is by
month, showing a dramatic decrease during the summer
break (December to February) and a moderate decrease
during the winter break (July).
Figure 3illustrates the evolution of demand and the
capacity of the Internet bandwidth in the period from
2011 to 2015. The demand has increased about four
times in the last 2 years of the study, whereas the cap-
acity almost doubled in the same period. The relation-
ship between the demand for the network (traffic and
connections) and the demand for infrastructure is
included in the analysis. This information illustrates the
requirements that the network supplier (Plan Ceibal) has
to consider when planning the evolution of the demand.
Finally, Fig. 4shows a projection of the trend for the
next years. This considers that the behaviour of the glo-
bal users remains the same.
Scenario construction
Each of the four scenarios shows a possible paradigm re-
garding the adoption and use of technologies in the pub-
lic education system in Uruguay. The word paradigm is
used to refer to a dominant educational and techno-
logical model in the system under study.
When analysing each scenario, we identified key
characteristics:
–2020-1: Transformational
11
scenario. A new
equilibrium is achieved between supply and demand
via the powerful use and effective adoption of
technology in the field of education.
Fig. 2 Global Internet traffic download at schools
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–2020-2: The supply is drastically reduced by political
and economic considerations. The system tends to
go back to previous stages before the existence of
Plan Ceibal.
–2020-3: A conflictive scenario in which Plan Ceibal
and the educational system struggle to take the
dominant paradigm in the field of technology and
education.
–2020-4: Collapsing scenario, in which the system
descends to a “lower”stage of development
(as Dator discussed [32]) and is about to become
extinct. However, this should not necessarily be
seen as a worst-case scenario.
In the “Results”section, a map is presented to visualise
the four scenarios, as well as narration based on key
factors.
Limitations of the study
In the Delphi study, there were three main limitations.
The first was that the number of iterations was limited
to two rounds in order to fit into the time-frame of the
project. Secondly, the tools to support communications
and quizzes did not allow for the fluency of interaction
with and real-time feedback to the panellists. Finally,
new items suggested the panels could not be incorpo-
rated into the initial questionnaire.
Fig. 3 Bandwidth capacity versus consumption of Internet at schools
Fig. 4 Schools’Internet traffic growth projection
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With regard to the network use analysis, two main
limitations appeared. The first is it was not possible to
identify whether the traffic and connections come from
devices delivered by Plan Ceibal or from personal
devices. Secondly, it was not possible to distinguish the
nature of the traffic (in other words, whether it was edu-
cational, recreational or another kind of activity on the
network.)
Another limitation of the study was the time scope:
5 years. We consider it was an appropriate time frame
because it matches strategic time scope. A long-term
scenario (10–20 years or more) would have brought
more complexity to the analysis taking into account un-
certain political and cultural dimensions among others.
Finally, with regard to the scenario planning, as ex-
plained earlier, it is important to stress that its goal is not
to predict but to identify, elucidate, align and understand
relevant trends that are influencing the actors and the
contexts that are linked to education and technology.
Results and Discussion
A principal result of the research is that challenges to
achieving transformative and desirable scenarios for
technological and educational integration at the system
level are not of a technological nature. This finding is sup-
ported by the evidence driven directly from answers both
in internal and external panels. Nine out of 10 top chal-
lenges prioritised by Delphi panels refer to the education
process mainly, not to the technological one (see Table 4).
This is a major confirmation of Plan Ceibal’sPublicPolicy
and focus on new pedagogies accelerated by new tech-
nologies (and not the other way around).
Delphi outcomes
New technologies ranking
The first output from the Delphi rounds is the ranking
of most relevant new technologies for each panel. This
can be seen in Table 3.
Ranking of implementation challenges
The second output of the Delphi study is the ranking of
the challenges. In Table 4, we summarise the top five
implementation challenges based on both panels’views.
A high level of overlap was found between internal and
external rankings.
Network use analysis
The most important finding is the exponential nature
of the growth of Plan Ceibal’s Internet traffic at an
aggregate level (i.e. the entire education system).
Download traffic has grown 13 times between 2011
and 2015. CISCO VNI [33]reportedthatglobalInter-
net download traffic had grown five times in the
same period. In other words, Plan Ceibal’sInternet
use has grown about 2.5 times faster than that of glo-
bal Internet users.
Download traffic doubled every 18 months during the
period between 2011 and 2015 (an average annual
growth rate of 68%.
With regard to simultaneous connections per site,
we found that this index doubled every 12 months
between 2011 and 2015 (an average annual growth
rate of 105%).
Another finding was related to the download/upload
ratio, which was 11 to 1, on average, between 2011 and
2015. That means that, for every 11 bits of information
that users consume, 1 bit of information is delivered
from a user’s device to the network.
Table 3 New technologies ranking sorted by relevance
Rank External panel Internal panel
1 Cloud Computing Adaptive Learning
2 On-line Learning Mobile Learning
3 Social Networks On-line Learning
4 Mobile Broadband Social Networks
5 Mobile Learning Virtual Remote Labs
6 Info Visualisation Gamification
7 Adaptive Learning Mobile Broadband
8 Gamification Learning Analytics
9 Bring your own Device Bring your own Device
10 Learning Analytics Cloud Computing
11 On-line identity Inverted Classroom
12 Crowd-sourcing Badges & Micro-credits
13 Flipped Classroom MOOCs
14 Visual Data Analysis Open Licensing
15 New Generation Batteries Augmented Reality
16 Augmented Reality Speech-text Translation
17 Open Hardware Holography
18 Internet of Things Internet of Things
19 Natural User Interfaces Crowd-sourcing
20 Semantic Applications Self-quantified
Table 4 Top 5 implementation challenges
Rank External Internal
1 Profit from system-wide
big data
Integrate new techs in the
educational change process
2 Integrate new techs in the
educational change process
Empower teachers on their
educational practices
3 Empower teachers on their
educational practices
Integrate personalised learning
4 Rethink teachers’and
professors’roles
Develop complex thinking
and communications
5 Integrate personalised learning Rethink teachers’and
professors’roles
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A final parameter that is very important in the plan-
ning and roadmapping of the educational infrastructure
is the ratio between the download bandwidth demand
and the installed capacity (supply). This ratio was re-
ported as being 40% utilisation of installed capacity.
All these findings confirm the exponential growth of
both traffic and connections in Plan Ceibal’s network in
the period from 2011 to 2015.
Scenario planning
The four scenarios are illustrated in Fig. 5. The following
is a description of the four scenarios constructed.
2020-1: new paradigm
This scenario presents a new paradigm that is based on
systemic innovation of educational technologies, with a
key role being played by the association Plan Ceibal -
ANEP.
The most relevant characteristic of this scenario is that
the main challenges have been resolved, whereas the
design and implementation have been consolidated into
a new methodological framework for the system—or
New Pedagogies for Deep Learning. This new paradigm
implements, tests and improves disruptive pedagogical
practices and experiments with a focus on methodology
(schools’networks), pedagogy (based on creativity,
problem-solving and collaboration) and assessment
(using with new metrics for assessing educational out-
puts) [34].
From an educational change perspective, the system
fosters techno-educational innovations, and change-
management capacities are developed within the system.
Plan Ceibal consolidates its philosophy of “learning by
doing”, and improvements are made in the process of
the personalisation of education based on analytics and
future studies, among other methodological approaches
to making decisions concerning the public policy.
2020-2: traditional paradigm
This scenario drastically reduces Plan Ceibal’s scope by
either institutional or economic restrictions. The public
policy is discouraged.
The education system has experimented with a regres-
sion in its capacity to develop techno-educational inno-
vations. Neither the equity nor the quality of Plan Ceibal
has been fulfilled. From the point of view of educational
change, the education system loses its capacity to
develop techno-educational innovations at the system
level, and there is no development of change manage-
ment capacity either.
Plan Ceibal is reduced to its minimum expression, and
a new divide in access and use of educational technolo-
gies is increasing.
2020-3: conflict paradigm
This is a scenario in which two paradigms face each
other, namely the traditional and the emerging para-
digms proposed by Plan Ceibal. As the system has a
series of stakeholders who interact with each other, this
complexity introduces a divergence of perspectives
among public, private and communitarian visions
regarding education.
The rivalry among stakeholders and parts of the
system neutralise the impacts and effects of the techno-
educational innovations developed by Plan Ceibal.
Fig. 5 Future scenarios for technology and education (x—technology supply, y—technology demand)
Mateu et al. European Journal of Futures Research (2018) 6:6 Page 9 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
2020-4: collapse paradigm
In this scenario, the system itself is redefined. It is the
end of the system as we currently know. The system
descends to a “lower”stage of development and could
also become extinct. This should not necessarily be seen
as a worst-case scenario. This could be given by a radical
discontinuity public policy (given by a new administra-
tion, for instance). The system is about to be redefined;
thus, innovation capabilities and culture depend on the
redefinition of the same system.
Conclusions
As we have seen, the Delphi method allowed us to map
the relevance of new technologies toward the year 2020
and to identify critical challenges for effective adoption
of these new technologies in public education. In
addition, a great degree of similarity was seen between
the internal and external panels.
The network use analysis then modelled the users’de-
mands for technology and evidenced that the beneficiar-
ies of Plan Ceibal have profited from resources at an
exponentially accelerated rate.
The third objective was to create possible scenarios for
technological and educational integration. We found
four plausible scenarios concerning the demand for and
the supply of technology.
The two dimensions used to build these scenarios
were technological supply (measured through the Delphi
study output) and technological demand (measured
through the patterns of network use). The key factors
that would determine each scenario were constructed
from critical challenges identified in the Delphi study.
Many aspects still remain open for further studies.
One aspect is how to harmonise the long and short-term
effects of technology.
As a public policy, Plan Ceibal has a five-year budget
and maintains a strategic view for action in this time
frame. On the other hand, we tend to overestimate the
short-term effects of technology while underestimating
the long-term effects (Amara’s law
12
).
For governments and administrations that typically
manage budgets for no more than 4 to 5 years, a pro-
spective long-term view of the technological and educa-
tional integration problem becomes a great challenge.
Furthermore, challenges for public policy do not exist
solely within the complexity of our system studied but
also with regard to the change of complexity in techno-
logical, educational and political dimensions over time.
This study tries to bridge the gap between strategic
short-term decisions in technological public policy and
implementation (5 years) and a long-term, comprehen-
sive perspective effective integration of education with
technologies (20 to 30 years). The next steps to continue
this work is to systematise a prospective process based
on expert panels, focus groups, or other techniques that
enable the flow and organisation of opinions and views
concerning possible technological and educational
futures for Plan Ceibal. This may help anticipate and
align public educational and technological policies and
craft implementation strategies to help realise preferred
futures.
Finally, the authors consider an approach like this
could work as a framework to help public educational
and technological policies in other countries with middle
to high incomes that have strong public education pol-
icies worldwide, with a particular eye toward Europe. As
Michel Godet said [22], “... the world changes but prob-
lems remain the same”. Thus, this vision of the invari-
ance of problems can give us a hint regarding that on
which we need to focus; in this case, the purpose of edu-
cational change across the world.
Endnotes
1
Information about Plan Ceibal can be found on its
web-site: www.ceibal.edu.uy/en/institucional) [Last visited:
31st of July, 2017]
2
http://www.fundacionceibal.edu.uy/en [Last visited:
31st of July, 2017]
3
The seven participating countries are Australia,
Canada, Finland, the Netherlands, New Zealand, the
USA and Uruguay.
4
Accounts for the sum of the traffic or connections of
all users of the network at a given time.
5
Set of educational technologies, access technology,
methodologies and digital strategies. The definition
was extracted from the K-12 Horizon Project 2014/
2015 [17].
6
Set of technological, pedagogical, curricular, political,
ethical and institutional issues that could act as barriers
to the adoption and integration of new technologies.
7
https://www.nmc.org/nmc-horizon/ [Last visited: 31st
of July, 2017].
8
For a comprehensive understanding of Plan Ceibal’s
network architecture, please visit (Spanish) http://blogs.
ceibal.edu.uy/tecnologia/redceibal/ [Last Visited: 27th of
July, 2017].
9
A busy hour is determined statistically and refers to
the hour of the day during which the network registers
the greatest use in terms of traffic and connected users.
By selecting busy hour time frame, we observe the
system’s behaviour when it is statistically demanded the
most, being able to compare it to its maximum capacity,
for instance.
10
https://en.wikipedia.org/wiki/Likert_scale [Last visited:
12th of May, 2017].
11
Jim Dator explained future scenarios as being a com-
bination of four paradigms: Transformation, Continued
Growth, Discipline and Collapse [32].
Mateu et al. European Journal of Futures Research (2018) 6:6 Page 10 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
12
https://en.wikipedia.org/wiki/Roy_Amara#Amara.
27s_law [Last Visited: 1st of August, 2017].
Acknowledgements
Special thanks are extended to all the participants of the panels and Jorge
Rasner from Universidad de la República, Uruguay.. We also would like to
thank all Plan Ceibal staff, particularly Sofía Doccetti and Fiorella Haim, for
the support.
About the authors
Matías Mateu is a Telecommunication Engineer and Technical Manager at Plan
Ceibal. He has co-led the implementation of the infrastructure and new tech-
nologies in the Uruguayan education system for the last 10 years. He is
co-leading Plan Ceibal’s strategy to develop big data analytics and the
prospective process of #edtech. His purpose is to help people and systems to
embrace change and uncertainty through strategic and future-oriented mind-
sets. He holds a Master. in Innovation Management (2016), a Diploma in Tele-
communication Engineering (2013) and a Degree in Electrical Engineering
(2006), all from the Universidad de la República, Uruguay.
Cristóbal Cobo (Ph.D.) is the Director of the Center for Research Ceibal
Foundation in Uruguay and is also an associate researcher at the Oxford
Internet Institute at the University of Oxford in the UK. He has served as an
external evaluator for the Inter-American Development Bank, the National
Science Foundation and MIT Press (US). Cobo works at the intersection of
the future of education, knowledge, technology and heutagogy.
John Moravec (Ph.D.) is the founder of Education Futures, a research and
advisory firm with a service mission, serving governments, schools and
universities in the Americas and Europe. His research and action scholarship
agendas are focused on exploring the convergence of globalisation,
innovation society, accelerating change in human knowledge development,
and building positive futures for knowledge creation systems in an era of
exponential uncertainty.
Authors’contributions
All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Publisher’sNote
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Author details
1
Plan Ceibal, Montevideo, Uruguay.
2
Fundación Ceibal, Montevideo, Uruguay.
3
Education Futures LLC, Minneapolis, MN, USA.
Received: 5 October 2017 Accepted: 11 April 2018
References
1. Skinner, B.F.: Review lecture: the technology of teaching. Proceedings of the
Royal Society of London Series B, Biological Sciences 162(989), 427–443
(1965). URL http://www.jstor.org/stable/75554
2. Papert, S.: Teaching children thinking. In: Proceedings of IFIPS world
congress on computer and education. Amsterdam, the Netherlands (1970)
3. Fullan M, Watson N, Anderson S (2013) Ceibal: Los próximos pasos. Michael
Fullan Enterprises, Toronto, Canada
4. Plan Ceibal y ANEP (2009) En el camino de Plan Ceibal, Referencia para
padres y educadores. UNESCO
5. Plan Ceibal y ANEP (2011) El modelo Ceibal. Nuevas tendencias de
aprendizaje. Plan Ceibal and ANEP
6. Plan Ceibal y ANEP (2013) Aprendizaje abierto y Aprendizaje flexible: más
allá de los formatos y espacios tradicionales. Plan Ceibal y ANEP
7. Busso M, Cristia J, Hincapié D, Messina J, Ripani L (eds) (2017) Aprender
mejor. Políticas públicas para el desarrollo de habilidades. Banco
Interamericano de Desarrollo Available at: https://www.iadb.org/es/
habilidades
8. Chaia, A., Child, F., Dorn, E., Frank, M., Krawitz, M., & Mourshed, M. (n.d.).
What drives student performance in Latin America? | McKinsey & Company.
Retrieved February 21, 2018, from https://www.mckinsey.com/industries/
social-sector/our-insights/what-drives-student-performance-in-latin-america
9. Cobo C (2016) La innovación pendiente. Reflexiones (y Provocaciones)
sobre Educación, Tecnología y Conocimiento. Penguin Random House
Grupo Editorial Uruguay URL http://digital.fundacionceibal.edu.uy/jspui/
handle/123456789/159
10. Fullan M, Langworthy M (2013) Towards a new end: new pedagogies for
deep learning. Tech. rep., Global Alliance For Deep Learning
11. Linstone H. A, & Turoff M. (Eds) (1975). The delphi method. Reading, MA:
Addison-Wesley. pp. 3–12.
12. Cobo C, Moravec J (2011) Aprendizaje Invisible. Hacia una nueva ecolog’ıa
de la educación, chap.4. Herramientas y metodologías para estudiar el
futuro de la educación. Collección Transmedia XXI. Laboratori de
Mitjans Interactius/Publicacions i Edicions de la Universitat de Barcelona,
Barcelona, España
13. Glenn, J., Gordon, T.: Futures research methodology: version 3.0. The
millennium project (2009)
14. Green RA (2014) The delphi technique in educational research. SAGE Open
4(2). https://doi.org/10.1177/2158244014529773
15. Chipchase L, Schabrun S, Cohen L, Hodges P, Ridding M, Rothwell J, Taylor
J, Ziemann U (2012) A checklist for assessing the methodological quality of
studies using transcranial magnetic stimulation to study the motor system:
an international consensus study. Clin Neurophysiol 123(9):1698–1704.
https://doi.org/10.1016/j.clinph.2012.05.003
16. Doran DM, Baker GR, Szabo C, Mcshane J, Carryer J (2014) Identification of
serious and reportable events in home care: a Delphi survey to develop
consensus. Int J Qual Health Care 26(2):136–143. https://doi.org/10.1093/
intqhc/mzu008 URL http://intqhc.oxfordjournals.org/content/26/2/136
17. Johnson L, Adams Becker S, Estrada V, Freeman A (2014) NMC horizon
report: 2014 k-12 education edition. The New Media Consortium, Austin
18. Johnson L, Adams Becker S, Gago D, Garcia E, Martn S (2013) Nmc
perspectivas tecnológicas: Educación superior en America Latina 2013–2018,
un análisis regional del informe horizon del nmc. Tech. rep. The New Media
Consortium, Austin
19. Moravec J (2007) A new paradigm of knowledge production in
Minnesota higher education: a Delphi study. Ph.D. thesis, University of
Minnesota
20. Somerville JA (2007) Critical factors affecting the meaningful assessment of
student learning outcomes: a Delphi study of the opinions of community
college personnel. Ph.D. thesis, Oregon State University
21. Cobo C, Mateu M (2016) A conceptual framework for the analysis and
visualization of Uruguayan inter- net for education. Interactions Magazine
VOLUME XXIII 6:70–73. https://doi.org/10.1145/2998387 URL http://digital.
fundacionceibal.edu.uy/jspui/handle/123456789/157
22. Godet M, Coates JF, Gerber A, Radford K (2006) Creating futures. Economica,
Genve, Paris, London
23. Davis G (2002) Scenarios as a tool for the 21
st
Century. Shell Centre,
London, England.
24. Meinert S. (2014), "Field Manual Scenario Building”. Brussels: European Trade
Union Institute.
25. Kosow H, Gaßner R (2008). Methods of future and scenario analysis:
overview, assessment, and selection criteria. Bonn: Deutsches Institut für
Entwicklungspolitik. URL http://www.die-gdi.de/en/studies/article/methods-
of-future-and-scenario-analysis-overview-assessment-and-selection-criteria/
26. Kahn H, Wiener, A. J, & Hudson Institute (1967). The year 2000: A framework
for speculation on the next thirty-three years. New York: Macmillan.
27. Glenn J. C, Gordon T. J, & Florescu E (2009). The Millennium Project. 2007
State of the Future.Washington: The Millennium Project. ISBN, 978(0):
9818941–2.
28. Hsu CC, Sandford BA (2007) Minimizing non-response in the Delphi process:
how to respond to non-response. Practical Assessment, Research &
Evaluation 12(17):62–78
29. Raskin MS (1994) The Delphi study in field instruction revisited: expert
consensus on issues and research priorities. J Soc Work Educ 30(1):75–89.
https://doi.org/10.1080/10437797.1994.10672215
30. Rayens MK, Hahn EJ (2000) Building consensus using the policy Delphi
method. Policy, Politics, & Nursing Practice 1(4):308–315. https://doi.org/10.
1177/152715440000100409 URL http://ppn.sagepub.com/cgi/doi/10.1177/
152715440000100409
31. Krippendorff K, Wolfson L (1990) Metodología de análisis de contenido:
teoría y práctica. Paidós Comunicación, Paidós
Mateu et al. European Journal of Futures Research (2018) 6:6 Page 11 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
32. Dator J.A, Sweeney J.A, Yee A.M (2015). Alternative Futures at the Mānoa
School. In: Mutative Media. Lecture Notes in Social Networks. Cham:
Springer.
33. CISCO (2015) Cisco visual networking index: global mobile data traffic
forecast update, 20142019. Tech rep., CISCO
34. Cobo, C., Brovetto, C., Gago, F.: A global network for deep learning: the
case of Uruguay. Digital inclusion: transforming education through
technology (2016). URL https://digital.fundacionceibal.edu.uy/jspui/
handle/123456789/158
Mateu et al. European Journal of Futures Research (2018) 6:6 Page 12 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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