Evaluating System Dynamics as a Tool for Teaching
History
Margarita Maria Cruz Barrientos
Mphil. in System Dynamics / University of Bergen, Norway
Corso Vittorio Emanuele 474, 90100 Palermo-Italy
+39 3345786165
macusita.82 @ gmail.com
Abstract
Key words: conventional education, weaknesses, behavior over time, structure,
understanding, identification, transfer, learning, performance, revolutions.
History has been traditionally taught as a presentation of isolated facts which fill
students’ minds with a great volume of dates, actors and events. However, students are
seldom encouraged to relate what they learn with changes over time. Thus, they present
a lack of understanding of what history has to do with them. Therefore, there is a strong
need of placing the understanding of this subject into a structured pattern that leads
students to the understanding not only of the past, but also of the present and the future.
In this paper, SD is evaluated as a tool to enhance students’ understanding of history.
Experiments with high school students were run, in which SD and the conventional
method of teaching history were tested with groups of students with either no previous
experimental experience with the teaching method or without previous experimental
experiences on them. The results present the SD teaching method as a better tool to
teach history with students who used SD before. however, the conventional method
reveals to be persistent in student’s minds when they do not posses any previous
experience with SD. Important outcomes are documented for future replications of the
experiment.
1. Problems with Conventional Methods of Teaching
History
The goal of learning history is subject to two main interpretations by educators:
enhancing collective memory or the disciplinary approach. Enhancing collective
memory is the conventional goal of history education, which proposes history
instruction provide learners with a base of historical knowledge that is deemed
important by authority figures who guide educational policies. Under this goal,
students’ primary task is the chronological memorization of events, and their associated
names, dates and locations. The second approach is based on teaching skills for
understanding history in the way historians do, which indeed, is not the conventional or
widely used method of teaching this field (Wiley & Ash, 2005).
The usual history book combines text of historical narratives with maps, charts,
timelines, pictures, diagrams and paintings to convey the historical happenings.
Furthermore, history teachers often supplement reading assignments and lectures with
films or documentaries based about how history occurred. However, despite the use of
this media, students are not provided yet with the proper understanding of the past in
light of comprehending the present and interpreting possible futures (Potash 1995).
It has been widely discussed among critic educators that school education is not
preparing students to cope with modern life. It is argued that the main failure is revealed
in the form of corporate executives who misjudge the complexities of growth and
competition, government leaders who are at a loss to understand economic and political
change, and publics that support inappropriate responses to public concerns (Forrester,
1992). Furthermore, since students are overloaded with facts without having a
framework of reference for making those facts relevant for the complexities of life, it is
strongly discussed that there is an important part of the learning process, which is
discarded. Thus, there is strong agreement in the fact that traditional education, because
of its fragmentary nature, becomes less relevant as society becomes more complex,
crowded, and tightly interconnected (Forrester, 1992). In addition, there has been
extensive accordance in the fact that Conventional teaching methodology seems to
make many students lose motivation about some fields that are difficult to relate to the
present. Furthermore some students after being taught with the Conventional method
fail to recall previous knowledge and thus, they make mistakes due to ignoring lessons
of the past (Forrester, 1992), (Burton, 2006)', (History News Network, 2006). This is
the case of social sciences, especially history, a subject that is widely taught as a mere
presentation of dates, events, and actors, which are hardly related to causes,
consequences and effects that have to do with other fields of study and with real life.
Hence, history is widely taught without analyzing the context that gave life to the
happenings and without relating similar behaviors on a shorter time scale that a student
can experience in a week or a year (History News Network, 2006). As a result, students
find difficult to relate to changes over time in the present and future. They can hardly
understand the reason why they learn something that has happened already and is not
going to change by its study (Forrester, 1992), (History News Network, 2006).
Beyond the previous thoughts and impressions of those critic educators lay in students’
performance as the determinant factor about whether or not students, certainly,
understand what it is presented to them about history, and about whether or not such
critics are truth.
Results of this Conventional schema of teaching history speak for themselves.
Embedded into this frame, students —-especially those in high school- dislike those
subjects that are barely related to real life, that seem to be impractical. When they list
their favorite subjects, history always comes in last. They consider it the most irrelevant
of 21 school subjects; “boring” is the description most often applied (Loewen, 1996).
Up to 20% of the student population at Fisher School in United States have classified
history as the least favorite subject they are ever taught (Jianting, 2006). On the other
hand, it has been found that history has not only been classified by students as the most
boring subject but also as one of the hardest and most difficult to understand and recall
in mind after the examination periods, just 10% of the population at Fisher School find
' Orville Vernon Burton is Professor of History and Sociology at the University of Illinois, Urbana-
Champaign (UIUC). He is also a Senior Research Scientist at the National Center for Supercomputing
Applications where he heads the initiative for Humanities and Social Science projects. Further
information at: http://historymatters.gmu.edu/d/6164
it easy to learn (Jianting, 2006), (Burton, 2006). Furthermore, Pinette? has stated that
because the typical high school history curriculum requires students to do little more
than memorize names, dates, and major historical events, students often begin college
with the belief that history is "Truth" rather than interpretation, which may highly
intervene in their performance by limiting the learning sense of such field (Pinette,
2002).
Such performance confirms, then, what educators tend to highlight with the intention of
claiming for improvements in history education. Therefore, this overview cannot be
nullified and deserves full attention, especially when history is seen as a discipline
whose learning and understanding takes students into the commitment with social
reality (Burton, 2006). Furthermore, history’s understanding becomes crucial because
mistakes made in the past recur often because there is not sufficient knowledge and
understanding of the lessons of the past (Burton, 2006). Hence, it is clear that history
education requires much more than the presentation of snapshots of what happened in
the past. There is an evident weakness of the Conventional method in giving the
students the tools to interpret more effectively the world around them. The method,
then, call for its enhancement in order to fulfill the dynamic understanding demanded
from students when they face real life complexities.
Innovative teachers and schools have made several efforts to improve the learning
process of history and to motivate students to learn more. Some professors have
encouraged their students to think about other ways of problem solving that could have
been used in the past to make historical happenings to occur differently. This
methodology has taken students into a deep analysis of the historical facts and made
them relate a piece of history to some other historical patterns (Burton, 2006). More
recently, informatics technologies have been introduced by some institutions as the
main tool to improve student’s learning about history. Digital History is a website
developed to support the teaching of American history in schools and colleges, which
intends to be innovative by presenting interactive learning modules where history is
taught as a part of the society, and visual effects are used to emphasize the important
issues in history (Mintz, 2003). However, there has been no assessment of the
performance of students using such methodologies.
The concept of multimedia learning, defined as acquiring knowledge in a domain
through interacting with an educational environment that presents information using
multiple sources, has also been applied to history in an attempt to improve the learning
process. Two main reasons support the use of the multimedia learning theory in history:
(1) Multiple-source environments attempt to make history learning more like the
activities of real historians, and (2) Graphics or archives are often used to make the
context of the time more engaging, vivid, or personally relevant for the learner. The
approach is based on a constructivist point of view, which proposes that learning that is
done as a form of inquiry leads to better understanding of the subject matter than
learning that is transmitted through lecture or memorization. In a history classroom with
this approach, rather than being simply told to believe a single story or learn what is in
the textbook, students are presented with information from a variety of sources and
perspectives, and taught the standards of historical inquiry, investigation and debate.
* Denise Pinette Domizi is the designer of the instruction “Constructing History: How historians see the
light” whose purpose is to help students examine their beliefs about history and to assess a conceptual
change for them to understand better this field (Pinette, 2002).
One of the most representative studies of the multimedia learning in history is the work
of Kathrin Spoehr, in which a corpus of high school hypermedia instructions (called
ACCESS —American Culture in Context: Enrichment for Secondary Schools) was
created to enhance student understanding by supplementing text book materials and
class instruction. Several assessments of learning outcomes show that this use of
multimedia was beneficial to students with ACCESS: Those students who were taught
with ACCESS outperformed those who were taught with the non-ACCESS class
instruction. However, those improvements cannot be entirely attributable to the impact
of multimedia learning on history because students in the ACCESS classroom profited
from the role played by the teachers who were accompanying the process in the
ACCESS classrooms, whose advance knowledge on the field could help students
intensify and maximize the construction of the hypermedia corpus. Thus, the only
conclusion that can be drawn from such experiment is that when multimedia learning is
used in problem-based inquiry tasks, with teachers who are involved in the construction
of a corpus and who think about the best ways to integrate the corpus into ongoing
instruction, then improvements in historical understanding can be obtained.
Furthermore, other studies on multimedia history instruction report pre/post test gains in
learning. However, those gains cannot address whether the multimedia environment is
better than learning from a text book or a lecture (Wiley & Ash, 2005). Thus,
advantages of the multimedia learning method over the Conventional teaching method
of history are not strongly conclusive so far.
However, even when some students and teachers find these methods as innovative and
useful, they have not been widely recognized as a Conventional method to teach history
(Forrester, 1992). In addition, despite these and other intentions to improve history
instruction, students who are taught by these methodologies are not involved in a real
thinking environment in which they can find out how history happened, what causes
change over time, how lessons of history could be interpreted to the present, and how
consequences of the historical happenings affect other matters along the years. Thus, it
is important to mention what Donovan and Bransford (2005) have proposed for making
history a useful and enjoyable discipline for students.
After several meetings with teachers, Donovan and Bransford concluded that history
cannot be learned unless it is presented to students in a general framework in which
some concepts inherent to it must be considered. Such concepts include: time taken for
the historical event to be developed, change in the state of affairs, causes that make the
change occur, empathy that leads to understand people’s ideas in the former times,
evidence of the historical situations which is important to be interpreted for the
understanding and learning of the discipline, and most important, what they called
accounts which looks for accumulating knowledge of history through the learning life
of students. Once students have been through such a learning process of history, they
find this subject as a discipline that really contributes to the understanding of the past,
the present and the future. Some short experiments were run with students of high
school and after being analyzed qualitatively, the author concluded that students do well
when history is conceived as a dynamic and interrelated discipline (Donovan &
Bransford, 2005). Given this perspective, history stops being perceived by students as a
mere recall of events and becomes a dynamic discipline that, even when it is based on
former happenings, its implications go through time. Thus, if there is an approach to
teach history, which can meet the tenets proposed by Donovan and Bransford, it would
be really helpful in broadening students’ understanding and motivation.
Rather than looking for media that eases the communication of the history, it is required
an approach that allows making real the learning methodology proposed by Donovan
and Bransford, which lets students understand why and how history occurred and
changed over time, and how those changes affected different fields and situations that
happened in the past. Furthermore, once such methodology is brought to life, historical
patterns must be able to be related to other situations that behave similarly, and thus,
students may be committed themselves to the society and all its complexities. Such
approach is described with this paper.
2. Using System Dynamics to teach History
2.1 Usefulness of SD as a teaching tool in social sciences and
History: looking over the evidence
From the definition of its founder’, System Dynamics (SD) is a perspective that
combines theory, methods and philosophy for analyzing the behavior of systems. In
such perspective, the world is understood as a whole, rather than as the result of isolated
pieces. Thus, SD shows how thing really change through time (Forrester 1998).
Complementary, SD is defined by John D. Sterman as “a perspective and set of
conceptual tools that enable us to understand the structure and dynamics of complex
systems. It is also a rigorous modeling method that enables us to build formal computer
simulations of complex systems and use them to design more effective policies and
organizations (Sterman 2000).
Thus, SD seems to be a promising methodology to meet the proposal done by Donovan
and Bransford (2005) given its nature of expressing relationships between different
elements, changes over time, and causes and effects related to past, present and future
happenings. SD provides as well the possibility of understanding history within a
certain context.
In the field of education, SD has been found as a useful tool to facilitate students’
performance*. The dynamic approach based on S&F and CLD provides a foundation
that is transferable from field to field, a basic that places the knowledge into a structured
pattern, which augments the learning and ability to transfer knowledge to other
happenings. There are several schools doing excellent work in this respect. Pioneering
schools are scattered mainly over the United States, extend into the Scandinavian
countries and Germany (Forrester, 1992; Skillings, 1997; Road Maps, 1992). Before
1992, no network has existed for interchanging information regarding SD among those
involved in pre-college education. Thus, the Creative Learning Exchange has been
founded in order to distribute SD materials among all those who are interested in it
(Creative Learning Exchange, 1992).
Road Maps is a series of self-study guides that use modeling exercises and selected
literature to provide a resource for learning about the principles and practices of SD;
cases studies are related to social sciences, biology, management (Road Maps, 1992).
* Jay Wright Forrester
* Besides education, SD has been even more widely used to approach management, urban, and
development problems, performing an important role due to its contribution for a better understanding
and improved policy making of these issues (Forrester 1992)
Roberts concluded that SD, as an organizing framework, can be a very useful tool to
teach and improve performance of fifth and sixth grade students, through the
implementation and evaluation of a curriculum to teach children about SD and its
application in many fields of study. Though the sample was small, the results seem
positive enough to warrant further experimentation with this strategy for teaching and
understanding problems (Roberts, 1978).
The Feedback Method is an SD approach to teach macroeconomics to college and high
school students. Assessment in this regard has revealed that students not only preferred
the explanations given by the SD approach, but also they perform better when they are
taught with it (Wheat, 2007).
In the field of History, Greg Reid has explored the causes of the American Civil War in
light of systemic thinking and SD tools. Instruction made of five one hour lessons given
to students, aimed to supply the students with an understanding of why the Civil War
took place, and that the war was not an isolated event that came out of the blue, but a
conflict that began brewing during the foundation of the country. Students were
encouraged to help the teacher complete causal loop and S&F diagrams that illustrated
the gradual increase in the main reasons of the civil war (Reid, 1996). Another case
study is the Easter Island population problem, which has been taught using S&F
diagrams by Diana Fisher as part of her curriculum. A population model has been
utilized to explain the reasons of the depletions of the population of this isolated island.
Concepts, such as the carrying capacity of the main resources, are introduced for
explaining the behavior over time of the population. Learning by doing is the
methodology followed by students. As they are taught about what happened in the
Island, they also model by themselves what they are taught. Policy making also makes
part of the case study, thus, students are encouraged to answer what would happen with
the population if more coconut palms were planted to support the nutrition of the island
(Fisher, 1992). Unfortunately, there is not available information about the way Fisher’s
and Reid’s lessons were assessed and how much they enhanced students’ understanding
regarding populations’ problems.
Doubtless, the most significant contribution to the use of SD in the history curriculum
has been done by Jeffrey Potash and John Heinbokel, who have adopted great interest in
using SD in the social sciences’ classroom. A conventional curriculum based on SD for
the teaching of social sciences and mainly human history became their main focus of
attention after they have realized that repeated patterns of behavior are present along
history, in which populations have shaped the course of human history because of
constraints given by the interaction with resources and human attitudes. Furthermore,
they believe that understanding how and why history has unfolded replete with
recurring patterns, will be determinant for the student’s motivation and to enable them
to learn from the past when thinking about the present and future (Potash 1995; Potash,
2005; Potash & Heinbokel, 2006).
Their first effort, entitled Plagues and People, commenced with a relatively simple
model of disease dissemination that drew upon historical epidemics to develop the
historical contexts within which these operated, and to better understand the current
AIDS epidemic in terms of cultural as well as biological factors. This model has been
tested with students in the form of a curricular practice, in which students were taught
gradually how to build and simulate models based on S&F diagrams. This methodology
led the students’ understanding of the case studies to be related to other facts over time,
and certainly, to the context in which they were developed (Potash et al, 1996). Later
on, Population Dynamics and the Human Experience, is doubtless their most exciting
and ambitious project of all. They identify myriad structures which influence how,
where, and why human populations have grown over the course of history; and then
look at the role of human population growth as it has affected economic, political, and
social systems, past and present (Potash, 2005). Correspondingly, Heinbokel and Potash
with the Center for Interdisciplinary Excellence in SD (previously the Waters Center for
System Dynamics) have designed Demo Dozen, a collection of 12 interactive lessons”
about American history, bacteria reproduction, finances, which are accompanied with
dynamic models (CIESD, 2001; Waters Center for System Dynamics, 2001). One of the
most famous case studies taught with Demo Dozen is the Irish Potato Famine. Beyond
the conventional causes found for this happening, they explain using S&F diagrams and
time series graphs, how and why this happening is related to past and future happenings
such as the great depletion of the Irish population even several years after the famine.
Thus, a stock representing the Irish population at any time is increased by the birth rate
and the death rate in Ireland. The most interesting point of their approach is the
consideration of the available resources, and the attitudes and expectations of the people
towards believing about getting welfare in Ireland. These factors become the most
determinant factors for population loss in Ireland in the period 1846-1900, even after
the famine (Potash & Heinbokel, 2006).
After a while of exploring in the history classroom, Potash and Heinbokel state that
passing from the learning of discrete events regarding the social sciences to the
understanding of patterns as part of a whole, is a process which is really enhanced by
using generic SD concepts and tools. Furthermore, they strongly believe that “When
students develop the capacity for and the interest in understanding the powerful role of
dynamic feedbacks between populations, resources, and attitudes in the past and, more
critically, when they can see the relevance of that learning when applied to their own
world, we will have truly made progress in our efforts to bring social studies to the level
of creating systems citizens” (Potash, 2005; Potash & Heinbokel, 2006).
Nevertheless, assessment is absent in all the practices employed by those who have
intended to approach history by using SD, even in the most important contribution made
by Potash and Heinbokel. Despite all of them highlight the fact that students benefit
from using SD as a teaching tool, none of them has evaluated how much benefit those
students get. Controlled experiments, in which it is possible to measure how much
enhancement and improvement the students profit from an SD approach, is still missing
and is calling for answers. In the intent of recognizing SD as a generic tool to teach
different fields, scientific assessment is widely required.
2.2 SD for teaching revolutions
2.2.1 Revolutions as diseases
Revolutions are among the most often repeated happenings in history. They describe
more or less similar patterns of behavior, which come from similar structures or
° Such collection of interactive lessons is called Demo Dozen, which is available at
http://www.ciesd.org/influence/demo_dozen.shtml
relationships between elements. Thus, revolutions result an interesting case to approach
history.
Crane Brinton (1965) analyzes and compares the development over time of different
revolutionary processes such as the American Revolution, the French Revolution, the
English Revolution and the Russian Revolution too. He finds out that all of them share
common patterns that made them unfold in the way they did. He describes such patterns
through the analogy of the development of a fever over time, in which three stages are
present most of the time: the symptoms, the fever itself, and the breakdown. The
symptoms represent the dissatisfaction of a current state versus a desired state; the fever
itself represents the development of the revolution over time; and the breakdown
represents the loss of morale by those who support the revolution, and therefore this
stage describes the revolution’s end (Brinton, 1965). Among all stages, the fever itself
exhibits the core point that determines the course of revolution; therefore, the process of
understanding how a revolution gains and looses power is essential for the students to
manage and interpret similar situations in the past, present, and the future.
Specifically, as Brinton (1965) states, the fever itself goes through different stages.
Likewise, once the revolution has started, it experiences different phases in which its
popularity and support of the people varies over time.
The full symptoms disclose themselves and the fever of the revolution has then begun.
After a hard beginning because of constructing reliability on the revolution, the fever of
the revolution faces a period of great popularity. The revolution then works up, not
regularly but with advances and retreats, to a crisis, frequently accompanied by
delirium, the rule of most violent revolutions: reigns of terror. Specifically, the
revolution gains great support, in which several chaotic happenings occur for a while
until the first and main event occurred: the breakdown of the often oppressor
government is reached (Brinton 1965). From the revolutions analyzed by Brinton
(1965), in the specific case of the French Revolution, million of conversations between
the French population spread the fear that the king and his party were about to dismiss
the revolutionary assembly and rule by armed force. The revolution started to gain even
more power. Paris and other French towns, therefore, rose in its might and with a sure
instinct did impressive revolutionary facts such as the seizing on the Bastille. The
revolutionaries stirred up France in a hundred ways: they sent orators to street corners
and cafes, they distributed radical news-sheets and pamphlets, they sent agents to spread
discontent among the royal troops, and they even subsidized prostitutes to get at the
soldiers more effectively. People joined the Revolution because their neighbors already
did it. A strong motivation to diffuse the fever of the revolution is revealed in events
like these presented in France.
Once the revolutionaries have gained what they wanted, they wish to stay in power.
New ways of government arise and a revolution is still on against those who do not
support it. Until the moment, a process of strengthening the revolution through more
support is essential to keep the power. In the meantime of these events, the incipient
government lacks ability to meet the interests of all those who had hopes in the
revolution, and this is the cause for stronger and radical supporters of the revolution to
take over the power and start reigning. In this moment, radical and lunatic events start
happening such as the terror reigns, in which many people are killed at a search of
virtue of the revolution (Brinton, 1965). The revolutions analyzed by Brinton (1965)
showed to be very successful in the first stage. They became actual revolutions instead
of mere discussions and desires, especially after revolutionaries have beaten, or won
over, the armed forces of the revolution.
Crane Brinton (1965) also states that in social systems, as in the human organism, a
kind of natural healing force tends almost automatically to balance one kind of change
with another and restorative change. Thus, social systems such as revolutions seek
themselves for the balance, in order to gain equilibrium after a period of crisis and
disorder. Once the revolution has gained power, its natural trend is to recover a state of
equilibrium, in which the population feels satisfied with it. Tranquility is claimed by the
population and so the revolution itself starts losing power. The equilibrium is then
restored and the revolution is over. In all four revolutions analyzed by Brinton (1965)
the crisis period was followed by a convalescence, by a return to a fundamental desire
of calm (Brinton, 1965).
Thus, the fever itself of a revolution should be taught using an approach, such as SD,
that describes the dynamics of revolutions rather than mere discrete events that
happened.
2.2.2 Useful SD concepts for teaching revolutions
The description of the fever itself as stated by Brinton (1965) presents two main
processes that reveal dynamics and diffusion of the passion of revolution. On one hand,
the gain of strength of the revolution and all the critical happenings occurring alongside
are the result of a reinforcing process, in which the desire of revolution is increasingly
supported by the population. The spread or diffusion of such desire of revolution is
given by the several conversations, news-pamphlets, orators, and different strategies
adopted by the revolutionary parties. The diffusion process amplifies and reinforces the
popularity of revolution among people. In SD terms, this process is given by a
reinforcing loop describing an exponential growth. On the other hand, there is a process
of seeking balance to restore calm among population. This process is then given by a
balancing loop, in which a goal seeking behavior proceeded by a collapse describes the
way the population lose interest in the revolution and tranquility is recovered.
Thus, in terms of SD, the fever itself of a revolution is analogous to a diffusion proces
given by a generic SD structure called the SI Model or Diffusion Model. This model is
simplification of diseases, which represents the spread of a disease within a population
over time.
In the model, the total population of a region or community is divided into two
categories: those susceptible to the disease, S, and those who are infectious, I, (for this
reason the model is known as SI model). As people are infected they move from the
susceptible category to the infectious category. The SI model is the simplest model of
spread of epidemics and is based on the assumptions of not taking into account births,
deaths, and migrations. Furthermore, it has to do with chronic infections in which once
people are infected, they remain infectious indefinitely®. The SI model contains two
° Due to the simplicity of the ST model, extensions of it have been made, in which recoveries from the ill
state and deaths are pi le. Therefore, the stock of infectious population is decreased at the last stage. In
the way revolutions are approached for the present experiment, both, the simple SI model and the
loops, the positive Contagion loop and the negative Depletion Loop. Infectious diseases
spread as those who are infectious come into contact with and pass the disease to those
who are susceptible, increasing the infectious population still further (the positive loop
is dominating) while at the same time depleting the pool of susceptible (the negative
loop). Both categories of population, Susceptible and Infectious are represented by
stocks in the SD nomenclature, while the rate at which the population gets infected and
migrate from susceptible to infectious is considered a flow. The infectious population
exhibits s-shaped growth, in which after great difficulty of infecting new people at the
beginning of the disease, new cases of infection rise exponentially the stock, which later
on keeps constant as there are no new cases of infection.
Three more constant variables make part of the model: the probability of infecting a
susceptible person when is contacted by infectious people, monthly contacts per
infectious, and total population.
As follows the S&F diagram of the SI model is presented with its corresponding graph
of behavior over time.
Probability of infecting a
SUSCEPTIBLE person when is
contacted by INFECTIOUS =
people
Monthly contacts Total Population a
>
per Infected 3,
5
ir
ot
=
SUSCEPTIBLE INFECTIOUS S
Becoming Infected
ty 5 10
Figure 12. S&F diagram and behavior over time of diseases
From this perspective this model becomes very useful to teaching about the
revolutionary process in history.
2.3 In-service Training: the outset of infecting with the SD
approach
At each school in which the history experiment was run, a three hour in-service training
with teachers was done in order to share the basics of SD and the core meaning of SD
with which history would be explained to students in the SD groups. The teachers were
taken into some theory about SD through a verbal presentation (with power point
presentation as an aid), then were encouraged to play the Infection Game’ and finally,
the presentation of the Diffusion Model was used to debrief the game and transmit the
understanding of situations which are spread as diseases do.
considerations about deaths are taken into account. Further information about the Diffusion Model (with
all its extensions) is available in Business Dynamics, Chapter 9 (Sterman, 2000)
” The Infection Game is adapted from The Epidemic Game by Hill Glass at the catalina Foothills School
District, Tucson, Arizona, 1993.
10
Main concepts of SD such as accumulation, multiple influences, feedback loops, non
proportionality, and delays were taught to teachers through the explanation of the
bathtub analogy. The teachers did not have previous knowledge or experience in SD;
thus, in order to let them understand those new concepts, the Infection Game was
played and immediately debriefed in an active plenary session. At this point, the
Diffusion model was presented as the core model that leads to the understanding of how
the disease was spread among all the members of the group, and how the number of
people who was infected every day changed over time. The diffusion model played an
important role because it led teachers to understand from which perspective the history
instructional method will be approached when being taught to the students. Figure 13
illustrates the way the Infection game was debriefed using the SI as approach during the
in-service session.
The Infection Game:
Stocks and Flows
The INFECTED people appear through NEW
INFECTIONS. When a SUSCEPTIBLE is infected
he becomes into an INFECTED.
SUSCEPTIBLE ( ) INFECTED
New_laféctions
SUSCEPTIBLE-<«——New Inieetions. INFECTED
Figure 13. Slide # 8 Infection Game debriefing during the In-Service training
Interest and enthusiasm were the main reactions of teachers during and after the in-
service training session. At first, their attention was focused on learning about how to
improve education in K-12 and how to make the students more interested in it; but
while taking them into the entire in-service session they could see the kind of generic
applications that this tool can have on different fields, and thus, teachers got enthusiastic
and really interested in learning how to apply such approach.
Concepts such as accumulation, flows and feedback loops were difficult for them to
grasp. However, the idea of approaching different fields (such as diseases and history)
from a systemic point of view was challenging and encouraging enough to make them
ask further questions and to keep interest in the session. The queries were mainly about
the previous applications of SD in the education field, their results in the understanding
and interest of the students, and about the advantages of using this tool instead of using
a conventional teaching method. Furthermore, the most eager ones were interested in
knowing how to apply it in examples of physics, biology and informatics that make
trouble to the students.
This session was really important because it revealed how relevant the improvement of
education and the need that teachers have to approximate to the best approach for
teaching K-12 students. It was revealed a strong need to enhance the understanding of
students in both, the soft and hard sciences.
11
Because of all stated in this section, it may be thought of SD as a better approach to help
students understand history within the context in which it occurred and to interpret it in
light of the present life and possible futures. Specifically, it may lead students’
understanding into why and how history occurred and changed over time, and how
those changes affected future situations and different fields. Furthermore, generic
structures of SD, such as the SI model, that can be applied to different fields of study,
allow relating historical happenings that behave similarly, and thus, students may be
committed themselves to the society and all its complexities. Thus, this study aims to
answer this research question:
Does SD enhance students’ understanding of history as a disciplinary approach?
Exploring whether students’ understanding of history is enhanced when the students
either have or do not have previous knowledge of SD is highly interesting to determine
the role of that teaching method in the learning process of history. Assessment of the
impact of the SD teaching method on students’ performance is aimed to be provided to
validate the contribution of SD in students’ understanding of history.
3. Experimental Design
3.1. The Research Method
The chosen method of research is a laboratory experiment in which actual history
classrooms constitute the “laboratory”. Different instructional treatments were applied
to different groups of students in order to compare their performance.
The Teaching Method and the Experimental Experiences were the two treatments
applied to the groups of study. The Teaching Method treatment concerns the method
used to teach history to the students, and it is made of two levels, the Conventional
method and the System Dynamics method. The Experimental Experience treatment
concerns students’ previous experience in experiments using the teaching method
assigned to them. Those without prior experience represented the First Experimental
Experience, while those who participated in the Civics’ Engagement Experiment by
Maria Teresa Gonzalez® represented the Second Experimental Experience.
These treatments definitions lead to the following experimental design, in which four
different groups were taught with different teaching methods and must go through
different experimental experiences.
|____ Teaching Method
SD Method_| Conventional Method
| First Experimental
Experimental Experience $D1 group | CONTROLt group
Experiences | Second Experimental
Experience SD2 group | CONTROL2 group
Table 1. Treatments
* Further information about the Civics’ Engagement Experiment is available by contacting its author.
Email address: maria.galvis@student.uib.no or at www.clexchange.com/ftp/newsletter/CLEx16.1.pdf
12
The Conventional teaching method is the traditional way of teaching history in a
Colombian classroom. This typically involves reading passages about the development
of a historical process based on the presentation of isolated events, reading about the
biography of the main characters in history, presentation of pictures, and timelines.
Additionally, graphs over time accompanied the explanation of the development over
time of the historical case study. Such graphs are not often used as a tool to teach
history, but certainly could be added to the Conventional curriculum. By using the time
series graphs in both teaching methods leaves the SD concepts as the only difference
between both teaching methods. The SD teaching method provided the students with the
same information as the Conventional teaching method; however, SD tools (stocks,
flows, S&F diagrams, and SI model) were used to approach the case study from a SD
point of view. Thus, both system thinking and S&F diagrams in the SD method were the
main difference presented in the teaching methods. The Conventional method presented
isolated historical events, while the SD Method presented connections and a structure
underlying the happenings of such events. Both teaching methods were presented to the
students in computerized slideshow format.
In the First Experimental Experience, students studied a history case study using either
SD or the Conventional method. Students in the Second Experimental Experience
approached the same history case study, and in addition, a Civics’ case study, using in
both experiments the same teaching method (either SD or the Conventional method).
Thus, more than one field of study was approached with the teaching method.
3.2 Students’ Task
Table 2 summarizes the way the teaching method was presented to each group,
according to what was said above. Differences in the presentation of the teaching
method between groups are expected to make their performance discern.
3.3 Teaching Method: French Revolution
As previously mentioned in the section 2, given the analogy between the development
of fevers and revolutions over time presented by Crane Brinton (Brinton, 1965), the
course of a revolution can be taught by using the concept of “infection” of the desire of
revolution within a certain population. A person who makes part of the revolution is the
infectious one who can transmit the desire of revolution (the disease) among people.
Infecting other people to join the revolution is not an easy task at the beginning and it
takes some time until people starts getting infected by such purpose. However, once
there are more revolution’s supporters (more infectious), the desire of joining the
revolution starts to increase and to become popular among the people (contagion loop).
After a while, there are few non-revolutionaries to who transmit the passion for the
revolution, thus the number of people supporting the revolution does not increase
anymore, and this can either remain constant or collapse. In figure 14, the behavior of
an infectious population and a revolutionary population are presented to reflect at some
extent their analogy in their behavior as stated by Crane Brinton (1965)"°.
° The Civics Engagement Experiment was run a day before the students in the Second Experimental
Experience went through the history experiment.
figure 14, both behaviors represent at some extent the behavior of both populations over time.
However, such behaviors can differ, especially at the late phase, because of the deaths or other factors
that decrease the number of people in both populations. Furthermore, it is important to be aware that not
13
-Teaching Method: SD
-Teaching Method:
Conventional
ups
-Teaching Method: SD
-Teaching Method:
Conventional
-Experimental Experience:
First
First
-Experimental Experience:
-Experimental Experience:
Second
-Experimental
Experience: Second
-Pre test (one week in
advance)
-Pre test (one week in
advance)
-Pre test (one week in
advance)
-Pre test (one week in
advance)
-Verbal instruction about SD
principles and the Infection
Game. Duration: 3 hours
-Verbal instruction about SD
principles and the Infection
Game. Duration: 3 hours
-Computerized slideshow
about the French Revolution,
using SD as approach.
Duration: 2 hours
- Computerized slideshow
about the French
Revolution, approached
with a Conventional
method. Duration: 1 hour
-Computerized slideshow
about Civies, using SD as
approach. Duration: 2 hours
- Computerized slideshow
about Civics, approached
with a Conventional
method. Duration: 1 hour
- Computerized slideshow
about the French
Revolution, using SD as
approach. Duration: 2 hours
- Computerized slideshow
about the French
Revolution, approached
with a Conventional
method. Duration: 1 hour
-Post Test -Post Test -Post Test -Post Test
Table 2. Tasks per group
26. B.
rf
a 20. e 20-
a Zz
o 15 o 15.
5 =
1S io. 2 10.
= g
5 we 5
o 6 10 15 0 6 10 16
Time Time
Figure 14. Behavior of revolutions as diseases.
With the purpose of clarifying this concept to the students who are learning history in
this experiment, the French Revolution has been chosen as the case study. Thus, the
generality of the development over time of the revolution can be transferred to the
French Revolution, and the SI model can be utilized to explain students in the SD
groups how the revolution changed over time in light of those persons supporting it. For
those students involved in the Conventional method, the focus is on the changes that the
revolution suffered over time.
The Conventional instructional method approaches the instructional goal by using
readings, passages, pictures, presentation of isolated events regarding the French
revolution, and presentation of graphs about the number of revolutionaries supporting
the revolution. However, the SD relies on system thinking and S&F diagrams. In the SD
instructional method, the case study utilized the SI model, explained in section 2.
every revolution behaves in the same way. Revolutions studied by Brinton (1965) are alike in this sense;
however, other kind of revolutions may totally differ from the disease analogy.
14
3.3.1 SD approach of the French Revolution
Revolutions describe aped growth in which the number of people joining a
revolution changes according to the dominance of a reinforcing (strengthening) loop or
of a balancing (weakening) loop. The strengthening loop is analogous to the contagion
loop in the SI model and the balancing loop is analogous to the depletion loop. The
groups of revolutionary and non-revolutionary people can be thought as stocks. At the
same time, the people joining the revolution can be interpreted as a flow, which
decreases the non-revolutionary stock and increases the revolutionary stock.
At the beginning of the French Revolution, the strengthening loop takes a while until
people star believing in the usefulness of joining the revolution. So, the stock of
revolutionaries starts accumulating people who make part of the revolution. New
supporters of the revolution might want to involve more people in the revolution. Thus,
the contagion loop starts to dominate and to convince many people to join the French
Revolution. At this point the stock has started to grow exponentially and the revolution
has become quite popular between the French people. However, once the revolution has
gained popularity and gained lots of supporters, fewer people are susceptible to become
revolutionary. Thus, the stock of revolutionary people stops to increase in that
accelerating way, and begins to seek balance. The depletion loop takes dominance at
this moment, and slowly all those who were not part of the revolution join it as well.
The stock still accumulates revolutionary people, but the accumulation occurs slowly
now because conversions from non-revolutionaries to the revolutionary party do not
occur that often. When there is no more susceptible population to convince of joining
the revolution, the stock stops to increase and reaches stability. The depletion loop has
balanced the contagion loop and the French Revolution does not last forever.
Thus, the French revolution is suitable to be approached with the SI model mentioned in
section 2. The first approximation to the French Revolution with the SI model considers
the simplest SI model, without deaths of revolutionaries and returns to the non-
revolutionary state are not considered. At this point the stock of revolutionary people
behaves as shown in figure 14. In the last parts of the instructional method, the
extension regarding the dead revolutionaries is included in the model for enhancing
students’ understanding of such system",
" This extension of the SI model is called SIR model, where S$ and I are still the Susceptible population to
get infected and the Infectious population correspondingly, and R is the Recovered population from the
disease. This case treats the diseases which are not chronic, such as the flu, in which the population gets
recovered from the disease after some time (Sterman, 2000).
15
Probability ofinfecting a Probability of convincing a Noa
Sueceptible persoa when is Revohttionary whenis contacted
contacted by Infectious people by a Revolstionary
‘Monthly contacts Total Population ‘Monthly contacts per Population
per lefocticus Revolutionary
SUSCEPTIBLE INFECTIOUS SOL WARE REVOLUTION ARIES
Becoming
Becoming Infected Revelutionares
v
Figure 15. S&F of revolutions as diseases
Thus, the model, initially made of two stocks, one flow, two feedback loops, and three
parameters was used to explain the dynamics of the French Revolution over time,
considering its difficult beginning, its peak, its slow down, and its later stability. The
understanding of the flow of people from being non revolutionaries to become
revolutionaries is highly decisive of the dynamics associated to revolutions. This same
structure gives rise to the s-shaped behavior of a disease. Enhancing the understanding
and reality of the model is intended to be done by adding in the model a stock of dead
revolutionaries, which die at a certain rate over time. The assumption is that certain
amount of revolutionaries dies as a result of the violence of revolutions. The third stock
accumulates the number of dead revolutionaries and is fed by a negative feedback loop,
the deaths loop. Revolutionaries dying in the French revolution increase such stock and
decrease the Revolutionaries stock. The greater the number of revolutionari , the
greater the death rate is, and the smaller the number of remaining alive revolutionaries
is (Sterman, 2000). Figure 16 shows the full S&F diagram, in which the dead
revolutionaries are considered.
Because of the effect of the deaths loop, the stock of Revolutionaries after the
dominance of the depletion loop is decreased. At this point, the number of
revolutionaries dying per month is greater than the number of non-revolutionaries
becoming revolutionaries. Thus, the characteristic s-shape growth in the simple SI
model collapses when the dead revolutionaries are taken into account. Figure 17
presents a representative behavior of the stock of revolutionaries (infectious) with the SI
model considering deaths (recoveries).
Revolutionary when is contacted
by a Revolutionary
Monthly contacts per Population
Revolutionary Death Rate.
BON: REVOLUTIONARIES DEAD
REVOLUTIONARIES Monty Death REVOLUTIONARIES.
Becoming ;
a a Se
Figure 16. S&F Revolutions
16
Revolutionaries
Pate}
5a 8
0 5 10
Time
Figure 17. Behavior of revolutions according to the SIR model
3.4 Test Instrument
As history teaching has been oriented to the memorization rather than to the
understanding of relationships that made history to occur in a certain way, there are no
previous elaborated tests useful to assess students’ performance regarding revolutions
and their dynamics. Thus, the test used to measure students’ performance has been self
designed by the author. Rather than recalling knowledge regarding the French
revolution, the test intended to measure the general understanding of revolutions, based
on their dynamics (change over time and the relationships that give rise to that change)
and the transferability of such understanding to other happenings. Transfer tests require
that the learner applies what was learned to a novel situation. The characteristic that
distinguishes someone who learns by understanding from someone who learns by rote is
the ability to transfer knowledge (Mayer, 1999). Thus, the understanding of the case
study was required to be transferred along all the questions of the test, due to the
questions encouraged the students to apply the understanding of the relationships
underlying and explaining the dynamics of revolutions.
The test was made of 14 multiple choice questions which are presented in Table 3. The
questions were classified in three types according to their main measurement purpose’”.
The transferability of the structure underlying the development of the revolutionary
population among the French revolution was one of the tasks that students should face
most often in the test. These questions were presented in the form of analogies between
the case study and other historical happenings, and in the form of questions asking for
correct explanations of why certain happenings occurred during revolutions. Questions
number 1, 5, 6, 7, and 8 belong to this type of question. This type of question was
relevant because it tested the understanding of different relationships between the
elements that caused a revolutionary population to develop in a certain way.
Furthermore, these questions reveal whether a student is able to associate the
understanding of the case study to another topic that may come from similar structural
patterns.
A second set of questions had the purpose of measuring the understanding of the
behavior of revolutions over time and the application to such knowledge to new
2 Question number 2 was not included within the groups because its objective was not intended to
measure knowledge nor learning process but to test students’ ability to interpret graphs in the pre test
because the instructional methods were based on several graphs.
17
situations. This type of question was presented in the form of analogies with other fields
of study and of graphs recalling possible development over time of the populations of
the revolutions. The importance of this set of questions is the possibility of measuring
whether or not a student is able to associate the general behavior of revolutions with
another situation that may unfold in the same way than revolutions over time. Questions
number 3 and 4 belong to this group.
The last questions intended to measure the application of the understanding not only of
the structure underlying the French revolution development, but also the understanding
of the behavior over time of the populations involved in such revolution. These
questions are the “what would have happened if...” type, referring to forecasting and
thinking about hypothetical scenarios based on the understanding of the structure and
the behaviors underlying the case study. Questions 9-14 belong to this type of questions.
All set of questions required different cognitive skills. Questions in the groups of
behavior and structure may be easier answered by students than what the last group of
questions can be. In the structure based questions the main requirement had to do with
identifying constituent parts and functions of a concept. In the behavior questions it was
demanded the identification and relation between parts and function of a process. While
the last group of questions had to do with making an assessment of elements,
relationships, values and effects. The latter process shows a more difficult process for
the students to perform correctly.
Even though the aim of each question is to measure different levels of understanding of
revolutions, there is still chance for the students to answer them properly without having
the expected understanding required for the question.
The test was applied as pre test and post test, thus results due to the treatments’
application may be compared.
3.5 Measures of Performance
Both treatments, the teaching method and the experimental experiences, represent the
independent variables of this experiment in that they are controlled by the experimenter.
The application of these variables determined the students’ performance, in other words,
the dependent variables. The dependent variables are the response variables, which are
given by the performance of the students in both tests after receiving the different
treatments.
Assessment of students’ performance has been done by two different measures:
Students who improved per group (SWI), and Effective Improvement (EI). The first
measure talks about how wide the effect of the treatment was on the students and
excludes the amount of improvement per student. The second measure shows how much
improvement of the maximum gain'* based on the pre test scores is reached by the
students. In this measure, not only the amount of improvement is considered per
student, but also such improvement is contrasted with student’s learning potential. The
benchmark to be reached by the students is an EI that equals the learning potential.
Maximum possible gain is defined as Learning Potential = (100-Correct Answers % in the Pre test)
18
Question a. b. c. d.
; . . The prohibition by the state of
1. What makes a Revolution to gain The meetings offered by | [7p iat avec ib become yaaa)
strength in a group of people? Revolutionaries part of the Revolution
2. Take a look to the following graph:
Once the Non
The number of Non Revolutionaries start to Th aN
i Revolucionaries does not_ | decrease, the depletion of the |p, salience ‘ eee hot
| decrease significantly in the | group occurs very fast until it Gecrnee
‘ early years stops decreasing and remain
rr a a a a id ina fix level
Which one of the following statements.
describes what is shown by the graph?
3. Which of the following graphs describes 2 i ae 2 ,
best the number of Revolutionaries H : i i:
supporting the Revolution along its be L i 7
duration? 1 ‘on Se ees TF “| to
4. Which of the following sentences is more | 9 the speedused bya The interest accumulation in
similar to the development of a Revolution
ever ima? rocket to fly to the space
5. Which pair of elements presented at each
possible answer (a. to d.) is more similar to
the relationship of the people joining the
revolution and the number of people who
don't support it?
6. The relationship between “the people
joining annually the Revolution” and “those
who are part of the revolutionary group” is
similar to:
bank account
The relationship between the | The relationship between the
ne rela le who go to the stadium
uice filling a glass and the | P°0P! ;
Flovel af fabs in the glass | andthe soccer players in the
team
a) and b)
a) and c)
The relationship between the
peasant people who migrated
to the cities after the
The relationship between the
people who annually were
killed in the guillotine during
the French Revolution and
the number of people who
supported the French
Revolution
Industrial Revolution and the
people who lived in the
countryside before the
Industrial Revolution
None of them
Table 3. Test Instrument
19
7. The relationship between “the possibility
of convincing people of joining the
Revolution” and “the number of people
annually joining the Revolution” is similar to:
The relationship between the
number of the Spanish
conquistadores in America
and the number of native
people who died during the
conquest of America
The relationship between the
probability of being a country
liberated by Simon Bolivar
and average lifetime of Simon
Bolivar
8. The relationship between “the number of
Non revolutionaries in a revolution” and the
“number of revolutionaries in a revolution” is
similar to:
None of them
The relationship between
people purchasing new
products in the market and
the quality of the new
products
The relationship between
people infected with HIV and
the babies that annually are
born with HIV
9. Which of the following strategies might be
applied by a Governor in order to stop a
revolution and thus, to avoid the negative
effects of it:
To isolate the Revolutionaries
from the Non Revolutionaries
To declare the Revolution as
To keep the people satisly illegal
10. What would happen if a Governor, with
the attempt of stopping a Revolution, tries to
arrest all those who look suspicious of
making part of the revolution?
The revolutionaries would
reject those who might want
to belong to the revolutionary
party.
All those who do not support
the Revolution yet would
follow the rules of the
Governor
11. Which of the following strategies could
be applied by a Governor in order to delay
the development of a Revolution?
To keep quiet about the
actions of the Revolution for
not altering it
To kill some of the
revolutionaries
If the Governor of a country, which faces a Revolution, decides to grant one time some rights and privileges as citizens to those who do not want to join the Revolution, how
b) and c)
a) and b)
b) and c)
In order to answer the following questions, please read the coming paragraph:
would it affect the following items?
12. The number of revolutionaries
supporting the Revolution:
The Revolutionary party is
not radically affected by such
policy
Less people would be willing
to join the Revolution
People would take longer to
decide joining the Revolution
13. The number of dead bodies during the
Revolution
Every year, there would be
less dead bodies than the
previous year.
The number of dead bodies
would be the same
14. The development of the Revolution
along the time would be:
The same
d. a) and b)
Does not have anything to do
with the policy
Table 3. Test Instrument
20
Total Students per group with improved scores in
Students who Improved (SW!) the Post Test / Total number of students per group
-If Total Score Post Test > Total Score Pre Test:
(Correct Answers% Post Test-Correct Answers %
- Pre Test) / (100- Correct Answers % in the Pre test)
Effective Improvement (El)
-If Total Score Post Test < Total Score Pre Test:
(Correct Answers% Post Test-Correct Answers %
Pre Test) / Correct Answers % Pre test
Table 4. Measures used to calculate improvement in the performance of students
These two measures of performance have been used in both the full test and the groups
of questions defined in the previous section. Measuring students’ improvement in the
full test leads to have an overview of their general performance, while knowing how
their performance was along the groups of questions reveals were such improvement is
located. Strengths of SD and CONTROL groups in the understanding of revolutions can
be identified through the analysis per group of questions.
The benchmark in the performance per group of questions is given by consistent
improvement in the three groups. When students improved only in one group of
questions, the performance is not considered as a better one. However, if they show
better performance in all groups of questions their improvement turns consistent and
reveals that there was less likelihood of answering the questions by guessing. Thus,
knowing the importance of the questions, in which students improved, provides a
complementary tool to determine whether or not SD groups had better performance than
the CONTROL groups.
Even though all questions demand certain knowledge of SD, it is straightforward to all
students to answer correctly questions 5-7, 1, 8, and 3 after either the CONTROL or SD
instructional methods were presented, though SD groups are more skilled to answer
them more correctly. However, questions 4 and 9-14 are more demanding even to the
students who went through the SD treatments due to understanding of dynamics of
revolutions is required.
Besides the independent variables, some uncontrollable and immeasurable ones
influenced as well students’ performance during the experiment. The main nuisances
were the finalization of the scholar year at the same time than the experiments’
application, and the cognitive training some students had during the first semester of
2006 to pass the final examination for graduating. Regarding the first one, students from
all grades in the school were experiencing high load of tasks and exams to be done in
order to finish the year properly. Some students had more exams than others because
they did not present them on time. Therefore, to diminish the effect of this nuisance, the
students for the experiment were picked from the bunch of students who did not have
such great pressure and stress as those who had exams left. This helped to have on
average the same level of stress and cognitive load on the students. Regarding the latter
nuisance, not much was to be done to diminish its effect, due to absence of chances
given by the school to mix those students, who received training for specific exams,
with the rest of the students who did not receive any training of this kind.
Emotional and social differences in students had a diffusion effect (nuisance) on their
performance in the experiment, which unfortunately were not susceptible to be
controlled somehow by the design itself.
3.6 Hypotheses
The following hypotheses are intended to test whether SD is a better method to enhance
understanding of history as a disciplinary approach. Both perspectives from which the
research question is approached, students with and without previous SD knowledge,
will be tested by making use of such hypotheses as well. Hence, there are two sub-sets
of hypotheses, which will use the measures of performance to be tested and give answer
to the research question.
Hypotheses 1: Regarding groups with different teaching method'* and the same
experimental experience! 2
SIW Null Hypothesis: There is no significant difference in the SWI of groups who
were taught with different teaching method but attended the same experimental
experience.
Ho, SWE SWI sD1= SWI CONTROLI
Hoswr SWI sp2= SWI CONTROL2
EI Null Hypothesis: There is no significant difference in the EI of groups who were
taught with different teaching method but attended the same experimental experience.
Ho, er: El spi= El conrrowi
Hozr: El sp2= EI conrror2
Hypothesis 2: Regarding groups with the same teaching method and different
experimental experience
SIW Null Hypothesis: There is no significant difference in the SWI of groups who
took the same teaching method but attended different experimental experience.
Ho, swi! SWI sp1= SWI sp2
Hows: SWI conrroi1 = SWI conrroi2
EI Hypothesis: There is no significant difference in the EI of the students who took the
same teaching method but attended different experimental experiences.
Ho, ex: El sp1 = El spa
Hor EI conrroti = El conrror2
'4 Bither the Conventional or SD teaching method
'S Bither the First Experimental Experience or the Second Experimental Experience
22
All hypotheses will be tested using a two-tailed test with a level of significance equal to
0.05.
3.7 Sample Selection Process and characteristics of the
sample
The experiments were run in the Fray Rafael de la Serna School in the city of Medellin,
Colombia, during the first two weeks of November, 2006. In Colombia the scholar year
goes from late January until late November. Thus, the time of the year in which the
experiments were done was crucial in determining the availability of the students who
could be subjects under study. During the last month of school, all students are required
to take final exams, and for those students, who did not perform excellent along the
year, several assignments are required to be handed in as well. Therefore, students who
did well the whole year were under less pressure than those who had to repeat some
tasks in which they did not do well.
According to this, the Principal of the school decided to provide the students required
for the experiment, from those students who only had to present exams and few
assignments left. Students made part of 8", 9", 10" and 11" grades'®, whose age ranged
between 15 and 17 years. Thus, 30 students were assigned to each group. Table 5
describes the characteristics of the sample size per group.
Characteristics ‘spt CONTROL1 D2 CONTROL2
Sample Size 30 30 30 30
-8 Students from 9th -10 Students from 8th -5 Students from 9th -4 Students from 8th
grade grade grade grade
-22 Students from 10th -20 Students from 11th -25 Students from 10th -26 Students from 11th
Students in Grades
grade grade grade grade
Students’ Age 15-17 years old 18-17 years old 1-17 years old 18-17 years old
Female Population 0% 13% 0% 13%
Students repeating the oa aah ag oe
grade
Day:Tims tor the Morning Afternoon Morning Afternoon
‘experiment
Grades In Social Outstanding Outstanding Outstanding Outstanding
Sciences
Table 5. Categories according to the type of question
Since it was not possible to elaborate a full random process to select the students, one of
the factors that helped determining certain homogeneity in the initial conditions of all
groups was the grades of the students in the field of Social Sciences and History. The
grades of the students per group were averaged out and then compared. All four groups
had an average grade of “O-Outstanding (above average)” in such subject, thus,
despite all the differences between groups, they shared certain homogeneity and equal
initial conditions to perform the experiment.
'© In the school each grade had two different groups: the 11th grade had group 1 and group 2. Likewise
for the 10", 9", and 8" grade.
‘7 All four groups presented in average a grade of “Outstanding (above average)” among a qualitative
scale in which the highest grade is E= excellent, followed by O= Outstanding, A= Acceptable, D=
deficient, and I= insufficient.
23
Another important factor to be mentioned is the discipline and attitude of the students
towards learning activities. Three of the four groups presented similar behavior
regarding the attention paid and the attitude to perform those scholar demanding tasks.
SD1, CONTROLI and CONTROL2 groups were undisciplined and disobedient, noisy
and few attempting to the scholar activities in general. Those students are used to
receive ticking off by the teachers of the school, who are the same used to tell them off
often. In contrast, the discipline and attitude of the SD2 group is rather positive oriented
to new scholar tasks. They get easily concentrated and motivated by new things to do,
thus, teachers do not give ticking off regularly. Thus, since most of the students were
undisciplined, a teacher was accompanying each experimental session, in order to
establish authority and order in the classroom. However, the teachers were not allowed
to interfere at any stage of the experiment.
As it was stated previously, the students of the 4i* grade who participated in the
CONTROL groups were finishing the last year of school, in which all students must
take official exams measuring their knowledge gained during the 11 grades of school
life. This exam is relevant in the sense that it is the first admission criterion that
Colombian universities consider for conceding places for the students and so, it is
enough reason for the students to get training in such exam along the previous months
to the exam in order to perform well at it. Both 11" grades groups had special training
to perform well in such exam and to review the most important issues they were taught
in the school. However, most of the questions of this test are the rote knowledge type, in
which the knowledge is required to be repeated rather than to be understood and to be
applied. Hence, these students gained some training to learn how to resolve such
questions and how to recall the knowledge. Therefore, this special training is expected
to help these students perform well at the lowest type of question in the test. However,
this training is not expected to have influence on the performance of these students on
the highest type of question, mainly because this test is the transfer knowledge type and
its demands result much less susceptible of being overcome by training in answering
certain types of questions rather than by understanding the subject itself.
The experimental design presented in this section shapes students’ performance, thus,
results are presented as follows.
4. Results
4.1 Students who improved -SWI-
The SDI group had better performance than the CONTROL] group based on the SWI
measure of performance for the full test. As table 6 shows, 53% of the students in the
SD1 group had improved scores, compared to the 43% of students in the CONTROL1
group. For those groups in the second experimental experience, the differences are even
greater: 60% of the students in the SD2 group had improved scores, compared to the
33% of students in the CONTROL2 groups who improved their performance. From the
groups who were taught with SD and assisted to different experimental experiences, the
SD2 group had more students with improved scores.
24
spi CONTROL1
SWI=53% ‘SWI=43% Pratue=0.447
sD2 CONTROL2 7
SWI=60% ‘SWI=33% Pyatue=0.039
Pyaue=0.610 -
Table 6. Students who Improved —SWI-
Two-tailed t-tests have been run to test the statistically significant differences of the
hypotheses concerning SWI. A significance level of 0.05 was used to test the
hypotheses. For the groups in the first experimental experience, the better performance
of the SD1 groups was not statistically. However, the better performance of the SD2
was statistically different. Acceptance or rejection of the SWI null hypotheses depends
on whether the group had additional SD training. After additional training, the
differences were large enough to justify rejection of the null hypotheses. 3
4.2 Effective Improvement -El-
Table 7 shows results of the full test according to the EI measure of performance. While
the CONTROL! improved more than the SDI group in the case of the first
experimental experience groups, the SD2 greatly outperformed the CONTROL2 group
in the case of the second experimental experience groups. However, t-tests showed that
there is no statistically significant difference at the 0.005 level in the performance of
groups who were taught with different teaching methods and assisted to the same
experimental experience.
In regard of those students taught with the same teaching method during different
experimental experiences, clearly, the SD2 group outperformed the SD1 group.
However, statistically significant difference in their performance has not been revealed
by the t-test at the significance level of 0.05".
spi CONTROL1
El=1.15% El=4.23% Pratue=0.707
sp2 CONTROL2 sj
El=10.96% El=-0,92% Praive=0.114
Pyauye=0.173 - ;
Table 7. Effective Improvement —EI-
'8 Since ANOVA provides considerably more flexibility in testing group differences when there are more
than two groups to be compared and more than one independent variable (treatment) affecting de
dependent one, an ANOVA has been applied to test the statistical difference between all groups. The
results agree with the t-tests’ results: There is no statistically significant difference in the SWI of all
groups. The P value for the ANOVA test has been 0.182 and the F statistic is 1.65.
An ANOVA has been applied to test the statistical difference in the EI of all four groups. Results show
that there is no significant difference between them. The Pvalue is 0.425 and the F statistic is 0.938. Thus,
this confirms what was found with the t-tests.
25
An often used measure of performance is the Absolute Gain (AG), which indicates
how much students improved. Results with the AG for the four groups of students in
this experiment are in the same direction than the results with the EF. However, the EI
provides a more trustworthy judgment of students’ performance because the number of
improved questions is compared to the size of their learning potential. In addition, the
AG excludes the improvement of many students because of the ceiling effects. Thus, in
this a ssment the EI is chosen as the measure of how much improvement the students
got.
4.3 Comparisons per groups of questions
The measures, SWI and EI, are utilized to test students’ performance per groups of
questions as defined in section 3. The results support the main conclusions given from
the EI and SWI in the full test. SD groups tend to outperform CONTROL groups, when
more training with the SD method is given to students. Though, statistically significant
difference is only found between groups in the second experimental experience.
Structure based questions revealed that more students in the SD1 group got —in average-
more strength over the CONTROL] group in understanding the structure underlying the
diffusion process of a revolution. In contrast, CONTROL1 group demonstrated to have
more students with great strength in the groups of questions of Behavior, and Policies
and Forecasting. In regard to the EI, the CONTROLI group is more outstanding in all
groups of questions. Then, CONTROLI students seemed to understand the behavior
and the structures supporting dynamics of revolutions, so that, they could get insights
about what kind of policies they should apply when desiring to change the course of a
revolution over time. However, statistically significant difference was not found in the
performance of these groups with none of the measures of performance.
On the other hand, the SD2 group had the greatest amount of students with
improvement (from all four groups) in the structure and behavior types of questions,
which represent, at some extent, deep understanding of dynamics of revolutions and its
transferability to other historical cases. Likewise, the EI for the SD2 group is once again
the highest. In addition, based on the SWI the behavior questions were statistically
better answered by the SD2 group, revealing an important difference in the performance
of CONTROL and SD groups in the second experimental experience.
Some differences are present among groups with the same teaching method. With both
the SWI and the EI, the SD2 group exhibits outstanding performance over the SD1
group in the structure and behavior types of questions. Statistically significant
difference with the EI is found between the performances of both SD groups in the
behavior questions. Thus, students from the SD2 group improved in average more than
what the SD1 did in this type of question. In contrast, though a lack of statistically
significant difference in the performance of both groups for the questions concerning
0 The Absolute Gain (AG) is defined as = (Correct Answers % Post test - Correct Answers % Pre Test)
*! In the case of the groups in the first experimental experience, the CONTROL] outperforms the SD1,
while the SD2 group greatly outperforms the CONTROL2 group in the case of the second experimental
experience. The AG for the SD1 group is 1.7%, for the CONTROL is 5%, for the SD2 is 6.2%, and for
CONTROL2 is -0.92. No statistically significant difference was found with the t-tests at the level of
significance of 0.05.
26
Policies and Forecasting, the SD1 performance was better than the performance of the
SD2 group for both measures SWI and EL.
As follows the results per groups of questions are presented.
4.3.1 Structured based questions
Based on the SWI criterion, the SD groups outperform the CONTROL groups for the
structure based questions. The SD1 group had 24% of students with improved scores,
while CONTROL] group had 19%. Though, statistically significant difference in the
SWI of these groups is not found, the P-value of the t-test was closer to the significance
level of 0.05, revealing an important difference in the performance of both groups. In
the case of the groups in the second experimental experience, their performances tend to
be more homogeneous. The SD2 group had 25% of the students with improved scores,
while the CONTROL2 had 21%. Statistically significance is not found with the t-test
applied. Likewise, the performance of both SD groups is rather similar in this group of
questions, which responds to the expectations given the SD treatments to both groups.
In the case of the EI measure of performance, the groups in the first experimental
experience improved in average the same in the structure based questions. Thus,
significant difference is not found with the t-test applied. In the case of the groups in the
second experimental experience, the SD2 improved in average more than the
CONTROL2 group, though statistically significant difference is not found after
applying the t-test. Similarly, for both groups taught with the same teaching method, the
improvement is much higher in the case of the SD2 group, while there is not statistically
significant difference in their performance.
Structure ‘SD Method Standard Method
sD1 CONTROL1
SWI=24% SWI=19% tt er
El=6% El=7% —_
sp2 CONTROL2
SWI=25% SWI=21% ee Pee
El=15% El=7% vale
oarce | SWIPiauc=0.647
Paves EI Paue=0.164 . -
Table 8. Performance in Structure based questions
4.3.2 Behavior based questions
The SWI and EI reveal wider differences in the performance of the groups in the
behavior based questions. In the case of the groups in the first experimental experience,
CONTROL] outperforms SD1 with both measures of performance. However, even
though, the SD1 group presented a deterioration of its performance with the EI, there
was not statistically significant difference in the performance of both groups based on t-
tests, nor with the EI neither with the SWI. In the case of the groups in the second
experimental experience, the difference in the performance between SD2 and
CONTROL2 groups is wide enough to cause statistically significant difference based on
the SWI measure. Thus, students in the SD2 group tended to answer more properly
those questions based on the understanding of the behavior of revolutions. In the case of
27
the EI, the difference in the performance of both groups is still wide and the SD2 reveal
greater improvement than the CONTROL2. However, statistically significant difference
is not found.
Both SD groups presented huge differences in the performance of the behavior based
questions. SD2 group appears to have more students improving their performance
(SWI) and gaining greater improvement in the post test (EI). The difference with the EI
measure of performance is higher, which leads to have statistically significant difference
between both groups.
sD1 CONTROL1
SWI=20% ‘SWI=27% ay iy ese a0
El=-3.3% E1-8.3% ve=0:
sD2 CONTROL2 |
SWI=35% ‘SWI=18% SW Praw=0.098
E1-23% El=10% vaive=0.
SWI Pyaive=0.201 . :
EI Pyaiyo=0.046
Table 9. Performance in Behavior based questions
4.3.3 Policies and Forecasting questions
Students from SD and CONTROL groups had almost the same performance with both
measures of performances in this group of questions. In the case of the groups in the
first experimental experience, CONTROLI group outperformed SD1 group with both
the SWI and the EI. However, there is not statistically significant difference in their
performance after applying a t-test. In the case of the second experimental experience,
the SD2 group had more students improving their performance than what the
CONTROL2 had. However, the difference is not statistically significant. Likewise, the
SD2 group presented fewer deterioration of its performance with the EI than the
CONTROL2 group, though there is no statistically significant difference in their
performance with the EI measure.
For both SD groups, the performance is in average the same for the SWI, though the
SD1 outperformed the SD2 for the first time. While SD1 had 17% of students with
improved scores, the SD2 group had 14%. However, with the EI measure, the SD2
shows a deterioration of its performance, while the SD1 group improved 2.2%.
Statistically significant difference in the performance of both groups is not found with
any of the measures of performance.
28
SD1 CONTROL
SWI=17% ‘SWI=22%
E1=2.2% E1=3.9%
sp2 CONTROL2
SWI=14% ‘SWI=12%
El=-2.8% El=5.6%
SWI Pyao=t . -
El Pyaiue=0.406
Table 10. Performance in Policies and Forecasting questions
4.4 Controlling for Other Influences
Results given by the SWI and the EI in the full test and in the groups of questions
suggest that the SD teaching method enhances the understanding of history if students
have more training in that method. Using the SWI measure of performance, for
example, the SD2 group outperformed more convincingly the CONTROL2 group than
the SD1 outperformed the CONTROL] group. For the EI measure, the SD1 group did
not outperform its CONTROL group, while the SD2 did. Furthermore, the SD2
outscored the SD1 group on both measures of performance. While these results are
suggestive, the results of the statistical significance t-tests do not provide strong
confidence.
Factors other than the teaching method applied to students may have influenced
students’ performance, and may have interfered in the perception of the absolute impact
of the teaching method on the groups’ performance.
The conditions and circumstances of the student selection and group assignment process
suggest that that process was not random. The absence of a random process in students’
assignation to each group represents an important issue affecting students’ performance,
mainly because guarantee of the same initial conditions for all groups was not given.
Then, students may have had different capabilities before the experiment was carried
out. The pre test applied to students one week in advance of the experiment was
intended to measure students’ initial capabilities, which were expected to be
homogeneous along all groups. However, all groups showed different performance in
the pre test, and with it, they revealed different initial capabilities to run the
experiment’. Thus, an important factor to be considered in students’ performance is
given by the prior capabilities that students had before the experiment was carried out.
Hence, it would be expected a positive correlation between scores in the pre test and in
the post test and that is seen in the data with a correlation coefficient equal to 0.44 for
such relationship. With respect to the measures of performance, SWI and EI, a negative
correlation with the pre test is expected because the pre test scores are subtracted to
obtain both measures. Again, the data support that assumption with correlations
coefficients of -0.51 between the SWI and the pre test scores, and of -0.37 between the
» The SDI group answered correctly 45% of the questions in the pre test, the CONTROLI group
answered 41% of them, SD2 51%, and CONTROL2 48%.
29
EI and the pre test scores. It is necessary, therefore, to try to control statistically what
was not controlled effectively by the group assignment process. Therefore, a multiple
regression analysis was performed. This analysis includes not only the teaching method
but also the students’ prior capabilities as explanatory variables of the performance.
Controlling other effects on students’ performance different from the teaching method is
the main attempt of the multiple regression analysis.
In the following equation, Y represents students’ performance and is a function of the
teaching method and the pre test scores (given in %). Coefficients b and c indicate the
relationship between students’ performance and each explanatory variable. The
coefficient “‘a” represents the intercept or constant and the errors are also considered in
the model.
Y= a +b*Teaching Method + c*Pre Test Scores + error
The inclusion of the pre test scores as an explanatory variable of students’ performance
leads to ensure that any given effect on the performance is not due to some effect of the
prior capabilities but due to the teaching method. In other words, the linear regression
helps hold the pre test scores constant, while the teaching method influences the
performance according to the SD exposure received by students. Thus, the teaching
method per student is defined as a number referring to the number of days of SD
training received during the experiment. Thus, students in the SD1 group received a
number | in the method variable due to one day of instruction based on SD, students in
the SD2 group received a number 2 due to two days of instruction based on SD, and
students in both CONTROL groups received a zero because they had no instruction
based on SD”.
All 120 students participating in this experiment are considered as a full group for the
multiple regression analysis.
The performance is given by the two measures of performance previously used, the SWI
and the EI. Thus, there are two multiple regressions to run:
SWI= a +b*Teaching Method + c*Pre Test Scores+error (1)
EI= a +b* Teaching Method + c*Pre Test Scores + error (2)
After applying the multiple regression analysis the values for the coefficients are given.
In the case of the first (1) equation, the coefficients determine the equation as follows:
SWI= 1.111 +0.159*Teaching Method -0.016*Pre Test Scores +error (la)
* The “number” representing the “amount” of SD training per group is certainly arbitrary. However,
those numbers have been assigned in an effort to draw general conclusions about the impact of the
teaching method on students’ performance. This numbering scheme implies a linear relationship between
the number of days of SD training and the effect of such training, while in fact the effect is probably
nonlinear and increases at a decreasing rate as more and more days of training are received.
The hypotheses regarding having coefficients without impact on students’ performance
(coefficients equal to zero) are rejected with a Pvalue of 0.001 for the method and with
a Pvalue of 0.000 for the pre test scores. As expected, the exposure to SD has a positive
correlation with the SWI meaning that the more exposure to the SD teaching method,
the higher SWI. Similarly, the pre test scores were expected to have a negative
correlation with the SWI, because the more students did well in the pre test, the less
reflected is their improvement in the SWI (measure based on the difference between
post and pre tests scores).
Likewise, in the case of the second equation (2), the coefficients are certainly different
from zero. Furthermore, the hypotheses regarding coefficients equal to zero are rejected
with statistical difference in the case of the teaching method coefficients (Pvalue equal
to 0.041), and the Pre test scores’ coefficient (Pvalue equal to 0.000).
EI= 31.561 +6.208*Teaching Method -0.704*Pre Test Scores+error (la)
Similarly to the SWI case, the correlation between the teaching method and the EI was
positive as expected, indicating that the more exposure to the SD teaching method, the
greater the improvement gained by students. Accordingly, there is no wonder in the
negative correlation between the pre test and the EI. The higher the scores in the pre
test, the less improvement the students can reveal through the EI (considering the nature
of the equation, in which the nominator subtract the pre test).
Through the multiple regressions, the effect of the method on students’ performance
could be isolated when taking into consideration, simultaneously, the effect of the
students’ prior capabilities. Both regressions reveal, then, that the method of teaching
history matters and that any observed effect of the teaching method on the performance
is not due to the students’ prior capabilities but because of the method itself. The more
exposure the students have to the SD method, the higher is their EI and the more
students improved their performance. Statistical difference in the impact of the
explanatory variable “teaching method”, for both measures SWI and the EI, evidences
that certainly the SD has an important effect on students’ performance”.
These results seem to be encouraging. However, there is a potential methodological
problem in the fact that the pre test scores are being subtracted in both sides of
equations 1a and 2a. Given the nature of the SWI and the EI equations, the results of the
pre test are subtracted from the post test scores to calculate the improvement given by
students. Thus, a more trustworthy way of calculating the impact of the teaching method
on students’ performance must be based on the post test scores (%) as the performance
variable (dependent variable), which is predicted by the teaching method and the pre
test scores. The linear equation must be then:
Post Test Scores (%) = a +b*Teaching Method + c*Pre Test Scores+error (3)
This way of approaching the impact of the teaching method on students’ performance
provides more conservatism and confidence on the results given by this test. Any effect
* Tn addition, the assumptions regarding normality of the residuals and dispersion of the residuals
according to the teaching method are fulfilled with the linear regression for both measures of performance
(SWI and EI).
of the teaching method on students’ performance will be more reliable given the fact
that the pre test scores effect are not affecting both sides of the equation.
The results do not go far away from the conclusions provided in the two previous
regressions. The coefficient for the pre test scores predicts statistically the post test
scores of students. However, the level of statistical confidence resulting from this more
conservative approach is at the 0.06 level, revealing a less strong effect of the teaching
method on students’ performance than what was revealed with equations la and 2a.
Nonetheless, the Pvalue for rejecting the hypothesis is rather close to the significance
level of 0.05, which shows results almost as strong as those mentioned before. Thus, if
the sample size were larger, the power of the effect of the teaching method on students’
improvement will be stronger, and the level of statistical confidence might meet that
customary target level. The effect of both explanatory variables on students’
performance is positive, indicating as expected that the higher the scores in the pre test,
the higher the scores in the post test. Likewise, the greater the exposure to the SD
teaching method, the higher the score in the post test.
Important findings result from this analysis, in which the teaching method seems to be
still a strong explanation of students’ performance, when keeping track of the effect of
the students’ prior capabilities on the their performance. Even though the
implementation of the experiment may not have adequately randomized the effects of
students’ prior capabilities, the multiple regression helps to control that influence. Thus,
it was not possible to build randomly the groups for this experiment, it can be concluded
that when controlling the initial conditions regarding the prior capabilities of students,
the effect of the SD teaching method on students’ performance is positive and enhances
students’ understanding of revolutions”.
5. Discussion
Based on the SWI for the full test, the SD groups had more students improving in the
post test than the CONTROL groups. However, while the CONTROLI group
outperforms the SD1 group, the SD2 is the group with the greatest EI not only from the
groups in the second experimental experience but also from all groups. Statistically
significant difference between the performances of the groups has been found only
between SD2 and CONTROL2 based on the SWI measure.
In the case of the groups of questions, SD1 group showed strength with the SWI in
understanding the structure underlying the diffusion process of a revolution, and in
using such understanding for interpreting other events that behave similarly. In contrast,
the CONTROLI group did better with the SWI in the questions based on behavior of
revolutions and in the questions concerning policies and forecasting questions. In
addition, the group did better based on the EI in all groups of questions. However, there
is no statistical difference in the performance of both groups. The SD2 clearly
outperformed the CONTROL2 group in all groups of questions and with both measures
of performance (SWI and EJ). Statistical difference in their performance is found with
* The assumptions regarding normality of the residuals and dispersion of the residuals according to the
teaching method are fulfilled with the linear regression for the Post Test Score (%). This fact strengthen
the reliability of the linear regression as test for measuring the impact of the teaching method on the
performance of students.
the EI in the groups of questions based on behavior of revolutions. Similarly, the SD2
outperformed the SD1 group in the structure and behavior based questions with both
measures of performance. In addition, questions regarding behavior had statistical
difference in the EI of both SD groups.
The performance of the SD over the CONTROL groups differs depending on the
measure of performance, which suggests some uncontrolled effects that may have
caused the performance to differ. Thus, in an effort to control effects that were not
controlled in the assignment process of the students to each group, the multiple
regression analysis has been carried out in light of providing a stronger point of view to
identify the role of SD in the learning process of history. In this case, the consideration
of the pre test scores as an explanatory variable of the performance of the students
helped isolating the effect of the teaching method on students’ understanding of
revolutions. Thus, the perception of the absolute effect of the method is more clearly
understood. Results suggest insights in the same direction than those provided by the
SWI and EI in both, the full and groups of questions. The method for teaching history
matters and students’ understanding of revolutions seems to be enhanced by the SD
teaching method if students have more training in the method. The longer is the
exposure of students to the SD teaching method, the better is their performance in the
post test. In addition, this analysis also reveals the importance of considering the initial
students’ capabilities in light of interpreting the results. Thus, any observed effect of the
teaching method on the performance of students is not given by students’ prior
capabilities but by the method itself. Despite absence of statistical significance in the
relevance of the teaching method on students’ performance, the nearness of the Pvalue
builds confidence on the outcomes, especially when they strength the insights given
already by the measures of performance SWI and EI in the full test and groups of
questions.
Conclusions based only on either the SWI or the EI for the full test or in groups of
questions do not explore totally the effectiveness of the SD teaching method on
students’ understanding of revolutions and their dynamics. Likewise, conclusions given
from the multiple regression analysis provide more enhanced insights about the
effectiveness of the teaching method when they are not analyzed in an isolated way.
Thus, rather than focusing the attention on one single measure, it is more important to
keep an overview of how many students improved per group, how much the group
improved, on which groups of questions this improvement was concentrated, and how
strong is the impact of the teaching method on students’ performance. At the end, it will
be possible to draw finally whether SD enhances the understanding of revolutions.
Certainly, SD2 group presented the greatest SWI. The performance of SD2 students’,
based on the SWI, is statistically different from its CONTROL group. In addition, the
SD2 group improved more questions in the full test than what the rest of the groups did
(high EI). SD2 students’ improvement was focused consonantly on questions based on
the understanding of the behavior of revolutions and the structure underlying such
behavior. The performance of the groups in behavior questions is statistically different
from the CONTROL2 group and the SD1 group also. Furthermore, the amount of SD
training received by students seems to be a good explanatory variable of the students’
performance. Thus, since students in the SD2 group received the largest amount of SD
training in this experiment, their good performance may have been given by the effect
of the method itself rather than by other effects such as students’ prior capabilities.
33
Reliability on SD2 accurate performance, as a result of the effectiveness of the SD
teaching method, is increased then by the suggestions provided by the multiple
regression analysis. Thus, given the consistency of the results of all views of students’
performance, it can be concluded that students in the SD2 group did not improve
accidentally, and that SD may be considered as a proper tool for enhancing students’
understanding of history, specifically of revolutions.
The SD1 group outperformed the number of students who improved in the CONTROL1
group, especially in the structure based questions. However, the CONTROLI group
outscored the SD1 group with the EI applied not only to the full test but also to the
groups of questions. In accordance with the expected effects of the teaching method on
both groups in the first experimental experience, it can be seen that performance of
students in both groups seems not to be explained solely by the teaching method
applied. As a first attempt to control other various effects, the students’ prior
capabilities have been considered as an important effect influencing students’
performance and the impact of the teaching method may be analyzed more confidently.
Statistical significance of the SD method is not found. However, since the Pvalue is still
close to the significance level, it is possible to conclude that the amount of SD exposure
received by students has certain effect on students’ performance. Students without
exposure to SD teaching method (CONTROL groups) are tended to have poorer
performance than those who have had at least one day of SD based instruction.
Nonetheless, the teaching method seems not to be a good explanatory variable for the
outstanding performance of CONTROL] group in comparison to the SD1. Thus, some
other uncontrolled effects, different from the students’ prior capabilities, must have
influenced students’ performance.
According to the treatments applied to each group of students, it was expected to find in
the results of this experiment that those students, who were taught with the SD teaching
method and participated in the second experimental experience, would have the best
performance from all the groups in all measures of performance. Similarly but less
significant, the performance of the students who were taught with SD during the first
experimental experience was expected to follow the same direction than the
performance of the SD2 group. None of the Conventional groups were expected to be
outstanding. However, as seen before, the results differ at some extend from the
expected ones, mainly in the groups in the first experimental experience. Factors that
have influenced students’ performance need to be discussed in light of the effectiveness
of the SD method of teaching history. Factors such as the expected better performance
of the SD1 group and the outstanding improvement of the CONTROLI group over the
SD1 cannot be overlooked.
There were factors, controlled within the experiment, that were expected to delimit
groups’ performance. The experiment design, the treatments, the instructional design
were all factors that carefully defined the learning process and the understanding of the
students about the revolutions over time. The research method and the experimental
design were established in a way that students could show the outcome of being under
certain type of treatments. Besides, content of the French revolution was provided to the
students in the form of instructional methods and facilitated the chances for the students
to show the skills acquired during the experiment given certain type of applied
treatment. Furthermore, despite absence of a random students’ assignment process to
the groups, all four groups were statically homogenous and their average performance
in the subject of social sciences was rather the same. At some extent, groups were under
similar conditions to be guided with the treatments towards the expected results.
Students from the SD1 group were under the effect of the SD teaching method
treatment and First Experimental Experience treatment. The introductory session to the
SD basic concepts, the Infection game, the debriefing using the diffusion model, and the
instruction about the French revolution from an SD point of view, were determinants of
the students’ scores. This group was taught about the concept of diffusion of a disease
of a revolutionary population over time. S&F structures were the essential tools to place
in a structured pattern the general understanding of revolutions and their dynamics over
time. Furthermore, behavior over time was presented as a result of the interaction of the
elements in the S&F diagrams, so that students were able to understand such behavior
rather than merely recall it. However, even though SD1 students were taught about all
mentioned above, the time for understanding this approach was few. Thus, this group
was expected to have improved performance in the structure and behavior groups of
questions. Some of these expectations were fulfilled. With the SWI, the SD1 group
outperforms the CONTROL] group in the structure questions.
SD students in the second experimental experience had as great strength the fact that
they already were in touch with the SD tools, mainly with the Diffusion model and S&F
diagrams, in order to understand the importance of Civics. These students studied the
same diffusion structure from three different fields of study: infections, civics and
French revolution. Therefore, they were more skilled than the rest of the students to
improve their performance in the three groups of questions. Indeed, this group has
fulfilled most of the expectations in the sense of being rather outstanding not only in the
full test, but also in types of questions based on the structure and behavior of
revolutions. In the last group of questions, the SD2 group was not the most outstanding
group; however, its performance in such group was not bad, meaning that some of the
students who improved in the other groups confirmed their understanding in the Policies
and Forecasting group of questions.
In contrast, students from the CONTROL groups were taught about behavior of
revolutions over time and the way the French revolution was unfolded. However, they
were not taught about the way to understand such behavior and the reasons why the
revolutionary population in the French revolution developed in the way it did. Thus,
these groups were expected to answer properly the questions of the test in which recall
of behavior of revolutions was required. In the case of the CONTROL2 group, this
group did not even perform well in such questions. Nonetheless, it was not expected a
greater performance of CONTROL] group in comparison to the SD1 group. Certainly,
CONTROLI group outperformed the SDI group in behavior and policies and
forecasting questions.
Thus, besides the treatment effects, some more causes (unmeasured effects) may have
influenced students’ performance. Specifically, other factors different from the teaching
method may have, in some cases, undermined or amplify students’ performance. Issues
regarding implementation of the experiment (mainly duration), motivation, and
cognitive loads could have undermined the possible performance of SD groups,
especially the SD1 group. Furthermore, such effects may have caused the results of the
CONTROL group to be better in categories in which it was not expected. Figure 23
shows the presence of the various effects on students’ performance. It describes, as
stated previously, that measured factors such as the teaching method and the students’
prior capabilities have a positive influence on students’ performance. The more training
the students receive with SD, the more enhanced their understanding of revolutions is.
Likewise, the higher the pre test scores of students, the better their performance in the
post test. In addition, the figure shows that other unmeasured factors may have
influenced students’ performance but since those factors were not controlled by the
experiment, their type of impact on the performance is not known numerically.
Teaching Method Duration of the
Experiments
t ge Motivation
Students’ Performance
+ Lo Cognitive Loads: Working
Memory Limitations
Students’ Prior oo,
capabilities Special Training in
exams
Measured Effects Unmeasured Effects
Figure 23. Influences on students’ performance
Thus, as follows a description of those unmeasured effects is presented according to the
way the intervened in the experiment, in an attempt to determine their role and influence
on students’ performance.
a. Duration of the experiment
The duration of the experiments’ sessions is one of the factors that limited the SD
groups’ chance of maximizing the benefits from the SD teaching method. Specifically,
2 hour sessions are not enough to understand the concepts of SD. Even people who have
received training in SD take time until they can understand how the process of
accumulation occurs, how the feedback loops are given, and what an S&F diagram
represents. Learning to think systemically and to understand changes over time implies
more practice. Thus, it is very likely that SD groups did not achieve exactly what was
expected from them because in few sessions they could not get the concepts. This must
have certainly undermined the performance of students in the SD1 group. The evidence
for this is the fact that the SD2 group showed more enhanced performance after going
through 3 day sessions rather than just two. This fact leads to think that having longer
time for introducing the SD teaching material to the students is essential for them to
respond to the benefits of the teaching method, and with this a more enhance
improvement in the understanding of revolution may be is given.
b. Motivation
A student could be motivated to learn new skills because he or she understands their
potential utility or value, or because learning the skills will yield a good grade and the
privileges a good grade affords. According to Self Determination Theory (SDTy®
students can perform extrinsically motivated actions with resentment, resistance and
disinterest, or alternatively, with an attitude of willingness that reflects an inner
acceptance of the value or utility of the task. In the first case, one feels externally
propelled into an action; in the later case, the extrinsic goal is self endorsed and thus
adopted with a sense of volition (Deci & Ryan, 2000). Extrinsic motivation is aimed to
be achieved in school tasks by internalizing the goal of the activity and by
understanding the potential utility on such task. Likewise in the present experiment, the
task itself should have been motivating enough to be self internalized by the students in
order to focus their will and disposition on learning about revolutions. Besides,
instructional design and the people involved in the application of the experiment aimed
to motivate the students as much as possible. However, other factors undermined the
motivation of some of the groups (Deci & Ryan, 2000).
The scholar year in Colombia ends at mid November, time in which these experiments
were run. Certainly, students were strongly motivated to accomplish all the goals they
were required to do before the academic year ended. However, it is very likely that their
motivation could not be strongly oriented into an activity that demanded from them to
learn something extra during such critical academic period of time. Besides this factor,
the students did not receive any kind of reward for participating in the experiment.
Rather, they had to follow a compulsory activity given by the Principal of the school”,
Acceptance of the potential utility of such task was a tough process for the students,
who at first tried to reject to go through more overloading activities different from the
regular ones. Thus, relying only on the motivation that the instruction itself could
provide to the students was not enough to ensure their best, especially because the
students had many things to do alongside the experiments. This may have been essential
in undermining the performance of all groups according to what was expected from
those students.
The autonomy and the perceived benefits from the task are factors that promote the
internalization and integration of the activity by the students (Deci & Ryan, 2000;
Heckhausen, 1989). In the motivation through identification, the student has identified
personally with the importance of the task and thus, accepted its regulation as his or her
own. Studies have revealed that the more students are externally regulated, the less they
show interest, value or effort in the tasks to be performed”’. The more autonomous
extrinsic motivation, the more associated it is with greater engagement, better
performance, less dropping out, higher quality learning, and greater psychological well-
°° In SDT the types of motivation are differentiated according to the reasons and goals that give rise to an
action. The most basic distinction is between intrinsic motivation, which refers to doing something
because it is inherently enjoyable, and extrinsic motivation, which refers to doing something because it
leads to a separable outcome. Further information about Self Determination Theory (SDT) is available in
(Deci & Ryan, 2000).
*7 Since the Principal chose the students who participated in the experiment, they only had to follow what
he wanted them to do.
°S The least autonomous form of motivation is the external regulation, in which some behaviors are
performed to satisfy an external demand or obtain an externally imposed reward contingency. However, a
more autonomous, or self determined form of motivation is regulation through identification.
being. Thus, the fact that the scholar year was finishing and students had to focus their
interest on more relevant tasks at the same moment, could have caused certain degree of
demotivation on them, making more difficult the process of internalizing the goal of the
experiment and to visualize its potential utility in the activity (Deci & Ryan, 2000).
Furthermore, the experiment and its goals were presented to the students some minutes
before the pre test were applied to them. At the beginning of this test, the students were
told by a teacher about what was expected from them in the activity and what the
importance of their performance was. Hence, each teacher was responsible for
introducing these words to the students and for presenting the person in charge of
applying the experiment. The role of the teacher on the students’ motivation on the
experiment (and on its consequent internalization as a students’ personal interest) was
rather important, and everything he said could have been a source of shedding interest
or not on the students. With almost all groups, teachers kept faithful to present only
what the experiment was about, however; when introducing the pre test and the
experiments to the SDI group the teacher bawl them out because they were still too
energetic and noisy from the lunch break they took before. Right after, the teacher
introduced the experiment and the pre test to be applied.
Cognitive Evaluation Theory (CET)” argues, among other tenets, that a high level of
motivation cannot be achieved when a few sense of autonomy is surrounding the task to
be performed. Furthermore, not only tangible rewards, but also threats, deadlines,
directives and competition pressure diminish motivation. Certainly, the teacher
accompanying the SD1 group took out whatsoever motivation students could have had,
after giving them a tick off. Thus, it is very likely that students mixed the teacher’s
sermons with the sense of the experiment and thus, this single event could affect their
performance, which did not entirely respond towards the expected goal. On the other
hand, students from the CONTROLI group were told about the experiment by the
social sciences teacher, who indeed, told them anything else than the purpose of the
experiment and what was expected from them. No berating, no ticking offs were given,
and furthermore, students were already in social sciences class, which could make them
relate the experiment to a subject’s task instead of an extra task to be performed at the
end of the year. Thus, the task itself could be more internalized and so, a high level of
extrinsic motivation arose, which explains the sometimes lower performance of the SD1
group in comparison to the CONTROL.
c. Working Memory Limitations
When dealing with novel information the working memory” has two severe limitations:
its capacity and the duration that this information can remain in memory. All
instructional methods requiring learners to deal with novel information must be
processed by a structure that is minute in capacity and that retains the new information
for no more than a few seconds. These limitations become successively less critical as
familiarity increases (Sweller, 2005).
The French revolution was not an unfamiliar topic for the students; however, for those
students whose teaching method was SD, the approach was indeed novel for them and
°° Further information about Cognitive Evaluation Theory (CET) is available in (Deci & Ryan, 2000).
*’ The working memory is the cognitive structure in which information is consciously processed (Sweller,
2005).
provided lots of novel information about how the topic could be understood. System
thinking, S&F diagrams, and understanding of behavior and structure, were just some of
the novel issues students from the SD groups had to go through in order to understand
the activity. The information presented was required to be recalled at any step further of
the instruction. Both constraints of working memory, capacity and duration of the
information, were violated. Capacity was overloaded by introducing so many SD
concepts, required for the understanding of the entire instruction, in such a short period
of time. Furthermore, the information was demanded to be recalled as long as the SD
students went through the instruction, and so, the duration period for the information to
be used was rather long. These factors may have undermined, especially, the effect of
the treatments applied to the SDI group, which were expected to enhance more
students’ understanding about revolutions. The more practice acquired by the SD2
group with the SD approach gave the students the chance to have one day more of
getting to know the novel information. Even though instructional methods for both SD
groups were the same, the experience gained by the SD2 group, due to being part of the
Civics’ experiment, let them understand better the novel information that were
presented to them. Nevertheless, the entire learning potential that these students had was
still far to be reached.
Instructional methods presented to SD groups failed in considering the working memory
capacity, and added a rather high level of element interactivity*'. Intrinsic cognitive load
was inherent to the SD approach. Changing the way of approaching historical issues
demands a great effort from students, especially when it is required from them to relate
several elements introduced along the instruction for achieving a general understanding
of the topic. Furthermore, extraneous cognitive load was presented in the need for the
students to relate multiple sources of visual information, which all were essential for the
understanding and were not intelligible in isolation. Thus, total cognitive load for the
SD groups was rather heavy, which certainly undermined the performance of SD
groups, especially of SD1 group that had less SD training.
On the other hand, students from the Conventional teaching method went through an
instructional method that presented an approach of the topic that did not add complexity
and novelty to the task. Extraneous cognitive load still is seen in this instruction because
pictures, graphs and written texts were still present and were required to understand the
topic. However, the total cognitive load of CONTROL groups was not as heavy as SD
groups.
d. CONTROL groups: Special training for the State exam
Both CONTROL groups went through the final exam of the school run by the
Colombian State. The exam is presented at mid September and students are trained
during the first semester of the year to improve their cognitive skills for passing the
exam. When the experiment was run at mid November, those students still had fresh
*! In respect to the Cognitive Load Theory, the extraneous cognitive load is caused by inappropriate
instructional designs that ignore working memory limits and fail to focus working memory resources on
schema construction and automation. Intrinsic cognitive load is the cognitive load due to the natural
complexity of the information that must be processed by the students. It is determined by levels of
element interactivity. High element interactivity material imposes a high working memory load (Sweller,
2005).
what they got in such training. Thus, their cognition was highly increased and attentive
for focusing on relevant issues taught in the instruction and to recall them in the test.
This factor certainly enhanced the capacity of the CONTROL groups, in answering
questions better than they were expected to do. Consequently, the performance of
students in SD groups, mainly the SD1 group, can result overlooked.
Consequently, keeping in mind an integral point of view of the SWI and EI (in both the
full test and the groups of questions), of the significant impact of the SD teaching
method on students’ performance, and of all the various unmeasured effects provides
support for concluding that certainly the SD approach is a tool that enhances students’
understanding and learning process in the field of history when students receive long
training with the method.
Contribution to the Learning Process of History
Certainly, history is a discipline whose understanding goes beyond the accumulation of
knowledge of the past. Its learning provides schemata and frameworks that when are
seen as part of a whole allow individuals to identify recurrent patterns of behavior
between different historical happenings. Thus, not only a single historical situation can
be understood and recalled, but also such understanding becomes relevant to understand
the diverse events in the society.
Teaching history with the SD method provides the students with a general framework,
in which they can consider the relationships between all elements interacting in a
historical happening. The methodology for teaching history proposed by Donovan and
Bransford (Donovan & Bransford, 2005) is met by the SD approach. Thus, the
consideration of changes of the state of affairs over time, the consideration of the time
in the historical happenings, and the accumulation of knowledge are all factors that
students in the SD groups revealed to grasp and to consider for the entire understanding
of the case study.
Furthermore, Potash and Heinbokel’s beliefs regarding the benefits of SD when
teaching history have been, at some extent, confirmed by the present assessment of the
SD tools. Thus, understanding historical patterns as part of a whole is an issue indeed
given by the SD teaching method, which places such understanding in schemata that
can be recalled and applied in further learning processes.
Understanding of the connections between the isolated events and variables playing an
important role in the course of a revolution is determinant for altering the long term
memory and to settle this understanding into the form of knowledge of history. Students
who still approach the case study with the Conventional way of thinking can hardly
reveal understanding of why history unfolded in certain ways. A mere recall of isolated
events is the instrument for them to face history, which becomes a poor instrument
when it is intended to make of history a science whose reflection and learning provides
the students with tools for the understanding of society and for better approaching social
problems, which reveal similar patterns than some occurred in the past, such as wars.
In addition, as Potash and Heinbokel believe, the understanding of how and why history
occurred is greatly enhanced by the SD approach, and this understanding may lead
40
students into the comprehension of the complexity of the present and the future in light
of the lessons learned of the past (Potash 1995; Potash, 2005; Potash & Heinbokel,
2006). The assessment of students’ performance in this experiment suggests then, that
SD teaching method may be a useful approach for the students to learn from the past
and the way consequences of the historical happenings affected other matters over the
time in order to interpret better the present and future situations they will face.
At the same time, the present assessment has revealed more clear procedures to
implement the SD teaching method as a conventional method to teach history. Longer
and continuous sessions, in which different case studies are approached through the SD
perspective, matter in the enhancement of students’ performance. Thus, the longer the
time a student has been in touch with the SD approach, and the more fields she has
learned with SD, the easier to profit from such teaching method to get a deeper
understanding of how certain historical happening was developed over time. Therefore,
the possibility of constructing lighter instructional methods that do not load students’
working memory more than necessary is an important issue for getting students’
attention in learning with a different teaching method. Designing gradual increase of the
cognitive demands of the SD instruction will guarantee that students do not loose any
chance of improving their understanding of revolutions. Furthermore, it is required to
enhance their external motivation by providing instructions and instructors that transmit
autonomy and high perceived benefits to the students. Motivation seems to be an
important factor influencing students’ performance, which may be enhanced by the
providing students with all conditions for identifying with the activity and to give worth
to its utility for them.
Also, it is required to consider having much better and equal initial conditions for all
groups who are tested with such experiment. Wherever possible, students must have in
average the same capabilities to perform the experiment.
Thus, ensuring the control of those effects mentioned above, which undermined or
amplify students’ performance must be a must to do task in further experiments.
Complementary, having bigger sample sizes may enhance the statistical power of the
teaching method on the performance of the students. In this case, the performance of the
SD groups would be highly enhanced in comparison to the performance of the
CONTROL groups.
System Dynamics is still a young approach in the classroom, especially in those fields
of study which have to do with social sciences, as in the case of history. Hence, further
research and validation of the role of SD in the performance of the students of history is
still a critical matter that deserves being at least considered as a possible conventional
method to teach such subject.
6. Future Research
The present study suggests important insights regarding the usefulness of SD in the
history classroom. However, it is still necessary to do more research in this field, given
the few applications of SD in social sciences, and the great absence of assessment of the
benefits that students really get from such approach. Therefore, in this section important
aspects are mentioned in order to improve in the future the outcome of this and coming
experiments for those who may be interested in the field.
41
Factors such as the duration of the experiments’ sessions and the number of case studies
approached with the SD teaching method seem to be relevant to enhance students’
understanding of the dynamics and change over time of history. SD is an approach that
itself provides the students with a greater understanding of the developing over time of
history, but at the same time provides the students with lots of information and new
reasoning that must be taught gradually over several teaching sessions. Thus, slowing
down the presentation of the SD approach of history is an issue that really matters when
thinking about further research in regard of these experiments.
An introductory session is still required to enroll the students into the SD thinking, to
teach its basic concepts, and to play the Infection Game with its corresponding
debriefing. Furthermore, the case study should be split into sessions of no more than 30
minutes, in which the content is presented step by step in the sessions. One week for
one single case study would be the ideal situation in order to guarantee that students are
not too cognitively loaded and that they will not loose attention because of tiredness. As
mentioned in the previous section, this experiment has failed in loading the students,
especially those in the SD treatments, with lots of information in very few periods of
time.
Besides, teaching more than one case study, all supported on the same basic SD
structure (in this case the diffusion model), let the students succeed in grasping the
proper knowledge and understanding of the dynamics of history. Thus, all groups under
the SD treatment should study at least two case studies. In addition, from the lessons
learned in the present experiment, it is very important to assess students’ understanding
after every teaching session. Thus, if different case studies are intended to be taught in
daily sessions within a week, assessment after each session is necessary. Every session
should be proceeded by a test asking for the concepts learned during that session, and
thus, the learning process of the students can be followed for measuring performance
and for giving immediate feedback to the students about how they are performing in the
experiment. Likewise, students’ maximization of the benefits of such approach might be
strengthened by running the experiment in a period of time, in which the students are
not facing a too hectic moment, such as the end of the scholar year. These two
considerations may be useful to lessen the cognitive load intrinsic to the SD approach
itself and may increase the students’ possibility to gain more profit from this teaching
method.
Accordingly, a great sense of autonomy, given not only by the experiment but also by
those people accompanying the learning process, is required to guarantee motivation
and that students will identify with the activity’s goal and will integrate it with the
personal goals. In this sense, high school students have shown the need of a figure of
authority to behave during teaching sessions, which are not done in the conventional
schema they are used to. Thus, people accompanying the students during the teaching
sessions are necessary but should limit to perform the unique role of a figure of
authority and respect. Teachers must be prepared for not playing the role of the
responsible of the activity, in order to avoid having different attitudes that interfere in
the performance of the different groups of study.
Furthermore, a constant and immediate feedback of the performance along the sessions
is highly decisive for the students’ performance and their motivation. The present
42
experiment did not provide the students with feedback about their understanding of
revolutions and their performance. Thus, students could not know whether their
performance was correct or whether further efforts and attention should be put in the
activity. Information about their understanding of each session should encourage them
either to put more efforts in the activity or to keep on doing the same well in order to
finish with a high performance (Deci & Ryan, 2000).
External rewards such as monetary and academic rewards can only persuade the
external motivation of students, and can easily undermine the intrinsic one. However,
when the instruction contains factors such as high sense of autonomy, clear benefits
from the learning experience, and immediate feedback of the performance; it is possible
to increasingly persuade students’ motivation with an external scholar reward such as an
academic grade. Feasibility of this motivational strategy may be negotiated with the
schools. A combination of all those factors will define the students to do their best in the
task.
The computer based instruction is absolutely important to guarantee the provision of the
same information to all students. This should be less loaded by information and should
be interactive enough to present immediate feedback of the performance to the students.
An Interactive Learning Environment (ILE) must be an ideal computer aid to transmit
the information of history and to interact with the student along the sessions.
The test instrument is an important matter for measuring what is expected from the
experiment. Thus, wherever possible, the test used to measure students’ understanding
regarding revolutions and their dynamics must be based on previous elaborated tests
that measure the purpose of this experiment. Wherever not possible, the test should be
carefully designed in cooperation not only with historians but also with system
dynamicists, who can contribute with their understanding of the field and of the
dynamic approach to the case study. After the design, the test should be widely tested
before being applied to students in order to filter those questions that even though are
intended to measure high understanding of revolutions can be easily correctly answered
by guessing. Furthermore, from what has been experienced in the pilot experiments
previous to this experiment, presentations in groups about different case studies
analyzed with the SD perspective is a revealing instrument to test understanding of
revolutions and their dynamic behavior. Sharing the personal understanding regarding
revolutions with others is an important exercise to commonly build knowledge about
this topic. However, designing a proper way of assessing students’ understanding from
the groups’ presentations is a relevant issue, in which certain minimum parameters of
performance might be created to measure and classify students’ performance.
All the above considerations might want to be applied to CONTROL groups as well.
For this purpose, all initial conditions for Conventional and SD groups must be the same
in terms of cognition, knowledge, and attitude conditions. To ensure this, randomization
of students’ samples is essential. Each subject should be assigned randomly to the
corresponding group to which she will belong. Thus, coordination with the schools
should be done very well in advanced in order to control any disturbance that makes
more complicated the randomization of the samples (such as the time pressure presented
in the school).
43
Additionally, the fact that the SD2 group was the most outstanding group and that SD1
revealed high SWI, provides the insight that SD could be, indeed, a better way to teach
history and to place its understanding in a structured pattern in students’ minds. Thus, it
is required to keep on building a conventional methodology based on SD to teach
history in high school classrooms. In order to reach such goal, it is important to continue
experimenting with the SD approach in the real history classroom.
44
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