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Eskrootchi, R., & Oskrochi, G. R. (2010). A Study of the Efficacy of Project-based Learning Integrated with Computer-basedSimulation - STELLA. Educational Technology & Society, 13 (1), 236–245.

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A Study of the Efficacy of Project-based Learning Integrated with Computer-based Simulation - STELLA

Rogheyeh Eskrootchi and G. Reza Oskrochi1*

School of Management and medical Information Sciences, Iran University of Medical Sciences & Health services,

Tehran, Iran // [email protected] of Technology, Oxford Brookes University, Oxford, UK // [email protected]

*Contact author

ABSTRACTIncorporating computer-simulation modelling into project-based learning may be effective but requires careful

planning and implementation. Teachers, especially, need pedagogical content knowledge which refers toknowledge about how students learn from materials infused with technology. This study suggests that students

learn best by actively constructing knowledge from a combination of experience, interpretation and structuredinteractions with peers and teachers when using technology. Simulations do not work on their own, there needsto be some structuring of the students' interactions with the simulation to increase effectiveness. The purpose of

this study was to investigate the effectiveness of project-based learning in a technology-rich environment. Ascience project, Land-use in Watershed, that takes advantage of Internet facilities was developed and integratedwith a simulation software package, Structural Thinking and Experiential Learning Laboratory, with Animation,(STELLA) developed to promote deeper understanding of Land-use by students. The Participants in the study

were 72 students in a quasi-experimental research design. Statistical analyses showed that students who participated in the manipulation of the experimental model of the watershed experiment and the STELLAsimulation performed best on understanding the watershed concept.

KeywordsSTELLA, computer-assisted simulation, learning technology, watershed concepts and modelling, project basedlearning

Introduction

An often-stated belief is that transferring skills is the main job of education. However, an increasing body of research

shows that the way knowledge is presented to students in school and the kinds of operations they are asked to

perform often result in students knowing something but failing to use it when relevant. Brown, Collins and Duguid

(1989) believed that classroom activities lack the contextual features of real-life problem-solving situations and

therefore weaken the ability of students to transfer and apply their knowledge from the school setting to the outside

world. The challenge as Santos-Trigo and Camacho-Machín, (2009) purposed is to question; “Can routine problems

be transformed into problem solving activities that promote students' mathematical reflection?”

Studies suggest that in order to facilitate transfer, promote effective learning and encourage a high degree ofownership and personal relevance, educators should provide training on real tasks. Similarly, researchers believe that

cases and examples must be studied as they really occur, in their natural contexts, not as stripped-down ‘textbook

examples’ that conveniently illustrate some principle (Blumenfeld et al., 1991). The extent at which the process ofsolving textbook problems can help students develop a way of thinking to be consistent with mathematical practice is

still under an investigation (Santos-Trigo & Camacho-Machín, 2009).

The National Research Council’s (NRC, 1999) standards for science education suggest long-term inquiry activities

including argumentation and explanation, communicating ideas to others and using a wide range of manipulative,

cognitive and procedural skills will promote learning. The standards suggest that to develop their understanding,students need to relate new information to existing knowledge and build connected networks of concepts. In

addition, NRC (1999) called for the teaching of “fluency with information technology” and strongly recommendedthe use of technology to promote understanding of science and mathematics.

Theorists and educators are promoting reality-centred projects and other reality-centred activities as ways to engage

students in meaningful learning. Experienced educators tend to agree that students learn best through a project-basedapproach in which they are able to discover things for themselves and take advantage of technological tools

(Blumenfeld et al., 1991; Clinchy, 1989; Linn, et al., 2000; Lebow, & Wager, 1994).

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While technology can be valuable in supporting students and teachers in projects requiring higher level thinking

(Blumenfeld et al., 1991), it is not the kind of technology that matters most, but rather how it is used (Dyrli &

Kinnaman, 1994; Ehrmann, 1995; Green & Gilbert, 1995). The intention of the researcher in this study was to

examine and discuss ways in which learners engage in an intentional learning process and analyze the effectivenessof such approach in two areas: a) an authentic learning activity in the content of project-based learning; and b)

educational simulations.

Project-based learning

Project-based learning (PBL) blends traditional subject-matter goals and objectives with authentic learning

environments. The primary rationale for using authentic activity as the model for appropriate learning activities is the

enhanced understanding that develops through application and manipulation of knowledge within context. Finding

solutions to a problem whether posed by the teacher or a new social environment, more likely develop generic, as

well as subject specific skills when using project-based curriculum. In other words, PBL provides productiveenvironments for the development of meta-cognition (Downing et al., 2009). In addition, in another study conducted

to identify dental students' self-reported sources of stress, the findings revealed that PBL when compared to

traditional curricula was inversely associated with perceived stress and that in turn had a strong impact on learning

(Polychronopoulou & Divans, 2009). Nevertheless, transformation of the conventional classroom into an authenticlearning environment involves much more than incorporating features of real-life situations into school work.

Furthermore, curriculum innovations are never easy to implement or to examine systematically. Balasooriya et al.,(2009) carried out a study on the impact of a new integrated medical educational design on students' approaches tolearning. Although, the program was based on curriculum features identified in the research literature to promote

deeper approaches to learning, the results indicate shifting students towards deeper approaches to learning may be a

more complex task than previously understood.

Krajcik et al., (1994) suggest that there are five features of PBL that help communicate the complexity of theinnovation in terms that are familiar to teachers. These are driving questions, investigations, artefacts, collaboration

and technological tools. This approach can be supported by multimedia and network technologies such as the

Internet. The introduction of microcomputers into classrooms has generated innumerable instances of such

innovations which involve considerable change in classroom management, lesson structure and student assessment.Powerful hardware and sophisticated software tools are enabling people to become more active learners about their

environment (Jackson et al., 1997).

Research has shown that students can make significant gains when computers are incorporated in the learning

process. Computer-based technologies integrated in project-based learning are particularly useful for constructive

learning (Roschelle et al., 2000). Students instantaneously can see the results of their experiment. Computer

technology supports learning; it is especially useful in developing the higher-order skills of critical thinking, analysisand scientific inquiry (Roschelle et al., 2000). But the mere presence of computers in the classroom does not ensure

their effective use. Many factors influence how and who learns in the classroom: (1) active engagement, (2)

participation in groups, (3) frequent interaction and feedback and (4) connections to real-world contexts. Omale et

al., (2009) performed a study to investigate how the attributes of 3-D technology affect participants' social, cognitiveand teaching presences in a PBL environment. The results indicated that although the attributes of 3-D technology

promoted participants' social presence, additional technical and instructional features of the 3-D environment were

required to further enhance cognitive and teaching presence leading to overall learning experience. Some of the pioneers in learning research believe computer simulation when used effectively has the potential to address these

related factors (Blake & Scanlon, 2007).

Educational Simulations

Simulations as defined by Alessi and Trollip (2001) are a representation of some phenomenon or activity that users

learn about through interaction with the simulation. Simulations offer an easy way of controlling experimental

variables, opening up the possibility of exploration and hypothesizing. Simulation is also valuable in presenting

many types of representational formats including diagrams, graphics, animations, sound and video that can facilitateunderstanding.

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Pea’s framework of distributed intelligence suggests that computer-assisted simulations have the potential to

reorganize mental processes by closing the temporal gaps between thought and action and between hypothesis and

experiment. Pea has proposed that by allowing the user to engage in "what-if thinking" through a partnership

between user and technology, deep qualitative effects are made possible on how problem solving occurs (Lebow &Wager, 1994). From an instructional design perspective, educational simulations support predetermined learning

outcomes by providing participants with opportunities to deal with the consequences of their actions and to respond

to feedback. In other words, the simulation construction kit is a laboratory for scientific inquiry, for exploration,explanation and testing. STELLA, which stands for Structural Thinking and Experiential Learning Laboratory, with

Animation, seems to facilitate this disciplined approach to inquiry (Steed, 1992). Understanding how a simulation

construction kit, like STELLA, can be used to refine thinking is important. Simulation models are simplified

representations of real-world systems over hypothetical time. Using simulation software, characteristics of selected

variables can be altered and their effects on other variables and the entire system assessed (Steed, 1992). STELLA isa program designed to assist users in creating their own simulations using system dynamics. One needs to think in

terms of dynamic processes, positive and negative causal loops, flows, accumulation and converters. STELLA is one

technology that can enable individuals to enhance their understanding of and appreciation for the complex web of in-terrelationships that govern environmental behaviour (Peterson, 1985). The real value of the STELLA modelling

package is the cognitive processing that goes on in the creation and development of its model. Good science is good

questions. Through creating simulations one has to generate good questions and as the simulation evolves interestinginquires are naturally pursued.

The simulation modelling generally takes two forms. Depending on the courses, students are (a) required to developtheir own models of scientific phenomena, or (b) given existing models and are asked to alter particular parameters

to examine the subsequent effects on the entire system. These two distinct approaches to modelling are likely to

produce different cognitive outcomes in terms of content knowledge and general problem-solving skills. In this

paper, we are considering interactive simulations (Blake & Scanlon, 2007) that allow students to change some of the parameters in the program and observe what happens as a result. Although theory supports using technology to

engage students in project-based learning, and the literature provides descriptions of suitable classroom technology

to engage students, we have few case studies of middle-school teachers describing their development and effective

use of simulation in educational learning (Blake & Scanlon, 2007 and Steed, 1992). In fact, with the re-emergence ofexperiential learning as a dominant model of learning in education and the recent research on infusing information

technologies into classrooms, it is a good time to examine the effectiveness of project-based learning integrated with

computer-based simulation.

The study reported here explores the effectiveness of the project-based learning which takes advantage of simulationexperiment. The following research question was proposed: How effective is the reality-based project in engaging

students in meaningful learning and enhancing their motivational attitude, especially when integrated with computer-

based simulation?

A science project, Land-use in Watershed, funded by the National Science Foundation (NSF) was developed to

investigate this research question. The project was integrated with STELLA simulation software to enhance deeperunderstanding for students. Land-use in Watershed was a collaborative science project which was developed by the

researcher for the Kansas Collaborative Research Network (KanCRN).

Method & Aims

Procedure & Sample

The participants of this study were 72 sixth to eighth graders, (32 males and 40 females). All students attended Northwest Middle-school, Kansas city, Kansas at the time of the study. Three separate multi-age classrooms were

included in the study. The multi-age classrooms were randomly allocated to one of the three treatment groups.

Students from all groups read the project materials on-line through KanCRN and benefited from on-line learningfeatures such as collaboration with peers, finding definitions of related terminologies and using hyperlinks to

additional information. Teaching material was delivered by the same teacher. Students were pre-tested with respect

to their understanding of the watershed concept and their content knowledge. The first treatment group (n 1=19) the

Project-Based group (PB), were taught the subject by receiving a traditional lecture. The second treatment group(n2=33), the Project-Based Experimental Simulation group (PBES), were taught the subject by performing an

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experimental model and a simulation model. The third group n3=20, the Project-Based Simulation group (PBS),

performed a simulation model but not an experimental model. Students were further divided into sub-groups of three

or four within each classroom based on their pre-test score in order to improve learning while obtaining homogenous

groups.

The researcher prepared a lesson on the “effect of land-use on the watershed” in which she designed an experimental

model of the watershed using sponge and cardboard. Two simulation applications using STELLA software were alsodesigned by the researcher to further emphasize the concept of watershed and in particular the effect of land-use on

runoff. The first application represented the experimental model and was created using experimental data obtained

from the sponge-cardboard experiment (STELLA1). The second application was more advanced and was created by

real data from a watershed (STELLA2). The simulation models played a role as a supplemental tool for practicing

“what if scenarios” by manipulating interacting factors and understanding the impact of important parameters on thewatershed.

Hypotheses

The first null hypothesis (H01) is: gain in students’ content knowledge is the same between groups. The second nullhypothesis (H02) is: students’ comprehension knowledge is the same between groups.

The third null hypothesis (H03) is: students’ attitude towards the project is the same between groups.

Instruments

A 58-question student survey was used to collect four types of information:

I. Eight true/false questions; used in statistical analysis to test gain in content knowledge.II. Seven open-ended questions to test students’ understanding of the watershed concept.

III. Twenty-three multiple-choice questions that tests the students’ attitude toward the project.

IV. Five true/false questions that gathered information about students’ computer background knowledge.

In addition, information about the amount of time spent on reading the project on-line, type and amount of small-

group interaction and number of requests for help in different parts of the project were collected by observation.

Results

The design of the study included three independent factors: gender (male or female), grade (sixth, seventh or eighth),treatment (PB, PBES or PBS) and computer background as a categorical covariate on the 5-points Likert scale.

The dependent variables consisted of three measures: content knowledge; comprehension of the subject; students’attitudes towards the project.

The results of a one way ANOVA test failed to reject H01 (Pvalue >0.05) and therefore conclude that the gain in

students’ content knowledge is not significantly different between groups (Table 1). In contrast H02 was rejected at

5% significance level, hence students’ comprehension knowledge is significantly different between groups (Pvalue =

0.002). A Post Hoc test result indicated that students in the PBES (mean = 8.61, SD = 2.42) treatment groupsoutperformed the other two groups (PBS; mean=5.45 SD=3.78 & PB; mean=4.16 SD=2.52) on subject

comprehension.

Table 1: Mean change and significance level of comprehension knowledge between treatments

Treatment (I) Treatment (J) Mean (I-J) Sig.

Project-Based Experimental Simulation Project-Based Simulation 3.162 .002Traditional 4.450 .000

Project-Based Simulation Traditional 1.294 .692Based on observed means. The mean difference is significant at the .05 level.

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Second, analysis of interaction between gender and treatment showed that there were no significant interaction

effects between the PB and PBES groups within the male category while the females in the PBES group performed

significantly higher than the females in the PB group. This interaction between gender and treatment variable

indicated that the project had a stronger effect on females and led to the higher mean score for the PBES group incomparison to the PB group.

Further analysis suggested that the gain (value added) in students’ comprehension of the watershed concept wasindependent of the students’ grade-level.

Students’ attitudes toward the project, especially toward STELLA simulation, were promising (85%). Students who

experienced STELLA units and enhanced their understanding about the watershed through this activity found the

reading part of the project that they encountered prior to the STELLA lesson less difficult.

The analysis of data on students’ computer background indicated that only 2% of the students have never used a

computer before, 61% of students use a computer at home, 76% of students had previous experience with computersimulation, but 80% of students had never worked with STELLA.

Figure 1: Students’ comprehension gains by treatments for male and female

Discussion

This study emphasizes on two important and interesting findings. First result indicated that although the PBES

performed significantly higher than the PB class, the PBS group which used computer-based simulation but did not perform the experimental part of the project (Sponge-Cardboard model) and consequently could not benefit from the

project to its full potential did not score higher than the PB class. According to NCTM, (Linn et al., 2000, pp. 25)

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this would further emphasize that “technology should not be used as a replacement for basic understandings and

intuitions; rather, it can and should be used to foster those understandings and intuitions”. Furthermore, the PBES

groups outperformed the PBS as well. However there was no significant difference between the two classrooms

treated with PBES.

Simulation and its Role

An explanation of the high performance of the PBES group could be due to the experience they gained first through

the experimental model of the watershed which generated data for modelling the first STELLA application

(STELLA1), and enhanced deeper appreciation of a more advanced and complicated model (STELLA2). Many

studies have identified the benefits of combining technology and other materials, such as construction kits or hands-on experiments for projects to make projects successful (Linn et al., 2000). For example modelling environments

such as Model-It combine the strengths of technology with opportunities for personal data collection. Technology

can support and encourage those projects and activities that are more meaningful to students (Roschelle et al., 2000).Research indicates that simulations can play an important role in science learning, however their use is not as

straight-forward as it seems. Many researchers emphasize the importance of a good instructional plan when using

simulations. They argue that despite their popularity in instruction, the lack of support for learners in somesimulations is the reason for finding no conclusive evidence for effectiveness and efficiency of simulations (Blake &

Scanlon, 2007).

PBL and Interactions

In the PBES treatment group there is more opportunity for collaboration during the experiment and simulation, hence

more interaction between students, and also with the teacher and the model compared to the other two methods. This

finding also supports Schutte’s (1997) suggestion that the enhanced levels of interaction with other students and theteacher results in greater efficacy of computer-mediated communications. Another study demonstrates that all

learning activities such as constructive, self-directed and collaborative learning occur as a result of verbal

interactions through PBL environment (Yew & Schmidt, 2009).

Two factors explain reasons for improvement of problem-solving skills in a group work (Teaching Professor, 2009).

One is the knowledge that students acquire from other students' explanations and another is the students' involvement

to solve the problem causes them to think more deeply about the problem and its solution. Other findings report thatsuccessful innovative programs improve instruction for all students and have the greatest impact on those who are atgreatest risk for learning less (Linn et al., 2000). Chu et al., (2009) indicate that in spite of most e-learning platforms

that offer theoretical knowledge content, a problem-based e-learning (PBeL) model which incorporates the PBL

theory, social constructivism, and situated learning theories assist teachers in effectively developing practicalknowledge for mathematics teaching for students with mild disabilities.

On the other hand, according to Linn et al., (2000), adding technology to science instruction has the danger ofincreasing biased stereotypes and promoting the idea that these are male domains; however, if used effectively,

technology can connect science to problems that interest individuals who have been assumed under-represented in

science careers. As Linn et al., (2000) indicate, although there is often a belief that male students may make greater

usage of information technology, some studies suggest that females and members of various cultural groups who

have fewer opportunities for learning science and mathematics in the elementary and middle school in traditional

practice can benefit from new technological innovations where students work in groups, and therefore males andfemales have equal contributions to the discussion. Likewise, these reports support the second finding of this study.

The interaction between gender and treatment variable indicated that the project had a stronger effect on females and

led to the higher mean score for the PBES group in comparison to the PB group. In contrast, the PBES treatment hadno significant effect on the male students (Figure 1). Basically, this interesting finding supports a few researchers’

views and requires additional investigation. Figure 1 shows the average score gained for males and females by

treatment group.

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PBL and Critical Thinking

Overall, the findings of this study supported the use of the project-based experimental simulation on learning

outcome. The result of this study indicated that the students’ comprehension of the watershed concept had improvedas a result of the innovative approach, although it did not improve students’ content knowledge (multiple-choice

questions) significantly. One possible explanation for this finding is the lack of sufficient time to cover multiple

concepts in the PBES groups. While the PBES groups spent their time on various activities to comprehend a fewconcepts deeply, the PB group focused on direct instruction for receiving and memorizing multiple concepts. This in

turn will explain why PBES students performed better in comprehension. Examination of these students’ responses

indicated that they achieved better and deeper understanding of the watershed concept. They were able to interpret

the graphs of runoff, absorbed water in the ground and inflow correctly and in more detail. Similar results were

obtained in the study by Şendağ and Ferhan (2009). This study investigated how the online PBL approach employedin an online learning environment influenced undergraduate students’ critical thinking skills and content knowledge

acquisition. The results indicated that learning in the online PBL group did not have a significant effect on the

content knowledge acquisition scores but it had a significant effect on increasing the critical thinking skills.

Furthermore, this finding is consistent with the report provided by NSF (Linn et al., 2000) on The Middle School

Math through Applications Project (MMAP), a series of project-based units that offers the most technology-intensivemiddle school curriculum. MMAP uses the HabiTech application, a simplified version of STELLA. According to

NSF, the evaluation of this unit of MMAP was very positive, indicating that the unit met the visions of the 1989

NCTM standards, engaged students and enhanced mathematical communication in classrooms. Roschelle et al.,(2000) also agreed that innovative computer-based simulation demonstrated significantly higher gains compared to

those receiving only traditional instruction.

Moreover, it has been concluded that the gain in students’ comprehension of the watershed concept was independent

of the students’ grade-level. This finding further emphasized that the multi-age computer-mediated group as a whole

performed better in comprehension than the multi-age traditional group due to the treatment effect.

The promising students’ attitudes toward the project, especially toward STELLA simulation, might be due to their

positive perception of the whole project afterwards. The NSF’s evaluation report also indicated that MMAP has positive effects on students’ attitudes as well as on their performance (Linn et al., 2000).

Research Role

Research is moving ahead to introduce the computer into the classroom to ensure this technology is used effectively

to enhance learning. Research should also help teachers to teach with technology rather than to use computers for

personal productivity. Teachers, especially, need pedagogical content knowledge which refers to knowledge abouthow students learn from materials infused with technology. Successful technology use and effective learning for

science teaching is dependent on the teachers’ knowledge of the technology itself, and how a particular tool is best

utilized for particular purposes, classroom or laboratory settings, and students themselves (Hennessy, 2006).Simulation encourages the student to interact with the variables, understand their sensitivities and appreciate how a

change in one variable results in changes in other variables. However, we have shown here that the success of

simulations as effective learning tools is dependent on how simulations are used. Finding ideal uses of technology in

science instruction remains an active research area, and the technology itself is a “moving target,” as new projects

emerge on a regular basis. As Chiocchio and Lafrenière (2009) recommend, teamwork and technology are becoming

important components of PBL in academic settings but fostering computer-assisted teamwork is complex and timeconsuming. Knowing how and when to intervene would prove useful. Finally, research demonstrates that

technological tools can enhance learning in science and mathematics, in a PBL setting, since they allow more

personalized and project-oriented commitments (Linn et al., 2000). According to Hakkarainen (2009), PBL offers agood model to support students’ knowledge and skills, and students will benefit from learning with and about

technology such as computer-based simulations in science and mathematics instruction. Nevertheless, effective

incorporation of these technologies into the curriculum has been controversial, difficult and demanding.

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Conclusion

In conclusion, the method by which features of project-based learning should be implemented to have its full impact

on learning requires further investigation. Also as it was noted, many studies suggest that project-based simulationsfor visualization and modelling have transformed some fields of science and seem promising for elementary and

middle school instruction. However, research indicates that incorporating computer-simulation modelling into

project-based learning requires careful planning and implementation. Recent research demonstrates simulations ofcomplex relationships, such as graphs of change over time, connections between components of a geometricconstruction, and location of a local minimum in a three dimensional surface can help students learn these difficult

topics. At the same time, considerable research suggests that all simulations are not successful. Often simulations fail because they are too complex or too difficult to understand. In fact, in replicated studies, researchers have noted

significant improvements in students’ understanding of scientific concepts and motivation when using simulation

software, but few studies elaborate on reasons of its failure or underling success.

In this study, the researcher administered the same simulation model to both groups PBS and PBES and conduct anexperimental model only to one group (PBES) in order to demonstrate that although the structure and the design of

the STELLA models were the same and presented similarly to both groups, the PBES group significantly

outperformed PBS. Nevertheless, the number of interactions of students with the simulation models and themselves

also increased as a result of deeper insight gained with experimental model in PBES.

This research suggests that once the learners learn the bases of using simulation, in this case through experimentalmodel, it enables them to interact efficiently and effectively with the more complicated models. In other words,experimental model in this study helps the students to understand how primary data and flows operate in the first

simulation model (STELLA1) because the model was built upon those data, therefore allowing them to build up

deeper intuitions into the simulation model and its role, which in turn pursue them to appreciate more advanced

subjects that is impossible to perform in natural settings, through a more complicated simulation model (STELLA2).

This is an analogy for learning a new language by learning bases of vocabularies and grammatical rules which resultsin writing more sophisticated sentences, in comparison with learning through environment. This study also suggests

that students learn best by actively constructing knowledge from a combination of experience, interpretation and

structured interactions with peers when using simulation in a PBL setting. This is only possible by a careful step by

step instructional design in which simulation model should solely be considered as one component of whole pedagogical structure of the PBL. The challenge is to ensure that simulation is used effectively to enhance how and

what children learn. Careful planning is required for constructing a project to be purposeful and uses technology

specially computer simulations such as STELLA in a constructive, real-world manner. Simulations do not work ontheir own, there needs to be some structuring of the students' interactions with the simulation to increase

effectiveness, as it was initiated through experimental model causing to raise the quality and quantity of

interactions with the STELLA models.

Hence, the first important finding of this research indicates that simulation models such as STELLA are used to

expand students' experience of experimental science and should not be used as a substitution for basic

understandings and intuitions; one can promote students to higher level STELLA model only when they learned the

basic role of STELLA. . The second important finding advocates that in spite of common belief that the use oftechnology is male dominant activity, a few studies such as this paper suggest females and those who are at risk for

learning less in traditional practice can benefit from new technological innovations. This study strongly suggests

further research in this area.

In addition, it should be noted that the experimental model may only be one way to promote students’ understandingof and interactions with STELLA model in this PBL. As an enhancement to this project, development and evaluation

of further PBL in which students are required to create their own STELLA models (integrating developing

simulations not interactive simulations) instead of using experimental models is highly recommended. Computermodel developments are mirrors of one’s own mental development. Model building is an interactive process; moving

from identification of causal loops to computer simulation provides deep involvement in the topic and consequently

deep understanding of the subject as well as STELLA mission.

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Furthermore, it is recommended that further research be conducted with randomly selected participants to be truly

representative for the study. Also, as this study suggests, it would be desirable to have a clear measure of

effectiveness before committing to continual investment in technology.

Nevertheless, it is important to note that the results of this study are limited to the integration of simulation model, in

particular STELLA, in a PBL settings and cannot be extended to all kind of educational technologies nor to other

learning strategies.

Acknowledgment

We would like to acknowledge and extend our gratitude to Dr. V. Simonite and Dr. R. Long for their comments and

corrections.

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