Learning through creating robotic models of biological systems

Learning through creating robotic models of biologicalsystems

Dan Cuperman • Igor M. Verner

Published online: 3 February 2013� Springer Science+Business Media Dordrecht 2013

Abstract This paper considers an approach to studying issues in technology and science,

which integrates design and inquiry activities towards creating and exploring technological

models of scientific phenomena. We implemented this approach in a context where the

learner inquires into a biological phenomenon and develops its representation in the form

of a robotic model. Our multi-case study involved middle school students and prospective

teachers. We considered learning processes, in which the learners used PicoCricket robot

construction kits to create a variety of bio-inspired robotic models. We present two such

models and the teaching strategy which organizes modeling activities into five learning

stages. Based on analysis of learning activities and their outcomes along with the studied

cases, we explored characteristics of the learning environment and of the proposed inte-

grative teaching approach. The findings indicate the potential of modeling as a thread,

tying together engineering design and scientific inquiry into an integrative learning

activity.

Keywords Science–technology education � Design � Inquiry � Robotics �Biological system � Modeling � PicoCricket

Learning by design and inquiry

Recent literature explores strategies of incorporating emerging technologies into science

education, aiming to foster higher order thinking skills by leveraging multiple media and

establishing realistic inquiry-based contexts (Dede and Barab 2009). The effectiveness of

the technology enhanced science education in schools is widely recognized, but is often

determined solely by the utility of providing only technical support for the learning pro-

cess. With this, there are calls emphasizing additional potential benefits of the

D. Cuperman � I. M. Verner (&)Department of Education in Technology and Science, Technion––Israel Institute of Technology,32000 Haifa, Israele-mail: [email protected]

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Int J Technol Des Educ (2013) 23:849–866DOI 10.1007/s10798-013-9235-y

accommodation between science and technology education in the curriculum (Lewis 2006;

Fensham 2009).

Lewis (2006) proposes to study engineering design and scientific inquiry at school in

ways that utilize their complementarity and conceptual proximity. One way is to employ

design as a vehicle for teaching scientific content, and the other is to harness science as the

driving force for prompting design. Lewis suggests design as a bridge between science and

technology education towards achieving scientific and technological literacy. He calls to

achieve this goal by new interdisciplinary pedagogies ‘‘that are integrative in approach,

showing fluidity between engineering and science’’. In this regard, Fensham (2009) points

to the need to study technology as the real world context of science and as the way for

applying science to serve society. We acknowledge this notion and share Fensham’s

concern about the existing tendency of eroding and removing technological contents from

Science–Technology–Society (STS) curricula.

Resnick et al. (2000) emphasize yet another argument in favor of keeping the techno-

logical content in the curriculum: failing to do so may lead to a situation in which tech-

nological systems utilized in science education are grasped as ‘‘opaque’’ black boxes,

without understanding the principles of their operation. To avoid this circumstance, the

students should be nurtured to ‘‘look inside’’ the technological artifacts in the world around

them and develop their own tools for exploring phenomena in their immediate

environment.

Researches explore possible ways for aligning between learning by design and learning

by inquiry in the middle school science and technology curriculum. Kolodner (2003, 2009)

analyzes learning-by-design processes, in which the learners, triggered by an explicit

design challenge, ‘‘mess about,’’ generate ideas, identify what they need to inquire, collect

data, and gradually build artifacts. Kolodner presented a learning model that combines

design and inquiry activities organized in two connected cycles: the ‘‘Design\Redesign’’

cycle answers the ‘‘need to do’’ while the ‘‘Investigate & Explore’’ cycle answers the

‘‘need to know’’. Kolodner’s learning model is grounded on the principles of construc-

tionism (Papert 1991) arguing in favor of involving the learner in the creation of artifacts

that serve as ‘‘objects-to-think-with’’. In the cases presented by Kolodner (2003), design of

technological artifacts was motivated by the need to understand scientific concepts.

When acting towards integrative teaching of natural science and technology through

binding design and inquiry, or in any other way, we need to take into account the different

nature of the two domains. Science focuses on natural phenomena, while technology deals

with man-made creation (Ropohl 1997).

International Technology Education Association (1996, p. 15) defines the relationship

between science and technology from the perspective of symbiotic interdependence:

‘‘Science is dependent upon technology to develop, test, experiment, verify, and apply

many of its natural laws, theories, and principles. Likewise, technology is dependent upon

science for its understanding of how the natural world is structured and how it functions’’.

Other manifestations of the relationship between science and technology can be seen in

historical and contemporary practice of science and engineering (Verner and Cuperman

2010). Both science and technology implement solutions borrowed from one another. The

history of science and technology provides many examples of the human desire to create

artifacts that mimic solutions existing in nature or, furthermore, attempts to improve them.

One such example is the aspiration to imitate bird flight, which motivated Leonardo da

Vinci’s invention of flying machines (Cianchi 1988); similar aspirations paved the way to

the development of bionics.

850 D. Cuperman, I. M. Verner

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Robot design as well, is greatly influenced by the attempt to imitate appearance,

functionality and behaviors of nature-made creatures and, in particular, the human loco-

motion and intelligence. In the opposite direction, science is trying to understand and

explain natural phenomena by exploring existing, or specially developed technological

systems. Neuroscience, for example, uses principles of ‘‘information processing theory’’,

which explains mental functions by exploring computer operation (Miller 2003). The

above mentioned manifestations are explicitly based on analogies between natural and

technological systems. Researchers note that exploring such analogies not only facilitates

the development of science and technology, but can also make a strong contribution to

education (Gilbert et al. 2000).

This paper proposes a model of integrative teaching of science and technology through

practice which involves the learner in investigation and exploration of a biological system

along with the design and construction of its robotic model. Technology educators consider

integrative teaching as a way to consolidate knowledge of concepts from different disci-

plines through applied learning experiences (Wan 2007). Following this view, our

approach aims to set a common ground for studying reactive behaviors, i.e. behaviors

manifesting responses of biological and robotic systems to external events.

Learning with robotic models

Gilbert et al. (2000, p. 15) consider learning with models as a promising approach to bridge

science and technology. As noted, the place of this approach is well established in science

education, but yet to be determined in the design and technology education. de Vries

(2006) in his review of Gilbert’s book points out that technology education can develop its

own understanding of models and modeling practices by inferring from the experience

acquired in science education.

Elmer and Davies (2000) argue that the purpose of modeling activities in design and

technology education is more than acquisition of technical capabilities; it includes

development of thinking skills. The same view underlies the concept of digital manipu-

latives introduced by Resnick et al. (1998). Accordingly, manipulative materials with

embedded capabilities for sensing, computing and communicating open opportunities for

creative construction of technological systems and foster systems thinking.

A key feature of a digital manipulative is that it can be programmed to demonstrate a

reactive behavior. In educational practice, the inspiration to develop a digital manipulative

and program its behavior usually comes from the desire to reflect on phenomena and

imitate behaviors existing in the world around us. Thus, the digital manipulative serves as

the object-to-think-with in learning practices of its construction, programming, and

exploration. We consider such a digital manipulative to be in essence a robotic model

which is both a technological system and a representation of a phenomenon. Learning with

a robotic model can occur in two domains: one in which the model is designed, built,

operated and evaluated as a technological system, and the other, in which the model is

understood and assessed as a representation of a phenomenon.

International Technology Education Association (2000, p. 102) considers a model as ‘‘a

replica of an object in three-dimensional form,’’ created to answer a certain need. From this

perspective we see the robotic model as designed to satisfy the need for a tangible rep-

resentation by which concepts and processes related to the biological system can be

learned, tested and communicated. As such, the robotic model design is directed not only

towards technological efficiency. It also represents the designer’s perception of the

Biological systems 851

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source––a personal expression which is typical for artistic design (International Technol-

ogy Education Association 2000, p. 90).

The concept of robotic model can be better understood when contrasting it with the

concept of model commonly used in science education. A suitable way to make this

comparison is in terms of the following categories used by Ropohl (1997) for the com-

parative analysis of knowledge types in science and technology:

• Models in science education are objects usually presented in a generalized symbolic

form. Physical models, and especially dynamic ones, are rare and mainly used as visual

aids (Lipson 2007). A robotic model, on the other hand, is a dynamic physical object

which facilitates learning through hands-on activities of its construction and operation.

• The objective of modeling in science education is to assist understanding of phenomena

and share knowledge (Seel and Blumschein, 2009). Practice with a robotic model

serves an additional purpose of fostering systems thinking through devising an artifact

(Resnick et al. 1998).

• Regarding the methodology, a model in science education is treated as an ideal

representation, while practical considerations are overlooked. Robotics education, in

contrast, deals with models that function in the real world.

• Regarding the characteristics of results, the outcome of modeling in science education is

a representation of a conceptual model in learner’s mind. Modeling in robotics education

prompts several outcomes: mental representation of scientific and technological

concepts, and creation of a robotic model which is a physical expression of the concepts.

• Criterion of quality of a model in science education is its suitability to promote the

acquisition of valid conceptions while avoiding misconceptions. A robotic model

answers yet an additional criterion of proper functioning.

To summarize the comparison, a robotic model can feature as a science model with the

added value of being a real technological system. In the context of this study, the learner,

being engaged in devising a robotic model that represents a biological system, develops

mental representations of concepts related to the biological and robot systems.

The proposed approach to learning with robotic models goes beyond robotics courses

that concentrate on building simple mobile robots and programming their basic movements

in response to sensory input. We follow the new strategies for introducing students to

robotics, as recommended by Rusk et al. (2008): focusing on themes, combining art and

engineering, encouraging storytelling, and organizing exhibitions.

In our case, creation of a robotic model of a phenomenon is a theme which combines

engineering thinking with personal artistic expression. The developed robotic model is

used not for competition, but serves as a tangible exhibit which assists storytelling concepts

of science and technology.

Rusk et al. (2008) noted that there are different robot construction kits, each of which

supports some type of activities and learning styles better than others. In this regard, the

authors recommended the PicoCricket kit for implementing alternative learning pathways

into robotics: ‘‘to combine art and technology, enabling young people to create artistic

creations involving not only motion, but also light, sound, and music’’.

Modeling biological systems

In our approach, biological inquiry and technological design are connected for the purpose

of creating a robotic model of a biological system. To understand this connection, there is a


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need to clarify the meaning and function of the inquiry and design practices in our context.

According to National Research Council (1996 p. 23), scientific inquiry is a multifaceted

activity that involves, among other things, ‘‘making observations; posing questions;

examining books and other sources of information to see what is already known’’. In the

context of modeling a biological system, the function of observations, questioning, and

information search is to identify and understand the features of the system that are relevant

to the model design. The design practice is defined in the Standards for Technological

Literacy (ITEA, 2000, p. 118) as a process that includes the following steps: identifying the

need, generating ideas, exploring possible solutions, building and testing prototypes, and

refining the solution. As already mentioned, the robotic model design answers the need for

a tangible representation, by which the features of the biological system can be learned,

tested and communicated. Therefore, the ideas, solutions and prototypes developed

throughout the design steps are verified by matching them with the features of the bio-

logical system, revealed by the inquiry.

Based on the discussed view of learning by modeling, we developed the course

‘‘Control in Technological and Biological Systems’’ and delivered it to prospective

teachers of science and technology, high school and middle school students.

The course consisted of 14 weekly meetings of two hours each, and dealt with the

following topics: introduction to robotics (2 h), basics of building and programming using

the PicoCricket kit (4 h), sensors and control (4 h), DC motors and mechanical trans-

missions (4 h), inquiry into a biological system (4 h), creation of a robotic model (8 h),

presentation and evaluation of the robotic model (2 h).

Dozens of robotic models were developed by our students in the framework of teacher

training and outreach courses. The models featured topics such as: plant tropism, animal

behavior, control in biological systems in general and homeostasis in particular.

All the models (some of which are described below) were built using the PicoCricket

robot construction kit. The kit consists of a programmable microcontroller that can operate

different actuators and manage input from various sensors. The microcontroller provides

bi-directional infrared communication with a host computer or other PicoCrickets. In

addition, data management capabilities are offered, with an opportunity to sample data

from the sensors, implement reactive behaviors, and upload the data to a computer for

graphical representation. These capabilities can further promote the use of the kit as a tool

for inquiry based learning. The PicoCricket ‘‘specialties’’, such as preprogrammed animal

voices, colorful lights, and craft materials, are useful for building robotic models of ani-

mals and other biological systems.

A venus flytrap model

Inquiry into the phenomenon

This project was performed by two pre-service teachers, who inquired the ability of plants

to detect and trap prey. The inquiry started with a basic question: How do some plants act

to trap prey? Through web-search the pre-service teachers found video clips of several

carnivorous plants that implement different trapping mechanisms. They chose to model the

Venus flytrap behavior and posed a more specific question: What is the mechanism of

trigger and movement in the plant? To answer the question, the pre-service teachers made a

deeper web-search and found two relevant articles. From the articles, they learned the

following features of the flytrap mechanism:


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Closure of the Venus flytrap is one of the fastest movements in the plant kingdom.

The trap consists of two lobes, which close together forming an enclosed pocket. The

center of each lobe contains three mechanosensitive trigger hairs (Pavlovic et al.

2010). When a prey crawls into the trap it bumps into the small trigger hairs. Two

touches of a trigger hair are needed to activate the trap which snaps in a fraction of

second. The closing process essentially involves a change of the leaf’s geometry. The

upper leaf is convex in the open position and concave in its closed position. The

driving force of the closing process is most likely the elastic curvature energy stored

and locked in the leaves (Volkov et al. 2007; Pavlovic et al. 2010).

Designing the model

The need was to develop a robotic model of the Venus flytrap plant which represents its

trapping mechanism as authentic as possible, within the limited means provided by the

PicoCricket kit. The design ideas, generated by the pre-service teachers, were based on the

features revealed by the inquiry and related to the ‘‘mechanosensitive’’ trigger mechanism,

the trap structure and movement. These ideas were implemented in the design solutions.

For the trigger mechanism the pre-service teachers used touch sensors supplied with the

kit. They designed a linear moving trap mechanism consisted of Lego parts driven by a DC

motor. For this purpose, several mechanical transmissions that convert rotary to linear

motion were evaluated. A crank mechanism was selected due to its simplicity and good

performance. A structure imitating the plant stem was also built from Lego parts included

in the kit. The final Venus flytrap model (Fig. 1) includes two touch sensors and a dc

motor, driving a crank that opens/closes the trap structure.

The pre-service teachers used the PicoBlocks software to design and program model’sbehavior. The program includes basic procedures such as conditions, loops and

subroutines.

The PicoCricket controller executes the main program, emulating the triggering process,

and the secondary trap activation module (Fig. 2). This module is executed in one of two

cases: if a simultaneous touch is sensed at both sensors or if any of the individual sensors is

touched several times. The motor is then actuated to close the trap mechanism. After a

delay, the trap is reopened.

A

D

CB

Fig. 1 The flytrap model:A Sensors; B Motor and crank;C Trap mechanism;D PicoCricket


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Pulse rate control: a heart functional model

Inquiry into the phenomenon

This project was performed by three middle school students, who inquired the influence of

external stimuli on the heartbeat rate mechanism. The inquiry started with a basic question:

How is the heartbeat regulated? Through literature and web search the students learned

about the natural pacemaker located in the heart and about the normal heartbeat rate. The

students posed further questions: What external stimuli might be involved in increasing or

decreasing the heartbeat rate? What is the mechanism of this change? What is the

acceptable range of heartbeat rate? To answer the questions the students made a deeper

inquiry and found a relevant textbook. Using this book, they identified the following

features of the heartbeat mechanism:

Heart rate control is one of the means by which the volume of blood pumped by the

heart is regulated. This control function is managed by the autonomic nervous system

(sympathetic and parasympathetic nervous systems). Strong sympathetic stimulation

(stress state) can increase the heart rate from a normal rate of 70 beats per minute up

to 200 beats per minute, while strong parasympathetic stimulation (rest state) can

decrease the heart rate to 20-40 beats per minute (Guyton and Hall 2006).

Designing the model

The robotic model of the heart was designed to represent visually and audibly the heartbeat

mechanism as authentic as possible, within the limitations of the PicoCricket kit. The design

ideas and solutions, generated by the students, utilized visual and audio effects to simulate the

Fig. 2 The PicoBlocks program for driving the flytrap model


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dependency of heartbeat rate on changes in the external environment. For sensing the external

environment the students used sound and light sensors supplied with the kit. They designed a

mechanism that expanded and contracted in a controllable rate. The Lego structure was driven

by a DC motor and was covered with a heart-shaped red fabric skin (Fig. 3). Several

mechanical structures were designed and tested until a satisfactory visual effect of a beating

heart was achieved. A sound box was added to emulate the heartbeat sound.

A PicoBlocks program was designed to facilitate the model ‘‘behavior’’. The

mechanical structure repeatedly contracted and expanded while each repetition was

accompanied by a heartbeat sounds. In idle state, repetitions were at a rate of 70 cycles per

minute. When surrounding light dropped below a preprogrammed threshold, the model

responds by switching to a ‘‘rest’’ state, in which the rate of repetitions gradually dropped

to 40 cycles per minute. In response to loud noise, the model switches to a ‘‘stress’’ state, in

which the rate of the ‘‘heart’’ beats jumps up to 120 times per minute. When loud noise is

discontinued, the rate gradually decreases, until reaching the idle state.

Educational study framework

Research aim and questions

Our research was directed to develop and explore an educational approach which involves

the learner in investigation and exploration of a biological system along with the design

and construction of its robotic model. The research questions posed were:

• What are the specific features of learning through the proposed approach?

• What are students’ attitudes towards this learning practice?

Participants

The study involved four categories of participants:

• Prospective teachers (N = 41) majoring in science or technology education at the

Department of Education in Science and Technology, Technion.

D

B C

A

Fig. 3 The heart model:A Sensors; B Heart mechanism;C Sound box; D PicoCricket


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• Middle school students (N = 21) who were finalists of the nation-wide science-

technology competition OlympiYeda (Verner et al. 2012).

• Middle and high school students (N = 40) learning in an enhanced science program at

schools in Haifa.

• Middle school students (N = 44) learning a regular science program at schools in

Haifa.

Method

To answer the research questions, we applied the grounded theory methodology (Glaser and

Strauss 1967). The constant comparison procedures of data collection, refinement, and

categorization were focused on robot project design, learning activities, outcomes, and

perceptions of learning with models. In these procedures we applied the qualitative inductive

reasoning method (Lodico et al. 2006, pp. 4–21), so that the bottom-up process was directed

to get insight into the project stages, the specific features of the learning activities, the

progress in acquisition of technological and biological concepts, and the reflections of

prospective teachers and school students on the practice of learning with models.

A multi-case study framework (Yin 2003) was used to enhance internal and external

validity of the study, by implementing the proposed approach to different categories of

learners and by triangulating the findings of different case studies.

Data collection and analysis

Narrative and numerical data in our multi-case study were gathered through participant

observations, document and artifact analysis, interviews and questionnaires. To enhance

internal validity of each case study, the mixed methods analysis (Lodico et al. 2006,

pp. 280–288) was used, so that data of different types were triangulated and used to present

the proposed approach from several perspectives.

At the beginning of our research, in the case study with prospective teachers of tech-

nology, we conducted pre-course and post-course semi-structured questionnaires that

addressed students’ experience in learning and teaching with models. More detailed

reflections were gathered by semi-structured interviews. The data were coded, analyzed

and categorized, while the obtained categories were used as focal points for the subsequent

case studies with school students and prospective teachers. For example, one of the cat-

egories pointed out the need to outline limitations under which the model is valid. In the

subsequent case studies we acted to find out how can students learn from those limitations.

For this purpose, we developed a special questionnaire that requested students to explicitly

compare the robotic model with the source biological system. The questionnaire requested

the student to give a written description of the robot and biological systems, and explain

similarities and differences between the systems with regard to appearance, functionality

and structure. It also asked the student to evaluate the model authenticity. Further analysis

and coding of the responses related to model limitations led to formulating a characteristic

feature of the learning practice, described in the next section, together with other findings

obtained in the same way.

Document and artifact analysis relied on project reports, in-class presentations, and

model evaluations. We searched for commonalities in the staging of different projects and

for indications of scientific and technological competences applied when creating the

robotic models. Results of this analysis were supported by the evidence collected through

observation of inquiry and model construction activities.


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Findings

Stages of learning by modeling

Learning activities included in our robotic modeling projects can be commonly divided

into the following five stages:

1. Acquiring technological knowledge

The learners were provided with technological content knowledge essential for using

the construction kit and building simple robotic systems. In particular, the students

learned about sensors, control, simple mechanisms, motors, actuators, and intuitive

brick programming. When introducing concepts related to technological systems we

deepened into their scientific principles and explained them using their connection to

similar concepts related to biological systems. For example, when learning about

sensors, the broader aspect of sensing and senses in the animal kingdom was discussed.

2. Selecting a biological process

The students participating in each case study were assigned to inquire various biological

control mechanisms. In each of the case studies a certain type of biological processes was

selected as a featuring topic. Examples of the topics were given in ‘‘Modeling biological

systems’’. The students were assigned to inquire a specific biological control mechanism

within the selected topic. They had some freedom of choice for selecting what specific

biological process within the topic they would like to model. The students selected the

modeling tasks, while taking into account technological opportunities that can be provided

by the construction kit as a modeling tool. In one case study, for example, the students

selected from various phenomena of plant tropism, including heliotropism, phototropism,

gravitropism, and thigmotropism. The students examined ways to model those plant

behaviors using the light, touch, and resistance sensors available in the kit.

3. Inquiry into the biological system

After choosing the biological system, the learners (as individuals or team members)

were engaged in a self-regulated inquiry, in which they studied the biological concepts

and the characteristics of the nature phenomenon relevant for creating the robotic model.

When studying the biological concepts, special attention was paid to the biological

mechanisms to be imitated by the robotic model. Examples of such inquiries were

presented in ‘‘Modeling biological systems’’.

4. Building the model

After the acquisition of technological and scientific background and getting insight

into the natural phenomenon, the learners set to designing and building the robotic

model. The models were developed through rapid prototyping rounds, in which

characteristics of the model prototype were examined and improved to better resemble

those of the biological system.

5. Assessing differences and similarities

Once the model development was completed, the learners were assigned to

individually answer a questionnaire that asked to systematically analyze the analogy

between the model and the biological system. For example, when analyzing the heart

functional model described in ‘‘Modeling biological systems’’, the students evaluated

its resemblance to the human heart with regard to components (such as resemblance of

the robot mechanism to muscles), geometrical form (heart shape, color and size),

functioning (idle and trigger states), and control (natural pacemaker of the heart to the

PicoCricket controller).


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Features of learning practices

The features that repeated throughout the case studies were as follows:

1. We found that the students were highly motivated to learn scientific and technological

concepts and perform hands on activities. We observed that desire to build a robotic

model typically triggered students’ curiosity to the biological phenomenon and drove

the inquiry. For example, after learning about sound sensors and constructing a sensing

circuit, the students became curious to learn more on how the ear functions. Also, the

aspiration to implement the knowledge about the phenomenon and create a robotic

model motivated students to learn the needed technological concepts. For example,

interest to authentically imitate a tropistic mechanism motivated a search for an

appropriate mechanical solution. Those observations are reinforced by reflections of

both the prospective teachers and the school students participated in the study. A

recurring reflection was:

The method arouses motivation to learn. Working with the robotic kit was

attractive and interesting. The combination with scientific content was good

and helpful. (A student majoring in mathematics education).

2. A team of two or three learners was found preferable for providing self-expression and

opportunities of contribution, while still allowing the benefits of team diversity and

collaboration. As observed, the students formed the project teams by themselves. Each

student took leading in one of the three project areas: inquiry, building and

programming. A typical reflection:

The students benefit from learning in a team …The collaboration was good. I

enjoyed very much working with my partner and learned a lot from him, things I

didn’t know previously… It is better to work in pairs then to be part of a big

group. (A student majoring in physics education)

3. The models created by students through rapid prototyping were simple and usually

consisted of a controller, no more than two sensors, one electrical motor and

mechanicals. They tangibly illustrated the studied concepts and provided meaningful

analogies:

Studying theoretical concepts along with constructing their tangible models

helped to understand the subject more deeply. (A student majoring in physics

education)

The model provides plenty of analogies, largely regarding properties of its func-

tioning. (A student majoring in physics education)

In the process of constructing a robotic model that took not more than a few hours, the

students underwent the experiential learning cycle of agile technological prototyping

and scientific inquiry activities. As typically reflected:

When I built the model I went back and check the scientific concepts behind the

model. (A student majoring in technology education)

4. Throughout the case studies we observed that the exploration of similarities and

differences between a biological system and its model facilitated understanding of

biological and engineering concepts. In this exploration students dealt with questions

such as: What features of the biological system are essential for the model, and does


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the model authentically represent them? Can the model be improved to better represent

the system within the limitations of construction and programming using the

PicoCricket kit?

An example for such exploration is the process of perfecting the mechanism for

modeling tropistic movements in plants, observed in the Venus flytrap project. In this

model, described in ‘‘Modeling biological systems’’, the ‘‘trap’’ movement is

generated by powering an electric motor that changes the orientation of two ‘‘lobes’’

via a crank mechanism. Further inquiry of the trap closure in the plant revealed that its

mechanism is different and utilizes stored elastic energy to change leaf’s geometry.

This finding motivated the development of a more realistic mechanical solution in the

succeeding project that modeled a plant opening/closing mechanism. The developed

solution, that imitates the plant hydrostatic pressure movement mechanism, utilizes

pneumatic pressure to simultaneously unfold two ‘‘leafs’’ and move them apart, as

shown in Fig. 4.

To further facilitate integrative learning practice, we asked the students to evaluate the

similarities and differences between the model they built and its source. Analysis of those

written evaluations indicated that the students succeeded in performing this comparison.

Attitudes towards learning with models

Prospective teachers

Twelve prospective teachers answered pre-course and post-course questionnaires that

asked about their attitudes towards learning with models and about their prior experience

in this field. The questionnaire indicated that this prior experience was limited. More

than 66 % of the prospective teachers reported that, when studying at school, they were

not engaged in any learning activities with physical computerized models, while the

others had very limited engagement. Over 83 % of the prospective teachers stated that

they had little or no practice in building such models during their academic studies. In

spite of the limited experience, more than 83 % of the prospective teachers expressed

interest or strong interest to practice teaching with physical computerized models and

more than 66 % were willing to acquire practical experience in building such instruc-

tional models.

The post-course questionnaire repeated the questions on prospective teachers’ atti-

tudes towards learning with models, asked before the course. It also requested pro-

spective teachers’ recommendations about ways to incorporate physical computerized

models into learning activities, in the form of demonstrations with ready-made models,

experimentation with teacher-made models, and model development. The questionnaire

indicated that all the prospective teachers were strongly interested to build physical

computerized models and use them as teaching aids. With regard to incorporating

models into learning activities, more than 83 % of the prospective teachers recom-

mended in-class demonstrations and experimentation with ready-made models, while all

the students strongly recommended engaging learners in making models as part of

inquiry activities.

Results of the questionnaires are in line with prospective teachers’ reflections expressed

in the post-course interviews. The prospective teachers recognized the advantages of

learning with models, and especially, the value of models as means for visualizing dynamic

processes. A representative reflection was:


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There are things you can only visualize using physical objects, which you can touch,

change and play with. (A student majoring in technology education)

The prospective teachers stated that model making was easier than they expected, and its

educational benefits justified the effort:

The effort was justified. When you create, build something, this enhances the

learning process. (A student majoring in technology education)

School students

Pre-course and post-course questionnaires on attitudes towards learning with models were

conducted in the course delivered to high school students (N = 14). Before the course, all

the students expressed interest or strong interest to practice learning with physical com-

puterized models. They all were more interested to focus practical activities of the course

on building instructional models rather than on using pre-built models. Over 78 % of the

students assumed that practice with models will be helpful. After the course, all the

students stated that practice with robotic models, and especially designing and building

robots, really helped to learn the science and technology concepts of the course.

Learning outcomes

We witnessed students’ progress in learning technological concepts that was indicated by

the literate explanations they gave when presenting their models. For example, one of the

students, who built the heart model (presented in Modeling biological systems), described

her project:

The model contains sensors, a PicoCricket controller, a motor and a mechanical

system. The sensors collect data and send them to the controller. The controller sends

instructions to the motor that drives the mechanical system to contract repeatedly.

The program in the cricket controls the operation.

D

B A

C

Fig. 4 The plant model:A Pressure generator;B Pneumatic mechanism; C The‘‘leafs’’; D PicoCricket


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The use of biological concepts in students’ oral and written explanations was examined

with the assistance of biology teachers. The analysis revealed a gain in knowledge and

literate use of concepts related to the studied topic. For example, one of the students

participated in the team that built the heart model wrote in her knowledge questionnaire:

There is a region in the heart that is called a pace-maker. Its task is to regulate the

heartbeat. It sends electric currents to the heart that cause repeated contractions of the

heart muscle. The brain sends control pulses to the pace-maker. This keeps the blood

flow and the needed oxygen levels to the body while the body performs different

activities.

The teachers helped students to validate information that they collected and knowledge

they acquired through self-regulated inquiry. In some cases this was followed by an

intriguing discussion. For example, one of the students built a robotic model of the

sunflower heliotropism process, described in our previous paper (Verner and Cuperman

2010). When inquiring sunflower’s movement towards the sun (heliotropism), the student

found in literature that the flower-head movement is caused by differential translocation of

auxin (a plant growth hormone). The hormone causes greater cell elongation in the shaded

side of the stem, bending the stem and ending in the flower-head facing the sunny side

(Sherry and Galen 1998). When he presented this information to the biology teacher, she

first disagreed, arguing that the mechanism behind the phenomenon is probably related to

changes in hydrostatic pressure. Such changes in the pulvinus (a joint-like thickening at the

base of the stalk of a leaf) cause its expansion and lead to leaf movement. After a deeper

examination the teacher acknowledged that the explanation given by the student was

correct and that her version is relevant to leaf movement. Her input motivated inquiry of

other students who built the robotic model described in ‘‘Findings’’ and shown in Fig. 4.

Discussion

Based on the experience gained through the case studies, the following features of the

robotic modeling environment can be noted as essential for sustaining the proposed

learning process:

1. The learning environment should provide the integral infrastructure for both conducting

scientific inquiry and building robotic models. From our experience, in addition to

facilities for inquiry (web access) and modeling tools (robot kit, craft materials and

Fig. 5 A model gallerypresented to middle schoolstudents


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instruments for modular construction and programming), a gallery of previously

developed models serves as a worthwhile constituent of the environment.

The models in the gallery encompass a variety of inquiry themes and technological

solutions which can inspire students in developing new robot projects (Fig. 5).

2. A framework, in which teams share the same open workspace, facilitated active

interactions within the teams, between the teams and between the students and the

teacher (Fig. 6). In our course, team workplaces were organized to provide space for

individual and team activities, while collectively using facilities for inquiry and

modeling.

During the workshops the teams were free to communicate and discuss their ideas

and insights. The teacher’s guidance was directed to facilitate both inquiry and model

building activities. The teacher stimulated students’ inquiry by asking questions that

invoked further investigation and prompted the need for validation of results. During

the model building activities, the students were advised to ‘‘break-up’’ the modeled

biological system into smaller subsystems or elements, and come up with their tech-

nological analogies. The teacher was open to discuss possible technical solutions.

Based on the findings of the case studies, the following arguments can be posed in favor

of the proposed approach:

1. From the design and construction of a robotic model students can derive benefits that

cannot be obtained only by analyzing models built by others. This argument was also

pointed out by other researches (Milard 2002).

2. The interplay between construction and inquiry in the creation of a robotic model

serves as a motivating factor for learning of both science and technology. The

motivating effect of this interplay was noted in recent studies of technology enhanced

learning (Hsieh et al. 2008).

3. The practice of creating robotic models through rapid prototyping is an effective

learning strategy. Even though the analogy between the model (target) and the

biological system (source) is incomplete, student’s involvement in the analysis of

source-target similarities and differences facilitates learning of both robotics and

biology. Limitations of modeling tools can reinforce the challenges of the inquiry and

design-based learning. The educational value of such analysis is noted in literature

(Ming 2009).

4. Through the robotic modeling project the student can acquire knowledge and skills in

robotics and biology. In addition to specific competences, the student can develop

Fig. 6 Students sharing an openworkspace


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understanding of the core concepts of technological literacy related to design, the

nature of technology, and the abilities for a technological world. At the same time the

students can acquire skills of learning with models, skills which are considered to be

important components of science literacy (Hofstein and Lunetta 2004).

Conclusion

Our research is motivated by the need for new ways to bridge science and technology

education in middle schools. It proposes a learning environment, in which the study of a

scientific phenomenon prompts and inspires practical design activity, which in turn leads to

further learning of scientific concepts. Specifically, the students perform inquiry into

biological systems to acquire knowledge needed for creating robotic models. In this set-

ting, the robotic model becomes a ‘‘nucleus’’, which organizes and triggers the learning of

technology and science subjects around the modeling process. All the stages of this

modeling process, i.e. the model ideation, materialization and exploration, have their

specific educational roles.

The students are becoming involved in model ideation from the first experiments with

the robot kit, when they explore analogies between its components and biological organs.

From these analogies the students acquire a new perspective on biological systems and

gain motivation to develop their robotic models. The ideation continues, when the student

selects a biological system and performs a self-regulated inquiry into its control mecha-

nism. At this stage the student applies knowledge on control of technological systems to

the study of biological systems, and ideates the concept of the model. At the materiali-

zation stage the student creates the model through iterations of rapid prototyping. The

aspiration to improve the prototype directs the learning towards in-depth understanding of

the biological system and development of effective technological solutions. At the model

exploration stage, the analysis of similarities and differences between the model and the

biological system guides the student to evaluate the model.

Our study indicated that the proposed course of action fostered growth in learners’

scientific and technological literacy, positive attitudes towards teaching and learning with

models, and motivation for building robotic models. Because of the limited assortment of

components and materials in the kit, the robotic model can provide only partial analogical

resemblance to the biological system. Findings of our research indicate that exploration of

this partial resemblance and a systematic examination of similarities and differences

between the systems constitute a meaningful learning experience leading to better

understanding of concepts in both robotics and biology.

While guiding inquiries into biological systems towards creating the model, we acted to

avoid inaccuracies in acquisition of biological concepts that might happen while self-

regulating learning. We encouraged the students to carefully analyze specific features of

the biological systems and consult with their biology teachers to validate the findings of

this analysis. We found these means effective and worthwhile.

In conclusion, we acknowledge the potential of modeling as a thread, tying together

engineering design and scientific inquiry into an integrative learning experience. We

continue the study of the proposed approach towards deeper understanding of cognitive

mechanisms and wider implementation of learning with analogies.


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Learning through creating robotic models of biological systems

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