Int J Technol Des Educ (2009) 19:289–307 DOI 10.1007/s10798-007-9043-3
Robotics projects and learning concepts in science, technology and problem solving Moshe Barak Æ Yair Zadok
Published online: 20 November 2007 Springer Science+Business Media B.V. 2007
Abstract This paper presents a study about learning and the problem solving process identified among junior high school pupils participating in robotics projects in the Lego Mindstorm environment. The research was guided by the following questions: (1) How do pupils come up with inventive solutions to problems in the context of robotics activities? (2) What type of knowledge pupils address in working on robotics projects? and (3) How do pupils regard or exploit informal instruction of concepts in science, technology and problem solving within a project-based program? Data collection was made through observations in the class, interviews with the pupils, observations of the artifacts the pupils had constructed, and analyses of their reflections on each project. The study revealed that the pupils had often come up with inventive solutions to problems they tackled by intuitively using diverse kinds of heuristic searches. However, they encountered difficulties in reflecting on the problem solving process they had used. In robotics projects, the pupils deal primarily with qualitative knowledge, namely, the ability to identify specific phenomena in a system or factors that affect system performance. The study also showed that pupils are likely to benefit from implementing informal instruction on concepts in science, technology and problem solving into a project-based program. This type of instruction should take place in the context of pupils’ work on their projects, and adopt a qualitative approach rather than try to communicate in the class procedural knowledge learned by rote. Keywords
Projects Robotics Problem solving
Introduction Brandt (1998) mentions some of the conditions under which people learn well, such as: what they learn is personally meaningful to them; what they learn is challenging and they accept the challenge; what they learn is appropriate for their developmental level; they can M. Barak (&) Y. Zadok Department of Science and Technology Education, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel e-mail:
[email protected]
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learn in their own way, have choices, and feel in control; they use what they already know as they construct new knowledge; they have opportunities for social interaction; and they receive helpful feedback. Projects in robotics could serve as a good vehicle for implementing the concepts identified above. Indeed, an increasing amount of literature (Barak and Doppelt 2000; Barak 2004; Vernado 2005; Bers and Portsmore 2005; Petre and Price 2004; Hussain et al. 2006; Murray and Bartelmay, 2005) has reported on the advantages of engaging pupils in robotics projects to foster pupils’ problem solving, creativity and teamwork skills. Modern robotics construction kits, such as the Lego Mindstorm system, provide opportunities for pupils to design and build interactive artifacts using engineeringoriented instrumentation, including gears, motors and sensors, and to engage in active enquiry by creating playful experiences (Bers and Portsmore 2005). Project-based learning draws considerably from the constructivist philosophy of learning, attributed to prominent philosophers of education such as Jean Piaget (1896– 1980) and John Dewey (1859–1952). Constructivist pedagogy encourages pupils to build new knowledge based on existing knowledge and their own experience. Papert and Harel (1991) and Kafai and Resnick (1996) discussed the concept of ‘constructionism,’ according to which pupils are more deeply involved in their learning if they construct artifacts they can share with others, for example, peers or parents, and that this construction engages the learner in complex tasks and problem solving efforts. An increasing number of studies (Doppelt and Barak 2002; Petre and Price 2004) have shown that pupils consider the freedom they have in developing their own ideas and using their imagination as major factors influencing their motivation to participate in technology projects. Apparently some difficulties or questions exist about implementing project work in robotics in school. First, there is a gap or contradiction between pupils’ expectations in constructing sophisticated robotics systems, on the one hand, and the need to base their work on scientific-technological knowledge, on the other. For example, we expect that a pupil will grasp an understanding of the factors determining a robot’s speed, power and accuracy, or express robot speed in meters or centimeters per second, rather than just saying that the robot is fast or slow. Second, in technology education, we often desire that pupils design a system or solve a problem through systematic work rather than by relying exclusively on intuition. However, the issue of whether and how problem solving and creative thinking skills can be taught in school is debatable. For example, the well-known problem solving model, often called ‘the design process,’ has been subject to increasing criticism in educational literature (Hennessy and McCormick 1994; Johnsey 1995; Mawson 2003) since it is likely to convey to learners the notion of involving a general ‘all-purpose’ problem solving method; in contrast, designers or expert problem solvers in technology and engineering use diverse working methods, to be discussed further in the next section. With these questions in mind, we designed the current study to explore pupils’ intuitive learning and problem solving methods in developing small robotics systems, the types of knowledge they use, and ways of enhancing their learning and problem solving skills in the context of project-work in robotics.
Theoretical framework Can problem solving be taught? Although the issue of problem solving has been the subject of considerable theoretical analysis during the recent century, questions such as whether a general problem method
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exists or to what extent can people learn or improve their problem solving and creative thinking skills still trouble psychologists and educators. On the one hand, prominent writers such as Dewey (1910), Polya (1957), and Newell and Simon (1972) have suggested hierarchical models of information processing and action according to which people progress from identifying a problem or a difficulty to be resolved until they find a satisfying solution. On the other hand, authors such as Hayes (1978) and McCormick (1997, 2004) state that problem solving is a compound process that can hardly be delineated into separate steps or phases. Moreover, as Perkins and Salomon (1992) stress, intellectual skills such as learning, problem solving and creativity are domain-specific, and people have a fairly poor ability in transferring learning from one context to another. Although education can be designed to promote transfer of learning to closely related contexts and performances (‘near transfer’), the notion of teaching general problem solving methods must be considered very carefully. A further discussion of this point follows.
Role of strategies, schemes and heuristics in solving technological problems To learn more about the question of how education can foster pupils’ problem solving skills, it is useful to compare the ways experts or novices solve design problems. A wide range of literature (Hayes 1978; Mayer 1992; Wankat and Oreovicz 1993; Hennessy and McCormick 1994; Kolodner 2002; Kolodner et al. 2003; Koen 2003; Cross 2004) suggests that: • While novices have difficulties in describing a problem, experts use many techniques to re-describe or re-define a problem; • While novices use trial-and-error, experts use domain-specific strategies, schemes and heuristics; • While novices memorize knowledge as small disconnected facts, experts have ‘‘chunks’’ of specialized knowledge and patterns they can use in different contexts; • Experts in a specific domain are likely to jump easily from one working method to another, combine given strategies in new ways, or solve problems by using shortcuts or rules-of-thumb rather than work according to a specific method. In light of these differences, there is room to explore the influence of teaching pupils diverse problem solving methods (for a further discussion on the role of teaching strategies, schemes and heuristics in solving technological problems, see Barak 2007). With this notion in mind, we aimed at exploring how pupils deal with problems in constructing small robotics-type systems, and how their skills could be enhanced in class.
Types of scientific-technological knowledge addressed in robotics projects The comparison between expert and novice problem solvers, described above, clarifies that knowledge in a specific domain plays an important role in effective design and problem solving. Yet, young children not only lack scientific-technological knowledge in robotics, but also commonly regard robotics as a framework for creativity and imagination rather than learning specific subject matter. How can we foster pupils’ knowledge of concepts in science and technology within a robotics program? The distinction between procedural knowledge and conceptual knowledge in different domains can help in this discussion.
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Mathematics educators (Rittle-Johnson and Alibali 1999; Haapasalo and Kadijevich 2000; Ben-Hur 2006) regard procedural knowledge as the ability to answer questions or solve problems by manipulating particular rules, algorithms and procedures. In contrast, conceptual knowledge has to do with understanding general concepts and recognizing their application in various situations, or the ability to transfer knowledge between situations. McCormick (1997) similarly addressed concepts of procedural knowledge and conceptual knowledge in technology education. According to this author, procedural knowledge in technology has to do with ‘knowing how to do,’ such as how to build a stable mechanical structure, design an electronic circuit, or write and test a computer program. Conceptual knowledge, according to McCormick, is about understanding ‘the relationships among items of knowledge,’ for instance (our examples), understanding how concepts such as energy, feedback in systems or data conversion cross diverse technological domains like mechanics, electronics or communication systems. What kinds of knowledge do pupils working on robotics projects use? To what extent can a robotics course foster pupils’ procedural knowledge on the one hand, or broad conceptual knowledge in science and technology on the other? A third type of knowledge, qualitative knowledge, as McCormick (2004) suggested, helps at this particular point of the discussion; this type of knowledge accounts for the ability of understanding or evaluating a specific phenomenon in a system without relying necessarily on formal (procedural) knowledge such as mathematical equations or exact physical terms. Some examples of qualitative knowledge in robotics are: understanding how changing a gearbox affects the velocity and power of a robotics car; identifying the factors influencing the rigidity of a mechanical structure, or understanding the advantages and disadvantages of feedback control versus open-loop control. The question regarding the types of knowledge the pupils deal with in the context of learning robotics is discussed in more detail later in this paper.
The study Research questions As previously mentioned, the general objective of this study was to explore learning and problem-solving processes among pupils participating in robotics studies. More specifically, the research aimed at answering the following questions: 1. How do pupils come up with inventive solutions to problems in the context of robotics activities? 2. What type of knowledge do pupils address in working on robotics projects? 3. How do pupils regard or exploit informal instruction of concepts in science, technology and problem solving within a project-based program?
Context of the study The study took place within the framework of a robotics course offered to junior high school pupils (7th and 8th graders) in a robotics laboratory at the Holon Academic Institute (HIT), an engineering-oriented academic college located in the Tel-Aviv region. The pupils attended class 2 h a week for 15 weeks (about half a school year). The instructors included the co-author of this paper and another teacher, both having at least 5 years of
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experience in teaching robotics. The robotics program was considered an extension of science and technology studies in the school, and a teacher from each school followed up on the pupils’ participation in the course. The course format was gradually changed, as explained later in this paper.
Sample In the first year (2004/2005), 80 pupils (38 of them girls) participated in the robotic course in its original version. In the second year (2005/2006), 76 pupils (29 of them girls) participated in the revised course. In the third year (2006/2007), all of the second-year pupils took an advanced course, and another 116 pupils (67 of them girls) took the basic course, which was further improved. More details on the courses are provided later in this article.
Data collection methods The research adopted a qualitative methodology, in order to expose as many aspects of learning process as possible, mainly pupils’ feelings, thoughts and actions as they related broadly to their project work (Guba and Lincoln 1994; Silverman 1997). Data collection aimed at following up on pupils’ activities in the class, their individual and team work approaches, the processes they used in completing the tasks they tackled, and the content of the presentations they prepared and presented to the class. Data were gathered by: preparing a detailed journal of each class meeting; documenting spontaneous conversations with the pupils and unique events in the class; keeping records of pupils’ computer files, such as programs and electronic presentations; photographing the systems constructed by the pupils; videotaping selected lessons; and carrying out discussions with parents, school teachers and principals regarding their points of view about the course. This paper focuses primarily on pupils’ working processes, the artifacts they constructed, and their reflections on the course.
Findings In the first year: the content-oriented course The beginners’ course observed at the beginning of this study concentrated primarily on teaching pupils a diversity of principles considered useful for the construction of small robots. The teacher gave lessons on subjects such as types of mechanical structures or gearboxes. The pupils constructed small robotics systems using Lego blocks and explored their properties. They learned, for example, how to describe a gearbox quantitatively using a formula and graph, as is common in science. An attempt was made to teach a combination of qualitative and procedural knowledge, as previously mentioned. Although the course was presented to the pupils as a preparatory stage in building sophisticated robots, in the subsequent advanced course, discussions with the pupils and observations made in the class revealed that the pupils regarded the course just like any other school subject. For example, the pupils frequently came late to class, and attendance in the class was about 80%, similar to the rest of the school. Not all of the pupils made serious efforts in
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completing the tasks presented to them, and they seldom prepared their homework assignments or studied for tests.
Strong motivation among pupils who participated in a robotics contest In contrast to the picture described above, very strong motivation was found among 10 pupils from the same class who developed an original robot to compete in an annual nation-wide robotics contest. In this class: • The pupils worked independently, while teachers’ intervention was minimal. For example, the pupils split themselves into three teams: the investigation team, the construction team and the programming team. • The pupils often remained in the laboratory until very late in the afternoon or came to the laboratory over the weekend to work on their project. • The entire group met at the home of one of the pupils’ at least once a week. The strong motivation of pupils on this team in comparison to pupils who attended the basic robotics course indicated the necessity to revise the robotics program, as described in the following paragraph.
In the second year: the project-based learning course To increase pupils’ motivation and foster learning in the class, the robotics course was re-designed in the second year to meet the following guidelines: 1. The learning would be project-based. The pupils start out with relatively simple tasks, such as constructing the longest and strongest fishing rod possible using Lego blocks. The project’s complexity gradually increases, whereby at the end of the semester, the pupils deal with tasks such as designing a computer-controlled car. Figure 1 shows two examples of pupils’ projects. 2. The teaching of subject matter to the entire class is minimal; the teacher just explains specific points to the pupils in the context of the projects they are working on.
Fig. 1 Examples of pupils’ projects
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3. The pupils are encouraged to document all their work on the projects by using a digital stills/video camera that is readily available in the class. 4. At the end of every project, each group prepares an electronic presentation about their work and presents it to the class. 5. Pupils’ pictures, videos and electronic presentations are put on the course’s website shortly after the lesson. As previously noted, the new course described above was given in the second year of the current study, and involved the participation of 76 pupils (four groups of 16–20 pupils each). Basing the course on project work resulted in a considerable change in pupils’ motivation, as described below: • Pupils often arrived at the laboratory before the lessons formally commenced and remained there during the breaks or after the lessons to continue working on their projects. • One pupil reported that she worked with her father on his laptop to improve her presentation to the class and they watched videos together about class discussions they retrieved from the course’s website. • One schoolteacher, having no background in technology or science, sent some material on bridges she had found on the Internet to the robotics course instructor; she mentioned that she had become interested in bridges after ‘‘the pupils did not stop talking about what they were doing in the robotics course.’’ The change in pupils’ motivation on the course characterized the vast majority of the pupils in the four groups that attended the class, although they came from two different schools and varied in their scholastic achievements and socio-economic backgrounds. Building the program around a series of increasing complex projects enabled a close observation of the ways pupils were working on their projects, with special focus on issues relating to the scientific-technological knowledge and problem solving approaches they used, as discussed in the next paragraph.
Intuitive design and problem solving approaches The first task the pupils dealt with was to construct the longest and strongest fishing rod they could using Lego components. The pupils could decide by themselves about the rod’s length and the maximum weight it could carry at its edge. What did the pupils do when they discovered that their rod was too fragile and broke rather easily? Most of the pupils tried to strengthen their rod by attaching more and more Lego bricks at different points along the rod. Others pupils just shortened the rod until it could carry a reasonable weight, in their opinion. In each class, there were some pupils who made significant efforts in elaborating their rod or suggesting an original design, as the case shown in Fig. 2. This group constructed their rod with four arcs of increasing diameters from the rod’s edge towards its handle. The pupils, however, could not explain how they arrived at the idea of using arcs or how these arcs worked. In Fig. 2, we see three video frames in which one of the pupils explains using his finger how, as he understands it, the arcs ‘‘move the force from the rod’s edge to its middle and to the handle’’ (Fig. 2a, b, c respectively).
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Fig. 2 A fishing rod strengthened with four arcs in increasing diameters. A pupil shows with his finger how the arc ‘‘moves the force’’ from the end of the rod (a) to its middle (b) and to the handle (c)
Four conclusions may be drawn from this example: • Firstly, the pupils intuitively comprehended that the load (namely, the torque) at different points along the rod is proportional to the distance from its edge, where the maximum load acts close to the handle; • Secondly, the pupils found an inventive solution to the problem (Sternberg and Lubart 1996, define an inventive idea as being original, surprising and useful); • Thirdly, the pupils could not explain how they arrived at their design; • Fourthly, the pupils’ explanations as to how their solution worked hinted at a misconception in physics on the part of the pupils. Similar to the latter example, other pupils in the class arrived at clever solutions to problems using trial-and-error, patching and tinkering, but often had difficulties in explaining how their solution worked. About midway through the course (weeks 7–9), the pupils had gained more experience, having completed two or three small projects. At this stage, many groups paid greater attention to the task, for instance, by considering possible constraints or difficulties, rather than starting to build immediately. For example, for the task of building a bridge that could bear a weight of 2 kg, a group of four pupils spent considerable time discussing the task, each passing the weight from one hand to the other in order to enable making an estimation of how heavy it was. The pupils also regularly added weights to the bridge during construction, rather than first completing the bridge. In the project involving constructing a car that would climb an inclined plane (see Fig. 3), a group of pupils was seen testing and improving their model every 3–5 min. One of the most challenging tasks the pupils in the advanced group addressed was building a robot that would throw a ball quickly into a basket. All of the groups constructed a motor-driven mechanism that thrust the ball forward into the basket, as seen in Fig. 4a; the problem was that this method was too slow. One of the groups disassembled their first construction and came up with the solution shown in Fig. 4b, whereby the ball is thrown into the basket by a simple arm. One of the pupils in the group who built the simple mechanism seen in Fig. 4b said: ‘‘We wanted to use the car’s acceleration to throw the ball.’’ Yet, the pupils reported that they had not ‘designed’ the bent rod; rather, they had looked through all of the Lego block components until they found something that they thought could be useful. When they found the bent rod, they thought it would work ‘‘like an arm’’ throwing a ball, and consequently arrived at the structure seen in Fig. 4b. What can we learn from this example about problem solving? We will return to this point in the Discussion section.
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Fig. 3 Pupils testing a car climbing up an inclined surface having the highest possible slope
Fig. 4 Two different mechanisms for throwing a ball into a basket. (a) The ball is moved forward by a motor-driven tray. (b) The ball is thrown into the basket by an arm activated when the robot reaches the target
Role of scientific-technological knowledge in designing robotic systems So far, we have seen some examples of how pupils arrive at original designs. Below, we will deal specifically with the role that scientific-technological knowledge plays in developing robotics systems. We will focus our report on a case of three pupils who dealt with the task of building a car that climbed an inclined plane, with the aim of reaching the highest possible slope (see Fig. 3). The interviewer joined the pupils in their work for about 25 min, freely discussed what they were doing, and reviewed the problems they encountered and how they were trying to resolve them. The event took place just before the course-end ceremony and was videotaped in full. While two pupils on the team tried to improve their car, a third prepared an electronic presentation for the closing ceremony. The following report is based on the videotape, the pupils’ presentation and the reviewer’s notes.
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Problem 1: the gearwheels slip In their trials to make the car climb up a maximum slope, the pupils noticed that the gearwheels linking the motor to the wheels often disconnected and slipped over one another. Occasionally, they had to re-attach the Lego blocks holding the gearwheels together. The pupils did not know that this phenomenon occurred since forces were acting on the gears, as seen in Fig. 5. Hystad (2002) had dealt with this problem and suggested some ideas as to how to construct a rigid gearbox, as shown in Fig. 6. Since the pupils were not aware of this solution, they just kept repairing their car every few minutes instead of trying to resolve the problem. In our opinion, the pupils could benefit much by receiving instruction or ideas and tips about the DOs and DON’Ts of constructing mechanical systems. The question is, however, how to convey this information to the pupils; we will discuss this point later in the paper.
Problem 2: the car overturns A problem faced by all groups was that at a certain point along the incline, the car overturned. Below are excerpts from the interviewer’s discussion with the pupils during their efforts in dealing with this problem (I-interviewer; P-pupil). I: ‘‘What do you think could be done to prevent the car from overturning?’’ P1: ‘‘Maybe adding force to one side [namely to drive the front wheels as well].’’ P2: ‘‘Perhaps adding some weight here [at the front of the car].’’ P1: ‘‘The big [rear] wheel gives the car power, but... [no power is delivered to the front wheels... also, they are too small...].’’ Pupil no. 1 mistakenly thinks that the car overturns because it is driven only by the rear wheels; furthermore, she suggests using larger wheels in the front, although this could raise the car’s center of gravity and therefore make the car even less stable. Pupil no. 2 understands intuitively, but correctly, that balancing the car weight could improve its stability.
Fig. 5 Forces working on gears (Hystad 2002)
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Fig. 6 A gearbox designed to reduce slip between the wheels
This example also shows that intuition can either help or interfere with pupils’ design and problem solving, and a simple explanation for the need to low the car’s center of gravity could save the pupils a great deal of time and effort.
Problem 3: the car slips back down the slope Although all five groups tried to raise the angle their car could climb, all of the cars started slipping back at an angle of 35–40 degrees. The following excerpts from a 12-screen presentation the pupils prepared on their project illustrate their ideas regarding how they tackled the task, in particular the above-mentioned problem. The pupils wrote: 1. ‘‘We started the car with a motor that moves many gearwheels and saw that it doesn’t work properly.’’ 2. ‘‘After we saw that the gearwheels didn’t work, we decided to replace them with a [ready-made] gearbox that operates the wheels better.’’ 3. ‘‘We added a frame [body] and cover to the car.’’ 4. ‘‘Finally we added rubber bands to the four wheels, which gave the car an equable movement and made the wheels move at the same speed.’’ 5. ‘‘We noticed that the wheels rotated slower because the bands were under too much pressure [they were overstretched].’’ 6. ‘‘After consultation [with the teacher], we replaced the colored [original Lego] bands with brown [conventional] bands, which were wound a little bit looser; first we added a band to only one wheel, and after seeing that this was a good idea we added a band to the other wheel as well. At this stage, the car climbed from 35 degrees (slope) to 48 degrees.’’ 7. ‘‘After adding the rubber bands to the car, we noticed that the problem was that it slips [on the inclined surface]. We thought of an idea that, just like skis are sharpened to grip ice, we would have to do the opposite to avoid slippage. We thought about a tractor whose wheels are thick and chunky. Therefore, we decided to double the number of wheels.’’ 8. ‘‘We saw that even though the car didn’t slip any more, the [extra] wheels added weight, which drew it down and enabled it to climb a maximum slope of only 30 degrees.’’ 9. ‘‘Therefore we reversed one stage back: one motor, four wheels, two conventional rubbers bands, and a car that climbs 48 degrees.’’
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10. ‘‘In summation, after hard work, considerable thinking and many trials—unsuccessful and unsuccessful—we arrived at a final product that could climb up a slope of 48 degrees.’’ 11. ‘‘We succeeded, using a great deal of thinking and cooperation. And we certainly could not have achieved this without the help of our teacher.’’ Did the pupils quoted above make random experiments in their trials solve the problem? Not exactly; they used what is often called in the literature ‘heuristic search’, as we explain in more details in the Discussion section of the paper.
Implementing informal instruction of concepts in science, technology and problem solving into the project-based course To improve pupils’ knowledge both in scientific-technological concepts relating to building small robots and problem solving methods, a series of short abstracts have been developed on subjects, such as ‘‘What is force?’’, ‘‘What is power transmission?’’, ‘‘What is a problem?’’ and ‘‘What is creative thinking.’’ These learning units were in the form a PowerPoint presentation (about six pages each), using rich graphics rather than text. Examples from the learning unit entitled ‘‘What is force?’’ are shown in Fig. 7. Earlier experience with pupils’ reports on their work showed that they often confuse between the terms ‘task’ and ‘problem’; therefore, it was decided to prepare an abstract entitled ‘‘What is a problem?’’, which shows that: • The term ‘problem’ expresses a question or state of difficulty that needs to be resolved where the answer is not immediately evident; • Not every task is a problem; • It is useful to express a technological problem in terms of contradicting demands; for example, in a race car, we would like to increase the car’s power, on the one hand, but reduce its weight, on the other. The short learning units described above, which were presented to the pupils as supplemental material rather than as compulsory subject matter, were delivered to the class in various ways:
Fig. 7 Samples from the abstract entitled ‘‘What is force?’’ The idea is to present to the pupils concise scientific-technological concepts relating to robotic systems
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• Occasionally, the teacher presented a unit in the class for about 15 min in the context of the pupils’ work on their projects; • The abstracts were printed as posters and hung on the lab walls; • The files of the abstracts were placed on the course’s website, and the teacher encouraged the pupils to use the materials freely at their own initiative. There was a question regarding the pupils’ attitudes towards this attempt at teaching topics in science, technology and problem solving; after all, they were participating in a course to build robots and not learning school-type content. Yet, observations in the class and interviews with the pupils indicated that they accepted these instructional materials quite well. Within a short period of time, many pupils started using terms such as force and torque, as well as scientific units like Newton and Newton 9 meter, either in discussions in class or in the reports they prepared on their projects. For example, a group of pupils wrote in their presentation: We measured [calculated] the torque by multiplying the length of the rod and weight [it carries]. In our case, the length is 64 cm and the weight is 300 Newton, therefore the calculation is 64 * 300 = 19,200 (Newton * meter) Our final rod is twice as long as the first one; however, it is still strong and stable. It can carry a weight of 6,000 Newton (two weights). There are two errors in what the pupils wrote, as seen above: the rod length should be expressed as 0.64 m, and the original weight (mass) was 300 g, which causes a force of about 3 N. Although the pupils correctly tackled the issue, they failed in their detailed scientific calculations. The pupils did well in qualitatively explaining how strong their rod was: they noted that although they had doubled both the rod’s length and the weight hanging at its end, it did not fall apart. In an open discussion with a group of pupils in the class while they were working on their projects, we asked them what they thought about the teacher’s short scientific presentations in the class. The pupils had the following comments: ‘‘It is good to know what you are doing.’’ ‘‘When the teacher explains something, it is clearer... it is easier.’’ ‘‘It saves you time.’’ ‘‘We carry out less redundant experiments.’’ In summary, the above example indicates that using informal instruction in the context of project work is likely to foster pupils’ qualitative knowledge on the subject they are dealing with. Yet, fostering pupils’ procedural knowledge on scientific-technological concepts, such as correctly using or converting scientific units, requires more systematic instruction and practice. Evidence about the pupils’ use of the abstract related to problem solving was also observed. One example appears in a summative presentation made by a group of pupils on their first project—the fishing rod. The pupils wrote: On the one hand, we wanted a rod that is long and strong. On the other hand, we had to ensure that the rod would be light. A second example is of a group describing their third project, the car that climbed an inclined plane, as follows: In the beginning, we started working without thinking too much about what we were doing. We tried building a car that would climb up an inclined surface. Here was
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where we encountered a problem with our car: on the one hand, it was fast, on the other hand, it was not strong enough to climb up the surface. Also, the car was not stable enough to climb the incline. The last two examples indicate how the pupils had internalized the notion of presenting a problem by identifying contradicting demands, and for this, used the wording ‘‘on the one hand, on the other hand,’’ as appears in one of the units on ‘problem solving.’ It is important to note that it is not enough to show pupils a specific abstract only once, like the one on ‘problem solving.’ For instance, some pupils used the wording ‘‘on the one hand, on the other hand’’ to raise two different problems and not two aspects or contradicting demands of the same problem. Additional indications of pupils’ learning from the abstracts on problem solving to which they were exposed were found in their written reflections about the course. Upon completing their third project—a car climbing an inclined plane—the pupils were asked to write their views of the course on cards; the teacher suggested that they relate to questions such as: What did you like or dislike about working on the car project? What would you advise a friend who is going to start the robotics program? The following quotes from pupils’ answers show what they had learned from the above-mentioned abstracts on problem solving: One pupil wrote: Although we did not welcome difficulties and problems, they are essential parts of the learning process. Through them, it is possible to learn how to avoid making mistakes in the future and how to solve problems. Despite their negative effect, we overcame them, understood how to achieve our goal, and finally constructed an excellent model. Another pupil wrote: If a friend of mine would have started a task similar to ours, I would have suggested three things to her: first, work in teams all of the time, because only in this way can the goal can be achieved; second, write down all ideas proposed by the group members, and if possible, combine several of them so that no one in the group is offended and the model will be original; and third, not to be ashamed to ask for help from a friend or from the teacher. A third pupil wrote: Open up your minds! Start out by assuming that in order to suggest a specific idea there is a need for knowledge and experience on this subject! Think about other subjects, make a connection between them and your task, and draw conclusions! Although it is difficult to highlight a specific event or point in time when the pupils stopped working and spent time on defining a problem or holding a brainstorming session, the above examples from pupils’ reflections on the course demonstrate how they regarded the questions: ‘‘What is a problem?’’ or ‘‘What is brainstorming?’’
Discussion In this part of article, we discuss the findings described in the previous paragraph, by relating to three research questions and the theoretical framework we have presented previously.
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Heuristic search in problem-solving The first research question we raised in this study was: How do pupils come up with inventive solutions to problems in the context of robotics activities? Observations in the second and the third years of the current study indicated that in the first projects, the pupils often started to construct the system they were working on immediately and progressed through cycles of trial-and-error. As the pupils gained more experience, they paid greater attention in considering different solutions to the task they were tackling. In their third or fourth project, the pupils came up with original ideas according to what Hayes (1978) calls ‘heuristic searches,’ namely the process in which the problemsolver uses knowledge about the problem to identify promising paths in seeking a solution. One kind of heuristic search is what Hayes calls the proximity method, i.e., combining aspects of both forward and backward reasoning aimed at gradually closing the gap between the given situation and the target. A second kind of heuristic search is planning, for example by modeling, using analogies and abstraction. We have seen two examples of these problem solving patterns: one group of pupils explicitly stated that they wanted to ‘‘use the car’s acceleration to throw ball into a basket’’ (see Fig. 4); another group reported that when they tried to prevent their car from slipping on a tangential surface, they thought about skis, on the one hand, and tractor wheels, on the other. The pupils who developed a robot that throws a ball into a basket, mentioned above, intuitively used three heuristics that are well known in the literature on inventive problem solving (see, for example, the SCAMPER method, Eberle 1977, and the TRIZ method, Altshuller 1988). • One method is solving a problem by eliminating a component from the system; in our case, the pupils took out the motor that throws the ball; • A second heuristic that frequently helps in solving technical problems is assigning a new function to a component already existing in the system; in this case, the pupils used the robot’s movement to throw the ball; • A third useful method for solving problems is systematically examining all the ingredients available in the system and its nearby environment and trying to use or modify each of them to solve a problem; in the case under discussion, the pupils came up with their solution after they found the bent rod in the Lego box. Rather, they had not designed this component in advance. The pupils used the above problem solving methods based on life experience; no one had taught them these heuristics. Indeed, the literature on problem solving in general, and learning science and technology in particular, stresses that pupils come to school with some instinctive understanding of the world both in terms of scientific-technological phenomena and problem solving methods. Education needs to build on this knowledge, strengthen and expand it (Hayes 1978; Roschelle 1995). For example, Barak and Goffer (2002) and Barak and Mesika (2007), who investigated the effectiveness of teaching a range of principles for inventive problem solving to engineers or middle school pupils, have found that people derive great benefit from learning a range of principles or techniques for solving technological or day-to-day problems. These findings encouraged us to introduce instructional elements of problem solving into the robotics project-based program in the third year.
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The role of qualitative knowledge in robotics projects The second question we presented in this study was: What type of knowledge do the pupils address in working on robotics projects? In the literature review, we distinguished between three types of knowledge (Rittle-Johnson and Alibali 1999; McCormick 1997, 2004): procedural knowledge, which is the ability to answer questions or solve problems by manipulating particular rules, algorithms and procedures; conceptual knowledge, which has to do with understanding broad concepts and recognizing their application in various situations; and qualitative knowledge, which accounts for the ability of understanding or evaluating a specific phenomenon in a system without relying necessarily on formal terms or mathematical formulas. In the current study, the initial course (first year) that we called ‘content-oriented’ focused primarily on procedural knowledge, with the notion of preparing the pupils to handle sophisticated assignments in robotics later in the more advanced course. The teacher taught basic concepts in robotics, such as types of mechanical structures or gearboxes, and the pupils built given robotic models and examined their properties through scientific-type experiments. Although the course was based on sophisticated Lego-robotics instrumentation, the pupils regarded it as just another school subject and were rarely highly motivated in completing the class assignments. Actually, this course exposed the disadvantages of traditional teacher-instructed schooling aimed at teaching pupils formal content for future use. The revised version of the course in the second year adopted the project method. The pupils worked on three to four projects of increasing complexity, and prepared a summative presentation for each project. In this course, pupils’ motivation and interest in learning was much greater, but their lack of knowledge on scientific-technological concepts relating to robotics, such as force or friction, frequently limited their ability to design efficient robotics machines or understand the disadvantages of the system they were working on. For example, when a group of pupils were unable to explain why their robotic car turned over on a tangential surface, they tried to resolve the problem by adding weights at different points on the car. We have also seen an example of pupils who used an unsuccessful gearbox simply because they lacked the knowledge about building a more rigid construction (Figs. 5 and 6). In these cases, the pupils could benefit greatly from learning the physical concepts of mechanical construction principles. Another finding was that when the pupils were asked to reflect on their work on their projects, they were often unable to describe how they dealt with a specific assignment or were confused between the terms task and problem. In summary, these finding emphasized the need to integrate elements of instruction into the project-based course. In the third year, the course was further developed by preparing a range of abstracts in the form of PowerPoint presentations on subjects such as ‘‘What is force?’’ or ‘‘What is a problem?’’ The teachers presented these materials to the pupils in the context of their projects, in an unconstrained manner, and the pupils could decide whether or how to use them. The pupils very quickly started using terms or concepts presented in these abstracts, such as force, frication, torque or center of gravity, in their discussions with their friends or in their summative reflections on each project. However, they were only able to describe these concepts qualitatively. The term ‘qualitative knowledge’ (McCormick 2004) mentioned in the theoretical review is useful here, because the pupils could understand or evaluate a specific phenomenon in the system they constructed, but were less successful in performing specific calculations. As we have seen, more systematic instruction in the class is required to develop pupils’ formal procedural knowledge in specific issues, for example, using mathematical formulas and scientific units like kg or Newton.
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How did the pupils regard instruction by the teacher? The third question that guided this study was: How do the pupils regard or take advantage of the teacher’s informal instruction of concepts in science, technology and problemsolving while working on their projects? This question is interesting because the literature on constructivist learning frequently stresses the notion of knowledge construction by the learner, rather than the delivery of subject matter by the teacher. The current study taught us that the pupils willingly accepted the short presentations by the teacher. They not only immediately used what the teacher showed them both regarding scientific-technological concepts and issues relating to design and problem solving, but explicitly stated that the teacher’s explanations helped them in understanding their projects better and saved them considerable time and effort. Further research is required, however, to investigate in a more in-depth fashion what extent or how the instruction of concepts in science, technology and problem solving affects pupils’ working patterns or the quality of the robotics artifacts they construct.
Concluding remarks The current study proposes that it is useful to teach pupils basic knowledge on scientifictechnological concepts relating to the projects they are working on, as well as concepts relating to problem solving and design. It should be emphasized that the idea of implementing instruction by the teacher into a project-based learning program does not conflict with the constructivist view of learning, which underlies project-based schooling. As Richardson (2003) stresses, constructivism is a theory of how learning happens and not of teaching; many kinds of pedagogies, including instruction by the teacher, can help in promoting meaningful learning in class. It is important, however, that this type of instruction should take place as follows: • In the context of pupils’ work on their projects, rather than as general or universal knowledge for future use. • In a flexible, easy-going manner, rather than through strict teaching. • As an enhancement of the robotics activity, rather than as compulsory content to be learned. • With focus on a qualitative-conceptual approach, rather than as procedural knowledge to be learned by rote. One should consider that problem solving and creative thinking are complex phenomena that involve conscious and unconscious processes; they use explicit knowledge and intuition and a combination of ordered and disordered thinking, which are all influenced by cognitive and affective factors. References Altshuller, G. S. (1988). Creativity as an exact science. New York: Gordon and Breach. Barak, M. (2004). Issues involved in attempting to develop independent learning in students working on technological projects. Research in Science & Technological Education, 22(2), 171–183. Barak, M. (2007). Problem-solving in technology education: The role of strategies, schemes and heuristics, In D. Barlex (Ed.), Design & technology – for the next generation (pp. 152–167). London: The Technology Enhancement Program and the Nuffield Design and Technology Project.
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