Session F4F Students’ Working Strategies and Outcomes in a Creativity-Supporting Learning Environment
Mikko Apiola, Matti Lattu, and Tomi A. Pasanen [email protected], [email protected], [email protected]
Abstract - This paper describes results from a teaching department decided to purchase 60 Mindstorms sets, and we experiment at the Department of Computer Science at also presumed that Mindstorms could be a great platform for the University of Helsinki, in which we studied students’ this experiment. different working strategies and tried to find patterns To put our ideas into practice, we designed and carried between these strategies and the creativity of the out a 10-week pilot course with intermediate level students students’ work. In a typical computer science course in (n=33), with good basic skills in computer science and Finland, the teaching is quite strictly structured and the project work. The course was set as optional in the support structures (e.g. lectures, lab sessions) are highly curriculum. The task for students was to define a robotics teacher-driven. In contrast, our intention was to create a task suitable for CS1 or CS2 students and create a robot for learning environment where the support structures an example of a solution. Students were required to build would focus on supporting creativity to bring forth new and program a robot, document the solution and clarify ideas and innovation. We were especially interested in which CS1 and CS2 course objectives the task revises. the working strategies that students would use outside Students were encouraged to explore, have fun, and amaze our learning sessions, the students´ outcomes with us and the other participants. regards to creativity, and the interplay between working In contrast with other practical lab-courses, we strategies and the creativity of the outcomes. To put our deliberately did not recommend any working strategy, which ideas into practice, we designed a pilot course utilizing created the possibility to study the approaches students practices from research into creativity and intrinsic would take and the possible interplay between the chosen motivation. To answer our research questions we strategy and the resulting project work. interviewed all course attendees (n=33) twice, at the beginning and at the end of the course. We chose OUR LEARNING ENVIRONMENT LEGO® Mindstorms robots as the platform for the A learning environment can be defined as the factors that project. While further studies are needed, our define the context for studying and learning (for example preliminary results suggest that there is a pattern [20]). These factors are many, and include, for example, the between working strategy and creativity. learner’s personality, the social environment and the physical surroundings. Meisalo and Lavonen [23] define an Index Terms – Creativity, Working strategy, Open Learning open learning environment by using the metaphor of a Environment, Robotics market place. At the market place the learner transacts with INTRODUCTION those market stalls that best fulfill her learning needs. The roots of the concept of an open learning Creativity and creative skills have become widely regarded environment are related to the cognitive revolution in the as highly important in education and for future technology 1970s and the development of educational sciences in the industries (for example [6, 28]). However, in a typical direction of constructivistic learning theories, often seen in computer science course in Finland, the teaching is quite opposition with instructivistic learning theories. Thus, strictly structured and the support structures (e.g. lectures, starting from the 1990s there has been great debate between lab sessions) are highly teacher-driven. In practical computer the acquisitional or participational nature of learning [29], science lab-courses, highly structured software engineering for example. Yet, as Sfard [29] points out, it is good to models are almost always recommended as the working remember the dangers of choosing just one viewpoint. In strategies for students. In contrast with this common designing a learning environment, the cleverest approach is practice, our intention was to create a learning environment probably not to take any single viewpoint, such as where the support structures would focus on supporting instructivism or constructivism, but to aim for a proper mix creativity to bring forth new ideas and innovation. We were of different approaches. also interested in the use of robots, which are often reported I. Intrinsic Motivation as being successfully used in basic programming courses, but also seem to offer a framework for more advanced The Self-Determination Theory (SDT) of Ryan & Deci [26] domains, e.g. artificial intelligence (see e.g. [12-16, 18, 19]). defines intrinsic motivation as performing some activity for Thus, after some preliminary planning and research [17] our the sake of the activity itself, not, for example, to accomplish
978-1-4244-6262-9/10/$26.00 ©2010 IEEE October 27 - 30, 2010, Washington, DC 40th ASEE/IEEE Frontiers in Education Conference F4F-1 Session F4F rewards extrinsic to the task at hand. Ryan & Deci [26, 27] components of intrinsic motivation are competence, define three basic needs which they perceive as crucial for autonomy and relatedness [26, 27], and the components of general well-being and motivation; competence, autonomy creativity are intrinsic motivation, domain-relevant skills, and relatedness. While intrinsic motivation is a favorable and creative processes and working styles. Since intrinsic condition in itself, it is also often seen as one necessary motivation is defined as one component of creativity, component in creativity (see for example [3, 24, 30, 31]). creativity inherits all the components of intrinsic motivation. Thus, in attempting to support both intrinsic motivation and II. Creativity creativity, we are left with five components; competence, Creativity is often defined as the producing of original, autonomy, relatedness, domain- relevant skills, and creative unexpected and useful work (for example [30]). Herrmann processes and working styles. Table 1 shows all our [10] summarizes a variety of creativity definitions: “the components and literature-derived ideas customized to our ability to challenge assumptions, recognize patterns, see in environment on supporting each component. new ways, make connections, take risks, and seize upon change”. Pioneers in creativity research have come to share TABLE I somewhat similar views; that creativity requires three COMPONENTS OF OUR LEARNING ENVIRONMENT components; domain-relevant skills (expertise and talent in Component Method of Support Competence Use of creativity enhancing methods, providing the task domain), creative processes (cognitive skills and effectance promoting feedback work styles) and intrinsic motivation (for example [3, 30, Autonomy Providing choice and opportunity for self- 31]). direction The literature suggests several methods for enhancing Relatedness Encouraging teamwork, promoting social creativity, of which methods especially intended for concrete interaction and creative working methods problem-solving situations include; brainstorming [25], Domain relevant skills Requiring good computing skills from all verbal check-lists [7, 25], picture stimulation and mind attendees. mapping (for example [5]). Higgins [11] has also provided Creative processes and Use of creativity-enhancing methods in course many methods for enhancing creative problem solving. A working styles sessions: brainstorming, 3+ [21], and open- space workshops [9]. general idea with many of these methods is the purpose of Constructionism Use of LEGO-mindstorms robots. Lend each generating ideas by suppressing the common tendency to student their own robotics-kit. criticize or reject ideas using different types of games or tasks. Collaborative methods include for example Open Spaces Technology (OST) [9] and a method developed at the To put theory into practice, we set up a voluntary University of Helsinki Teacher Education Department, programming course targeted at students with good named 3+ [21]. computing skills, i.e. students at the intermediate level in our curriculum. There were three of us instructors and we had III. Mindstorms and Constructionism six course meetings. At the first meeting the idea and LEGO Mindstorms is a robotics kit based on a small practical arrangements were presented and every student was microcontroller unit, a set of input sensors, motors and parts lent his own Mindstorms kit for personal use during the for building robots. The robot can be programmed with course. At all the following sessions we experimented with multiple programming languages, libraries exist for example creativity methods such as 3+[21], and open space for Java [22] and C/C++ [4]. workshops [9]. In 3+ the idea is to generate a Constructionism is a learning theory developed by psychologically safe environment for ideation by setting Seymour Papert [8], and is based on constructivistic students in circles, where everyone in turn has to present learning. Papert has worked closely with LEGO Mindstorms an idea regarding the project, and give supportive comments and also, for example, with the LOGO programming on the previous student’s ideas. At open space workshops language. Constructionism is connected with experiential students would prepare ideas, solutions and problems in learning and builds on similar ideas of Jean Piaget on posters, and then present the posters. It has to be noted, that constructivism. Papert himself defines constructionism as these working methods are not common in Finnish follows: "From constructivist theories of psychology we take computer science education, as the mainstream of a view of learning as a reconstruction rather than as a learning sessions include only student presentations transmission of knowledge. Then we extend the idea of of their ready-made solutions or projects, but hardly any manipulative materials to the idea that learning is most discussion regarding the ideating or planning phases of effective when part of an activity the learner experiences as learning tasks. After some initial confusion, the classroom constructing a meaningful product [8].” activity seemed to progress naturally. Sitting in a circle, for example, turned out to work in a natural way, there was IV. From Theory to Practice: Teaching Experiment a lot of laughter, fun and useful ideation that took place to We designed our learning environment for maximum support the actual work. support of intrinsic motivation (as it is defined in Ryan & Though only 19 students completed the course, the Deci´s SDT Theory), creativity, and constructionism. The course can be considered very popular. This kind of dropout rate is very normal at our university where students are 978-1-4244-6262-9/10/$26.00 ©2010 IEEE October 27 - 30, 2010, Washington, DC 40th ASEE/IEEE Frontiers in Education Conference F4F-2 Session F4F allowed to register for courses and drop out any time they themselves. Indeed, we need more creativity in CS not only wish without any consequences. Practically every student to bring up new innovations but also to intensify learning. dropping out said that their dropping out was due to the We want our students to go beyond their skills. optional nature of the course in the curriculum; they would Based on these speculations, we deliberately decided have wanted to finish, but they had to concentrate on the not to push for any specific working strategy, such as some mandatory courses. engineering model, in our learning environment. Our approach is opposite to every mandatory practical computer ON WORKING STRATEGIES science course at our university, which all push for waterfall, Developing software is often taught from a software or other models. Instead we wanted to research which kind engineering perspective in universities. Software of working strategies the students would adopt, and how engineering is the discipline concerned with the application those working strategies would be connected with the of theory, knowledge, and practice for effectively and students’ coursework and creativity. efficiently building software systems that satisfy the RESEARCH QUESTIONS AND DATA ANALYSIS requirements of users and customers [2]. In software engineering, the concept of life cycle The purpose of this study was to investigate the students’ models is used to define the phases that occur during behaviors and outcomes in a creativity-enhancing learning software development [1]. The common set of phases in a environment. We were interested in the students’ working software development process are; requirements analysis, strategies and the students’ outcomes, especially from the design, implementation, verification and maintenance. viewpoint of creativity. Would the students indeed be Examples of life cycle models are the waterfall-model, creative and be able to produce creative outcomes? evolutionary development, the spiral model and iterative/incremental development. These models define the The main research questions (RQ) were: phases of development and tasks related to each phase. In the widely used waterfall model, for example, those phases 1. What kind of working strategies will the are executed in sequence; when one phase is finished, the students use in a creativity-enhancing learning development process moves to the next phase. Other environment? common models include iterative models, where the phases 2. What levels of creativity can be determined are iterated, for example, to meet the changing requirements from the students´coursework (outcomes)? of a customer better. Popular iterative models nowadays 3. Is there interplay between the working strategy include XP (extreme programming) and Agile models. and the creativity level of students’ coursework At the University of Helsinki all mandatory (outcomes)? undergraduate practical computer science courses (three smaller and one larger project) approach programming and To answer the research questions we interviewed all course development of software from an engineering perspective. A attendees twice, at the beginning and at the end of the substantial aspect of such learning is to follow a structured course. Every student (n=33) was scheduled a one-hour time development process to develop some software product to slot for both interviews, which were tape-recorded, meet the requirements of some interest group, such as a transcribed and analyzed by finding common patterns in the customer or employer. In the smaller projects, the course interview data using the ATLAS.TI qualitative tool. In structure is often highly based on waterfall models; in the addition, detailed observation notes from each learning larger project also other development models are session was collected. As explained before, there were 19 recommended. In a way these projects resemble practical on- students who completed the course. All drop-outs were the-job training in an information technology industry. excluded from this study, since their non-completed projects Although in-depth understanding of software would not be comparable. Three foreign students who engineering principles and knowledge of standard software completed the course were excluded since they did not project phases are important aims in CS studies, we argue attend any of the learning sessions, but worked separately. that these are not the most efficient ways to promote Thus, 16 students´ data could finally be included in this learning. While the intention of software engineering is to study. produce a flawless software product in the most efficient way, they do not encourage risk-taking and creativity which STUDENTS’ WORKING STRATEGIES (RQ 1) are needed for new innovations. Following industry standard We have classified the students’ working strategies into recipes and defined processes restricts the students’ three categories based on the interview data. Categories 1 possibilities to come up with ideas, explore, dwell on (n=3 students) and 2 (n=8 students) resemble working subjects, problems and matters of the students’ own needs strategies similar to the waterfall-type process model used in and interests. If we require the students to follow effective software engineering, and category 3 (n=5 students) and risk-free production principles we cannot expect them at resembles working approach which can be described as the same time to try or invent something new. It may not be experimental and iterative. new for the teacher or computer science but new for 978-1-4244-6262-9/10/$26.00 ©2010 IEEE October 27 - 30, 2010, Washington, DC 40th ASEE/IEEE Frontiers in Education Conference F4F-3 Session F4F I. Category: Waterfall 1 The locus of causality when faced with trouble is reflected on the technology. As one student of this working Projects in this category strongly resemble waterfall-type strategy burst out at the end of his interview when asked projects in software engineering. There is practically no about ideas for developing this course further “Just get that ideation phase, but the subject has been determined fast in more accurate type of sensors!”. the beginning phase of the project, which resembles the working style of other practical lab courses at our Example: (Student #8) ”…well it was really quite in the department. It also resembles software engineering working beginning of the project when we decided that we want this styles, where the subject is not for the computer scientist to kind of robot. Then we tried, built some pieces as the base think of, but usually comes from outside. Other important structure of the project. We built it for some time, and made decisions regarding the project have been decided and three iterations of it. After that we were happy about it. The locked at an initial phase of the project. After that the goals first iteration was not at all working, neither was the second are pursued with a brute-force way of working sometimes although it started to work a little better. It was like trial- resulting in dead ends and badly working solutions without error kind of learning. Then again, I cannot think of a better quite understanding where the problems are coming from. way [to learn]. After week 5 we had a working prototype In many cases the effort can be described as finding constructed. At that point it was only lacking the program. instructions from the Internet and then building according to Indeed, we focused only on building the mechanism at the them. The locus of causality in failing to produce a decently start.
Example (Student #24) ”We thought of some ideas and then III. Category: Experimental we decided what we are going to do. We thought a little bit about how we are going to develop the thing. After that we The working process of this strategy can be described as started building the robot. When the robot was ready we experimental and iterative. This strategy differs started coding it. We wanted something that would interact fundamentally from approaches 1 and 2; it seems that the with its environment, but that turned out to be difficult. at primal motivation seems to be an interest in exploring the some point we returned to the building phase, on second possibilities of this technology. The working approach can thoughts a few times, but it was not caused by our plans, but be described as experimental. There has been a lot of the cause was the bad inaccurate data from Lego sensors. ideation which has been mixed with experiments related to The specs of the sensors did not give us enough information. different aspects of the technology; measuring the So then we decided to make the model more simple, like effectiveness of the sensors for example, trying the stability those problems we were facing were due to that. Like we of different kind of mechanisms etc. The process was were aiming to counter all those problems with the sensors iterative in such a way that there were many different by doing everything as simple as possible.” prototypes. There were different prototypes and different kinds of experiments, which were then abandoned and the II. Category: Waterfall 2 work was started from scratch with gained knowledge and expertise. There was interest in why and how things work The working strategies of this category also resemble the way they do and which approach would be best for waterfall-type projects in software engineering. The ideation different kinds of situations. phase is short, and the project has progressed with previous In this type of projects, the performance of the phases being locked, and the subject has been determined at technology, sensors and motors, has not become a problem, quite an early phase of the project. For example, also the since their capability has been researched first with fundamental mechanism, the structure of the robot has been prototypes, tests and measures before they have been applied locked so that it has not been changed in any part once it has as a part of the project. The mechanism of the robot, the been finalized. Some subparts of the project have been done program code and the surrounding world in which the robot in an iterative or experimental fashion, yet the process in operates has then been built in such a way that works well. whole is of a waterfall type. This type of working strategy differs from working Example: (Student #19) ”…well I started [the project] from strategy 1 in that there is great effort and motivation in a concrete viewpoint: I took the Lego bricks in my hand and solving the subproblems. There have been iterations, started to build all sorts of different things.. I thought that experiments, prototypes regarding the subtasks. The “well, let’s try this kind of thing: I will test this sensor and solutions are made by the students themselves from scratch, then I will test that other sensor and measure how much they are not imitated from anywhere. torque this motor has and things like that, I built small prototypes and wrote program codes for them. A program
978-1-4244-6262-9/10/$26.00 ©2010 IEEE October 27 - 30, 2010, Washington, DC 40th ASEE/IEEE Frontiers in Education Conference F4F-4 Session F4F like this does something funny and then I realized that this is file, which was then transferred to a pc-computer and the not at all what I want, and then you just build on it and at steps of the robot were analyzed using a spreadsheet some point you have like one thousand lines of code and you (calculus) program. This individual attempt was thus lacking think that this subject is not at all going to work and it is not the domain understanding of the context, that it is impossible what I want. Kinda like all the phases were processed in for the robot to know its exact positions if the surrounding turn, in an iterative way. It was not at all like I thought world has not been made recognizable, simplified, for the about things for 5 weeks and then I started to develop the robot. code or such…” Example: Navigating car (for picture see table 2). The CREATIVITY OF COURSEWORK (RQ 2) project was based on a very simple car model, which is very In the following section the students’ coursework has been easy to find on the Internet. The program code was very classified into three categories according to our view about simple, and as such resembles simple example codes their level of creativity. Our categories are 1 (minimal presented, for example, in the tutorial of the programming creativity, n=5 students), 2 (creativity in subtasks, n=7 environment (Lejos) used. The robot moves in an students), 3 (creative work, n=4 students). environment and detects surrounding items with its The categorization is based on a definition of creativity, ultrasonic sensor, then takes turns to the left or right according to which creative work is original, unexpected and according to a simple algorithm. There seems to be useful and that creativity requires challenging of enormous effort in irrelevant decoration of the car. assumptions, recognition of patterns, seeing in new ways, TABLE 2 making connections, taking risks (for example [30, 10]). We EXAMPLE ROBOTS have then attempted to apply this definition in a computer Navigating car, Checkers-playing robot, Tic-Tac-Toe robot science and robotics programming context. For the projects to be considered creative, the general idea, synergy of the mechanism and the program code have to be original, somehow useful, and new. The creativity must occur in the context of computer science; the robot must be functional and interact with its environment without being too simplistic or without being an imitation of some existing robot. Alternatively, if the functionality is imitated, II. Category: Creativity in subtasks the brain of the robot, i.e. the program code must be written from a new, original point of view. The “ground factors” for Projects of this category seem to have creativity in the each project topic; the technical and mechanical limits set by subtasks of the project: in building the mechanism or in the the environment, have to be recognized and solved. technical ideas and the program code. The project as a whole Programming with robots poses a lot of challenges related to has failed to be creative, often because some restrictions both the mechanism and the uncertain nature of robotics caused by, for example, the project topic or a fundamental programming, i.e. communicating with the environment structure of the robot. The creativity in subtasks may be seen using inaccurate sensor data, which differs compared to a in attempts to fix the inaccurate sensor signals. All efforts more linear type of programming which many students are are original, they are not imitations from anywhere. This more used to. For creativity to occur, the patterns that these category also includes projects which have been developed many challenges constitute must be recognized and solved in as a side-product of some other project. For example one some original way. student had been working on her BSc-thesis concerning reinforcement-learning algorithms, and then implemented I. Category: Minimal creativity her algorithm for a simple Mindstorms-robot design. The creativity in that case was in her algorithms, but not in the Projects of this category are simple, yet not original in all whole robot invention. aspects: the topic, the mechanism, the technical ideas and the programming. Both the mechanical structure and the Example: Checkers robot (for picture see table 2). This program code seem to be quite straight imitations from was an impressive attempt. The mechanism was stable and existing projects; certainly, the program code has been self- well designed, and there was enormous effort in fixing the written, yet the solutions are very simple and they often insufficient signals from the light and ultrasonic sensors in closely resemble ideas that have been implemented before. an attempt to reliably recognize the current state of the The solutions are very simple, even childish or they work board. No matter how hard the effort, the robot could not be badly. made to suffice in all situations; it could not reliably detect In some projects of this category there is clearly some all the positions of different buttons. In our view, the creativity in the sub-tasks of the project, for example in fundamental structure of the mechanism was blocking the attempts to debug the robot: in one robot, for example, the creativity. robot collected information about its surroundings as a log 978-1-4244-6262-9/10/$26.00 ©2010 IEEE October 27 - 30, 2010, Washington, DC 40th ASEE/IEEE Frontiers in Education Conference F4F-5 Session F4F III. Category: Creative work learning environment was not efficient production as in software engineering, but the producing of creativity and Projects in this category meet our apprehension about what innovation, we could not push students toward software creativity and creative work is in the context of computer engineering development models. science and with robots. All aspects and subparts of the Instead of supporting some working method, we wanted project work together to form a creative whole. The idea of to investigate the working strategies that students would the project, the mechanism and the program code are adopt outside of the course sessions, and the interplay creative in themselves and also they co-operate and fit between the chosen strategies with the outcomes of students, together impressively. Larger patterns, the limitations of the i.e. the students´ coursework, especially from the viewpoint technology and difficulties of the robotics environment as of creativity. regards this specific task in hand has been understood and solved with appropriate, stable, well-tested and working TABLE 3 solution. As the documents display, attempts have been WORKING STRATEGY AND LEVEL OF CREATIVITY CROSSTABULATION made to solve all sub-problems with multiple approaches, Working Level of Creativity Total strategy and the solutions that do not work so well have been Minimal In Subtasks Creative dropped, resulting in a creative and also well-working, stable Waterfall 1 2 1 0 3 end product. Waterfall 2 2 6 0 8 Some projects in this category consisted of many Experimental 1 0 4 5 smaller independent robot solutions; it was not explicitly Total 5 7 4 16 demanded that the solution should be just one robot. By interviewing all attendees of our learning Example: Tic-tac-toe robot (for picture see table 2). This experiment, we were able to identify three distinct categories is a tic-tac-toe-playing robot which is based on a car-type- of different working styles that students did adopt outside of robot design. The car navigates on top of a playing field the course sessions. We were also able to categorize the detecting the player’s (human player) movements, which the students’ outcomes into three distinct categories, which player marks by black squares, then counts its best move represented our view of the creativity level of the using a MinMax algorithm, moves to the correct position coursework. In our data, we also found a strong interplay and draws its mark using a pencil. The robots work is stable: between these two variables, so with our students it seems it can detect where it is on the board all the time without that the working strategy and the creativity of the course getting lost. outcome are highly linked. Due to the small sample size, it is hard to draw airtight INTERPLAY: WORK STRATEGY AND CREATIVITY (RQ 3) conclusions. It is possible that there are other underlying factors to explain the differences in coursework. For Table 3 shows crosstabulation of working strategy and example: perhaps some students just succeed better in creativity level variables. As can be noted, there seems to be almost anything they do, and perhaps the students’ evident interplay between working strategy and level of performance level would be a better predictor of the creativity. It seems that in four cases out of five, the creativity of coursework. Even so, we argue that our findings experimental working strategy resulted in a student outcome are relevant for further research. If the more successful which we categorized as creative. On the other hand, all of students are using more efficient working strategies the most creative outcomes (n=4) resulted from experimental compared to other students, it would be of great importance working strategies. Statistical analysis (two-sided Fisher´s to teach the efficient working strategies to all students. Also, exact test) confirms that this interplay is most likely not it would seem unwise to force all students into waterfall-type caused by chance (P < 0.01, Fisher´s exact test, FET). working models, for example, if the goal is to learn new domains and not just to learn to follow the production CONCLUSIONS AND DISCUSSION model. Doing this would prevent students predisposed to This paper has described results from a computer science creativity to utilize the creativity in enhancing their own teaching experiment at the University of Helsinki, in which learning. we studied students´ working strategies and their We are convinced that these preliminary results are connections with the students’ outcomes, especially from the important, and that further studies should be conducted viewpoint of creativity. To contrast our typical structured, about this matter. Finding a clear pattern between the teacher-driven learning environments, our aim was to create working strategy and creativity would mean a great help in a learning environment where the support structures would designing better computer science learning environments focus on supporting creativity to bring forth new ideas and with support for creativity, and would thus be a great help in innovation. educating more reflective IT specialists. We are not Usually, in practical computer science courses, the questioning the importance of software engineering in working strategies of students are driven for software computer science, but arguing that in addition, there is need engineering working models, such as waterfall, or other for more creativity in computer science education. software development models. 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Proceedings of the 38th SIGCSE technical symposium on Matti Lattu, ICT manager, PhD (Educ.), University of Computer science education (Covington, Kentycky, March 2007). Helsinki, IT Department, [email protected]
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