Wireless Sensor Networks for elementary school learning environments Ricardo Silva
Maria José Marcelino
Jorge Sá Silva
University of Coimbra Pólo II, Pinhal de Marrocos, 3030-249 Coimbra, Portugal
University of Coimbra Pólo II, Pinhal de Marrocos, 3030-249 Coimbra, Portugal
University of Coimbra Pólo II, Pinhal de Marrocos, 3030-249 Coimbra, Portugal
[email protected]
[email protected]
[email protected]
ABSTRACT Technology has played an important role supporting education. Well-known paradigms like e-learning and m-learning have been revolutionizing the traditional concept of learning, which due to ubiquitous computing characteristics has became closer to students. In this paper we approach the concept of Wireless Sensor Networks (WSNs) and their potential to improve the quality of teaching and learning in elementary education. Nowadays, WSNs are the ultimate interface between subject matters and students, enhancing the interactivity with real learning and consequently improving the acquisition and construction of knowledge. We also present uMove2Learn: a tool, based on WSNs, designed to assist learners and teachers in their daily lessons. This proposal aims to use WSNs to help inserting learners in the learning context, accommodating the requirements of the educational curricula.
1.
INTRODUCTION
Learning is a complex process whose efficiency level depends on learner’s endeavour [1]. The biggest challenge of teaching is not to transmit information, but to get the learner’s attention, as well his interest in different subject matters. Over the years, a huge effort has been made in order to choose the right curricula, tools and techniques to enhance the teaching and learning quality of the educational systems worldwide. Several paradigms have emerged over time, grouping types and techniques of learning. Behaviourist, Constructivist and Context-aware learning are just some examples. Behaviourism [2] is based on the concept that an antecedent (stimulus) can trigger a new behaviour. Behaviour consequences should be included in the previous antecedent, reinforcing the same behaviour. In behaviouristic learning the key is to create the right stimulus in learners in order to start the cycle. Although a bit out of date behaviouristic
approaches are still too much used in our schools. Constructivist learning [3], enhanced by Piaget and Vygotsky, defines that learners developed and construct new learning concepts based on existing and on novel knowledge. Context-aware learning [4] is a paradigm where learners are able to acquire new knowledge based on the local environment, its characteristics and events. Constructivism and Context-aware learning paradigms are, among others, the main structure of modern learning concepts. Technology have allowed the implementation of those approaches, leading to e-learning, m-learning and u-learning, introducing the concept of anytime and anywhere learning. The spread of handheld devices brought into place flexible and cost-effective mobile platforms. Mobile learning is deeply approached in [5], where besides the theoretical principles are presented several practical cases. Also in [6] are presented significative contributions, capable of being used in several areas. After the appearance of ubiquitous computing and the concept of m/u-learning, contributions mainly related with context-aware learning have appeared, exploring the potential of such mobile platforms. Ubiquitous learning is more than interaction between people and context-objects; it is also interaction among people. Based on such concept, first in [7] and recently in [8] are presented scenarios where the learners, while handholding a device, are able to receive information from different context-objects and also interact with other people in the same or different situations. In [9] it is presented a study where the main goal was to evaluate the capacity of the pervasive technologies to integrate learners with the learning object. In this case, the object of study was the forest, and the evaluation was carried on by a selected group of students under different situation, but always guaranteeing free mobility and encouraging the exploration. The experience concluded that learners have become able to recognize and describe/explain what they had seen through their PDA’s while in the forest. In [10] it was developed a suite of games to enhance the learning experience of Museum visitors, like quiz or memory games. Such simple games were the sufficient to captivate the attention of visitors and guarantee an efficient guide by the museum. Moreover, in [11] pervasive computing like sensor and RFID was introduced in toy environments, bring-
ing learning to children plays. While children play with a Playmobil Knight’s Castle, sounds, movies and stories were playing in a handheld device. These concepts can be applied in almost all learning contexts, even in traditional schools. All of them are significant and useful contributions. However, nowadays, it is possible to go deeper in ubiquitous computing and interact with the object or with the environment conditions, instead of waiting for their interaction. Such idea was already widely approached in [12], introducing the concept of sensing the context. Nevertheless, only recently, with technology improvements, the sensing concept is well known and ready to be used. It is called Wireless Sensor Networks. Wireless Sensor Networks (WSNs) appeared bringing the missing interface between the real and the virtual. Quickly such tools started to be applied in all areas, such as industry, healthcare, environment, communications, transports and education. Wireless Sensor Networks [13][14] are networks composed by low cost devices, capable of sensing, process and communicate wirelessly. Such devices are also provided with their own energy resources and are able to be deployed anywhere. Natively, the communication protocol is the IEEE802.15.4 [15], supporting star and mesh topologies, which enhances the dynamic of such type of networks. Each device is called mote or sensor node and each network has one powerful node called Sink Node. The Sink Node is the interface to the exterior of the network. Each mote is capable of sensing real parameters, such as: light, temperature, humidity, pressure, acceleration, positioning, among others. In [16] it is identified the main design constraints to integrate WSNs in ubiquitous learning and in [17] the author presents a context-awareness appliance of WSNs in Ubiquitous Learning, i. e., the author designed a theoretical optimal solution where the teaching content was adapted to the learner’s context, using several types of sensors to measure since ease-to-read parameters as temperature to critical aspects as human emotions. In this paper, based on ubiquitous learning using Wireless Sensor Networks, we propose a platform to explore the capabilities of WSNs related only to easy-to-read/easy-tomeasure parameters. Our solution aims to enhance the learner’s role in the educational context, using WSNs to surround him/her in the real context, using activities, games and challenges to embolden learners and ensure their motivation. In the next section we present more deeply our paradigm. In the third the designed architecture to implement the paradigm is presented as well as a case study. In the fifth section we conclude the paper with some conclusions and future work.
2.
WSNS IN LEARNING ENVIRONMENTS
As mentioned in the previous section, [7] to [11] presented ubiquitous learning solutions, where the learner would be able to receive information from his/her context and interact with other learners/people in the area, through its own handheld device. Nevertheless, with WSNs it becomes possible to interact with the context elements too. And [12] to
[14] approached deeply such possibility from a theoretical point of view.
2.1 Paradigm The integration of WSNs in educational activities can help learners to improve the learning process, helping them to become more active from the start and to make learning an easier and more enthusiastic activity. Quoting [18]: ”Learning is not an automatic consequence of pouring information into a learners’ head, which requires the learner own mental involvement and doing”. We can get such involvement using WSNs. The hardest issue in learning is to get learners attention and interest about the discussed topic. It is necessary to conquer learner’s willingness. Theoretically, independently of the application type, it is necessary first conquer learner’s and teacher’s attention. After that, the learner will be presented with different challenges supported by real/live data. Such challenges will be based on the learner’s context and the main data will be obtained through a local WSN. This approach is completely based on constructivism learning within a contextaware paradigm. Teacher’s role is crucial in order to use, design and improve our platform.
2.2 Practical Application From an application point of view, we intend to apply WSNs to help practical experiences of elementary school learners. We take as an account the Portuguese learning system and as a case study the 3rd and 4th school years. In such school years, there are several situations where it is possible the application of WSNs to help learner’s interaction and understanding. The list of potential applications is big and the majority of the items are related to the discipline of science and environmental studies. From the case studies, we emphasize items that can be easily monitored, as well as integrated in a WSN, such as described in the table 1. We considered only activities that are easily supported by the available sensor nodes. WSNs can be applied to show what the value of each parameter really is. Moreover, students can do everything by themselves, trying each experiment more than once, and observing the results in their own computers or handheld devices for different situations. This possibility accomplishes with the Constructivist paradigm, reenforcing its importance. They are actually able to observe and collect data outside the classrooms, instead of studying them first and observing them later. [9] proved the efficiency of pervasive technology to enhance the learning activity. Therefore, the study of properties like sound, temperature, light or humidity can be easily supported by technology. For instance, to study and understand the power of sun, as a source of heat and life, it is possible to integrate technology with an activity or a game where learner would be looking for the highest hotspot of their school playground. Besides, they would have the opportunity to measure such a parameter
outside of the school and out of any school activity too, like in the park. Motes are cheap and it is easy to integrate them with handheld devices. Our application aims to deliver one mote per learner and at least one mote per classroom. Students will use them to interact with everything in their current context, anywhere and at anytime (a context-aware learning triggered by the learner). The next section explains the platform we have developed, called uMove2Learn. Table 1: WSNS MEASURABLE ITEMS FOR LEARNING APPLICATIONS Type of item Vital signals Sound
Temperature and light
Air quality
Water quality
Soil quality
Humidity
Description - Showing in values what is breath, arterial pressure, heart rate, etc. - Recognize the intensity and sound velocity. - Recognize the sound level as pollution, studying different environments. - Recognize the sun as a source of heat and light. - Measure heat and light parameters and recognize their values. - Relate the heat and light values with the different sun positions. - Recognize other types of light and heat sources. - Study the reflection of light through different objects. - Monitor the air quality of several indoor/outdoor zones. - Recognize different gases and their values in the current environment. - Monitor the water quality of several water sources. - Observe the water components and their levels. - Measure well known mineral in the soils. - Recognize each mineral and understand its measured level. - Measure the humidity level in different places. - Create hot spots with hot water and test the humidity there.
3. UMOVE2LEARN uMove2Learn is an application that uses WSNs to frame learners in the learning context, allowing a free exploration of controlled scenarios. The first subsection presents the application architecture. The second subsection explains how it works and the third presents a case study.
3.1 Architecture First of all, the architecture of the uMove2Learn platform is composed by at least three applications, which can be enhanced if we considered a national or international social network. The three applications are: • The handheld application, called iLearn. • The classroom Sink Node application, called iTeach. • The school Central Server, called imInCharge. There is also the mote device called Tami, responsible for sensing the required property. A Tami can be any kind of object; it will depend on the learner’s age and the situation being studied. As mentioned before it is also possible to extend the platform to connect different schools, establishing social networks among them. In such case it would be possible to cross information of the same activities and create challenges among learners. To support this functionality, the platform would need to include external servers deployed per zone, district, and even country, organized hierarchically. At this point we only consider one school, however the scalability is feasible. At least, theoretically. We also consider that our Tami can talk directly with the iTeach when the connection is available (scenario 1). If not the Tami must talk with the iLearns (scenario 2). Figure 1 presents both. Figure 1 presents the platform in what could be a school with three classrooms. Each one has one iTeach and three Tamis. Each Tami can belong to a specific learner or to the classroom. At the bottom of the figure we can observe an iLearn and a Tami. This Tami cannot reach the iTeach, however it is able to interact with the handheld device (iLearn), which will manage the application in that current context (scenario
Figure 2: Creating a new activity.
Tamis and iLearn as well are able to support different applications and operate in different scenarios.
Figure 1: Scenario 1 and 2 of the uMove2Learn application.
2). In scenario 1, without iLearn, iTeach deals with all local Tamis. Such an architecture allows a dynamic platform to be used for many applications, anywhere and anytime. The design of Tamis and iLearn interfaces are essential to hold learner’s interest to use uMove2Learn. The type of application and its relation/adaptation with the learner skills are fundamental to the success of knowledge building.
3.2 Operational Mode Tami runs a 6lowPAN [19] implementation, which means that it supports IPv6 connections, enhanced with the ICatchYou Protocol and an efficient handover mode presented in [20], in order to allow the mobility between different iTeachs and iLearns. For different school years, Tamis will be adapted with the necessary hardware modules, and reprogrammed with the respective software. Learners can use Tamis as a usual school tool like the pen and the paper. Outside the school Tamis switch the connection to the learner’s handheld device (iLearn) and can remain connected to the uMove2Learn network. iLearn capabilities are dependent on the school year of the learner. Hence, for each year the learners must update the iLearner and Tamis, growing all together. Tamis should be like a friend that evolves at the same pace of that of the learner.
For each application, Tamis is the interface between the main parameter being studied, e.g. the sound, the light, the humidity, etc., and the iTeach. iTeach collects the information of all learners of the classroom, maintaining an updated database of applications and results. Such database can be crossed with others, from others classrooms, in imInCharge. imInCharge controls the school applications and evaluation results, maintaining updated information of all activities. iTeach and imInCharge have also great potential, because both interconnect teachers and learners, helping constructing a social network, which can be very useful for the learning process.
3.3 Case Study iTeach is a powerful tool where teachers can design their own applications or games, always based on the supported and existent sensors. Although the system has such capability, there are already some basic activities integrated, which teachers can also adapt. Figure 2 presents the iTeach ”activity creation” form. To create a new activity, teachers must insert the name of the activity; select the attributes available on the list, insert the objectives and the activity description. It is also possible to include an icon. To add a new attribute teachers have just to click on the attribute and drag and drop it on the attribute field. To start an activity it is necessary to associate the learners with the sensors and consequently with the activity. Hence, another form was developed to support it (see Figure 3). In Figure 3, activities are listed based on the available sensors and sensors are listed based on the selected activity. For instance, if the teacher selects the first activity, where the
Figure 3: Configuring an activity.
unique sensor necessary is the temperature sensor, only that sensor will appear as available in the sensor field.
Figure 4: Ranking in Hot and Cold.
After that, the teacher must distribute the available sensors in the class and save the configuration. For instance the first activity has an icon of a sun over a glacier and it corresponds to the game of ”hot and cold”. Hot and Cold is a traditional game where one kid hides an object and the others have to find it. During the game, the kid who hid the object guides the others telling them if they are cold or hot, considering the distance to the object. This game, using WSNs, can be done replacing the object to find by the hottest point of a specific area. (The hottest point can be changed to the coldest point, the more polluted point, the more sound polluted point, etc...) Thus, each learner can walk freely around an open space, looking for the hottest point. At the same time, the value measured by each learner is sent to the central computer (iTeach), where the ranking is calculated and showed. Figure 4 presents the ranking interface. Learners have a time limit to choose a place that in their opinion is the hottest point of the zone under study. Feedback will be given and learners, based on that, can change their selected place. At the end, the final Ranking, temperature and respective classification will be presented. This game will allow students, in a natural way (as in [10] and [11]), to learn about the sun and respective cold and hot zones in open spaces. They will be able to recognize the effect of shadows, wind, airflows and time of exposition, of the temperature in a specific local or object. Furthermore, learners will understand, by experience, the relation between those factors and the Celsius/Farenheits measured degrees, learning not only what temperature is, but also what is the importance of the sun as a heat source and how such parameter is measured and how the Celsius scale works. Such information should be complemented with the usual information provided by the teacher. After the activity, learners will certainly understand better the theory, identifying it with the experience performed.
Figure 5: iLearn Hot and Cold interface. Moreover, they can also play the activity outside school, at home for instance. To do that, they only need to own Tamis and iLearn. iLearn as mentioned before can be a handheld device or even a Laptop like Magalh˜ aes [21]. It also must have installed the application to support activities, like hot and cold. Figure 5 presents the interface of the iLearn hot and cold version, where the learner can observe by himself/herself the temperature of the spot where he/she is at a particular moment. The learner can also observe the history since the application was started. The uMove2Learn platform allows the development of many activities, being also a challenge for teachers to find new and innovative ways to improve learning.
4. CONCLUSIONS AND FUTURE WORK Learning is a process dependent of several qualitative variables. In order to improve the learning process many studies have been performed and different paradigms approached. Constructivism and Context-aware learning paradigms are the most popular due their theoretical efficiency. When sup-
ported by technologies the theorem becomes real and platforms like e/m/u-learning have increased learner’s success. [10] In this paper we presented a solution based on WSNs called uMove2Learn. This solution increases the possible contact between learners and the object of learning and allows teachers to adapt and developed new modules, meeting with their claims. Constructivism and Context-aware learning were thus seriously applied. uMove2Learn is capable to support several activities based on the real monitoring of any supported parameter. In this paper was presented the example of ”Hot and Cold ”, but much more different activities could be presented, for instance: an activity where learners could measure the air pollution of a specific place and conclude about the main reasons for the obtained result or a more exigent activity where learners would be encourage to plant a tree in a specific place and with Tamis measured the soil constituents and their impact on the tree’s development. uMove2Learn also aims to include a Website where new modules can be downloaded. Besides, the website should also allow the upload of new modules, being a share point among teachers as well as the centre of the social network thus generated.
5.
[11]
[12]
[13]
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[15]
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