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CLASSROOM, UBIQUITOUS, AND MOBILE ADVANCED TECHNOLOGIES TO ENHANCE LEARNING Hitoshi MIYATA Director, Center of Educational Research and e-Learning, Shiga University 2-5-1, Hiratsu, Otsu-city, Shiga, 520-0862, JAPAN [email protected] ABSTRACT Mobile educational systems have started to emerge as potential high quality educational environments that support not only school/college/university education but also life-long learning. The exponential growth of wireless technology in recent years, increasing availability of high bandwidth network infrastructures, advances in mobile technologies and the popularity of handheld devices have opened up new accessibility opportunities for formal education and life-long learning. This keynote address will discuss various aspects of the research that is aimed to exploit the benefits of location, context, device and learner modeling, and combine them with advanced mobile technology to achieve personalized delivery of rich multimedia learning objects: anywhere and anytime; collaborative problem-solving in the context of learners' surroundings, authentic problem-solving through multiple forms of input; and appropriate use of these different media formats as part of problem-solving for rich learning experiences. KEY WORDS Mobile advanced technology, Ubiquitous Learning Environment, Using ICT in Education, Automatic generation of geo-tagged picture map, Mobile devices for learners, 1. Introduction In the educational world, the Internet has created a new learning environment called “e-Learning” and “Ubiquitous Learning”. This u-Learning environment is expected to create a more flexible way of learning than the traditional classroom environment. The Internet environment, for example, is a huge depository of distributed information and knowledge. Therefore, it is natural that people try to use this monster resource to serve their various educational needs. However, this technological resource asks people to create a new framework for their learning environments at the same time. In the future, learners may see new ways and forms of learning, curriculum development, digital contents, learning tools / applications and management of educational data etc. In this environment, people would have closer communication, exchange ideas and opinions with each other and acquire meaningful knowledge from far sites to satisfy their learning/working needs. From 2006 to 2009, the Shiga University ran a four- years project called the ‘GP Project’ as part of a national project named “Selected Efforts of the Distinctive University Education Support Program (Good Practice Project)”, with the support of the Japanese Ministry of Education, Culture, Sports, Science and Technology. In this project, we replaced more than 24 existing courses with u-Learning. The courses had to be integrated seamlessly into the course management information system currently for usage in the educational affairs section. Students can own the data on u-Leaning site and exercise control over that data. These sites may have an "Architecture of participation" that encourages students to add value to the application as they use it. 2. Design of e-Learning Environment Modality of computerization in education is generally categorized as follows: (1) Self-study entities through electronic information media-based materials/courseware; (2) Learning entities with electronic information media as learning/ problem-solving/ representing/ knowledge transmitting tools; (3) Learning entities about information and communication technology/social problems/others; (4) Computerizing entities of education itself. The relationships among these entities should be mutually compensatory so an e-Learning cycle can be developed. The ideas here are in line with building an environment for “anybody” to learn from “anywhere” and at “any time” in the e-Society. There are two purposes for these expansions: on the one hand to enlarge the study opportunity; and on the other to develop people’s new competencies. When people build their e-Learning environment, three issues should be considered (Okamoto, 2000) [1]: the pedagogical goal representing the ability /knowledge as learning objectives, the subject contents and the learning modes. The learning modes are defined by seven learning environments: (1) Distance individual learning environment for mastery learning. This environment provides courseware for KEYNOTE PAPER II 8

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CLASSROOM, UBIQUITOUS, AND MOBILE ADVANCED TECHNOLOGIES TO ENHANCE LEARNING

Hitoshi MIYATA

Director, Center of Educational Research and e-Learning, Shiga University 2-5-1, Hiratsu, Otsu-city, Shiga, 520-0862, JAPAN

[email protected]

ABSTRACT Mobile educational systems have started to emerge as potential high quality educational environments that support not only school/college/university education but also life-long learning. The exponential growth of wireless technology in recent years, increasing availability of high bandwidth network infrastructures, advances in mobile technologies and the popularity of handheld devices have opened up new accessibility opportunities for formal education and life-long learning. This keynote address will discuss various aspects of the research that is aimed to exploit the benefits of location, context, device and learner modeling, and combine them with advanced mobile technology to achieve personalized delivery of rich multimedia learning objects: anywhere and anytime; collaborative problem-solving in the context of learners' surroundings, authentic problem-solving through multiple forms of input; and appropriate use of these different media formats as part of problem-solving for rich learning experiences. KEY WORDS Mobile advanced technology, Ubiquitous Learning Environment, Using ICT in Education, Automatic generation of geo-tagged picture map, Mobile devices for learners, 1. Introduction In the educational world, the Internet has created a new learning environment called “e-Learning” and “Ubiquitous Learning”. This u-Learning environment is expected to create a more flexible way of learning than the traditional classroom environment. The Internet environment, for example, is a huge depository of distributed information and knowledge. Therefore, it is natural that people try to use this monster resource to serve their various educational needs. However, this technological resource asks people to create a new framework for their learning environments at the same time. In the future, learners may see new ways and forms of learning, curriculum development, digital contents, learning tools / applications and management of educational data etc. In this environment, people would have closer communication, exchange ideas and opinions

with each other and acquire meaningful knowledge from far sites to satisfy their learning/working needs. From 2006 to 2009, the Shiga University ran a four-years project called the ‘GP Project’ as part of a national project named “Selected Efforts of the Distinctive University Education Support Program (Good Practice Project)”, with the support of the Japanese Ministry of Education, Culture, Sports, Science and Technology. In this project, we replaced more than 24 existing courses with u-Learning. The courses had to be integrated seamlessly into the course management information system currently for usage in the educational affairs section. Students can own the data on u-Leaning site and exercise control over that data. These sites may have an "Architecture of participation" that encourages students to add value to the application as they use it. 2. Design of e-Learning Environment Modality of computerization in education is generally categorized as follows: (1) Self-study entities through electronic information media-based materials/courseware; (2) Learning entities with electronic information media as learning/ problem-solving/ representing/ knowledge transmitting tools; (3) Learning entities about information and communication technology/social problems/others; (4) Computerizing entities of education itself. The relationships among these entities should be mutually compensatory so an e-Learning cycle can be developed. The ideas here are in line with building an environment for “anybody” to learn from “anywhere” and at “any time” in the e-Society. There are two purposes for these expansions: on the one hand to enlarge the study opportunity; and on the other to develop people’s new competencies. When people build their e-Learning environment, three issues should be considered (Okamoto, 2000) [1]: the pedagogical goal representing the ability /knowledge as learning objectives, the subject contents and the learning modes. The learning modes are defined by seven learning environments: (1) Distance individual learning environment for mastery learning. This environment provides courseware for

KEYNOTE PAPER II 8

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knowledge/skills acquisition, i.e., typical e-Learning courses, such as WBT/VOD (Video On Demand) systems (Hui, 2000) [2]. Streaming Media-Based Education (Uskov, V. & Uskov, A.,2005) [3], e-Learning resource for teacher education utilizing VOD-compatible teaching portfolio system (Miyata, 2007) [4]. (2) Distance individual learning environment for discovery learning using various search engines (VOD search and navigation mechanism). (3) Distance individual learning environment for problem solving learning using simulations, ILE (Interactive Learning Environment), etc. (4) Videoconference systems in the classroom environment for discussion, instructional presentation, question-answer sessions and telecommunications (Chen, 2001) [5], (Nieminen, 2001) [6]. (5) Collaborative learning environment for small groups/pairs using videoconferencing, various types of communication tools, various applications accompanied by shared-screen viewing and learning log tracking mechanisms. (6) Collaborative simulation learning environment for learners of different learning performance, different functions in team-work learning patterns to form special skills in the learner’s own domain, e.g., a collaborative activity within the cockpit of a jet airplane. (7) Linkage/ Coordination among different organizations and/or areas, e.g., access to an online school library, online museum, etc. The most important point in the establishment of e-Learning environments is to start by defining the instructional goals, and then to classify the learning contents that are best equipped to build the required learning environment. Moreover, research into appropriate methods is required to build the asynchronous collaborative learning contents. Further research should be devoted to the study of learning environments with the virtues of individualized learning and collaborative learning. In this case, the transmission of real images and voice data is required. The fundamental environment components for e-Learning systems include the whole information system related to e-Learning environments should consist of several management functions, such as curriculum/learning materials management, learners’ profile/log-data management, learning support as the core framework, LMS (Learning Management System) and LCMS ( Learning Contents Management System). To construct such educational management systems, several data/file processing modules are required, such as a distributed file system, synchronous data communications, etc. If any applications and tools related to e-Learning can be plugged into the core framework, we can build an integrated e-Learning environment where learners can share/operate this software/data in real time. In addition, the total management system of e-Learning is required for implementation in a real educational project/practice, which means a requirement for research project management, learning schedule management, courseware development, etc.

3. Case Study The fellows of the Center of e-Learning at Shiga University developed mobile & collaborative Learning environment by a concept of "mobile-as-participation-platform" as follows; 1) Improvement of Classroom Communication in Large-scale Remote Lecture Classes Utilizing a Cell Phone-compatible Comment Card Database System (Miyata, 2004, 2006) [7] [8]. 2) Digital Contents for u-learning about Planktons by using PDA, PSP, and Mobile Phones (Miyata, Ishigami, 2007) [9]. 3) Lunar Observation Support System for Mobile Phones and PDA (Miyata, Suzuki et al, 2007) [10]. The case study about Mobile and Collaborative Learning Development Projects, “Development and evaluation of the flower identification database for mobile with a geo-tagged picture map” is addressed in this paper.

Figure 1 The international project for Lunar

observation in science education

3.1 Introduction Through its “New Strategy for IT Revolution (2006) in Japan,” the Japanese Ministry of Education promotes the use of information technology in school education, identifies the active use of information and communication technology (ICT) to enhance learning, and advances the improvement of the teaching skills that leverage ICT as key challenges. Further, the fact that the use of ICT leads to enhanced scholastic performances has been objectively proven in various studies including “Research to assist in the promotion of informatization in Education” (Shimizu, 2007) [11]. In practice, however, the outcome from the “Survey on Information Education and use of ICT” showed that among the 256 primary and junior high schools surveyed in K City, the average achievement index reflecting a teacher’s ability to leverage ICT was only 67.1 points (“partially achieved”). Moreover, the proportion of schools that utilized ICT in classrooms remained at 73.3%. Some of the reasons for

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ICT not being utilized despite its proven effectiveness included “lack of skills in collecting and developing content” and the claim that such tasks were “too laborious.” At the same time, it was noted that there was an increasing number of newly-employed primary school teachers who were conscious of the deficiency in their flower-identifying skills, which led to the inclusion of an assignment in the teacher training program that involved the creation of a flower observation picture map. We have thus decided to develop a flower identification and picture map system as a joint research project with the university.

Field studies are led in various places, in order to improve the concern for science education. However, in such field studies, as the studies are often done in places which are geographically remote one from the other, the documents which can be carried have to be limited, and the instructions about the contents of the study have to be modified according to the situation, as we experience various restrictions. Therefore, it is often the case that the study is only lead as an experience. In that case, the object of the children's interest is deeply involved, but their interests are not stimulated at all. In some cases their experience of a particular instant cannot be sustained anymore, then we have the problem that the study cannot be deeply understood by them. On the other hands, many education support systems with using mobile information devices have been developed as the advance of mobile device technologies (Hsi et.al. 2004 [12], Roschelle and Pera 2002 [13], Miyata 2007 [14]). In such situations, some researches have been using mobile information devices for field studies in order to solve this problem; they have accomplished remarkable development in recent years and have therefore flourished significantly.

These researches are divided roughly into two themes: (1) studies where mobile devices were applied to the material presentation of the field study, (2) records of learners’ activities using mobile devices in the field study. The examples for the first theme (1) are utilization of a mobile phone in a zoo for the presentation of each animal's information (Chou et.al. 2004 [15], O’hara et.al. 2007 [16]). In these two researches, the function of contents display has been achieved by reading GPS and QR code in correspondence to the place of the study. However, in order to promote the children's interest, we can think that the contents display according to each study situation is effective, but has not been achieved. As an example of the second theme (2), we have the example of the information gathering in the outdoor activity using PDA (Haapala et a. 2007 [17], Yoden et al. 2005 [18]), and the example where camera and e-mail function of the cellular phone were used. (Takenaka et al. 2006 [19]); however, the function of the first theme (1) was not realized in this case. As an example of the combination of two themes, we have the example of the cellular phone with GPS based learning support system for field studies at zoo. The system can display dynamically the contents that were suitable for study based on a learners' position information and his past activity history, and conducted by using a cellular phone with a GPS function (Ogino et

al. 2008 [20] ). However, teachers must prepare lots of contents about animals before the field work.

In this paper, we have described how we have used cellular phones with a GPS Logger as mobile computing devices. By acquiring and saving information about a user's position and the history of his past activities, we have developed a system and contents of flowers for a field study support. We have attempted to deal with some parts of the second theme (record of the study history) by recording the learners’ comments with a cellular phone in the student's study history, for every user and we could thus suggest a solution for the problem mentioned in theme (1). Furthermore, we have evaluated this system by taking up fields outside the school, developing the contents about flowers for field study as an object of field study, and conducting an evaluation experiment. 3.2 Research Objectives There are two objectives to this research. The first is to develop a system for assisting in the identification of flowers and creation of picture maps during field observation learning. The second is to trial the system with sophomore university students who are studying to become teachers in order to validate the effectiveness of the system. Specifically, the following four domains will be analyzed in order to measure the effectiveness of the developed system. (1) “Interest, motivation, and attitude” – whether the

students were able to feel an affinity with nature and further enhance their motivation for exploring it through the field observation of flowers using the mobile information terminal.

(2) “Thinking and decision making” – Whether the students’ breadth of observation and research activities increased on completion of the flower observation fieldwork that involved utilizing the multimedia contents on the information terminal, as opposed to relying exclusively on library resources.

(3) “Technique and expression” – Whether the students became proficient at utilizing various tools and equipment to fulfill particular needs and create picture maps efficiently through the use of creative techniques following their completion of the field observation utilizing a mobile information terminal and a GPS logger.

(4) “Knowledge and understanding” – Whether the students were able to identify flowers accurately and comprehend phenomena that are hard to observe directly, such as seed dispersal, by using the multimedia field guide during the fieldwork observation.

3.3 Research Methodology In June 2008, an inquiry was made regarding the current flower observation learning being imparted in primary schools, and interviews were held with twelve primary

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school teachers and one curriculum director to discover the requirements with respect to the enhancement of this curriculum.

In order to validate the effectiveness of the system, a paper-based survey regarding the learning content was administered to the participants. Each question in the survey belonged to one of the following three domains: (1) interest, motivation, and attitude; (2) thinking and decision making; and (3) technique and expression. In addition, a short objective test was conducted to measure the knowledge and understanding of the students. Further, we investigated motivation, feeling of participation, satisfaction, and confidence as overall elements in relation to the learning activities using the present system. Finally, the flower observation map and the learning portfolio created by the students were analyzed. 3.4 The Content and Functionality of the Flower

Identification and Picture Map System On the basis of the results of the prior inquiry, it was decided that the system would comprise the following contents and features: (1) 961 color images, showing 220 flower varieties that are commonly observed in the Kansai region, equipped with the facility to search on the basis of each flower’s season, color, and name so as to facilitate its identification (Figure 2); (2) the ability to view high-resolution video clips of difficult-to-observe scenes such as dispersal of seeds; (3) detailed explanations on how to identify flowers that are difficult to distinguish from each other (Figure 3); and (4) a picture map creation system whereby observation records and photographs would automatically be shown on a Google Map using GPS data (Figure 4). Observation records would be stored on the server, which could then be used for collaborative learning.

Figure 4 A flower picture map created using this

developed system

3.5 System Configuration and Architecture The Flower Identification Database System for Mobile Devices with a Geo-tagged Picture Map developed for this research is a client-server system that comprises (1) the mobile phones owned by the students for sending picture and text messages; (2) the client PC used by the lecturer; and (3) the server running a SQL database server for storing the submitted pictures and comments and a Web server for displaying the submitted information. The client interface for the learners’ use was developed using Ajax and the Google Maps API, and it can run on Windows NT 4.0, 2000, XP, and Vista. The comments submitted from the students’ mobile phones are dynamically processed using Asynchronous JavaScript and XML, stored on the database server, and outputted as XML or CSV files. CentOS version 5 (Redhat Linux compatible), My SQL version 5, and PHP version 5 were used for the server. Figure 5 shows the Flower Identification Database System for Mobile Devices with a Geo-tagged Picture Map. KML (Keyhole Markup Language) is a file format used to display geographic data in an Earth browser such as Google Earth, Google Maps, and Google Maps for mobile. KML uses a tag-based structure with nested elements and attributes and is based on the XML standard. The most common way to embed geo-data into an image file is using the Exchangeable Image File Format (EXIF). The data is stored in binary form in the EXIF headers in a standard way. We developed the library for reading the headers of JPEG files.

Figure 2 A screen showing flower search results

Figure 3 A screen containing an explanation on the

method of distinguishing between flowers

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3.6 Educational Practice Utilizing the System at

Outside Fields Work The educational practice at outside fields work were undertaken with a total of 208 students (78 male and 130 female) comprising 36 sophomore students training to become teachers at S University and taking the course entitled “Multimedia and Classroom Enhancement” and 172 students from B University taking the “General Studies” course (across three classes). The flower observation fieldwork was undertaken in pairs. Each pair was given a Sony PSP and GPS logger, and the students were asked to bring along mobile phones equipped with cameras. Figure 6 shows a scene in which the observation is taking place using the setup. For those pairs that could not bring mobile phones, a USB camera was attached to the PSP provided. The students observed flowers as they walked on the university campus, took pictures with the cameras on their mobile phones, and sent emails to the system server comprising the name of the flowers observed, any related observation notes taken, and photographs of the flowers in the form of an attachment. When the students were unable to identify the name of a particular flower, the multimedia field guide for PSP was used to assist in its identification. The GPS logger automatically recorded the position information in its internal memory every five seconds. After the observation was complete, students returned to the lecture room and connected the GPS logger to a PC. The position data were then sent automatically to the system, geo-tagged (i.e., the position data were added for referencing), and an observation map such as the one shown in Figure 4 was generated.

In order to comparatively investigate the effectiveness of the system, the 208 students were divided into two equal groups: Group A (104 students) and Group B (104 students). The system was then utilized according to the execution schedule shown in Table 1. Since the students were enrolled in three classes, the maximum number of students at any one session was 36.

Figure 5 The Flower Identification Database System for Mobile Devices with a Geo-tagged Picture Map

Table 1 Execution Schedule for the Observation Activities of Each Group

First Week (flower observation fieldwork on campus)Group A (104 students) Group B (104 students )

Collection and identification of flowers without this system, taking of pictures and creation of a picture map on the paper not by using this system

Collection and identification of flowers with PSP system, taking of pictures and creation of a picture map on the web by using this system, GPS Logger

Attitude survey taken, self assessment sheet filled, and short test completedSecond Week (flower observation fieldwork at the school where the students had undertaken internship ) Group A (104 students) Group B (104 students )

Collection and identification of flowers with PSP system, taking of pictures and creation of a picture map on the web by using this system, GPS Logger

Collection and identification of flowers without this system, taking of pictures and creation of a picture map on the paper not by using this system

Attitude survey taken, self assessment sheet filled, and short test completed

Figure 6 A scene from the flower observation learning

session (GPS logger is located inside her hat)

3.7 Results and Discussion 3.7.1 Evaluation of the System by the Students The results of the students’ survey regarding their assessment of the developed flower observation assistive system’s ease of use, clarity of flower photographs, and flower identification method are summarized in Table 2. Many students responded positively in the above context regarding the ease of use, clarity of photographs and video clips, and display size with respect to the flower field guide. Moreover, while many students also

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responded positively regarding the function whereby one could search for a flower by name, season, and color, some students commented that the function through which the observation record was submitted to the server was slightly cumbersome. It thus became clear that the developed system required further enhancements that would enhance its usability.

3.7.2 Validation of the System’s Effectiveness The result of the test to objectively measure the students’ knowledge and understanding of the developed system that was administered following the completion of fieldwork is summarized in Table 3. There were four types of questions in the test: (1) those related to identifying and naming a flower given its picture (8 questions); (2) those connected to looking at illustrations of seed dispersal and choosing the correct one (4 questions); (3) those concerned with reading the explanations and illustrations on the method by which to distinguish between similar flowers and choosing the correct explanation (4 questions); and (4) those inviting free-form comments on the observational study of flowers.

An analysis of variance was performed in order to compare four factors: 2 (intra-group) × 2 (inter-group). As a result, a significant interaction with 1% standard was detected, and the LSD method was used to perform multiple comparisons on the mean score. This resulted in a statistically significant difference being confirmed within Group A between week 1 (when photo identification sheets were utilized) and week 2 (when the present system was utilized). Furthermore, there was a statistically significant difference between Group A in

week 1 (where photo sheet identification sheets were utilized) and Group B in week 1 (when the present system was utilized). On the other hand, there was no statistically significant difference in the mean scores of weeks 1 and 2 within Group B.

This outcome can be interpreted as follows. The reason for Group A having a lower test score f in week 1—wherein learning took place based on photo sheets of flowers—was that, as shown in Figure 7, their mean scores for the questions related to flower identification, seed dispersal, and flower identification method were consistently lower than Group B, with 32% of the students leaving more than one question on the identification of flowers unanswered.

Table 2 Evaluation of the system by the students

good not good No response Overall usability 196 2 2 Clarity of pictures and videos 197 1 2 Appropriateness of display size 196 2 2 Identification

method by color 197 1 2 Procedure for

submitting pictures 195 3 2 Procedure for

submitting obser- vational comments 179 19 2

(n=200)

While color photo sheets were used for looking up

and identifying the name of the flowers, these sheets only included 24 representative spring and summer flowers, resulting in the students responding with “other flowers” when they were unable to identify the name. In addition, as in the photographs used in textbooks, the photo sheets only showed photographs taken from an angle that was optimal for capturing the characteristics of each flower. When the students observed the same flowers in the field, there were many instances whereby they saw the flower from angles other than those shown in the textbook, making identification problematic.

Figure 7 Analysis of the test results for Group A

Table 3 Score results of the objective test on knowledge and understanding

Group A Group B Inter- Group 1st Week 46.1 69.9 *p<.05 2nd Week 75.8 60.2 ns Intra-Group **p<.01 ns

(n=200)

In contrast, the number of Group A students leaving questions related to flower identification unanswered was reduced to 8% in the second week, thereby causing the mean score to rise. Using the present system, students began the identification process on the basis of the current season and color of the flower. After the relevant candidate flowers are shown, photographs could be seen of not just the flower but also of its stem and leaves taken from various angles, thus aiding identification as well as boosting the retention of knowledge. This fact was backed up by the students’ free form comments such as follows: “it was easy to search for flowers by their color” and “identification was possible as photographs of not just the flowers but close-up photographs of the stems and leaves as well were provided.”

Further, while a significant difference was not detected in the questions related to seed dispersal and those related to the identification method between weeks

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1 and 2, there was an increase in the mean score for these questions. From the free form comments such as: “looking at the seed dispersal video stimulated my interest” and “I was able to understand the explanation clearly after looking at the slow-motion video of seed dispersal,” it can be deduced that the video clips were able to supplement areas that were difficult to grasp based exclusively on photo sheets.

Next, the result of the self-assessment questionnaire comprising 4-scale multiple-choice questions is shown in Figure 8 for Group A and in Figure 9 for Group B. The analysis of variance performed resulted in a significant interaction with 5% standard being confirmed between the two groups. The LSD method was used to perform multiple comparisons on the mean value. As a result, it became clear that scores for questions related to “thinking and decision making” (e.g., “Did you understand how to differentiate between the Kansai Dandelion and Western Dandelion?” and “Have you been able to formulate your own opinion based on information gained through investigation?”) were significantly higher in Group A when the present system was used for the concerned study.

The fact that the scores for questions related to

“interest and motivation” were high for both groups with or without the use of the present system and did not show a significant difference is attributed to the incorporation of the outdoor fieldwork activity, which served to increase the interest and motivation of the students. Further, scores for questions related to “technique and expression” also improved when the present system was utilized. Free form responses included the following: “it was easy to create the picture map automatically, so more

time could be spent on discussions related to the problem on flower identification”; “even when I uploaded an erroneous response due to the incorrect identification of a particular flower, I was able to discover the error during our discussions by comparing our map with maps created by other groups;” “an observation map was created and uploaded during the second week at the school where I undertook my internship; this enabled me to compare the mountainside and city regions;” and “I have endeavoured to describe the identification method in the observation comment.” These comments reflected signs of the students’ creativity in the course of learning as well as their proactive attitude.

Based on the outcome and observations stated above, the effectiveness of the system has been validated in the domains of “knowledge and comprehension,” “thinking and decision-making,” and “interest and motivation.” 4. Conclusion and Future Work This article describes the development and the evaluation of the Flower Identification Database System for Mobile Devices with a Geo-tagged Picture Map. Learners can create the geo-tagged observational picture map with observational comments of flower on the Google maps by this system. This database of flowers includes 961 color photographs. Learners can search and identify flowers by season, color, and name, can watch high-resolution video clips showing scenes that are difficult to observe, such as the dispersal of seeds. Learners can read the detailed explanations on the method of identifying similar flowers that are hard to distinguish. The system was trialed with 208 university students as part of a fieldwork involving the observation of wild flowers. As a result of the evaluation, the effectiveness of the system was validated in the following four domains: (1) interest, motivation, and attitude; (2) thinking and decision making; (3) technique and expression; and (4) knowledge and understanding. In the future, we plan to undertake field trials with primary school students using PSP with GPS and a camera connected via USB.

Figure 8 the average scores of the self-assessment

questionnaire for Group A

Figure 9 the average scores of the self-assessment

questionnaire for Group B

Acknowledgements A portion of this research was conducted through assistance in the form of a research grant made in accordance with Subject No. 20500834 (Representative: Hitoshi Miyata) of Grant-in-Aid for Scientific Research of the Ministry of Education in Japan for FY 2009. References [1] Okamoto, T., “A Distance Ecological Model to Support Self/Collaborative-Learning via Internet”, Proc.

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of the International Conference of Computer on Education, pp.795-799, 2000.

[2] Hui, S., “Video-On-Demand in Education”, http://www.cityu.edu.hk/~ccncom/net14/vod2.htm (2000)

[3] Uskov, V. and Uskov, A., “Streaming Media–Based Education: Outcomes and Findings of a Four-Year Research and Teaching Project”, The International Journal on Advanced Technology for Learning (ATL), 2(2), pp. 45-57, 2005.

[4] Miyata, H., “e-Learning Resource For Teacher Education Utilizing VOD-compatible Teaching Portfolio”, The International Journal on Advanced Technology for Learning (ATL), 5(1), (Now Printing), 2007..

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