Ubiquitous learning environment: An adaptive teaching system using ubiquitous technology

Education has undergone major changes in recent years, with the development of digital information transfer, storage and communication methods having a significant effect. This development has allowed for access to global communications and the number of resources available to today's students at all levels of schooling. After the initial impact of computers and their applications in education, the introduction of e-learning and m-learning epitomised the constant transformations that were occurring in education. Now, the assimilation of ubiquitous computing in education marks another great step forward, with Ubiquitous Learning (u-learning) emerging through the concept of ubiquitous computing. It is reported to be both pervasive and persistent, allowing students to access education flexibly, calmly and seamlessly. U-learning has the potential to revolutionise education and remove many of the physical constraints of traditional learning. Furthermore, the integration of adaptive learning with ubiquitous computing and u-learning may offer great innovation in the delivery of education, allowing for personalisation and customisation to student needs.

Introduction

Ubiquitous computing

The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it. (Mark Weiser, 1991)

Weiser's third wave in computing describes a many to one relationship between computer and human (Weiser, 1993). This relationship is common in the evolving ubiquitous computing era. This also correlates to the u-learning concept currently emerging. Each student interacts with many embedded devices. In the ubiquitous classroom, students move around Ubiquitous Space (u-space) and interact with the various devices.

Adaptive learning

Adaptive learning can offer great advantages in providing students with specific and personalised knowledge as and when required. It has been haled as a 'promising alternative approach' and is believed to improve student learning outcomes by catering to the diverse learning needs of individual students. Adaptive strategies were implemented in education as early as the start of the 20th Century as educators began looking at alternative means to improve the outcomes of student learning and understanding (Talley & Martinez, 1998). The development and use of adaptive learning environments allow for the integration of the concepts and theories of education and information technology. Jones, et.al. (1992) believe that the development of such systems can, in due course, "provide or support effective learning experiences for a wide range of learners across a broad spectrum of knowledge domains".

The development of a ubiquitous learning environment combines the advantages of an adaptive learning environment with the benefits of ubiquitous computing and the flexibility of mobile devices. Students have the freedom to learn within a learning environment which offers adaptability to their individual needs and learning styles, as well as the flexibility of pervasive and unobtrusive computer systems.

CBE, e-Learning and m-learning

M-learning is often thought of as a form of e-learning, but Georgiev et. al (2004) believe it would be more correctly defined as a part, or sub-level, of e-learning. They believe m-learning is a new stage in the progress of e-learning and that it resides within its boundaries. M-learning is not only wireless or Internet based e-learning but should include the anytime/any place concept without permanent connection to physical networks. The advantages of m-learning compared to e-learning include: flexibility, cost, size, ease of use and timely application. The devices used include PDAs, mobile phones, portable computers and Tablet PCs.

The ubiquitous learning environment

Ubiquitous = pervasive, omnipresent, ever present, everywhere
Learning = educational, instructive, didactic, pedagogical
Environment = surroundings, setting, situation, atmosphere

In this paper we report on the adaptation of u-learning in an educational setting. The ULE resides within the physical environment. Microprocessors are embedded in objects, or devices. The use of wireless and mobile technology makes them easily accessible and contributes to educational functionality. The wireless and mobile devices include mobile phones and PDAs. A ULE can provide the props and stimuli needed to easily encourage student involvement but without needing the active attention of the student. The benefits of the many to one relationship found in u-learning include the potential for one ULE (of many devices) to service an unlimited number of individuals at once. Essentially, the many to one relationship exists for every one of the students within the environment.

Figure 1 shows an example of four students within a ULE in which there are five ubiquitous objects/devices. Each student is part of the many to one relationship within this u-space. It is immaterial which particular device the student is currently interacting with, as all devices are networked and communicating within the Ubiquitous Space (u-space) - see the purple dotted lines linking the objects in Figure 1. So if Student1 is interacting with Object1, all devices that are part of the network are aware of this interaction. However, for each student the relationship is unique and their interaction is uninterrupted by the interaction of others. This also allows each student to progress through the learning experience at their own pace.

Figure 1: Students within u-space

In designing the ULE, the application of learning theories is an important consideration. Jacobs (1999) states that using learning theories in educational design helps to create a relationship between the information, the learner, and the environment. Gersten and Baker (1998) explain that when this relationship does occur there is a greater chance that the student will retain the information within their own knowledge base. For example, if a student can understand why and how something happens in nature, such as why and how a seed will sprout in soil and not in rocks, rather than just being told that it is true; the information has more relevance and therefore more meaning. Put simply, once an individual understands a concept they are more likely to remember it. A lack of understanding results in the opposite, as Jacobs (1999) explains:

... if learners learn facts of information that are isolated from a meaningful context, their understanding is often incomplete and meaningless.

The ULE model

The ULE model is not unlike the interactive guides currently being produced and implemented in large museums. Electronic museum guides provide an information service to aid museum culture and tend to mimic or replace human guides; however, this model is designed for use in the education sector rather than entertainment or enrichment. Also, the source information is meant to be both adaptable and flexible, allowing updates and amendments to be applied through the network's database. In this way curriculum changes can be easily achieved.

Components of the ULE include:

1. Microprocessors with memory will be embedded in every object/device. The information each microprocessor will hold will be about the object. When a student approaches, the sensor detects their presence and will start relaying information to the student's PDA.

2. ULE Server Module will include the Server, the Educational Strategies Unit and a Database: The ULE server manages the network resources:
   The Educational Strategies Unit allows for the application of strategies to reinforce and aid student understanding through interaction and feedback. It analyses student responses to short quiz questions and returns more information or information in a different form when needed;
   DataBase - stores all the data about the 'objects/devices', the users and the interactions that occur.
   

3. Wireless technology - this will be in the form of Bluetooth and WiFi:
   Bluetooth has weak signal strength, uses little power and covers a relatively short distance. Its low power consumption and ability to communicate with many devices is extremely beneficial when using handheld devices.
   WiFi, based on the IEEE 802.11 specification, has a range and speed which surpasses that of Bluetooth. It is compatible with any brand of Access Point and client hardware built to the WiFi standard (Brevard User's Group, 2002)

4. Sensors will be used to detect any changes in surroundings. These will be placed adjacent to the objects/devices and will be used to recognise the presence of students. The sensors used will include proximity, to detect movement, and light, to detect changes in light intensity.

The ubiquitous learning centre

Seamless interaction between student and device

Figure 2: Student object interaction

A discreet quiz by way of a game or other entertaining method may be sent to the student's handheld device and then on to the student (b2 and b3). The student's responses are transmitted to the ULE Server Module (c1 and c2) and the results analysed by the Educational Strategies Unit. If the student requires some additional help in understanding the topic or some reinforcement, then this is sent back to the student via the PDA (c3 and c4). Information about all students is held in the ULE Server Module, whereas information about an object is held by the object as well as the ULE Server Module.

Communication between objects/devices

1. Object1 is approached by Student1
2. Information is sent to Student1
3. Object1 analyses the student's responses and hence understanding of the topic (with help from the ULE Server Module)
4. This information is relayed to all other objects in the u-space e.g. 'Student1 understands 6/10 points on this topic'
   

   Figure 3: Communication between objects/devices

The type of content suitable to be taught within the ULE includes knowledge based disciplines such as History, Geography and the Sciences, which require knowledge transfer, reflection and active (physical or mental) participation. This may also be referred to as museum, or gallery, style learning which caters for the primary learning styles of visual, aural, and kinesthetic/tactile learning. Students are encouraged to create their own knowledge from their surroundings as they move around in u-space and interact with various objects and devices. Constructivist theory is used to allow students to build knowledge from what they see, hear, read and perceive.

Conclusion

The concept of ubiquitous computing and u-learning goes beyond portable computers. As new technologies evolve and more pervasive forms of technology emerge, computers will become 'invisible' and will be embedded in all aspects of our life. They will be seamlessly integrated into our world in a phenomenon referred to as calm technology. Wearable computers and embedded microchips are not as unbelievable or mind boggling as they were when first depicted in early science fiction novels and movies. Many technologies have become integrated into our lives over the years, for example: the telephone; television; PCs; the Internet and mobile phones. These innovations may have appeared strange and futuristic at first but, over time they blended into our everyday lives. In this age of progress and great change, we tend to easily adapt to the technologies and pedagogies that emerge. Ubiquitous technology and u-learning may be the new hope for the future of education.

References

Gersten, R. and Baker, S. (1998). Real world use of scientific concepts: Integrating situated cognition with explicit instruction. Exceptional Children, 65(1), 23-36.

Jacobs, M. (1999). Situated cognition: Learning and knowledge relates to situated cognition. [verified 31 Oct 2004] http://www.gsu.edu/~mstswh/courses/it7000/papers/situated.htm

Jones, M., Greer, J., Mandinach, E., du Boulay, B. and Goodyear, P. (1992). Synthesizing instructional and computational science. In M. Jones & P. Winne (Eds), Adaptive learning environments: Foundations and frontiers (pp.383-401). Berlin: Springer-Verlag.

Paramythis, A. and Loidl-Reisinger, S. (2004). Adaptive learning environments and e-learning standards. Electronic Journal of eLearning, 2(1), March. [verified 31 Oct 2004] http://www.ejel.org/volume-2/vol2-issue1/issue1-art11.htm

Talley, S. and Martinez, D. H. (1998). Tools for schools: School reform models supported by the National Institute on the Education of At-Risk Students. Washington, DC: US Department of Education, Office of Educational Research and Improvement. [verified 31 Oct 2004] http://www.ed.gov/pubs/ToolsforSchools/title.html

Weiser, M. (1991). The computer for the twenty-first century. Scientific American, September, 94-104.

Weiser, M. (1993). Some computer science issues in ubiquitous computing. Communications of the ACM, 36(7), 74-83. In Special Issue, Computer-Augmented Environments [verified 1 Oct 2004] http://www.ubiq.com/hypertext/weiser/UbiCACM.html

Authors: Vicki Jones and Jun H. Jo, School of Information Technology, Faculty of Engineering and Information Technology, Griffith University Gold Coast, QLD 9726, Australia. v.jones@griffith.edu.au, j.jo@griffith.edu.au Please cite as: Jones, V. & Jo, J.H. (2004). Ubiquitous learning environment: An adaptive teaching system using ubiquitous technology. In R. Atkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips (Eds), Beyond the comfort zone: Proceedings of the 21st ASCILITE Conference (pp. 468-474). Perth, 5-8 December. http://www.ascilite.org.au/conferences/perth04/procs/jones.html

© 2004 Vicki Jones and Jun H. Jo
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