Learner-Space Knowledge Awareness Map in Computer Supported Ubiquitous Learning

Moushir M. El-Bishouty, Hiroaki Ogata and Yoneo Yano The University of Tokushima, Japan

Introduction

While a learner is doing a new task to practice, s/he usually needs some help and instructions.

How to get the appropriate knowledge immediately? Refer to educational materials which are

around the learner. Ask another person (friends, experts,

teachers, …).

Introduction “continue”

It is so difficult to know who has this knowledge even that he is at the same local area.

The learner needs to be awareaware of the other learner’s interests that match his request.

Introduction “continue”

Knowledge Awareness (KA) is defined as awareness of the use of knowledge

Knowledge awareness map graphically displays KA information:what kind of educational materials are available?Who can help to solve this problem?

The map enhances curiosity and induce collaborative learning.

Objectives

Design and implement of computer supported collaborative learning in ubiquitous computing environments.

Detect the environmental objects that surround the learner .

Recommend the best peer helpers. Support the learner with the knowledge

awareness map (KAM) which is personalized according to his current need.

PerkamII(PERsonalized Knowledge Awareness Map).

•In Perkam*, the knowledge awareness map is personalized according to the learner’s interest and location.

•In PerkamII, the system uses RFID tag to detect the environmental objects that surround the learner those he uses in his practice study, and to map from the physical space to the digital space.

*Moushir M. El-Bishouty, Hiroaki Ogata, Yoneo Yano, “Personalized Knowledge Awareness Map in Computer Supported Ubiquitous Learning”, Proc. of ICALT06, pp. 817-821, The Netherlands, 2006. (Best Paper Award)

RFID tag RFID reader / writer

PerkamII “continue”

•Each object in the physical space is detected, recognized and presented graphically by this system.

•Recommend the best learners where their interests matched the current learner’s task.

•The learner can forward his digital space to the peer helper in order to facilitate easy understanding of his environment that augments the collaboration between them.

PerkamII “continue”

Assume that the knowledge space contains a number of unique keywords.

keywords define Environmental objects Learner’s request Learner’s interest.

keyword item is very important to recommend the peer learners.

PerkamII Model

1-LearnerEach learner’s interests is characterized according to Learner Profile:

-Learner explicit registration.-Learner academic level.-Learner actions during using the

system.

PerkamII Model “continue”

2- Environmental Objects:-The available environmental objects that

may surround the learner. -It may be computers, electronic parts,

chemicals…etc. -A RFID tag is attached on each object to

identify it.-Each object has its own keywords that

specify its specification. -One object may share one or more

keywords with one or more other objects.

PerkamII Model “continue”

3-Environmental Objects Map: -While the learner is interacting with another learner remotely, asking him for help and trying to explain to him his current environment and situation. -It may be difficult or at least need long time to describe exactly the available objects that he uses during his practice.-The role of environmental objects map is to map the physical space to a digital space, where each object in the physical space is detected, recognized and presented graphically by this system.

PerkamII Model “continue”

-The learner can forward this digital space to the peer helper.

-For example, learner1 is doing an experiment in a chemistry lab, each object surrounds learer1 is recognized, mapped into the digital space and forwarded to the peer helper.

-According to the knowledge from the environmental objects map the peer helper can recognize the learner situation and can efficiently collaborate with him.

Learner 1

Learner getting help

PerkamII Model “continue”

4- Peer Learners Map-This map displays the knowledge space of the recommended learners who are using the system and have enough knowledge about the learner’s need -It represents the Level Of Interest of a peer helper,

LOI = where

nL=# of matched learner’s interest keywords n = # of keywords of learner’s query

n

nn L 10 LOI

System Usage

•Consider a learner (Matsuka) is doing a task “PC assembling”.

•He does not have the enough experience to complete the task

•He uses PerkamIIPerkamII to detect the PC components and to build their KA map. PC Assembling Task

System Usage “continue”

•Each component is presented in a small icon (Modem, VGA, Mother board, RAM and HDD)

•He asks the system to recommend the suitable peer helpers whom he can interact and collaborate in order to finish his task successfully.

Environmental Objects Map

System Usage “continue”

•The system recommends two peer helpers.

•First recommended peer helper is Sasada and the other is Yin, it is easy for Matsuaka to discover that Sasada is more familiar and expert than Yin regarding the detected components.

•When Matsuka moves the pointer over the Sasada’s icon for example, he can get his full information (name, phone number, email…).

Peer Helpers Map

System Usage “continue”

•Matsuka can send him a message using PerkamIIPerkamII system, use chat tools, or call him by phone.

•Matsuka forwards to Sasada his digital KA map, takes photos for some components and sends them to him.

•It is easy for Sasada to recognize Matsuka problem, collaborate with him to reach to his final goal.

System evaluation •An experiment is done to evaluate the system performance and the learner satisfaction.

•The main idea is to ask a number of students who are learning PC hardware assembling and maintenance to do a ask and measure how much the system can help them to do the task in a certain time.

• 12 students are involved, the are divided into two groups

-Experts group, who are experts and have a strong knowledge about this problem

-Learners group who are beginners.

System evaluation “continue” •In the first phase, 5 students from the learners group were asked to do the task without using the system, and using only a web page access.

•3 students completed and 2 did not.

•In the second phase, 9 (7 + 2) students from the learners group were asked to do the task with the aid of PerkamIIPerkamII system and the support from 5 students who were using the system.

• A questionnaire is filled by all students at the end

Scanning objects

Finding peer helpers

Here he can get a peer helper!!

System evaluation “Result”

•In the first phase, “2” students from “5” hardly completed the task just in time.

•In the second phase, all students “9” successfully completed the task.

•The students agree that

-The system performance is fast.

-It is easy to use the system.

-The system is so useful as a learning assistance tool.

Future Work Design the second experiment to

measure how much the learners have learnt while using the system.

Integrate this environment with a location model where the system can recommend the peer helpers not only depending on their interests but also how close are their physical locations to the learner.

Sharing learning experiences with videos.mLearn2006.

Another scenario: Cooking Japanese foods

Situation A

My situation

Situation B

I want to cook Japanese needle, called Udon.It’s difficult to describe the situation exactly.

The system tells youmissing tools or ingredients I can help.

Conclusion

Knowledge awareness map supports learning immediately when a problem occurs.

It’s a kind of a personal learning assistant (PLA, not PDA) in ubiquitous computing environments.

Thank you…