Iddhipada Agent for versatile e-Learning

D.H.W. Kannangara, S. Ahangama, S. N. Perera, M. Pushpakumara, A.S. Karunananda, D. K. Withanage Faculty of Information Technology

University of Moratuwa Colombo, Sri Lanka

Dasuni7@gmail.com

Abstract— Despite the growing demand for e-Learning, the importance of role of a good teacher in a learning session is undisputable. We have exploited Theravada Buddhist concept of Iddhipada, which identifies four mental factors, namely, desire-to-do, mindfulness, effort and investigation as key factors to successful learning, to emulate the role of a good teacher in e-Learning environments. In our approach, Iddhipada concept has been implemented as a software Agent that drives the entire e-Learning session of a learner. The Agent automates learning session of an individual as per the development of Iddhipada. More importantly, learning sessions driven by Iddhipada Agent inculcates good learning habits and capacity to learn with learners, as it happens when a good teacher takes part in a classroom scenario.

Keywords— iddhipada agent, e-learning, multipoint, genetic algorithms

I. INTRODUCTION The world around us is rapidly changing. As such, traditional learning strategies cannot meet the demand for education in the modern world. In this context, e-Learning has emerged as a potential solution for breaking the barriers in traditional learning strategies. The vast movement towards e-Learning is clearly motivated by the many benefits it offers. Some of the benefits gained through the e-Learning can be identified as flexibility, cost effectiveness, up to date content and timely access to knowledge. However, much e-Learning is praised and innovated; computers will never completely eliminate human teachers from learning environments. This is because; in a classroom scenario, teachers always give more than subject knowledge, and inculcate good learning habits and capacity to learn with learners. All learning theories assert that human interaction is vital to learning. Over the e-Learning, there exist advantages and also disadvantages. In order to overcome its potential drawbacks, e-Learning systems exploit the power of modern ICT for devising interactive learning environments.

However, most of the e-Learning systems still provide reservoirs of knowledge without emulating the role of a good teacher who has already proven the success of face-to-face learning. In this sense, we have been researching into mechanism to emulate the role of a good teacher into e-Learning environments and recognized the possibility of exploiting Buddhist Philosophy to introduce a model for implementing teachers’ role in e-Learning environments.

Buddhist Philosophy presents the concept of Iddhipada which defines four mental factors, namely, desire-to-do (chanda), mindfulness (chitta), effort (viriya) and investigation (vimansa) [1] as the key to successful learning. Undoubtedly, good teachers ensure balanced-development of these four factors of learners during a teaching session. This paper presents our approach to develop a software Agent that implements the Iddhipada concept to emulate the role of a good teacher into e-Learning systems.

II. IDDHIPADA LEARNING CONCEPT Development of understanding ability is an unchallengeable

result of a learning process. In the context of understanding the real world as it is, among others, Buddhist Philosophy presents various concepts that can be used to develop models for successful learning. This research has exploited the concept of Iddhipada in Buddhism to postulate the model for e-Learning that can emulate the role of a good teacher. The concept of Iddhipada, defines four computable mental factors, namely, desire-to-do, mindfulness, effort and investigation [7] as the key to a successful learning session. Therefore, it is very important to gain knowledge on how to cultivate these four virtues in minds and how to use them in a learning process.

It should be noted that purpose of Iddhipada is much

broader than supporting a learner to learn a specific subject, but allows to inculcate capacity to learn any subject. For example, investigation ability developed by learning Mathematics, adds to our life long analytical skills. A brief description of the four mental factors of Iddhipada is given below.

A. Desire-To-Do Desire is the primary requirement to accomplish any goal

in our lives. As such, a successful learner should know how to maintain a continuous desire regarding the subject matter and the learning process. The learner should be ready to learn to work with his/her best ability with interest and determination. Therefore, for a learning process to be successful, a learner should be provided with the materials that are capable of developing the learner’s desire. In a face-to-face learning

978-1-4244-1900-5/07/$25.00 © 2007 IEEE ICIAFS07129

scenario, a good teacher monitors the development of learners’ desire in the learning session and move forward accordingly.

B. Mindfullness The term mindfulness stands for a learner being conscious

during a learning session. Regardless of other mental factors, mindfulness is of great importance for a learning session. In fact, it is evident that the purpose of other mental factors such as desire and effort fade away when the learner has no ability to be conscious. A good teacher knows the art of binding minds of learners into a lesson and even to help them to inculcate concentration power so as to use it for learning of other subjects too.

C. Effort It is undisputed that continuous effort is the force behind

any success. Effort stands for the ceaseless application of energy to finish work to achieve a goal. In a learning session, the student should work with balanced effort to complete the work. Thus, blind effort can be as destructive as no effort and too much effort can tend to develop restlessness in the mind. All good teachers are so clever to develop learners with the capacity to put efforts, without spoon feeding learners. For example, additional tasks such as take home assignments and supplementary reading are means of improving effort.

D. Investigation Investigation ability is yet another mental factor which is of

great importance to ensure a successful learning session. It is common to notice that some people are educated without having any analytical skills. Good teachers move away from the spoon feeding and ensure the development of learners’ analytical skills during a learning session. While in the classroom, a good teacher can ask simple questions to assess the development of investigation skills of learners.

It should also be noted that these mental factors are intertwined and cannot be developed independent of the others. For example, development of investigation skill also needs support from the effort as a mental factor. More importantly, as it is stated earlier too, developed qualities of desire, mindfulness, effort and investigation skills in a certain learning session can be carried forward to use in learning of other subjects in subsequent sessions. Thus development of Iddhipada inculcates good learning habits and capacity to learn in a student.

III. OVERVIEW: AGENT TECHNOLOGY

It is necessary to examine how the Iddhipada concept can be developed as a software solution. Obviously, there are number of software technologies, which could be used to implement the Iddhipada concepts into e-Learning systems. Due to various reasons, we argue that the Agent is the best software technology to implement Iddhipada concept for e-Learning systems. In the modern context, Agent technology is a rapidly developing area of research that comes under Artificial Intelligence [8]. As a software paradigm, Agent

technology has special features including autonomy, reactivity, proclivity, adaptability and evolvability.

In view of the above, using the Agent technology primarily can automate the Iddhipada concepts within an e-Learning environment. Since the Iddhipada concept is expected to implement the role of a good teacher, it is undisputed that our software solution must be autonomous to a large extent. Furthermore, just like a good teacher, such a software solution should be able to operate in both reactive and proactive manner by allowing the evolution of performance of the software to generate better solutions in subsequent sessions. Agent’s ability to be customized to cater for several learners simultaneously is also another attractive feature of Agent technology to implement the concept of Iddhipada.

IV. AGENTS FOR E-LEARNING

Agent technology is used for the implementation of variety of applications. Before discussing the design and development of e-Learning system based on the concept of Iddhipada, the related work using Agent technology is discussed below.

Application of software agents can be widely seen in many e-Learning systems. In systems as Angel Learning [6], software agents are used to guide the learners to study effectively and to improve their performance. The standard Learning Content Management Systems (LCMS) such as ATutor, WebCT and Moodle [9] can also be considered as software agents. These systems generally allow the e-Learning content developers to upload the e-Learning material and manage the e-Learning environment for each e-learner. However, none of those systems has exploited Iddhipada like concept to develop role of a good teacher into e-Learning. Therefore, the implementation of Agent technology with the use of Iddhipada concept will lead to a new pedagogy for e-Learning.

Sharable Content Object Reference Model (SCORM) [5] is a new trend of e-Learning which is used for sharing information among different Learning Management Systems (LMSs). Nevertheless, current approaches have no emphasis on individuality or constructivism of learning concepts from an education point of view. From the educational viewpoint, e-Learning systems can be identified as cognitive tools [2] [3] [4] provided that the system has been developed with a proper pedagogical basis. Agent technology with the concept of Iddhipada can be named as a potential candidate technology for developing cognitive tools.

It should also be noted that several researches have already been conducted to exploit Iddhipada concept into e-Learning systems. For example, Karunananda [10] has developed an Iddhipada Agent to humanize e-Learning systems. Another research work, without using the Agent concept, has attempted to develop a computer system which evaluates Iddhipada of a learner on request [11]. Although these research work talks of the same theme of Iddhipada for e-Learning, they have taken

130

different approaches to quantification of Iddhipada. For example, Karunananda [10] quantifies Iddhipada through an approach where each lesson in e-Learning systems has annotated with Iddhipada. Having completed a lesson, development of Iddhipada has been measured through a set of questions pertaining to the lesson. In contrast, Devendra and Karunananda [11] have quantified Iddhipada by asking set of questions regardless of the subject area. This is similar to the approach taken for IQ testing. Former is more specific and rather difficult to implement yet can be applied during a learning session to guide a learner accordingly. In contrast, latter is more generic and simple to implement yet cannot be used while a learning session is on.

The research work presented in this paper can be considered as an extension to work presented above. This paper reports on a novel way to quantify Iddhipada of a learner and presents a more versatile approach to drive a learning session as per the evolving Iddhipada.

V. IDDHIPADA AGENT FOR E-LEARNING

Our approach to use Iddhipada for e-Learning has been presented as a development of Software Agent that implements role of good teacher. For explanation sake, the approach is presented under three headings, namely, general features, group learning and solution to limited resources.

A. General Features The Agent maintains learner profiles and guides learners as

per the development of Iddhipada with the aid of e-Learning materials, discussion forums, multimedia support and mobile applications. The Iddhipada Agent has the ability to monitor learners’ performance and compute the evolution of Iddhipada. Performances are measured through a set of questions asked at the end of each session. These questions are prepared as per four factors of Iddhipada. This process is similar to a good teacher asking questions at the end of a lesson to see whether learners have developed the interest in the subject, have concentrated properly, have developed encouragement to do more studies, etc. Note that this approach of computation of Iddhipada is different from what was presented in the above. More importantly, in contrast to Karunananda’s [10] approach, here, there is no need to classify the lesson materials as per lessons; still questions are in relation to the lesson. Therefore, using this approach, incorporation Iddhipada concept into e-Learning systems can be done at the quizzes level, without doing modification or annotations to main lesson material. In addition, when incorporating consent from good teachers, improvement to quizzes pertaining to Iddhipada can be done very easily.

B. Group Learning Emulation of group learning through Iddhipada is yet

another key feature of our approach. When a learning session is on, the Agent can also bring the group learning effect, for example sharing of desire and investigation skills, to improve

the quality of learning. Group learning helps to build learning communities and also to construct the knowledge through a collaborative effort. Activation of group learning has been implemented with the Agent as simple application of Genetic Algorithm. During group learning session, Iddhipada Agent provides facilities such as video conferencing, discussion form, file sharing, chat, etc. Note that all these audience are provided as per Iddhipada. For instance, in a group learning session, all learners have a common Iddhipada vector. In the vector if desire is low, chat sessions will be recommended by the Agent. Further, if investigation is low, an analytical problem from the e-Learning system will be provided to solve as a team.

C. Solution to limited resources Proposed approach also introduces a means for addressing

the issue of lack of computer resources for e-Learning, especially in rural areas. In fact, rural learners have severely been affected by not having good teachers than learners in developed urban areas. In addressing the issue of resources, the Agent has been equipped with the ability to provide multiple accesses to a single PC by using multiple mice. In this case, the Agent can run learning sessions independently for two or more learners on the same machine.

Overall approach can be identified as new pedagogy for e-Learning that falls under the education theory of socio-constructivism in the context of Concept Economy in the tomorrow's world.

VI. DESIGNS OF IDDHIPADA AGENT

In the design and development of the Iddhipada Agent, capabilities of Iddhipada Agent must be recognized and each component ought to be implemented based on its defined capabilities. The Iddhipada Agent, the most important constituent of the Iddhipada Agent software system performs as the intermediary between e-Learning learners and e-Learning material while providing services with the utilization of e-Learning material, websites, databases and Genetic Algorithm (GA) engine. Iddhipada Agent is designed to locate on a server through which learners can access other e-Learning sites.

A. Computing of Iddhipada The Iddhipada Agent drives the entire session as per the

development of Iddhipada. For this purpose, regarding each learner, the Iddhipada Agent maintains a vector of length four (4) to represent the value of desire, mindfulness, effort and investigation. When a learner logs into the system for the first time these values are set to non-zero equal numbers without loss of generality. End of each lesson questions related to lesson are asked with reference to Iddhipada. If answered correctly, the value of particular factor of Iddhipada will be updated as 1, otherwise 0. Final resultant modification to the Iddhipada vector of a learner is computed as follows.

R(s) new = R(s) old + update(s)/T (1)

131

Internet

General Advice & Guidance Module

Group Learning Module

Multi-user interaction

Module

Interaction Module

Alerts & Messages Module

External resources Module

Iddhipada Agent

Where s ∈{desire, mindfulness, effort, investigation} R(s) new = New value of Iddhipada factor s R(s) old = Previous value of Iddhipada factor s Update = update value of s after a session T = mean square value of Iddhipada vector

Note that computation of resultant value of a particular Iddhipada factor has been done as a function (T) of all other Iddhipada factors. According to Buddhism this is essential, because one factor of Iddhipada vector cannot be increased or decreased independent of other factors. This is quite evident from our real world experience too. See also Karunananda [10] for a discussion on the derivation of above formula.

B. Design and Implementation of Agent The Iddhipada Agent has been implemented to run on a Web server. It works as a middleware for e-Learning systems on the Internet. Figure 1 shows the top level design of the Iddhipada Agent.

Figure 1: Design of Iddhipada Agent

C. General Advice & Guidance Module This module maintains learners’ profiles, and gives general advice and guidance to use basic services provided by the Agent. This is the main module of the Iddhipada Agent. Similar to a good teacher, this module of the Iddhipada Agent provides with reading materials, quizzes, assignments, home works, etc. to learners. During a learning session of a learner, the Iddhipada Agent evaluates the learner’s performance by asking quizzes that are based the learnt materials with a reference to Iddhipada. The Agent award 1 mark or 0 mark

depending on the correctness of the answer. Having awarded marks the Agent uses the formula stated in the previous section to update the Iddhipada vector of an individual. Then the learner is guided accordingly. The Agent automatically monitors the progress and reports when necessary. Figure 2 shows a typical progress chart generated by the Iddhipada Agent for a student.

Figure 2: Graphical Representation growth of Iddhipada

The recommendations will be provided to each student by analyzing the Iddhipada vectors. For example, a learner represented by Figure 2 will be given more activities to improve his desire, as it is the least developed Iddhipada factor of that learner.

D. Group Learning Module Iddhipada Agent has a special module to introduce and maintain group learning among selected learners. The Agent activates group learning by analysing development of Iddhipada of learners. For example, if Agent notices that some have developed the Iddhipada very well, while others are weak, the Agent activates group learning to enable learners to share their experiences. In this case, all learners being with a common Iddhipada vector that is computed by a Genetic Algorithms (GA) engine in the module. Here the Agent uses Tournament Selection method to apply GA for computing a common Iddhipada vector for all participants. The use of a common Iddhipada vector gives the effect of sharing experiences of a learner with others. For example, interacting with the learner of high desire helps the others also to develop

010203040506070

1 2 3 4

Lesson

Suc

cess

fato

r(10

0%) Desire

MindfulnessEffort

Investigation

DesireMindfulnessEffortInvestigation

132

desire. During a group work session individual learner’s Iddhipada vector will be recomputed and guided accordingly.

E. Multi-user Interaction Module Initiating and maintaining of multi-user interaction is handled by a special module in the Agent. The multi-user interaction is a facility offered by the Agent to handle the situations where limited resources are available for access e-Learning sessions. Owing to the high cost of a computer, some learners may evade from using this system. This application used with Microsoft Multipoint Technology will provide a solution for such, as this enables two users to log into a single machine with one additional mouse connected. Two user profiles will run simultaneously on the same machine, providing the same learning material with different assessments on the computer screen by the Agent.

In this case, two unique cursors will be displayed on the screen with each having a unique ID to identify the user movements. Hence, learners will be able use the system as a single user since each cursor could be used simultaneously.

F. Interaction Module A specific module has been built into the Agent to handle interactions pertaining to the use of Discussion forums, Chat sessions, Video Conferencing, etc. Activation of these sessions is decided by the Agent on the basis of Iddhipada vectors of individual learners. For example, if some learners appear to have lower analytical skills, then the Agent activates discussion forums by drawing discussion topics associated to the lesson. They are stored with learning materials in the General Advice and Guidance modules. In contrast, Chat sessions will be activated if some learners show a reduced desire during a learning session.

The Chat sessions are supported with audio and video facilities as appropriate. During Chat and Discussion forum the Agent monitors the active participation by using parameters such as response time, density of answers, etc. The Agent encourages the less active learners to become active.

The interaction module of the Agent also initiates video conference sessions with human teachers, if a learner is exceptionally weak during several sessions.

G. Alerts and Messages Module The Agent can also send Alerts and Messages by communicating with users using various means such as SMS, MMS and email. This is done by a separate module. For example, before a lesson the student will receive warm up messages and after a lesson the student will receive recommendations as SMS written in native language (e.g. Sinhala, Tamil). Learners can request media files with voiceovers of positive thinking speech and meditation via MMS. The progress reports of each student will be e-mailed to the teacher and the parents. The notification messages too will

be sent by e-mail to the psychologist, by the teacher as and when required.

A. External resources module There is a separate module for linking learners with various learning resources available on the web. For example, the Agent links the user with extra learning materials. In addition, if a learner is weak in some areas such as mindfulness, the Agent directs the learner to a web site such as mindtools.com. Similar extra helps can be supplied by the Agent. Ideally, when the Agent allows the learners to learn from various e-Learning servers through the Iddhipada Agent, this module has a bigger role to play.

VII. DISCUSSION AND FURTHER WORK

This paper emphasizes on the fact that e-Learning is vital for expanding educational opportunities in the modern world. We pointed out that the mere use of modern ICT cannot still compensate the role of a good teacher in a successful learning environment. As such, e-Learning environments with huge reservoirs of learning resources cannot provide with an effective solution for e-Learning. Therefore, our research work postulates to device an approach to bring the role of a good teacher into e-Learning environments. In this sense, we exploited Buddhist Philosophical concept of Iddhipada to develop an approach to emulate the role of a good teacher into e-Learning environments. Our research has implemented the Iddhipada concept as a software Agent that integrates various services of e-Learning environment. The Agent has been designed to monitor learners’ Iddhipada development in terms of desire, mindfulness, effort and investigation skills, during a learning session.

The primary role of the Iddhipada Agent is to advice and guide learners during a learning session as per Iddhipada development. There are several facilities central at the primary role of the Agent. In this sense, Iddhipada Agent emulates the group learning behavior to ensure knowledge sharing and community building. The Agent has also developed with the ability to provide multi user interaction as means of addressing the issue of lack of computer resource for e-Learning in rural areas. Chat sessions, Discussion forum and Video conferencing are supported as yet another dimension for versatility of the Agent. Alert and messages is an offline facility provided by the Agent for the learners to interact with the Agent to get selected information. The Agent also provides with the facility to access external resources pertaining to a learning session and other resources that can enhance the capacity to learn by the learners as per the development of Iddhipada. This is a gateway to expansions.

At present the Iddhipada Agent has been hosted in an e-Learning server. Ideally we expect to introduce Iddhipada Agent as a server through which other e-Learning servers can be accessed and learners can start sessions. In such a scenario, the Iddhipada Agent creates an instance of a learner and monitors the development of Iddhipada during the learning

133

session. This is quite possible since this current approach does not require any changes to e-Learning resources at a particular site. Our Iddhipada Agent has also been presented at Microsoft Imagine Cup 2007 competition held in Sri Lanka and won a place. At present we are continuing with the further development of the Iddhipada Agent to make it widely available for the e-Learning communities.

We argue that the Iddhipada Agent has taken a step to address the issue of lack of role of a good teacher in a learning environment. Since the Agent is driven by the development of learners’ desire, mindfulness, effort and investigation skills, the Agent not only contributes to improve the knowledge in a particular subject, but also to develop capacity to learn through the development of mental factors that ensures a quality learning process. This process amounts to inculcate the good learning habits with the learners as it happens in a classroom scenario with the involvement from the user.

ACKNOWLEDGMENT

We wish to acknowledge the comments given by Ms. Subha Fernando, Lecturer, Faculty of Information Technology, University of Moratuwa, Sri Lanka, during the process of implementation of the Iddhipada Agent.

REFERENCES

[1] A. S. Karunananda, “Learner’s Perspective driven ontology for e-Learning”, Proceedings of the Eight International Conference on Humans and Computers,Japan, pp. 143-149, 2005.

[2] J.T. Mayes, Cognitive tools for learning, ch. Cognitive Tools, A suitable Case for learning, Springer, 1992, pp 7-18.

[3] R. B. Kozma, The implications of cognitive psychology for computer based learning tools, Educational Technology 27, 1987, pp 20-25.

[4] Gunter Schmitt, “Cognitive tools in teaching and learning”, Proceedings of Eight International Conference on Humans and Computers, HC-2005, Japan, pp 187-196, 2005.

[5] The Sharable Content Object Reference Model (SCORM), Acquisition Guidelines for US Military, 2004.

[6] http://www.angellearning.com. [7] http://www.mbmc.iirt.net/books/bys017.htm, 1997 [8] Russell S. & Norvig P., Artificial Intelligence: A

Modern Approach, Prentice Hall, 2003. [9] Jason Cole, Using Moodle, O’Reilly community press,

2005. [10]Karunananda A. S., “An approach to humanizing e-

Learning systems”, Proceedings of the International Conference on Industrial and Information Systems,IEEE Sri Lanka Section, Aug 2007.

[11]Devendra L. and Karunananda A. S., “On computing Learning Ontology with Mental Attributes”, Proceedings of the International Conference on

Industrial and Information Systems, IEEE Sri Lanka Section, Aug 2006.

134