The New Paradigm for Networked Learning: Inhabited Virtual Learning Worlds and Intelligent Agents
Chi-Syan Lin
Associate Professor
Graduate Institute of Computers and Information Education
National Tainan Teachers College
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The applications of Internet on education are widely promoted nowadays. The effectiveness and values of networked learning environments, however, are remained to be seen so far due to the lack of sufficiency on providing learning services. For overcoming the insufficiency of networked learning environments, the study proposes a framework for constructing an inhabited virtual learning worlds and intelligent agents on them. In addition, five other intelligent agents those who are learning companions, genies, moderators, digital librarians, and evaluators are also considered for the proposed networked learning environments.
Key Words：Networked Learning Environments Intelligent Agents Networked Learning Activities Inhabited Virtual Learning Worlds Learning Community
1 Introduction
After hyping for several years in the field of education, especially in the level of K-12 education, networked learning has come to a point to reshuffle itself for reality. To date, there exists no clear evidence that Internet in general, or Web in particular, brings “added value” to learning. It seems that a sufficient networked learning environment has not revealed yet.
In addition to the lack of qualified digital content, we have also observed that the existing networked learning environments or platforms are Web-based and they are more like an information warehouse than a learning space. Above all, Web-based networked learning environments for now are either in publishing or communication paradigms. These paradigms of networked learning usually create too much individual learning and isolation among learners. They are too passive and unable to provide enough student motivation. They are also hard to keep online students on task, to monitor their progress [11]. Learning community and learning supports that are needed for learning to take place in those networked learning environments are completely missing from them. Hence, the learning engagement is just not there. It is clear that networked learning needs a new pedagogy other than the existing Web-based publishing and communication oriented rationales.
The issue here is that we need to create a networked learning environment that is not only full of learning supports, but also allowing the presence of learners on it and is able to build up a learning community in the end. It seems that the solutions are the idea of inhabited virtual learning worlds and intelligent agents.
The fundamental rationale of inhabited virtual learning worlds is creating a shared learning space in 3D and virtual formats for avatars where they can pursue collaborative learning activities and form a solid learning community [8, 12]. Avatars, they are intelligent agents and the representations of learners in cyber space, can talk, move, gesture, point within the worlds and interact to each other or with objects of the worlds. The virtual worlds can be seamlessly integrated with Web pages extending the possibilities for interaction both social and intellectual.
According to the definition of Gilbert, an intelligent agent is “software that assists people and acts on their behalf” and it could make “computer systems easier to use by allowing people to delegate work back to the computer” [3]. Research on intelligent agents has mushroomed in the past few years. There are two conflated areas of the research on agents [4]. One is focusing on the use of AI techniques to create software that performs information filtering and other autonomous tasks such as computing or searching for users. Intelligent agents of this sort, referred as autonomous agents, may or may not display any explicitly anthropomorphic features. The second area is focusing on the agent acting as an interface metaphor that aids the user in interacting with the system or environment. These agents, referred as interface agents, may or may not incorporate new AI techniques. Their essential function is to act as effective bridges between a user’s goals and expectations and the system’s capabilities. The agent metaphor is used to make the interface more intuitive and to encourage interactions that might be difficult to evoke with a GUI. Usually, agents of this sort have their own unique anthropomorphic characters and figures.
It is claimed that creating learning communities and providing learning supports are the two most essential pedagogical issues for the success of networked learning. In the light of resolving these two issues, it seems that the combination of inhabited virtual learning worlds and intelligent agents are appealing as one of the best solutions.
2 The Significance of Virtual Learning Worlds
We have to abandon the existing practice of Web-based learning pedagogy and extend the concept of virtual reality. We need to create a virtual learning world that combines the strengths of 3D spatial learning (immersion), telepresence, immediate visual feedback, and interactivity.
The virtual learning world will transfer the networked learning environments to a 3D learning space and which will present the learners with avatars and provide the playground for all kinds of intelligent agents.
The 3D learning space could help to promote interpersonal interaction via spatial dimensions and create learning communities with its analog to the social bond in reality that would engage students in learning activities.
In essence, virtual learning worlds could provide a shared learning space for inhabiting avatars. In other word, avatars are part of virtual learning worlds and they could not exist without them.
3 The Significance of Avatars
Many researchers asserted that people learn best through the medium of human relationships [10]. This is the reason that current Web courses emphasize the implementation of student-to-student interaction or teacher feedback features. Those have suggested the importance of building up a learning community in networked learning environments. But some researchers insisted that the richest communication occurs when people are physically face-to-face, and the most sophisticated technology for connecting people with audio and video has not been able to substitute for face-to-face communication [10]. What do all those statements mean to networked learning? We need an alternative communication approach other than providing video channel in networked learning environments that is as effective as face-to-face.
Table 1 summarizes the abilities of communication scheme in face-to-face, video conferencing, and avatars. Avatars are the representations of learners in virtual learning worlds with the format of characters or icons. They are one of the intelligent agents and inhabiting inside the virtual learning worlds.
In face-to-face communication, the communicator has relative position, the ability to point and gesture, and to use facial expression to convey meaning. In the video teleconferencing model, the ability to use facial expression is still available, however there is no shared space, nor is the ability to gesture in that shared space. In an avatar model, the ability to use facial expression is no longer available but there is a shared space and the ability to use gestures.
Furthermore, given the assumption that the ability to share a space and to gesture with relation to that space is important, the amount and quality of information conveyed using an avatar should be similar to or greater than that of the face-to-face interaction. Hence, for the purposes of education or learning in communication channels, the ability to share space, to have a presence whether real or virtual is more beneficial than is the ability to see facial expressions [2].
Table 1 The Comparison of Communication Scheme
/ Facial Expression / Shared Space (Telepresence) / Gestures in the Shared Space / Physical FreedomFace-to-Face / P / P / P / O
Video Conferencing / P / O / O / ?
Avatars / ? / P / P / P
Legends P: full support ?: not full support O: unavailable
The use of avatars is closer to face-to-face in its ability to communicate, for the following reasons. First, avatars allow participants to interact with one another directly in a virtual environment, much as face-to-face interaction does. Second, avatars allow participants the ability to communicate nonverbally through position and gesture, which, again, makes it similar to face-to-face interaction. In video conferencing, interaction is possible only through the two dimensional screen, and nonverbal cues can only be observed from the image that is on the screen, the area of interaction is not shared. Thirdly, this sharing of space, or presence, is more important in education settings than is the ability to see and interpret facial expression.
In essence, avatars are for providing identities, telepresence to the learners in networked learning environments. Due to the lack of physical limitations such as size, distance, and time, their potential to convey meaning beyond human capacity for avatars seems possible. They are the necessary tools for the learners to perceive their learning circumstances and help them gain the sense of belongings and ownership of the networked learning environments.
4 The Significance of Intelligent Agents
Intelligent agents are proposed to provide incredible learning supports in customized and adaptive manners for learners. In essence, intelligent agents are created to provide all kinds of learning supports and make adaptive learning possible in the networked learning environments. In other words, the role of intelligent agents is to monitor learners’ learning behaviors, to record learning processes, to understand learners’ progress and to assist learners at any time. Thus, intelligent agents could drive the learning activities on the networked learning environment dramatically.
In order to achieve those goals above, networked learning environments probably require these five intelligent agents: (1) learning companions, (2) moderators, (3) genies, (4) digital librarians and (5) evaluators.
4.1 Learning Companions
As the name implies, learning companions are assistants or friends for every individual learner who would accompany he/she along the learning paths all the time. To increase learners’ learning motivation, the role for learning companions is to learn with them, give support to them, interact with them and reduce their learning difficulties. They would also suggest learning styles suitable for every individual learner. For instance, Best Cyber Academy has developed a learning companion ---- WuKong. (Figure 1) With WuKong’s assistance, the motivation and learning performance of learners in Best Cyber Academy have improved [7].
4.2 Moderators
Collaborative learning activities and interpersonal communication are essential to networked learning. It has been claimed that providing moderating strategies is a key to the success of collaborative learning projects or activities [9]. Moderators are created to direct the collaborative learning activities by tracking learning procedure and monitoring learning process. An experienced moderator would guide learners to interact with others effectively and increase the quality of team works.
Figure 1 Learning Companion WuKong in Best Cyber Academy
4.3 Genies
Genies act as the mentors to learners in networked learning environments. Genies can examine and search the database of learners’ student models, understand their learning situation and difficulties, answer learners’ inquiries and provide them appropriate assistant. They are the opposites of learning companions in terms of tenderness toward learners.
Figure 2 is a genie in Best Cyber Academy, San-Chang, who could provide scaffolding learning support to learners in a collaborative learning environment.
Figure 2 A genie serves at Best Cyber Academy
4.4 Digital Librarians:
Inquiry-based and project-based learning strategies are common for networked learning materials design. On those learning strategies, searching for resources in networked learning environments is the required learning activity. However, searching tools such as search engines are not appropriate for kids and are note suitable for learning purpose. Digital librarians are proposed to assist young learners for searching, filtering and organizing information to suit individual needs and cope with chores of information overflow automatically. Through the help from digital librarians, young learners can receive the information they really need and allow them focusing on learning tasks.
4.5 Evaluators
In networked learning environments, dynamic learning assessment is required from time to time for adjusting the learning paths or providing adaptive learning supports. Evaluators are proposed to conduct assessment to individual learner, groups, artifacts, and learning process based on student models. After evaluation, evaluators would provide immediate feedback or live online guidance to other agents.
Among these five intelligent agents, learning companions and genies are interface agents who are responsible for interacting with learners directly instead of avatars. The other three agents (e.g., moderators, digital librarians, and evaluators) are autonomous agents who will process the information in the background of networked learning environments and provide them to the interface agents.
5 The Framework for Implementing the New Paradigm
There are several issues worth of consideration when implementing the inhabited virtual learning worlds and intelligent agents.
5.1 Logging Mechanism
The logging mechanism of the learning space is designed to keep tracks of all the activities happen in it. The data in log files is the primary resource for constructing student model.
5.2 Student Model
Student model represents each individual learner’s learning behaviors and status dynamically. It is the required ingredient for embedding intelligent and adaptive features into the networked learning environments. It’s the heart of the brand new pedagogical approach for networked learning.
5.3 Spatial Dimensions
We need to transform the student model to 3D spatial dimensions that represent characteristics of learners and their relationship in learning communities when providing access to avatars. Spatial dimensions consist of learning attitudes such as motivation, learning experiences, personal demographic information, affective factors, and concurrent context situation of the virtual learning worlds. Student model holds the information of individual learner; nonetheless, spatial dimensions represent the relative relationship among learners in the learning community who are inhabited in the virtual worlds represented with their own avatars respectively.
5.4 Virtual Interaction
Interaction that takes place in the virtual learning worlds should combine the features of visual, gestural, and verbal communication. With these features, the learners in the virtual learning worlds would be able to apply the communication skills that resemble to the real social interaction environments.
6 Conclusions
With the experience in the field during these couple years, we realize that we need to resolve the issues of telepresence, learning communities, and learning supports in networked learning before it could really take place. We propose a new paradigm that will abandon current practice of Web-based learning. Our approach (i.e., inhabited virtual learning worlds and intelligent agents) is to create a virtual learning world within the networked learning environments that could provide a 3D shared learning space as the residence of avatars those who are the delegations of each individual learner. In practice, each individual learner will be represented with an avatar in the virtual learning worlds and supported by other five agents who are implemented in the networked learning environments.