SimLearning: Taking eLearning beyond multimedia, M MCGARITY, C SIMON

Tags: learner, eLearning, learning process, Kindergarten teachers, speech recognition technologies, instructional designers, instructional designer, piece of information, Hands on Learning, rectangular prisms, experience, corporate eLearning, corporate training courses, technologies, recognition, learning design, learning modules, effective learning, grammar-based, specific group, adult learners, learning environment, instructional design, Voice Recognition
Content: SimLearning: Taking eLearning beyond multimedia
Michael MCGARITY; Craig SIMON Adacel Technologies [email protected]
Abstract. Educators have long realised that the best way to teach a person is within the environment that the end task will be performed. Within the simulation community, improvements in human interfaces such as voice recognition and graphical representation are combined with improved interaction capability such as behavioural modelling. This is in contrast to the eLearning space, where solutions are restricted by web-based capability. We present our experience taking the best of the approaches offered by SimLearning to courses delivered by the Web.
1. INTRODUCTION In the last couple of years, the corporate eLearning world has stumbled across probably the greatest learning process that they have ever had the opportunity to utilize. We call it "Simulation Learning" ­ learning something by simulating an experience as closely as possible to the desired end experience. 1.1 Lessons Learned From Kindergarten Surprisingly, a hidden world not far from you and I has been using this pedagogy for many years, long before the corporate world. An organisation and a group of people has been profiting from this powerful piece of information to the gain of their own clients. Not wanting to have their ideas further exploited, they have managed to keep this crucial piece of information to themselves... until now! I speak of the realm of Kindergarten teachers. The cornerstones of the education system into which we entrust our future have known this for a long time and have employed these powerful techniques in their teaching. They however have not been able to think of a powerful term such as "Simulation Learning" (Their marketing dollars must have run out prior to the branding exercise) They call it "Learning by doing" or "Hands on Learning" ­ but it is bigger and greater than that, as they incorporate many other techniques 1.2 Hands on Learning Kindergarten teachers (and many others for that matter) have known that if you want to be effective in teaching something to children, then you need to observe some very basic, yet powerful enabling techniques. Allowing a child to actually "do" something that is part of the learning process, will increase the ability for that child to grasp the concept being taught. In the world of maths, if you are trying to teach a child about 3 dimensional prisms, one of the most effective ways of developing this concept is to allow the children to make one, and experience the cognitive development through the process. The teacher would provide the net of a prism, such as a cube, and allow the children to "build"
the cube. Learning by doing or simulating the end result is very effective. 2. LEARNING METHODOLOGIES In order to teach something to a child, you have a better chance of success if you are able to show them the real life application of what it is that you are trying to teach. For example, when learning about prisms, any good teacher will take the learners on an exploration of the school grounds, looking for the hidden cubes, rectangular prisms, cones, tubes, and perhaps even that elusive icosadodecahedron! When a child sees how prisms have an effect on their day to day lives, they find it easier to learn the new concept. Learning has to be relevant children need the opportunity to learn through exploring and discovering things for themselves. In order for them to do so, they need to be in an environment, and participate in learning events that are non threatening (Knowles, 1980). In the classroom, if the children are scared of making mistakes, they are less reluctant to take chances and learn by exploring. Learning has to be non threatening classroom teachers will tell you that there is an optimum duration of a lesson that assists in facilitating effective leaning. In the kindergarten room this is usually about 5-10 minutes (Cooper, 1990). Learning should be delivered in such a way to facilitate "chunked" learning to allow the working memory to pass through skills and information to the long term memory. Learning should be designed to reduce Cognitive Load. Good teachers know that if the learners in their room don't have a reason for being in the classroom (or understand the reason), learning is more difficult to achieve (Sweller, 1996). The learning event that is full of bells, whistles and everything that moves and is colourful, will be the most remembered and most effective. The learner must be motivated to learn. Teachers are constantly assessing and evaluating the cognitive levels of their pupils. They need to know exactly where on the learning curve each of their pupils are located. They need to know this in order to teach at the correct level, and design learning events that are
specific to the needs of their students. (Knowles, 1980). There is no sense in trying to teach 3 dimensional objects to a child that has not grasped the concept of 2 dimensional objects. The learning event must be designed with the needs, ability, and current skills of the learner in mind. Teachers don't just assess and evaluate for sake of filling in lists of numbers into a spreadsheet. They do this to adapt their teaching to the needs of the students, and provide learning events that are targeted at the specific group of pupils. The most effective learning event is one which has been adapted to suit the specific learner at a specific time. 3. ENABLING TECHNOLOGIES In the corporate world of training, we have been hamstrung by one overarching factor when it comes to effective learning ­ Employees are at their jobs to work ­ not learn. The school teacher has all day and every day (well only between 9 and 3 each day..... except 12 weeks of the year, plus morning and afternoon tea time, and lunch, and free play time) So how might the busy corporate cope with the additional strains of learning when they were at their place of employment to achieve a desired outcome. In the past the learning world consisted of classroom face to face learning ­ which was time and cost consuming, and didn't actually deliver effective cognitive advantage to the learners. In recent times however, emerging technologies have enabled the incorporation of good learning design into effective and successful learning. 3.1 Voice Recognition Speaker-independent continuous voice recognition is an exceedingly difficult problem, given the variation in human voices and speaking behaviour. Most commercial dictation systems use speaker-dependent neural net technologies that require training by individual users. For most eLearning voice recognition tasks, dictation-based speech recognizers do not provide nearly the accuracy nor exploit the techniques available from grammar-based recognizers to anticipate, and thereby limit, what the systems expect the user to say next. They are thus less effective for eLearning VR tasks than command and control grammar-based technologies. Voice recognition (VR) is a highly useful enabling technology within simulation learning, allowing learning in domains that are otherwise difficult to teach. However, VR is also a useful interface as such, providing an additional learning dimensions to existing learning modules. Voice Recognition enables simulation learning over a range of domains. Situations such as making a sales call, interacting with a retail customer or working in a call centre, all have verbal communication by the learner central to the task. The other common feature of the situations listed is that the learner is required to make use of a very limited vocabulary and grammar to ensure consistency of service. This coincidentally
allows for the use of grammar-based voice recognition technologies, which provide much greater levels of recognition accuracy over dictation-based approaches. But voice recognition is applicable even in domains where verbal isn't central to the task. Our understanding of learning methodologies shows us that the more of our senses that are involved in piece of information, the greater our recall will be. VR provides an additional learning dimension in that allows learners to interact with the courseware using verbal and auditory parts of the brains that would be inactive otherwise. 3.2 Agents in Learning The term agent is widely used to describe a range of software components. This paper uses "agent" to mean an intelligent agent capable of reasoning in a welldefined way. The reasoning ability of an agent is analogous to a person with access to a Procedures Manual. The Procedures Manual describes the steps that the agent should take when a certain event arises or when it wants to achieve a certain outcome. In particular, the agent is designed to be goal-directed, to have real-time context sensitivity, and be able to respond to multiple events concurrently. Agents can be incorporated into simulation learning modules in several ways, but the three most common roles are character replacement, information aid, and mentor. Character replacement agents take the role of a character other than the learner in the simulation. If the learner was to be a project manager, the agent may take the role of a subcontractor, or of legal representation. If the learner is to play a sales role, the agent could take the part of a potential client. The agents may be supportive or confrontational. Naturally, the learner may be interacting concurrently with multiple agents. An Information Aid is an explicitly helpful agent, designed to guide the learner through the information that they are to know on the job. A sales executive might wish to work through which of his products would satisfy the clients needs just before a meeting. Originally little more than advanced search engines, information management agents will be more useful in reducing the cognitive load of the student during training and on the job. Mentoring agents offer a quite different service to the learner. By monitoring the actions of the learner in the simulation or even on the job, the agent is able to determine where the learner understands concepts and processes imperfectly and provide appropriate and timely advice. 3.3 Discrete event simulation Most systems that we are called upon to simulate can be modelled simply. All that is generally required is a small number of parameters that may be modified at fixed points through the process combined with screen representation of the system being simulated. This
observation leads to a robust method of simulation based on discrete events, which is relatively easy to build and modify without concerns of possibly complex interrelationships between segments of learning. 3.4 Templated eLearning An area of eLearning which has seen great improvement over the past 10 years has been the cost and speed of implementation. Tool which build eLearning modules from templates allow activity pages, such as multiple-choice questions, to be just as easy to implement as text pages. This frees the instructional designer up to include appropriate activities and interactions without the drive for simpler or less costly solutions. Templated learning also provides a solution which is easily customisable, allowing non-technical personnel, or even instructional designers from the client organisation to make changes to the wording or configuration of the learning module. Of all of the components of simLearning, the component that is most significant for learning outcomes is instructional design: Learning that is appropriate for the learning task, learning that addresses the learners need, and learning that is timely 3.5 Expanded Toolset Many corporate training courses have been based on one of two delivery methods. The first is to use eLearning, in which the material is presented on the computer screen, either textually or using multimedia. The second mode is talk and chalk, in which the material is presented on a board, possibly with a powerpoint presentation, and explained clearly or otherwise by the presenter. These courses do not work. The very best corporate training courses employ multiple instructors to engage the learners in a simulation exercise. These courses do work, far more effectively, because they teach learners by allowing them to perform the task that they are learning. However, this style of course is expensive and either has low throughput or some other issues such as a lack of standardisation. The tools and technologies that we have described in this paper as now available are valuable in their own right to simulation learning in that they engage the student using senses and interactions not previously available. However, they are most valuable in that the technologies enable the learner to learn by doing a greater range of tasks than has been hitherto possible.
4. EXAMPLES 4.1 Simulation Learning with voice recognitionCall centre training Moving into the new realm of elearning, utilizing voice and speech recognition technologies, we are able to provide an enabling tool that can only be reproduced, albeit poorly, by another human being. This can be used in the development of specific skills related to all call centre operations, especially that of synchronicity. Synchronicity, is the ability to talk, type and listen at the same time. To train this very specific skill, the learning event must incorporate the user being able to listen to a caller, type in information into a system, and talk to the caller. Currently this is not possible in a "tutor/mentor" situation with a live person as the caller, as they must synchronise their script with the system as well as the input from the learner. With the advent of voice and speech recognition, this is now possible, with the simulated caller being provided by the learning system, allowing for the flexibility of being able to utilize human resources to complete other tasks such as analyzing and assessing a students ability or performance. The scenario posed also allows the learner to be placed in a non-threatening situation, due to the fact that they aren't potentially talking to someone that they may know, and may potentially be "judged" for their mistakes. This can only enhance the learning event 4.2 Simulation Learning with Voice Recognition as well as Agent technologies-Adaptive learning.Sales training, product training Incorporating voice/speech recognition and the use of agent technology, allows us to design, and build adaptive learning solutions that can be utilized in providing a learning environment that is suitable for Sales and Product information. Being able to provide a system free training environment allows the training to occur primarily via the use of telephones. This is especially useful in situations where the main role of the learner is to sell or provide relevant information to clients over the telephone. This may be done as part of call centre training where the focus is sales/support. In this scenario the learner is placed in a simulated call scenario, whereby the caller may assume different roles/responsibilities, and whereby these may change depending on the time of day, the mood of the caller, and the responses of the learner. The training may also occur in a "Just In Time" scenario, whereby the learner is a frequent traveller and is often out of the office. This allows the learner to participate in learning via their mobile phones, just prior to an engagement, or meeting to refresh or update the relevant information required at that time.
5. CONCLUSIONS AND LESSONS LEARNT Kindergarten can teach us a lot about how adult learners best learn new skills. The concept of hand-on learning or "learning by doing" is just part of how simulation learning is able to transform that way that corporate training is designed and delivered. The following points capture some of the lessons that we have learnt when delivering Simulation Learning. 1. Simulating a required job role, in a learning environment, will increase the probability that effective learning will occur. 2. Adding fidelity to the simulated function further increases the effectiveness of the learning. 3. Voice/speech recognition technologies used in eLearning environments add another dimension to the learners simulated experience, increasing the cognitive proximity to their role or function. 4. Learners are more likely to be motivated if they know the reasons and the objectives of the learning. 5. Learning delivered in small chunks increases the probability of retention.
6. Adults who are unable to relate the training that they are doing to their current job role, are more reluctant to learn. The technologies that we have briefly described in this paper ­ voice recognition, agent based modelling of role-play and mentor behaviour, and discrete event modelling ­ enable additional modes of delivery and wider domains for eLearning. These technologies are not just additional "bells and whistles", but allow a change of approach ­ a shift in emphasis back to the instructional design that is appropriate for the learners and the learning task. They mean that theories of instructional design, which have been well known to educators for some time, can now be applied to eLearning with a greater relevance and applicability than previously possible. REFERENCES 1. Knowles, M. (1980). "The modern practice of adult education: From pedagogy to andragogy." Cambridge, NJ. 2. Cooper, G. (1990) "Cognitive load theory as an aid for instructional design" Australian Journal of Educational Technology, vol 6, no. 2, pp 108-113. http://cleo.murdoch.edu.au/gen/aset/ajet/ajet6/su90p108.html 3. Sweller, J., Chandler, P., (1996) "Cognitive load while learning to use a computer program" Applied Cognitive Psychology, vol 10, 151-170

M MCGARITY, C SIMON

File: simlearning-taking-elearning-beyond-multimedia.pdf
Title: SimLearning: Taking eLearning beyond multimedia
Author: M MCGARITY, C SIMON
Author: Michael McGarity
Subject: SimTect 2004 Paper
Published: Wed May 5 16:41:08 2004
Pages: 4
File size: 0.18 Mb


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