Adaptive learning takes place in a type of training where some aspect of the training is varied to create an optimal learning experience for a particular learner. The order of presentation, type of presentation, type of information, and/or task difficulty can be adjusted to meet the specific needs of each learner. There are many different ways to determine what should be varied and why. For instance, you could choose to adjust different aspects of the training based on how well the learner is performing, particular learning characteristics of the learner, or the needs of the learner. Traditionally, adaptive learning can be seen in classroom settings when a teacher adapts their instruction based on verbal or nonverbal cues they get from students. In one of its simplest forms, using adaptive learning in a training program can entail selecting which content to give to a learner based on pre-test results.
Adaptive learning can also be incorporated into a training program through more complex means. For example, during computer based training, adaptive learning can be performed in real-time. This means that the computer software needs to determine the proficiency level of the learners while they are interacting with the content and simultaneously provide adequate support to the learners. For this to occur, algorithms and mathematical models must be used in an attempt to understand how the learner is moving along the learning path and how that information should be used to make assumptions about their next response. This type of learning is adaptive in two ways, as students receive both unique feedback and an adapted learning pathway. An adaptive pathway signifies the learners’ journey through the training content. This pathway is dependent on several factors like what learners are doing, what they have done in the past, and what misconceptions they have exhibited. Given this understanding, learners who demonstrate a deeper mastery of the learning content will be fast tracked while those showing signs of misconception might be directed to remedial content.
There are also simpler applications of adaptive learning in computer based training. These simpler applications use a pre-test to allow learners to test out of content. The learner is then provided with the training content where he or she did not pass the pretest. In using this approach, it is important to have well-designed and validated assessment items to ensure that the test is a good indicator of what the learner knows.
As adaptive learning is implemented into training programs in more complex ways, the cost and time required to build that training program generally increases as well. If simply selecting which content to give a learner based on pre-test results is on the lower end of the spectrum, then using a full Intelligent Tutoring System (ITS) is on the opposite end of that spectrum. An ITS acts like a tutor. It can pose questions, analyze the learner responses, and provide customized feedback. Training designed to use an ITS differs from traditional computer-based training (CBT) in its analysis of complex learner responses and customized guidance and support. The ITS creates a profile for each learner and provides real time personalized feedback based on the level of the learners’ mastery over the subject matter. In traditional CBT, the feedback provided is generic and, in most cases, just states whether the answer is correct or incorrect. An ITS is capable of going one step further to determine where in the learning path the learner went wrong when an incorrect answer is given. An ITS can even be designed to give an explanation as to why the answer is wrong and suggest appropriate remediation steps if necessary. An ITS is an effective learning tool that can address the learning needs for a many different types of learners. Thought an ITS can be costly, difficult, and time-consuming to build, its potential in the learning and development field is immense. Some studies have shown that using an ITS can increase learner performance by as much as 60%.
While an ITS is mainly focused on the learner-tutor interaction, the Army Research Laboratory’s Generalized Intelligent Framework for Tutoring (GIFT) is looking to measure training effectiveness through the use of an ITS. GIFT is a set of tools, methods, and standards to help create computer based tutoring systems and assess their impacts. GIFT has been used to demonstrate the effectiveness of an ITS in training evaluation. Researchers investigated how the existing GIFT architecture could be extended to provide an automated analysis capability, what data collection mechanisms could be utilized to support the analysis, and how to present the outputs to support decision-making about instructional strategy. They selected the Basic Rifle Marksmanship (BRM) course to provide context, sample data, and a basis of research for evaluation. The approach of incorporating simulated data into the analytic system was called Health Indicators. Results showed that the prototype was able to support certain statistical tests and that this would go a long way for automated analysis.
It is important to note that while the cost, difficulty, and time required to build adaptive learning and/or an ITS into a training program generally increases as you make it more complex and automated, there are affordable alternatives. For instance, the Knewton learning platform is an off the shelf adaptive learning solution available online. This platform is offered to certain users at no cost. Another example is GIFT which is available as an open source ITS. When deciding what type of adaptive learning to incorporate into a training program, it is important to balance the required complexity of the adaptive learning solution with the cost and time requirements of building that complexity. In addition to needing the platform to support the ITS, it is also necessary to have ample content to allow customized instruction.
The chart below provides examples of types of adaptive learning and intelligent tutoring used in the transit and non-transit industry, as well as possible applications for the transit industry.
|Adaptive Learning / Intelligent Tutoring|
|Examples from the Transit Industry|
|Xpan Interactive||Xpan Interactive provides an eLearning platform that supports adaptive learning. Xpan has created training for Calgary Transit Authority for Electro Vehicle Mechanics and cites a reduction in the time required to train a fully qualified Electro Vehicle Mechanic from 2 years to only 9 months.|
|Examples Beyond the Transit Industry|
|Virtual Maintenance Trainer||Boeing uses intelligent tutoring capabilities in its Virtual Maintenance Trainer (VMT) to provide students with immediate feedback and instruction through a virtual instructor. As a result, students spend less time training on actual aircraft. Boeing’s VMT can be configured for multiple platforms:
|Ground Forces Training||Boeing’s Integrated Immersive Training Environment (I2TE) seeks to provide innovative tools that increase training preparedness, generate positive training and build the confidence of Soldiers and Marines for full-spectrum operations. One key tool used to achieve such training effectiveness is Boeing’s Intelligent Tutoring System. It provides personalized training content and expert-level instruction and feedback while tailoring the learning path based on the student’s ability and knowledge base|
|Generalized Intelligent Framework for Tutoring (GIFT)||GIFT is being developed under the Adaptive Tutoring Research Science & Technology project at the Learning in Intelligent Tutoring Environments (LITE) Laboratory, part of the U.S. Army Research Laboratory - Human Research and Engineering Directorate (ARL-HRED). It is a research-based service-oriented framework of tools, methods, and standards to help make it easier to develop computer-based tutoring systems (CBTS), manage instruction, and assess the effectiveness of CBTS. GIFT consists of several interchangeable modules that interact with each other within a CBTS. It is an open source and available at no cost.|
|Knewton||Knewton is an online adaptive course building portal. The Knewton learning platform is notable in the field of adaptive learning, and is an example of how adaptive learning can benefit learners in real-time. In the company’s words, ‘Knewton’s pioneering approach to adaptive learning draws on each student’s own history, how other students like them learn, and decades of research into how people learn to improve future learning experiences’. Knewton promises to help you build a course that is individualized, engaging, evolving, and versatile. Up to this point they have partnered with many of the world’s leading educational publishers, but they are interested in working with other industries.|
|Smart Sparrow||Smart Sparrow is another online adaptive course building portal. They aim to help you engage each student by giving you full pedagogical control over your students’ learning experience. They offer drag-and-drop interactive components to enable active learning and easy-to-author adaptivity. They also offer real-time analytics to help you understand your learners’ needs. This can help you zero in on common mistakes and misconceptions. Smart Sparrow also offers cloud-based solutions, LMS Integrations, question templates, and the ability to import simulations.|
|Possible Applications for the Transit Industry|
|Maintenance and Servicing Training||An ITS could be implemented in critical servicing or maintenance training that involves decision making. An incorrect decision would lead learners to a different path than a correct decision would. With the right amount of just-in-time guidance and feedback, learners would be able to get back on track. The ITS could also help in reducing the amount of time learners stay away from work. Another potential benefit of using an ITS is that learners should require less time to effectively learn the content. This is primarily due to the focused nature of adaptive learning and the use of an ITS.|
|Customer Service Training||Customer service training is an excellent topic for ITS and adaptive learning as there are many assumptions an misconceptions associated. These forms of training can help a learner experience virtually what could go wrong and the subtle hints and guidance can enable them to be better at customer service.|