The Future of Online Learning


Personalized Education

Imagine the best desktop computer you can imagine, slung over your shoulder like a slim handbag, connected to the billions of resources available on the internet, supporting instant multimedia communications anywhere on the planet, and you have a picture of the tool available for education within the next decade. The development of such a tool makes it not just possible, but inevitable, that education of the future will become deeply personalized.

Education today, from the kindergarten level to PhD seminars, is based on the model of the class. At the early levels especially, classes are organized not by the learning needed by the student so much as that student's age. In post-secondary education, age becomes less of a factor but education is still fundamentally time-based and depends on standard curricula for groups of students. The model is that of a group of people starting at the same time, studying the same materials at the same pace, and ending at the same time.

This model of education was adopted because it was the most efficient. It is heavily dependent on the teacher, and the teacher in turn is responsible for assembling, and often presenting, the materials to be learned. For the most part, customization and personalization are not practical, because personalized teacher-led instruction is not practical. It is much more efficient to deliver the same content once to a group of students than it is to deliver the same content thirty times to individual students. Given the technology that we had, the class was the only practical solution.

Education in the future will be much less class-based, and much more topic-based. This already is the model being explored by such alternative educational models as programmed learning and constructive learning. The idea is that learning is not paced so much by the teacher as it is by the student's own capacity to acquire the material. Additionally, the topic selection for an individual's education will be based on that student's need, not the preselected curriculum for a particular class. Any given student may at any time be taking any given topic, and progressing at a pace through that material appropriate to his or her learning ability.

What will make this possible is the development of Educational Delivery (ED) technology. The primary purpose of ED will not be so much to teach as it will be to manage learning. Individual students will be served by ED along a variety of dimensions:

Topics will be selected student interest, student aptitude and educational level, and societal need. The menu of available topics presented to any given student will be determined by the student's demonstrated prior learning, by parent input and control, and by legislation governing education in that student's political jurisdiction. Selecting an educational topic, for a student, will be like selecting a channel on television. A student's daily menu will be varied and constantly changing, building on each day's achievement.

This model for the selection of educational activities - I call it the Quest Model - has worked well in gaming environments. As various people log on to an online game, they may be at different levels, have different inclinations, and have different abilities. The game presents a variety of quests for them to fulfill, based on their level, and they select from these quests based on their inclinations. As they select a quest, they are joined by fellow-travelers attempting the same quest (for often, a group is required for the successful completion of a quest). Some quests may be short - just a few minutes - while others may require a sustained commitment over several days.

Although unusual in institutional settings, except at the very coarse course-selection level, the menuization of educational topics is common in business settings. My first experience with this occurred in 1981 with Texas Instruments. In addition to two required courses, I had a wide range of options to choose from as supplementary learning (I selected MVS-JES3, a processing language, and On The Way Up, a communications course). Learning was self-paced, supported by manuals and videotapes (state of the art).

Today's internet is offering adults especially more opportunities for topic selection than ever before. There is a proliferation of online courses - some short and to the point, such as those offered by Ziff-Davis, others long and involved, such as those offered by Athabasca University. Potential students now typically access course indices, such as offered by Tele-Education new Brunswick, and select the learning which suits their needs.

But these are merely course selections. The prominence of the course is based on the class-based learning model. As classes, in and of themselves, fade from the scene, the selection of learning will drop to a lower scale, with topics selected in hourly or daily increments. This trend I describe as the modularization of learning, and is discussed below.

The Presentation of Material will occur automatically, powered by the ED system, based on the students' progression through the topic. While the presentation of material will in some cases be linear (as it is always in a classroom), such as via video presentations or text-based reading, in other cases choices will have to be made, while in other cases the presentation of material will be multi-threaded (that is, material on two distinct subjects will be presented simultaneously, as for example is common in music videos or on internet chatlines).

As students progress through a topic, material will be presented to them dynamically, according to one of the following mechanisms: (a) student-selected, from a library of background information on the topic in question (for example, the student reads a description of the quest from a scroll); (b) event-driven, by the system, when the student reaches a particular point in the course (for example, upon reaching Athia, the student encounters a shopkeeper with a tale to tell); (c) time-driven, by the system, after a certain time has elapsed (for example, after an hour, it rains, and the writing on the sheepskin is revealed); or (d) instructor-driven, by the instructor, as additional information is requested or volunteered.

The personalization of education just described will be adopted - gradually, as traditionalists fade out of the scene - not because it provides better educational results (this has yet to be proven, although it is likely) or because students prefer it (this again needs to be proven, but is again likely), but because it is more efficient. Classroom education is in many ways wasteful. Material is reviewed for thirty students when in fact only five need review. New material presented is absorbed by half the students, but is beyond the capacity of the other half. That time in class which is spent by a student unproductively - either waiting for an instructor to address another student's question, discipline problem, or other need - is eliminated through personalized instruction.

Or to put the point another way: so long as the class remains the dominant paradigm of education, the potential for improved efficiencies inherent in the new technology will remain unrealized. Only when the capacity for new technology to customize and personalize education are employed will the efficiencies begin to show.

Learning Styles employed by online learning systems will be tailored to individual students as well. Different students learn in different ways. Online learning systems will identify individual students' preferred learning styles, and present educational materials accordingly.

Thus, for example, students who learn best by exploring (for example, learning software by trying every command to see what happens) will be presented a variety of options they may pursue, while students who prefer ordered, linear presentations may be presented with a video stream covering the same material. Students who learn orally may watch and listen to a taped lecture, while students who learn visually may be presented with graphical representations of the concepts being covered.

Learning styles exist across a number of dimensions, and designers of educational systems will need to, first, prepare materials appropriate to each of these dimensions, and second, incorporate a method of selecting materials from different dimensions. Learning style selection may be enabled via (a) a testing mechanism, which sets a system's default values, (b) student selected, via a set of sliding scales for each dimension, or (c) instructor selected, to satisfy desired learning or learning style criteria.

Recording and tracking student progress, currently a time-consuming and dull job for instructors (often still accomplished in course gradebooks they way it was done in the fifties) will to a large degree be handled automatically by the system. While the instructor will still have an essential role in monitoring and evaluating student progress, the computer will compile the data required for reasonable and efficient monitoring and tracking.

Most people when they think of automatic monitoring and tracking, think of two things: first, auto-marked tests and exams, and second, progress logs. Each of these will have a role in the future, but a much smaller role than might otherwise be assumed, because of the wealth of data available to the online instructor.

For example, an online test might measure a student's (current) recall of physics, but often of more interest to the instructor is how that knowledge is used. Since all the student's interactions online can be logged and recorded, and since intelligent searches can locate instances of particular terms or concepts in a body of data, an instructor can identify when, if at all, a given concept was used during the course of studies.

Or, for example, the results from a student's work with a simulator (in crop planning, say), may be fed directly into the student's course database. For example, suppose a student, based on the available data, decides to grow wheat and oats, applying pesticide and fertilizer to the crop at appropriate times. At harvest, the simulator would calculate the resultant yield, and feed this result to the student's database, where, if appropriate, completion of the simulation would be graded and the mark applied to the student's overall result.

Such dull tasks as recording grades, monitoring attendance (or participation) and progress, and the like, will all be performed automatically, the results presented in intuitive and informative graphics or charts.

What will not happen is this: students will not be summatively evaluated by the online learning system. In the end, insofar as they are graded, they will want to be graded by a human. The reason for this is much more psychological than it is practical. People will not react well to being graded by a machine. They will not like the automatic no-appeal-possible quality of such a system. Even where all inputs to the system automatic, students would want the final result consulted by, evaluated by, and awarded by, a human being.

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Copyright 2004 Stephen Downes
This work is licensed under a Creative Commons License.