Understanding Virtual Universitiesby Roy Rada
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All those involved in Higher Education are under pressure to familiarise themselves with the newest developments in Information Technology, and to understand the ways in which they can make use of these resources. This book will help academics from all disciplines take full advantage of IT. Anticipating a future in which distance learning and virtual reality tutoring systems play a central role in university teaching, Roy Rada provides guidelines for making best use of the technological opportunities. Unlike other books that focus on specific aspects of the subject, Understanding Virtual Universities combines managerial, social and technical issues, to provide a comprehensive approach to Information Technology for Higher Education.
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Understanding Virtual Universities
By Roy Rada
Intellect LtdCopyright © 2001 Intellect Ltd
All rights reserved.
Learning and Content
In this chapter readers will explore:
the complex mapping among students, the tools and methods used for learning, and the learning problems,
the different types of learning as reflected in the taxonomy of learning types,
the impact of learning by doing,
the impact of different media on different learning objectives,
the history of intelligent tutoring systems,
the components of intelligent tutoring systems,
standards for content,
examples and patterns of content production in higher education institutions, and
the extensive organizational commitment required for content production.
Under what conditions does learning occur? The dream of digital content developers is that students can interact with computers in ways that would have otherwise been restricted to the interaction between students and teachers. Since at least the 1960s some educators have been attracted to the possibilities of using computers and networks to support learning. Have the anticipated impacts followed the expectations of the enthusiasts?
The efforts to apply computers and networks to learning have been so many and so diverse that the terminology that applies is also varied. At the level of an individual student learning online, some of the terms that have been applied to the technology include: courseware, learning technology systems, computer-based training systems, electronic performance support systems, computer-assisted instruction systems, intelligent tutoring systems, education and training technology, Web-based instruction systems, and interactive learning environments. In this chapter the preferred synonym will be 'courseware' and refers to the content plus technology that is used to support individual learning.
People have a long history across generations of dealing effectively with paper forms of information. Should paper be replaced with computer forms? Or might the better solution be complementary combinations of paper and digital media?
A wide range of tools is available to educators, but what experience has been gained in the application to learning. Unfortunately, the wealth of experience does not distill easily into detailed guidance about what to do next. The many developments in the field have often been one without proper reference to another. Even the terminology used by the developers has not been consistent. Thus comparing one observation to another observation is fraught with difficulties of knowing whether one person's apples are the same as another person's apples or whether apples are instead being compared to oranges. How will agreement arise about what has been done?
Learning and Pedagogy
Some psychologists specialize in learning psychology; some educators specialize in pedagogy or the art of teaching. What is known about learning and teaching?
Taxonomy of Learning Types
A group of educational psychologists developed a classification of levels of learning. This became taxonomy, sometimes called Bloom's taxonomy that included three overlapping domains: the cognitive, affective, and psychomotor (DLRN, 1997 and Bloom, 1956).
Cognitive learning is demonstrated by knowledge recall and the intellectual skills: Bloom's taxonomy identified six levels within the cognitive domain, from the simple recall or recognition of facts, at the lowest level, through increasingly more complex and abstract mental levels, to evaluation at the highest level.
For a teacher to help a student integrate new knowledge into the student's existing models of the self or the environment, the teacher must help the student identify the relationships between what the student already knows and what is new to be learned. Giving students questions to answer that stretch their thinking about the new knowledge typically does this. Below are the six cognitive levels as they correspond to questions that a teacher might ask to help a student learn:
Knowledge involves recall of information and relates to questions such as whom, what, when, where, how ...?
Comprehension involves organizing and selecting facts and ideas, and asks how would you describe in your own words?
Application is problem solving or use of facts, rules and principles. Typical questions take the form: How is ... an example of ...? How is ... related to ...?
Analysis is separation of a whole into component parts. Questions include: What are the parts or features of ...? How does ... contrast with ...?
Synthesis is the combination of ideas to form a new whole. Questions include: What would you predict from ...? How would you create a new ...?
Evaluation is the development of opinions, judgments or decisions. Typical questions are: What is the most important ...? What criteria would you use to assess ...?
Affective learning is demonstrated by behaviors indicating attitudes of awareness, interest, attention, concern, and responsibility and ability to listen and respond in interactions with others. The depth and breadth of information processed and what and how much is learned and remembered is influenced by
self-awareness and beliefs about self and one's learning ability (personal control, competence and ability);
clarity and saliency of personal goals;
personal expectations for success or failure;
affect, emotion and general states of mind; and
the resulting motivation to learn.
Psychomotor learning is demonstrated by grace and actions which demonstrate the motor skills such as use of precision instruments or tools.
Basic principles of learning motivation and effective instruction apply to all groups of learners. However, learners differ in their preferences for learning mode and strategies, the pace at which they learn, and unique capabilities in particular areas. These differences are a function of both environment and heredity.
Learning by Doing
Some say that students will learn better when they can test the models they are learning in real world situations. Educators who are also proponents of using the computer in education sometimes claim that learning by doing is vital and that computers can support this. This approach is also called constructivist learning (Jonassen, 2000).
Roger Schank directs the Institute for the Learning Sciences at Northwestern University, Illinois, USA. Schank (1997, 2000) claims that the number one problem with education is:
Schools act as if learning can be dissociated from doing. There really is no learning without doing.
Learning by doing can be realized in any discipline. For instance, students can explore the history of the American Civil War by constructing an economic model of factors motivating the North and the South. Such a learning-by-doing approach contrasts with an approach in which students are asked to read a chapter about the American Civil War and then to answer multiple-choice questions about the dates at which certain events occurred. The constructivist approach addresses a higher level of learning than does the memorization approach.
Ben Shneiderman's (1997) motto is 'Real Projects for Real People'. He says (Shneiderman, 1993):
The post-TV media of computers and communications enables teachers, students, and parents to creatively develop education by engagement and construction. Students should be given the chance to engage with each other in team projects, with the goal of constructing a product that is useful or interesting to someone other than the teacher. Challenges remain such as scaling up from small class projects to lecture sections with hundreds of students, covering the curriculum that is currently required by many schools, evaluating performance, and assigning grades.
Students will be engaged by writing and drawing, composing and designing, and planning and drawing. Teachers should promote engaging in the world, helping where needed, caring for others, and communicating ideas. Project-oriented learning allows the aforementioned guidelines to be realized in the most natural way.
In project-oriented learning or learning-by-doing, students need to have objectives and to be assessed for their progress towards the objectives. Educators should monitor the following stages of the education cycle (see Figure 8 "Education Cycle"):
1) identify and analyze education needs or objectives,
2) design and plan education,
3) provide and deliver education, and
4) evaluate education outcomes and improve the education process.
In the ideal situation, the output of one stage will provide the input for the succeeding stage.
Identifying and analyzing needs is the starting point. Educators should identify the needs for students, assess the competencies of the students, and develop plans to close any gaps. The design and plan phase provides the specifications for the education. This phase includes:
the design and plan of actions to address the needs identified in the earlier process; and
the design of the criteria for evaluating the outcomes and monitoring the education process.
The relevant methods of education that can meet the education needs should be identified. This cycle of identify, plan, deliver, and evaluate makes sense for teaching and for other activities too.
Delivering Interactive Content
Simply delivering information by computer has relatively little advantage over delivering by paper in many cases. However, with the computer one can gain interactivity that is not possible with paper. By placing some intelligence into the computer so that the interactions it provides do some work of a teacher, one gains a kind of cost effectiveness in education. Much work has been done over the past forty years to help establish the principles and practice by which computers can incorporate some of the intelligence of the teacher (Wenger, 1987; Cartwright, 1993).
One example of courseware incorporating multiple techniques for delivery and interaction is described next. This example was ahead of its time but illustrates the kind of product that has appeared in isolation repeatedly in the past. Such products may someday become prevalent in educational environments and the ensuing sections sketch how such products might appear.
This example from the 1980s integrates several tools and methods. In 1985 (Diaz 1991) students taking the course Introductory Pathology at Cornell School of Medicine, New York, USA, could enroll in PathMac, an electronic version of the course. Macintosh computers tied into the PathMac database were scattered throughout the campus for student access. Students could study online textbooks, run simulated laboratories, or test their mastery of physiology via online dissections. PathMac provided online access to approximately seven gigabytes of images and bibliographical material that could be searched intelligently, cross-referenced, and printed.
One online application was an electronic pathology text called HyperPath, which included large portions of a version of a well-known textbook. Teachers could add text and graphics. A visual archive called Carousel included thousands of images. Carousel images could be paired with questions.
Another program was used to perform simulated laboratory experiments that otherwise would be performed on live cats. The system could test the effect of various drugs on simulated cat muscle. The students chose which drug to inject, in what quantity, and then electrically stimulated the muscle and recorded the results on a simulated strip chart. Much more control over the results could be achieved than is possible with live muscle.
Medical students can explore patient treatment situations through simulation. For instance, in one simulation a young man presents with a severe asthmatic attack after a walk (Corvetta et al. 1991). The season is spring and the walk was in the countryside, both facts suggesting an allergic etiology of the disease. If the student's choice is to perform a case history or skin tests, the computerized tutor comments that the choice is wrong and that the priority is to relieve the patient's symptoms. A physical examination and appropriate treatment should be immediately performed. Once the prescription of the correct medication results in normalization of the respiratory sound and congratulations from the tutor, a case history may be taken. The tutor emphasizes the key questions in the case history that should be asked in order to determine the possible allergic origin of a respiratory disease. Next the student performs the skin tests and evaluates the reactions. Diagnosis of the allergy pollens may be made and a correct hyposensitizing treatment planned. Such simulations can be part of an effective learning environment.
The preceding Pathmac example did not have widespread impact on the teaching in medical schools. However, multiple-choice questions delivered online have had a major impact on teaching in medical schools and elsewhere. The computer is an excellent tool for supporting multiple-choice questions or tests. The user chooses a particular answer and the computer can immediately explain to the student whether the student's answer was correct or incorrect. By storing explanations for why an answer is incorrect, the computer can also readily supply this explanation to the user. Multiple-choice questions have been a mainstay of interaction for courseware for decades.
Multiple-choice tests have been shown to promote retention learning. However, announcements of an upcoming test did not have a positive effect on retention learning without a test actually being given. Increased studying due to anticipation of a test did not result in better retention – only the act of taking the test increased retention (Haynie, 1994).
In a multiple-choice question, students must select the correct answer from a number of possible answers. The incorrect answers are termed distracters (see Figure 9 "Multiple Choice Question"). These distracters should embody misconceptions; partly correct answers and common errors of fact or reasoning so that they distract students who are not well-prepared for the test from giving the correct answer.
Multiple-choice questions are usually used to test a student's ability to recall information, to interpret data or diagrams, and to analyze and evaluate material. The principal strengths of multiple-choice tests are (Ballatyne, 2000):
They test a wide range of issues in a short time.
A computer can reliably mark them, as all answers are predetermined.
Computer marking gives easy access to an item analysis of questions to pinpoint problem areas for students.
A large bank of questions can be built up to reduce future preparation time.
They can be used for quick revision at the start or end of a class.
The principal weaknesses of multiple-choice question tests are:
They do not test a student's ability to develop and organize ideas and present these in a coherent argument.
It takes a long time to write plausible distracters - especially in cases where higher order cognitive skills are being tested.
Restrictions are placed on a students' answers, as they must select from the author's alternatives.
Questions are often re-used which means attention to security.
Questions need to be pre-tested and items reviewed to ensure the validity of the items.
Other possible disadvantages to online multiple-choice questions are the same as the disadvantages that can accrue for any computer use, namely, that certain groups of people do not have as ready access to or familiarity with computers (Fairtest, 2000).
Despite some unresolved problems, online quizzes can be useful. Students at the University of California at Irvine's Graduate School of Management, California, USA, carry their laptops into classrooms in which every seat has a high-speed Internet connection. Teachers give Web-based electronic quizzes at the start of class, receive instant feedback on how the students did on each question, and adjust their lecture plans on the spot to focus on the areas where students need the most help.
Less than a second after finishing each test the students can see all wrong answers on their screens and an explanation of what the right answer should have been. This instant feedback, according to the school's Administrative Computing Manager Tony Zamanian, has changed the way the school uses tests and quizzes. Zamanian says (QuestionMark, 2000):
The tests are not only tests any more; rather they are tools that help students understand what is required of them. Faculty members can convey to students the kind of information they want to receive from them. We are starting to look at tests as learning tools in a very active sense of the word; instant feedback gives students an idea of their strengths and weaknesses and puts them on the right track for studying the material.
Public Policy Professor Peter Navarro says that students thrive on the instant feedback they receive from computer-based tests. Navarro sees the primary goal of such tests as motivation rather than evaluation:
The ability to administer electronic tests gives me a very powerful tool to encourage students to keep up with the reading material on a regular basis. I believe such even- paced learning greatly increases the half-life of a student's knowledge retention relative to the 'cram before exam' mode that so many students fall into.
Electronic testing can be a complement to rather than a substitute for other forms of testing and interaction between teacher and student.
Excerpted from Understanding Virtual Universities by Roy Rada. Copyright © 2001 Intellect Ltd. Excerpted by permission of Intellect Ltd.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
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