Design Of Learning Systems Research Articles

EC research in language learning and it – some experiences with LINGUA

Abstract This paper begins with a description of ongoing research which has the objectives of designing and producing a Danish business course for speakers of English, and of investigating the design of multimedia language learning systems in general. It then discusses certain aspects of the role and overall philosophy of LINGUA, a European Community Programme to promote Foreign Language Competence. It concludes that the statistics of activities may be impressive, but that new insights into language learning are few.

The Impact of Data Accuracy on System Learning

:The purpose of this paper is to study the impact of database accuracy on system learning. The paper assumes a basic model of an information system with a database, a rulebase, and an embedded machine learning approach that is used to add rules to the rulebase. The system learns from its database, changes to that database, and the examination of other databases. The results in this paper can be of use in the analysis of the design and behavior of such learning systems. It is found that the information system accuracy impacts the magnitude of a measure of goodness of individual rules. Thus, if only rules of a certain magnitude are kept, then some rules will be discarded because of database inaccuracy, unless that inaccuracy is accounted for. In addition, by accounting for database inaccuracy, the direction of the impact on measure of goodness can be determined. In some cases, the impact on the direction is monotonic. This finding allows us to understand the impact of database inaccuracy, without explicitly taking account of that inaccuracy. Further, information system accuracy can impact the resulting order of importance of rules, within a set of rules. Since only those higher-ranked rules are kept, database accuracy and measure of goodness can impact what rules are retained in the rulebase of the system. As a result, it is important to account for the information system accuracy in learning information systems.

INCREMENTAL LEARNING OF PRODUCTION RULES FROM EXAMPLES UNDER UNCERTAINTY: A ROUGH SET APPROACH

This paper introduces an algorithm, LEM3, for incremental learning of production rules from examples. Based on the concept of rough sets introduced by Pawlak, LEM3 is capable of learning rules from consistent as well as inconsistent examples. In LEM3, rules are generated by using the rule-generating procedure implemented in a nonincremental learning program LEM2. Consequently, the rules learned by LEM3 do not use redundant attribute-value pairs. One major feature of LEM3 is the incorporation of a separate global data structure for storing information learned from new examples. The global data structure is updated on an example by example basis, and it provides all the essential information for the incremental updating of lower and upper approximations of a concept and the generating of rules. This separation of learned knowledge from rule-generating procedures provides a more modular design of learning systems.

Literature review

With the advancement of Web technology, hypermedia learning systems are becoming more widespread in educational settings. Hypermedia learning systems present course content with non-sequential formats, so students are required to develop learning paths by themselves. Yet, empirical evidence indicates that not all students can benefit from hypermedia learning. Research into individual differences suggests that prior knowledge has significant effects on student learning in hypermedia systems, with experts and novices showing different preferences to the use of hypermedia learning systems and requiring different levels of navigation support. It is therefore essential to develop a mechanism to help designers understand the needs of experts and novices. To address this issue, this paper presents a framework to illustrate the needs of students with different levels of prior knowledge by analyzing the findings of previous research. The overall aim of this framework is to integrate students’ prior knowledge into the design of hypermedia learning systems. Finally, implications for the design of hypermedia learning systems are discussed.

High-tech instructional development: It's the thought that counts

Predictions that technology will soon bring about a revolution in teaching are now common. Some see this occurring as an inevitable result of the information storage and processing capabilities that new technologies possess; others believe that changes in values and technology application strategies will be more significant factors. This article argues that technologies affect education greatly by shaping attitudes about the nature of teaching and learning, and presents a simple model to illustrate this process. Also, it suggests that, to be effective advocates of the new technology, instructional developers must address the ideological dimensions of learning system design and make deliberate decisions regarding the educational values these designs are to embody.

A model of integrated learning

Research in integrated learning is concerned with designing learning systems that combine empirical (inductive) and analytical (deductive) approaches to learning. A model of integrated learning is proposed, and is illustrated with a detailed case study from the field of epidemiology. An algorithm called Negative Instance Elimination algorithm is presented. We show that it is orthogonal to the well-known Candidate Elimination algorithm, i.e. the former is based on a set of assumptions similar to the letter, except that the roles of features and instances are interchanged.

Principles of intelligent learning systems design

One of the possible system approaches to the construction of artificial intelligence (AI) systems is described in this paper. The approach integrates three well-known AI trends: heuristic programming, structural modelling and simulated evolution. The structure of an experimental learning system ELS Y is described. The system is designed in accordance with the proposed principles. The main feature of the system is a dynamic generation of AIS architectures on the basis of means-ends analysis method. An AIS architecture can be subjected to mutation in order to obtain a more intelligent one. Every AI system is capable of self-organization on two levels: the first one formed with an associative computing memory, and the second one with arrangement of knowledge structures.

The ART of adaptive pattern recognition by a self-organizing neural network

The adaptive resonance theory (ART) suggests a solution to the stability-plasticity dilemma facing designers of learning systems, namely how to design a learning system that will remain plastic, or adaptive, in response to significant events and yet remain stable in response to irrelevant events. ART architectures are discussed that are neural networks that self-organize stable recognition codes in real time in response to arbitrary sequences of input patterns. Within such an ART architecture, the process of adaptive pattern recognition is a special case of the more general cognitive process of hypothesis discovery, testing, search, classification, and learning. This property opens up the possibility of applying ART systems to more general problems of adaptively processing large abstract information sources and databases. The main computational properties of these ART architectures are outlined and contrasted with those of alternative learning and recognition systems.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Champions of open learning

The Council for Educational Technology is the central organisation in the UK for the application and development of education and training. CET interprets the term educational technology as being concerned in the broadest sense with the design of learning systems, drawing upon all the available methods, resources and communications media, and integrating them effectively with established teaching techniques.

Systems Planning for Environmental Education

The development of citizen capacity to function from a systems perspective on major public issues is needed to combat the "politics of selfishness' as practiced through single-issue political action groups. Environmental education offers an opportunity to develop citizenship functions through the challenge set forth in the Environmental Education Act of 1970. Systems methodologies have been developed that offer the possibility of citizen learning and doing through participative effort. Examples of the use of various systems methodologies relate to defining environmental education, exploring core themes for use in environmental education, classroom learning, and acceptance in field testing of methodology. Design of a regional environmental learning system (RELS) offers another opportunity to apply systems methodology. A general methodology for conceptual design of systems can be readily applied to public design of environmental learning systems.

Towards a Model of Learner Variation in Autonomous Foreign Language Learning

My intent in this short piece is to provide a context for consideration of learner variables in foreign language learning. I first propose a question set outlining the major issues, as I see them, arising in the design of learner-based foreign language learning systems. I then present a simplified three-part design model comprising knowledge considerations (language needs assessment), instructional considerations (learning access alternatives) and learner considerations (characteristics of learners). A review of some recent work in the first two of these prefaces the discussion of the third, learner considerations. A brief state of the art report on research in learner variables is followed by some speculation on next directions in the determination and description of learner variables within a general design model for learning foreign languages.

Evaluation of Learning, Performance, and Productivity

This presentation informally explores some of the requirements for understanding evaluation goals and techniques in designing learning systems. It attempts to further clarify what is meant by the term or title of “applied learning technologist.” The theme is approached in layman's terms, concentrating on the need for validating both the “learning” requirements and the corresponding “learning system” design. Suggested contents of a curricula for an “applied learning technologist” certificate program are discussed. The results of a survey questionnaire distributed at the presentation are summarized at the end of the paper (see Appendix).

AN EXPOSITION OF THE CONCEPT OF LIFELONG SELF‐EDUCATION

Education has been conceived as a continuing lifelong activity that is important for increasing the quality of life. The changing population structure of the world will present us with a variety of social and economic problems, including the design of educational or learning systems throughout adult development and aging. This paper discusses the concept of self‐education as it applies to the utility of continuing educational opportunities in age‐graded societies.

Book Review: Learning System Design: An Approach to the Improvement of Instruction

Book Review: Learning System Design: An Approach to the Improvement of Instruction

A Learning Technology Curriculum: The First Step

The concepts of learning technology are based on several decades of research and demonstration. A formal curriculum to train people to enter this field, however, does not exist. To initiate the development of such a course of study a conference was held at American University on March 11 and 12, 1975. This meeting, sponsored by American University and the Society for Applied Learning Technology, brought together a group of experts in this field with experience in both theoretical concepts and general applications. Topics covered included the following: performance architecture; instructional delivery methods and management; learning systems design; and, the cost and economics of various approaches to learning technology. Most concepts were illustrated with a number of current applications. As a result of the meeting it was recommended that a learning technology curriculum be specified, broadly consisting of the following categories: 1) a section on performance architecture or systems design, 2) a grouping devoted to instructional delivery methods, 3) a treatment of costs and economics, and 4) a series of case studies for training in the problem solving process.

Computer science seminars on pedagogical techniques and methods for evaluation

Interdisciplinary subject matter appropriate for computer professionals who will participate in the design of computer-based learning systems is discussed. Broad issues of computer-managed instruction are mentioned, but the potential contribution of computer techniques is assumed to be much greater in the direct use of computers in instruction and this type of use is emphasized. Primarily, computer Professionals should be prepared to suggest techniques that will permit more imaginative uses of computers than those appropriate for workbooks or memory drums. Promising pedagogical techniques derived from a variety of disciplines and used successfully in computer-based learning systems are discussed. These techniques are roughly classified as drill and practice, tutoring, and dialogue on one dimension and as simulation, gaming, optimization, and student control on another dimension. The interdependence of these pedagogical techniques with evaluations of instructional effectiveness and with computer techniques associated with timesharing, formal language processing, natural language processing, information structuring, and varieties of terminal devices is emphasized and explicated.

System Optimization via Learning and Adaptation †

ABSTRACT This paper presents an approach to the design of adaptive and learning systems for achieving optimal control. The design procedure makes use of decision theory and dynamic programming. The system up-dates the knowledge of the probability density function on the basis of the observed information pattern, The fresh information which is learned during each stage is used in performing the optimization process.