Author: Denis Lander

Royel Melbourne Institute of Technology

Keywords: online learning, interactivity, visualisations, labs, demonstrations, simulations, concept mapping.

Article style and source: Peer reviewed. Original ultiBASE publication.

Contents

• Abstract
• Introduction
• Examples of Interactive Online Learning Activities
• Demonstrations and Visualisations
• Simulations and Lab Studies
• Problem Solving
• Concept Mapping and Model Building
• Investigations
• Asynchronous Discussions, Debates and e-Seminars
• Case Study: An Online Psychology Lab Supporting Classroom Learning
• References

Abstract

Introduction

It is now widely recognised that the effectiveness of online learning tasks depends on the way they generate interaction. As Barker (1994) has put it, interactivity is a "necessary and fundamental mechanism for knowledge acquisition" and Mesher (1999) claims interactivity is the "key to successful online learning." However, it is not quite so obvious exactly what sorts of interaction are most effective. Interaction can occur at different levels and in different ways. McLoughlin & Oliver (1995) have pointed out that the terms "interaction and interactive are now ubiquitous," as indicated by the acronym IMM (for Interactive MultiMedia), but the intention is often not matched by the result, as indicated by the study of Yeo et al (1998) which found that students did not use its interactive possibilities or even follow instructions in some instances. There are two sorts of interaction to consider; social and cognitive interaction. Obviously, online learning will be most effective when these are integrated. An example of a pedagogical approach that incorporates both social and cognitive forms of interaction is given by Schneiderman (1998) who uses collaborative team projects that result in publication of valuable, peer-critiqued, products under the rubric "Relate-Create-Donate." While social interaction raises important issues, particularly how to compensate for its reduction in online learning, it is not dealt with in any detail here. Rather the chief focus of this article is on interactions in the cognitive domain.

The effects of interactions between the learner and tasks at a cognitive level can, in many cases, be richer and more effective in online than face-to-face situations. It is here that the computer comes into its own, allowing interactions in the virtual situation that are not always attainable in real life. A number of features of interaction in online situations have been pointed out. Oliver, Omari & Ring (1998) emphasise learner control and engagement that involves making decisions and learning from their consequences. Schaverien & Cosgrove (1997) present a theory of learning based on a "generate-test-regenerate" interaction heuristic similar to the notion of the brain as a Darwin machine (Plotkin, 1994). McLoughlin & Oliver (1995) argue for interaction in the sense of giving the learner control over the "pace, sequence and form of the instruction." Phillips (1998) summarises four models of learning that have been applied to online delivery, all of which incorporate interaction in some way. It may also be noted that, through interaction, online learning tasks can be used to generate the 'variation' in experience identified by Bowden & Marton (1998) as critical in many forms of learning. top

Examples of Interactive Online Learning Activities

Because I teach Psychology, most of the examples are drawn from that field. However, the principles involved should apply quite widely. In all cases, the resources are put online but they must be activated and operated by participants. Giving control to the user in this way incorporates some of the interactive features discussed above. They are like games in that they call for responses and generally give feedback to the user. They differ from games in that their content is not arbitrary but emulates concepts in the field of study and the way these are understood. top

Demonstrations and Visualisations

Computers provide powerful tools for visualising complex information in ways that make it more understandable or useful. An example is the Visible Human Project of the National Library of Medicine in the U.S. This provides a database of a complete set of cross-sectional images of a human male cadaver, soon to be followed by those of a female. This is a large professional database, not just a learning tool. However, concepts can often be demonstrated economically with quite simple graphics or programs on web pages. For example, in the field of perception there are excellent sites on visual and auditory illusions. A view of the world through the eye of a bee (B-EYE) is another example. An advantage of these is that they allow the user to see the effects of altering parameters. This can also be seen in a site on colour perception (click and drag the cursor across the reflectance graphs). There are numerous sites that illustrate Single Image Random Dot Stereograms (SIRDS). Some of these deal with the theory behind stereoscopic vision and show the user how SIRDS can be constructed. Other examples of demonstrations (of the Blind Spot, the Stroop Effect and Illusory Contours) can be seen on my web site. With nothing more than simple graphics, these enable the user to test their own responses. More sophisticated visualisations can be seen in the projects of the Knowledge Media Institute (Kmi)

A rather different sort of demonstration is of an 'expert system' named ELIZA. This gives responses to the user's questions or comments in the manner of a counsellor, albeit a rather simple-minded one. top

Simulations and Lab Studies

Some of the most interesting current interactive applications are simulations. Among the earliest was the Virtual Frog Dissection, an example of which can be seen at a Computer-Enhanced Science Education site. Simulations are also available in genetics and earth science. In Psychology, simulations are beginning to appear which enable the user to act as a subject in experiments or actually conduct experiments themselves by manipulating variables and gathering data. I have been using a suite of psychology labs, provided by John C. Hay, with my students. One of these is detailed in the case study below. Sites which enable the user to participate in simulated or real experiments include the Online Psychology Lab, the Cognitive Psychology Online Laboratory, Experiments in the Laboratory of Social Psychology and Cognitive Experiment of the Month.Quite sophisticated simulation software (eg. STELLA) that examines such things as physical, biological, ecological and economic systems is now appearing. In general, such programs provide a platform for highly interactive learning. top

Problem Solving

Various forms of problem solving lend themselves to interactive approaches. Problem-Based Learning is a structured approach that has proved particularly popular in training for professions such as Medicine and Engineering in which problem solving is a central activity. It lends itself well to online applications (eg. an online version at San Diego State University). Other examples can be found at the Center for PBL. Less formal problem solving exercises have considerable potential for interactive activities. Roger Schank (1998) provides examples in what he refers to as Case-Based Teaching.

The importance of interaction is indicated in a study of students learning to match algebraic rules which showed better performance when they actively solved problems as opposed to studying examples the computer solved (Nguyen-Xuan et al, 1998). With conferencing software, problem solving can be collaborative and utilise information from databases. top

Concept Mapping and Model Building

Concept maps, which are useful in consolidating learning, have already been computerised (Gaines & Shaw, 1995) and have been proposed as a useful learning tool online (Jonassen et al, 1997).

A number of concept mapping software tools are now available. (eg. Inspiration & KSI Watt & Mulholland (1998) have devised a cognitive modelling language (HANK) for use by students of cognition. This is an application that deserves further exploration since it not only provides a useful learning device but also enables teachers to monitor the development of students concepts. top

Investigations and Discovery Learning approaches use a range of interactive online resources including simulations, collection and analysis of data and collaborations with other students online. Even when they are little more than routine searches, they still require an understanding of what the project is about, its goals, strategies that can be useful and decisions about the selection and relevance of information retrieved. Publication on web sites adds another dimension. These approaches are becoming increasingly popular in schools but are also appearing in college-level courses (eg. The Kentucky Team investigations and the Artic Observatory Project; Learning Space Projects; The Salmon Conflict Investigations; Institute for Learning Technology projects). top

Asynchronous Discussions, Debates and e-Seminars

The first interactive online activities were supported by e-mail and asynchronous discussions and these are still a mainstay. With increasing use of groupware, collaborative elements can be added to investigations and other activities. In addition to their uses in providing social interaction, they remain powerful tools for critique and for comparing understandings and points of view. Asynchronous discussion is often more thoughtful because it allows time for reflection, clarification or help (Brown, 1998; Mason & Hart, 1997). Following the threads of such discussions and seminars often shows how the conceptual interactions between participants shape their ideas (eg. ASSC e-seminar on affect in consciousness). top

Introductory Psychology courses typically cover a form of learning termed conditioning. There are two conditioning paradigms, Pavlovian (classical) and operant (instrumental) conditioning. For each, students need to learn quite a large set of concepts and the associated jargon, a variety of procedures and their expected outcomes, a range of theoretical issues and practical applications. Usually, one chapter of introductory texts is devoted to conditioning. Not surprisingly, what students learn of conditioning from texts is often superficial. In particular, they have difficulty in understanding certain concepts, comparing the similarities and differences between classical and operant conditioning, difficulty in predicting outcomes of conditioning procedures and in applying what they have learned. To improve learning, Psychology departments used to provide laboratory studies in conditioning. The experiences generated by these interactions were effective but time-consuming and very expensive, requiring a large investment in apparatus, animal colonies and staff to maintain them.

In an undergraduate Psychology course on campus, I have used two interactive simulations of conditioning labs available online. These are in a suite of lab simulations at a web site provided by Professor Emeritus John C. Hay at the University of Wisconsin-Milwaukee. Access requires only a web browser with a Macromedia Shockwave plugin. The labs are simple to use and enable students to produce conditioning by manipulating key variables. Despite being based on just a few programming rules, they demonstrate most of the fundamental concepts of conditioning and are rich enough to allow investigation of surprisingly sophisticated questions. Importantly, these labs are presented without the sort of contextual and instructional material a student would need to make full use of them independently. They are, then, intended as a tool for Psychology instructors to use by providing their own pedagogical process. While I have used them in the classroom rather than an online program, the way they provide an interactive medium should apply to both situations.

First, students are introduced to the concepts through a text and class discussion followed by a standard multiple-choice test. While this produces surface learning, it ensures they have at least encountered the basic technical terms and concepts. Next, one of the simulations is demonstrated and students are encouraged to ask questions and predict the effects of manipulating variables. As homework, they are given the task of locating the web site and using the simulation to answer a few basic questions about conditioning. They discuss what they found at the next class. They are then assigned a question concerning a particular conditioning concept. This requires that they design an experiment (supported by the instructor as necessary) and carry it out with the simulation. The results must be analysed and written up in a formal Psychology report. In this way, they get first-hand experience of conducting conditioning, of conceptualising questions, of using the experimental method to test them, and making sense of their findings. Since all this involves working with simulated animals, there is always the imperative to compare their results with empirical and theoretical descriptions based on studies of real animals. Finally, students have an individual assignment to formulate a further question about conditioning, conduct an experiment and present a written report. Thus, this procedure not only provides experience generated by direct interactions with the software but, also, several iterations in using the simulation, adopting the stance of the experimenter and of testing ideas relevant to their understanding of conditioning concepts. Used in this way, the interactions these virtual labs provide make them almost as rich a source of understanding as real labs. top

References

Barker, P. (1994) Designing interactive learning. In T. de Jong & L. Sarti (Eds.) Design and Production of Multimedia and Simulation-based Learning Material. Dordrecht: Kluwer Academic.

Bowden, J. & Marton, F. (1998) The University of Learning: Beyond Quality and Competence in Higher Education. London: Kogan Page.

Brown, A. (1998) Wise design for WWW courses. In B. Black and N. Stanley (Eds), Teaching and Learning in Changing Times. Proceedings of the 7th Annual Teaching Learning Forum, The University of Western Australia, February.

Gaines, B.R. & Shaw, M.L.G. (1995) Concept Maps as Hypermedia Components. Accessed 4 November, 1998.

Jonassen, D.H., Reeves, T.C., Hong, N., Harvey, D. & Peters, K. (1997) Concept Mapping as Cognitive Learning and Assessment Tools. Journal of Interactive Learning Research, 8, 289-308.

Mason, J. and Hart, G. (1997). Effective use of asynchronous virtual learning communities. Creative Collaboration in Virtual Communities Conference. University of Sydney, Sydney. February.

McLoughlin, C. & Oliver, R. (1995) Who Is In Control? Defining Interactive Learning Environments. ASCILITE95 Conference, University of Melbourne, Melbourne. December.

Mesher, D. (1999) Designing Interactivities for Internet Learning, Syllabus, 12, (No. 7).

Nguyen-Xuan, A., Bastide, A. & Nicaud, J.F (1998) Learning to match algebraic rules by solving problems and by studying examples with an intelligent learning environment. CiP98, Computers in Psychology Conference, York University, U.K., April.

Oliver, R., Omari, A. & Ring, J. (1998) Connecting and engaging learners with the WWW. In B. Black and N. Stanley (Eds), Teaching and Learning in Changing Times. Proceedings of the 7th Annual Teaching Learning Forum, The University of Western Australia, Perth. February.

Phillips, R. (1998). Models of learning appropriate to educational applications of information technology. In B. Black and N. Stanley (Eds), Teaching and Learning in Changing Times. Proceedings of the 7th Annual Teaching Learning Forum, The University of Western Australia, Perth. February.

Plotkin, H. (1994) Darwin Machines and the Nature of Knowledge. London: Penguin.

Schank, R. (1998) Engines for Educators. Accessed 3 November, 1998.

Schaverien, L. & Cosgrove, M. (1997) Computer Based Learning Environments in Teacher Education: Helping Students to think Accurately, Boldly and Critically. ASCILITE97 Conference, Curtin University of Technology, Perth. December.

Schneiderman, B. (1998) Relate-Create-Donate: A teaching/learning philosophy for the cyber-generation. EDUCOM98: EDUCAUSE Conference on Information Technology in Higher Education. University of Central Florida, Orlando, October.

Watt, S. & Mulholland, P. (1998) HANK: A cognitive modelling language for humans. CiP98, Computers in Psychology Conference, York University, U.K., April.

Yeo, S., Loss, R., Zadnik, M., Harrison, A. & Treagust, D. (1998) Interactive multimedia: What do students really learn. In B. Black and N. Stanley (Eds), Teaching and Learning in Changing Times. Proceedings of the 7th Annual Teaching Learning Forum, The University of Western Australia, Perth. February. top

About the author

Denis Lander
Department of School and Early Childhood
RMIT University
Melbourne, Victoria 4072
Australia
Telephone: +61 (0) 3 9925 7911
Fax: +61 (0) 3 9925 7860

Email: lander@rmit.EDU.AU