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Cognitive Learning Research in Online Multimedia Education
Dr. Juhani E. Tuovinen
Senior Research Fellow in Interactive Multimedia
Monash University, CeLTS, Churchill, Vic. 3842
Ph 03 99026942
Fax 03 99026578
A framework incorporating multiple modalities is proposed for cognitive research into online learning interaction. Its fundamental interaction dimensions are taken to be various combinations of text, graphics, video, sound and immersive virtual reality. These dimensions are then considered at two further levels of analysis, distinguishing between 1-way and 2-way and synchronous or asynchronous interactions.
Useful ways for siting current cognitive learning research and new research directions among these framework components are proposed. Methods for improving learning of cognitively demanding content by reducing the learning cognitive load in these online contexts are derived from recent cognition research. These are goal-free problem solving, worked and completion examples practice, reducing split-attention and redundancy effects, relating the heavy use of worked and completion examples to learners' expertise, the imagination effect, using multiple modalities and identifying and employing optimal conditions for discovery learning.
The implications and scope of effective new learning approaches for online learning and opportunities for research are discussed. The current research is argued to have immediate implications for improving learning in non-online contexts, and be highly suggestive of fruitful areas of research and development in online learning environments, especially if multimedia or virtual reality are employed as interaction modalities. It is also argued that the existing cognition research provides powerful methods of planning, prioritising, developing, implementing and evaluating online learning using judicious combinations of multiple interaction modes and instructional methods.
Introduction TO INTERACTION MODALITIES FRAMEWORK
Some years ago I suggested a very basic classification of online education and training which I will use as a starting point for this presentation in a modified form.
The simplest level of online education and instruction is via text only, such as in archived gopher materials, email, etc. At the next level we may have text with graphics, such as in a typical Web page. Alternately we may have sound-only messages, such as in radio broadcasts (one-way), or telephone (two-way). We could combine text, graphics and sound, as in audiographics or Web pages, and include video, which may be synchronous or asynchronous, and allow for one-way or two-way interaction. However, if we really want to immerse a student in a learning environment, we would use virtual reality enhanced with full surround sound.
We may represent these categories as a diagram, which captures these distinctions in nine cells.
Figure 1 Online eduction and training media
However, all the above online interactions may occur in either synchronous or asynchronous manner, and may include one-way or two-way interactions. We may extend the above classification to incroporate these further dimensions as shown in Figure 2.
Figure 2 Online instructional interactions
Thus the possible categories of educational online interaction range from pure symbolic text or sound presentations in 1-way, asynchronous mode to the totally immersive Virtual Reality with sound 2-way, synchronous interactions. In this paper an attempt is made to specify where in this categorisation obvious applications may be found for the recent cognition research findings. I will also point out the research and development opportunities I see within the online educational technology and cognitive research.
Introduction to research
My educational cognition research over the last few years has been conducted in the Information Processing framework. It has drawn heavily on both Schema Theory and Expert-Novice studies. An important aspect of the Information Processing framework is to see the mind as a computer. The three basic computer concepts, input, processing and storage, in particular, have been useful in developing theories with significant learning and teaching implications.
The basic principles of this line of thinking are based on the three-store model of the human information processing system .
Figure 3 Three component model of mental processing
That is, the human mind receives information from the outside world through the senses (Input stage) which are decoded in the Sensory Memory. The information from the Sensory Memory is then processed in the Working Memory (Processing stage) and stored in the Long-term Memory (Storage). Of course the previous information stored in the long-term memory can also be drawn on, or activated by the working memory to help deal with the
processing in working memory . The processing in the working memory is what we commonly call conscious thought .
One of the most interesting and significant aspects of the human mind is the very small capacity of the working memory. In 1956 G. A. Miller coined the famous term, "the magical number seven plus or minus two" to describe the number of distinct items he thought humans could hold in the working memory at any time . Since then the exact number of items has been shown to depend on a number of factors, ranging from age, health, level of fatigue, the type of item, familiarity with the content, training, etc. . However, without doubt the capacity of the working memory to deal with distinct items is quite limited, whereas the capacity of the long-term memory is very large, in fact no clear boundary has been established for it .
There are two main mechanisms that improve the working memory operation. They are Schema Formation and Automation . If the items of information are grouped together in a meaningful way, e.g. 29011981 vs 29.01.1981 (my daughter's birthday) they become easier to remember and use as one item, called a chunk . Instead being eight separate items, they can be treated as a single entity by working memory. The structure we have used to link these numbers together, the date notation, is an example of a schema, which helps to organise and simplify mental processing.
The second mechanism is automation. By this I mean processing that is so familiar that one does not have to think about the components of the processing consciously. This is the type of processing fluent readers use when reading text, where they do not try to make out individual letters, but process larger groups, words or groups of words, without attending to individual letters or even words separately.
As one develops better schemas and automation one gains expertise in a given field. Then one is able to select and use more elaborate schemas and automated processes to avoid the bottleneck of processing in the working memory, with too many individual separate items of information leading to confusion, and poor processing, due to a mental overload.
Cognitive Load Theory
Based on this view of the human information processing a number of significant advances in improving learning have been developed under the banner of the Cognitive Load Theory . Principally the Cognitive Load Theory work has been aimed at reducing the cognitive load on the working memory during learning.
A. Reduction in extraneous cognitive load
Goal-Free Problem Solving
The first method developed from the Cognitive Load Theory is called the Goal Free Problem solving . For example in the kinematics topic in physics a small number of equations of motion under constant acceleration are taught in senior high school. After being the taught the equations of motion, the students are commonly given problems of the type:
If a body starts from rest under the action of a constant acceleration of 3 m/sec2, find the distance moved over 4 seconds.
This requires the student to manipulate the equations of motion, combining them and substituting known values for the variables until they find the value of the distance variable.
The following alternative way of presenting the same problem was tried:
If a body starts from rest under the action of a constant acceleration of 3 m/sec2, find all the things you can know about the body after it has been in motion for 4 seconds (using the equations of motion).
It was found that the second type of problem led to far more effective learning. This was called the goal-free problem solving. The reason for the improvement in learning was due to reduction in the use of less effective means-ends analysis approach involved in common problem solving. In means-ends analysis the students are comparing the current state of their problem with the final end to be reached, and trying to move closer to the final end, stage by stage. Thus they not only have to attend to the details of the problem, but also to start, end and mid stages. In the goal-free problem solving they can concentrate only on the problem itself, and the next stage only. Thus they have more working memory capacity available to develop better schemas for the material to be learned. In a sense this is a form of Discovery Learning - in fact, one of the few effective forms of discovery learning, according to my research!
However, there are limitations to the effectiveness of goal-free problem solving, thus the mechanism involved and the context where it is to be used need to be thoroughly understood before assuming it will improve learning in a particular context.
This method has been tested and found beneficial in text, and text with graphics one-way, asynchronous presentations in conven