User Model and Modeling for Human Performance - Term Paper Example

Models of Human Performance Misconceptions: General: To err is human, but in many instances, such errors can be the direct result of misconceptions that prevent clear cognitive thinking about a problem or situation. Madhu Mahadeva offers the view that misconceptions result in myths being presented as scientific facts and these could be due to (a) the inevitability of myths because conjecture and speculation is a legitimate aspect of the scientific method and (b) the propagation of such myths by educators and society at large(www.2ucsc.edu). Luchins and Luchins suggest that misconceptions in mathematics may arise due to incorrect assumptions made by students as well as improper presentation of stimuli, while Marjory Martin points out that students face difficulties in science and especially biology, because they represent abstract ideas which escape the students’ understanding (www.2ucsc.edu). Misconceptions occur in various areas but their detrimental effects are felt most acutely in the academic field, because it interferes with the progress that students are able in the development of cognitive skills and learning. Misconceptions that occur in the field of academic studies make it difficult for students to effectively assimilate their lessons and perform well, because these misconceptions function as a barrier that impedes the cognitive assimilation and understanding of concepts. The National Curriculum Council for Great Britain has pointed out some common student misconceptions in Algebra, such as treating letters as objects or completely ignoring their presence (www.learnquebec.ca). Misconceptions in Science: Misconceptions in the field of science occur mainly because of the difficulties students face in understanding everyday phenomena through abstract or symbolic representations. In biology, misconceptions occur because students are unable to grasp the concepts which they find to be too theoretical and abstract, especially in regard to concepts such as natural selection and evolution.(Burton and Dobson, 2009). According to Joan Solomon, students may also find it difficult to assimilate concepts because they may be associated with every day use, for example the word energy, and using concepts in science requires the interpretation of everyday phenomena in abstract terms, which may also involve the use of symbols to explain commonplace events(www.2ucsc.edu). In effect, there is some contextual learning that may have already taken place before a student attends classes and it becomes necessary to ensure that the student is able to learn how to learn through the use of concept mapping, as Joseph D Novak of Cornell University has suggested. (www.2ucsc.edu) Edward(2002) points out that some of the difficulties that are experienced by science students at the undergraduate levels may be the result of an inadequate educational preparation process at the school levels. When education has been imparted in a manner such that knowledge structures which are constructed during the school years can be accessed without conscious thought, then those students will be technically intuitive. But in cases where the process of education has failed to impart such a knowledge base through controlled experimentation, then the result is often a gap in literacy and a multitude of misconceptions which to the students, appears to be common sense but is actually not. User model examples: One of the most common tools that are being used by educators to address misconceptions in science is concept mapping. This is a tool that is especially useful in biology for example, where it helps in a better assimilation of abstract concepts by giving them a pictorial form. A concept map is essentially a schematic device that represents key concepts in a hierarchical format with the more general ones at the top and the more specific concepts at the bottom with links to graphically demonstrate the links between them.(www.fed.cuhk.edu.hk). This can be very useful in helping students to understand abstract elements because it helps to transform them into a visual representation that is simple and easy to assimilate cognitively. The use of links is especially useful in helping students understand the interrelationship between the various elements, while placing the more general elements first and gradually diversifying into the more complex elements helps students to grasp the basic concepts quickly and apply them within different contexts as well. Another means to address misconceptions is through the use of simulation based activities. When such activities are used to teach students, it can enable a comparison between the student’s own physical intuition that may be based upon misconceptions and the behaviour of the model that enables a deeper and more realistic understanding of concepts. This has been found to be especially efficacious in teaching students about basic electricity, because these qualitative simulation based activities help the student to overcome misconceptions when faced with the reality of the behaviour of the model (Ronen et al, 1997). Since misconceptions generally develop contextually, the student is faced with the actual behaviour of the model in the same context and this results in a revision of the misconception. Misconception can also be addressed through learning tools that work to correct misconceptions by replacing them with new knowledge and committing it to memory through a series of repetitive tasks. One example of this kind of method of correcting misconceptions is the Old Way New Way and the Conceptual Meditation programs, where the ultimate objective is to target bad habits and wrong learning patterns that have set in and replacing them with new knowledge.(www.changetools.net) User modelling systems may be less relevant and effective in the case of misconceptions that develop in a social context. For examples, misconceptions that exist about race and gender cannot be addressed through the use of models, which may be efficacious only when an abstract complex concept needs to be simplified and presented in a form that can be assimilated cognitively. Misconceptions arising within a social context are often fashioned over years and years and are deeply inbred. They are largely the product of feelings and impressions, and prejudices that may have subsisted over generations. Since such misconceptions are subjective rather than cognitive, they may not yield to tools such as concept mapping or simulation based activities; rather they may only be addressed over a period of time, through persistent public education messages and changes within the social context. Modelling human performance: The ACT-R model is a cognitive architecture that sets out a theory about how human cognition works and is based on production rules or conditional statements. One example where this can be applied is in the field of biology, where several misconceptions exist, as in the case of photosynthesis. Some of these misconceptions are based on over simplifications, such as the assumption that only chlorophyll is required for photosynthesis or that glucose is produced as the main product of the process.(Hershey, 2004). Similarly, seedless fruits are not necessarily always the result of genetically treated plants, they generally develop due to the phenomenon of parthenopcarpy, wherein fruits develop without pollination or fertilization. In setting up a human model to correct some of these misconceptions for example, some of the production rules or conditional statements would be as follows: If a seedless fruit is produced, And parthenocarpy occurs, Then no fertilization or pollination has taken place. Another production rule or conditional statement dealing with photosynthesis for example, would be: If leaves absorb more than 50% green light And chlorophyll absorbs more red and blue light but little green light Then photosynthesis occurs. The underlying premise behind the use of conditional statements, which are called production rules in cognitive theory is that a cognitive skill is composed of conditional statements, which describe the action that should be taken or the conclusion that should be reached when a condition is met.(Hochstein, 2002). A conceptual framework for such a model may be somewhat as follows: YES The model above has been used to represent misconceptions about photosynthesis and how they can be corrected, either by encouraging declarative memory where the misconception is replaced by the actual facts or the process of building procedural memory to correct misconceptions. An assumption made in this model is that the misconceptions about photosynthesis exist because cognitive skill has not been effectively harnessed. As a result, generalizations and over simplification has produced the misconceptions about photosynthesis and seedless fruits, i.e, that chlorophyll is the green agent catalyzing photosynthesis and that seedless fruits are produced by treating them with chemicals. Predicting errors: Altering the production rules for example, could lead to errors. In the example of the model above, the production rule about chlorophyll states that if chlorophyll absorbs little green light, then photosynthesis occurs. If the production is altered such the word “little” is removed, the production rule becomes “if chlorophyll absorbs green light, then photosynthesis occurs”. This would perpetrate the existing myth that it is green chlorophyll that is responsible for photosynthesis, whereas in actuality, the reverse is true. Hence, in creating the model above, it is vital to ensure that the production rules are framed appropriately. Comparing errors with misconceptions: The model focuses upon simplification of the concepts, however this is achieved through the use of production rules, i.e, conditional statements. One way to correct the misconceptions would be by tapping into the declarative memory through presentation of the correct sentences in chunks. Through repetition of these declarative statements, i.e, (a) Seedless fruit are caused when pollination and fertilization do not occur and (b) Chlorophyll absorbs very little green light. Another way to harness the cognitive skill of the person using the model would be through production rules which are framed in a manner that avoids confusion. In the model above, a production rule sets out the conditions, i.e, (a) are the fruit seedless and (b) are the leaves absorbing more than 50% of the light? When these conditions are met, then the conclusion that must be reached or the action that must be taken is set out. When a production rule is applied, then it fires human cognition and makes it easier for an individual to remember the new knowledge, so that it is able to supersede and override the misconception. But it is only by framing the production rule correctly that the perpetration of misconceptions can be avoided. This model can also be translated into a computer program in LISP and executed so that it could set out the various misconceptions that arise in high school biology, due to generalizations and over simplifications and correct them. In the case of misconceptions existing in physics for example, conditional statements act as the spur dictating the action that must be taken. Theoretical knowledge as set out in text books may be confusing and a fertile ground for misconceptions because it is abstract and difficult for the student to see in practice. But production rules function as the catalyst for acquisition of a cognitive skill, so that the misconception is replaced by knowledge that is based upon the actual fact. Bibliography Abstracts of papers presented at the proceedings of the misconceptions in science and mathematics”, Cornell University, June 20-22, June 1983, http://www2.ucsc.edu/mlrg/proc1abstracts.html; “Algebra : Some common misconceptions”, http://www.learnquebec.ca/export/sites/learn/en/content/curriculum/mst/documents/algemisc.pdf; Burton, Stephen R and Dobson, Christopher, 2009. “Spork and Beans: Addressing evolutionary misconceptions”, The American Biology Teacher, 71(2):89-94 “Case studies in correction of misconceptions and other errors”, http://www.changetools.net/misconceptions/misconceptions-casebook.html; Edward, N.S., 2002. “Misconceptions as a cause of undergraduate difficulties and a diagnostic instrument”, Engineering Education 2002: professional Engineering Scenarios, IEE, 2: 38-46 Hershey, David R, 2004. “Avoid misconceptions when teaching about plants”, http://www.actionbioscience.org/education/hershey.html; Hochstein, Lorin, 2002. “Theories in computer human interaction”, http://www.cs.umd.edu/class/fall2002/cmsc838s/tichi/actr.html; Ronen, M and Eliahu, M, 1997. “Addressing students’ common difficulties in basic electricity by simulation based activities”, Physics Education, 32: 392-399 “Using conceptual maps to establish meaningful relationships”, http://www.fed.cuhk.edu.hk/~johnson/misconceptions/ce/learn/concept_map.htm; Read More