|[ Teaching and Learning Forum 2001 ] [ Proceedings Contents ]|
The research design is based on Wittgenstein's Language Games theory, which is used as a conceptual tool to measure students' entering and outcome levels of understanding accounting concepts and information. Results of a survey of students' learning experiences and conceptions of learning improvement are provided, and results of pre/post tests are given.
Accounting accreditation requirements are important because they specify the need for students to think critically. This means that they must acquire procedural knowledge rather than declarative knowledge (Kurfiss, circa 1995), be deep thinkers, and have a clear understanding of the concepts and principles that underpin the discipline. From day one at university they must acquire concepts upon which to build this knowledge. As Bruner (1974) reminds us:
Man constructs models of his/her world, not only templates that represent what he encounters and in what context, but also ones that permit him to go beyond them. He learns the world in a way that enables him to make predictions of what comes next by matching a few milliseconds of what is now experienced to a stored model and reading the rest from the model (18).Thus the essence of learning is understanding.
This paper has two objectives. First, to examine the importance of prior knowledge in developing concepts, and second, to propose a constructive form of education that develops the conceptual schema necessary for acquiring critical thinking skills. It also reports on an experiment to teach students in a pre-university accounting course. This experiment used a pre-test post-test design to measure the change in students' prior knowledge during a semester.
Prior knowledge (PK) is defined as 'the knowledge, skills, or ability that a student brings to the learning process' (Jonassen & Gabrowski (1993). Other theorists have also provided vague definitions, using numerous terms to refer to prior knowledge [as current knowledge, world knowledge, expert knowledge and pre-knowledge]. Prior literature reviews (Alexander, Shallert & Hare, 1991; Dochy; Dochy & Alexander, 1995) have also identified the large number of terms available as a problem with the knowledge literature.
Research also indicates that there is a strong relationship between prior knowledge and performance. Because literacy is now essential to commerce and domestic life, the need to acquire good reading and writing skills is urgent. As Kurfiss (1995: 32) notes:
Reading is not simply a matter of absorbing individual words; ...it is a progressive effort to construct a "model of the meaning of the test" (Armbuster, 1984)...Effective readers remain absorbed by texts... poor readers often do not recognize their own failure to understand a word or passage...This research confirms Resnick's (1981) results that showed that prior knowledge explained a greater amount of variance than any other variable [i]. Investigations using causal modelling techniques also support the importance of prior knowledge. Most studies considered the direct effects, but there are other learning variables related to prior knowledge that are essential for student performance. These include accessibility and availability of information and the structure of prior knowledge. In addition, methods of assessment have been shown to influence the observed effect of prior knowledge on performance. However, misconceptions and inconsistent information has hindered this research.
An important message is that the positive effects of prior knowledge are apparent when objective methods are employed. However, while, superficial methods like familiarity ratings have consistently failed to show a clear relationship between prior knowledge and learning outcomes, a closer examination of these studies often reveals that flawed assessment methods are useful for exploring learning processes that provide explanations for the prior knowledge effect. Thus determining prior knowledge levels should be a primary consideration in designing studies and assessing performance.
Research also highlights the paradoxical nature of prior knowledge: inaccurate knowledge hinders students' development, and lack of it makes it impossible for them to progress (Pintrich, 1993). On the other hand, addressing misconceptions through instruction and alerting students beforehand that new knowledge may be inconsistent with what they already know, helps them to learn (Biemans & Simons, 1994). By contrast, prior knowledge plays a mediating role in generating constructive activity (Chan et al., 1992), and the quality of study materials can affect a student's prior knowledge and indirectly his/her performance (Dochy, 1992). Research also shows that prior knowledge is potentially an important contributing variable in explaining post-test variance (Dochy, 1992).
Following Miller's (1956) discovery that short term memory lasts for milliseconds but that long term memory lasts from a few seconds to a lifetime, Fillenbaum and Sachs (1966) discovered that people have poor memory for words, but good memory for meaning. Barclay, Bransford and Franks (1972) discovered that initial understanding of a text depends on applying relevant prior knowledge that is not in the text. The constructive hypothesis as it is known, indicates how important prior knowledge is for supplying the meaning of a text. People's experiences are interpreted in classifications that are neither specific nor general if no other constraints are at work [ii]. How can this be so? Once a long piece of text has been remembered the elements are combined into 'chunks' or smaller elements. There's no logic or reasoning behind the exercise: it is a strategy for remembering.
This strategy for remembering is based on the distinction between sensory, working or short term, and long term memory. Together these modes of remembering are integrated to define an information processing model of the human cognitive architecture. A model of this architecture is shown in Figure 1.
Figure 1. Source: Cooper G, (1998:7)
Short term or working memory, provides one's consciousness. Its key characteristic is that it helps us to process information by relating how and where one thinks and processes information.
Perhaps the most pervasive feature of human intellect is the limited capacity at any moment for dealing with information. There is a rule that states that we have about seven slots, plus or minus two, through which the external world can find translation into experience. We easily become overwhelmed by complexity or clutter (Bruner, 1974: 18).Long term memory by contrast consists of the large amount of knowledge and skills that are held more or less in permanently accessible form (Cooper, 1998: 6). This memory is characterised by familiar knowledge like names, dates, the alphabet, heroes, playing games of all sorts, and 'other how to' information, and not so familiar knowledge. Unfamiliar or less familiar knowledge includes concepts of all types, concepts that are isomorphic and allow the possessors to think across a range of disciplines and to see the world from many perspectives. Thus we observe that some knowledge and skills are activated automatically: others less so. Students search their long term memory to establish whether they 'know' or 'don't know.' This is why prior knowledge is crucial.
To pursue the practical importance of this fact let us explain how schemata works. The first breakthrough came when in 1922 Schultz identified the tendency to 'schematize' (Hirsch, 1988: 55) and second, ten years later, when Bartlett showed that everyone constructs memories from their habitual schemata. Bartlett claims that:
An individual does not normally take a situation detail by detail and meticulously build up the whole....Very little of his construction is literally observed. But it is the sort of construction which serves to justify his general impression (cited in Hirsch, 1988: 55)A schema is a hierarchical information network: its centrality in learning cannot be overstated. It holds the detail and the complexity learned and understood over time, and integrates new content knowledge. The question is, How does knowledge and skill become encoded and stored in long term memory? [iii].
According to Bruner (1974), there are many devices: theories, models, myths, cause and effect accounts, ways of looking and seeing, and ways of thinking. The focus of this paper is on the theory - the concepts or connected collection of concepts that are the means of acquiring a lot within a 'chip.'
A theory avoids the clutter that surrounds explanation and facilitates understanding. It has the advantage of being compact, accessible, and manipulable. This hierarchy includes knowledge, some of which is more significant than the rest, for knowing about some aspect of nature and life. This knowledge is significant because once a student knows it, and has a theory and procedures for putting it together and going beyond it, he/she can reconstruct the less significant knowledge and other aspects that make up the body of knowledge.
[These] models or stored theories of the world that are so useful in inference are strikingly generic and reflect man's ubiquitous tendency to categorize....We organize experience to represent not only the particulars not only the classes of events that have been experienced but the classes of events of which particulars are exemplars (Bruner, 1976: 19).Theory is thus a way of stating tersely what one really knows without the burden of detail: it is a canny and economical means of keeping vast amounts in mind without having to think about much. This view dates back to Whitehead (1932).
Key elements in learning are first, the interactivity of prior knowledge with the knowledge to be learned, and second [iv], the degree of interactivity required (Cooper, 1998: 14). The higher the interactivity the more difficult the learning. For example, Cooper provides an example of building sentences:
To build sentences that are grammatically correct...one must attend to all the words in the sentence at once while also considering the syntax, tense, verb endings and so on. Grammar is an example of a high element interactive material because to learn it, many elements have to be considered simultaneously.It is a form of personalising knowledge, explained by Bruner (81) as the act of making the familiar an instance of a more general case, and thereby achieving awareness of it.
According to Ausubel, the cognitive structure is hierarchically organised in terms of highly inclusive conceptual traces [past experiences] under which are subsumed past experiences of less inclusive concepts. The major organising principle of these trace elements is progressive differentiation, in which concepts range from greater to lesser inclusiveness 'each linked to the next higher step in the hierarchy through a process of subsumption' (Ausubel, 1968: 25, cited in Addison, 1982). Thus he postulates that learning occurs when potentially meaningful material is absorbed into the cognitive structure and becomes subsumed under a conceptual system which is both relevant and more inclusive. Thus information is given to students and managed by ensuring that subsumers called 'advanced organisers' are given to students.
We decided on Wittgenstein's (1957) description of concept formation as a game because it is a light hearted approach and achieves results. It is used here to underpin the proposed epistemological approach. The essence of Wittgenstein's philosophy is that language consists of:
Think of the tools in a tool chest. There is the hammer, pliers, a saw, a screwdriver, a ruler, a glue jar, nails and screws. The function of the words is as varied as the functions of these objects - there are also similarities (Wittgenstein, 1957:11, cited in Grayling, 1988).He defines forms of life as those assumptions, practices, traditions, and natural propensities that humans, as social beings share with one another, and which is therefore presupposed in the language they use. As such language is woven into a pattern by the shared outlook and nature of its users. Thus, learning the language of accounting is learning the outlook, the assumptions, and the practices with which the language is inseparably bound and by which its expressions acquire meaning.
Wittgenstein's concept formation consists of a form of mental map. The map requires students to identify a list of concepts for a particular word. Hirsch (1988) used a canary, Cooper (1998) a car. The concepts we chose are given in Appendix A. Our objective was to determine how and whether students were using surface [specialised] or abstract [general] concepts. We defined surface learning as declarative, or rote type learning: "Declarative knowledge [is] acquired through memorization...[such] knowledge is not helpful in solving problems" (Kurfiss: 34). We defined abstract learning as procedural knowledge or doing type learning: "Procedural knowledge is relevant to critical thinking [and] includes knowledge of how information is obtained, analyzed and communicated in a discipline" (Kurfiss: 40).
We also asked students to interpret a five line passage relating to the determination of profit, the objective being to gauge whether they understood what they had learned so far.
The purpose of the experiment was to free students of a surface approach to learning and to promote a constructive learning context. The idea was that students should think rather than rote learn, and be actively engaged with the information they had to study. The tasks we set did not allow them to use textbooks.
|Number of students||Female||Male|
|Educational background||High School Cert.||No High School Cert.|
Objectives of the course
The results in Table 2 indicate that for these items, students were reasonably happy. They also indicate that there were no significant differences between groups.
Assignments and Assessment
The results shown in Table 3 also indicate that all students were satisfied with the assignment and assessment procedures adopted for the course.
Perceptions of lecturer presentation shown in Table 4 were all above 4 out of 5, with the exception of Question 5 for Group 1, which had a mean of 3.7895.
The results of the survey suggest that students were happy with the way the course was conducted and the care and attention given by their teacher.
|Progressive assessment||1. 2 x 1 hour tests||30 marks|
|Classroom participation||10 marks|
|Final examination||50 marks|
Classroom participation included the pre-post tests.
The following table provides students' quotation responses [see Appendix A] as follows.
|*Some students were missing on the day|
The following student responses were given in respect of the comments about the quotation:
Q. What did you not understand?
Five weeks later students were tested again to determine their progress. They were asked to define asset, and to draw a concept map to demonstrate their understanding of an asset. The expectation was that they would define asset in terms of the Statement of Accounting Concept Statement (SAC) 4 definition. Very few did so. We are at a loss to understand why this is so, given that part of their tutorial was concerned with accounting concepts and related theory. Some students did try. Others fell back on specific instances like car, and other related sub-concepts. One possible explanation is that students had English difficulties and did not read the text book. They had been given lecture notes and could have relied on them. Another explanation might be that these students were dismotivated, or had difficulty in settling into their new surroundings. Answers to these questions may be gleaned by the results of the survey of their learning experiences. Whatever the answer, it is clear that the course will have to be tailored more closely to their needs. The results of the post-test were very poor. The mean score for the post-test was 1.64 out of a range of 6.
However, students scored well on progressive assessment which included:
The textbook used for the course may not have been ideal for the teaching of theory. Students' understanding of theory is deficient. We noted on page seven that theory avoids the clutter that surrounds explanation and facilitates understanding. Theoretical knowledge is critical because once a student encodes it, he or she can reconstruct less significant knowledge and other aspects that make up the body of knowledge. It is significant that students learned one particular aspect, cash budgeting (Question 2 in the examination) far better than any other aspect, and their results were significantly higher than for other questions. Cash budgeting is a topic that can be learned in isolation, requiring less prior knowledge than needed for the presentation of a profit and loss statement (Question 3).
Unfortunately, students' knowledge was not personalised and they were not able to move from a familiar instance to a general case.
The results concerning intra-individual development are disappointing. The diffuse factor structure may be explained by a settling in period of 'friction' as students had to adapt to a new learning environment.
Adler, M. J. (1988). Reforming Education: The Opening of the American Mind. Ed. Van Doren, G. New York: Macmillan Publishing Co.
Alexander, P. A., Schallert, D. L. & Hare, V. C. (1991). Coming to terms: How researchers in learning and literacy talk about knowledge. Review of Educational Research, 61, 315-343.
Ausubel, D. P. (1968). Educational Psychology: A Cognitive View. Holt Rinehart and Winston, New York.
Biemans, H. J. A. & Simons, P. R. J. (1994). How to use preconceptions: The contact strategy dismantled. University of Nijmegen: Department of Educational Sciences
Bruner, J. (1974). Relevance of Education. Great Britain: Penguin Education.
Chan, C. K. K., Burtis, P. J., Scardamalia, M. & Bereiter, C. (1992). Constructive activity in learning from text. American Educational Research Journal, 29(1), 97-118.
Cooper, G. (1998, March). An Introduction to applications of Cognitive Load Theory to Instructional Design. A presentation at the Education 1998 Conference.
Cooper, G. & Sweller, J. (1987). Effects of schema acquisition and rule automation on mathematical problem solving transfer. Journal of Educational Psychology, 79, 347-362.
Dewey, J. (1916). Democracy and Education. New York: Free Press Paperback.
Dochy, F. (1992). Assessment of prior knowledge as a determinant for future learning. Ultrecht, London: Lemma BV/Kingsley Publishers.
Dochy, F. & Alexander, P. A. (1995). Mapping prior knowledge: A framework for discussion among researchers. European Journal of Psychology of Education, 10(3), 225-242.
Dochy, F, Segers, M. & Buehl, M. (1999). The relation between assessment practices and outcomes of studies: The case of research on prior knowledge. Review of Educational Research, 69(2), 145-186.
Grayling, A. (1988). Past Masters: Wittgenstein. London, Oxford University Press.
Hirsch, E. (1988). Cultural literacy: What every American needs to know. US: Vintage Books.
Jonassen, J. H. & Grabowski, B. L. (1993). Handbook of Individual Differences, learning and instruction. Part VII, Prior knowledge. Hillsdale: Lawrence Erlbaum Associates.
Kurfiss, J (1995). Critical Thinking: Theory, Research, Practice, and Possibilities. Washington: ASHE-ERIC Higher Education Report, 17(2): 1-154.
Larkin, H., Chandler, P., & Sweller, J. (date unknown). The role of Visual Indicators in Dual Sensory Mode Instruction. Educational Psychology.
Pintrich, P. R., Marx, R. W., & Boyle, R. A. (1993). Beyond cold conceptual change: The role of motivation beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63, 167-199.
Resnick, L. B. (1981). Instructional psychology. Annual Review Psychology, 32, 659-704.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257-285.
Wittgenstein, L. (1922). Tractatus Logico-Philosophicus. London, Routledge and Kegan Paul.
Wittgenstein, L. (1957). Philosophical Investigations. Translated by G. E. M. Anscombe. Oxford: Blackwell.
Appendix A was not available at date of creation of this HTML file.
|Authors: P. A. Addison and V. K. Hutcheson|
School of Accounting
Curtin University of Technology
GPO Box U1987, Perth WA 6845
Auhor for correspondence: P. A. Addison
firstname.lastname@example.org Phone: (08) 9266 7567
Please cite as: Addison, P. A. and Hutcheson, V. K. (2001). The importance of prior knowledge to new learning. In A. Herrmann and M. M. Kulski (Eds), Expanding Horizons in Teaching and Learning. Proceedings of the 10th Annual Teaching Learning Forum, 7-9 February 2001. Perth: Curtin University of Technology. http://lsn.curtin.edu.au/tlf/tlf2001/addison.html