The importance of prior knowledge to new learning

This study discusses the importance of prior knowledge in learning. It distinguishes between surface concepts and general concepts, and explains the limitations of short term memory for in depth learning. A rationale is developed for using a constructive learning context to promote long term memory.

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.

Introduction

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).

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.

The importance of prior learning

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...

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).

The critical need to develop long term memory

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)

Definitions

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).

The idea of schema

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)

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).

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.

Research methods

The students and the study design

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:

• Varied language games practiced by language communities,
• the rules of the language community by members through training, and
• a consensus of definitions, outlooks, assumptions and practices,

Language games

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).

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.

Research questions

1. What were students' subjective learning experiences?
2. How did students' conceptions of learning improve during the semester?
3. What learning outcomes were achieved under examination conditions that measured (a) concepts and (b) other content?

Data collection and data analysis

1. A survey was administered to ask students about their subjective perceptions of their learning experiences.

2. A pre-test/post test design was administered to collect data about students' conceptual understanding. Pre-testing of students was a critical element in the evaluation. The pre-test provided data about students' entering prior knowledge level understanding of profit determination, and the depth of understanding of an accounting concept. The post test provided data about students' learning.

3. The end of semester exam was used to assess student learning - this examination involved reproducing information.

Student profile

Students' background

Results

1. Students' subjective learning experiences

Students perceptions of learning

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.

Lecturer presentation
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.

2. Measurement of students' conceptions of learning

Classroom participation included the pre-post tests.

Pre-test
The following table provides students' quotation responses [see Appendix A] as follows.

The following student responses were given in respect of the comments about the quotation:

Q. What did you not understand?

1. Not really sure
2. It is not specific enough
3. I think I still need to study more
4. The part which said 'most accounting concepts are commonly referred to as conventions (3)
5. I don't know exactly what this means
6. Some people make up questions just to do a survey
7. I don't know where I should put the debit or credit for transactions
8. The typical characteristics of accounting is different so it do not really specify
9. It is easy to say what they are but not the characteristics.

Discussion

Post-test
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.

3. Students' examination results

However, students scored well on progressive assessment which included:

1. Class participation
2. Homework assignments
3. Tests (2)

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.

Conclusion

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.

Endnotes

1. See also Tobias, cited in Dochy, who agrees that a considerable amount of the variance of performance is explained by the level of prior knowledge.

2. We have relied on Hirsch, 1988 for this overview of prior knowledge in memory.

3. As Kurfiss (26) observes: 'To make its way to memory, knowledge must be acted upon by the learner. In terms of the metaphor of information processing...short term memory is the [active processing of information]. When integrated with prior learning it becomes useable knowledge...stored in long term memory...This knowledge is organized into patterns that provide a context for new information called...schemas.'

4. Cooper has given his approval for using Figure 1.

References

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

Appendix A was not available at date of creation of this HTML file.