QJER logo 2
[ Contents Vol 8, 1992 ] [ QJER Home ]

Object categorisation and concept development of adult learners

P.A. Danaher
Senior Research Officer in Education
and

K. N. Purnell
Coordinator of the Graduate Diploma of Teaching
University of Central Queensland


INTRODUCTION

In late 1990, Linda Gilmore reported in the Queensland Researcher on an object categorisation exercise which she had conducted. Gilmore examined concept development with a limited sample size of nine people. Three subjects were from each of three age groups - seven to 10 years, 13 to 15 years and young adults. They were asked to arrange 30 objects into 'groups of things that go together'. From the results, Gilmore made several inferences about concept development in the three age groups, then suggested some implications for the teaching of concepts. Gilmore (p.54) suggested that future studies in this area should be undertaken with a larger sample to 'supply further valuable information" and acknowledged the possible effects of her sample size, stating that 'the results must be viewed with caution'.

Gilmore (1990) draws several conclusions about adult learners from her study with a sample size of only three subjects. This paper reports on the same object categorisation exercise undertaken this time with adult learners only. One hundred and three students from the first year Bachelor of Teaching course at the University of Central Queensland were involved in this study.

RELATED LITERATURE

As noted, Gilmore's 1990 work is central to the present study as we endeavoured to extend her work using adult learners. Gilmore found that, of the three groups she studied, the adult group experienced most difficulty with the task of categorising the 30 objects. Two of the three subjects in the adult group employed the criterion of function, while the other used materials. One adult formed one large group of nearly half the objects, on the basis that they were simply all 'odds and ends', expressing an inability to form any other connections between items. Each adult was, however, left with one or more single items that could not be grouped which may, as Wallach and Kogan (1966) suggested, represent a failure in conceptualisation. Children and adults tended to form one or two quite large groups of objects, along with (in the case of adults) up to three single ungrouped objects. The adults identified the main criterial attributes of objects such as function and material, without being influenced by their physical/ perceptual properties. Gilmore (p.52) hypothesised that concepts may be built on experience and since adults have usually had greater experience with the use of objects they focused on functional criteria.

Bowden and Hancock (1983) applied the model of human development expounded by Egan and Cowan (1979) to young adult learners (between the ages of 23 and 30) and presented case studies of two mature age students. They reiterated their conviction that learning is best approached by regarding the learner as a whole person, rather than isolating the learning situation, and they concluded that tertiary teachers need to adjust to the personalities of life cycle stages of their students. Their study provides a possible explanation of the considerable variety of responses to the exercise reported here: students may be at different stages of their life cycles, which could account for the differences in their categorisation of objects.

Harvey, Hunt and Schroder (1961) define learning in terms of how concepts are acquired, or the relational processing of information. The middle two stages of their cognitive stage model - most relevant to this discussion - describe the learner as increasingly examining herself or himself with less dependence on external causality or concrete rules. The greater capacity to separate self and externality is tied to a growing level of abstractness in conceptual thinking. This presumed connection between self awareness and conceptual abstractness suggests that students with greater self knowledge in the study presented in this paper are more likely to display a higher level of abstractness in their categorisation of the objects, an hypothesis which cannot be tested with the present methodology.

Kolb (1980) cites several items in the literature to report that university faculties devoted to the 'social professions', such as education, social work and law, tend to favour active/applied rather than reflective/pure, and concrete rather than abstract learners, and that the most successful students in those disciplines are generally those with the equivalent learning style Although this study did not seek to relate the Bachelor of Teaching students' preferences in object categorisation to their presumed learning styles, the same exercise carried out by beginning applied science, arts, engineering and health science students might yield interesting comparisons. Two qualifications are that diversity among and across groups is as likely as conformity to a small number of patterns, and that the possibility of students enrolling in courses for which their learning styles are unsuited needs consideration.

The British educational psychologist Salmon (1989) argues that the notion of personal stance (defined broadly as 'the positions which each of us takes up in life' [p.231]) in learning has implications for teachers as well as learners. She suggests that, while learning may involve the provisional 'trying out' of a new stance, '... teaching entails the public living out, wittingly or unwittingly, of what such stances may mean personally' (p.240). This is a useful reminder that the diversity of concept development, as illustrated by the variety in object categorisation reported here, should be celebrated rather than lamented, because it indicates that personally empowering experiential learning may be taking place.

METHOD

Subjects

The students who participated in this study were of good to very good reading ability. One hundred and three students studying Social Studies in the first year of the Bachelor of Teaching course at the University took part. Three groups were identified based upon age - those students in their teens, 20 to 29 years of age and 30 years of age and over. This allowed us to test for any differences in object categorisation between various age levels - something which Gilmore (1990) had found to be a significant variable.

Design and materials

In this study, each student was asked to perform the same task of object categorisation. In their five tutorial groups they were presented with the table listing the objects for categorisation on a screen using an overhead projector. Students recorded their answers on a blank sheet of paper. For consistency, the list was the same as Gilmore's (1990, p.49); it is shown in Table 1.

Table 1: Objects for categorisation

1.tea in a packet16.shell
2.medicine glass17.pencil
3.key18.blue plastic bag
4.hook19.rubber
5.button20.round coaster
6.screw21.metal spoon
7.cork22.plastic drink stirrer
8.blue comb23.blue bottle top
9.batter24.white dice
10.small book25.metal hair clip
11.postcard26.rock
12.toy man27.toy car
13.toy block28.small bottle
14.packet tablets29.photo in frame
15.white string30.glass ornament

Procedure

There were five tutorial groups for these students. When all the students entered the room and were seated, they were asked to sort the 30 objects into 'groups of things that go together'. This was also written on the top of the overhead transparency: 'Sort these 30 objects into things that go together'. Each tutorial group was given sufficient time for each student to complete the exercise - approximately 10 minutes. Once all the students had completed their categorisation of the 30 objects, the paper they wrote their lists on was collected.

RESULTS

Many students used more than one criterion for categorising the 30 objects into groups. Observation of Table 2 suggests that there are few differences between the three age groups on the proportion of students using a particular category for grouping the objects. Statistical analysis of the data (using analysis of variance procedures) supported this observation and the comparison between the three age levels and the categories students used for the objects did not reach significance [F(2,204) = 0.03, p > .05]. The data in figure 1 indicate that there was little difference between the three age groups in the average number of objects they put in each category. This observation was supported by statistical analysis - there was no significant difference between the three age levels on the average number of categories of objects [F(2,102) = 0.08, p > .05].

Table 2: Grouping categories used by the students

Category% of age group
Teens20-2930+
Shape1.40.00.0
Size6.92.50.0
Material15.122.519.1
Colour10.37.59.5
Function36.340.052.4
Other30.127.519.1
Total100100100

Figure 1

Figure 1: Average number of categories used for the three age levels showing standard error bars

IMPLICATIONS FOR TEACHER EDUCATION COURSES

As in Gilmore's (1990) study, our students found the task of categorising the 30 objects challenging and had difficulty with the task as they expressed verbally after the exercise. Their efforts, like those of Gilmore's subjects, had largely focused on developing 'neat' categories where the objects fitted together easily and none were left over. Unlike Gilmore, we found that about one-third of our students tried to use one criterion to categorise the objects. The others, as in Gilmore's study, used two or more criteria to categorise the objects. This suggests that even among adult learners there are differences where some use a 'one track approach' in their thinking while others perhaps think more diversely. This also suggests significant differences in concept development amongst the students involved in this study - an issue that needs to be addressed in higher education courses generally and teacher education courses particularly.

Concept development is a crucial process in learning: it is associated with knowledge acquisition, skill formation and attitude reinforcement, and it presents a means of gauging progress in learning. Object categorisation may provide an indication about the stage of concept development of a particular learner, although the nature of the link is not clearly established. Certainly asking prospective teachers to engage in this exercise gives them information about their approach to object categorisation and hence their current level of concept development. It also acquaints them with a procedure which they can follow with their own students and alerts them to object categorisation as a useful means of investigating concept development. However, generalisations about particular age groups reaching certain levels of concept development are unlikely to be very helpful, in view of the variety of approaches and their non-correlation with age revealed in this study. Recognition of this finding puts in perspective Gilmore's citation (1990, p.53) of Stones' comments on the teaching of concepts (1979).

CONCLUSION

Gilmore's generalisations about object categorisation and concept development of adult learners on the basis of three subjects have been supported to some extent by this study using a much larger sample. This certainly highlights the need for reliable and valid statistical samples when quasi-experimental educational research is being undertaken. It shows also the tenuous nature of suggested links between object categorisation and concept development. The warning by Ramsden, Beswick and Bowden (1986, p.162) 'against extrapolation of evidence from learning strategies and training programs carried out under experimental or quasi-experimental conditions to the everyday setting of undergraduate learning' is certainly worth noting.

Nevertheless, there is potential value in using the results of this type of research to suggest possible changes to teaching strategies and learning experiences in pre-service te acher education courses. As Gilmore (1990) suggests, teachers of adults might encourage concept development and the use of a wider range of concepts in problem solving. At the very least, this study has illustrated on a larger scale many of the issues which Gilmore identified as warranting further examination.

REFERENCES

Bowden, J.A. & Hancock, L. (1983). Living and learning as a mature-age student. Research and Development in Higher Education, 6, 241-250.

Egan, G. & Cowan, M.A. (1979). People in systems - A model for the development in the human-service professions and education. Brooks/Cole, New York.

Gilmore, L. (1990). Categorisation and concept development. Queensland Researcher, 6(3), 48-54. http://www.iier.org.au/qjer/qr6/gilmore.html

Harvey, D.J., Hunt, D.E. & Schroder, H. (1961). Conceptual systems and personality organisation. John Wiley and Sons, New York.

Kolb, D.A. (1980). Student learning styles and disciplinary learning environments: Diverse pathways for growth. In A.W. Chickering (ed). The Modern American College. Jossey-Bass, San Francisco.

Ramsden, P., Beswick, D.G. & Bowden, J.A. (1986). Effects of learning skills interventions on first year university students' learning. Human Learning, 5, 151-164.

Salmon, P. (1989). Personal stances in learning. In S.W. Weil and I. McGill (eds). Making sense of experiential learning: Diversity in theory and practice. Society for Research into Higher Education and Open University Press, Milton Keynes, 230-241.

Stones, E. (1979). Psychology of education: A pedagogical approach. Methuen, USA.

Wallach, M.A. & Kogan, N. (1965). Modes of thinking in young children. Holt, Rinehart and Winston, New York.

ACKNOWLEDGMENT

The authors are grateful to Mr Peter Hallinan, lecturer in the School of Education at the University of Central Queensland, for his helpful comments on an earlier draft of this paper.

Please cite as: Danaher, P. A. and Purnell, K. N. (1992). Object categorisation and concept development of adult learners. Queensland Researcher, 8(1), 13-20. http://www.iier.org.au/qjer/qr8/danaher.html


[ Contents Vol 8, 1992 ] [ QJER Home ]
Created 21 May 2006. Last revision: 21 May 2006.
URL: http://www.iier.org.au/qjer/qr8/danaher.html