learning processes differentiated within the learning process complex. ... differentiation, the learning processes that do emerge are dependent upon which ...
Educational Psychology, Vol. 4, No 1, 1984
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Differentiation of Learning Processes within Ability Groups
JOHN B. BIGGS & JOHN R. KIRBY, University of Newcastle, New South Wales
ABSTRACT This paper describes a mediational model for conceptualising the relationship between individual differences and academic achievement and presents the results of a study concerning some predictions of that model. According to this model, intervening or mediating variables mediate between stable personological traits (e.g. mental abilities) and task performance. Mediating variables are thus transitory and situation-specific to some degree, and in academic tasks, are represented by the learning process complex, which consists of motives and strategies for learning. The mediational model predicts that students' information processing abilities will help determine the number and the nature of learning processes differentiated within the learning process complex. Results conform to the model's predictions, indicating that (1) as students' processing abilities increase, they show greater learning process differentiation and (2) for students intermediate in differentiation, the learning processes that do emerge are dependent upon which processing abilities they possess. These results are discussed with respect to their implication for the mediation model and for strategy instruction.
The study of individual differences in educational psychology has usually been considered in the context of determining academic performance, and it is in that general context that the present discussion is centred. Several different models conceptualising the relationship between individual differences and performance have evolved over the years.
(1) Behaviourist Model The simplest model, which in fact ignores individual differences, is that adopted by radical behaviourists (e.g. Skinner, 1953): Situation
* Performance
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Here, individual differences play no part at all. Practically, the most effective way of promoting learning is to manipulate the situation in which learning is to take place, for example by reinforcing the individual to devote maximum time to the task. This does not deny of course that individual differences exist, but merely adopts the position that increases in learning will take place due to situational manipulations, and that reference to differences between individuals are unnecessary. (2) Individual Differences Model
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This model is probably given strongest emphasis by psychologists who hold a strong hereditarian view of intelligence, such as Jensen (e.g. 1973): Individual differences
* Performance
Essentially it is held that strongest variations in performance are attributable to underlying differences in mental abilities, and that apparent environmental effects may be accounted for in terms of unequal distributions of abilities (e.g. the so-called SES effects of the Coleman Report, Coleman, 1966; Moynihan & Mosteller, 1972). Again it should be noted that such theories do not necessarily deny the effects of environmental manipulation; rather, they argue that differences between individuals will contribute substantially more to educational outcomes. (3) Aptitude X Treatment Model This model originated in attempts to combine behaviouristic-experimental research with individual differences-correlational research (Cronbach, 1967): Situation X individual differences
* Performance
The basic proposition of the model is that both environmental (treatment) and personological (aptitude or individual difference) factors are important in understanding learning. Thus different individuals may approach different situations in different ways, achieving comparable results. For example, some students may perform better following a structured course of lectures, while others perform better following discussion sessions (e.g. Hunt & Sullivan, 1974). The important aspect of this model in the present context is that the individual differences or aptitude variables are stable personological traits, such as abilities, personality types, and cognitive styles. While this model provides a more comprehensive conceptual framework, research based upon it appears plagued by two problems: (a) relatively few significant interactions are found, and even these are seldom of much magnitude; and (b) there is seldom a clear theoretical relationship among the aptitude, treatment and performance variables. (4) Mediational Model We propose that the Aptitude X Treatment model requires elaboration, specifically by the inclusion of what we term mediating or intervening variables: Situation X Individual differences
X Intervening variables
^Performance
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Intervening variables are conceived of as linking the stable individual difference variables to the task (performance) at hand. They are more situation-specific than individual differences variables, and more closely related to the particular task. Mediating variables thus describe the way the task is being handled; in the case of academic tasks, this description is in terms of the motives and strategies being brought to bear by the student upon a particular task. In the remainder of this paper we will elaborate upon this model, and provide some data upon several of the important relationships predicted by the model.
A Mediational Model An example of the mediational approach is outlined in the following model (adapted from Biggs, 1978; Biggs, in press).
FIG. 1. Mediational model of learning and study processes.
Independent variables exist prior to and independently of any particular performance and may be divided roughly into personological and situational variables. The former refer to process abilities, content abilities, personality factors, developmental stage, prior knowledge of the task and related content, and so on; and the latter to teaching method, time allowed for learning method of evaluation, and so on. Each of these factors may exert effects directly on performance, but their effect may also be mediated by particular strategies and motives. Intervening variables here refer to what has been called the 'study process complex', or more generally, the 'learning process complex'. For present purposes, this complex consists essentially of motives for learning within the academic context, and of strategies for going about that learning. These strategies may occur at varying levels of generality. Rigney (1978), for example, distinguishes detached and embedded learning strategies; the former are distant from the immediate task, and applicable to a range of tasks, while the latter are task specific. Biggs (in press) distinguishes three levels of strategy—macro, meso, and micro—but these distinctions need not concern us here. The present point is simply that students, with particular personality and home backgrounds, who are placed in particular institutions with certain courses of study to complete therein, will be motivated, for
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whatever reason, to learn a particular task. According to that motivation, they will adopt some strategies of learning rather than others, which will be more or less appropriate, according to the nature of the task. Finally, then, the performance itself needs to be considered in relation to all preceding factors. There are two main dimensions of performance: quantitative (how much has been learned), and qualitative (in what form of organisation has it been learned). The quantitative dimension is that traditionally used to assess performance; the second in some form of measurement of learning quality, such as the SOLO Taxonomy (Biggs & Collis, 1982). This distinction, between quantitative and qualitative learning outcomes, is particularly relevant to the present discussion in that different learning strategies do promote differences in both the amount learned, and in the quality of organisation of what is learned (Biggs, 1979). There has been a great deal of research at various times linking these stages with each other (summarised in Biggs, in press). (1) Independent—Dependent Direct independent to dependent variable relations are postulated in all models, exclusively so in the behaviourist and individual difference models. Some situational factors, such as time allowed for learning, clearly have a direct relation to learning outcomes (Harnischfeger & Wiley, 1976) but others may affect outcomes also via mediational processes, for example the effect of task difficulty on students' beliefs in their self-efficacy is likely to compound the direct effect of task difficulty (Bandura, 1977). Direct relationships between abilities and performance have been documented in the literature for many years (e.g. as summarised by Lavin, 1965). (2) Intervening—Dependent There is an increasing literature on connections between the intervening learning process complex and the learning outcome (see Schmeck, in press, for a useful recent review). Particularly interesting is that these relationships may be studied nomothetically (Biggs, 1979) or idiographically (Marton & Salsjo, 1976). This distinction is one that will be re-addressed later in the paper: it will be argued that the idiographic perspective on mediational processes is important in understanding the link between abilities and performance. This is so because how a student views his abilities, vis-d-vis the task, is likely to be a determinant both of how he goes about the task, and of the likely success of the outcome. (3) Independent—Intervening This last link is the major focus of this paper. We wish to concentrate on the relationship between a student's abilities, measured in the usual nomothetic paradigm, and his interpretation of the components in the learning process complex. Learning Processes and Process Abilities In this paper we focus primarily upon the question of how the personological (independent) domain acts to determine the learning processes of the intervening domain. This determination could take several qualitatively different forms. Most
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simply, task-oriented learning processes could be independent of more enduring personological variables. A second straight-forward interpretation would be that personological variables largely determine the degree to which certain learning processes may be employed; for instance, level of intelligence could determine the degree to which a meaningful approach to learning would be used. The third possibility is that the personological variables define the structure of a person's learning processes, but do not determine the degree to which particular processes are used. The distinction between these last two alternatives is a subtle but important one for the model we have proposed in the preceding section. If stable personological variables determine the learning processes to be used, and presumably their success (alternative two above), then learning processes would not be fundamentally different from personological variables. In other words, if the determinants of the learning processes are stable, and if their causal relationships with the learning processes are stable, then the learning processes themselves will be stable, and are thus better considered to be part of the independent domain. Cognitive styles (e.g. field independence, impulsivity) are examples of stable personological variables that are related to learning; they are not examples of our intervening variable category, wherein learning processes are selected with respect to given tasks. Our conception of the relationship between independent personological and intervening learning process variables is based upon the third alternative above. While it is likely that the effectiveness of certain learning processes will be circumscribed by stable personological variables (e.g. the success of a rote learning strategy would be limited by various memory abilities), those stable traits will not determine which processes are selected for a given situation. Therefore it should not be surprising if personological variables and learning processes are not highly correlated. However, it is likely that stable traits will affect the manner in which the individual defines his or her learning processes. In saying this we are conceiving of learning processes as complex amalgams of motives and strategies of which the individual is metacognitively aware to some extent. In academic tasks, for example, an individual will have access to a certain number of ways of approaching the task, and to decide implicitly or explicitly what to do. We suggest that stable personological traits, and patterns of abilities in particular, will play an important role in determining the nature and number of these learning processes. The Learning Process Complex When a student is placed in a learning situation, in effect two questions are raised: (a) What do I intend to get out of this?; (b) How do I intend to go about getting it? The first question is a matter of predominant motives: Is the learning to be instrumental in reaching some other goal; does it represent an intrinsic interest in the subject matter; or is it to allow the opportunity to manifest excellence by achieving the highest grades? A student may be motivated in multiple ways; for example to study a subject out of intrinsic interest and to achieve highest grades (if it is intended to study that subject at university then it will be necessary to do precisely that). The second question is a matter of strategies. Does the student tend to reproduce the bare essentials (the facts, details, formulae) that are estimated to be crucial in the course; or to find maximum meaning in the course, fitting the concepts to what is
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already known and trying to apply them in ways that are personally meaningful; or to obtain maximum marks by organising work so that all required readings are covered, efforts are made to tackle all the important examples, to submit assignments on time, and generally to behave like a model, high achieving student? Each of these strategies may be useful, particularly if they are congruent with the student's motives for learning. The student's motives may however be mixed. Some may want to achieve multiple outcomes, and in that case, their strategies for learning will also be mixed. Others may rote learn this aspect, try to understand that aspect, and overall, to achieve the best marks they can. Others may misjudge: they may want to try to achieve maximum grades, but adopt a fail-safe strategy that is good only for minimal passes—and if they misjudge too badly, they may fail in even that intention. A strategy may be adopted that makes too many demands on available cognitive resources, so that a student may not be capable of reaching the standards that are self-set, or set by others, such as teachers. There are, in short, as outlined in Fig. 1, many other determinants of a student's academic performance other than motives and chosen strategies: ability, the teaching methods used, the nature and difficulty of the course studied, and so on. Nevertheless, the student's motives and strategies are important, and that is the area addressed by the Learning Process Questionnaire (LPQ), which is the instrument used for operationalising the learning process complex (Biggs, Note 1). The theory underlying the LPQ was established as a result of considerable research (summarised in Biggs, 1978). Three major dimensions of students' learning or study processes have been isolated, each dimension having motive and strategy components, as outlined in Table I. TABLE I. Relationships between motive and strategy in studying Dimensions
Motive
Strategy
Utilising
Instrumental: main purpose is to gain a qualification, with pass-only aspirations and a corresponding fear of failure.
Reproducing: limit target to bare essentials and reproduce through rote learning.
Internalising
Intrinsic: study to actualise interest and competence in particular academic subjects.
Meaningful: read widely, inter-relate with previous relevant knowledge.
Achieving
Achievement: obtain highest grades, whether or not material is interesting.
Organising: follow up all suggested readings, schedule time, behave as 'model student'.
This model is a particular instance of Mischel's (1973) description of how people behave in situations. There is a 'psycho-logic' in how persons construe their roles in situations, and what they decide to do about it. In a learning situation, for example, if the student decides only to pass, then as discussed above, it makes subjective sense to rote learn only those facts and details that are thought likely to be tested. It is the student's psycho-logic that is at issue here, not the teacher's or the researcher's. This
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idiographic view of student learning derives much from Marton & Sals jo's (1976) distinction between 'surface level' and 'deep level' processing. These authors showed that students would adopt one or other means of processing academic tasks according to their intentions in approaching the task in the first place. If they wished merely to display the symptoms of having learned, they would adopt a surface level approach; and if to extract maximum meaning, they would adopt a deep level strategy. The emphasis in the present model, then, is very much upon the way a student experiences the learning environment, differentiates the options perceived to be available, and acts accordingly. The LPQ summarises the more common goals and ways of acting to reach those goals. Some students do not consciously think out their position in this way, so that their actions may not in fact be very appropriate, either to their own intentions, or to their teachers'. Other students make quite clear differentiations as to their options for going about learning. To summarise, then, the LPQ is based upon the following assumptions about student learning. (1) A formal learning situation generates three common expectations: to obtain a qualification with minimal effort, to actualise one's interest, and to publicly manifest one's excellence. These expectations refer to the three motives in Table I, and correspond well to those nominated in the psychological literature (e.g. Biggs & Telfer, 1981) for motivating academic performance: extrinsic, including both positive reinforcement (task as a means to a desired end) and negative (fear of failure); intrinsic; and need-achievement. There may well be other motives, such as social ones, but they are not considered here. (2) Students may endorse any or all of these motives to any extent (the dimensions are independent); e.g. a student may be both intrinsically and achievement motivated (and in fact top performing students are so motivated). (3) It would seem good 'psycho-logic' for students to adopt the strategy most appropriate to their own complex of motives. As will be seen below, students tend to see instrumental motivation as congruent with the reproducing strategy; intrinsic motivation with the meaning strategy; and achievement motivation with the organising strategy. (4) The motivational mix—and consequent strategy adoption—may vary from subject area to subject area, and from time to time. For instance, a student who is basically intrinsically interested in one particular subject and is continuing at school or university in order to pursue it, may nevertheless have pass-only aspirations towards another subject that is needed to make the chosen course pattern. (5) The three strategies are likely to lead to different levels of quality of learning. Reproducing is likely to lead to high factual recall, but low meaningfulness; the meaningful strategy is likely to lead to greatest structural complexity; and organising is likely to lead to whatever goals the student sees as most pertinent to high grades (Biggs, 1979). Relevant Personological Factors
The personological domain has been so extensively researched that it is not feasible in any one study to include measures that exhaust that domain. Rather one must select personological variables that are most likely to be relevant to the task at hand. In our analysis of learning processes, we have chosen to explore the effects of two established mental abilities.
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A consistent theme concerning learning processes is the distinction between learning that is meaningful and integrated, as opposed to that which is more rote or factual in nature (e.g. Ausubel, 1968). In selecting mental abilities for study, we wanted ones that would address this basic distinction, such that one ability could be argued to be basic to meaningful learning and the other to rote learning. The two information processing abilities of simultaneous and successive processing (Das, Kirby & Jarman, 1975,1979) match this requirement. Because these abilities are not as well known as, say, verbal or spatial abilities, it is worthwhile briefly to review them here. Simultaneous and Successive Processing Luria (1966a,b) proposed that these two information processing skills are based in distinct cortical locations, as shown by evidence gathered from his brain damaged subjects. Das et al. (1975, 1979) derived measures of simultaneous and successive processing that could be given to normal subjects, and their subsequent research has shown how these processing skills are employed by a variety of ability and cultural groups. In simultaneous processing information is related to other information, forming a unitary code; other terms for this relating process include chunking and integrating. In successive processing, information is kept in discrete bundles or codes which are related to each other only in a temporal sense; thus one code leads only to one other code. Each form of processing represents a broad category of skills, which can be involved in verbal, spatial and other kinds of tasks. We will refer to simultaneous and successive processing as processing abilities: by this we mean that they measure how well subjects perform certain tasks. We consider them to be different from traditional mental abilities, because they are denned theoretically to be less restricted by task content (as opposed, e.g. to verbal or spatial abilities) or by task format (as opposed, e.g. to memory or perceptual abilities). By essentially cutting across traditional abilities, however, they necessarily overlap with them. Simultaneous and successive processing are particularly relevant in the present context because of their theoretically-defined relation to meaningful and rote learning. By definition, rote learning must operate by means of successive processing. The connection between simultaneous processing and meaningful learning is more abstract but still clear. The essence of meaningful learning is the relating of new information to old, or the integrating of new information into existing cognitive structures. This relating or integrating takes place, again by definition, by means of simultaneous processing. If our argument to this point is correct, students' learning processes should relate to their pattern of simultaneous and successive processing abilities. As our study will examine groups defined by these two processing abilities, we will attempt to characterise the four groups involved before proceeding to our hypotheses and the design of the study. If we conceive of simultaneous and successive processing as two abilities which are approximately uncorrelated (as shown by Das et al., 1979, in various studies), we can form four ability subgroups by splitting each ability dimension at its median. Students with above average levels of both processing abilities are most easily seen as bright students who are capable of employing all strategies successfully (given appropriate motivation). Subjects with below average levels of both processing abilities can similarly be seen as less generally able, and thus less likely to
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successfully employ any particular strategy. In this way we see simultaneous and successive processing abilities as representing two broad categories of mental ability. Our point is not that they are adequate to fully assess mental ability (many more factors would be required), but that they represent the two major information processing categories. For these reasons, students with equivalent levels of both processing abilities can be seen as basically varying in degree of general ability. The two 'off-diagonal' groups, that is those above average in only one of the two abilities, are more interesting. Given previous research (Das et al., 1979; Cummins & Das, 1978; Gordon, 1982; Kirby, 1982; Leong, 1980), it is possible to describe the information processing activities of these groups. The low simultaneous-high successive group is able to encode and retain information, but integrating and relating of this information is less likely to proceed to a very high level. It is worth noting that integration and relating would still take place to some degree in normal students; only brain-damaged subjects would be unable to proceed with any integration at all (e.g. Luria, 1966a, b). This group would be expected to spontaneously employ rehearsal or factual strategies, though they would be likely to benefit from externally-imposed instructional support toward integrating and relating. The other off-diagonal group, with high simultaneous processing and low successive processing, would behave in quite a different way. These students are more likely to attempt to relate and integrate information in tasks, but without accurate representation of that information, in particular without a clear retention of the information's sequential structure. Less information retained produces an impoverished basis for integration, resulting in vague or gestaltic interpretations or approaches. Again, only in brain-damaged groups (cf. Luria, 1966a, b) would information-retention be entirely absent. In less extreme cases (particularly at younger ages), such students are likely to have reading disabilities (Leong, 1980; Robinson, Note 3). Within normal ability ranges, members of this group would tend spontaneously to adopt integrating strategies, but their success would depend upon the degree to which data-support was available. It is important to stress that the subjects of the current study were a random sample of normal students, so extreme cases of disability should be rare. Kirby & Das (1977) have shown that both processing abilities are related to achievement, and furthermore that the two off-diagonal groups attain comparable levels. Given their different information processing skills, it seems likely that each group either makes use of its strengths to achieve adequately, or alternatively develops coping strategies to compensate for its weaknesses (cf. Kirby, 1980). The point to be made in the present context is that both of these groups consist of normal students who are likely to attain moderate levels of achievement, though by different means. The Mediational Approach
The basic issue we are addressing in this paper is the relationship between these process abilities and the differentiation of learning processes. Given the above discussion one would expect that differentiation of the learning process complex would differ qualitatively in students of different process abilities. Thus one would expect for instance that students whose predominant mode of processing was successive would tend to see a reproducing strategy and its associated motive as more related to achievement motivation than they would a meaning strategy. This is because an ability to sequence events in time is a prerequisite to effective rote learning, while it is unrelated to strategies for discovering meaning; thus, rote
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learning would tend to be the chosen route to the goal of academic success. Likewise, students with a predominantly simultaneous processing mode would tend to relate meaning strategies with achievement motivation and an organizing strategy, because the ability to hold several points in mind to inter-relate them is basic to the discovering of meaning; thus meaningful learning would be perceived as the proper route towards academic success. It is important to note that we are not talking here about the effectiveness of use of this or that strategy, but the extent to which the student differentiates comfortable options in his learning repertoire. In the case of the learning process complex, we have seen that normal students differentiate the 36 motive and strategy items of the LPQ in terms of three underlying dimensions—indeed this is how the dimensions were identified in the first instance. However, will subgroups of students, for instance those with above average simultaneous processing ability, differentiate that domain in the same way? Theory would lead us to predict that learning process differentiation will depend upon ability subgroup membership.
Method Subjects
The subjects were 321 Year 9 students (mean age of 15 years, standard deviation of 5.8 months) at two urban high schools, 176 male and 145 female.
Tests
All tests were administered to classroom-sized groups.
Simultaneous and Successive Processing. Two tasks were selected to measure simultaneous processing, and two to measure successive. Previous studies (Das et ah, 1979) had employed younger subjects, so it was necessary to employ more difficult versions or adaptations of these measures in the present study. The measures of simultaneous processing were Raven's Standard Progressive Matrices (Raven, 1938) and Figure Copying. The measures of successive processing were Serial Recall and Visual ShortTerm Memory. These tests have been used extensively to assess simultaneous and successive processing abilities (see Das et al, 1979, for a review of previous studies and descriptions of tests). Details concerning the adaptation of the tests for this study are given in Kirby & Biggs (1981), as are scoring criteria.
Learning Process Questionnaire (Biggs, Note 1; see also above). This test consists of 36 items; in each item the subject is required to respond on a three point scale how true a particular characteristic is of him or her. Previous research has shown the items to form three major scales or dimensions, each of which has a strategy and a motive component (see Table I). Each strategy or motive subscale is assessed by six items. Thus the total score possible for each subscale is 18. The six subscales are: reproducing strategy, instrumental motive, meaningful strategy, intrinsic motive, organising strategy, achievement motive.
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Results It was first necessary to define measures of simultaneous and successive processing. Two principal components (eigenvalues >1.0) were extracted from the first four tests listed above, and rotated to a Varimax criterion. These two components correspond exactly to the two information processing ability factors hypothesised on the basis of extensive previous research, simultaneous being defined primarily by Raven's Matrices and Figure Copying, and successive by Serial Recall and Visual Short-Term Memory. Factor scores were computed from this analysis, giving each subject a score on simultaneous and on successive processing. Let us first consider whether the processing abilities determine the various learning process dimensions. As we argued above (see Learning processes and process abilities section), there is little reason for expecting this to be the case. Table II shows the correlations between the two sets of measures. TABLE II. Correlations between simultaneous and successive factor scores and LPQ scales (AT=321) Learning process dimension Reproducing strategy Instrumental motive Meaningful strategy Intrinsic motive Organising strategy Achievement motive
Simultaneous
Successive
028 -062 093 053 034 111
000 041 -021 -028 -018 000
For 320 df, r(0.05) =0.10 (two-tailed).
Only one of these correlations is even marginally significant, that between simultaneous and achievement motivation, and none accounts for an appreciable amount of variance. It is clear that information processing abilities and learning processes are independent in the large sample represented here. There is no evidence in these correlations that simultaneous processing is related to meaningful learning, or that successive processing is related to the reproducing strategy. From the present perspective, it is more relevant to use the simultaneous and successive scores as individual difference variables, to divide the sample into information processing ability groups. Both dimensions were dichotomised at their medians, forming four groups. LPQ results were factor analysed separately for each of these four groups. Correlations were calculated and principal components extracted and rotated to Varimax criteria. The major hypotheses concern which LPQ factors coalesce, if indeed these factors do coalesce, in each of the groups. To simplify presentation, only results for factors with eigenvalues greater than 1.0 will be tabulated, though other solutions will be mentioned. We will deal with each of the groups in turn. Results for the high-simultaneous high-successive group (N= 89) are presented in Table III. For this group, three factors emerged, accounting for 70.5% of the total variance, and corresponding to the three LPQ dimensions, utilising, internalising and achieving. These results indicate that the students above average on both abilities articulate all three learning process dimensions. A two-factor solution was also attempted (unreported), in which the internalising and achieving factors merged.
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J. B. Biggs &J. R. Kirby TABLE III. Principal components results for high-simultaneous high-successive group . (Varimax rotation) (JV=89) Factor
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LPQ scale Reproducing Instrumental Meaning Intrinsic Organising Achieving
I -12 26 81 84 42 -07
% Total variance
II
III
-21 52 18 -05 58 87
86 62 -03 04 -21 -01
24.0
27.3
19.5
Decimals omitted from factor loadings.
While this merger was only predicted for the high-simultaneous low-successive group, its occurrence in the high-high group suggests that simultaneous processing has had a more powerful effect than successive. The three factor solution is preferable, but the two factor solution does not affect our major predictions. A two factor solution was indicated for the high-simultaneous low-successive group (N=72) by the eigenvalue criterion (Table IV). TABLE IV. Principal components results for high-simultaneous low-successive group (Varimax rotation) (N=72) Factor LPQ scale Reproducing Instrumental Meaning Intrinsic Organising Achieving % Total variance
I -27 29 71 74 69 65 35.2
II 78 85 -32 05 04 03 23.9
Decimals omitted from factor loadings.
It can be seen that the first factor represents the hypothesised merger of internalising and achieving, while the second factor is utilising. This finding confirms one of the major predictions made for this study. A three factor solution was calculated for this group as well. As for the high-high group, all three factors emerged. These results indicate that while all three factors can be discerned for this group, internalising and achieving tend to coalesce if allowed to. The second major prediction is addressed by the results presented in Table V for the low-simultaneous high-successive group (N=70). Again the two-factor solution is favoured by the eigenvalue criterion, the first factor being the hypothesised coalescence of utilising and achieving, and the second internalising. While specification of three factors showed complete differentiation, the point is once more that the predicted merger occurred when it was allowed to,
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TABLE V. Principal components results for low-simultaneous high-successive group (Varimax rotation) (N= 70) Factor
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LPQ scale Reproducing Instrumental Meaning Intrinsic Organising Achieving % Total variance
I
II
69 78 -14 02 58 60
-12 -07 85 74 62 37
30.1
30.0
Decimals omitted from factor loadings.
and that this was the solution favoured by the eigenvalue criterion. Taken in conjunction with the results for the high-simultaneous low-successive group, this is persuasive evidence that learning processes are differentiated quite differently in these two groups. Both of the last two groups accounted for less variance than the high group, but the same as each other. One apparent irregularity in Table V is that organising loaded upon both factors in the two-factor solution whereas the corresponding achievement motive did not do so, loading only upon the utilising-achieving factor. This suggests that the lowsimultaneous high-successive group perceive achievement motivation as involved in utilising, while the appropriate achievement strategy (organising) is related to both utilising and internalising. In other words, the road to high marks is seen as involving a reproducing approach, whereas organising, which high-simultaneous students see as related to achievement, also relates to another dimension. Table VI presents the results for the low-low group (AT=90). The one factor solution is favoured by the eigenvalue criterion, and only 48.3% of the variance is accounted for. For this group, neither two nor three factor solutions presented acceptable simple structures. One clear inference is that this group has not evolved differentiated learning styles; instead this single factor suggests a global dimension, perhaps 'Interest in School'. Some members of this group are more interested in school than others, but they do not appear to know what to do about it. TABLE VI. Principal components results for low-simultaneous lowsuccessive group (JV=90)
LPQ scale
Factor I
Reproducing Instrumental Meaning Intrinsic Organising Achieving
49 65 72 80 80 66
% Total variance
48.3
Decimals omitted from factor loadings.
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It is possible to summarise these results in two broad statements: (1) as students' processing abilities increase, they show greater learning process differentiation, and (2) for students intermediate in differentiation, the learning processes that do emerge are dependent upon which processing abilities they possess. These two conclusions will be the focus of the discussion which follows.
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Discussion The results presented above demonstrate that students who differ in abilities also differ in how they perceive and organise their learning processes. This provides indirect support for the mediational model presented earlier in this paper. No evidence was found that ability levels determine the degree to which various learning motives and strategies are present. We will begin by reviewing these results, and then go on to consider aspects of the mediational model in depth. Previous research (e.g. Biggs, 1978) has shown that it is possible to distinguish among three major learning process dimensions, each with a motive and a strategy component. The present study's results show that this complete differentiation is only clearly present in very able students, the group with high levels of simultaneous and successive processing abilities. It is worth noting that this group is the one most likely to proceed to tertiary study, where there is ample evidence for complete learning process differentiation (e.g. Biggs, 1978; Entwistle, Hanley & Hounsell, 1979). At middle levels of ability, only two learning process dimensions are differentiated. In this study, middle levels of ability were composed of students who were skilled in only one of the two forms of processing, i.e. the high-simultaneous, lowsuccessive and the low-simultaneous, high-successive. Had the same two dimensions emerged for these two groups, little more could be said than that more able students are more differentiated. The distinct differences in factor structures found for these two groups, however, point to a deeper theoretical interpretation, namely that the abilities one possesses determine which learning processes will be defined, not only how many. Finally, the low ability students show no differentiation at all. Their one factor is most easily interpreted as an approach-avoidance attitude towards school. Any interest in school is spread across the range of strategies and motives, which perhaps accounts for their lack of success. Mediational nature of LPQ The Learning Process Questionnaire scales are intended to represent mediational variables. While it is clear that they represent more situation-specific constructs than do traditional personality traits, they are not as situation-specific as such constructs as Rigney's (1978) embedded strategies, because subjects answer the LPQ questions about learning in general, not about any specific instance of learning. There is, then, a continuum, within the learning process complex, ranging from detached, almost trait-like, approaches that are typical of an individual in a learning situation, to quite specific moves that an individual makes in interaction with a particular task. At the extreme end of specificity a description of these task specific moves becomes a description of content, of what-is-learned (Marton, 1981); at the other end, of generality, one is back to the original ATI model, with a broad aptitude as the point of departure. The LPQ scales clearly represent a compromise in
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terms of generality, and focus on the school learning context as a whole. What has been shown in this study is that learners differentiate, both quantitatively and qualitatively, their ways of handling that context, according to their information processing abilities.
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Learning Processes and Strategy Instruction
In the mediational model underlying this study, we have postulated a learning process complex mediating fixed personological characteristics and performance. This complex is intimately related to the strategies that subjects employ in given tasks, and thus related to the constructs of metacognition (awareness of, among other things, the usefulness of particular strategies) and of executive processes (selection and control of strategies). As Lawson (in press) has emphasised, the awareness-control distinction is an important one. Strategy selection and control are affected by awareness, so both aspects are relevant to the learning process complex. In spite of this, we would argue that executive processes are more important for practical consideration: there is little evidence that awareness as such has any impact upon performance (Cavanaugh & Borkowski, 1980; Kirby & Moore, Note 2), and there is growing evidence that strategy instruction can be effective (Brown, 1974). The most vexing question regarding strategy instruction is that of transfer and generalisability. While subjects can be taught to employ an optimal strategy in a particular task, it is not certain that they will continue to use the strategy after instructional support is removed, or if they will use it in even a slightly different context. Spontaneous strategy selection and performance monitoring may be a function of general intelligence, and not easily modified; Kirby & Lawson (1983) for instance have argued that some tests may measure intelligence precisely because they require subjects to discover what the problem is and what strategies to use. There are several aspects of strategies that must be considered if these issues are to be resolved. One is the useful distinction drawn by Rigney (1978) between detached and embedded strategies. Embedded strategies are task specific and easily teachable even to those individuals who would not spontaneously use them (e.g. Case, 1980); such strategies are however of little use outside the task itself. Detached strategies apply to a wide range of tasks and are not easily teachable to those whose personology is constructed otherwise. Then there are those tasks, like Pask and Scott's (1972) classification task, which are equally soluble by two or more strategies. The most successful strategies are those that fit the personology of the learner. Finally, we might mention the work of Marton (1981) whose phenomenological theory leads him to an idiographic approach: the learner's second-order conception of his learning space determines how the task is carried out and what the outcome will be. Marton's work describes the intervening-dependent variable linkage in an idiosyncratic way—in both technical and everyday meanings of 'idiosyncratic'. To him, there is no 'learning process' as such: to define a person's learning is to list the contents learned. If a student is asked how he learned a topic, he will proceed to list components of the topic. When an observer such as a teacher or researcher describes the process that person uses, the observer will be describing what the observer has learned about the person, not what the person learned about the task. Nevertheless, many psychologists would argue that first-order learnings-aboutthe-learner can help the second-order learning of learners. Such first-order learning is what is studied in nomothetic approaches to learning: second-order learning is
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idiographic in nature, and as Kirby & Biggs (1981) have argued, both are necessary. There is, in other words, a mid-way position between Jensen's (1973) comment that the psychology of individual differences is the single most fruitful approach to educational learning, and Marton's concentration on the situational here-and-now. One aspect of that midway position is that proposed in the present paper, the learning process complex. Individual differences in abilities exist, and those differences do relate to learning in a quite detached way; that is, transfer across tasks is eminently demonstrable. Subjective perceptions and aspirations, and executive decisions to implement those aspirations in the face of a presented task, also exist and result in both quantitatively and qualitatively differentiable learning outcomes (Biggs, 1979). Finally, it is true that particular task-specific strategies can be taught. The present model is intended to bridge these three levels, postulating the learning process complex as the mediational domain. In operationalising that domain, we have used self-report statements about the motives students may have and the strategies that are potentially available for them to use. By factor analysing the motive and strategy scales we have in effect determined the complexity of that domain, in much the same way as Bannister & Maier (1968) used factor analysis in personal construct theory. The factors listed for the groups in Tables III-VI define the complexity of the learning process complex for the four groups of students. Viewed in this way, the low first order correlations between simultaneous and successive abilities, and the motives and strategies, are expected; likewise, it does not follow that the correlations between the components of that study process complex and performance need be high (they are not). The important thing which has been demonstrated here is that the learning process complex is phenomenally different to groups of students: '"the" learning process complex is clearly something of a misnomer. Some students do not discriminate many options, others discriminate different ones. Whether those discriminated components are functionally effective is yet another question, which we have not investigated here. As a working hypothesis, however, it seems reasonable to suggest that the effectiveness of a student's utilisation of the learning process complex would depend on other factors such as other abilities, prior knowledge, and so on. To use an analogy, differentiation would determine which signpost to follow when placed at the metacognitive crossroads in performing a task (when several roads lead to successful completion), but not how fast one travels. To pursue the analogy further, perhaps the student differentiating only one road would simply continue in any direction at random. Such a one would have low metacognitive flexibility in this context, and perhaps would be the most suitable candidate for intervention. In this respect, it is worth noting that Kirby & Biggs (1981) and Biggs (in press) showed that highest correlations between the organising strategy and performance were either in a highly achievement motivated group, or in poor achieving and low motivated groups. To these latter students, it is perhaps any port in a storm: when one cannot decide what to do, doing something is likely to be preferable to doing nothing.
Implications There are several implications of this study, in at least the following areas.
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(1) Intervention There are four problems here: a different one for each of the four information processing groups. The high-high group presents the least problem. These students have all options open to them, and intervention, in the sense of strategy training, may need only to be restricted to embedded strategies that suit the particular task in question. They are, in other words, aware of task requirements, and likely to be receptive to particular content-related strategies that will optimise performance. The 'off-diagonal' groups present a different problem: each is 'blind' to strategies that are congruent with the deficient ability. Thus, low-simultaneous high-successive students do not appear to perceive a meaning strategy as particularly related to achievement; and high-simultaneous low-successive students do not associate the reproducing strategy with achievement. Two alternatives are open: compensatory or complementary (cf. Kirby, 1980). According to the compensatory alternative, one would coach students in the deficient strategy, in order to widen their options, as did Krywaniuk & Das (1976); within the complementary alternative, one would coach students in their stronger strategy, for that is the way they perceive the route to success. The compensatory approach tends to regard the underlying personological variable (e.g. level of successive processing ability) as mutable, while the complementary approach accepts the personological context as relatively fixed. Clearly, more research is needed on this important point. The low-low group are probably those most receptive to intervention, of any kind. They seem to lack any differentiation, or even metacognitive awareness, of the learning process complex; like the retarded children studied by Brown (1974) they should benefit from any external attempts to help them, in the presence of adequate motivation. (2) Theory of Individual Differences In this paper, we have drawn attention to two classes of individual difference variable: the nomothetic and the idiographic, or to use Marton's (1981) terms, the first-order and the second-order perspectives. Our independent variables (the process abilities of simultaneous and successive processing) are traditional nomothetic variables, as viewed from the first-order perspective of the detached observer. They clearly exert their effects on performance, as has been demonstrated clearly, many times (e.g. Kirby & Das, 1977). However, they also exert an important second-order effect: they affect the idiographic, phenomenal perspective of the individual learner, and that perspective determines the performance of the student too, in that, according to that perspective, the student sees, or does not see, what strategic options are possible. That perspective must be taken into account, both in practical decisions outsiders might make affecting that student's learning, and theoretically, in determining the domains researchers need to take into account in learning about learning. As Entwistle & Hounsell (1979) have said, the nomothetic and idiographic ('illuminative') paradigms each has its own limitations: the former "is forced to ignore the totality of a student's experience" (p. 360), while the latter can mislead "by swamping the researcher with particulars of doubtful general validity" (ibid.). The two paradigms "contain the tension of opposites—a thesis and an antithesis out of which a fruitful synthesis might be anticipated, but is still far from being achieved" (ibid.). It is hoped that the present research may have advanced this synthesis to some extent.
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Correspondence: Professor John B. Biggs, Department of Education, The University of Newcastle, New South Wales, 2308, Australia. NOTES
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[ 1 ] BIGGS, J.B. (forthcoming) Student Motivation and Strategies of Learning and Studying: A handbook for teachers, counsellors and researchers (Hawthorn, Vic, Australian Council for Educational Research). [2] ROBINSON, G.L. (1983) Simultaneous and successive information processing, language, and reading processes in reading disabled children (in preparation). [3] KIRBY, J.R. & MOORE, P J . (1983) Metacognitive knowledge and reading ability. Manuscript submitted for publication.
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