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Human Movement Science 9 (1990) 387-435 North-Holland

387

SCHMIDT’S SCHEMA THEORY: THE EMPIRICAL BASE OF THE VARIABILITY OF PRACTICE HYPOTHESIS

A critical analysis *

Jacques H.A. VAN ROSSUM Free University, Amsterdam, The Netherlands

Van Rossum, J.H.A., 1990. Schmidt’s schema theory: The empirical base of the variability of practice hypothesis. A critical analysis. Hu- man Movement Science 9, 387-435.

This paper is addressed to Schmidt’s (1975) schema theory of motor learning. Within this theory, most attention has apparently been given to the variability of practice hypothesis. The hypothesis claims that variable practice is more effective for schema development than constant practice. The empirical foundation of the variability prediction is evaluated here on the basis of 63 relevant studies (mainly journal articles and dissertations), reporting 73 different experiments and covering 12 years of empirical research (from 1975 through 1987).

Experiments with adult (n = 48) and with child subjects (n = 25) were distinguished. In the literature, it is often stated that solid empirical support is available for the hypothesis, especially with child subjects. From the review presented here, it was concluded that, firstly, about half of the experiments were factually not addressing the variability prediction, particularly because no learning was evident during practice. Secondly, only limited support favouring the prediction could be obtained from the remaining experiments. The variability prediction cannot, therefore, rest upon consistent supportive evidence, neither with adult nor with child subjects.

1. Introduction

For motor learning theory the year 1975 is a landmark, it heralded the appearance of R.A. Schmidt’s paper on a schema based theory of

* The author wishes to thank Dr. H.T..A. (John) Whiting for his support throughout the successive stages of processing the information and his stimulating help in writing it up; thanks are also extended to Dr. SW. Keele, Dr. N.H. Zelaznik and two anonymous reviewers for their perceptive, critical, and motivating comments on an earlier version of the manuscript and Dr. R.B. Wilberg for his generous assistance in putting the finishing touches.

Author’s address: J.H.A. van Rossum, Free University, Faculty of Human Movement Scien- ces, Dept. of Psychology, V.d. Boechorststraat 9, 1081 BT Amsterdam, The Netherlands.

0167-9457/90/$03.50 0 1990 - Elsevier Science Publishers B.V. (North-Holland)

388 J. H.A. uan Rossum / Motor schema

discrete motor skill learning. In June 1983, Schmidt’s original publication on the schema theory (Schmidt 1975) was selected as a citation classic in Current Contents (Schmidt 1983): the paper, at that time, having been cited in over 155 (journal) publications. In addition to being referred to often, Schmidt’s point of view has since generated a large amount of research. To date, only two overviews of the schema theory have appeared: Shapiro and Schmidt’s (1982) widely cited evaluation of some six years of research and, more recently, Lee et al.‘s (1985) paper, which addressed specifically the schedule of variable practice.

In the Shapiro and Schmidt (1982) paper, a general review of Schmidt’s earlier theoretical notions was put forward in the light of empirical research - directed to three aspects of the theory. In addition to studies on the independence of recognition and recall schemata and on the generalized motor programme, most empirical concern and attention has been directed towards the suggestion that performance on a novel task will be better following varied, rather than constant, prior practice. This suggestion was termed the ‘variability of practice hypothesis’ by Moxley (1979) - a label that has since that time become generally adopted.

In this paper, assessment is limited to this latter hypothesis. An overview of studies within the context of the variability of practice hypothesis will be presented, based upon a computer-file search yielding more than 170 references to the original paper in which the schema theory was formulated (Schmidt 1975). These references have been analysed elsewhere (Van Rossum 1987) with respect to author, periodi- cal and date of publication. That set of references covered the years 1975 through 1985 (June). In the present paper a review will be presented of all those reports which contained original empirical material addressing the variability of practice hypothesis; updated through the year 1987.

In their reviews, both Shapiro and Schmidt (1982) and Lee et al. (1985) come to the conclusion that the ‘variability of practice hypothesis’ is empirically supported when children are used as subjects, whereas the findings of adult studies have been inconclusive (Lee et al. 1985). In this paper, the distinction based on age of the subject is maintained. The empirical studies are evaluated with respect to a number of methodological aspects, the most important being empirical evidence of progress during practice. It is argued that those studies, in which such

J. H.A. uan Rossum / Motor schema 389

evidence was not forwarded, must in fact be disregarded in the context of an evaluation of the variability of practice hypothesis. Before doing that, a short overview will be offered of Schmidt’s schema notion. This not only provides the necessary theoretical background against which the empirical studies presented can be evaluated, but it also leads to conclusions about relevant methodological aspects in the context of studies testing Schmidt’s hypothesis.

1.1. The schema concept and Schmidt’s conceptualisation

A schema oriented theory is by definition a theory of knowledge: that is, a theory about the storage, representation and management of previous experience. A schema is then a knowledge system.

The roots of the schema concept lie as far back as Kant (Langer 1970) although Head (1926) was probably the first to use the concept with respect to motor behaviour. In the 1930s the concept is found in the writings of both Bartlett ([1932] 1977) and Piaget ([1936] 1977), albeit in different contexts. Bartlett was mainly concerned with the functioning of memory with respect to social psychological phenomena (stressing the recognition function of the schema as memory structure) while Piaget used the schema in the description and explanation of cognitive development (emphasising the initiation or recall function of the schema). More recently, Pew (1974) introduced the schema as the highest or most abstract level of control and organization in his description model of human information processing. Schmidt (1975) acknowledged the contribution of Bartlett and Pew to his schema theory. Schmidt’s schema theory proved to be timely, for ‘by 1975 there had been a Zeitgeist which prepared the cognitive science for schema theory’ (Brewer and Nakamura 1984: 131).

It would probably be too easy to regard the ‘Zeitgeist’ as the main force that caused Schmidt to develop his theory. There was at that time a growing discontent with the leading theoretical model on motor skill learning. This model, advanced by Adams in 1971, stressed the importance of Knowledge of Results (KR) for learning. That is, it stressed the importance of the ‘perceptual trace’ (involved with motor recognition: evaluation of the correctness of the executed response) and the ‘memory trace’ (motor recall: ‘selection and initiation of the response’ (Adams 1971: 125)). Fundamental problems in motor control theory did not appear to be solved by Adams’ model, because the perceptual

390 J. H.A. uon Rossum / Motor schema

and memory traces could not be effectively studied separately in ‘slow’ movements (that is, movements the execution of which takes longer than one reaction time). Schmidt’s (1975) schema theory, on the other hand, emphasized ballistic or ‘fast’ movements; given that recall and recognition processes could be adequately distinguished in such movements.

In the context of Adams’ (1971) model slow movements were mainly employed in experimental tasks (especially, lever positioning tasks). While, at the time of publication of Adams’ 1971 paper most existing theories of motor learning were related to the performance of previ- ously acquired skills, Adams’ orientation was explicitly towards the learning of novel, ‘not-yet-acquired’ motor skills. However, Schmidt (1975: 227) endorsed Adams’ concern for the learning of novel motor skills, notwithstanding his methodological critique of Adams’ model. The starting point of both Adams’ and Schmidt’s motor learning models is that skills are learned and that experience is deposited in meinory structures (respectively termed ‘ trace’ or ‘schema’).

Schmidt (1975, 1976) introduced the schema concept as a solution to what he called ‘some persistent problems’ in motor learning and control; namely the problems of storage and novelty. Following Adams, two motor schemata were distinguished by Schmidt (1975) the recognition schema (cf. the ‘perceptual trace’, controlling the ongoing response) and the recall schema (cf. the ‘memory trace’, initiating the response). As Schmidt (1975) writes, the recall schema is supported mainly by anecdotal evidence, while there exists much empirical evidence to support the recognition schema notion. It is not suprising then that many of the studies initiated by Schmidt’s theorizing were directed towards providing empirical support for the recall schema. In this context, and related to the problem of novelty (how can one execute a movement which one has never executed before?), the variability of practice hypothesis (also termed ‘the variability prediction’) was formulated. This hypothesis proposes that not all practice is equally efficient in improving motor control; the claim being that variable (i.e. continually changing) practice in contrast to constant (i.e. always the same) practice leads to superior learning.

In a ballistic movement, only the recall schema is involved. The response specifications are determined by a rule which relates the following three sources of information together. First, initial conditions, ‘information received from the various receptors prior to the reponse,

J. H.A. van Rossurn / Moior schema 391

such as proprioceptive information about the positions of the limbs and body in space, as well as visual and auditory information about the state of the environment’ (Schmidt 1975: 235). Second, response specifications, specifications of ‘variations of the basic pattern possible by changing such important elements as the speed with which it is run off, the forces involved, etc. ( . . . ) before the movement can be run off (Schmidt 1975: 235). Third, the response outcomes, ‘the success of the response in relation to the outcome originally intended’ ( . . . ) ‘the

actual outcome of the movement is stored, not what was intended’ ( . . . ) arises from information the subject receives after the movement, and consists of KR (when present) and subjective reinforcement that the subject obtains from other sources of feedback. The accuracy of the outcome information is thus a direct function of the amount and fidelity of the feedback information, and a subject without any feedback information does not have outcome information to store’ (Schmidt 1975: 235).

In the case that a movement of longer duration is executed, the possibility exists to adapt the movement in the course of its execution. The recognition schema is involved here. Three sources of information are also combined in the schema-rule of the recognition schema. First, the initial conditions as described earlier. Second, the sensory conse- quences, ‘response-produced sensory information ( . . .) the actual feedback stimuli received from the eyes, ears, proprioceptors, etc. ( . . .) an exact copy of the afferent information of the response’ (Schmidt 1975: 235), and third, the response outcome.

Although the schema rule is based on partly different sources in each of the two discernible schema-systems, the rule is, in both cases, inferred from past experience and can be modified or adapted on the basis of new experience. This relatively consistent, but nevertheless changeable memory system can be considered a plausible solution for both the problems of storage and novelty. The execution of movements is thus not seen as a literal reproduction of earlier experiences, but as a fresh construction via a constantly elaborated schema. In the variability of practice hypothesis an optimal route has been proposed to ‘in- creased schema strength’ (Schmidt 1975: 245).

According to Schmidt, the (recall) schema notion up to 1975 was supported mainly by anecdotal evidence. Many subsequent studies, initiated by Schmidt’s theorizing, were directed towards the development of empirical support for such a notion. By providing variations in

392 J.H.A. “an Rossum / Motor schema

the initial conditions of a task, the practising subject develops a recall schema rule that should be more valid in the case of a new, i.e., not yet encountered, initial condition. The variability of practice could thus be (and, in fact, was) experimentally manipulated through the initial conditions. In a throwing for accuracy task, for example, throwing balls of various weights would constitute variable practice, while throwing balls of the same weight throughout the practice trials would be constant practice. The variability prediction holds that the provision of variously weighed balls is advantageous in the case that a throw must be executed with a differently weighted ball. Recall schema rules developed under such variable practice conditions, should permit the subject to generate the response specifications necessary to obtain the intended response outcome.

In addition to the motor schema, Schmidt (1975) introduced the concept of a ‘generalized motor programme’ (GMP), the latter being a movement programme for a given class or category of movements. The GMP requires, however, translation into specific movement details; ‘the program requires response specifications that determine how the program is to be carried out’ (Schmidt 1976: 46). These specifications are generated by the motor schema. Thus the choice of the GMP determines whether, in terms of football for example, the ball is thrown or kicked. If the decision is made for the throwing action, the schema specifies the details of the movement. The variability of practice hypothesis does not therefore, address the choice of the movement class, but is only concerned with the optimal execution of the selected movement within the already chosen movement class.

As indicated above, Schmidt limited the schema theory for methodological reasons to ballistic movements, while for theoretical reasons he argued that empirical research should be directed to the recall schema notion. Schmidt’s (1975, 1976) plea for empirical support for his recall schema notion found a response through a large number of studies on the variability of practice hypothesis, at different ages in the life-span: at the college age (e.g. Newell and Shapiro 1976) at the school-age (e.g. Moxley 1979) and at the pre-school-age (e.g. Kelso and Norman 1978).

1.2. Some characteristics and problems of empirical tests of the variability of practice hypothesis

Studies designed to evaluate the variability of practice prediction are in general terms, similar. At least two groups are necessarily involved,


each of which practises a particular task under one of two different conditions (variable practice, constant practice) for a certain number of training trials. After the training trials, the experimental and control groups are required to perform a novel (transfer) task. The variability of practice hypothesis is taken to be supported in the case that the variable practice group performs significantly better on the transfer task than the constant practice group. Such differences between the two groups are a necessary, but insufficient condition to evaluate the variability prediction. To this end, learning needs to be evidenced during the practice period. If no learning is shown, there is no guaran- tee that the motor schema in question was not already in existence. The consequence is that in experiments designed to gain insight into the development of the motor schema precautions have to be taken by the experimenter to confirm that the particular schema has not already been formed.

Schmidt made it explicitly clear that support could not be expected for the variability of practice hypothesis from subjects in whom the schema is already well formed: ‘future work ( . . . ) should use subjects in whom the schemata have not been developed’ (Schmidt 1975: 246). The implication of this statement is, however, far from clear. Following the suggestion by Schmidt (1975) the ages of the subjects were taken to be a sufficient indication of schema development. Such precautions in an experiment demonstrate that the experimenter has appreciated that research on the recall schema notion must be focused on learning aspects. (In some studies, this is made more explicit in the title: e.g., ‘Motor schema formation in children’ (Kelso and Norman 1978), ‘Motor schema formation and retention in young children’ (Carson 1978), ‘Formation of a motor schema in educable mentally retarded and intellectually normal males’ (Porretta 1982a), and ‘Development of movement schema in young children’ (Williams and Werner 1985).)

Studies aimed at empirically testing the variability of practice hypothesis must ensure that learning has taken place during the practice period. One might take different ‘routes’ to evaluate whether this indeed has occurred (cf. Campbell and Stanley 1966). For example, a control group could be included in the experimental design. Both the variable and constant practice group should outperform the control group on the transfer task in order to conclude that learning for each of these groups has occurred. This option has not been particularly popular in studies testing the variability prediction. A second option

394 J. H.A. “an Rossum / Motor schema

could be the use of a pretest-posttest design. Each of the experimental groups should show an increase from the pre- to the post-testing session, in order to confirm that learning for that group has taken place. This variation has been employed in only a small minority of studies on the variability prediction. A third option is the analysis of training trials. While this procedure was employed as an index of learning in earlier studies addressed to the process of learning, more recent texts on motor learning claim that such an analysis is not to be regarded as a valid indication of learning (Schmidt 1987; Magi11 1985). Reminiscence effects after training under fatigue or massed practice conditions demonstrate that performance during training may give too low an estimation of what has been learned. In such cases this might be construed to be a sound argument. However, it would not rule out the effectiveness of an analysis of training trials for purposes of clarifying whether or not learning has taken place in situations in which the training conditions for all groups of subjects are equated. This third option has often been employed in studies on the variability prediction.

The empirical base of the variability of practice hypothesis will be evaluated in this paper on what is believed to be a central prerequisite; that is, evidence of progress during the course of a training task. In several studies on the variability prediction a similar statement was found (e.g., McCracken and Stelmach 1978; Margolis and Christina 1981; Wrisberg and McLean 1984). Such a determination is required for a correct interpretation of any differences found among experimental groups on the transfer task. In order to ascertain whether or not learning has occurred, each of the three options described above are considered.

In the remainder of this paper, the central hypothesis stemming from Schmidt’s (1975) motor schema theory will be assessed, along with an overview of those original studies which purported to test the variability of practice hypothesis. The variability prediction seems straightfor- ward (that is, uncomplicated) and its translation into an appropriate experimental design presents few problems. Although the solidity of the empirical base of the prediction is widely recognized, a valid test of the variability prediction may be revealed as more complicated than is generally suggested. The major goal of this paper is to assess the empirical foundations from the perspective of learning during practice. Those empirical studies reporting improvement during practice will be considered to constitute the empirical base of the variability prediction.

J. H.A. van Rossurn / Motor schema 395

It must be taken for granted that no learning has occurred in those studies in which improvement during practice was not apparent. Such studies are not considered in the context of this paper.

2. Method

During October 1984, a computer search was carried out, dating back to 1975, with respect to references to Schmidt’s schema theory notions. This database was checked as to its adequacy and was extended by consulting (through 1987) the relevant sources of publications and/or reports about the variability prediction. The precise procedures used in compiling the data base have been described elsewehere (Van Rossum 1987), and only an abbreviated listing of data sources and procedures can be mentioned here (a complete description can be obtained from the author). A computer-search of the Social Scisearch, Psycinfo, Eric, Dissertation Abstracts, Psycalert, SSIE Cur- rent Research, EXER/EXCEP Child, Medline, Scisearch, Conference Papers, Scientific and Technical Proceedings files was made. This search disclosed 170 references which were then subdivided into grouping dependent upon their relevance to the variability prediction. The overwhelming majority of the reference articles report original research (74%: 125 out of the 170); this tendency is especially present in articles published in what can be considered ‘key’ journals with respect to motor learning: the Journal of Motor Behavior, Perceptual and Motor Skills and Research Quarterly (or from volume 50 (1979) Research Quarterly for Exercise and Sport), the Journal of Human Movement Studies and Human Movement Science. Within the category of original research, the number of research articles did not, in the main, address Schmidt’s theoretical notions. In most cases, reference to one of the target articles (Schmidt 1975, 1976) was used to designate ‘a recent motor learning theory’ - and was as such, often mentioned along with Adams (1971).

Articles retrieved through the use of the computer based information systems were augmented by a variety of other citations gleaned from textbooks, unpublished and published proceedings, schema review papers, and periodicals not included in the initial computer search. The computer ‘search and the up-date resulted in a total number of 83 relevant reports of original research (42 journal articles, 33 disserta-

396 J.H.A. unn Rossum / Motor schema

tions, 6 conference papers and 2 unpublished manuscripts). Of these, a total number of 73 reports of empirical research were obtained. A small number of the obtained reports had to be discarded however, as they did not report information relevant to the present investigation or reported virtually identical information as another included reference.

Two journal articles (Williams and Rodney 1978; Zelaznik et al. 1978) were not included as motor recognition and not motor recall was addressed, while two other (Lee and Magi11 1985; Shea and Zimny 1983) were mainly of a theoretical nature.

Kaylor’s dissertation (1979) was not included as only variable practice groups were included in the study. The study was designed to determine the optimal position of the transfer task in relation to the practice tasks; Kaylor’s (1979) study is, however, certainly of relevance in the more general context of the motor schema notion (cf. Van Rossum 1987: ch. 5).

Further, five dissertations were discarded as separate references, as a journal article reported identical experiments; Carson (1978; Carson and Wiegand 1979), Cummings (1981; Cummings and Caprarola 1986), Flanagan (1980; Margolis and Christina 1981), Lee (1982; Lee and Magi11 1983), Porretta (1982a, 1982b). In these cases, the journal article was taken as the primary report of the experiment(s).

In conclusion, 63 separate reports were used to evaluate the empirical base of the variability of practice hypothesis (38 journal articles, 21 dissertations and 4 conference-papers). These reports were classified as resulting from either adult or child based subjects, and are shown as such in tables 1 and 2 respectively (see below).

3. Summarizing the studies on variability of practice

Evaluation of the following studies is based upon empirical evidence with regard to improvement in performance during training trials.

(a) Adult subjects. With respect to the studies listed in table 1, it should be noted that most of the subjects were aged 18 to 28 years (mostly university students). In total, 40 studies, reporting 48 experiments, are listed in table 1. Of these, a number of experiments cannot be used in evaluating the variability of practice hypothesis. Seventeen experiments were eliminated because no indication was present that the

J. H.A. van Rossum / Motor schema 391

experimental subjects showed improvement during practice. In the 30 experiments in which learning was evident, the procedure most often employed was the analysis of the training trials (in 16 of the 19 journal articles and in 9 of the 10 dissertations). Six studies, reporting 9 experiments, were excluded since no transfer task was administered, only retention trials. In sum, 24 of the original 48 adult experiments (50%) appear to be useful to evaluate the empirical base of the variability prediction (16 reported in journal articles, 7 in dissertations, and 1 in a paper).

(b) Child subjects. The studies in which children participated, are summarized in table 2. Of the 25 experiments, contained in 23 studies, 10 (40%) are not relevant to the evaluation of the variability prediction, as no learning over practice was demonstrated. Of most importance to the variability hypothesis are the studies in which a learning effect was found. In these 15 studies (10 journal articles and 5 dissertations) the procedure of the analysis of the training trials was again used, although a combination of this procedure with the inclusion of a no-practice control group in the experimental design was also relatively often used.

In one study (Ramsay 1979) a significant ‘age by block’ interaction was found, indicating that the ‘adult’ group showed no improvement over practice, while the ‘child’ group did.

To recapitulate, 73 experiments addressing the variability of practice hypothesis were unearthed. Of these, 48 involved adult subjects and 25 used children as subjects. From a first review of these studies, as presented in tables 1 and 2, it was apparent that about forty percent of the adult experiments and of the child experiments were inadequate for an evaluation of the variability of practice hypothesis, specifically because no improvement over practice was reported. Three out of four of the experiments reported in proceedings papers (75%), 14 of the 26 reported in dissertations (54%), and 17 of the 43 reported in journal articles (40%) were discarded on that basis. Although the applied criterion can hardly be viewed as the requirement regarding the quality of experimental research, the rejection figures appear to be in line with the opinion that work which makes it through the journal review process tends to be of better quality than unpublished work.

The remaining 39 experiments (24 ‘adult’ and 15 ‘child’ experiments), which are 53% of the originally collected 73 experiments, are described

398

Table 1

J. H.A. “an Rossurn / Motor schema

An overview of all publications included in the database of the review, using adults as subjects.

Author(s) F’ubl. Set N Sex Trials Eval- Learn- uation ing

Journal articles

Bird and Rikli Catalan0 and Kleiner Crabtree and Crabtree Cummings and Caprarola

experiment 2 Del Rey et al. Del Rey et al. Frohlich and Elliott

experiment 1 Gabriele et al. Goode and Magill Husak and Reeve Johnson and McCabe Kerr Lee Lee and Magill

experiment 1 experiment 2 experiment 3

Lee et al. experiment 1 experiment 2

Magi11 and Reeve Margolis and Christina McCracken and Stelmach Newell and Shapiro

experiment 1 experiment 2

Shea and Morgan Tumbull and Dickinson Williams

experiment 2 Wrisberg and McLean Wrisberg and Ragsdale Wrisberg et al.

Dissertations

Barto experiment 1 experiment 2

Blake Cummings


1983 1984 1987 1986

1987 1982 1984

1987 1986 1979 1982 1982b 1985 1983

1985

1978 1981 1978 1976

1979 1986 1978

1984 1979 1987

1986

1984 1975

2 2

2

l/2

1

1

1 /2 /2

1

2

l/2

48 m/f 60 C

120 m/f 40 C

96 m/f 40 _

120 m crit. _

72 f 64 C

60 f 64 C

40 m 14 a 30 m/f crit. C

30 f 324 C

72 _ 6/18/36 _

75 _ 50 a 40 m/f 20 a, b 30 m/f 40 _

24 m/f 54 C

30 _ 54 C

30 f 54 C

36 _ 60 C

48 _ 60 C

45 m/f 12 _

60 m 60 C

48 _ 300 C

96 m/f 60 C

100 m/f 60 C

72 m/f 54 C

70 m/f l/5/15 a

44 _ 20 200 m 150

48 m/f 40 126 m 180

30 f 48 30 f 48 48 m 45

60 m/f 28 60 m/f 25

+ _ ?

? + +

+ + + ? + + ?

+ + +

+ + ? + +

+ + + _

? ? ? +

+ + +

? ?


Table 1 (continued)

Author(s) Publ. Set N Sex Trials Eval- uation

Leam- ing

Elfaqir Gabriele

experiment 2 Goode


Kaplan Meeuwsen


Melville Moon Tietz Whitehurst

Proceedings papers Reeve Salmoni and McIlwain Zelaznik

1982 1986

48

40 1986

1981 1987

1976 1985 1982 1981

I977 80

1980 2 28 1977 l/2 60

36 36 60

60 72

1 30 48 40 48

m/f

m/f

f f

m/f

m/f m/f m/f _

m f

1.000 b +

cl-it. _

144 c

144 c 30 _

30 c 45 c

520 c 96 _

90 b 50 c

_ 16 _ _ 520 a _ 72 a

?

+ + ?

? - +

Note: Publ.: Set:

N: Sex:

Trials:

year of publication. 1= included in Shapiro and Schmidt’s (1982) review; 2 = included in Lee, Magi11 and Weeks’ (1985) review; empty cell: computer-search and up-date. number of subjects involved in the statistical analysis. m/f (male and female in equal proportions); f (female only); m (male only); - (not reported). the number of practice trials administered (‘m-it. indicates that practice was performed until criterion was reached).

Evaluation of learning during practice: a no-practice or (different type practice) control group; b pretest-posttest analysis; c training trials analysis; - no evaluation procedure reported.

Learning during practice: + = analysis yielded significant effect ( p < 0.05); - = analysis yielded non-significant effect (p > 0.05); ? = no results of a statistical analysis reported.

more fully below and are used to gain insight into the viability of the variability of practice hypothesis.

Note that no statement has been made on the variability prediction per se in this section. Each study has only been judged on the basis of a necessary condition (‘improvement over practice’), which should not be

400 J.H.A. oan Rossum / Motor schema

confused with a sufficihzt condition. The studies which have ‘passed’ this selection threshold might be of relevance to an evaluation of the variability prediction. In the next section empirical support for the prediction that variable practice is more advantageous than constant practice is discussed.

Table 2

An overview of all publications included in the database of the review, using children as subjects.

author(s) Pub]. Set Age N Sex Trials Eval- Leam- uation ing

Journal articles

Carson and Wiegand Clifton Kelso and Norman Kerr Kerr

Kerr and Booth Moxley Pease and Rupnow

Pigott and Shapiro Porretta

Williams and Werner


Wrisberg and Mead Wrisberg and Mead

1979 1985 1978 1977 1982a 1978

1979 1983 1984

1982b

1985

1981

1983

Dissertations Cashin Connell Crumbaugh

1983 1984 1980

Dummer (experiment 1) 1978 Eidson 1985

experiment 1 experiment 2 d

Ramsay 1979 Smultkis 1981

Sundstrom Wulf

Proceedings papers

Kerr and Booth

1979 1985

1977

l/2

l/2

1

l/2 2 2

2 2

1

3-5 92 - 5.8/6.8 203 m/f 3;4 36 m/f 7;2 72 m/f

12-14 48 - 8.3/12.5 64 -

7.3 80 m/f

9/11 120 m/f

7;6 64 m/f

(“) 72 m

6-7 48 m/f

6.6-7.3 40 m/f 6;ll 36 m/f 7;2 60 m/f

100 a 45 a

160 a,c 20 C

12 C

16 b 40 C

40 a,c

24 C

60 a,c

4 C

12 _

96 a,c 96 C

6.5-7.5 60 m/f 7;2/11;8 79 m/f

(Y 27 -

(‘) 72 -

6.4/10.9 6.4/10.9 6;4/21;1

3-4/5-6/

48 m/f 37 m/f

95 m/f

O-18 a 32 C

50 a

80 a,c

18 C

18 C

18 C

7-8/9-lO/ 11-12 120 m/f

6/8.5 48 m/f 11:8 106 -

40 C 40 a

120 a.c

1 7/9 36 - 16 -

+ -

-/+ - + + + + + +

_ ? + +

_ + -

-/-

+ _ +

+ -

-/+

?


4. Empirical support for the variability prediction

In the previous section, the number of studies of relevance to a proper evaluation of the variability prediction was decreased drastically by applying the criterion of improvement over practice trials. The remaining studies form the empirical foundation for the evaluation of the variability of practice hypothesis.

In discussing the equivocal results of studies on the variability of practice hypothesis various explanations have been put forward. In their review, Shapiro and Schmidt (1982) point to the relevance of taking the age of subjects into consideration. They distinguish between studies with adult and with child subjects. In ‘the present review, this distinction was also employed (see tables 1 and 2). The experiments

Notes to table 2:

Publ.: year of publication. Set: 1= included in Shapiro and Schmidt’s (1982) review; 2 = included in Lee, Magill and

Weeks’ (1985) review; empty cell: computer-search and up-date. Age: Indicated in years (7.6), years and months (7;6) or age-range (3-S). N: number of subjects involved in the statistical analysis. Sex: m/f (male and female in equal proportions); f (female only); m (male only); - (not

reported). Trials: the number of practice trials administered (‘crit.’ indicates that practice was performed

until criterion was reached). Evaluation of learning during practice:

a no-practice or (different type practice) control group; b pretest-posttest analysis; c training trials analysis; _ no evaluation procedure reported.

Learning during practice: + = analysis yielded significant effect ( p < 0.05); - = analysis yielded non-significant effect ( p > 0.05); ? = no results of a statistical analysis reported.

a Porretta’s (1982b) study involved 3 subgroeps, each consisting of 24 boys: (a) mentally retarded boys (CA 10 yr; MA: 6.5 yr); (b) MA-matched boys (CA 6.5 yr; MA: 6.5 yr); (c) CA-matched boys (CA 10.1 yr; MA: 10.1 yr).

b In Crumbaugh’s (1980) study, a group of 27 mentally retarded persons (mean CA: 28 years, range: 20-47) participated, of which the mean IQ was 29 (range: 9-65).

’ Trainable mentally retarded children participated in the experiment, in the age-range of 9 to 16 years of - chronological - age, with a mean mental age of 4.3 years.

d In Eidson’s (1985) thesis, two groups of subjects participated: a group of 24 mentally handicapped persons (mean chronological age of 19.0 years and mean mental age of 6.4 years) and a group of 24 non-handicapped schoolchildren (mean chronological age 10.9 years). Each group participated in both experiments. In the second experiment, 11 handicapped persons did not, however, reach the selection criterion for participation.

402 J.H.A. uan Rossum / Motor schema

with adult and child subjects are presented separately in the present paragraph (tables 3 and 4, respectively), making a separate evaluation of the variability prediction possible for adult and child studies.

A second explanation suggested in the Shapiro and Schmidt (1982) review involves the similarity between practice conditions and transfer task for each of the experimental treatments. If the experimental groups are different in this respect, a so-called proximity effect (Wris- berg et al. 1987) exists. To illustrate, suppose a study is carried out in which the variability prediction is tested in a throwing for accuracy task, and variability is manipulated through ball weight. Three groups are included in the experimental design, each performing an identical number of trials: one variable practice group and two constant practice groups. The variable practice group practises with six weights (210, 230, 250, 290, 310 and 330 g); one of the two constant practice groups employs only a weight of 230 g, while the other practises with a weight of 310 g. In the transfer task, a ball weight of 270 g is employed. If the effect of variable practice is examined in a one-way ANOVA with three levels, a proximity effect is evidently present, since the the mean weight used by the variability group is identical to the transfer weight (270 g), while that of the constant practice groups is less (230 g) or more (310 g) than the transfer weight. The interpretation of the results on the transfer task is difficult in this case, as the nearness of the transfer task is confounded with variability of practice. If a combination of the two constant practice subgroups into one constant group were analysed in a one-way ANOVA with two levels, interpretation difficulties would not have arisen because of a proximity effect. In the evaluation of experiments regarding the presence of a proximity effect the statistical analysis must play a central role. Each of the remaining experiments on the variability of practice hypothesis has been critically examined for the presence of a proximity effect. The results of this examination are included in tables 3 and 4. Each experiment suffering from a proximity effect is discarded in the evaluation of the empirical support of the variability prediction. In addition to the first threshold of progress during practice, now a second threshold is introduced: the similarity amongst experimental groups between practice conditions and transfer conditions.

As a third explanation for the equivocal results of the studies on the variability prediction, Lee et al. (1985) have suggested to consider the structure of the variable practice session. While the variability of


practice hypothesis, as originally formulated by Schmidt (1975), states that variable practice is more beneficial than constant practice, Lee et al. (1985) argued that a distinction should be made between random variable practice and blocked variable practice. This suggestion was implemented in the present review by presenting the experiments separately in which this approach has been explicitly put to the test (see table 5). Such experiments cannot be seen to address the original hypothesis, as only variability per se is examined. In a way, such experiments investigate a qualification of the original variability prediction, one which has been termed the ‘contextual interference effect’ (e.g. Shea and Morgan 1979). The presence of a proximity effect is indicated also for each of these experiments in table 5.

As a fourth factor in the interpretation of experiments on the variability prediction, the characteristics of the experimental task must be considered. For the experimental task to be an appropriate one, it should, according to Schmidt (1975), conform to at least two conditions: it should be ‘ballistic’ and ‘discrete’ (cf. the title of Schmidt’s original article) - as was indicated in the Introduction (section 1.1). The argument for the requirement of a ballistic or fast movement made it difficult to investigate recall and recognition processes separately in ‘slow’ movements.

In a discrete motor skill the beginning and end of an action are clearly defined. For example, throwing a ball, hitting a typewriter key and as an experimental task, knocking down a barrier, have that definition. If discrete actions are put together in a series, a serial motor skill is formed (e.g., hitting the six typewriter keys in order to form the word ‘schema’, performing a routine composed of different gymnastic skills, or knocking down a number of barriers in a particular order). In a continuous skill, the beginning and end points of an action may be arbitrarily defined (e.g., steering an automobile, tracking tasks), or they may be repetitions of identical actions (‘cyclic skills’). Similarly, swim- ming and running are considered continuous skills. The experiments included in tables 3, 4 and 5 are grouped according to the experimental task employed. In experiments on the variability prediction, various operationalisations of discrete skills have been used: timing tasks, coincident timing tasks, directional aiming, force production and missile projection tasks; a serial motor skill is found in the knocking- down-barriers task, while a continuous motor skill is found in tasks such as pursuit tracking and two-hand coordination.


Each of the experiments, relevant to evaluate the empirical base of the variability of practice hypothesis, is classified on the basis of the task employed, the experimental treatments (i.e., groups, differing in ‘practice’), and the results found in the statistical analysis, limited to ‘groups’ main effects and interactions in which the ‘groups’ factor was involved. Note that an indication of a significant ‘groups’ main-effect or interaction does not imply that a result is supportive of the variability of practice effect.

In the experiments, various dependent measures have been used in the statistical analysis: absolute error (AE), constant error (CE), the absolute value of the constant error (ACE), variable error (VE) and error (E, a composite score of AE en CE; cf. Schmidt 1982). The results of AE, CE and VE are shown in tables 3, 4 and 5. Occasionally, other measures were employed, often even in addition to the measures AE, CE and VE. In such cases, footnotes indicate which dependent variable was employed, or which results were obtained.

In conclusion, the variability prediction has been addressed in two ways. First and most frequently, the performance of a variable practice group is compared with that of a constant practice group. These experiments are described in tables 3 (adult subjects) and 4 (child subjects). Second, different amounts of variability are administered and compared to each other (e.g., blocked-variable vs. random-variable practice), and no constant practice group is included in the experimental design. These experiments are described in table 5. An experiment was considered relevant for an evaluation of the variability prediction if there was no indication of a proximity effect.

4.1. Variability of practice hypothesis: Adult subjects

The experiments in which adult subjects were employed are summarized in table 3. It should be noted that in the majority of studies provisions were taken by the experimenter to avoid a proximity effect. Six experiments showed such an effect and were discarded. The results of these experiments were equivocal regarding the variability prediction. In two experiments (Frohlich and Elliott 1984; Margolis and Christina 1981) support was claimed by the authors, in one (Johnson and McCabe 1982) the authors reported partial support, and in three (Cummings and Caprarola 1986; Melville 1976; Zelaznik 1977) no support for the prediction was obtained. The results of these studies are

J. H.A. oan Rossum / Motor schema 405

difficult to evaluate properly however, since the effect of variability is confounded with that of differential similarity of practice conditions to transfer conditions.

In the remaining 9 studies the results of 12 experiments on the variability prediction are reported. Two of these need further attention. In one it is difficult to determine whether a proximity effect was present (Elfaqir 1982); in this study a ball throwing task was used, in which variability was manipulated through ball weight, while ball size differed for the various weights. The results of this study are discussed, but they should be interpreted with care for the reason indicated. The second study is of special relevance, since the issue of proximity was the topic of investigation (Wrisberg et al. 1987). The task was to knock down a barrier with the arm in a specified movement time. Various experimental groups were included, each with its own requirements regarding movement distance and movement time. The results indicated that ‘transfer benefits of variable practice are ( . . . ) to some extent always determined by the similarity of training and transfer conditions of constant-practice subjects’ (Wrisberg et al., 1987: 374). The results of this study regarding the variability prediction itself are discussed below.

The relevant statistical results are discussed for each of the nine studies separately. In each experiment a discrete task was employed. In five studies, reporting seven experiments, a timing or coincident timing task was used; these experiments are addressed first. Next, the two studies employing a missile projection task and those using a directional aiming and a positioning task are discussed (‘aiming tasks’).

4.1.1. Experiments employing a timing task In six experiments a timing task was employed in which subjects had

to execute a movement of a specified duration. That is, they displaced a handle over a specified distance in a specified time. The experiments are discussed in chronological order.

In the Newell and Shapiro (1976) study, two experiments were reported. The first experiment involved two constant groups (practising a 70- and 130-msec movement, respectively) and one variable group. The latter was composed of two sub-groups, each practising the same duration (70 or 130 msec) for 30 trials, but differing in the order (respectively, 70-130 and 130-70). In each of these four experimental conditions, half of the subjects transferred to a lOO-msec duration,


while the other half transferred to 180 msec. On the transfer data various statistical analyses were carried out. A significant main effect was obtained on the fourth analysis, conducted on one of the transfer

Table 3

A summary description of all experiments using adults as subjects, in which improvement over

practice was reported and in which a constant practice group was included in the experimental

design (see text for explication and further interpretation).

Author(s) Task Treatment Prox. AE CE VE

Journal articles

Bird and Rikli (1983)

Cummings and Caprarola (1986)

experiment 2

Del Rey et al. (1982) a

Frohlich and Elliott (1984) b

exp. 1: ‘track A’

‘track B

Johnson and McCabe (1982) ’

Ker? (1982b)

‘distance error’

‘direction error’

Lee et al. (1985) a

experiment 1

experiment 2

Margolis and Christina (1981) d

‘analysis a’

‘analysis b’

McCracken and Stelmach (1978) e

‘analysis a’

‘analysis b’

Newell and Shapiro (1976)

exp. 1 ‘analysis a’ f ‘analysis b’

‘analysis c’

exp. 2 ‘analysis a’

‘analysis b

Wrisberg et al. (1987)

Dissertations

Barto (1986) experiment 1

experiment 2

Elfaqir (1982)

Melville (1976) s

Proceedings papers

Zelaznik (1977)

PO

ti

ct

tr

mp PO

vr, c (2), ctr, ct

vr (2), ctr, ct

ti vb, vr, c

ti vb, vr, c

da vb, c

ti vr, c (2)

ti vb, c (2)

ti vb (2), vr, vs. c

ti vb (3), c (3). ctr

mp mp mp

ti

PO

vb, c

vb (4), c (4) vb, vr, c

vr, fP, c, ct

+ _ -+ +

+ +

+ + _

+- ??

_ na _ na +

+-

+-

-+ +-

_-

vr, ctr

vr, ctr

vb, c-vb, vb-c, ctr

vb, c (2). ctr (2)

vb, c (2). ct

+- -

-+ * ++

- +- - +-

? + ++

+ +?

na

na

-+

na

na

+

+-

??

-+

-+

na

na

--

na

na

na

na

na +-

na

na

na ++

na

na

na -+

na

na

+

??

+?

-+ -+

na

na

-+

na

na

na

na

na

+-

+-

+-

na

++

-+


tests (the faster speed, 180 msec; thus involving half of the 96 subjects) and involving all four groups. The 70-130 variable practice condition was found to be significantly better than the 130-70 variable group

Notes to table 3:

Task: ct = coincident timing task; da = directional aiming task; mp = missile projection; po = positioning task; se = sequencing task; ti = timing task; tr = tracking task.

Treatment: (the experimental groups included in the design of the study) v = variable practice (VT = random; vb = blocked; vbr = blocked and random; vbi = blocked interpolated; vs = variable serial); c = constant practice; c-vb constant practice, followed by variable blocked; vb-c = variable blocked practice, followed by constant; ct = no practice of different type practice control group; ctr = control group, practising on the transfer task; fp = free practice. The number of similar groups is indicated between parentheses.

Prox.: proximity effect (‘-’ no proximity effect; ‘+’ proximity effect; ‘?’ proximity effect cannot be determined; ‘ * ’ investigation of the proximity effect).

AE, CE, VE: the results of a statistical analysis on the respective variable with respect to the ‘groups’ main effect (first row) or an interaction involving the ‘groups’ factor (second row): ‘ + ’ indicates a significant effect p < 0.05) ‘ - ’ a non-significant effect ( p > 0.05) ‘?’ result of analysis not reported and ‘na’ not applicable (i.e. not employed, or no analysis reported). A significant effect does not, however, implicate support for the variability of practice hypothesis.

The measurement ACE (absolute constant error) was employed instead of CE. The task is to ‘bimanually control the movement of a computer-displayed cursor along a track on a CRT-screen’ (Frohlich and Elliott 1984: 40); dependent variable is time to complete a track. Transfer tasks: track A and track B; track A was practised by the constant practice group, while track B was new to each of the experimental groups. One-way ANOVA’s were performed on the data of each of the transfer tasks. A one-way ANOVA was performed on each of the dependent variables. A total error score was employed, being similar to AE. Two analyses were reported, one on the first block of 5 transfer trials (‘analysis a’) and one on all four transfer blocks (‘analysis b’). Both an immediate and a delayed transfer test was administered; its effect was evaluated in one statistical analysis, in which the last three blocks of 10 trials were also included (‘analysis a’), involving each of the experimental conditions. A second analysis was carried out, pertaining only the transfer trial-blocks and the variable and constant practice group (‘analysis b’). Newell and Shapiro reported various statistical analyses on the data of experiment 1 and experiment 2. With respect to the first experiment the first, third and fourth analysis have been included in the table (the second analysis was excluded as it only concerned the variable practice groups); in the first analysis the factor ‘groups’ has 3 levels (1 variable, 2 constant practice groups), while this factor has 4 levels in the latter two analyses (2 subgroups of variable practice group, 2 constant practice groups), while the third analysis was carried out on one transfer task (slower speed) and the fourth on the other transfer task (faster speed). With respect to the second experiment both analyses were included. The first analysis of variance on the transfer data included all 20 trials, the second was (post-hoc) limited to the first five trials. The transfer test was administered a week following the second, and last, practice session.


and both constant groups. In the second experiment of the Newell and Shapiro (1976) study, a significant interaction involving the ‘groups’ factor was found in the analysis conducted on the first five transfer trials. This indicates ‘a tendency for some of the variable groups to reduce error over the initial five no-KR trials, whereas the group that trained solely at the 130-msec target tended to increase error’ (Newell and Shapiro 1976: 240). All in all, the results obtained in these two experiments are weakly supportive of the variability prediction. Varia- ble practice, experienced in a particular order is to be preferred (in the case of transfer) to a movement duration outside the range practised.

In McCracken and Stelmach’s (1978) study, one experiment was reported on the data of which two analyses were carried out. The first analysis involved the last three practice blocks, the immediate transfer as well as the 2-day transfer test. Two significant interactions were found, indicating that (for AE) the variable practice group improved somewhat from the last blocks of practice to the immediate transfer test, and the constant group showed a severe decrease. Similar scores were achieved by both groups on the 2-day transfer test. The second interaction (for VE) indicated that the superior performance of the constant group (compared to the variable group) on the last three practice blocks disappeared on the immediate as well as the 2-day transfer. On these occasions, both groups achieved nearly identical mean scores.

The second analysis was limited to the variable and constant groups and the transfer tests. For AE, a significant main effect was found, indicating that the variable practice group performed significantly better than the constant group. While the results of the first analysis provide only weak support for the variability prediction, the second analysis was clearly supportive.

In the Lee et al. (1985) study, two transfer durations were used, one inside (500 msec) and one outside (800 msec) the range practised (cf. Newell and Shapiro 1976). In the first experiment, the results of the statistical analysis paralleled each other. An ACE (absolute constant error) and VE significant ‘groups by blocks’ interaction was found for both dependent measures. No differences were observed on the ‘inside’ transfer test, but on the ‘outside’ test the random and blocked variable practice group performed significantly better than the constant practice group (for ACE). The random group on the other hand, was significantly less variable than both the blocked and constant group (for VE).

J.H.A. unn Rossum / Motor schema 409

In the second experiment, again a significant ‘groups by blocks’ interaction was found. The results did not confirm those obtained in the previous experiment, in the sense that the random group failed to out perform the blocked group. The latter showed a higher mean error score than the constant group for ACE, while for VE, only the blocked variable group showed a lower mean score than the constant practice group. In these experiments then, only partial support favouring the variability prediction was obtained.

In the study by Wrisberg et al (1987) the experimental groups were formed in order to compare the proximity of practice trials to transfer trials (or, the degree of similarity between task conditions on acquisition and transfer). With respect to the significant interaction involving the ‘groups’ factor on AE, post-hoc analysis showed that on the first trial block the three variable practice groups and one of the constant practice groups (the one that practised the transfer task) were significantly more accurate than the other three constant practice groups. On CE and VE measures, only a significant ‘groups’ main effect was found. One of the variable practice groups and the constant practice group, that practised on the transfer version, both had a significantly lower mean CE score than one of the other constant practice groups. For the VE score, the three variable practice groups and the constant transfer group had significantly lower mean VE scores than one of the constant practice groups. Although the authors claim that the findings provide support for the variability prediction, the results, firstly, are not identical for each of the three dependent measures, and secondly, particular forms of constant practice, other than practising the transfer task, apparently are as effective as variable practice.

In the coincidental timing study of Del Rey et al. (1982), subjects (only female subjects participated) had to ‘depress the button coincident with the arrival of the moving lights at the last lamp at the end of the runway’ (Del Rey et al. 1982: 109). Different speeds of the moving lights were used during practice, ranging from 5 to 13 mph. The transfer task speeds used (6 and 12 mph) were inside the range practised in the variable practice condition. The transfer trials were administered in two orders: a blocked version preceding or succeeding a random version. Two significant interactions were found in this study; one for ACE and one for VE. A significant third order interaction found for VE indicated that, at the slower transfer speed, the blocked-variable practice group was significantly less variable when


L/i 50_

i i i

Y NOV

40-

EXP

J BL RA

Experimental Group

Fig. 1. Graphical representation of significant ‘groups’ by ‘experience’ interaction. The means of absolute constant error (/CE/) for the 12 mph transfer task are depicted for the constant practice (CO), blocked variable practice (BL) and random variable practice (RA) groups. (Adapted from

Del Rey et al. 1982.)

starting with the blocked version of the transfer task than with the random version. The significant third order interaction for the ACE score indicated that, under the faster transfer speed, the novice subjects performed better than the experienced subjects after constant practice, while the effect was reversed after random-variable practice (see fig. 1). Variable practice apparently is most effective in expert subjects, while, for novice subjects, it appears indifferent whether random or blocked variable practice is offered. These findings provide limited support for the variability prediction, but offer the explicit suggestion that the advantage of variation in practice is dependent upon the level of proficiency of the subject.

In summary, the findings obtained in experiments involving a timing task with adult subjects provide limited support for the variability prediction. Variable practice is preferred to constant practice in the case of transfer outside the range experienced during practice. Further, the findings cannot be regarded as conclusive with respect to the most informative dependent measure. It was suggested that the subject’s level of expertise is relevant in evaluating the effectiveness of the type of practice.

4.1.2. Experiments employing an aiming task In the two studies to be described next (in chronological order) a

missile projection task (throwing a ball or a dart) was employed in each of the three experiments.

J.H.A. uan Rossum / Motor schema 411

Elfaqir (1982) designed a study in which 1,000 practice trials were administered on a ball throwing task for accuracy. In addition to a constant practice and a variable practice condition, two conditions were included in the design in which constant and variable practice were alternated (500 trials of constant practice, followed by 500 variable practice trials, or in reverse order). Following the practice trials, retention as well as transfer trials were administered. On the latter, no significant differences were found between groups. The findings of this experiment were, therefore, clearly not supportive of the variability prediction.

In two experiments reported by Barto (1986) subjects were asked to throw darts at either a moving target (experiment 1) or a stationary target (experiment 2). To qualify for the study subjects could not have engaged in darts competitively, could not have performed in any ‘throwing’ sport, and did not have parents who were or had been professionally involved in any sport. The findings of the first experiment indicated that the variable practice group had a significantly lower mean AE and VE score than the constant practice group. In the second experiment, the constant practice group was significantly better (that is, lower mean AE score) than the variable practice group. While the findings of the first experiment (with an open skill task) were clearly supportive of the variability prediction, those of the second experiment were not supportive at all. Constant practice was found to be more beneficial in the case of a closed skill task.

In Kerr’s (1982b) study subjects had to perform two-dimensional movements while being blindfolded. The movements were executed from the centre of a semicircle, in accordance with the distance and direction specifications of the experimenter. In addition to provisions to avoid a proximity effect, Kerr (1982b) computed the mean values of the target positions as they were actually performed by subjects in the variable practice and constant practice groups, thereby confirming the similarity of movement execution during practice. The results of this study were only partially reported in the Kerr article. With respect to distance, two main effects were found significant. The no-practice control group was reported to have significantly higher AE and CE scores than each of the other groups. On the direction measure, a significant groups effect on VE was reported to indicate that the group which practised on the transfer task was less variable than the variable practice group, but not significantly different from the no-practice


control group. The results reported by Kerr, therefore, do not, in this author’s opinion, sustain the conclusion that ‘the data in this study support a schema interpretation in the process of motor skill learning’ (Kerr 1982b: 250).

Bird and Rikli (1983) designed a horizontal, curvilinear positioning task in which subjects had to extend the forearm in a clockwise position and stop at a specified target position. In addition to variable vs. constant practice conditions, two further experimental treatments were employed. Subjects were asked to either physically practise the task, or to observe a model practising the task. A significant interaction was found, indicating that variable and constant practice were no different in the physical practice mode, but variable practice resulted in better performance in the modelling mode (and, perhaps not surpris- ingly, physical practice resulted in lower error scores in comparison to the modelling groups). Although Bird and Rikli claim that the results are favourable to the variability prediction (as variable practice was found to be superior), the present author would argue that, on the contrary, no support whatsoever was provided since physical practice did not result in differences between variable and constant practice.

In conclusion, the five experiments in which an aiming task was used as the experimental task appear to portray a negatively balanced picture: one supportive and four non-supportive findings were found with respect to the variability of practice hypothesis.

4.1.3. Conclusions Out of a total number of 48 experiments in which adult subjects

participated, only 12 experiments appeared to constitute the empirical base of the variability prediction. Of these 12 experiments, two were found to clearly support the variability prediction, six reported limited, weak or partial support, and four were found not supportive of the prediction. In general then, the empirical base of the variability of practice hypothesis appears rather weak in adult subjects. As well, the picture is not as clear as one might have expected, the lack of distinction undoubtedly caused by variations in methodologies employed in the various studies.

The grouping of studies by similarity of experimental task did not allow a more lucid conclusion. Because of the relative inconsistency of the findings, the variability prediction cannot be considered valid in all cases and must be qualified. In this context, a number of methodologi-


cal aspects were considered relevant by the experimenters: the level of expertise of the subjects (Del Rey et al. 1982), the choice of the transfer task (e.g., inside or outside the practised range; Lee et al. 1985), the order of presentation of variability (Elfaqir 1982; Newell and Shapiro 1976), open or closed skill (Barto 1986), and sex of subjects (Elfaqir 1982). None of these aspects has been investigated thoroughly enough to warrant conclusion yet.

4.2. Variability of practice hypothesis: Child subjects

The 14 studies, reporting 14 experiments, in which child subjects participated are described in table 4. In each of the studies a constant practice group was included in the design. An interesting aspect of this set of studies is that in some experiments two, and sometimes even more, age-levels were involved. Further, in some studies the subjects were mentally handicapped children.

The 14 experiments catalogued in table 4 are summarized in an identical manner as was done with the adult studies, describing the experimental task, the experimental conditions involved, and the results of the statistical analysis. In three experiments (Carson and Wiegand 1979; Ramsay 1979; Wulf 1985), a proximity effect was found. These studies were discarded in the further evaluation of the variability prediction. Further, in two studies (Kerr 1982a; Porretta 1982b) it was difficult to determine whether a proximity effect could have been present. In Kerr’s (1982a) study, the task was identical to the one in Kerr (1982b), discussed above - a two-dimensional directional aiming task, performed blindfolded; no specific distances and directions of target positions were reported, but only the range of the target positions of the variable practice group. In the study by Porretta (1982b) the subject had to kick a ball to a target at the top of an incline; the specific degrees of inclination were not reported.

The 11 studies remaining form the basis on which evaluation of the variability prediction with child subjects was made. The studies are discussed after having been grouped according to the experimental task employed. In each of the experiments a discrete task was used.

4.2.1. Experiments employing a timing task In two studies a coincident timing task was employed, in which

children had to tap a barrier at the end of the runway at the moment

414 J.H.A. “an Rossum / Moror schema

that the last light of the runway illuminated. Both studies were reported by Wrisberg and Mead.

In the first study (Wrisberg and Mead 1981) a significant main effect was found solely for AE, indicating that the constant practice group showed a significantly smaller mean error score than the control - no-practice - group. The variable practice group mean was between, but not significantly different from, each of these means. This finding does not support the variability prediction, rather it tends to contradict it.

In the second study (Wrisberg and Mead 1983), one control group (no-practice), two constant (practising, respectively, a slower (1.8 ms) and a faster (3.1 ms) speed) and two variable practice groups (random and blocked variation, practising 1.8, 2.2, 2.7 and 3.1 ms) were included in the design. Transfer performance was measured on the day following

Table 4

A descriptive summary of all experiments using children as subjects, in which improvement over

practice was reported and in which a constant practice group was included in the experimental

design (see text for explication and further interpretation).


Journal articles

Carson and Wiegand (1979) a

Kelso and Norman (1978)

Kerr (1982a)

‘distance’

‘direction’

Kerr and Booth (1978)

Moxley (1979)

Pease and Rupnow (1983)

Pigott and Shapiro (1984)

Porretta (1982b)

Wrisberg and Mead (1981)

Wrisberg and Mead (1983)

Dissertations

Eidson (1985) b

experiment 1

Ramsay (1979) ’ ‘ immediate transfer’

‘delayed transfer

Smultkis (1981)

‘immediate transfer’

‘delayed transfer’

Wulf (1985)

mp f P- da

mp mp fP

mp da

ct

ct

ti th

fP

w

vr, c, ctr, ct

vr, c, ct

vr. ctr

vb, ctr

vb, c

vbr, c, ct

vb (2), vr, c

vb, c, ct

vr, c, ct

vb, VT, c, ct

+ + _ +- ?

--

_ +? _ ++

_ +- ? ++ _ +- - -+

vr, c

vbr, c

- +- +

vb, c -

+- --

yb (2) vr, c (2) ct + +-

+ --

-- -- +? na

na

na

na --

-+

na

na na

na

na

++

+ +-

+- -- ?? -+ na

na

na --

-+

-+

na na

na

na +-


the last practice session and consisted of two tasks, differing in speed: ‘fast’ (3.6 ms) and ‘slow’ (1.3 ms). Two third order interactions were found for AE and VE (‘groups’ by ‘sex’ by ‘velocity’), while two significant second order interactions were found for CE (‘groups’ by ‘ blocks’; ‘groups’ by ‘velocities’). In general, differences between experimental groups were only apparent at the ‘slow’ transfer velocity: the constant-fast practice group scored consistently lower than the various other groups, yielding a complicated picture of significant differences. It was clear, however, that variable practice per se was not ‘better than’ constant practice: ‘The most beneficial training method appeared to involve varied-blocked speed practice’ (1983: 73). The results of this study give at most only partial support to the variability prediction.

Notes to table 4:

Task: ct = coincident timing task; da = directional aiming task; fp = force production task; mp = missile projection task; th = two-hand coordination task; ti = timing task.

Treatment: (the experimental groups included in the design of the study) v = variable practice (vr = random; vb = blocked; vbr = blocked and random); c = constant practice; ct = no- practice or different type practice control group; ctr = control group, practising the transfer task. The number of similar groups is indicated between parentheses.

Prox.: proximity effect (’ - ’ no proximity effect; ‘ + ’ proximity effect; ‘?’ proximity effect cannot be determined).

AE, CE, VE: the results of a statistical analysis on the respective variable with respect to the ‘groups’ main effect (first row) or an interaction involving the ‘groups’ factor (second row): ‘ + ’ indicates a significant effect ( p < 0.05) ‘-’ a non-significant effect ( p > 0.05), ‘7’ result of analysis not reported and ‘na’ not applicable (i.e. not employed, or no analysis reported). A significant effect does not, however, implicate support for the variability of practice hypothesis. It has to be noted that in each study the results of the statistical analysis refer to an immediate transfer task, except for the Wrisberg and Mead 1983) study where transfer was measured on the day following the last day of practice, while in two studies, in addition to the immediate test, a delayed transfer test was employed (Ramsay (1979): 1 week; Smultkis (1981): 24 hours).

a Performance is measured in terms of mean accuracy score; one-way ANOVA’s were carried out. Three transfertasks were employed: task A (column AE), task B (column CE) and task C (column VE).

b In the transfer phase, two tests were administered: a transfer test and a retention test. The order of administration was counterbalanced over subjects. The statistical analyses were carried out separately for each of the two transfer test orders. No significant results, involving the ‘groups’ factor, were obtained in the order retention-transfer. ‘Analysis a’ refers to the analysis for the transfer-retention order.

’ The variable measured is ‘total movement time’.


In Eidson’s (1985) study, a group of ‘moderately mentally handicapped’ (1085: 17) adolescents (mean mental age 6.4 years; mean chronological age 19.0 years) and a group of non-handicapped elementary schoolchildren (mean age 10.9 years) participated in the study. The experimental task was to match a specific movement time over a set distance. Two tasks were administered at the transfer phase: a real transfer task (i.e., a not practised movement time) and a retention task. Half of the subjects received the order ‘transfer-retention’, and the other half the reverse order. Statistical analysis (involving practice, transfer and retention trials) on the order ‘transfer-retention’ yielded a significant main ‘groups’ effect for AE, indicating an overall lower mean score for the variable practice group. On the VE score, a significant interaction involving the ‘groups’ factor was found on the transfer trials. The variable practice group had a lower mean score than the constant practice group. The influence of variable practice then, was only apparent on VE error and with the ‘transfer-retention’ order, and can thus be considered of limited support to the variability prediction.

Taking the findings of these studies together, only limited support was obtained for the variability of practice, as in two studies part of the results can be interpreted as supportive of the variability prediction, and in one contradictory evidence was obtained.

4.2.2. Experiments employing an aiming task Kerr and Booth (1978) had children of two ages (8 and 12 years)

throw beanbags to a target. Between the first and second testing a physical education program was offered, which was identical for each of the experimental groups. Practice in throwing (variable or constant) was only offered immediately before the two occasions that the transfer task was administered. A significant main effect was found on AE and CE, in each analysis indicating that the variability group had a lower mean score than the specificity group (practising on the transfer task). In the text only main effects are reported. From the results of two analyses of co-variance (pretest score as co-variate), as presented in table 1 (Kerr and Booth 1978: 399), it is apparent that the effect on AE is only significant for the g-year-old group, and the effect on CE for the 12-year-old group. The conclusion that ‘the superior performance of the schema group in the posttest data cannot be explained by closed- loop theory, but is consistent with a schema interpretation’ (1978: 400)

J.H.A. onn Rossum / Moror schema 417

is, therefore, only valid for the younger age group regarding the absolute error score and for the older group regarding the constant error score. The results of this study can be regarded as partial support for the variability prediction.

In the study by Moxley (1979) a significant ‘groups’ by ‘blocks’

interaction (on AE score) was found, indicating, firstly, superior performance in the variable practice group compared to the constant practice group and, secondly, improvement over transfer trials of the variable group while a ‘severe dropoff in performance’ (1979: 67) was observed in the constant practice group on the transfer task. The results clearly support the variability prediction.

In the study by Pigott and Shapiro (1984) a significant main effect was found on AE: one of the variable practice groups (practising blocks in random order) was significantly better than each of the other groups, indicating that constant practice was as effective as random variable or blocked variable practice. The study, therefore, did not support the variability prediction.

4.2.3. Experiments employing a force production task In three studies in which a force production task was employed

children had to push a ‘car’ along a linear trackway over a specified distance.

In the Kelso and Norman (1978) study two main ‘groups’ effects were found, for AE and VE. In both cases, the variable practice group outperformed the constant and control group, a finding which clearly supports the variability prediction.

In the study by Smultkis (1981), a main ‘groups’ effect was found for the AE score on the immediate transfer test: the variable practice group performed better than the constant practice group. This finding was not repeated, however, on the delayed transfer test. Nevertheless, the results of this study are supportive of the variability prediction. It should further be noted that no significant interaction was found, involving the factors ‘age level’ and ‘groups’, indicating that the difference between variable and constant practice condition on the immediate transfer test was similar for each of the five age levels.

In Pease and Rupnow’s (1983) study, a significant ‘groups’ main effect was again found on the AE score. The non-practice control group performed with significantly more errors than both the variable and constant practice groups, which did not differ. This finding, then, was clearly not supportive of the variability prediction.


In the study by Porretta (1982b) a task similar to a force production task was employed. The seated subject had to kick a small soccer-ball to a vertical target on top of an incline, using the non-preferred leg; the level of inclination could be varied. In addition to EMR boys, non-retarded groups were involved, matched on chronological (10 years) or mental (6.5 years) age. The significant ‘groups’ by ‘blocks’ interaction (on AE) indicated that the variable practice group performed better than both the constant and control group on the first block of five trials, while on the second block both the variable and constant practice groups outperformed the control group. The results give, therefore, limited support to the variability prediction.

In Kerr’s (1982a) study, a stylus had to be moved from the centre of a semicircle to a target position. The task was identical to that used by Kerr (1982b). Errors in distance and direction were analysed separately. Only on ‘distance’, and for VE was a significant ‘groups’ main effect found, indicating that the constant practice group was significantly less variable than the variable practice group. Although Kerr (1982a) interpreted the results as ‘certainly supportive of a schema view of learning’ (1982a: 223) pointing to the fact that both groups improved over practice, the results on the transfer task should, according to the present author, be interpreted as being contradictory to the variability prediction.

4.2.4. Conclusions From a set of 25 experiments, 11 experiments remained to evaluate

the empirical base of the variability prediction with child subjects. The 11 experiments provide equivocal empirical evidence for the variability of practice hypothesis, as three experiments were clearly supportive, four offered limited or partial support, two gave no supportive evidence and two even provided contradictory evidence. The findings of these studies are thus, at most, partially supportive of the variability prediction.

It should be noted that in four of the studies more than one age level was included, and in one, three subgroups of children were used to evaluate the influence of a general experience factor on the variability prediction. In each case a significant ‘age’ main effect was found, but no significant ‘age’ by ‘groups’ effect, suggesting that the effect of the type of practice is not dependent upon age or more generally, on proficiency level.


4.3. Random versus blocked variability of practice

In most of the studies on the variability of practice hypothesis, the variable practice condition was evaluated against a constant practice condition (cf. tables 3 and 4). In some other studies, the original transfer design is altered in favour of a design involving different degrees of variability (e.g. random variation versus blocked variation). These studies are considered in this section. In table 5 six studies are described, reporting seven experiments. The discussion of the results is grouped in accordance with the exprimental task. In five experiments a discrete task was employed; these experiments are addressed first. Next, the two remaining experiments are presented, one using a serial, the other a continuous task.

In the Del Rey et al. (1987) study, two levels of experience were distinguished: subjects with regular involvement in open sport skills and subjects with no involvement at all. The task was to press a button coincident with the onset of the last lamp of a series of lamps. Different speeds of the moving light were used. The transfer tasks were identical to those in the earlier study (Del Rey et al. 1982, described above). In addition to a regular blocked condition, a condition was included in which an interpolated task, throwing for accuracy, had to be executed after each trial. The analysis of the AE scores yielded a significant ‘groups’ by ‘experience level’ by ‘ transfer task’ interaction. Apparently, the random variable practised experts were better than their less experienced peers on the faster speed, while the slower speed experts, having practised in the blocked condition, performed better than their less experienced peers. The main effect for the ‘groups’ factor on CE score indicated ‘overshooting’ in the random variable condition, while ‘undershooting’ was apparent in both blocked conditions. The findings indicate that level of expertise is an important consideration when evaluating variations in the type of variable practice.

In the Goode and Magi11 (1986) study, badminton serves were practised by subjects who ‘were screened as to extended experience in badminton, raquet ball, or tennis’ (1986: 310). Following the acquisition trials, retention trials and transfer trials were administered. A statistical analysis (MANOVA), involving the last block of acquisition trials, the retention trial block and the transfer trial block, yielded a significant ‘groups’ by ‘block’ interaction. In follow-up ANOVA’s, this

420 J.H.A. unn Rossum / Motor schema

interaction appeared to be significant for one of the three transfer tasks. Thus, the three types of variable practice (random, blocked and serial variable practice) were not differentially effective to the par- ticipating novice subjects.

In her dissertation, Goode (1986) reported three experiments. In two (experiments 1 and 3) less experienced subjects participated (novices to open skill sport activities and inexperienced in throwing), and in one (experiment 2) expert subjects participated (experienced in open sport skills). In both experiments, the task was to execute a throw for accuracy so that the arrival of the trackway light coincided with the arrival of the ball at the target. As transfer tasks, four new speeds of the trackway were offered: two inside and two outside the range of practised speeds. Both the random and the blocked variable practice groups were subdivided on the transfer tasks. One-half of the subjects had the transfer trials administered in random order, while the other half received them in a trial block. In experiment 1, considering the four dependent measures (AE, VE, CE and E), a significant ‘groups’ effect was not observed. A significant ‘groups’ by ‘speed’ interaction

Table 5 A summary description of all experiments using adults or children as subjects, in which improvement over practice was reported and in which a constant practice group was not included in the experimental design (see text for explication and further interpretation).


Adult subjects

Journal articles Del Rey et al. (1987) a ct vb, vr, vbi _ -+ +- --

Goode and Magill (1986) mp vb, vr, vs _ -+ na na

Shea and Morgan (1979) b se vb, vr _ +- na na

Dissertations Goode (1986)

experiment 1’ ct vb, vr _ -+

experiment 3 ’ ct vb, vr _ +-

Whitehurst (1981) d tr vb, vr - na na

Child subJects

Journal articles none

Dissertations Connell (1984) e

‘analysis a’ ‘analysis b

mp vb, vr _

-+

J.H.A. uon Rossum / Motor schema 421

for VE was found, indicating that the random practice/random transfer group showed the highest VE score on the inside speeds, but were least variable on outside speeds. The reverse was true for the blocked practice/ blocked transfer group.

In the third experiment reported by Goode (1986), again no significant differences were observed between groups on AE, ACE and E (a composite score of CE and VE; Schmidt 1982). A significant ‘groups’ main effect was found, however, for VE: the blocked practice/blocked transfer group had a higher mean VE score than the variable practice/ blocked transfer group.

Notes to table 5: Task: ct = coincident timing task; mp = missile projection; se = sequencing task; tr = tracking

task. Treatment: (the experimental groups included in the design of the study) v = variable practice

(vr = random; vb = blocked; vbi = blocked interpolated; vs = variable serial). If more than one similar group is involved, this is indicated between parentheses.

Prox: proximity effect (‘-’ no proximity effect; ‘ + ’ proximity effect; ‘?’ proximity effect cannot be determined.

AE, CE, VE: the results of a statistical analysis on the respective variable with respect to the ‘groups’ main effect (first row) or an interaction involving the ‘groups’ factor (second row): ‘ + ’ indicates a significant effect ( p < 0.05), ‘-’ a non-significant effect ( p > 0.05) and ‘na’ not applicable (i.e. not employed, or no analysis reported). A significant effect does not, however, implicate support for the variability of practice hypothesis.

In addition to AE, CE and VE, the absolute constant error score (ACE) was analysed. The results for ACE were identical to those on VE: no significant ‘groups’ main effect nor a significant interaction involving the ‘groups’ factor. In this study, transfer tests were administered immediately (after 10 minutes) or delayed (after 10 days) - the effects were evaluated in one statistical analysis; preceding to the transfer tasks, a retention test was carried out on the tasks practised. The results included in the table are concerned with the transfer test. The statistical analyses were carried out on three variables: total performance time, reaction time and movement time. As the results of the variables ‘total time’ and ‘movement time’ parallel each other closely, only those on ‘total time’ were included in the table (column ‘AF). Instead of CE, the absolute constant error score (ACE) was analysed, the results of which are indicated in column ‘CE’. In addition to AE, ACE and VE, the error-score E (a composite score of AE and CE) was analysed. The results for E are identical to those on AE and ACE: no significant ‘groups’ main effect or an interaction involving the ‘groups’ factor. A pursuit tracking task was employed and time-on-target was taken as dependent variable; the results of the analysis are indicated in column ‘AE’. _ ‘analysis a’: a 2 (age) x 2 (sex) x 4 (group) x 2 (block) analysis of variance; the factor ‘group’ involved 4 levels: ‘random’, ‘blocked’, ‘organized’ and ‘non-organized’ practice. _ ‘analysis b’: a 2 (age) X 2 (group) x 2 (block) analysis of variance; the factor ‘group’ involved 2 levels: ‘random’ and ‘blocked’ practice.

422 J. H.A. unn Rossum / Motor schema

The findings of the two experiments reported by Goode (1986) suggest that, in general, no differential effectiveness is apparent for blocked and random variable practice, while the findings with respect to response consistency (VE score) are ambivalent.

In Connell’s (1984) study, a throwing for accuracy task was used. Children of two age levels paricipated. A significant interaction was found in a second analysis of the data. That analysis was limited to the two practice conditions (random and blocked). The ‘groups’ by ‘age’ interaction (for AE) indicated that the 11-year-old subjects performed better after blocked-variable practice, while the 7-year-old subjects did so after random-variable practice. These findings are again, suggestive of the importance of proficiency level in relationship to the effectiveness of the variability of practice.

The study by Shea and Morgan (1979) addressed the amount of variable practice in a serial task with adult subjects. The task consisted of knocking down barriers as fast as possible in a prescribed order. For both the dependent variables ‘total time’ and ‘movement time’ a significant main effect was found, indicating that the random variable group outperformed the blocked variable group.

Whitehurst (1981) examined the effect of type of variability in practice on a continuous pursuit tracking task. Adult subjects were selected who had no present or past regular recreational participation in any open sport skill. Task difficulty was manipulated through three different templates (circle, square, triangle); speed of the rotor was varied< during acquisition, and two new speeds were administered at transfer, one inside and one outside the practised range. Statistical analyses on transfer time-on-target showed that first of all, the circle template was the least difficult task at the inside rotor speed and secondly, that no significant results were found involving the ‘groups’ factor. Thus, the way in which variable practice was administered (random or blocked) apparently made no difference to the novice subjects.

In conclusion, six experiments were carried out on the effectiveness of the type of practice variation using adult subjects. The findings are equivocal and suggestive. On a discrete task, differences between random and variable practice are only apparent in expert subjects. In a serial task random variation appeared more effective than blocked variation. On the other hand, when a continuous task was used, no differences were found for novice subjects between these two varia-


tions. The finding that children of different age-levels benefitted differently from random and blocked variation is again suggesting that there is no simple answer to the question whether random or blocked variable practice is most effective. Although much more empirical work is necessary, the implication of the present findings is that experience must be considered as a relevant factor.

4.4. Empirical support of the variability prediction: Conclusions

To recapitulate briefly, 23 adult and 15 child experiments remained after the learning-during-practice threshold. These studies have been described in three tables. In the first two tables (tables 3 and 4) the studies were presented in which a variable and a constant practice group was included in the experimental design. These studies were considered to test the original variability of practice hypothesis. In the third Table (table 5) studies addressing the amount of variability were presented. Of the 17 adult experiments addressing the original hypothesis, 12 did not violate the ‘proximity’ threshold. A similar figure was obtained for the child studies: three of the 14 experiments had to be discarded for reasons of proximity. The empirical foundation of the variability of practice hypothesis thus does not appear as solid as is often claimed. And, if the ‘actual’ findings of this relatively small set of experiments are considered, the empirical base of the variability prediction becomes even less solid. In only two adult and four child experiments, supportive evidence has been clearly provided, while only limited support can be claimed on the basis of respectively, six and three experiments. It should further be noted that the results of six experiments were clearly not supportive of the variability prediction, while two child experiments yielded contra-indications to the variability prediction.

In a small number of studies, notably with adult subjects, the type of variable practice subjects participated in was specifically investigated. It would be tenuous to conclude from these studies that random variable practice is more effective than blocked variable practice. Of possibly more interest is the fact that the studies carried out to date signal the relevance of level of expertise.

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5. Conclusions and discussion

In this paper, one central aspect of Schmidt’s (1975) schema theory has been addressed: the variability of practice hypothesis. In the first review of the schema theory, Shapiro and Schmidt (1982) were con- vinced of the empirical foundation of the variability prediction: ‘So, clearly, in spite of the weight of the evidence that we have reviewed here that seems to support the theory, most of the work is related to variability in practice where solid support is usually found’ (1982: 143-144). In a more recent review by Lee et al. (1985) some qualification, notably with respect to the subject’s age, apparently was in order. According to Lee et al., ‘the variability of practice hypothesis being consistently supported when children comprise the subject population, while no firm consensus has been determined using adults as subjects’ (1985: 283-284). The present review casts doubt on each of the above statements. The empirical foundation appears not to be solid, and the varfability prediction has clearly not been consistently supported, with either adult or with child subjects.

A thorough literature search yielded a collection of original empirical research on the variability prediction. Compared to the database of the two earlier reviews, the present collection has a number of advantages. It contains many dissertations, which have not been included in the earlier reviews, and, thus allows a more balanced judgement on the empirical foundation of the variability prediction. Further, the present collection is considerably larger, not just because of its later date of appearance, but also because of the broader range of sources attended. Nevertheless, it is doubtful if the present database can be considered a population description, as not all dissertations and conference papers were adequately covered. The sample can, therefore, only be considered provisional.

In the present investigation, the evaluation of the empirical foundation of the variability of practice hypothesis yielded 63 studies, reporting 73 separate experiments. Forty-eight experiments used adult subjects and child subjects were present in 25 experiments. These studies were evaluated on improvement during practice. The first conclusion to be drawn from the analysis is that a large number of studies apparently could not be counted as addressing the variability prediction. A mini- mum requirement is that an observed learning effect must be considered a necessary condition for the establishment of the ‘schema rule’.

J. H.A. uan Rossurn / Motor schema 425

This criterion cannot be regarded as sufficient - as already remarked by Wrisberg and McLean (1984). In other words, even in the case that learning has been demonstrated to have occurred, it could also be that the training was insufficient. This argument might be applied when interpreting those studies in which no differences were observed between the experimental groups on the transfer task, even though improvement over practice was statistically ascertained.

However, the applicability of the ‘learning criterion’ per se might be discussed. No misunderstanding should be present on the scope of Schmidt’s theory as a motor learning theory. Schmidt (1975: 227) endorsed Adams’ (1971) concern for the learning of novel motor skills, separating the learning of new skills merely from the performance of already acquired skills. One might wonder, however, how learning should be demonstrated. As was presented earlier, the argument that groups with different practice show significantly different mean scores on a transfer task, is apparently not enlightening.

In their review, Shapiro and Schmidt (1982) present the thought that it is highly improbable that only a few trials could change an existing schema rule. They proposed a number of at least 1,000 practice trials. Application of this criterion would lead to the inevitable conclusion that only one relevant study has been included in the present database (Elfaqir 1982); and that study did not support the variability prediction. At the time of Shapiro and Schmidt’s review, no such study apparently was available. Shapiro and Schmidt did not discuss the lack of adequate empirical research in their 1982 conclusions.

Any criticism on specific aspects of research on the variability prediction should be evaluated against the more general background of learning research. The following ‘tetrahedral’ model is introduced with the intention of organizing the evaluation of research on the recall schema notion.

5.1. Evaluating learning studies: The tetrahedral model

With respect to the evaluation of learning studies, Bransford (1979) argued that account has to be taken of four factors, pertaining to both the learner and the learning task. A model such as this has became known in the field of memory as the tetrahedral model (e.g., Jenkins 1979). This approach is elucidating, since it offers an interesting picture of the research carried out on the variability prediction. According to

426 J. H.A. van Rossum / Motor schema

Bransford (1979), the following four factors have to be taken into account in an evaluation of learning studies:

(1) the characteristics of the learner: the skills, interests, purposes and knowledge of the subject at the moment of undertaking the learning task;

(2) the learning activities: the instructions, directions or apparatus, administered to the subject, suggesting to him/her, for example, the kind of strategy the learner might best be using, which will also depend importantly upon the way the learner expects to be checked on his/her progress;

(3) the learning material: the structure implied by the task (physically or psychologically), the modality to which the material is presented, the sequence of tasks, etc.;

(4) the critical tusk: the way learning or progress is measured using, for example, recognition, recall, transfer, problem solving (including the particular measurement taken as index).

In general, the variability of practice hypothesis specifically suggests a relationship between factors 3 and 4. The organization of the practice trials (constant or variable) is intended to be reflected in the performance on the transfer task. Such a relationship, it is here maintained, can only be evaluated appropriately if factors 1 and 2 are controlled (whether by experimental or statistical means). In their review of studies on the variability of practice hypothesis, both Shapiro and Schmidt (1982) and more recently Lee et al. (1985) explicitly confirm that the age of the subject (factor 1) is of relevance.

In the studies comprising the database of the analysis presented in this paper, various methodological suggestions and/or statements have been made about relevant factors in research on the variability prediction. These suggestions concern the general characteristics of the experimental task (e.g., an open or closed skill), the order of presentation of variability, and the transfer task inside or outside the practised range. The effectiveness of each of these suggestions cannot be determined, since thorough investigations are lacking. In the Lee et al. (1985) review, the number of practice trials was included in the tables summarizing the adult and child studies, suggesting that the amount of practice is of central importance. The adult and child studies support- ing the variability prediction, however, did not employ, an exception-


ally large number of practice trials in comparison to those that did not (cf. tables 1 and 2).

Another suggestion of concern was the level of expertise of the subject (factor 1: the characteristics of the learner). In addition to being explicitly controlled and/or manipulated in some studies with adult subjects, the level of expertise has been recognized by experimenters employing child subjects. In these studies different age levels and/or different levels of cognitive ability have often been included. Pro- ficiency level, however, should not be inferred from a rather general characteristic of the subject, but should preferably be assessed on the task at hand (Van Rossum 1987). In a number of studies, a first step has been taken by selecting and/or screening the subjects on the expertise (or, in some cases, lack of it) on sport-type activities similar to the experimental task (e.g. Del Rey et al. 1982; 1987; Goode 1986).

A complicating aspect in evaluating the variability prediction is the apparent controversy among experimenters about dependent measures. This issue can probably be seen as an example of those found in factor 2 of Bransford’s model. As an illustration of the measurement problem, McCracken and Stelmach’s (1978) study is generally (and also in the present review) regarded as supportive of the variability prediction, although in ‘analysis b’ (cf. table 3) significant results were obtained only for the AE score and not for CE and VE. As another illustration, in each of the two experiments on the type of variability, reported by Goode (1986), only one (VE) of the four dependent variables (AE, ACE, VE and E) yielded significant results (cf. table 5). These findings were considered, in the present review, to partially support the notion that random variable practice is more effective than blocked variable practice.

Schmidt (1975) explicitly opted for the AE score in his original presentation of the schema theory. One of his arguments was that ‘having two dependent measures in one experiment can allow opposite conclusions to be drawn’ (1975: 243). This argument apparently has carried little weight, although it is still valid (cf. tables 3 and 4). The question is not just of relevance to research on the recall schema notion; in fact, the optimal error score by which to judge motor performance has long been debated (e.g., Henry 1974; Newell 1976; Schutz and Roy 1973; Spray 1986). In numerous studies on motor performance, various error scores are reported without ever being properly argued by the experimenter that different dependent measures

428 J. H.A. uan Rossurn / Motor schema

are necessary. Apparently, the usage of various error scores seems to be justified more by their availability than by their appropriateness to the research question at hand. In the present review, no preference has been given to any one of the various measurements employed in the evaluation of the particular experiment.

With respect to factor 4 (‘the critical task’) an interesting phenome- non is the transfer task employed in most studies on the variability prediction. The motor schema refers to a class of movements. The class is determined by the generalized motor programme; the motor schema defines possible translations of the general motor pattern chosen (e.g., a throwing motion) into a specified movement execution (e.g., an over- hand throw, executed with a particular speed). The variability prediction is concerned with changes in the motor schema, not in the motor programme. It is, therefore, of special interest to determine the class of movements to which any particular schema ‘belongs’. This is of critical importance as it has implications for the appropriateness of the transfer task to be used in research on the variability prediction (Van Rossum 1980). In only two studies on the recall schema notion (Cummings and Caprarola 1986; Kaylor 1979) was the transfer task explicitly investigated in empirical terms. In most other studies, the transfer task appeared to have been chosen intuitively, that is, on the basis of its a priori similarity to the task used in the acquisition phase. Nevertheless, the transfer task has been recognized in various studies as a relevant factor in the experimental design: tasks were deliberately chosen inside and/or outside the practised range.

In retrospect, more care could have been given to the choice of transfer tasks. The choice should probably be based upon, and generated by, an appropriate task analysis. The importance and relevance of such a task analysis is clearly illustrated in a study on generalisation by Colvin (1981). ’ A programme to teach mentally handicapped persons to use a screwdriver was empirically evaluated. Colvin (1981) distinguished between five types of tasks, each type representing another level of generalisation. At the first level are programme tasks or tasks that have been extensively practised (comparable to the retention tasks

’ I wish to thank Dr. S.W. Keele who suggested Calvin’s (1981) study as ‘one of the best studies done of relevance to schema theory’; I agree wholeheartedly! The very nature of the searching technique employed in this paper prevented the unearthing of Calvin’s (1981) dissertation by the

author.


in the recall schema studies). Next, interpolation tasks, in which a screwdriver is used within the range of tasks practised in the programme (comparable to the inside transfer tasks in recall schema studies). At the third level are the extrapolation tasks, in which the screwdriver is used outside the range of tasks practised in the programme (comparable to the outside transfer tasks in recall schema studies). Then, tasks requiring general application. That is, tasks in which the screwdriver is used are different from those in the programme (e.g. turning the screw of an electricity socket). Finally, related tasks, or non-screwdriver tasks that involve pushing, turning and align- ing (e.g., opening a padlock).

In Carson and Wiegand’s (1979) study an underhand toss was required in a throwing for accuracy task to a horizontal target, using bean bags. Tossing a yarn ball to a vertical target was one of the transfer tasks. It seems clear that the choice of such a transfer task cannot be well argued without a proper task analysis. The fascinating aspect of Colvin’s (1981) study is that a thorough description of the task at hand (in terms of stimulus dimensions and characteristics) allowed him to differentiate the various levels of generalisation (that is, the specific characteristics of the tasks to be employed at each level). In this way Colvin was able not only to empirically determine the degree to which the teaching programme was effective in its aim - to teach a motor skill - but also to determine at which time in the teaching programme a particular level of generalisation was achieved.

In conclusion then, the variability of practice hypothesis is concerned with the relationship between ‘the learning material’ and ‘the critical task’ components of Bransford’s (1979) model. In general, the studies intended to test the variability prediction have not been found to effectively control the two other factors included in the model: ‘the characteristics of the learner’ and ‘the learning activities’. It follows, therefore, that the studies generally have been addressing a two-way interaction (cf. Jenkins 1979), while not taking into account the larger entity within which the particular interaction should be considered.

5.2. Towards first-generation questions?

As a more general conclusion to the present review it can be said that, what in the first instance might be construed to be a clear hypothesis with a seemingly simple experimental methodology, has

430 J. H.A. uan Rossum / M&or schema

given rise to little supportive empirical evidence. This might easily lead to the statement that, as a consequence, the extensive body of research directed to the variability hypothesis has resulted in very little progress. The original research question was formulated as: ‘is variable practice to be preferred to constant practice?‘. The review of studies on this question has not answered the question in the affirmative, but has in some cases, qualified the question. One such qualification was advanced by studies on the type of variability (random or blocked variable practice) preferred. Presumably such work was advanced on the supposition that the original question had been adequately dealt with. Another qualification concerns the proficiency level of subjects. That is, at what level of proficiency is variable practice preferred to constant practice? This question asks about the necessary conditions under which the variable practice prediction would prove to be val- uable. It it suggested, therefore, that after dealing with the original question, so-called ‘first-generation questions’ (cf. Zanna and Fazio 1982) need to be raised and investigated.

The variability of practice hypothesis must be considered an important means to provide empirical support for the motor schema notion, as envisaged by Schmidt. Of course, the very formulation of the original hypothesis (‘ . . . increasing either the amount or the variability. . . ’ (Schmidt 1975: 245)) could have taken its course in studies on the amount of practice. In fact, its translation into experimental design ascertained that the issue at stake was not the number of trials, but the organization of the trials; that is, the structure of the practice session(s). This latter interpretation has been taken to the extreme in studies in which various forms of variable practice have been compared (blocked variation, random variation, and/or blocked-random variation). Some of the methodological problems which were apparent in the research on the variability prediction, might present themselves here as well.

The central issue in the research on the recall schema notion and its variable practice corollary is generalisation, or, in Schmidt’s (1975) terminology, the ‘novelty’ problem. Practice under various cir- cumstances should be most beneficial to performance on new rather than earlier encountered situations. Although, according to the present review, little empirical support can be forwarded for this proposition, it would be a mistake to dismiss the importance of research on the question of learning and generalisation.

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Bartlett, F.C., [1932] 1977. Remembering: A study in experimental and social psychology. Cambridge: Cambridge University Press.

Barto, J.L., 1986. Variable practice effects on recall schema development for an open and closed motor skill. Unpublished thesis (Ph.D.), University of Pittsburgh, Pittsburgh, PA.

Bird, A.M. and R. Rikli, 1983. Observational-learning and practice variability. Research Quarterly for Exercise and Sport 54, l-4.

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