Classifying the Interventions with learning sklills




 Classifying the Interventions
A typical way of classifying interventions is on the basis of their supporting
theories, but too often such theories are either ambiguous or not mutually exclusive. For example, as already noted, there are many variations on the metacognitive
theme, and most theories of intervention now refer to a metacognitive basis. These
variations involve self-regulation in some form or another, although some interventions in the recent literature are eclectic or atheoretical.
An examination of the thrust or purpose of an intervention is a fruitful way to
identify what parameters that particular intervention aims to change: performance,
attributions, self-concept, motivation, attitudes, study skills, and so on. These are
examined in the present study. Of course, like supporting theories, they are not
mutually exclusive, as many interventions are aimed at changing several dependent variables simultaneously.
It would be desirable to classify interventions in mutually exclusive terms that
relate to the nature of each such intervention.


 In other words, we would like to
classify interventions in terms of their independent variables rather than in terms
of their effects on dependent variables. Such a classification might refer to the
structural complexity of interventions and whether they are intended to achieve
near or far transfer. The so-called SOLO taxonomy (Biggs & Collis, 1982),
described in the following section, has been used to order the structure of responses. Because this taxonomy is based on structural complexity, it may readily
be adapted to suit the present case.
The SOLO Taxonomy: A Hierarchical Model of Learning Outcomes
Biggs and Collis (1982) started from a study of learning outcomes in (mainly)
high school content domains and found that students learn quite diverse material
in stages of ascending structural complexity that display a similar sequence across
tasks. This led to the formulation of the SOLO taxonomy, where "SOLO" is an
acronym for "structure of the observed learning outcome." This taxonomy makes
it possible, in the course of a student's learning a subject, to identify in broad terms
the stage at which the student is currently operating.
The following stages occur.
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Hattie, Biggs, and Purdie 


* The student engages in preliminary preparation, but the task itself is not
attacked in an appropriate way (prestructural).
* One (unistructural) and then several (multistructural) aspects of the task are
picked up serially, but are not interrelated.
* Several aspects are integrated into a coherent whole (relational).
* That coherent whole is generalized to a higher level of abstraction (extended
abstract).
The SOLO model is readily generalizable, and we use it here to provide a
convenient and exclusive system for classifying interventions intended to enhance
learning, as is explained and illustrated below.
The present classification begins with the unistructural and not the prestructural
stage, as the latter by definition refers to an intervention already expected to be
unsatisfactory.


 An example might be an intervention based on an unacceptable
and undeveloped theory base, such as learning in the presence of "good luck"
tokens (which may be an interesting question but is not one in which we are
interested here).
(1) Unistructural. A unistructural intervention is based on one relevant feature
or dimension. An example might be an intervention focused on a single point of
change, such as coaching on one algorithm, training in underlining, using a
mnemonic, or anxiety reduction. The target parameter may be an individual
characteristic or a skill or technique. 


The essential feature is that it alone is the
focus, independently of the context or its adaptation to or modification by content.
A typical example of a unistructural intervention is that reported by Scruggs
and Mastropieri (1986a), in which a trained experimenter taught students to use a
mnemonic strategy for learning information that is not immediately meaningful
and which has an abstract, numerical component. In this instance, the material to
be learned was the hardness index, from 1 to 10, for each of eight minerals. The
content to be learned, however, could just as easily have been drawn from any
subject area. There were three experimental conditions involving use of mediating
keywords based on imagining pictures linking the numbers indicating hardness
(e.g., "one is a bun") with codings of the minerals (e.g., "actor" for the mineral
actinolite) in high-, medium-, and low-structure conditions (ranging from supplied
to self-generated keywords and pictures), and a control condition. Here the
experimental conditions were procedurally simple and direct,


 involving essentially one technique (mnemonic) aimed at accurate recall.
(2) Multistructural. A multistructural intervention involves a range of independent strategies or procedures, but without any integration or orchestration as to
individual differences or demands of content or context. Examples include typical
study skills packages taught directively, without a metacognitive or conditional
framework. An example is provided by Haslam and Brown (1968), who taught the
Brown-Holzman Effective Study Skills Course: High School Level to high school
sophomores in twenty 55-minute class periods. The course involved better time
utilization, reading and writing techniques, techniques for preparing for and
taking examinations, realistic goal setting, student-to-student tips, and the like. In
short, it was a typical study skills course. A basic assumption is that all the "study
habits" are detachable, teachable, and usable across the board in many school
subjects, resulting in greater increases in grade point average than would be found
in a control group. Instrumentation included manuals and workbooks developed
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Effects of Study Skills Interventions
by Brown and Holzman over several years prior to the study in question.


 It is
considered multistructural because it comprises a range of skills taught directively.
(3) Relational. All the components in a relational intervention are integrated to
suit the individual's self-assessment, are orchestrated to the demands of the
particular task and context, and are self-regulated with discretion. Metacognitive
interventions, emphasizing self-monitoring and self-regulation, would fit into this
category, as would many attribution retraining studies. For example, in Relich,
Debus, and Walker's (1986) study, a group of sixth graders identified as "learned
helpless" and deficient in arithmetic skills were given attribution retraining followed by manipulated success rates in division exercises, so that the beliefs about
success and failure set up by the retraining were directly reinforced by the
manipulated performances.
(4) Extended abstract. In an extended abstract intervention, the integration
achieved in the previous category is generalized to a new domain. Interventions
with this thrust would be those aiming for far transfer. In theory, Feuerstein's
(1969) Instrumental Enrichment program is an example and was the only one we
could find in this category.
Instrumental Enrichment was initially developed to cater to the learning needs
of culturally and economically deprived adolescents who were failing at school.
Its emphasis is on active student participation, with much independent work and
discussion, concentrating on basic cognitive processes, problem solving tactics,
and motivational factors. Curriculum content is deliberately excluded; instead,
there is an emphasis on teaching thinking about thinking, learning about learning,
and cognitive and metacognitive processes. There is a battery of curriculum
material with titles such as "organization of dots," "analytic perception," "orientation in space," "family relations," "comparisons," "classification," "numerical
progressions," "stencil design," "temporal relations," "transitive relations," and
"syllogisms." These exercises are aimed at nurturing learning sets and systematic
data-gathering behavior, developing skills in comparative analysis to improve
relational insights, and removing attitudinal inhibitions that often operate in lowachieving adolescents. It is claimed that none of the Instrumental Enrichment
tasks are designed to "teach to the test."
The Feuerstein packages are classified as extended abstract on the grounds that
the intervention aims to produce structural changes in an individual's cognitive
functioning to the point where autonomous or independent learning can occur.
The Instrumental Enrichment exercises are designed to develop specific cognitive
and metacognitive skills necessary not only for success in tests of general ability
but also in everyday classroom tasks that require the student to apply abstract
principles such as those relating to perception, reasoning, planning, communication, efficiency, elaboration, organization, and relationships.
The interaction of transfer and the SOLO taxonomy. A program may aim to
enhance performances that are either closely related or distantly related to the
training tasks. The former kind of transfer is called near, and the latter kind of
transfer is calledfar. 


Whether a program aims at near or far transfer is independent
of its structure in SOLO terms, although the question of near and far transfer
interacts with this taxonomic system. Unistructural models may, in theory, aim at
near or far transfer, but direct training in a single skill is generally in the context
of near transfer. Multistructural and relational models can readily be applied to
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Hattie, Biggs, and Purdie
situations testing near and far transfer. Multistructural models are frequently
constructed on the assumption that providing students with a wide range of study
procedures would enable them to operate effectively in a wide range of situations,
in the typical study skills training format. Relational models are most frequently
focused on the context in which they are used, but if the individual acquires
strategies and the conditional knowledge of when and where they might work,
some degree of far transfer might be expected. Extended abstract models, in being
involved with learning how to learn, for example, are essentially concerned with
far transfer.

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