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Special Professor of Comparative Education, University of Nottingham
Department of Exercise and Sport Science
The “PlaySMART” research project that was designed to explore methods of promoting the knowledge and cognitive skills required for skilled performance in a Physical education context. The following article outlines some early findings from that research and shares some of the methods and techniques developed in that context. I would like to claim at the outset of this article that the motivation for writing this was a lifelong commitment to teaching and lecturing in physical education and sports coaching however it is more likely that it derived from my concern with helping my two sons (who fortunately are as passionate about sport as I am) to become smart and effective performers in a range of contexts within and beyond the playing field.
Most, if not all, education agencies would list the development of skilled performance as being of their main goals. For example the UK National Curriculum (NC) (1999) stated that effective problemsolving, which is often seen as being synonymous with skilled performance, was a key learning objective for key stage 4 pupils (i.e. about 16 yrs old). Despite frequent encouragement to prioritize the development of these kind of cognitive skills in schools there is little evidence that otherwise bright young students arrive at university ready to take responsibility for solving their own problems. Literature concerned with problem solving, particularly in practical contexts, suggests that skilled performance is actually a complex phenomenon with multiple components. These include technical and physical dimensions as well as appropriate knowledge and the various cognitive and interpersonal skills used to develop and employ these. (Griffin & Placek, 2001).
During the latter part of the 20 th Century the teaching /learning approaches most commonly experienced by learners in all subject areas including Physical Education were characterised by a preoccupation with the development of narrowly defined techniques whilst the cognitive aspects of performance received very little attention.
Holt, Strean, & Bengoechea, (2002) argued this approach was not adequate and advocated for pedagogy that was based on an integrative and holistic model of skill that saw all performance components as being fundamentally interrelated i.e. with a change in one being reflected in a reciprocal effect upon the others. As such, rather than maintaining an isolated focus on one single component, Holt et al claimed that in order for them the be ecologically valid and authentic both the cognitive and the motor control components must be developed at the same time. However, whilst all components should be acknowledged as important contributors of skilled performance, they do not seem to be equally significant in determining expertise. Research by French and Thomas (1987) indicated that the maximum discriminator between the performances of expert and novice children was actually their knowledge and cognitive skills rather than any physical component.
Brooker, et al., (2001) suggested that by acquiring appropriate knowledge and cognitive skills rapid improvements in performance could be achieved. If this is true, then by prioritising the acquisition and use of problem solving knowledge learners could be placed in the motivating position of experiencing immediate improvements in their performance. Obviously in order to facilitate this kind of learning, as the N.C. UK (1999) requires them to do, it is necessary for teachers to be certain about the nature of the knowledge and cognitive skills involved. Whilst they are listed as desirable teaching aims the N.C. UK (1999) documentation is not sufficiently clear to provide teachers with appropriate guidance here.
A key goal for the PlaySMART project was therefore to develop clear definitions for the kinds of knowledge and the cognitive skills involved before going on to develop appropriate teaching and learning methods. Whilst this was done with physical education “problem solving” contexts specifically in mind, it was also designed to provide opportunities for that kind of learning to be transferred to enhance “performances” across the curriculum. The literature suggests that it is not just the quantity but also the nature and organisation of the knowledge and the cognitive skills, which provides experts with an advantage during problem solving (Turner & Martinek,1999). The following section attempts to summarise this information.
Figure 1. Newell (1993)
Figure (1) above adapted from Newell’s research articulates the general content of problem solving knowledge. This suggests that performers should know what must achieved (the goal), the kind of conditions (environment) that must exist for goal achievement opportunities to exist and the movement patterns (action) the performer is capable of executing that could be used to create and exploit those helpful conditions.
Anderson and Krathwohl, (2001) revised Benjamin Bloom’s work (1956) to produce a taxonomy, (see below) that is useful tool both for the planning for and the assessment of problem solving. The matrix produced by the interaction between both dimensions implies that expertise involves an ability to remember, understand, apply, analyze, evaluate and even create, as appropriate, problem solving knowledge which in turn could take four different forms i.e. as facts, concepts, procedures and the product of metacogntition.
Figure 2. Anderson and Krathwohl's revision of Bloom's Taxonomy
In a physical education context the kind of factual information a problem solver would need would include playing goals and any constraints laid down by the rules that might limit the action they could take whilst attempting to achieve these. In team games, goals are usually described in terms of the repositioning of the game object, often a ball, into a new more favourable location. Of particular importance here is the ability of experts to break up the main problem into smaller tasks and thereby develop associations between different problem contexts and the achievement of an appropriate sub goal. For example, in football these contexts could involve the creation or denial of a scoring chance on attack or defence respectively or the changing of roles during the transition between these contexts. ( Bell & Penney 2004).
Cognitive literature offers three key ideas that help differentiate between merely knowing and being able to replicate a fact or instruction and conceptual knowledge. Piaget (1978) proposed the idea that it was possible to remember and replicate a fact, i.e. to have knowledge, without understanding it. On the other hand if that fact could be explained and justified then some degree of understanding existed. In addition, when potentially viable solutions were proved, subsequently, to be inappropriate, they would be in a position to diagnose and explain why these failed to help them. Perkins & Salomon (1992) argued that transforming factual knowledge into conceptual terms enabled performers to adapt it to so that it could be used to solve problems beyond the context in which they were first encountered. Finally, Zazkis (1998) suggested that understanding was a developmental process that involved the assimilation, over time, of increasingly rich, inter connected and abstract schema and that these qualities that allowed conceptual knowledge to be used flexibly.
Procedural knowledge involved in practical problem solving might be defined as information as to how concepts could be used to solve a given problem. Experienced problem solvers are in the memory efficient position of being able to chunk together goal condition and action concepts into principles, which they could use flexibly to solve all variations of an appropriate problem category. Grehaigne, Godbout & Bouthier (1997). The most frequently referenced research relating to problem solving knowledge is Anderson ’s work on the “Acquisition of cognitive skill” (1982). He proposed the “If-Then Production” theory in which a “production” solved a problem by offering the performer an appropriate association between the goal, certain problem conditions and a possible course of action.
Finally metacognitive knowledge relates to a selfawareness and deliberate regulation of the cognitive process that the problem solver has used in connection with their own performance.
During the last century the “traditional” methods of teaching most commonly employed in all educational sectors were at the didactic / command end of the teaching learning spectrum. The knowledge that was promoted via this traditional approach was generally limited to easily articulated facts and concrete (context specific) instructions, possibly because these were viewed as being relatively straightforward to teach. In addition, all too often, the only cognitive processes that were assessed as part of this teaching/learning approach were the ability to remember and replicate these facts or instructions. (Ericson, 1996; Rink, 2001).
When “real life” (sports) problem solving contexts are analysed it is possible to identify, a finite number of types of problems that recur with more or less frequency. However, typically these kinds of problem solving environments change in dynamic fashion so that the way in which these problems are configured varies constantly. In these circumstances, context specific instructions become redundant as soon as the problem for which they were intended is reconfigured either by accident or as is more likely by tactically aware opponents. It could be argued therefore that learners, who have experienced only “traditional” teaching methods, are likely to have been denied opportunities to develop this knowledge and associated higher order cognitive skills. As a consequence many otherwise bright pupils may have left school unable to solve problems for themselves. It is worth emphasising that Anderson and Krathwohl argued that problem solving expertise requires all the cognitive processes and all the categories of knowledge referred to in their taxonomy. As such they argued that effective pedagogy would enable the learner to “tick all the boxes” in their matrix.
PlaySMART was designed to develop all of these cognitive learning outcomes within the context of programmes made up of three kinds of (sports related) problem solving tasks:
- Core Tasks. These are usually simplified adaptations of major sports i.e. 5 v 5 socer or 7 a side Rugby that provide an easily identified context for subsequent learning.
- Brain games. These are rather abstract thinking skills challenges that are designed to “warm up” learners brains and warn them that thinking will be required and valued in subsequent activities.
- SMART challenges: These are small sided, practical interactive challenges that usually require learners to collaborate within a competitive environment to solve a problem that clearly relates to the core task. Whilst these are designed to promote types of problem solving knowledge and cognitive processes that might generic in nature the “authenticity” of the task in terms of how learning can be transferred to enhance performance in the context of the core task is emphasised throughout.
A SMART problem-solving Task
An example of a SMART problem solving task is described below. (See Figure 3). This activity used for testing purposes was based on an Asian game called Kabbadi but was introduced to the participants as part of a developmental programme designed to help learners to develop an understanding of effective performance at a point of transition in an invasion game such as basketball.
Figure 3. The Kabbadi challenge
The game challenges an attacker to enter a square defensive area through one side (designated as the entrance/exit). In the testing sessions the square was marked out with non-slip mats or small cones. Within a time limit, the attacker has to tag one of two “defenders” located in this box and run back to a target mat located ten metres outside this box before the other defender can tag him back. The defenders are constrained in their response by a series of rules.
First defenders are not allowed to leave the box or attempt to tag the attacker until one of them had been tagged first! However, when one defender has been tagged their teammate is then allowed to leave the defensive area to chase the attacker. Second, the defender who was tagged is not permitted to tag the attacker back or leave the box. This defender is therefore reliant upon his teammate to chase the attacker and thereby prevent the opposition from scoring against their team.
Learning within these PlaySMART tasks is supported via specific pedagogy . One component of this is called the “S.M.A.R.T” planning system which was based on cognitive acceleration research by Adey and Shayer (1994). The “SMART” acronym stands for the five stages of the process “Situation”, “Methods”, “Adaptation”, “Reduction” and “Transfer” respectively, through which learners are “scaffolded” via a structured system of questions to analyse and improve their own and their teams’ problem solving performance in the context of specific practical challenges. ( Bell and Penney, 2004). This SMART scaffolding system would typically take the following form: In the first section labelled “Situation” performers collaborate with team mates to identify the task and key enabling goals and to gather facts about any constraints laid down by the rules of the game, as to how, when and where they may legally position or move themselves or the game object e.g. the ball. Also they would be required to audit the problem solving “tools” both technical and cognitive that they could currently to solve the problem.
(Rink, J.E. 2001). In a P.E. context these might be problem variables, constraints, relationships, positioning and movement sequences and pathways ( Bell and Penney 2004). Finally mentors would establish a shared terminology to ensure that they and the performers are able to communicate effectively whilst analysing and evaluating performances.
The next component of the “SMART” system encourages learners to develop ways of improving on their initial attempts. This requires performers to be given the opportunity to make judgments about the relationships they are creating, between key game variables i.e. themselves, their opponents and the game object. This process involved experimentation and a gathering of “intelligence” (i.e. of different performers’ abilities relative to their own).
Such experimentation inevitably leads to errors, however, rather than being a problem these mistakes are seen as a vital part of skill development. Unfortunately, as Rink, J.E. (2001) pointed out, learners all too often encounter a teaching environment, where, because it is premised on the exact replication of instructions, errors are consistently criticised.
In the “Adaptation” section, via a process termed “Cognitive Conflict” by Adey and Shayer, learners are deliberately presented with ideas that challenge their existing and possibly superficial or partial knowledge. The objective here is to encourage them to accommodate alternative and apparently contradictory information. Vigotsky (1978) recommended that learners in this state of conflict could be “scaffolded” so as to compare and contrast apparently alternative solutions to uncover any concepts held in common.
By deliberately engineering conflicting views in the context of group problem solving participants are encouraged to go beyond concrete thinking. However encouraging group members to challenge each others points of view as part of this problem solving process may be very challenging, even threatening, for group members who lack social confidence or who feel they do not have the necessary expertise. As such this dialectic style of teaching demands that more “expert” thinkers (that can be both peers as well as teachers) deliberately facilitate discussion and find ways of accommodating different views within discussions including those of the less able.
The “Reduction” section in SMART encourages learners to synthesise or “Chunk” together related goal, condition and action concepts into one exemplar movement pattern. In this way all relevant information is “reduced” to be represented as a team game principle that they could use both for planning and subsequently for review purposes i.e. For example, the expert defenders in the Kabbadi example are usually able to construct the following team game principles:
The SMART planning process is concluded when performers “Test” their own ability to employ these tactical principles within the context of the SMART game and if possible to “Transfer” their thinking to solve other related but possibly more complex problems. Critically, successful problem solving depend upon individuals willingness and ability to remember to implement this kind of knowledge and and subsequently reflect and review how well they did this. As such it could be argued that the development of metacognition i.e. the performers awareness of themselves as a learner and practitioner is the ultimate teaching and learning goal.
As McGuiness (1999) pointed out effective thinking appears to involve both a “will” as well as a “skill” adding that taking responsibility for the making and monitoring of performance decisions appears to be much more effortful and memory intensive than just following a coach or a teacher’s instructions.
Motivating learners to want to take responsibility for their own problem solving appears to be considerable importance here! With this in mind, the tasks used in the PlaySMART programme have been designed to be enjoyable, relevant and engaging as well as developmentally appropriate for a range of learners. The research evidence we have to date suggests that, whilst initially challenging students’ confidence and feeling of self worth and competence are generally enhanced when (even with a significant amount of teacher “scaffolding”) such challenges are eventually met.
Learners who are able to take responsibility for solving their own problem appear to have a critical advantage over those who merely wait for instructions, because they are able to work creatively and flexibly in response to changes in the nature of the problems encountered. As a father my ambition for my two boys is that they become smart enough to solve their own problems not only as contributors within the developing UK “knowledge economy” or even as participants in a sporting event of their choice but also, eventually, within the contexts of their own families. However, the development of this kind of expertise appears to be a far from simple process. Problem solving literature indicates, and this is confirmed my own research, the need for sophisticated teaching and learning methods that deliberately target in a holistic fashion appropriate cognitive processes as well as subject knowledge. The delivery of this kind of pedagogy has in turn, serious implications for both initial and continuing professional development.
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