Daily Archives: February 27, 2010

Implications of cognitive theory for instructional design

The following is a summary/reflection of Winn (1990), the abstract follows

This article examines some of the implications of recent developments in cognitive theory for instuctional design. It is argued that behavioral theory is inadequate to prescribe instructional strategies that teach for understanding. Examples of how instructional designers have adopted relevant aspects of cognitive theory are described. However, it is argued that such adoption is only a first step. The growing body of evidence for the indeterminism of human cognition requires even further changes in how instructional designers think and act. A number of bodies of scholarly research and opinion are cited in support of this claim. Three implications of cognitive theory for design are offered: instructional strategies need to be developed to counter the reductionism implicit in task analysis; design needs to be integrated into the implementation of instruction; designers should work from a thorough knowledge of theory not just from design procedures.

Summary

Suggests problems arise when decisions within instructional design are driven by cognitive theory, not behavioural. Mostly around the assumptions of rationality and predictability and the subsequent appropriateness of the traditional teleological design process used by instructional design. Suggests some approaches/implications that might help address these somewhat.

Reflection

The ideas expressed here offer support for the ideas I’ve been formulating about how to improve learning and teaching at Universities. Which obviously means I think it is an important bit of work by an intelligent person. It probably does have flaws. Will need to read and reflect more.

Still not sure that these principles have been applied broadly enough (though the conclusion seems to indicate yes). Winn has focused on changes to the practice of instructional designers in how they approach design without talking about how they may have to change how they work with the academics. Instructional design, for me, is as much about staff development as it is about design, at least within the current university context. Instructional design within universities can’t scale unless it builds capacity amongst the academic staff and the system to help in design.

Many of these limitations of instructional design are similar to those I’ve been trying to push around the institutional implementation of e-learning and more generally about approaches to improve learning and teaching e.g. graduate attributes.

Introduction

Starts with a definition of instructional design from Reigeluth (1993) – essentially it is a set of decision-marking procedures which, given the outcomes to be achieved and the conditions under which they are to achieve them, develops the most effective instructional strategies.

Generally done with analysis of outcomes/conditions, selection of strategies, iterative testing until some level of success achieved. The decisions are guided by instructional theory.

Gives examples of instructional design processes informed by cognitive theory.

Suggests evidence that cognitive theory is impacting thinking/actions of instructional designers, however, suggests that cognitive theory requires further changes in the way they think/act. Has problems with the analysis and selection/testing stages. Current approaches are not sufficient.

Suggests that instructional design should be driven by an understanding of theories of learning and instruction, rather than mastery of design techniques.

I’m assuming here he means that the type and nature of the steps within design process itself should be informed by these, not what he also recognises is that the decisions made within these steps are already driven by this. I’m a bit slow this morning.

Instructional design and behavioural theory

Supports/explains the notion that instructional design originated in behavioural theory, the dominant learning theory of the time when ID originated. Shows how instructional design processes evolved to fit the needs of behavioural theory. Examples include the reductionist nature of task analysis and pilot testing being sufficient to debug instruction that consisted of stimulus-response prescriptions. i.e. behavourists did not consider that there were “mental operations” within the learner that might mediate between stimulus and response. This resulted in design being separated from implementation.

If instruction can be developed to the point where acceptable student performance is likely to occur, then it matters little whether instruction is implemented immediately after the designer has attained this standard, or at some later time and in some other place.

Connects with literature that acknowledges the separation (Richey, 1986), thinks it creates problems (Nunan, 1983, Streibel, 1989, Winn, 1989) and others which think it desirable (Heinich, 1970 and 1984). Desirable because “it allows instruction to be brought up to a high standard, and then to be distributed far and wide so that all students can enjoy the advantages of top-rate teaching”.

Lastly, suggests the idea that instructional design can be “done by the numbers” also arises from the behavioural tradition. The idea is that any novice designer can be successful if they just follow the process – do it by the numbers.

In summary, 3 important areas where behaviourism still exerts power over instructional design:

  1. Reductionist premise that you can identify the parts, then you can teach the whole.
  2. Separate design from implementation.
  3. Assumption that following good procedures, applied correctly results in good instruction.

Sticking with the behavioural traditions, suggests that these 3 are not a problem, if you’re limiting yourself to low-level skills. The problems arise when you go to high levels of cognitive processing.

Cognitive theory

The aim here is to explain why the three assumptions are problematic as informed by cognitive theory – the obvious though here is what would constructivism or connectivism suggest.

The description of cognitive theory is

Changes in behavior are seen as indirect rather than direct outcomes of learning. Observable behavior is mediated and controlled by such mental activities as the acquisition, organization and application of knowledge about the world (Neisser, 1976; Rumelhart and Norman, 1981); by the development of skills that allow the encoding, storing and relrieval of information (E. Gagne, 1985; Shuell, 1986); by people’s motivation (Keller, 1983); their perception of what a task requires of them (Salomon, 1983a); and their perception of their likelihood of success (Salomon, 1983b; Schunk, 1984). Consequently, students are seen as active in the construction of knowledge and the development of skills, leading to the conclusion that learning is a generative process under the control of the learner (Wittrock, 1979, 1982).

To my somewhat untrained ear, this sounds like it has aspects of constructivism.

References Bonner (1988) as identifying a number of the differences between traditional designers and those informed by cognitive theory including:

  • task analysis;
    Traditionally aims to identify directly observed behaviours. Cognitive theory requires that “unobservable” tasks be analysed. i.e. the mental tasks to be mastered prior to observable performance being possible. examples including identifying declarative and procedural knowledge or schemata required to perform. Also recognition that novice to expert involves many steps that need to mastered.
  • objectives;
    Statements of what the student is to accomplish under what conditions and to what criterion is a behaviourist approach. Cognitive objectives are schematic representations of the knowledge to be acquired and procedures to apply.
  • learner characteristics;
    Focus on the schemata/mental models students bring to instruction, not their behaviours. May not be a clear line between what they need to know and what they know – learner as dirty slate.
    This acknowledges the importance of current knowledge of the world, represented in mental models, for the acquisition of new knowledge and skills. Research (De Kleer and Brown, 1981; Larkin, 1985; and authors contributing to Gentner and Stevens, 1983) has shown that learning occurs as students’ mental models acquire refinement and accuracy.

  • instructional strategies;
    Behaviourism selected instructional strategies based on the type of learning to take place, the type of learning outcome.
    But because the cognitive conception of learning places so much importance on the student’s development of adequate knowledge structures, cognitive procedures and mental models, the designer should create opportunities for what Bonner calls a “cognitive apprenticeship” centered around problem-solving rather than prescribe strategies apriori.

    Some general principle may determine aspects of the strategy, however, it evolves like a conversation.

Rieber (1987) point out, is that instruction that is designed from cognitive principles can lead to understanding rather than just to memorization and skill performance.

This speaks to me because too much of what passes for improving learning and teaching strikes me as most likely to create memorisation and skill performance, not long term change.

The need for further change

While instructional designers are adopting principles from cognitive theory, the idea is that recent thinking in cognitive psychology and related fields brings into question some the assumptions of cognitive theory as currently accepted. Moving onto the reasons:

  • metacognition;
    Metacognition research shows that students have or can be trained to acquire the ability to reflect on their performance and adopt/adapt different learning strategies. This means that the intent of a instructional design can be circumvented if the student finds the chosen strategy problematic. If the instruction is not adaptable or the student doesn’t choose a good strategy, then the instructional design is compromised.

    I wonder what implications this has for constructive alignment and its idea of forcing the student to do the right thing?

  • dynamic nature of learning;
    Very interesting. As the learner learns, they develop knowledge and skill that is different from the start. The analysis performed at the start to select the instructional strategy no longer holds. If the analysis was done now, a different strategy would be required.
    Nunan (1983) develops this line of reasoning in his argument against the value of instructional design, drawing on arguments against the separation of thought from action put forward by Oakshotte (1962) and Polanyi (1958).

  • emergent properties of cognition;
    This is the argument against reductionism. Emergence is defined as the idea where the properties of the whole, cannot be explained solely be examining the individual parts of the whole. The nature of the whole affects the way elements within them behave. The suggestion is that a number of people have claimed that the actions of the human mind exhibit emergent properties (Churchland, 1988; Gardner, 1985).

    The reductionism that underpins task and learner analysis “acts counter to, or at best ignores, a significant aspect of human cognition, which is the creation of something entirely new and unexpected from the “raw material” that has to be learned.

  • plausible reasoning;
    A designer informed by cognitive theory assumes that the thought processes of a student will be as logical as the instruction itself. In order to learn from a machine, the student has to think like a machine (Streibel, 1986). There is lots of evidence to suggest people are not logical. “Plausible reasoning” is Collins (1978) idea that people proceed on hunches and incomplete information. Hunt (1982) suggests plausible reasoning has allowed the human species to survive.
    If we waited for complete sets of data before making decisions, we would never make any and would not have evolved into intelligent beings.

  • situated cognition; and
    Somewhat related to previous. Streibel (1989) argues that “cognitive science can never form the basis for instructional design because it proceeds from the assumption that human reasoning is planful and logical when in fact it is not”. References Brown, Collins and Duguid (1989); Lave (1988) and Suchman (1987) – i.e. situated cognition folk – to argue that the way we solve problems is dependent on the situation in which the problem occurs. We do not use formal or mathematical reasoning.
  • unpredictability of human behaviour.
    The 5 previous points suggest that human behaviour is indeterminate. Csiko (1989) gives 5 types of evidence to argue that the unpredictability and indeterminism of human behaviour is central to the debate concerning epistemology of educational research. Winn (1990) suggests it applies equally well to instructional design:
    1. Individual learner differences interact in complex ways with treatments which make prediction of performance difficult.
    2. Chaos theory suggests the smallest changes in initial states lead to wild and totally unpredictable fluctuations in a systems behaviour. Something that is more pronounced in complex cognitive systems.
    3. Much learning is “evolutionary” in that it arises from chance responses to novel stimuli
    4. Humans have free will which can be exercised and subsequently invalidate any predictions about behaviours made deterministically from data.
    5. Quantum mechanics shows that observing a phenomenon, changes that phenomenon so that the results of observations are probabilities, not certainties.

Though eclectic, this body of argument leads one to question seriously both the assumption of the validity of instructional prescriptions and the assumption that what works for some students will work for others.

While prediction may not be part of instructional design, it is of the theories it depends upon and Reigelluth (183) points out that any theory of instruction, while not deterministic, does rely on the probability that prescriptions made form it for its validity. Without such validity, you may as well rely on trial and error.

Conclusions

Cognitive theory has been incorporated into instructional design, but behaviourism influence remains and that causes problems.

Cognitive task analysis to develop objectives is just as reductionist as behaviourist approaches.. The whole approach designers take needs to be re-examined. Three directions might include:

  1. Analysis and synthesis;
    Addressing reductionist analysis – instructional strategies need to ensure knowledge/skill components are put back together in meaningful ways….e.g. Reigeluth and Stein’s (1983) use of “summarisers” and “synthesizes” in elaboration theory.

    Balance analysis as a design procedure with synthesis as an instructional strategy. Such prescriptions should exist in instructional theories.

  2. Design and implementation;
    For instruction to be successful, it must therefore constantly monitor and adapt to unpredicted changes in student behavior and thinking as instruction proceeds……To succeed, then, instructional decisions need to be made while instruction is under way and need to be based on complete theories that allow the generation of prescriptions rather than on predetermined sets of prescriptions chosen ahead of time by a designer. (p64)

    Requires the teacher to monitor and modify strategies as they’ve been prescribed. Requires teachers to be well schooled in instructional design and a solid knowledge of theories of learning and instructions – so that they can respond in some sort of informed way. e.g. need methods that will allow them to invent prescriptive principles when the need arises.

    Second recommendation is that the designer needs to monitor the actual use of the instructional system during implementation, or for the designer to make provision for the use to change instruction strategies.

  3. Theory and procedure.
    Decisions about instructional strategies need to be based on more than just the application of design procedures. Rather than techniques being taught, the principles should be.
    This problem is made worse by researchers who are content to identify strategies that work on single occasions rather than determine the necessary conditions for their success (Clark, 1983).

Reservations about instructional design

The following is at first a rambling diatribe outlining some of my reservations with instructional design as it is practiced. Then it is a summary/reflection on Winn (1990) – “Some implications of cognitive theory for instructional design”. The abstract for Winn (199)

This article examines some of the implications of recent developments in cognitive theory for instmctional design. It is argued that behavioral theory is inadequate to prescribe instructional strategies that teach for understanding. Examples of how instructional designers have adopted relevant aspects of cognitive theory are described. However, it is argued that such adoption is only a first step. The growing body of evidence for the indeterminism of human cognition requires even further changes in how instructional designers think and act. A number of bodies of scholarly research and opinion are cited in support of this claim. Three implications of cognitive theory for design are offered: instructional strategies need to be developed to counter the reductienism implicit in task analysis; design needs to be integrated into the implementation of instruction; designers should work from a thorough knowledge of theory not just from design proceduts.

Actually, I’m running out of time, this post will be just the diatribe. The summary/reflection on Winn (1990) will have to wait till later.

Some context

The following line of thought is part of an on-going attempt to identify potential problems in the practice of instructional design because I work within a Curriculum Design & Development Unit at a University. I am trying to identify and understand these problems as an attempt to move toward something that might be more effective (but would likely have its own problems). The current attempt at moving toward a solution will hopefully arise out of some ideas around curriculum mapping.

The diatribe

Back in the mid-1990s I was being put in charge of my first courses. The institution I worked at was, at that stage, a true 2nd generation distance education provider bolted onto an on-campus university (the university was a few years old, having evolved from an institute of advance education). Second generation distance education was “enterprise” print distance education. There was a whole infrastructure, set of processes and resources targeted at the production of print-based study guides and resource materials that were sent to students as their prime means of education. A part of the resources were instructional designers.

From the start, my experiences with the instructional designers and the system they existed within was not good. The system couldn’t see it was increasingly less relevant through the rise of information technology and the instructional designers seemed more interested in their knowledge about what was the right thing to do, rather than recognising the realities of my context and abilities. Rather than engaging with me and my context and applying their knowledge to show how I could solve my problems, they kept pushing their own ideal situations.

Over 15 years on, and not a lot has changed. I still see the same problem in folk trying to improve learning and teaching at that institution. Rather than engage in an on-going process of improvement and reflection, it’s all about big bang changes and their problems. Worse, then as now, only the smallest population of the academics are being effectively engaged by the instructional designers. i.e. the academics that are keen, the ones that are willing to engage with the ideas of the designers (and others). This is perhaps my biggest concern/proposition, that the majority of academics are not engaging with this work and that a significant proportion of them (but not all) are not improving their teaching. But there are others:

  • Instructional designers are increasingly the tools of management, not folk helping academics.
    In an increasingly managerialist sector, the “correct” directions/methods for learning and teaching are increasingly being set by government, government funded bodies (e.g. ALTC and AUQA) and subsequently the management and professionals (e.g. instructional designers, staff developers, quality assurance etc.) that are institutionally responsible for being seen to respond effectively to the outside demands.

    There are two problems with this:

    1. the technologists alliance; and
      The professionals within universities, because of their interactions with the external bodies and because their success depends on engaging with and responding to the demands of the external body, start to think more like the external body. For example, many of the folk on the ALTC boards/etc are from university L&T centres. Their agenda internally becomes more about achieving ALTC outcomes, rather than outcomes for the academics. Geoghegan (1994) identified the technologists alliance around technology, it is increasingly in existence for L&T.
    2. do what management says.
      Similarly, because senior management within universities are being measured on how well they respond to the external demands. They to are suffering the same problem. In addition, because they are generally on short-term contracts there’s increased demand to respond via short-term approaches that show short-term gain but are questionable in the long-term. Instructional designers etc are then directed to carry out these short-term approaches, even if they will hurt in the long term are or seen as nonsensical by academics.

    The end result is that academics perceive instructional designers as people doing change to them, not doing change with them or for them. Not a good foundation on which to encourage change and improvement in something as personal as teaching.

  • Traditional instructional design is not scalable.
    My current institution has about 4 instructional designers. The first term of this year sees the institution offering 400+ courses. That means somewhere around 800 courses a year. That’s 200 courses a year per instructional designer. If you’re looking at each course being “helped” once every two years, that means each course gets the instructional designer for 2 days every 2 years, at best.

    In this environment, traditional ADDIE type big-bang approaches can’t scale.

  • Instructional design seems informed by a great knowledge of ideal learning and teaching, but none of how to effectively bridge the gap between academics and that ideal.

References

Geoghegan, W. (1994). Whatever happened to instructional technology? 22nd Annual Conferences of the International Business Schools Computing Association, Baltimore, MD, IBM.

Winn, W. (1990). “Some implications of cognitive theory for instructional design.” Instructional Science 19(1): 53-69.