Personalized Learning: Assessing Styles with Anne Groat & Tim Musson, Study notes of Design

Download Personalized Learning: Assessing Styles with Anne Groat & Tim Musson and more Study notes Design in PDF only on Docsity! Learning styles: individualizing computer-based learning environments Anne Groat and Tim Musson Napier University In spite of its importance, learning style is a factor that has been largely ignored in the design of educational software. Two issues concerning a specific set of learning styles, described by Honey and Mumford (1986), are considered here. The first relates to measurement and validity. This is discussed in the context of a longitudinal study to test the predictive validity of the questionnaire items against various measures of academic performance, such as course choice and level of attainment in different subjects. The second issue looks at how the learning styles can be used in computer-based learning environments. A re-examination of the four learning styles (Activist, Pragmatist, Reflector and Theorist) suggests that they can usefully be characterized using two orthogonal dimensions. Using a limited number of pedagogical building blocks, this characterization has allowed the development of a teaching strategy suitable for each of the learning styles. Further work is discussed, which will use a multi-strategy basic algebra tutor to assess the effect of matching teaching strategy to learning style. Introduction While the need to adapt teaching to the needs of a student is generally acknowledged (see Corno and Snow, 1986, for a wide review of the literature), little is known about the impact of individual learner-differences on the quality of learning attained within computer-based learning environments (CBLEs). What evidence there is appears to support the notion that individual differences have implications for the degree of success or failure experienced by students (Ford and Ford, 1992) and by trainee end-users of software packages (Bostrom et al, 1990). The problem is to identify the way in which specific individual characteristics of a student interact with particular features of a CBLE, and how the interaction affects the quality of the resultant learning. Teaching in a CBLE is likely to require a subset of teaching strategies different from that subset appropriate to more traditional environments, and the use of a machine may elicit different behaviours from those normally arising in a classroom context. Of the candidate-factors influencing learning - like personality, motivation, cognitive style, level of ability, and learning style - it is the last that we consider here. For this work, 53 Anne Groat and Tim Musson Learning styles: individualizing computer-based learning environments learning style is defined as a preference for processing information in a particular way when carrying out a learning activity; it is the observable behaviour that arises from a person's underlying personality, motivation, cognitive style and ability, and which is stable over a variety of situations. There is some disagreement about the stability, and therefore usefulness, of learning style. For example, Entwistle (1988), Pask (1976) and Schmeck (1983) argue that individual students tend to be consistent in their approach to learning, but on the other hand Laurillard (1984) and Ramsden (1979) consider that a student's perception of a particular situation is of overriding importance in influencing what and how a student learns. The position adopted here is that each student's approach to learning is determined both by a relatively stable entity called learning style, and by more situation-specific concerns. Determining learning style There are two basic approaches to modelling a student's learning style for use within a CBLE. It can be done dynamically during the course of a tutorial session. For the student, this has the advantage of being non-intrusive, but it is expensive in terms of system resources, and it is unlikely that a student would use a small tutoring system for long enough to enable it to infer what learning style is being used. An alternative is to model the student's behaviour by using stereotypes. For a small system this is a potentially useful approach that can substantially simplify the problem of modelling a student. The main disadvantage is that it requires the student to answer questions before starting work, and so runs the risk of alienating its target audience. The aim should be, therefore, to ask as few questions as possible, choosing those with good predictive power. The most radical approach is to ask only one question. This has been explored to some extent by Ford (1985) and by Clarke (1993). In each case, Ford's Study Preference Questionnaire was administered to a group of postgraduate students. One item was identified that differentiated, at an acceptable level of significance, between students on the holist/serialist dimension. The problem is that each attempt identified a different item, a result that Clarke attributed either to the interference arising from the reliability analysis or to sample characteristics. Whatever the reason, it highlights the difficulty of obtaining a reasonable balance between predictive value and user acceptability. Acceptance of a time-consuming procedure might be enhanced if the investment of time and effort on the student's part was made worthwhile. Knowing what one's learning style is can be shown to be beneficial not only within computer-based learning environments, but also in the wider educational context. Knowledge about how one learns has been shown to lead to more effective learning (Pennell, 1985). The instrument that was chosen to assess learning style is based on Kolb's experiential theory of learning (Kolb, 1984). This theory considers that learning is more than just a cognitive process; it is a series of experiences that involve cognition, and the learner is seen as moving iteratively through four stages. There are, however, problems with Kolb's Learning Styles Inventory (LSI): with the psychometrics (Freedman and Stumpf, 1978) and with the construct and face validity (Wilson, 1986). Although the underlying theory is considered helpful, the shortcomings of the LSI prompted Honey and Mumford (1986) to devise a questionnaire for measuring learning style. Their Learning Styles Questionnaire (LSQ) is based on self-reported behaviour, and their learning styles differ in some respects 54 ALT-J Volume 3 Number 2 other two learning styles prefer safety. Pragmatists prefer to be shown what to do and be given ample opportunity to practise, and Reflectors work best when given sufficient information to assimilate and time to reflect upon it. The learning styles can be placed on a graph formed by the intersection of the two axes (Figure 1). Consideration of the graph can be used to define appropriate teaching strategies thus: Figure I: Learning styles Concrete Pr Safety Re Ac Challenge Th Abstract Pr = Pragmatist Th = Theorist Re = Reflector Ac a Activist Concrete versus Abstract The choice of graphical or textual representation of a concept has implications for the way it is processed and communicated. Graphics enforce specificity, or at least restrict the level of abstraction possible, whereas text enables expression of abstract ideas (Stenning and Oberlander, in press). Perceptual and spatial relationships are better depicted by graphics, logical and temporal relationships by text (Larkin and Simon, 1987). The preference of learners for concrete or abstract processing, and for attending to relationships they find meaningful, can be addressed by providing either a graphical or a text-based environment. Safety versus Challenge 'Safety' can be provided by a highly structured environment, one that teaches the subject- matter in small incremental steps, and which provides ample opportunity either for observing what is to be done (Reflector), or for putting into practice what has been demonstrated (Pragmatist). Meta-information for the learner can consist of what has been done and what still has to be done, but the learner is given no opportunity to alter 57 Anne Groat and Tim Musson Learning styles: individualizing computer-based learning environments the order of events. For 'Challenge', what is required is the opportunity to attempt more demanding tasks as soon as the learner wants to tackle them, whether or not a teacher (or CBLE) would agree. Essentially, what is happening is that the learner is free to try out a course of action, or to test a hypothesis; in other words, to experiment in whatever way suits. The learning environment should, of course, allow back-tracking when the step taken proves to be too large. This implies that the learner should have complete control over the learning environment. Designing the system Once the teaching strategies have been derived from the learning styles, they have to be translated into teaching methods that are possible in a CBLE, at a level of granularity suitable for the design and implementation of a system. Chen (1993, pp. 299-300) has developed a methodology for classifying pedagogical methods, most of which are applicable to a small system. Such methods can provide the basis for designing the learning environment, and for analysing user actions. Her basic pedagogical methods, with some minor adaptations, are: 1. setting goals: the knowledge or skills the learner is expected to acquire during the lesson; 2. providing instructions: uninterrupted presentations of any type of knowledge through text; 3. providing demonstrations: illustration of a particular task, a worked example; 4. providing explanations: the rationale behind a particular action; 5. presenting tasks: activities presented through text or graphical representations; 6. asking questions: questions requiring specific answers are presented; 7. providing working spaces: opportunities to interact with the program, the learner being able perform a task only when a corresponding working space is provided; 8. providing examples: the designer relates a learner's daily experience to the present learning; 9. providing reminders: the designer presents key words, such as commands, or key concepts, that a learner needs during the performance of a task; 10. providing hints: implicit cues are embedded in the task to be performed; 11. providing evaluation and feedback: the learner's performance is evaluated and feedback is provided accordingly. Implementation of all of the pedagogical methods is possible within the proposed system, and each is relevant to one or more of the learning styles. All teaching strategies will have relevant goals set and stated, and appropriate evaluation and feedback provided; tasks will be presented and workspace will be provided. Thus each learning style will be targeted with a teaching strategy consisting of the core pedagogical methods (those concerned with goals and feedback possibly implemented differently to match learning style), with different combinations of the others. 58 ALT-] Volume 3 Number 2 For the 'concrete' strategies (Pragmatist and Activist learning styles), graphics will provide the medium of instruction (where the use of graphics will explicitly link the material to be learned with examples from the everyday world of experience), and for the 'abstract' strategies (Theorist and Reflector) text directly relating to symbolic manipulation will be used. For 'safety' strategies (Pragmatist and Reflector), a tightly structured environment will be provided, and for the 'challenge' strategies (Activist and Theorist), no structure will be imposed. Instead information about the contents of the system, and recommendations about what might be an appropriate activity, will be available. Each teaching strategy will require its own particular subset of the pedagogical methods. The teaching strategies for each of the learning styles are as follows: Concrete-safety learners will have graphical examples and demonstrations provided, to tie in with the need to learn how to do things. Only after students have been shown how to do a task will they be given the opportunity to perform similar tasks for themselves. Concrete-challenge learners will also have the material presented in graphical form, to allow opportunities for direct hands-on experimentation. These students will be given no explicit instructions; instead, tasks will be so presented that hints about what to do will be embedded in the material. Information about the content and organization of the system will be provided graphically. Abstract-safety learners will be text-based, and instructions, demonstrations, and reminders will be given before students are required to carry out a task. Abstract-challenge learners will also be text-based and, within an unstructured environment, students will have access to explanations and instructions. They will be provided with textual information on the content and organization of the system. Figure 2: Teaching strategies Graphics Provide demonstrations Provide examples Structure Provide Instructions Provide explanations provide reminders Provide hints Present Information about structure and content graphically Freedom Provide explanations Provide instructions Present information about structure and content textually Text 59