| Australasian Journal of Educational Technology 2004, 20(2), 248-273. |
AJET 20 |
This paper introduces the Quail Model, a device for the classification and visualisation of learning goals. The model is a communication tool that can smoothen the discussion within a course design team, support shared understanding, and improve decision making. Its theoretical background mingles contributions from instructional design (Bloom, Gagné, Merrill) with the insights of an author of philosophy (Lonergan). The paper presents a literature review, the Quail Model and some examples. Reference to a demonstration application is also provided.
This paper presents a novel tool for the visualisation of learning goals, called the Quail Model. Three claims by Anderson & Krathwohl (2001) may provide the best introduction, as they define the perspective in which the Quail Model was developed:
These are only some of the reasons why learning goals are one of the major topics in ID. A large part of the literature suggests that goals should be analysed and decomposed before expressing them verbally or mapping them on any kind of visualisation, during the instructional analysis phase (cf., Dick & Carey, 2001). Nevertheless, and this is the point, the instructor, the subject expert and the designer think in terms of high level goals. They can afterward be analysed and decomposed - but this is a technique, useful for the further design steps, yet unnatural. A teacher does not only think of behaviours, but also of ways of thinking, judging, perceiving values, interests, etc. This is why I believe a tool for representing high level goals before instructional analysis may be a powerful design support. The Quail Model introduced in this paper is not a tool for instructional analysis, but a visualisation device for enhancing team communication about goals. As such it can be used both before and after decomposing the goals: the representation of lower level goals does not present any particular difficulty. Entry competencies could be also represented on the Quail Model, thus allowing determining the learning gap.
The Quail Model was conceived as a representation device that instructional designers may use in order to share their ideas with instructors, subject matter experts, media designers, web programmers, or anyone who is part of the instructional development team.
The basic assumption underpinning the Quail Model is that in order to achieve high quality instructional experiences, learning goals should be clearly stated, thoroughly understood and shared by the whole design team. Moving from that assumption, the Quail Model relies on the hypothesis - which is actually a truism - that being able to see goals can enhance understanding and foster discussion. The idea is to provide a visual tool for it. Consequently, this work is not concerned with the verbal expression of (behavioural) goals, nor directly with assessment and evaluation.
Section 2 presents a literature review about the definition and classification of goals. Given the extension of contributions on this topic in the last decades, it does not have any claim of exhaustiveness, but it is functional for the development of the Quail Model, presented and discussed in the Section 4. Section 3 is devoted to introducing the work of Bernard J. Lonergan, which forms the main theoretical background of the model. Section 5 provides some examples, while Section 6 reports feedback from instructors and designers who used the model for their design practice. Finally, Section 7 draws some conclusions and scenarios for further work.
The general definition of learning goal is likely to be the only shared point among all the authors that dealt with the issue. A learning goal is the formulation of the expected outcome of the instruction in terms of acquired knowledge and competencies. The correct formulation of a goal should take the learner perspective ("be able to draw pie charts"), leaving aside the instructor's perspective ("show students how to draw pie charts") and the activity perspective ("discuss some pie charts with the students and let them work on a small data set on their own"). A goal should therefore describe the desired final status of the learner with respect to the changes developed during the learning activity (Gronlund, 1995). A more precise definition distinguishes goals - high level learning achievements concerning a whole course or module - from objectives - low level learning achievement concerning a single lecture or learning activity. Several objectives can be therefore defined for each goal; for example the objectives "Define leadership", "Recall examples of different organisations", or "Distinguish companies from institutions" are a specification of the goal "Provide a critical definition of organisation".
According to the perspective introduced above, the Quail Model only deals with goals, and is not concerned with the expression of objectives.
They distinguished two domains of learning, described in two handbooks[1]: (a) the cognitive domain, which includes intellectual knowledge and cognitive skills; and (b) the affective domain, which includes values, interests, attitudes, opinions, appreciations, values, emotional sets and what is called today emotional intelligence.
Each domain represents a specific type of knowledge (cognition/affective skills), and proposes different levels that could be reached. The taxonomy is hierarchical (levels increase in difficulty/sophistication) and cumulative (each level builds on and subsumes the ones below). Due to the extension of the taxonomy and the limitation of space, the complete list of knowledge levels is not reported here.
Bloom divides the cognitive domain into six main levels that do not form a continuum. The first one, called knowledge in the handbook, but often quoted as recall, includes types of knowledge, while other levels (comprehension, application, analysis, synthesis, and evaluation) include cognitive abilities. Notice that the final step of cognition, evaluation, has actually a strong relationship with the affective domain. The authors indeed declare the tight connection between the two levels, but do not provide a complete integration.
Affective goals have a slower attainment than cognitive ones, and are therefore more difficult to observe. The affective domain is structured on five levels: receiving, responding, valuing, organisation, and characterisation. Like the cognitive domain, they are sequential, but unlike it, they represent a continuum in a process of internalisation of values and practices, or in the assimilation of a culture. The analysis and statement of affective goals are more difficult than of cognitive ones, although several goals in K-12 and high school curricula belong to this domain. Lee & Merrill (1972) present an interesting discussion of affective goals.
Gagné & Merrill (1990) developed the idea of learning enterprise (which was also in Gagné, 1985): the combination of different types of knowledge into a more general expertise. The authors claim the necessity of expressing complex goals that reflect practice in the real world, in order to enhance transfer. Learning enterprises are defined within the context of a scenario, and are achieved through the provision of a general schema integrating the different knowledge types into one whole and specifying the connections between them. The idea of complex goals has consequences on the practice of design: "Whereas current instructional design methodology focuses on components such as generalities and examples, which are geared for promoting acquisition of single goals such as concepts or procedures, a consideration of enterprises as integrated wholes may lead to a future focus on more holistic student interaction for 'transactions'." (Gagné & Merrill, 1990, p. 29)
Figure 1: Merrill's performance-content matrix
Within the CDT theory, the performance-content matrix is linked to the specification of test items and to a discussion of the very idea of subject matter. Merrill's grid has the advantage of being straightforward (it defines only 4 content types and 3 performance levels) and at the same time rather precise, with 12 possible distinct outcome areas. The simple fact that it is a matrix - a visual representation - increases its usability. It will be reprised and merged with other contributions in the Quail Model.
The emphasis in Anderson and Krathwohl's work is on classifying rather than expressing goals. This was indeed the proper goal also for Bloom's, Gagné's and Merrill's works, but a great part of the work of the later interpreters focused on behavioural verbs and "correct" wording.
The vertical dimension of the grid (Figure 2) represents the knowledge dimension, i.e. the type of knowledge at stake; the horizontal represents the cognitive dimension, i.e. the cognitive process to be performed.
Figure 2: Anderson & Krathwohl's grid
Interestingly, the revised taxonomy presents both the elements on which Bloom and Gagné focus: types of knowledge and skills, and a representation of the cognitive process. Although the categories are similar to the original taxonomy, their arrangement on a two dimensional grid and the distinction of the knowledge and cognitive process dimensions make it a new and powerful tool.
Anderson and Krathwohl propose to chart on their grid not only goals, but also activities (in relation to the specific goals addressed) and assessment (in relation to what is being actually assessed), in order to control the alignment or consistency of the whole instruction.
Lonergan proposed an articulation of the learning process on three levels: experience, understanding and judgment (Lonergan, 1990; for a synthetic introduction to the model, cf. Lonergan, 1988). According to his view, our drive to know proceeds from personal experience: we want to know, as we express wonder as questions about the objects and situations we meet and we live by, and these questions are the primary sparkle of knowledge. The second step in learning is understanding, which means discovering the intelligible pattern in the image of the object. As analogy, it is the work of the detective or of the scientist, who sees a situation - a murder or a natural phenomenon - and tries to select the relevant features in order to build a complete model, a unitary vision of its causes. The third level is the level of judgment, in which objects of thought are transformed into objects of knowledge. This happens through the act of judging, or assenting: recognising that a certain understanding of a situation or a certain fact is true and corresponds to reality. This is the moment in which critical thinking comes into play, creating room for self commitment and behavioural change.
The process of learning through the three levels of experience, understanding and judgment can be analysed more finely through the activities in progress at each level, as represented in Figure 3.
Figure 3: Activities in progress at each level in the learning process
Sensations are filtered by perception, i.e. the active process of focusing on sensations and organising them in our consciousness. Perception is active: previous knowledge, conceptions and misconceptions, expectations and fears influence it, for example as in the famous research of New Look by Bruner & Goodman (1947; 1949). Cognitive science and psychology are the disciplines nowadays more concerned with this level.
The perception of data gathered through our senses is actively organised in our minds as image, or mental representation. The generation of a correct mental image, suitable to understanding, is one of the main concerns for the teacher. According to Lonergan, the image is our way of representing the object of experience to our inner flow of consciousness, and is the starting point for understanding.
Understanding, or insight, is the process through which we answer questions of this kind, and it means to recognise necessity or "the must" in the object, to grasp it "as it is". Let us imagine a child has to learn what a hexagon is: the teacher shows the child a drawing of an orange hexagon with a red border. Then the child is helped drawing a second shape just with a red line - and here he understands, or can understand the situation: a hexagon is a planar closed shape with six sides and six angles, independent of line color or filling. Notice that the proper verbal expression is not a condition for understanding. Understanding is not the formation of a concept, but the comprehension of the instance situation, the moment in which we feel we are grasping it. The act of understanding is active - teaching also means stimulating and fostering this process[2].
The formation of a concept, or conceptualisation, is the next step: a generalisation and a formulation of the understanding. "When we move to conception or formulation, the matter is more complex, since we form concepts in many ways .... By your insight into the image you are able to formulate the conditions, the elements in the image, necessary to having the insight" (Lonergan, 1990, p. 165). A concept is formed as soon as we think of the general case of which our specific object is an instance, like when proceeding from the understanding of a hexagon to its definition, which covers all possible cases. In web design, it is the difference between a good solution to the commissioner's problem - the right idea, an insight - and a sound model, with definitions and procedures, for developing web sites. It is likely that a good intuitive designer can propose a portal-like design, or a collection-like design even without having a clear conceptualisation of the distinction between portal and collection in general. Concepts can exist only by means of a (verbal) language; this is why linguistic expression is a powerful tool for helping students in shaping their own concepts. Teaching is in fact a matter of communication, and from this point of view, language can be considered as a set of formulated insights that we receive from our tradition.
The answer to such a question is an insight in our formulation. The method is reflective understanding: gathering evidence that our understanding and our concepts work or fit the knowledge object. Reflective understanding means moving backwards until we find some (virtually) unconditioned, i.e. some verified fact or previously verified understanding or concept, that supports the appropriateness of our understanding.
This detail may become clearer through an example. A man goes out in the morning, and when he comes back finds windows broken, smoke inside the room and a terrible smell. Given the situation, he comes to an understanding and says "something has happened" - the state of the house has changed, so an event has occurred. He can think further: "somebody entered my house, stole my things and lit a fire". This is a possible understanding of the situation; but is it true? A confirmation can come only from evidence. If the man sees footsteps inside the house, which do not correspond with his own and he lives alone, he can go a little bit further in the reflective analysis: the footsteps prove without conditions that someone has been there.
Judgment is the act by which we recognise and affirm the adequacy of our understanding and conceptualisation to the situation or the type of situation encountered in our experience. Judgments are of different types according to their objects: they can be formulated on facts, insights into instance situations, generalisations or concepts, mathematical theories, common sense activities or scientific discoveries. Moreover, judgments of any type can affirm truth at different levels, from complete certainty (as judging the fact that you are now reading) to all hues of probability. The acquisition of certainty depends of course on the psychological aptitude of the learner, who can also dismiss the request of judgment and refuse to take the risk of commitment. Judgment is necessary in order to get the learners to commit to what they have learnt and eventually to change behaviour.
This dynamic is supported by hypotheses making and by the definition of an ideal of knowledge (Lonergan, 1990). The top down flow in fact consists mainly in defining a hypothetical arrival point for the pursued knowledge, which serves as a grade for the whole process. It is a mere representation of something we do not know - hypothetical indeed - and this exactly its value: it is a name, like the x in mathematical expressions. One of the main challenges in teaching is offering a sensible, understandable and fascinating x to chase in learning.
| Tag | Statement |
| G1 | Know that we all have a brain and a nervous system as all animals (but not plants and things) |
| G2 | Describe a brain (macroscopic) |
| G3 | Describe the functional macroareas of the brain, and how they communicate with each other |
| G4 | Know that the brain is composed by neurons. Be able to provide a simple definition of neuron |
| G5 | Act safely in order to avoid brain damages |
| G6 | Develop interest into neuroscience, formulate questions |
The goals presented above in Table 1 are sketched below in Figure 4 on the Performance-Content matrix.
Figure 4: Example of goal visualisation on Merrill's matrix
While G1 concerns a fact (we all have a brain), G2, G3 and G4 have to do with concepts (what the brain is like, functional areas, and the neuron). G5 concerns an attitude (to act safely), which could be translated into principles to use in certain situations - although this does not fit completely. The representation of G6 (develop interest in neuroscience) is more controversial: the matrix does not have a specific space for interest - it was translated into principles (a way of behaving, in a certain way: it is good to know more about it), which are open to transformation at the find level.
The same goals could be represented on the grid developed by Anderson & Krathwohl (2001), as in Figure 5.
This grid allows the localisation of a goal in more then one cell. It happens for G3 and G4, which are split between facts to remember and concepts to understand. This reveals that those goals contain two components that share the same relationship existing between G1 (the fact that we have a brain) and G2 (what a brain is like). G5 was transformed into procedures (although principles grasped its essence better). The problem with G6 remains: interests do not have a proper location on the grid.
Figure 5: Example of goal visualisation on Anderson & Krathwohl grid
The representation of self reflective learning, i.e. learning experiences in which the learner's self is both subject and object of knowledge (such as in "Expressing and evaluating one's idea of education") is another distinctive feature of the model. Any knowledge type can be used for self reflecting knowledge. Self reflective goals are represented with a looping arrow. The visual key for goal type representation is provided in Figure 6.
Figure 6: The complete Quail Model
Figure 7: Example of goal visualisation with the Quail Model
First of all, notice that G6 gives here little trouble: the addressed level is that of inquiry about facts and concepts of neuroscience. Its scope is find, as it stimulates learners to look for new knowledge in this domain. Secondly, a slight distinction between G2, G3 and G4 is made evident: the former indicates the ability to describe how a single brain is (which means, getting the insight of it thanks to the concept of brain) while G3 and G4 concern definitions (of neuron and of functional area). Finally, G5 can be placed as an attitude on the level of action.
Figure 8: Example of prerequisite relationships
The next section will provide a complete example, while Section 6 will offer some elements for an evaluation of the impact of the model on design practice.
In order to refine the goals, let's point out that:
By the end of this course students will be able to:
|
Goals were therefore refined as in Table 2, and were mapped on the Quail Model, as in Figure 10.
| Tag | Statement |
| A | A1: Describe selected epistemologies of learning A2: Relate them to the teaching - learning process |
| B | Discuss major orientations leading to significant learning theories influencing instructional design theory. |
| C | Critically examine selected major theories of learning C1: Understand them C2: Evaluate them |
| D | Use one or more theories of learning as a lens to describe, discuss, and analyse teaching and learning situations using learning technologies. |
| E | Use one or more theories of learning to solve given instructional design problems or approved design problems arising from the students' own situations. |
| F | Explain own initial philosophy of / conceptions of teaching and learning |
Figure 10: QUAIL goal mapping for ETEC 512
It was specifically developed for instructional designers, ie. people who manage professionally the development of courses, instructional units or learning materials, coordinating an interdisciplinary team (instructors, tutors, technical staff, web programmers, etc). The time necessary for becoming familiar with the model and acquiring some fluency would be for them a sensible investment: the Quail Model could be a visual device for improving the shared understanding of goals within the team, and could also become a framework for developing instructional strategies, for example moving from experience to concepts, or from insights to judgments, etc. Instructors or teachers who develop their own courses are also potential users of the model.
The time spent in each process for classifying learning goals and for visualising them could be perceived as an additional cost. It is actually an investment, as it provides a shared understanding and a reliable compass for decision making: what strategy to use, what technologies to exploit for what activities, etc.
From this point of view any goal taxonomy, classification grid or visualisation device is a particular way of thinking teaching and learning, which goes beyond the "state goals" phase of the process. In this respect too, the Quail Model as a general design framework might be useful also to teachers, instructors and trainers.
A qualitative analysis of the collected feedback revealed that the Quail model was perceived by all respondents as an interesting and useful tool. In particular they described it as "easy to understand" and "important for team work".
Two teachers pointed out the "completeness" of the model: they felt that the Quail model offers "a deep insight of what objectives are - it is not limited to answers to who-what-why questions, but there are a wider number of factors to consider - such as the inquiry... and the verification of the teachers' proposal."
Moreover, the teachers indicated that the model "allows thinking globally to instructional activities", keeping all goals in mind, and that it "allows a simplification and clarification of goals", making them unambiguous and easy to share. Moreover, the teachers felt comfortable with the fact that "it stresses the importance of starting from experience" - a basic element of teaching confirmed by their own professional experience.
Some teachers pointed out that, although easy to understand, the model requires some practice: "it requires not only optimal competence with the topic you are working on..., but also optimal competence with the model itself, as it is very demanding in placing objectives on the grid".
This research is but initial: the Quail Model needs to be further refined through the collection and analysis of case studies, and its impact on the design practice should be evaluated in the long term and with different disciplines and school levels. Moreover, the possibility to produce an application to support the creation of visuals is a key element for making the model usable and appealing to practitioners[8] - this is a topic that has been up to now inexplicably marginal in instructional design.
An interesting area to investigate is the integration of affective issues along with cognitive ones, merging even more the two original domains by Bloom.
Finally, as long as it conveys a way of conceiving education, a model like Quail might raise some interesting issues for the development of learning technologies in their broad sense. For example: How can technologies broaden the experience of learners, e.g. with simulations or 3D worlds? Do these methods actually improve the understanding and conceptualisation of experiences? Can multimedia application support the generation of mental images? How to effectively support the generation of insights and judgments?
The perspective under which the Quail Model was developed and should be used considers teaching like painting or playing music. These skills can be acquired, and experience enhances the performance, but a good teacher, like the painter or the musician, is natural born: learning and practicing can bring improvements, but only if rooted in the fertile soil of natural aptitude. If we can hope to have (or to be) naturally talented teachers, what can be learnt? Specific knowledge, examples of best practices and common mistakes, and tools that improve the performance. The Quail Model belongs to the tools that the instructional designer can use for improving her/his performance.
Special thanks also to Rick Kenny (Athabasca University, AL), who completed my introduction to Instructional Design and provided me with up-to-date references. Thanks also to Bridget Cooper (University of Leeds, UK) for her appropriate feedback.
Bloom B.S., Krathwohl, D.R. et al. (1956). Taxonomy of Educational Goals: The Classification of Educational Goals, by a committee of college and university examiners. Handbook I: Cognitive Domain. New York: Longmans, Green & Co.
Bloom B.S., Krathwohl, D.R. et al. (1964). Taxonomy of Educational Goals: The Classification of Educational Goals, by a committee of college and university examiners. Handbook II: Affective Domain. New York: Longmans, Green & Co.
Bruner, J.S. & Goodman, C.C. (1947). Value and need as organizing factors in perception. Journal of Abnormal and Social Psychology, 42, 33-44.
Bruner, J.S. & Goodman, C.C. (1949). On the perception of incongruity: A paradigm. Journal of Personality, 18, 206-223.
Dick, W. & Carey, L. (2001). The Systematic Design of Instruction. 6th ed. New York: Harper Collins College Publishers.
Gagné, R.M., Briggs, R. & Wager, W. (1992). Principles of Instructional Design. 4th ed. Orlando, FL: Harcourt Brace Jovanovich.
Gagné, R.M. & Merrill, M.D. (1990). Integrative goals for instructional design. Educational Technology Research and Development, 38(1), 23-30.
Gagné, R.M. (1985). The Conditions of Learning. 4th ed. New York: Holt, Rinehart & Winston.
Harrow, A. (1972). A Taxonomy of the Psychomotor Domain. A guide for Developing Behavioral Goals. New York: McKay.
Lee, B.N. & Merrill, M.D. (1972). Writing Complete Affective Goals. A Short Course. Belmont, CA: Wadsworth.
Lonergan, B. (1957). Insight: A Study of Human Understanding. London: Longmans, Green and Co. and New York: Philosophical Library.
Lonergan, B. (1980). A Post-Hegelian Philosophy of Religion. [Lecture at the 14th Congress of the International Association for the History of Religions, Winnipeg, Canada, August 17-21]. Quoted in: Doran, R.M. (1990). Theology and the Dialectics of History. Toronto: University of Toronto Press, 1990.
Lonergan, B. (1988). Cognitional Structure. In F.E. Crowe & R.M. Doran (Eds.), Collected Works of Bernard Lonergan (vol. 4, Collection). Toronto: University of Toronto Press.
Lonergan, B. (1990). Understanding and Being: The Halifax Lectures on Insight. Toronto: University of Toronto Press [edited by E.A. Morelli & M.D Morelli].
Merrill, M.D. (1994). Instructional Design Theory. Englewood Cliffs, NJ: Educational Technology.
Merrill, M.D. (1983). Component Display Theory. In C.M. Reigeluth (Ed), Instructional-Design Theories and Models: An Overview of Their Current Status (vol. 1, pp. 279-333). Hillsdale, NJ: Lawrence Erlbaum Associates.
| Author: Luca Botturi NewMinE Lab - New Media in Education Laboratory Università della Svizzera italiana Via Giuseppe Buffi 13, CH-6900 Lugano, Switzerland Email: luca.botturi@lu.unisi.ch Tel: +41 91 912 4722 Fax: +41 91 912 4647 http://www.newmine.org/ Please cite as: Botturi, L. (2004). Visualising learning goals with the Quail Model. Australasian Journal of Educational Technology, 20(2), 248-273. http://www.ascilite.org.au/ajet/ajet20/botturi.html |