Choosing learner activities for specific learning outcomes: A tool for constructivist computer assisted learning design
Barney DalgarnoSchool of Information Studies
Charles Sturt University
Choosing learner activities for specific learning outcomes: A tool for constructivist computer assisted learning designBarney DalgarnoSchool of Information Studies Charles Sturt University | |
In the design of Computer Assisted Learning (CAL) resources, one of the most important tasks of the designer is to decide on the intended activities that learners will undertake as they use the resources. This paper describes a valuable tool for CAL designers, in choosing activities likely to facilitate the achievement of specific learning outcomes: a matrix connecting categories of learning outcome with categories of learner activity.The paper recognises that the learner will typically undertake many activities as part of achieving a particular outcome, not all of which are of primary importance. Consequently, the matrix specifies categories of activity likely to be of primary importance and categories of secondary importance in achieving each outcome.
The categories of learning outcome used in the matrix are drawn from Bloom's Taxonomy of Educational Objectives. The categories of learner activity are drawn from a new classification scheme proposed in the paper. In justifying the need for such a scheme, the paper discusses other related classification schemes, including those proposed by Merrill, Li and Jones; Laurillard; Gagne, Briggs and Wager; and Sims and Hedberg.
Examples of outcomes and activities, from a review of 22 different CAL resources, are used to illustrate the hypothesised connections. The paper concludes by discussing in brief how the proposed matrix could be used within the CAL design and development process.
This paper describes a tool for CAL designers, to assist with the process of choosing activities likely to facilitate the achievement of specific learning outcomes: a matrix connecting categories of learning outcome with categories of learner activity.
The categories of learning outcome used in the matrix are drawn from Bloom's Taxonomy of Educational Objectives (Bloom et. al., 1956). Section 2 of this paper explains the rationale behind the choice of Bloom's classification scheme over other similar schemes. Section 3 attempts to select a classification scheme for learner activity. However, after reviewing classification schemes for various aspects of the CAL process it is concluded that none is appropriate for the purposes of this paper. Consequently a new scheme is required, and Section 4 proposes such a scheme.
Having chosen classification schemes for learning outcome and for learner activity, the matrix, which hypothesises connections between categories of learning outcome and categories of learner activity, is proposed in Section 5. Section 6 attempts to make the hypothesised connections clearer by describing examples of outcomes and activities, from a review of 22 different CAL resources. Lastly, Section 7 discusses how the proposed matrix could be used within the CAL design and development process.
A fundamental principle implicit within this paper is that prior to undertaking any activity designed to facilitate learning, educationalists must be very clear on the intended learning outcomes. Consequently, although the activities of the learner are seen as being of central importance to the CAL design process, the choice of activities must begin with a clear statement of the intended learning outcomes. In order to be able to use the matrix proposed in this paper, the learning outcomes will also have to be classified into categories. The ease with which this is done will depend, to a large extent, on the classification scheme chosen.
The learning outcome classification scheme chosen must be one that is sufficiently easy to use that designers can conveniently classify their particular intended outcomes. Schemes having too many categories are likely to make this process more laborious. Conversely, the scheme chosen must have sufficient categories, to allow those outcomes that are likely to be achieved using very different learner activities to appear in different categories. Additionally, the scheme chosen should have categories that are clearly described, and ideally should be in widespread use, so that designers do not have to learn an additional scheme.
Classifications of learning outcome or educational objective typically refer to three broad groups of outcomes: cognitive outcomes which focus on knowledge, understanding and intellectual skills; affective or attitudinal outcomes; and psychomotor outcomes, which focus on physical skills. This paper focuses only on cognitive learning outcomes. The choice of learner activities that are likely to result in the achievement of affective or psychomotor outcomes is left as the subject of further research. Consequently, in reviewing existing classification schemes, only the categories within a classification scheme that fit into the cognitive domain are considered.
Other sources tend to refer to Gagne's and Bloom's classification schemes as being of prime importance. For example Borich and Tombari (1995), compare Gagne's scheme with Bloom's, stating that both Bloom's and Gagne's "ideas have significantly shaped our understanding" and "have contributed to a design for unit and lesson planning" (p. 249). Cazden (1986) states that Bloom's Taxonomy has been "the most influential scheme" and "it can be considered the prototype taxonomy, representing commonalities among the systems developed in the last 50 years" (p. 452). Rieber (1994) says that Bloom's Taxonomy is "still considered as the standard against which current perspectives are compared" (p. 35), but goes on to say that "Gagne has refined and extended Bloom's original descriptions" (p. 35).
The following section, then, compares the classification schemes proposed by each of Bloom, Gagne and Merrill.
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1. Knowledge 1.12 Knowledge of specific facts 1.22 Knowledge of trends and sequences 1.23 Knowledge of classifications and categories 1.24 Knowledge of criteria 1.25 Knowledge of methodology 1.3 Knowledge of universals and abstractions in a field 1.31 Knowledge of principles and generalisations
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2. Comprehension
2.2 Interpretation 2.3 Extrapolation 3. Application 4. Analysis 4.2 Analysis of relationships 4.3 Analysis of organisational principles 5. Synthesis 5.2 Production of a plan, or a proposed set of operations 5.3 Derivation of a set of abstract relations 6. Evaluation 6.2 Judgements in terms of external criteria
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Table 1: Bloom et al's categories of learning outcome
Gagne (1977) identifies the following five categories of learned capability: intellectual skill, motor skill, verbal information, cognitive strategy, and attitude. Recognising that the intellectual skill category covers a range of quite different learned capabilities, he divides this category into the following four sub-categories: discrimination, concept, rule, and higher order rule. Later Gagne differentiates between concrete concepts and defined concepts (Gagne, Briggs and Wager, 1992).
Given that this paper explicitly excludes affective or attitudinal outcomes and psychomotor or motor skill outcomes, the categories of learning outcome identified by Gagne that are relevant here are shown in the following table.
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1. Intellectual skill; 1.2. Concrete concept; 1.3. Defined concept; 1.4. Rule; 1.5. Higher order rule; |
2. Verbal information;
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Table 2: Gagne et al's categories of learning outcome
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1.2 execute 1.3 interpret 2. Abstraction transactions 2.2 classify 2.3 generalise 2.4 decide 2.5 transfer |
3. Association transactions 3.2 analogise 3.3 substitute 3.4 design 3.5 discover |
Table 3: Merrill et al's categories of transaction
The main difference between the schemes proposed by Bloom and Gagne is that Bloom uses a larger number of categories. Apart from this difference, the two schemes are very similar. Rohwer and Sloane (1994), compare the schemes proposed by Bloom et. al. and Gagne and conclude that,
The framework Gagne proposed arguably represents the closest parallel to the presuppositions we have identified in the Taxonomy. (p. 55)and that,
With regard to the propositions about varieties of learning, then, the 1977 version of the Gagne framework approximated that presented in the Taxonomy in 1956. (p.56).
Gagne himself describes Bloom's Taxonomy as being "somewhat different, although not incompatible" to his own (Gagne & Briggs, 1974, p.95).
In deciding which of these two schemes to use, the question, then, is what level of detail is required for the purposes of the proposed matrix. As discussed earlier, a scheme is required that separates outcomes that would be achieved using different CAL activities. This is best illustrated with an example.
The following are two possible learning outcomes for a CAL system on automotive engineering:
It would appear then, that the greater level of detail provided by Bloom is necessary in order to differentiate between learning outcomes that are likely to be achieved using different activities. Consequently, Bloom's scheme is the most appropriate for the purposes of this research.
Gaining attention.
Informing learner of the objective.
Stimulating recall of prerequisite learning.
Presenting the stimulus material.
Providing learning guidance.
Eliciting the performance.
Providing feedback about performance correctness.
Assessing the performance.
Enhancing retention and transfer.
(Gagne, Briggs and Wager, 1992, p. 200)
These events originally were intended to describe the activities of a teacher in a conventional learning environment, and although they could equally be applied to a CAL environment, they would describe the activities of the computer in "instructing" the learner. The idea of the computer instructing the learner is inconsistent with the constructivist theory of learning, which is fundamental to this paper.
Sims and Hedberg (1995) attempt to categorise the various aspects of learner control that are evident within a CAL resource. In doing so they suggest a five dimensional framework for analysing the characteristics of a particular resource. Each dimension is described as a continuum between two extremes. The following are the proposed dimensions:
| Instructor control | ß----------------------------------------------à | Learner control | |
| Linear | ß----------------------------------------------à | Hypermedia | |
| Viewed | ß----------------------------------------------à | Constructed | |
| Discrete | ß----------------------------------------------à | Integrated | |
| Informative | ß----------------------------------------------à | Self-Paced |
This framework provides an interesting way of measuring the degree of interactivity within a CAL resource, and could in fact be used as a way of classifying types of learner activity. However, such a method of classifying learner activities could not be easily used within the matrix proposed in this paper.
Although these three types of interaction do, in fact, describe three types of activities that a learner might carry out using CAL software, they are too broad for the requirements of this paper.
Laurillard (1993) analyses the teaching and learning process, which she sees as a dialogue between the learner and a teacher. She derives a Conversational Framework, which consists of a list of 12 activities that are carried out by a teacher or a learner, each categorised as either discursive, adaptive, interactive or reflective. The activities are as follows:
Descriptive:
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Interactive
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Adaptive
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Reflective
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Table 4: Laurillard's conversational framework
The following section, then, proposes a new classification scheme for learner activity suitable for use in the proposed matrix.
The 14 categories of learner activity are described in the following sections. Examples drawn from existing CAL resources are used to help explain each of the categories.
1. Attending to static information
Attending to information might include reading, looking at diagrams, listening to sounds and watching movies.
2. Controlling media
Typically, the information within a CAL resource will be in a variety of media forms, each requiring the learner to control them in a particular way. For example, media such as movie or sound clips require the learner to be able to play, pause, and rewind the clip. Large sections of text media may also need some form of control mechanism, so that the learner can control the passage that they are viewing at a given time. Note that this category does not include the more interactive forms of control that would typically occur within a graphical simulation.
The CAL system for undergraduate teacher education students, Teaching in Context (1995) includes many examples of digitised movies and voice recordings that can each be played under learner control.
Figure 1: Teaching in Context
3. Navigating the system
Navigating the system can involve choosing a content element, choosing a task to be undertaken or browsing through the system looking for information. Typical navigation techniques would include clicking on hypertext links, choosing items from menus or clicking on icons or hot spots.
The CD-ROM From Alice to Ocean (Smolan, 1992), uses a variety of navigation techniques that allow the learner to choose their own path through the system.
Figure 2: From Alice to Ocean
4. Answering questions
There are a range of different types of question that a learner could answer within a CAL environment, including simple multiple choice or true/false questions, single word or sentence answer questions or structured essay questions. Clearly, for some types of answers, automatic feedback will be feasible and for others it will not. This category also includes the answering of questions where the answer may involve multiple steps (sometimes termed problem-solving questions). However, it does not include the problem-solving activities that might be undertaken within a simulated environment.
The CAL system Curry Cookery Concepts (Dalgarno, 1996b) includes a number of different types of questions as part of a quiz on curry ingredients.
Figure 3: Curry Cookery Concepts
5. Attending to question feedback
Although attending to feedback is a similar activity to attending to static information, the fact that the information has been provided in response to something that the learner has done, is likely to alter the way that the learner will take in and encode the information. Question feedback might be in the form of text, diagrams, sounds, animations or movies. The Intelligent Physics Tutor (Mueller et al., 1996) dynamically generates feedback as the learner attempts to solve physics problems.
6. Exploring a world
The word 'world' is used to refer to graphical and non-graphical simulations or models of real world phenomena, as well as graphical microworlds that allow abstract concepts to be explored. Exploring such a world would typically involve clicking on hot spots or hypertext links or choosing items from menus, to navigate through the environment. This category does not include the provision of input that might change the behaviour of the world. For example, using the scroll bars to explore the different parts of the city in Sim City (Wright, 1989) would be in this category, but adding new roads or residential areas would not.
Figure 4: Sim City
7. Measuring in a world
Some simulations and microworlds allow the learner to carry out measurements or gather data within the environment, which the learner can use to develop their own understanding of the simulated phenomena or concepts. Investigating Lake Illuka (1995) provides a set of tools that allow the learner to measure the temperature, chemical composition and other information about parts of the simulated ecosystem.
Figure 5: Investigating Lake Illuka
8. Manipulating a world
This category includes, for example, the making of decisions within a time based simulation or the adjusting of parameters within a simulated model of a system. It does not include the construction of new objects within a graphical simulation or microworld. For example, the decision about which crops to plant in Bihari Farmer (Stainfield and Bailey, 1996) or the modification of the taxation percentage in Sim City (Wright, 1989) would be included in this category.
9. Constructing in a world
Within a graphical simulation or microworld, the learner is typically provided with tools to allow them to design, create or construct new entities within the environment. For example, in the Geometer's Sketchpad (1995) microworld the learner constructs geometrical objects and explores their characteristics, in Sim City (Wright, 1989) the learner designs cities, adding roads, parks, residential areas and power lines to the existing terrain, and in The Incredible Machine (1992), the learner constructs machines made from cogs, wheels, conveyer belts and many other objects in order to solve a given problem.
10. Attending to world changes
The activity of attending to changes within a simulated world is a similar activity to attending to static information, but the fact that the information is typically the result of actions the learner has undertaken within the environment is likely to result in significantly different learning outcomes. This activity is also different to the activity of attending to feedback, because attending to feedback is likely to result in the learner reflecting on their response to a specific question, whereas the activity of attending to world changes is likely to result in the learner adding to or modifying their understanding of the phenomena or concepts being simulated. For example, the activity of attending to the results of testing a constructed machine in The Incredible Machine (1992), would be in this category.
Figure 6: The Incredible Machine
11. Articulating
According to constructivist theories of learning (Dalgarno, 1996a) the process of articulating their current understanding of concepts, can help learners to develop this understanding. Articulation of ideas could take the form of brief text based annotations associated with specific bodies of text within a hypermedia environment. Alternatively, it might consist of longer pieces of writing that sum up the learner's knowledge of a particular domain area at a given time. The articulation might also include diagrams drawn using drawing tools, sounds recorded with a microphone, animations, movies or even hypermedia environment or simulations developed by the learner.
The quantum physics tutorial, Understanding the Unobservable (Cheetham, Rayner, & Bennet, 1995), provides an option on each screen that allows the learner to annotate the information with their own comments.
12. Processing data
Within some knowledge domains, particularly quantitative domains, learners need to make sense of data that they gather in order to understand the phenomena that is the subject of the CAL environment. This data might be gathered as the result of actions within a simulated world, or it might simply be presented as static information within a hypermedia environment. Typically, the task of making sense of such data can be made easier by providing tools that allow the learner to carry out simple calculations or more advanced statistical analysis or to create graphs based on the data. Such tools might consist of a calculator, a spreadsheet package, or a graphing tool. One approach to the provision of such tools is to encourage the learner to make use of existing tools such as Microsoft Excel, which provides all of the data processing capabilities that most learners would need, from within the CAL environment.
Figure 7: Microsoft Excel
13. Attending to processed data
This category includes attending to the results of data processing either carried out by the learner or carried out by the CAL system. In either case, this activity is likely to improve the learner's understanding of the phenomena to which the data relates. For example, Bihari Farmer (Stainfield and Bailey, 1996) provides a spreadsheet-like screen that allows the learner to choose from a range of financial investment options at the end of each year. The system then carries out the data processing that allows the learner to keep track of the cost of the various options and the amount of money they will have left over. It also provides a screen that allows the learner to look at graphical representations of the performance of their farm over previous years.
Figure 8: Bihari Farmer
14. Formatting output
Having articulated their understanding of a particular content domain, the learner will sometimes want to make this information available to others. Typically, they will want to improve the appearance of the information using the formatting tools provided within a word processing or desktop publishing package. This activity is quite distinct from the activity of articulating the information in the first place, and is likely to lead to different learning outcomes.
Additionally, despite the fact that the learning outcome classification scheme chosen (Bloom's Taxonomy) has a large number of categories, the characteristics of the outcomes that may be described within a single category are likely to vary widely. Consequently, it is likely that categories of activity that are appropriate for some outcomes within a category may not be appropriate for others. Thus, the set of activities included in the matrix needs to be a super set of the activities that might be appropriate for the different outcomes that could come under a particular category.
The designer of CAL resources, then, will use the matrix as a way of getting ideas for the types of activities that may be appropriate for a particular category of outcome, but will then choose activities appropriate to the specific intended learning outcomes of the resources they are developing. That is, it is not intended that designers attempt to include all of the activities shown in the matrix, for each outcome.
Another important issue is that the learner is likely to carry out a number of activities in order to achieve a particular learning outcome. For example, if the learner is manipulating objects within a microworld in order to gain an understanding of certain scientific principles, they are likely to carry out activities such as navigating the system as well as exploring, measuring, manipulating and constructing within the 'world'. Consequently, it is important to distinguish between activities that are of primary importance in achieving the learning outcome and activities that are of secondary importance.
Using these broad principles as a starting point, then, the matrix shown below illustrates the hypothesised connections between learning outcomes and learner activities.
| Key: | |
| Learner Activities of primary importance in achieving an Outcome: |  |
| Learner Activities of secondary importance in achieving an Outcome: |  |
| Learner Activities not likely to assist in achieving an Outcome: |  |
| CAL Resources Selected for Review | ||
| CAL Category | Package | Curriculum Area/Target Learners |
| Drill | French Word Torture (Rice, 1995) | Language - Secondary |
| Tutorial with Practice Component | Understanding the Unobservable (Cheetham, Raynor, & Bennet, 1996) | Quantum physics - Tertiary |
| Alge Blaster Plus (Hertz, De Witt, & Ely, 1995) | Mathematics - Primary | |
| Intelligent Tutoring System | The Intelligent Physics Tutor (Mueller et al., 1996) | Physics - Secondary |
| Lisp Tutor (Weber et al., 1996) | Computer Science - Tertiary | |
| Hypermedia Information Database | BioKiosk (Wellman, Herbert, & Le Blanc, 1996) | Environmental Science - Secondary/Tertiary |
| Passage to Vietnam (Smolan et al., 1996) | Geography - Secondary/Tertiary | |
| Grolier Multimedia Encyclopedia (1996) | General - Primary/Secondary | |
| Hypermedia Tutorial | Investigating Lake Iluka (1996) | Environmental Science - Secondary |
| Teaching in Context (1995) | Education - Tertiary | |
| Flashback (1993) | History - Secondary | |
| Somazone (1997) | Health Education - Secondary | |
| Simulation | Sim City (Wright, 1989) | Social Science - Secondary |
| Gold Fields (1990) | Social Science/History - Secondary | |
| Bihari Farmer (Stainfield and Bailey, 1996) | Geography - Secondary/Tertiary | |
| Microworld | The Incredible Machine (1992) | Science - Primary/Secondary |
| Interactive Physics (1995) | Physics - Secondary/Tertiary | |
| Geometer's Sketchpad (1995) | Geometry - Secondary/Tertiary | |
| Cognitive Tool | Stella (1996) | General - Secondary |
| SemNet (Faletti et al., 1993) | General - All levels | |
| Support Tool | Microsoft Excel (1996) | General - All levels |
| Microsoft Word (1996) | General - All levels | |
An alternative activity for achieving these knowledge outcomes, according to the matrix, is that of attending to question feedback. Constructivist theories of learning would suggest that this activity would tend to be more effective, because the learner would be more active. Resources reviewed, that make use of questions with feedback to achieve knowledge outcomes, include the algebra program Alge-Blaster Plus and the quantum physics program, Understanding the Unobservable.
However, the matrix also suggests that the activities of exploring, measuring, manipulating and constructing a world and attending to world changes, can be of primary importance in achieving many knowledge outcomes. In fact, constructivist theories of learning suggest that such activities are likely to be even more effective in many situations, because the learner is more active again. Resources that make use of such activities, to achieve knowledge outcomes, include the geography resource Bihari Farmer, the environmental science resource, Investigating Lake Iluka, and the Australian history resource, Goldfields.
According to the matrix, the more complex learning outcomes, such as the application of principles to new situations, and the analysis of the relationships between principles, can be achieved through the activities of answering questions and attending to feedback. Again, however, the activities of exploring, measuring, manipulating and constructing a world can also contribute to the achievement of the outcomes, and constructivist theories would suggest that such activities are likely to be most effective. Resources that make use of a simulated world for the achievement of these outcomes, include the urban planning program Sim City and physics program Interactive Physics.
Having discussed some of the important connections between learning outcome and learner activity suggested by the matrix, with reference to examples in the reviewed resources, the next section discusses the use of the matrix within the CAL design process.
For many categories of learning outcome, the matrices suggest that a number of different types of learner activity will be appropriate. It is not intended, however, that all of these activity types will be used. Instead, activities will be chosen that are appropriate for the particular target learners, and ideally, which will help to achieve a range of different outcomes. For example, if most of the outcomes are in the category of knowledge of specific facts, then although activities like exploring a world might help to achieve the outcomes, basic attending to static information is also likely to allow the outcomes to be achieved, but with far less development effort. However, if there are a number of outcomes in the category of knowledge of principles and generalisations, then the use of activities like exploring a world are likely to be the most appropriate, and consequently these activities could also help to achieve outcomes in the knowledge of specific facts category.
The first task of the designer, however, in using the matrices, is to categorise the learning outcomes. The matrices use Bloom's Taxonomy (Bloom et. al. 1956) as the classification scheme for learning outcomes, and consequently the designer will need to acquire some familiarity with the Taxonomy. A complete description of the categories in the Taxonomy is beyond the scope of this paper but there are a number of books on the subject (see for example, Anderson and Sosniak, 1994; Bloom et. al., 1956).
Having listed the outcomes in their categories, the next task is to list the types of learner activity for each outcome. These types of activity can be read directly from the matrix. Specifically they will be the categories of activity that the matrix proposes will be of primary importance in achieving the outcomes. Having listed the possible types of learner activity alongside each outcome, the designer should be able to get a feel for the categories of activity that appear the most. The next task is to design the core learner activities. For example, for resources that will include the exploration and manipulation of a world, this is the time to sketch out the components of the world, and if the world is to be represented graphically, its visual appearance.
Once the core activities have been designed, the next task will be to describe the specific activities available to the learner to achieve each of the intended learning outcomes. This process will involve firstly choosing which categories of learner activity suggested by the matrices will actually be used, and then designing the activities for each of these categories.
In addition to the core activities, which are very specific to the content of the resource, there will often be more generic activities that will assist with the achievement of many different outcomes. The activities of articulating and processing data are often in this category. For these types of activities, the developer of the resources could create a generic "tool", which is accessible at all times from within the resource. Hedberg and Harper (1998) have advocated the use of such tools.
As part of the process of developing the matrix, 22 CAL resources were reviewed. Although this is not sufficiently large a sample to provide any solid empirical evidence in favour of the matrix, the examples from this review do serve to clarify the information contained within it to some extent. One possible direction for further research would be to run a more formal empirical trial, using a larger number of CAL resources, and including groups of learners in the review process.
The final section of the paper explains in brief how the matrix could be used within the CAL design process. A more thorough analysis of the process of designing and developing constructivist CAL resources, including the use of the matrix, will be the subject of another paper.
Bloom, B. S. (ed) (1956). Taxonomy of Educational Objectives. Handbook I: Cognitive Domain. London: Longman Group.
Borich, D.B. & Tombari, M.L. (1995). Educational Psychology A Contemporary Approach. New York: Harper Collins College Publishers.
Cazden, C.B. (1986). Classroom Discourse. In M.C. Wittrock (ed), Handbook of Research on Teaching. New York: Macmillan.
Cheetham, A., Rayner, J. & Bennet, S. (1995). Understanding the Unobservable [computer software]. Canberra: University of Canberra.
Dalgarno, B.J. (1996a). Constructivist Computer Assisted Learning: Theory and Techniques. In A. Christie, P. James, and B. Vaughan (eds), Making new Connections, Proceedings of ASCILITE Conference 1996, (pp. 127-148). Adelaide: University of South Australia. Available: http://farrer.riv.csu.edu.au/~dalgarno/publications.html [1998, June 12]
Dalgarno, B.J. (1996b). Authoring your own Learning Resources: An Analysis of the Tools Available. Proceedings of The Australian Computer Education Conference 1996 [online]. Available http://www.spirit.com.au/ACEC96/papers/dalg.htm [1998, June 12]
Faletti, J., Fisher, K.M., Patterson, H.A., Lipson, J.I., Brockenbrough, S.A., Logan, J.D., & Thornton, R.M., (1993). SemNet [computer software]. San Diego, California: SemNet Research Group. Available: http://www.biologylessons.sdsu.edu/about/aboutsemnet.html [1998, June 12]
Flashback [computer software]. (1993). Sydney: NSW Department of School Education.
Gagne, R.M. & Briggs, L.J. (1974). Principles of Instructional Design. New York: Holt, Rinehart & Winston.
Gagne, R.M. (1977). The Conditions of Learning. New York: Holt, Rinehart and Winston.
Gagne, R. M., Briggs, L. J. & Wager, W. W. (1992). Principles of Instructional Design. Fort Worth: Harcourt Brace Jovanovich College Publishers.
The Geometer's Sketchpad [computer software]. (1995). Berkeley: Key Curriculum Press. Available: http://www.keypress.com/ [1998, June 12]
Gold Fields [computer software]. (1990). Sydney.
The New Grolier Multimedia Encyclopedia [computer software]. (1996). Danbury, CT: Grolier Electronic Publishing Incorporated.
Hedberg, J. and Harper, J. (1998). Visual Metaphors and Authoring. ITFORUM Discussion List [online]. Available: http://www.immll.uow.edu.au/~JHedberg/ITFORUM.html [1998, June 12]
Hertz, A., De Witt, B., and Ely, D. D. (1995). Alge Blaster Plus [computer software]. Davidson and Associates Inc.
The Incredible Machine [computer software]. (1992). Sierra Online Incorporated.
Interactive Physics [computer software] (1995). San Mateo, California: Knowledge Revolution. Available: http://www.krev.com/ [1998, June 12]
Investigating Lake Iluka [computer software]. (1995). Wollongong, NSW: Interactive Multimedia Unit, University of Wollongong, NSW.
Laurillard, D. (1993). Rethinking University Teaching, A Framework for the Effective Use of Educational Technology. London: Routledge.
Merrill, M.D. (1983). Component Display Theory. In C.M. Reigeluth (ed), Instructional-Design Theories and Models: An Overview of their Current Status, (pp. 279-334). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
Merrill, M.D. Li, Z. & Jones, M. (1990). Second Generation Instructional Design (ID2). Educational Technology, 30(2), 7-14.
Merrill, M.D., Li, Z., & Jones, M. (1992). An Introduction to Instructional Transaction Theory, In S. Dijkstra, H.P.M. Krammer, & J.G. van Merrienboer (eds), Instructional Models in Computer-Based Learning Environments, (pp. 15-43). Berlin: Springer-Verlag.
Microsoft Excel for Windows 95 [computer software]. (1996). Redmond, WA: Microsoft Corporation.
Microsoft Word for Windows 95 [computer software]. (1996). Redmond, WA: Microsoft Corporation.
Mueller, S., Way, B., Patton, C., Wang, J., Bowen Loftin, R., Escobedo, J., Lee, B., Riley, G., Donnell, B., & Brown, S. (1996). The Intelligent Physics Tutor [computer software]. Available: http://nautilus.lincom-asg.com/icat/prod/PT.html [1998, June 12]
Rice, M.P. (1995). French Word Torture (version 3.0) [computer software]. Knoxville, TN: The HyperGlot Software Company, Inc.
Rieber, L. P. (1994). Computers, Graphics and Learning. Debuque, IA: Brown and Benchmark.
Rohwer & Sloane (1994). In Anderson, L.W. & Sosniak, L.A. eds (1994). Bloom's Taxonomy : A Forty-year Retrospective. Chicago: University of Chicago Press.
Sims, R. and Hedberg, J. (1995). Dimensions of Learner Control: A Reappraisal for Interactive Multimedia Instruction. In J.M. Pearce & A. Ellis (eds), Learning with Technology, Proceedings of the Twelfth Annual Conference of the Australian Society for Computers in Learning in Tertiary Education, (pp. 468-475). Melbourne: University of Melbourne.
Smolan, R. (1992). From Alice to Ocean [computer software]. San Francisco, California: Against All Odds Productions.
Smolan, R., Erwitt, J., Singer, S.A., Wheeler, M., Liddle, D., Laurel, B. and Hirst, N. (1996). Passage to Vietnam [computer software]. San Francisco, California: Against All Odds Productions.
Somazone [computer software]. (1997). Melbourne: Cinemedia.
Stainfield, J. and Bailey, P. (1996). Bihari Farmer [computer software]. Plymouth, UK: University of Plymouth.
Stella (version 3) [computer software]. (1996). Hanover, NH: High Performance Systems, Available: http://www.hps-inc.com/ [1998, June 12]
Teaching in Context [computer software]. (1995). Armidale, N.S.W.: Centre for Research into the Educational Applications of Multimedia, University of New England.
Weber, G., Wender, K.F., Specht, M. and Steinle, F. (1996). Lisp Tutor [computer software]. University of Trier Germany, Available: http://www.psychologie.uni-trier.de:8000/projects/ELM/elmart.html [1998, June 12]
Wellman, K., Herbert, E. & Le Blanc, R. (1996). BioKiosk [computer software]. Canberra: University of Canberra.
Wright, W. (1989). SimCity. Moraga: California: Maxis.
| Barney Dalgarno Lecturer in Information Technology, School of Information Studies Charles Sturt University, Wagga Wagga, NSW Australia Ph. +61 2 6933 2305 Fax: + 61 2 6933 2733 bdalgarno@csu.edu.au http://farrer.riv.csu.edu.au/~dalgarno Please cite as: Dalgarno, B. (1998). Choosing learner activities for specific learning outcomes: A tool for constructivist computer assisted learning design. In C. McBeath and R. Atkinson (eds), Planning for Progress, Partnership and Profit. Proceedings EdTech'98. Perth: Australian Society for Educational Technology. http://www.aset.org.au/confs/edtech98/pubs/articles/dalgarno.html |