Choosing Learner Activities for Specific Learning Outcomes:
A Tool for Constructivist Computer Assisted Learning Design
Paper Submitted to EdTech’98 Virtual Conference
Barney Dalgarno, Charles Sturt University
Abstract
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.
1. Introduction
In the development of Computer Assisted Learning (CAL) resources, one of the most
important tasks is the design of activities for learners to undertake as they use the resources.
This is especially important if a constructivist view of learning forms the basis of the
development, because one of the fundamental principles of constructivism is that learning
occurs primarily through the learner’s activity, rather than through passively receiving
information (Dalgarno, 1996a).
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.
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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.
2. Categories of Learning Outcome
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.
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2.1
Reviews of Learning Outcome Classification Schemes in the Literature
Gropper (1983), in discussing taxonomies of learning objectives, finds that such taxonomies
can be divided into two broad groups. Firstly, there are those that attempt to define objectives
as an intact whole (intact classification of objectives), and secondly there are those that
attempt to break objectives down into their constituents (dissection of objectives). For the
purpose of this research, where specific objectives are to be related to learner activities, a
taxonomy of the first type is required. Gropper lists three taxonomies that use an intact
classification: Bloom et al’s Taxonomy of Educational Objectives (1956); Gagne and Briggs’
Categories of Learning Outcomes (1974); and Merrill’s Performance-Content Matrix (1983).
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.
2.2
A Comparison of the Classifications Proposed by Bloom et. al., Gagne
and Merrill
2.2.1 Bloom et. al.’s Learning Outcome Classification Scheme
The contributors to Bloom’s Taxonomy published their proposed classification scheme in
three separate volumes, for the three domains of learning, cognitive, affective and
psychomotor. Their first volume addresses those outcomes in the cognitive domain (Bloom
et. al., 1956). The following table shows the categories and sub-categories of learning
outcome identified in this volume.
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1.
2.
Knowledge
1.1 Knowledge of specifics
1.11 Knowledge of terminology
1.12 Knowledge of specific facts
1.2 Knowledge of ways and means of dealing
with specifics
1.21 Knowledge of conventions
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
1.32 Knowledge of theories and structures
3.
Application
4.
Analysis
4.1 Analysis of elements
4.2 Analysis of relationships
4.3 Analysis of organisational principles
5.
Synthesis
5.1 Production of a unique communication
5.2 Production of a plan, or a proposed set of
operations
5.3 Derivation of a set of abstract relations
6.
Evaluation
6.1 Judgements in terms of internal evidence
6.2 Judgements in terms of external criteria
Comprehension
2.1 Translation
2.2 Interpretation
2.3 Extrapolation
Table 1.
Bloom et al’s Categories of Learning Outcome
2.2.2 Gagne’s Learning Outcome Classification Scheme
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.
1.
Intellectual skill;
1.1 Discrimination;
1.2. Concrete concept;
1.3. Defined concept;
1.4. Rule;
1.5. Higher order rule;
2.
Verbal information;
3.
Cognitive strategy.
Table 2.
Gagne et al’s Categories of Learning Outcome
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2.2.3 Merrill’s Learning Outcome Classification Scheme
Merrill first presented a classification scheme for learning outcomes in the form of a
Performance-Content Matrix, as part of his Component Display Theory (Merrill, 1983). This
later evolved into Instructional Transaction Theory (Merrill, Li & Jones, 1992). As part of
Instructional Transaction Theory, Merrill attempts to classify the different instructional
interactions that a learner might be involved in (either in a CAL environment or in a
conventional learning environment). These instructional interactions are termed transactions.
He notes that different transactions promote different learner capabilities and describes these
transactions in terms of observable behaviours. Consequently, the transactions effectively
each describe a type of learning outcome. The following transactions are identified:
1.
Component transactions
1.1 identify
1.2 execute
1.3 interpret
2.
Abstraction transactions
2.1 judge
2.2 classify
2.3 generalise
2.4 decide
2.5 transfer
3.
Association transactions
3.1 propagate
3.2 analogise
3.3 substitute
3.4 design
3.5 discover
Table 3.
Merrill et al’s Categories of Transaction
2.2.4 Comparison of the Three Classification Schemes
Merrill’s scheme is particularly cumbersome to work with, and although it has been used by
Merrill and his colleagues in the development work that they have carried out as part of their
second generation instructional design project (Merrill, Li & Jones, 1990), it has not been
widely used outside of this context. Consequently, it fails to fulfil the requirements that the
chosen scheme be easy to use and widely understood.
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).
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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:
1.
At the end of the instruction the learner will be able to describe using correct terminology
the parts of a 1986 Ford Telstar engine.
2.
At the end of the instruction the learner will be able to state the specifications for a 1986
Ford Telstar engine, including cylinder capacity, sump capacity and maximum horse
power.
Both of these objectives would come under the heading of Verbal Information in Gagne’s
scheme, whereas the first would come under Knowledge of Terminology and the second under
Knowledge of Specific Facts under Bloom’s scheme. It is likely that quite different methods
would be used for achieving the two outcomes. For example, an understanding of the
terminology could be obtained through reading of text containing the terms, with hypertext
links to a precise definition of each term. On the other hand, the numeric specifications of the
engine could be illustrated using a graphical simulation of the engine.
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.
3. Classifying Learner Activity
Having settled on a classification scheme for learning outcome, the next task of the paper is to
choose a classification scheme for the activities that a learner undertakes within a CAL
environment. The concept of learner activity, however, has not been as thoroughly researched
as the concept of learning outcome. Consequently, it is more difficult to find an appropriate
classification scheme. This section looks at classification schemes for various aspects of the
CAL process that have been proposed, specifically those proposed by Gagne and Briggs
(1974), Sims and Hedberg (1995), Merrill, Li and Jones (1992) and Laurillard (1993).
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3.1
Gagne, Briggs and Wager’s Events of Instruction
Gagne and Briggs (1974; 1992) describe the events that typically occur as part of an
instructional sequence, in terms of the actions of the teacher. They term these the Events of
Instruction. The events are as follows:
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.
3.2
Sims and Hedberg’s Dimensions of Learner Control
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
----------------------------------------------
Learner control
Linear
----------------------------------------------
Hypermedia
Viewed
----------------------------------------------
Constructed
Discrete
----------------------------------------------
Integrated
Informative
----------------------------------------------
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.
3.3
Merrill, Li and Jones’ Instructional Transaction Theory
In Section 2 of this paper, the classes of transaction described by Merrill, Li and Jones (1990;
1992) were compared to classes of learning outcome. Instructional Transaction Theory also
proposes that for each of the categories of transaction, there are three types of interaction:
information, demonstration and manipulation.
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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.
3.4
Laurillard’s Conversational Framework
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:
 Teacher describes conception
 Student describes conception
 Teacher describes conception in light of student’s
conception or action
 Student redescribes conception in light of
teacher’s redescription
Interactive
 Teacher sets task goal
 Student acts to achieve task goal
 Teacher’s world gives feedback on action
 Student modifies actions in light of feedback
Adaptive
 Teacher adapts task goal in light of student’s
description or action
 Student adapts action in light of teacher’s
description
Reflective
 Student reflects on interaction to modify
description
 Teacher reflects on action to modify description
Table 4.
Laurillard’s Conversational Framework
Although this framework focuses on the actions of a learner and a teacher, it could equally be
applied to a CAL environment, with the computer filling the role of the teacher. Unlike
Gagne’s Events of Instruction (discussed above), the role of the teacher that is implicit within
the framework is one of a facilitator rather than an instructor, and consequently the framework
is consistent with the constructivist theory of learning. However, for the purposes of the
matrix to be proposed in this paper, a classification scheme is required that refers only to the
actions of the learner and which includes activities specific to the CAL environment.
3.5
Comparing the Four Classifications
For the purposes of this paper, a classification of learner activity within a CAL environment is
needed that will be able to be used as the basis for the design of CAL resources that are likely
to allow these activities to be carried out. None of the classification schemes reviewed above
satisfies this requirement. Gagne and Briggs’ scheme has implicit within it a nonconstructivist view of the learning process, Sims and Hedberg’s scheme could not easily be
used as one dimension of a matrix, Merrill’s scheme is too broad, and Laurillard’s is not
phrased solely in terms of the activities of the learner.
The following section, then, proposes a new classification scheme for learner activity suitable
for use in the proposed matrix.
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4. A New Learner Activity Classification Scheme
The proposed classification scheme for learner activity consists of 14 activities a learner could
undertake within a CAL environment, which are consistent with a constructivist theory of
learning. It is worth noting that the various interpretations of constructivism (for example the
exogenous, endogenous and dialectic interpretations) each suggest the use of different CAL
techniques (Dalgarno, 1996a). This classification scheme attempts to encompass all such
techniques.
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.
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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 problemsolving 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.
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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
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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
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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
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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.
5. A Matrix Connecting Outcomes to Activities
Having chosen a classification scheme for learning outcomes, and devised a classification
scheme for learner activity, the primary task of this paper can now be carried out, that is, to
derive a method of choosing learner activities that are likely to facilitate the achievement of
specific learning outcomes. Specifically, a matrix that indicates the categories of learner
activity likely to assist with the achievement of each category of learning outcome is
proposed. 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.
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5.1
Discussion About the Matrix to be Proposed
It is important to note that, from a constructivist perspective, no single activity is likely to be
appropriate for achieving an outcome, for all learners. The role of the designer of CAL
resources is to provide an environment that allows a number of different activities to be
carried out. Such an environment will allow the learner to choose activities appropriate to
their learning style. Consequently, in proposing categories of learner activity likely to
facilitate the achievement of each category of outcome, a super set of the activities that will be
appropriate for different learners is required.
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.
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Learner Activities that are Expected to Lead to Learning Outcomes
Category of Learner Activity
1.11 Knowledge of terminology
1.12 Knowledge of specific facts
1.21 Knowledge of conventions
1.22 Knowledge of trends and sequences
1.23 Knowledge of classifications and categories
1.24 Knowledge of criteria
1.25 Knowledge of methodology
1.31 Knowledge of principles and generalisations
1.32 Knowledge of theories and structures
2.1 Translation
2.2 Interpretation
2.3 Extrapolation
3. Application
4.1 Analysis of elements
4.2 Analysis of relationships
4.3 Analysis of organisational principles
5.1 Production of a unique communication
5.2 Production of a plan, or a proposed set of operations
5.3 Derivation of a set of abstract relations
6.1 Judgements in terms of internal evidence
6.2 Judgements in terms of external criteria
14. formatting output
13. attending to processed data
12. processing data
11. articulating
10. attending to world changes
9. constructing in a world
8. manipulating a world
7. measuring in a world
6. exploring a world
5. attending to question feedback
4. answering questions
3. navigating the system
2. controlling media
1. attending to static information
Category of Learning outcome
(using Bloom's taxonomy)
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:
Figure 9
Hypothesised Learning Outcome-Learner Activity Matrix
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6. Examples from a Review of 22 CAL Resources
As part of the process of devising the hypothesised connections between learning outcomes
and learner activities, 22 CAL resources were reviewed. For each package the expected
outcomes and the learner activities that were likely to assist with the achievement of these
outcomes were listed. This section lists the resources reviewed, and provides examples of
some of the learning outcomes and learner activities contained in the reviewed resources.
6.1
Resources Reviewed
In order to ensure that as large a range of outcomes and activities as possible was included in
the review, it was necessary to choose packages representing the various different CAL
approaches. Using the broad categories of CAL resources identified in an earlier paper
(Dalgarno, 1996a) as a starting point, packages were chosen so that at least one example of
each approach was included. The packages were also chosen to include a cross section of
curriculum areas and target learner levels. The following table shows the packages chosen,
along with the broad category to which they belong, their curriculum area and their target
learner level.
CAL Resources Selected for Review
CAL Category
Package
Curriculum Area/Target Learners
Drill
Tutorial with Practice
Component
French Word Torture (Rice, 1995)
Understanding the Unobservable (Cheetham,
Raynor, & Bennet, 1996)
Alge Blaster Plus (Hertz, De Witt, & Ely,
1995)
The Intelligent Physics Tutor (Mueller et al.,
1996)
Lisp Tutor (Weber et al., 1996)
BioKiosk (Wellman, Herbert, & Le Blanc,
1996)
Passage to Vietnam (Smolan et al., 1996)
Grolier Multimedia Encyclopedia (1996)
Investigating Lake Iluka (1996)
Teaching in Context (1995)
Flashback (1993)
Somazone (1997)
Sim City (Wright, 1989)
Gold Fields (1990)
Bihari Farmer (Stainfield and Bailey, 1996)
The Incredible Machine (1992)
Interactive Physics (1995)
Geometer’s Sketchpad (1995)
Stella (1996)
SemNet (Faletti et al., 1993)
Microsoft Excel (1996)
Microsoft Word (1996)
Language - Secondary
Quantum physics - Tertiary
Intelligent Tutoring
System
Hypermedia Information
Database
Hypermedia Tutorial
Simulation
Microworld
Cognitive Tool
Support Tool
Table 5.
CAL Resources Reviewed
Page 17
Mathematics - Primary
Physics - Secondary
Computer Science - Tertiary
Environmental Science Secondary/Tertiary
Geography - Secondary/Tertiary
General - Primary/Secondary
Environmental Science - Secondary
Education - Tertiary
History - Secondary
Health Education - Secondary
Social Science - Secondary
Social Science/History - Secondary
Geography - Secondary/Tertiary
Science - Primary/Secondary
Physics - Secondary/Tertiary
Geometry - Secondary/Tertiary
General - Secondary
General - All levels
General - All levels
General - All levels
6.2
Example Outcomes and Activities
The matrix suggests that the activity of attending to static information can be of primary
importance in achieving any of the knowledge outcomes. A number of resources reviewed
used this activity extensively, including the teacher education resource Teaching in Context
and the Australian history resource Flashback.
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.
7. Use of the Matrix within the CAL Design Process
The matrix described in this paper is intended to be a tool for the designers of CAL resources,
in choosing the activities learners will undertake as they use the resources. It is intended that
a developer of CAL resources will use the list of activity types for each intended outcome, as
a starting point in designing appropriate activities.
Page 18
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.
8. Conclusion
This paper has proposed a matrix connecting categories of learning outcome to categories of
learner activity. In order to do this, classification schemes for learning outcome and for
learner activity were required. Bloom’s Taxonomy of Educational Objectives was chosen as
the classification scheme for learning outcome, but no suitable schemes could be found for
classifying learner activity. Consequently a new scheme was proposed. This scheme
includes 14 categories of learner activity that might occur within a CAL environment.
Page 19
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.
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