Towards a Useful Classification of Learning Objects

Daniel Churchill

The University of Hong Kong

Abstract

The learning object remains an ill-defined concept, despite numerous and extensive discussion in the literature. This paper attempts to address this problem by providing a classification that potentially brings together various perspectives of what a learning object may be. Six unique types of learning objects are proposed and discussed: presentation, practice, simulation, conceptual models, information and contextual representation objects. The common characteristics of each are synthesized in a proposal that a learning object is best described as a mediated representation designed to afford uses in different educational contexts. The classification of learning objects proposed could be useful as a framework for designers of digital resources and for those engaged in reuse of these resources in educational contexts.

Problem with Learning Objects In the last few years, the concept of the learning object has received considerable attention in education communities. Initially, the idea appears to have emerged from traditional, direct instruction courseware design approaches issuing from professionals attempting to articulate more effective and economical strategies for management and reuse of resources in computer-based networked environments. The immediate understanding was that curriculum content can be broken down into small, reusable instructional components that address specific learning objectives and that could be tagged with metadata descriptors and deposited in digital libraries for subsequent machine-defined reuse (see Cisco Systems, 2001; E-learning Competency Center, 2003; IMS Global Learning Consortium, 2002; LAllier, 1998; Wiley, 2000). Another idea was that a learning object might be anything with an application in technology-supported learning (e.g. IEEE, 2001). As the idea of the learning object spread through education communities, it began to attract the attention of teachers and other professionals with an interest in educational reforms and contemporary pedagogies (which promote learner-centeredness, inquiries, experimentation and transformation of material, knowledge construction, conceptual change, authentic activities, problem solving and collaboration). This resulted in growing recognition that initial ideas may be incomplete and of limited use, and a call for reconsideration of what a learning object may be (e.g., Jonassen & Churchill, 2004; Lukasiak, et. al, 2005; McGreal, 2004, Wiley, 2002). A situation was created where education professionals, aware of the notion of the learning object, constructed diverging interpretations of what it may be based on their views about learning, students, teacher roles and technology (see Churchill, 2005a). Recently, most relevant research effort concentrated on defining learning objects. Lack of a generally accepted definition appears to have resulted in researchers focusing their effort in this direction, rather than engaging in more productive activity such as - for example - exploring and developing strategies for design and reuse of better

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educationally-effective digital resources. Currently, it appears difficult to arrive at a single definition of a learning object that would align communities with diverse perspectives. In this paper, I suggest that an acceptable classification accompanying a definition is a solution to this problem. Such classification should synthesize different interpretations and allow learning objects to be labelled, described, investigated and understood in ways that make the simplicity, compatibility and advantages claimed for them readily apparent to teachers, trainers and other practitioners (Friesen, 2003). Proposed Classification I propose a classification that contains the following types of learning objects: presentation, practice, simulation, conceptual models, information and contextual representation objects (see Table 1). Table 1: Types of learning objects

LO Type Explanation Simple Example Presentation

object Direct instruction and

presentation resources designed with the intention to transmit specific subject matter

A presentation or an instruction on classification of triangles

Practice object

Drill and practice with feedback, educational game or representation that allows practice and learning of certain procedures

Quiz question requiring a learner to use representation of a protractor to measure angles and answer a question regarding ration between base and height of the right-angled triangle

Simulation object

Representation of some real-life system or process

Simulation of a compass allowing learner to draw a geometric shape (e.g. equilateral triangle)

Conceptual model

Representation of a key concept or related concepts of subject matter

Representation that allows manipulation of parameters of a triangle, which in turn changes displayed modalities such as visual representation of a triangle, and numerical values of sizes of its angles and sides, and displays a graph showing changes in relationship between sides or angles

Information object

Display of information organized and represented with modalities

Representation that allows learners to change angles and sizes of a triangle and, based on configuration, to obtain information such as the type of triangle illustrated, a picture showing it in real-life and a short description of its properties

Contextual representation

Data displayed as it emerges from represented authentic scenario

Representation of a showing real-life examples of triangle (e.g. roof of a building) and allowing a learner to use representation of a tool (e.g. tape measure) to collect data about dimensions of these triangles.

Three types of learning objects - presentation, practice and conceptual models - emerged from previewing definitions from the literature. The following interpretations of what a learning object may be are noted:

i) Any digital or non-digital entity for technology-supported learning (IEEE, 2001). ii) Any digital resource used to support learning (Wiley, 2000). iii) Any digital resource used to mediate learning (Wiley & Edwards, 2002). iv) A reusable digital resource built in a lesson (McGreal, 2004).

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v) Interactive practice exercise (Dunning, 2002 in McGreal, 2004). vi) Small, stand-alone unit of instruction (E-learning Competency Center, 2003). vii) An instructional component that includes instruction that teaches a specific

learning objective and assessment that measures achievement (LAllier, 1998). viii) A collection of 72 components containing content, practice and assessment

parts (Cisco Systems, 2001). ix) A content object with a pedagogical component (Clifford, 2002). x) Combined knowledge object and a strategic object representing a mental model

to be developed by a learner through incremental elaboration (Merrill, 2000). xi) Interactive digital resource illustrating one or more concepts (Cochrane, 2005). xii) Interactive visual representation (Churchill, 2005b).

Based on these interpretations, a learning object may be: (a) an instruction or presentation object (vi, vii, viii, and ix refer); (b) a practice object (v refers); (c) a conceptual model, (x, xi and xii refer); (d) anything digital (ii, iii and iv refer), or (e) anything digital and non-digital (i refers) McGreal (2004) writes that the reality lies in accepting the limitation that LOs must be digital learning resources (p. 26), thus suggesting that the possibility that a learning object might be non-digital should be excluded. However, confining learning objects in general to digital form is also inappropriate because, as Merrill (2000) suggests, a learning object must be something more specific. Anderson (2003) writes that many definitions of a learning object do practically nothing to meaningfully discriminate one learning resource from another (p.20) and this is not helpful to those in the profession actually looking to develop reusable instructional resources (p.20). Three types of learning objects emerge from these interpretations as candidates for classification: presentation (instruction), practice and conceptual model objects. Wiley (2000) previously proposed a classification of learning objects; however, it received little attention in the literature and does not appear to have been of much use. Contrary to his interpretation of learning objects as anything digital, in his classification he appears to assert that learning objects are predominately instructional components. Wiley classified learning objects according to parameters, such as types and quantity of elements contained and whether these can be extracted and reused in other learning objects (e.g., a single image, digital video, a web page, a machine-generated instructional module that monitors learner performance on practices and tests). Wileys classification appears to support the inclusion in the classification of two types of learning objects instruction and practice objects - on the basis of common function (how learning objects are used). Wileys taxonomy hints at another type of learning object: presentation (including a single media display and exhibit). However, instruction and presentation objects are similar in that they present certain material with the intention to transmit messages; therefore, they may both be classified as presentation objects. The fourth type, a simulation object, emerges from a relatively old classification of computer-based educational material by Alessi and Trollip (1991). This classification suggests computer-based instruction or tutorial packages, drill and practice, simulations and games as possible types of computer-based educational resources. Although such computer-based material is conceptually different from learning objects, their forms and intended uses are similar. This classification hints at two additional types of computer-based resources besides presentation (computer-based instruction) and practice objects: simulation and games. Although simulation is a clear candidate for inclusion in the

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classification, many educational games I previewed appear to be in form of practice-type learning objects. The educational intention behind them is that underlining the design of practice objects; for example, a learner practises until a degree of competency or understanding is achieved. The remaining two types - information and contextual representation objects - emerged from my reflection and experience in designing educationally useful material, and from literature in relation to mediated representation, including ideas such as: external multimedia representations (Schnotz and Lowe, 2003), dynamic visualization (Ploetzner and Lowe, 2004), information visualization (Bederson and Shneiderman, 2003), visual explanations and envisioning information (Tufte, 1990; Tufte, 1997; Tufte, 2001), visual and multimedia displays (Mayer 2003), multiple representations (Van Someren, 1998), modality and multimodality (De Jong et al. 1998; van Someren, Boshuizen, de Jong and Reimann 1998) and interactive computer visualization (Fraser, 1999). These ideas also influenced my thinking in relation to the design of other types of learning objects. In concluding this part of the paper, I would like to suggest a definition of learning objects that might serve as an umbrella for the six types proposed by the classification. All types of learning objects appear to have these common characteristics: (a) they are digital, utilizing different media (and often interactivity) to represent data, information ideas, knowledge or reality, and (b) they are designed to afford educational reuse. Accordingly, I propose a general definition: a learning object is a mediated representation designed to afford uses in different educational contexts. This definition, to be clearly understood, should be considered in the context of the proposed classification. Discussion of the Types of Learning Objects in the Context of the Proposed Classification In this section of the paper, I discuss and illustrate each of the types of learning objects in the proposed classification. The illustrations provided are products of my attempt to validate the understanding of different types of learning objects by producing an example for each of them.

Presentation Objects Presentation objects include resources designed with a purpose to transmit a body of subject matter or lead to achievement of a specific learning objective. A presentation object attempts to transmit knowledge to learners by displaying messages representing chunks of subject matter. These messages can be aided by modalities and usually, certain principles are in place to ensure that learners are motivated and not overloaded. Content of such objects is usually divided into screens and sections, with a learner going through one section at a time. Other forms of a presentation object can be slide presentations with or without talking heads, videoed or audio-recorded lecturers, demonstrations, instructional video segments and animated instructions. Figure 1 shows an example of a presentation object developed with a software tool that allows easy recording and packaging of a presentation for on-line delivery.

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This area presents visual content of a slide

synchronized with a presenters voice

This area presents content of the presentation with

links to slides

These controls allow a learner to move between slides by using buttons or a slider, and pause or play

the presentation

Figure 1: An example of a presentation object Although presentation objects are mostly developed to support traditional pedagogical approaches, they might also support more contemporary pedagogies and activities such as problem solving. Davydov (1999) suggests that any resource might be used to mediate learning activity if that resource is given an instrumental role in the activity. Learners do not learn simply from reading and being exposed to instructional messages from resources, but they may effectively use that information to inform their decisions and actions in a learning activity. Practice Objects Practice objects allows learners, to practice certain procedures (e.g. dismantling a water pump), complete crosswords, drag objects and carry on certain tasks (e.g. dragging a protractor to measure an assigned angle), engage with an educational game or answer quiz questions. They might be designed to:

i) Incorporate interactivity and modalities and require learners to engage in some purposeful action and decisions before answering a question or executing an action.

ii) Provide constructive feedback (which might utilize modalities) and encourage learners to reflect on their action and further explore material, digital libraries, the internet, post a question on-line, engage in discussion with classmates, etc.

iii) Facilitate extension of learners current levels of understanding (or misunderstanding).

iv) Enable learners to build models of their own action and mistakes while executing a procedure.

Educational games might also be considered as practice objects, because they can promote persistent practice until a degree of competency or understanding is achieved. In more contemporary approaches, practice objects can be considered as parts of a learning activity process, rather than as some post-learning task that aims to strengthen learners recall and understanding of subject matter presented by a teacher or resources. Thus, a practice object might be given an instrumental role in an activity. Whatever

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learners conceptualize from their involvement with a practice object can be utilized for examples to inform their problem-solving decisions. Figure 2 shows a screen from the Volume of a Pyramid practice object. The question in the object requires a learner to approximate the volume of the pyramid presented in the scenario. This pyramid is an interactive 3-dimensional representation that can be rotated and visually examined by a learner. A learner rotates the pyramid and uses the provided ruler to capture its dimensions. The scale on the ruler is randomised. This means that different learners will have rulers of different lengths and that their answers will be different. This opens a possibility for collaboration between the learners, while removing the possibility of copying answers. Exchanging ideas on the solving of a problem is an important part of the learners collaboration. Copying of a method and copying of answers are two different things. Copying of a method opens the possibility for learners to learn from each other.

The learner uses the ruler to capture measurements needed to answer the question. The

scale on the ruler is randomized. This ensures that different

learners will obtain different measurements when answering

the question.

The learner rotates this three-dimensional model of a

pyramid to examine its sides

Constructive feedback is provided for any response by the learner. If incorrect, the learner is informed of the reasons they are

incorrect and advised of steps they might take towards correctly

answering the question. If the answer is correct, the learner is

provided with additional information to expand on

understanding.

Figure 2: Volume of a Pyramid practice object Simulation Objects Simulation objects represent some real system or process: e.g. a simulation of a microscope or of electricity consumption in a household. They allow a learner to explore, usually by trial and error, operational aspects of a system, carry on a task that the system supports, and develop a mind model of that systems functionalities. Although fidelity is often high in simulations, development of skills is hardly ever completed and learners must usually move to a real system to complete their practice to genuine competency level. However, by the time a learner shifts to the real system, he or she would already have constructed a mind model of the systems functionalities and operational possibilities. This is particularly effective when learning to use the real system requires an understanding beyond being able to operate it (e.g. understanding how a system works) and when the real system is expensive, unavailable or available in limited number, or learning to operate it is costly and possibly dangerous. A simulation might also involve

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dynamic processes such as manufacturing processes, financial flows and energy consumptions. In this case, a learner might manipulate certain parameters as he or she learns to manage that process. Figure 3 shows an interface of a Digital Multimeter simulation object. This learning object allows a learner to explore uses of a digital multimeter instrument by collecting different measurements for Voltage, Current and Resistance. A learner also explores correct positioning of probes in the circuit. Besides the main purpose of this simulation object (learning how to use the instrument), a learner might also collect different measurements of Voltage, Current and Resistance and explore relationships which exist between these parameters in order to derive understanding of a relationship known as Ohms Law.

This is the measurement read by the instrument (Value of Resistance in this case)

A learner can rotate this dial to select measurements that he or she wants to capture (Voltage,

Resistance and Current)

A learner positions probes for correct capture of measurements

A learner manipulates circuit by changing its perimeters

Figure 3: Digital Multimeter simulation object

Conceptual Models A conceptual model is a type of a learning object that represents one or more related concepts or ideas, usually in an interactive and visual way. It might be appropriate to think of a conceptual model as a representation of a cognitive resource existing in the mind of a subject matter expert, as useful conceptual knowledge that aids decision-making, disciplinary problem-solving and discipline-specific thinking. Psychologists use a variety of terms such as schemas (Paivio, 1974), mental models (JohnsonLaird, 1983) and concepts (Vygotsky, 1962) to more or less indicate the same idea that there are constructs in the human mind that mediate higher psychological functioning. Sometimes the term representation is used for constructs in the human mind. However, Von Glasersfeld (1999) writes that this use of representation is misguided, because it entails the belief that certain ideas we abstract from our experience correspond to a reality that lies beyond experience. For von Glasersfeld, knowledge is never representation of the real world, but a collection of conceptual structures adopted from experience. He suggests that humans segment part of their experiences into raw elementary particles and combine these into dynamic conceptual structures.

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An example of a conceptual model, Exploring Trigonometry, is presented in Figure 4. This learning object represents a key concept from trigonometry: a trigonometric circle. A subject matter expert, a mathematics teacher in this case, identified this as one of the key concepts in his mathematics knowledge which guides his thinking in problem-solving involving trigonometry. Through design process and analysis of his own knowledge, the learning object architect constructed this artifact. Learners can input different values for angle x and observe changes in values of sine and cosine as they conduct an inquiry. The changes in the values of sine and cosine are presented in multiple representation formats:

1. Numerically, as numbers between 0 and 1; 2. Visually, as projections of an arm of an angle along the x-axis (for value of

cosines) and along the y-ordinate (for value of sine x) of a trigonometric circle (a circle with radius one unit long), and

3. As points along the sine and cosine line on the graph.

Figure 4: Exploring Trigonometry conceptual model

Learners can change values of an angle as many times

as they choose

Output of numerical values for sine and cosine

of the selected angle

Values for sine and cosine of the selected angle

shown graphically on the sine and cosine curves

Values for sine and cosine of the selected

angle shown graphically in the trigonometric circle

Previous research with visual educational material introduced a conceptual model (see Mayer, 1989). Mayer suggests that these improve the ability of learners to transfer their learning to solve new problems because learners have constructed useful mind models that they are able to mentally manipulate when needed. Based on later studies involving technology-based representations, Mayer (2003) suggests that multiple representations facilitate learning because different modalities are encoded and organized in different mind models which, when mentally connected, lead to deeper understanding. Limitations of traditional non-interactive technologies and tools made these conceptual models not much different from print-based diagrams, images, drawings and charts. Now we have powerful technology-based tools that enable us to add critical dimensions to the design of conceptual models - interactivity and modalities. For Fraser (1999), these capabilities of contemporary technology provide unique opportunity for communication of concepts to learners through representational pedagogical models. Fraser writes in the past, we relied on words, diagrams, equations, and gesticulations to build those models piece by piece in the minds of the students we now have a new tool - not one that replaces the older ones, but one that greatly extends them: interactive computer visualization. Models were also discussed by Gibbons (n.d.). Gibbon suggests that all instruction should be based around three types of models representing instructional content: (a)

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models of environment; (b) models of natural or manufactured systems, and (c) models of human performance. However, these models appear to be representations of reality and expert performance, rather than models of conceptual knowledge. Interactivity and modalities allow the creation of conceptual models that potentially represent conceptual knowledge and ideas (not a simulation or demonstration of a performance). My thinking here is influenced by ideas of higher psychological functions, and models as effective tools for sharing of socio-historical knowledge accumulated by humanity (Vygotsky, 1978; Wartofsky, 1979). However, I intend to call on further research in the future to explore this idea of a conceptual model as a representation of conceptual knowledge and ideas, and to investigate how supplying these models can bring learners to higher levels of zone of proximity development. To design a conceptual model, a learning object architect must primarily examine knowledge in a head rather than information. The process can be informed by external factors such as similar designs by other people, tools, reference material and discussion with colleagues, but essentially, analysis of knowledge is central. This presents a difficulty for traditional instructional designers who are not usually subject matter experts, but rely upon documents, books, artifacts and other material to design instructional resources. To design a conceptual model, a learning object architect must either experience and construct knowledge by acquiring and applying it, or be able to effectively articulate such models through interaction with a subject matter expert. The first option is difficult, because no concept is an isolated cognitive resource, relating rather to many other concepts held by the subject matter expert, and sometimes tacit and automated in ones cognition. Focus on a single concept carries the risk of failing to note relevant knowledge structures in a way that the subject matter expert may be able to do. Design is further mediated by pedagogical knowledge, creativity and drive for innovation. Innovation is important because every new conceptual model is most often an innovative artifact. Information Objects An information object utilizes information visualization capabilities of contemporary technology to provide educationally useful information. This type of learning object might be just a single representation (an image) or a multimodal display and a visual interface providing information dynamically based on interaction. Information can be represented in tables, matrixes, mind maps, illustrations, formulas, pictures, animations, videos, diagrams, 3D models and by the way of other modalities (see van Someren, Boshuizen, de Jong and Reimann, 1998). In a series of books, Edward Tufte (Tufte, 1990; Tufte, 1997; Tufte, 2001) discusses a range of visual techniques (e.g. graphs, illustrations, icons, pictures) to represent information. For Tufte, representations can be built to present complexity through visual clarity. He suggests that traditional visualization is greatly expanded with new technologies which allow interactive, three-dimensional and animated formats. Interactivity - e.g. buttons, clickable hot-spots, roll-over area, sliders, text-entries and drag-and-drops - allow information space to be organized in a way that enables learners to engage in exploring information, changing modalities, manipulating certain parameters or configuring options and observing changes in information, and otherwise manipulating the information they are accessing through the interface (raw information might reside within an information object, or in a database). Interactivity and modalities allow large quantities of information to be represented and made available for display in a small screen space. The ways in which technology makes this possible are best illustrated by a collection of articles edited by Bederson and Shneiderman (2003). A single interface - that is, a single screen without a change of page - might be designed to act as a point of access to a large amount of

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information. This would allow learners not just to experience interaction and/or a lot of information in mediated formats, but also to construct a mental space of information from the learning object and understand how different pieces of information are related. Figure 5 shows an example of an information object. This simple example of an information object contains multimodal information about native and non-native animals of Australia. Information about animals is accessed by rolling a mouse pointer over the text comprising the name of an animal and through decisions that include the dragging of the animals name into a corresponding area indicating its origin. The initial collection of web pages with information about Australian native animals was converted through content analysis into an information object that allows learners to explore this information space and connect different pieces of information. The essence of the information from web pages was preserved in the information object; however, long lines of texts have been reduced to short, informationally sufficient statements that are delivered to a learner randomly based on interaction. Different learners might discover different facts about certain animals, and this can lead to activities such as, for example, discussions and collaborative mind-mapping.

When a learner clicks on text next to an animal name, a random string of text providing

some information about that animal will appear automatically. This allows a learner to construct information space by exploring different information about the

animal. This also opens the possibility for discussion between learners. If an animal is placed in incorrect areas, a string of text

will be displayed, providing some hint to a learner that the animal

does not belong there. The hint is also provided from a set of

random statements.

The learner drags the text (animal name) and drops it in

the corresponding area

When a learner positions the mouse pointer over the name of

an animal, a picture (visual information) of the animal

appears in this box. Audio of a sound made by the animal is also

triggered.

Figure 5: Natives to Australia information object Contextual Representations The idea behind a conceptual representation is to allow learners to explore some realistic scenario and collect data, usually for the purpose of inquiry and problem-solving. For example, learners might collect data about volcanic activity, weather conditions, air pollutants in the atmosphere, population of life forms at great ocean depths, statements of opinion from people, and so on. Usually, there is a contextual representation of some imaginary or real place inaccessible to learners because it is distant, time and place dependent, involves danger, is too small or too big to allow data collection, requires sophisticated tools for collection of the data, requires lab conditions, requires expertise

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and so on. Engaging learners in collection of authentic data allows them to experience the origins of that authentic data, and explore the context and tools used in data collection. This might also enable learners to experience authentic problems or discipline-specific inquiries as they engage in collection and exploration of data. Figure 6 shows a screen from a Water Experiment contextual representation. This learning object allows learners to collect data on factors affecting the quality of water of the imaginary lake presented in the scenario. This data can be used, for example, in a problem-solving activity that directs learners to act as environmentalists, investigate the situation and propose a solution to a problem in the form of a report to an environment protection agency.

Some information about Water Quality Indicators and Tools is provided in these pull-down

menus

This is data collected for one of five areas from the lake. The

numbers are randomized. This means that different learners would collect different sets of

data. This allows groups of learners to engage in

collaborative discussion of possible pollution in the lake

and its causes.

A learner collects data - measurements of the water

quality - by selecting a tool from a set of tools and clicking on a

selected area on the image of the lake.

Figure 6: Water Experiment contextual representation Exploring Usefulness of the Proposed Classification I organized and participated in a collaborative activity to explore how closely a collection of learning objects developed by community of teachers and instructional designers reassembles the proposed classification. A small committee of three was formed to review learning objects from a collection. The committee included two instructional designers who had previously designed learning objects. One of the two instructional designers specialised in the field of sciences and technology, and the other in humanities. I was the third member of the review team. The source of learning objects was a Learning Object Competition held in Singapore in November 2003, organized by E-learning Competency Center, a Singapore Government founded organization, the task of which was to monitor, promote and facilitate developments in the e-learning industry. The competition attracted 83 submissions from educational institutions, the corporate sector and interested individuals. The majority of the submissions issued from educational institutions in Singapore. I was appointed as one of three judges who made decisions on the best learning objects submitted for this competition, based on criteria

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which included pedagogical value, interface design and reusability. Subsequently, I presented a keynote address at the Learning Object Conference 2003 in November, where the awards were announced and presented to the top entrants. Later on, this collection of learning objects was reviewed in the context of activity reported in this section of the paper1. An exemplary screen of learning objects was captured, reduced and printed on a sorting card of A5 size. Each card also contained a short paragraph of general description of that learning object (e.g. its content and any specific features). The committee held several meetings, during which we collaboratively sorted the 83 cards into a set of internally homogenous and externally heterogeneous piles representing types of learning objects proposed by the classification. When contradictions emerged, the committee revisited the learning object and discussed the best possible solution to resolving such contradictions. The proposed classification showed itself to be an appropriate tool, as the committee was able to place each of the learning objects from the collection into one of the classified types. Most numerous learning objects in the collections were presentation objects in forms of direct instruction. Difficulty in sorting was associated with what might be called granularity. Some presentation objects were combined with practice objects into products that reassemble courseware packages. Some conceptual models and simulation objects were also integral components of larger presentation objects. However, few learning objects existed independently as practice objects, conceptual models or simulation objects, thus validating the existence of these classification types. The few other learning objects appeared to be what the committee understood as information objects. The problem with information objects was that they were poorly designed, giving an impression of being just a set of ordinary web pages and reading material enhanced with media. Only one of the learning objects was identified as game-like. The committee revisited this learning object and agreed that it should be considered as a practice that assists learners to correctly pronounce and recognize certain German language terms. No learning object in this collection was found to be in the form of contextual representation. This is an indication that the proposed categorization may be useful beyond the context of this particular exercise, as it appeared to cater for more learning object types than were present in the collection. Conclusion This paper presents a classification of learning objects consisting of six types: presentation, practice, simulation, conceptual models, information and contextual representation objects. The paper opens a possibility for the proposed categories to be challenged, or for more categories of learning objects to emerge in further inquiries involving examination of larger repositories of learning objects such as MERLOT2. Based on common characteristics of these six types, a learning object is defined as a mediated representation designed to afford uses in different educational contexts. Some of the learning objects can be combined with other objects into direct instruction products supporting traditional pedagogies. Other learning objects are more appropriate

1 Special thanks to Lim Kin Chew, Executive Manager of E-learning Competency Centre in Singapore, for permission to examine the collection of learning objects submitted for Learning Object Competition 2003. 2 The MERLOT repository is reputedly the best collection of learning objects in the world (Zemsky & Massy, 2004). Currently, MERLOT contains references to 12,525 learning objects (data obtained from MERLOT in March 2005).

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in the context of more contemporary approaches as resources to be deployed in learning activities designed by educationalists. Design and reuse of learning objects are two independent processes likely to be planned by different professionals. In the conclusion to this paper, I provide some suggestions as to how this classification might be useful to the two groups. The classification might support people involved in design (e.g. a learning object architect who examines subject matter, conceptualizes potentially useful learning objects, and creates a blueprint of it for a production). It would direct design to facts, concepts, procedures, principles, real systems and tools, useful data and other stuff of a discipline that could be best represented for educational reuse with particular types of learning objects from the classification. Thus, the classification would provide a framework for subject matter analysis that might in turn lead to better quality indicators for design of educationally useful materials that exist as learning objects. The classification should also support people involved in reuse of learning objects (e.g. a teacher who locates a learning object in a digital repository and makes it available to students as a resource in a planned learning activity). A variety of learning object types would support reuse in a variety of pedagogical approaches (e.g. direct instruction, inquiries, problem-solving and collaborative knowledge-building). This might lead to personal epistemological change in education professionals involved in reuse of learning objects, because a variety of resources would encourage educators to experiment with their uses. Furthermore, the classification might lead to development of metadata strategy (beyond current metadata standards) that provides heuristics to people involved in reuse. Metadata might include information about a type of learning object, in addition to some pedagogical recommendations for its reuse. The concept of reuse of learning objects is currently very narrowly defined, and the reason for this could be linked to problems associated with lack of a useful definition and classification. A broadly accepted, well-validated classification would lead to better understanding of reuse, which would cater for a variety of educational situations such as, for example: use of a learning object as a presentation aid; to initiate classroom or on-line discussions; as a component in direct-instruction for on-line delivery; as a resource in an authentic problem-solving activity; as an object of an inquiry; during independent studies, assignments and projects by learners; as a component in design of other learning object, and as a basis for designing other learning objects. Finally, to acknowledge my own understanding by this stage, when I speak of learning objects, I am referring to reusable mediated representations designed for educational application. They reside in digital repositories, ready to be located and utilized by those involved in educational activities (e.g. teachers and students). These representations address: (a) key concepts from disciplines, in visual and often interactive ways not permitted with previous technologies, for sharing of socio-historical heritage of humanity (our knowledge), (b) information and data that can be useful in the context of developing disciplinary-specific thinking, culture of practice, spirit of inquiry, theoretical knowledge and information work, (c) presentation of small, instructional sequences and demonstrations delivering encapsulated descriptions of some aspects of subject matter which can support learning processes by providing just-in-time information, (d) simulations of key equipment, tools and processes from a discipline to enable development of deep understanding of artifacts used in a culture of practice. My immediate intention is to empower education professions with digital material which they can use to create a spectrum of educational activities.

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References Alessi, S. M., & Trollip, S. R. (1991). Computer-based instruction: methods and development.

Englewood Cliffs, NJ: Prentice Hall, Inc. Anderson, A. T. (2003). I object! Moving beyond learning object to learning

components. Educational Technology 43(4), 24-19. Bederson, B. B., & Shneiderman, B. (2003). The craft of information visualization: readings and

reflections. San Francisco, CA: Morgan Kaufmann Publishers. Bush, D. M. (2002). Connecting instructional design to international standards for

content reusability. Educational Technology, 42(6), 5-13. Churchill, D. (2005a). Teachers private theories and their design of technology-based

learning. British Journal of Educational Technology. Churchill, D. (2005b). Learning object: an interactive representation and a mediating tool

in a learning activity. Educational Media International. Cisco Systems (2001) Reusable learning object strategy: designing information and learning objects

through concept, fact, procedure, process, and principle template. San Jose, CA: Cisco Systems, Inc.

Clifford, R. (2002, August). Adding a pedagogical dimension to SCORM [Digital Audio Recording]. Oral presentation at the Online Instruction for 21st Century: Connecting Instructional Design to International Standards for Content Reusability, Brigham Young University, Rexburg, Idaho. Retrieved August 30, 2003 from http://zola.byu.edu/id2scorm/.

Cochrane, T. (2005). Interactive QuickTime: developing and evaluating multimedia learning objects to enhance both face-to-face and distance e-learning environments. Interdisciplinary Journal of Knowledge and Learning Objects 1(1) 33-54.

Davydov, V. V. (1999). The content and unsolved problems of activity theory. In Y. Engerstrm, R. Miettinen & R. Punamki (Eds.), Perspectives on activity theory (pp. 39-52). Cambridge, UK: Cambridge University Press.

De Jong, T. et al. (1998). Acquiring knowledge in science and mathematics: the use of multiple representations in technology-based learning environments. In A. Van Someren (Eds.), Learning with multiple representations (pp. 9-40). Kidlington, Oxford: Elsevier Science Ltd.

E-learning Competency Center. (2003). Explanation on learning objects. Retrieved September 15, 2003 from http://www.ecc.org.sg/loc/ecplain.htm.

Fraser, A. (1999). Web visualization for teachers. Retrieved February 23, 2004, from http://fraser.cc/WebVis/.

Friesen, N. (2003). Three Objections to Learning Objects. Retrieved July 24, 2004 from http://www.learningspaces.org/n/papers/objections.html.

Gibbons, A. (n.d.). Model-centered instruction: beyond simulation. Retrieved September 20, 2005, from http://www.gwu.edu/~lto/gibbons.html.

IEEE. (2001). WG12: Learning Object Metadata. Retrieved February 15, 2005, http://ltsc.ieee.org/wg12/.

IMS Global Learning Consortium (2002). Learning Resource Meta-data Specification. Retrieved February 15, 2005 from http://www.imsglobal.org/metadata/.

JohnsonLaird, P. N. (1983). Mental models. Cambridge, MA: Harvard University Press. Jonassen, D., & Churchill, D (2004). Is there learning orientation in learning objects?

International Journal of E-learning, April-May, 32-42. LAllier, J. J. (1998). NETg's precision skilling: the linking of occupational skills descriptors to

training interventions. Retrieved September 15, 2000, from http://www.netg.com/research/pskillpaper.htm.

14

Lukasiak, J., Agostinho, S., Bennet, S., Harper, B, Lockyer, L., & Powley, B. (2005). Learning Objects and learning designs: an integrated system for reusable, adaptive and sharable learning content. Research in Learning Technology, 13(2), 151-169.

Mayer, R. E. (1989). Models for understanding. Review of Educational Research, 59(1), 43-64.

Mayer, R. E. (2003). The promise of multimedia learning: using the same instructional design methods across different media. Learning and Instruction, 13, 125-139.

McGreal, R. (2004). Learning objects: a practical definition. International Journal of Instructional Technology and Distance Learning 1(9), 21-32.

Merrill, M. D. (2000). Knowledge objects and mental models. In D. A. Wiley (Ed.), The Instructional Use of Learning Objects. Retrieved July 24, 2004 from http://reusability.org/read/chapters/merrill.doc.

Paivio, A. (1974). Language and knowledge of the world. Educational Researcher, 3(9), 5-12. Ploetzner, R., & Lowe, R. (2004). Dynamic visualizations and learning. Learning and

Instruction, 14(3), 235-240. Schnotz, W., & Lowe, R. (2003). External and internal representations in multimedia

learning. Learning and Instruction, 13(2), 117-123. Tufte, E (1997). Visual explanations. Cheshire, Connecticut: Graphics Press. Tufte, E (2001). The visual display of quantitative information. Cheshire, Connecticut: Graphics

Press. Tufte, E. (1990). Envisioning information. Cheshire, Connecticut: Graphics Press. Van Someren, A. (Eds.). (1998). Learning with multiple representations. (Eds.). Kidlington,

Oxford: Elsevier Science Ltd. Van Someren, A., Boshuizen, P.A., de Jong, T. & Reimann, P. (1998). Introduction. In

A. Van Someren (Eds.), Learning with multiple representations (pp. 1-5). Kidlington, Oxford: Elsevier Science Ltd.

Von Glassersfeld, E. (1997). Piaget's Legacy: Cognition as Adaptive Activity. Retrieved December 12, 2003, from http://www.umass.edu/srri/vonGlasersfeld/onlinePapers/html/245.html

Vygotsky, S. L. (1962). Thoughts and language. Cambrige, MA: The MIT Press. Vygotsky, S. L. (1978). Mind in society. Cambridge, MA: Harward University Press. Wartofsky, M. W. (1979). Models: representation and the scientific understanding. Dordrecht,

Holland: D. Reidel Publishing Company. Wiley, D. A. (2000). Connecting learning objects to instructional design theory: A

definition, a metaphor, and a taxonomy. In D. A. Wiley (Eds.), The Instructional Use of Learning Objects. Retrieved July 24, 2004, from http://reusability.org/read/chapters/wiley.doc.

Wiley, D. A. (2002). The coming collision between automated instruction and social constructivism. Retrieved September 16, 2005, from http://wiley.ed.usu.edu/docs/collision_09.doc.

Wiley, D. & Edwards, E. (2002). Online self-organizing social systems: The decentralized future of online learning. Retrieved November 20, 2003 from http://wiley.ed.usu.edu/docs/ososs.pdf.

Zemsky, R., & Massy, W. F. (2004). Thwarted innovation: what happened to e-learning and why. Philadelphia, PA: The Learning Alliance, University of Pennsylvania.

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