Resource-Based Learning Environments: Methods and Models†
n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n
Michael J. Hannafin
University of Georgia
Learning and Performance Support Laboratory
611 Aderhold Hall
Athens, GA USA 30602
Information systems have traditionally supported the indexing, storing, and accessing of text. Emerging hypermedia systems, such as the World Wide Web (WWW), extend traditional views of both available media and support functions. Such systems can support learner-centered applications, where the intent and selection of available resources varies according to the needs of different users. Information resources can be accessed in theoretically unlimited combinations according to the background knowledge and ongoing needs of the individual. This has created both opportunities and challenges for fields involved in the design and development of learning systems. The purpose of this paper is to present an integrated perspective on the design development of teaching and learning applications of emerging information resource-based multimedia environments.
This paper introduces several concepts related to the design of resource-based learning environments (RBLE). It outlines the basic structures of RBLEs, provides a rationale for transformational learning using free-standing multimedia resources, and identifies goals for RBLE design.
RBLEs have evolved distinct functions rarely addressed in traditional or latter-day information systems. The key distinctions are not simply in their scope or media employed, but the extent to which individual efforts to learn from versus access available resources are enabled and supported. Traditional information systems enable access to, but are not designed to promote understanding of, the system’s contents [see Eisenberg, 1989, for a review of relevant research).
Information comprises two or more related data points that can be connected and coded via varied media, and can be presented in varied degrees of depth and detail. Dates, events, locations, and names are mere data points in isolation; the capacity to connect data points across categories provides the potential for unique application and meaning that individual data points do not. The connection may be supplied by the designers of the system, generated by individual users of the system, or negotiated dynamically among a learning community (Garrison, 1995).
Information systems organize information to enable access. They may supply explicit organization among information or the capacity to specify organization using supplied classification data. Many electronic information systems provide explicit links to resources considered to be potentially relevant, thereby organizing and connecting the resources contained in the system according to external judgments of relevance or importance. Such systems support learning by either directing or cueing users explicitly to related information. However, while the utility of the information contained in such a system may be improved for defined learning purposes, it may be limited for other important purposes. The same information is often applicable not only for other externally defined purposes, but for the unique purposes of individual users. NASA image databases have wide-reaching utility, much of which cannot be anticipated in advance. For example, such systems are used not only by scientists for detailed study of the composition of planetary atmosphere, but by graphic artists for image enhancement and commercial reproduction as well as elementary school children embarking on the study of the solar system.
Such is the nature of information in RBLEs: resources designed for one purpose are often used to support other purposes--some which may be contradictory to or inconsistent with their initial intent. As individuals encounter information from different perspectives and backgrounds, and with different purposes, meaning changes. The initial meaning of a picture, report, or graph is redefined according to preceding actions and events and the unique intentions and perceptions of different individuals. Due to their non-linear nature, RBLEs afford an infinite range of potential interpretive options, made unique by the evolved experience and intentions of the user.
If the meaning of the available information changes with each user and the goals of users vary, how is learning supported in complex information systems? RBLEs emphasize a transformation of meaning through learning-centered, system-facilitated action. RBLEs support and extend efforts to know, understand, and generate, that is, to reflect, construct, solve problems, and integrate new information for one’s own purposes (e.g., curiosity, dissonance) as well as for others’ purposes (e.g., research topic, gain varied perspectives on an issue, solve an assigned problem) (Land & Hannafin, 1996). They provide not only comprehensive collections of highly indexed data, information, and search engines, they help learners to reason, reflect, and assess the veracity of the systems’ contents.
Knowing is awareness that learning has occurred--the ability to recall or recognize information contained in an RBLE for individual purposes and/or a personal interpretation of meaning. A great deal of what people learn, they know; that is, they collect information at a basic level but have limited depth of knowledge, utility, or understanding. A learner might, for instance, state definitively that the sun rises in the east and sets in the west. Learners might also know that daylight hours are shorter during winters than summers. Yet, their knowledge may be limited in explanatory or productive value. They may be unable to explain how a sunrise occurs, or believe that the sun literally rises relative to the earth’s “fixed” position. They may be unable to explain why seasonal temperatures in the southern hemisphere run counter to those in the northern hemisphere, or why the moon’s phases progress as they do. They may know a great deal of information about the earth and its climate but have in-depth understanding of relatively little.
Understanding, in contrast, involves deep recognition of the implications of one’s knowledge and the capacity to deploy it to reason, analyze, interpret, and think critically. It encompasses comprehension of varied perspectives, the ability to explain, and the capacity to reason using one’s knowledge. Understanding involves a transformation of meaning based upon connections with personal experience and prior knowledge. In the previous example, the individual might know that summer seasons are cooler in the southern than northern hemisphere, and be able to relate several key concepts to the phenomenon (e.g., earth’s axis, rotation, location in orbital path). He or she can extrapolate meaning from knowledge and experience to, for example, predict tidal patterns based on lunar phase, explain why planets remain in relatively stable orbits, and describe why only one side of the moon is visible from the earth. Understanding implies awareness of diverse perspectives, and the ability to frame an opinion based on these perspectives and evidence.
Finally, generating is the capacity to act intentionally and purposefully on one’s understanding, that is, to deploy knowledge and skill to create artifacts that reflect or extend understanding. It is the grounded process through which knowledge and understanding catalyze, yielding something that previously did not exist or was not a part of the individual’s experience (e.g., forming an inference, solving problems, responding differentially to complex circumstances, creating a new product or articulating new ideas and perspectives). History is replete with examples of individuals who generated new ideas: mathematical equations were developed by early Egyptians to measure and design the pyramids; Copernicus generated and proved a theory of the universe; Greeks and Egyptians accurately predicted eclipses and lunar phases using mathematics and physics considered primitive by current standards, but new and revolutionary at the time. Likewise, tools have been generated that have redefined much of present-day society: Simple sorting devices were developed to simplify and accelerate the processing of immigrants to the United States at Ellis Island during the late 1800’s and early 1900’s; navigation was revolutionized by the invention of the sextant; barren deserts were made fertile through the development of irrigation. In the present context, generating is what learners do with, or as a by-product of, collaboration with RBLEs as they define needs, generate hypotheses, and refine understanding.
The potential to enhance learning is apparent, but relatively little guidance is available for the design of RBLEs. Various disciplines have developed text-based and multimedia information systems, including instructional systems design, psychology, communication, computer science, and information science (Hill & Hannafin, 1997). However, these efforts have been insulated from one another, with little crossover benefit or evidence of collaboration. This has resulted in segmented--often incomplete--perspectives. While some have explored RBLEs in the design of traditional learning environments (e.g., Grabowski & Small, 1991; Marchionini, 1988), few have been truly learning-centered. We need to better integrate guidelines, rooted in research, theory, and developments in instructional systems design, psychology, communications, computer science, and information systems, to the design and use of multimedia information systems that support student-centered learning.
Enabling contexts are the vehicles through which individuals are oriented to a need or problem and interpretive perspectives are situated. Enabling contexts guide students in recognizing or generating problems to be addressed and framing learning needs. They take three basic forms. Externally-imposed contexts both clarify the expected product of the learner’s efforts as well as implicitly guide strategy selection and deployment. Externally imposed enabling contexts are often presented as explicitly situated problem statements or organizing questions which aid students in referencing relevant aspects of their experience. Externally-induced contexts introduce the learner to a domain but do not identify specific problems to be addressed. Rather, a domain is encountered in which any number of problems or issues can be generated or studied at the discretion of the learner. The student interprets the context for meaning, generates sub-problems, and devises strategies based on individual interpretations of the enabling context. In generated enabling contexts, the learner establishes need based on circumstances that are unique. As with induced contexts, the generated context activates relevant knowledge, skill, and experience in order to frame problems and issues and to guide problem-solving strategies.
Resources are source materials that support learning. Resources range from electronic (e.g., databases, computer tutorials, video), to print (e.g., textbooks, original source documents, journal articles), to human (e.g., experts, parents, teachers, peers). The World-Wide Web is perhaps the most pervasive repository of available resources. While it contains millions of source materials of potential relevance, the utility of web resources is often limited due to a lack of clarity of contents, difficulty in accessing or using them, or both. A resource’s utility is determined by its relevance to the enabling context and the degree to which it is accessible to the learner.
In a simple sense, resources can be either static or dynamic. Static resources do not change through use. They may contain information that is stable over time and is not subject to variation, such as photographic images of historical figures. Some resources may only be available through technologies that do not permit their contents to be altered such as the contents of videodisks, multimedia CD-ROMs, textbooks, and electronic encyclopedias. Interpretation and understanding may evolve considerably through repeated access, but the literal contents of a fixed resource remain unchanged. Dynamic resources change through time and/or the introduction of new data. This affords the learner the opportunity to repeatedly access the same resource but with different outcomes (e.g., climatology databases created by the National Weather Service). Dynamic databases can also evolve based on the needs, queries, and intentions of individuals or groups. In some systems, users can transform data by adding new entries or annotating existing entries. CSILE (Computer-Supported Intentional Learning Environment), for example, is a social knowledge resource that changes as a function of usage and the ratings of its users (Scardamalia & Bereiter, 1994).
Tools provide the overt means through which individuals engage and manipulate both resources as well as their own ideas. Tool functions vary according to the enabling contexts as well as the intents of their users; the same technological tool can support different functions. Three types of tools are commonly used: Processing tools, manipulation tools, and communication tools.
Processing tools support information-processing models of human cognition. Seeking tools, for example, support detection and selection of relevant information by helping learners to locate and filter needed resources. Collection tools allow learners to gather resources or pieces of resources for their own purposes. Organization tools assist learners in representing relationships among ideas. Integration tools help learners to link new with existing knowledge. Finally, generation tools enable learners to create things. Generation tools have been developed across a wide range of learning environments.
Manipulation tools are used to test the validity of, or explore the explanatory power of, beliefs and theories. RasMol (Raster Molecules) is an Internet-based learning environment used to create and display the structure of DNA, proteins, and small molecules. Several RasMol shells can be downloaded and manipulated by learners. Molecules can be displayed as wireframe graphics, cylinder stick bonds, space-filling spheres, macromolecular ribbons, hydrogen bonds, or dot surfaces. These representations may be colored or shaded, and the molecules may be rotated and sized to increase the depth and vividness of the images manipulated.
Communication tools support efforts to initiate or sustain exchanges among learners, teachers, and experts. Synchronous communication tools support real-time interaction among participants. For example, telephones are widely available, low-cost tools that support live voice communication among two or more participants. Asynchronous communication tools allow for extensive exchanging of ideas and or resources, but do not rely on the simultaneous availability of all participants. Listservs, for example, provide a vehicle for common discourse among learners and teachers, but do not require their immediate presence.
Scaffolding is the process through which learning efforts are supported while engaging an OLE (Linn, 1995). Scaffolding can be differentiated by mechanisms and functions. Mechanisms emphasize the methods through which scaffolding is provided, while functions emphasize the purposes served.
Conceptual scaffolding is provided when the problem under study is defined, that is, for externally-imposed or -induced enabling contexts. It guides learners regarding what to consider and can help them to reason through complex or fuzzy problems, as well as for concepts where known misconceptions are prevalent. Hints can guide the learner to available resources, or tool manipulations might be suggested where understanding is typically problematic.
Metacognitive scaffolding supports the underlying processes associated with learning management. It provides guidance in how to think during learning, and can be either domain-specific, such as where enabling contexts are externally induced, or more generic where the enabling context is not known in advance. Metacognitive scaffolding might also reminder learners to reflect on the goal(s) or prompt them to relate a given outcome to the problem or need at hand. In contrast, the scaffolding for generic model-building, though uniform in task, represents a wide array of phenomena to be modeled with very different components and weights. In such a case, the scaffolding focuses on the processes of creating models, including finding ways to link models with prior knowledge and experience, linking representational models to current understanding, and enabling learners to manipulate ideas through modeling tools (Jackson, Stratford, Krajcik, & Soloway, 1995).
Procedural scaffolding emphasizes how to utilize available resources and tools. It orients to system features and functions, and otherwise aids the learner while navigating. Procedural scaffolding frequently clarifies how to return to a desired location, how to “flag” or “bookmark” locations or resources for subsequent review, or how to deploy given tools. Learners need not develop facility with all procedures until they have established the need for a given tool or resource.
Strategic scaffolding emphasizes alternative approaches that might prove helpful. It supports analysis, planning, strategy, and tactical decisions during open-ended learning. It focuses on approaches for identifying and selecting needed information, evaluating available resources, and relating new to existing knowledge and experience. Probe questions can provide an explicit strategic clue for those needing a place to begin, while also helping to trigger a series of related strategies for those who are immersed in, but have not yet reconciled, a problem. Another type of strategic scaffolding involves alerting the learner to available tools and resources that might prove helpful under given circumstances, and providing guidance in their use.
To be learning centered, RBLEs must exploit the unique capabilities and needs of individual users. The systems need to extend learners’ capabilities, enabling access to information uniquely organized to meet unique learning needs. The systems need to address the unique state of knowledge of individual users, and provide the support needed for understanding to develop.
RBLEs need to minimize the cognitive load associated with their use while promoting engagement. The processing complexity associated with the technology as well as the information encountered can be overwhelming. This can cause cognitive overload, resulting in reductions in processing capacity (Morris & Hinrichs, 1996). Intuitive systems not only assist learners in recognizing what is presented on the screen, but engages and motivates them during their search. Intuitive systems also minimize the complexity of their use; indeed, they often reduce complexity by utilizing familiar experiences and events that help the learner to develop knowledge and generate understanding (for a collective discussion of interface design, see Laurel, 1990). Systems become increasingly intuitive through transparent interfaces and familiar metaphors, such as the Macintosh Desktop, which are readily processed and understood with little effort because they are based in concepts already familiar to the user. Engaging systems elicit and sustain learner interest through “drivers” which establish the conditions, problems, and scenarios that influence how resources and tools are accessed and utilized (Hannafin & Land, 1997). Engagement is increased through techniques that cultivate transformation.
Unlike systems where the evaluation of needs and generation of resources is largely determined externally, RBLEs require that learners make decisions regarding the value of the information retrieved and how it meets (or fails to meet) their requirements. The enormous range of resources available on the WWW, for example, demands considerable evaluation by the learner. The learner must be able to critically assess the pool of possible resources, examine the information retrieved, and judge its value based on their unique needs. Learners need the skills associated with both critical analysis (Gilovich, 1991) and information literacy (AASL/AECT, 1997). Self-monitoring involves active participation and regulation by the learner. The ability to self-monitor needs to occur at several levels, including the initial identification of the information needed and/or wanted and in judging the success of the overall interaction with the system.
As learners seek information in RBLEs to facilitate the building of knowledge and understanding for generating new resources, empowerment is fundamental. By promoting thought, action, and reflection, the systems help the learner gain confidence and assurance with their abilities to engage in problem-solving. Studies have demonstrated that learner working in RBLEs that are not empowered become disoriented, frustrated, and even angry with the system (see, for example, Hill & Hannafin, in press). This can cause the learner to reject these environments for facilitating learning. By taking steps to empower the learner in their task, the systems become “user-friendly” and thus more viable as an environment that is not only conducive to, but promotes, learning.
Currently, few systems can readily communicate with each other without a great deal of work by the learner. Although the ability to transport information across and between platforms is becoming less cumbersome, ease of transfer rapidly breaks down at the program level. The information available on the WWW illustrates several problems inherent with current information systems. On one hand, the WWW allows a learner to access documents from multiple platforms (UNIX, DOS, Windows, Macintosh) and to view these using any of a number of Web browsers (e.g., Explorer, Navigator, Mosaic, Communicator, Lynx, etc.). As these systems have increased in their capabilities, developers of one Web browser have surpassed others, enabling functions (e.g., frames, animation, video file protocol) not available to all systems.
RBLEs assist learners as they work to gain knowledge and understanding. There is no single set, but rather multiple tools and resources from which the learner can select, use in complementary ways, and customize features to address unique learning needs. RBLE tools and resources assist the learner in assessing current knowledge and understanding as they progress toward generation. Learning-centered systems place the learner in control of what information is accessed, when it is retrieved, where it is obtained, why it is retrieved, and how it is manipulated and customized for their needs.
Learners need to interpret written word as well as pictures, moving images, and sound. Learners need to “read” a variety of media, but they also need to link the various resources to gain deeper understanding. Message interpretation becomes the central focus once the message reaches the receiver (Mercer, 1990). The sender hopes or presumes that it is interpreted and understood as intended (or, at least is clear and unambiguous in meaning). The open-ended nature of these systems makes critical analysis a fundamental part of learning; the learner needs to be able to judge relevance and accuracy of resources for their individual needs.
Negotiation is a critical component in the process of building understanding, as well as in the generation of new schema and connections. Negotiation involves conferring with another or others to reach consensus or agreement. Negotiation assists learners in clarifying their information needs as well as enhancing their understanding. As learners utilize resources available through emerging information systems, they encounter many new experiences. These diverse experiences serve to add and promote multiple perspectives beyond that which is available electronically. The learner, as an active participant in the generation of unique structures and resources, becomes a fundamental component in RBLEs.
In RBLEs, discourse needs to occur on several levels: system, other learners, and self. The manipulation of ideas enables the learner to think deeper, and perhaps differently, about ideas and concepts. The system and the learner need a common ground to facilitate discourse between the system and the learner as meaning and understanding evolve (Brennan, 1990). Discourse should also be promoted between resources, including other learners. CSILE (Computer-Supported Intentional Learning Environment) is an example of an RBLE which affords learners continuous engagement as they seek to build understanding. CSILE facilitates the development of metacognitive knowledge through the use of prompts to assist learners in the generation of questions, hypotheses, and/or theories (Scardamalia & Bereiter, 1994). By supporting reflection, dialogue, and collaboration, CSILE empowers learners in the social construction of understanding.
RBLE goals include enhancing current system capabilities, the ability to include new techniques and technologies, and the capacity to promote flexible use and understanding. System aspects are reasonably well understood. Spiro et al (1991) have developed cognitive flexibility theory, which focuses on cognition in ill-structured domains. One of the main tenets of the theory is that multiple perspectives--angling-- on the same information are necessary to learn complex material, as well as to assist the learner as their “need to know” evolves and changes. By allowing the user to connect information from a variety of perspectives, these systems enhance the capabilities of the tool being utilized in a particular learning-centered context.
Learner-centered tools in RBLEs are important for several reasons. First, these tools can assist the learner with identifying what they know, as well as what they need to know. Learner-centered tools can also be used to organize information in unique ways to match individual needs and/or desires. Finally, the tools in RBLEs can assist the learner with the generation of representations, not only in finding new ways to present what they know and understand, but also to represent the system itself. These representations may come in the form of mental maps, which can then be shared with others using the system.
In addition, learner-centered mechanisms can support learners as they engage in higher-order evaluation skills such as theory-building, data interpreting, hypothesizing, and experimenting (Roth & Roychoudhury, 1993). These embedded tools enable the learner to “mess around” with the information, testing hypotheses and creating new environments in which this testing can occur. Because the tools are embedded within a larger system, the learner has ready access to a wealth of resources to support their testing and experimentation. By affording the learner the opportunity to stretch the limits of their knowledge base, RBLEs create environments which assist the learner in expanding their understanding, enabling the generation of new knowledge.
Brennan, S. E. (1990). Conversation as direct manipulation: An iconoclastic view. In B. Laurel (Ed.), The art of human-computer interface design (pp. 393-404). Reading, MA: Addison-Wesley.
Eisenberg, D. (1989). Problems of the paperless book. Scholarly Publishing, 21(1), 11-26.
Garrison, J. (1995). Deweyan pragmatism and the epistemology of contemporary social constructivism. American Educational Research Journal, 32(4), 716-740.
Gilovich, T. (1991). How we know what isn’t so: The fallibility of human reason in everyday life. NY: Free Press.
Grabowski, B. L., & Small, R. (1991). Information, instruction, and learning. Performance Improvement Quarterly, 4(3), 2-12.
Hannafin, M.J., & Land, S. (1997). The foundations and assumptions of technology-enhanced, student-centered learning environments. Instructional Science, 25, 167-202.
Hill, J. R., & Hannafin, M. J. (1997). Cognitive strategies and learning from the World Wide Web. Educational Technology Research and Development.
Jackson, S., Stratford, S. J., Krajcik, J., & Soloway, E. (1995b). Making system dynamics modeling accessible to pre-college science students. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA.
Land, S., & Hannafin, M. J. (1996). A conceptual framework for the development of theories-in-action with open-ended learning environments. Educational Technology Research and Development, 44(3), 37-53.
Laurel, B. (1990) (Ed.). The art of human-computer interface design (pp. 229-233). Reading, MA: Addison-Wesley.
Linn, M. (1995). Designing computer learning environments for engineering and computer science: The Scaffolded Knowledge Integration Framework. Journal of Science Education and Technology, 4 (2), 103-126
Marchionini, G. (1988, November). Hypermedia and learning: Freedom and chaos. Educational Technology, 8-12.
Marchionini, G. (1995). Information seeking in electronic environments. Cambridge, UK: Cambridge University Press.
Mercer, N. (1990). Context, continuity and communication in learning. In F. Potter (Ed.), Reading, learning, and media education (pp. 27-38). Oxford, England: Basil Blackwell.
Morris, M. E. S., & Hinrichs, R. J. (1996). Web page design: A different multimedia. Mountain View, CA: SunSoft Press.
Roth, W. M., & Roychoudhury, A. (1993). The development of science process skills in authentic contexts. Journal of Research in Science Teaching, 30(2), 127-152.
Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. The Journal of the Learning Sciences, 3, 265-283.
Shotsberger, P. G. (1996, March/April). Instructional uses of the World Wide Web: Exemplars & precautions. Educational Technology, 47-50.
Spiro, R. J., Feltovich, P., Jacobson, M., & Coulson, R. (1991). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational technology, 31(5), 24-33.
© Michael J. Hannafin
The author(s) assign to ASCILITE and educational and non-profit institutions a non-exclusive licence to use this document for personal use and in courses of instruction provided that the article is used in full and this copyright statement is reproduced. The author(s) also grant a non-exclusive licence to ASCILITE to publish this document in full on the World Wide Web and on CD-ROM and in printed form with the ASCILITE 97 conference papers, and for the documents to be published on mirrors on the World Wide Web. Any other usage is prohibited without the express permission of the authors.
† This paper is based, in part, on a series of papers/presentations by Michael Hannafin and Janette Hill and a chapter titled “Open Learning Environments: Foundations and Models” to be published by Erlbaum in Instructional Design Theories and Models.