Many debates of effective online practice implicitly assume that those practices exist on one end or the other of a dichotomy. This article argues that this assumption inevitably limits the creation of effective and balanced online learning environments. Drawing upon relevant theory and research on teaching and learning, the article argues that learning goals should drive the creation, selection, and refinement of online learning environments. The article discusses two major areas of debate: information acquisition versus knowledge construction and teacher-centered versus student-centered learning. As an alternative to artificial dichotomies, the article proposes a learning-centered view of online practices where a combination of effective strategies support student progress toward identified learning goals.
Versus One: Information acquisition versus knowledge construction
Versus Two: Student-centered versus teacher-centered learning
The prospect of putting a course online can rattle even the most experienced college professor. Compounding the obvious technical challenges is the urgent need to examine basic assumptions about teaching and learning. The examinations often fuel ongoing debates among university faculty. More times than not, the debates pit one philosophical perspective against another. For instance, faculty weigh teacher-centered versus student-centered strategies; information acquisition versus knowledge construction; or skill development versus productive habits of mind.
While I agree that we must identify effective practices that support online learning, I disagree with the assumption that those effective practices exist on one side or the other of a dichotomy. In fact, I propose that the very habit of reducing an educational discussion to a dichotomy, or "versus", might very well be our fundamental vice. Portraying educational practices as "black or white," "right or wrong," or "good or bad" creates artificial and intrusive arguments that can blur our vision and limit our thinking.
In this article, I argue for a balanced view of online learning environments - a view that might put fruitless "either/or" deliberations to rest. To support this argument, the article investigates two major polarized educational debates placed into the convention of a "versus"-information acquisition versus knowledge construction and teacher-centered learning versus student-centered learning. Within the examination of each "versus", I suggest ways to focus on the reciprocal contributions of seemingly opposite practices. I utilize lenses from educational theory and research to refocus each "versus" squarely on student learning. Within the discussion of each "versus", I provide examples that reveal the ways the practices interact in effective online environments. I end the article by suggesting a metaphor for learning environment design that might prove useful to those facing the daunting prospect of higher education on the World Wide Web.
Versus One: Information acquisition versus knowledge construction
The first "versus" forms the root for many educational debates. It is based on the notion that there are two distinct camps of instructional design - the facts-people on one side and the process-people on the other. Separating instructional design in this way implies that information acquisition is inherently bad and that knowledge construction is inherently good. While the implication has no basis in reason, the real danger lies in the fact that the "versus" conceals the reciprocal relationships between facts and thinking process and between information and knowledge.
It is wrong-headed to insinuate that when educators design online environments that organize and store information, they somehow deny their students meaningful learning opportunities. It is equally wrong-headed to imply that when educators create opportunities for students to collaborate and problem solve, they do so at the risk of their students' intellectual discipline. In reality, the processes of information acquisition and knowledge construction are functionally bonded. Understanding that bond requires that we examine both processes, paying particular attention to the contributions that each makes to the other.
Information, even information resources in Web-based environments, is no more or less than it has ever been: "discrete little bundles of fact, sometimes useful, sometimes trivial, and never the substance of thought [and knowledge]" . Information resources in and of themselves are benign. Information is simply the raw material that learners use in the process of knowledge construction. Information is a resource and its sensing, collection, organization, communication, and use are critical factors in the process of constructing knowledge. In this way, information acquisition is part of knowledge construction, not a competing entity. In fact, it would be absurd to pursue learning in an empirical vacuum. While it is true that technology allows us to arrange information in ways that can contribute to successful learning, the mere act of transferring information from the mind of the teacher to the mind of the student does not result in knowledge construction (Cobb, 2000). In plain English, acquiring information is not the same as learning. We define learning by what students do with the information they acquire.
Successful learners are those who can integrate new information with existing understandings in meaningful ways to create new or enhanced understandings (Karpov and Bransford, 1995). Learners do that through thinking processes like comparing, contrasting, evaluating, analyzing, and synthesizing. The human denominator is the key. Knowledge cannot exist without "knowers." Information becomes knowledge when humans interact with it and with each other. Without the human process of meaning making, all of the information in all of the world would not equal a speck of knowledge. Learning then, is a process of actively building or constructing meaning - a process of connection, rather than a process of collection. During knowledge construction, the mind examines new information and reconciles it with what it already knows about a topic. Grappling with information in order to make sense of it results in various degrees of understanding. That is because what we learn cannot be separated from how we learn it, and all experiences do not lead to the same understanding. Rather, what we understand, and the ways that we understand it, is a function of three interrelated elements: the content, the activity of the learner, and the learning context (Savery and Duffy, 1995).
If we examine online learning in light of these interrelated elements of understanding - content, learner activity, and context - we can see with increased clarity the reciprocal relationship of information acquisition and knowledge construction.
By their very nature, higher education courses deal with domain specific information. When students work with that content online, technology provides highly effective tools for encouraging information acquisition, mediating knowledge-building, and encouraging discourse focused on that content among a community of learners (Brown, Ash, Nakagawa, Gordon, and Campione, 1993; Scardamalia and Bereiter, 1993). When students grapple with new and unfamiliar content, or when they apply familiar content to new contexts, technology becomes a mind-extension - a "cognitive tool" . This cognitive tool helps learners transcend the memory, thinking, or problem-solving limitations of their own minds (Pea, 1985). For that reason, online environments afford both teachers and students the opportunity to organize information in ways that can offset the cognitive load required to memorize and later recall information. Acting as an intellectual partner, technology enhances the performance of the learner (Salomon, 1993) as it assists in organizing, storing, and retrieving information. Educators can promote knowledge construction by providing access to information resources organized to assist comprehension, application, analysis, synthesis, and evaluation. In other words, when educators utilize technology to organize content in meaningful ways, they encourage students to recognize and judge patterns of information and then use those patterns to construct meaning and solve problems.
Clearly then, it is critical for instructors to organize course content in ways that simplify domain-specific information acquisition and promote knowledge construction. Table 1 provides examples for organizing content. Specifically, the examples illustrate ways that information can be organized to help students identify key characteristics; important sequences; important causal networks and their key processes; important problem situations and key solutions; important generalization patterns; and important defining characteristics and examples of key concepts. These examples of information organizers help educators make meaningful use of what technology does best - organize and store information.
Table 1: Examples of Information Organizers
Type of Information Organizer Purpose(s) Example Graphs and Charts To organize quantitative information Pie charts could represent the degree to which three authors use themes (i.e., women's rights, race relations, immigration), symbols (i.e., white dove for peace, tree for life of growth or strength, winter to depict old age or death), and stereotypes (i.e., the crotchety old matron librarian, the thick-headed athlete, the spoiled only-child) to advance their arguments. Organizational Patterns To: show
- descriptive patterns
- time and sequence patterns
- process/cause patterns
- problem/solution patterns
- generalization patterns
- concept patterns
Timelines, flow charts, causal networks and concept maps reveal patterns, promote the processes of comparing and contrasting, and aid in concept attainment. For instance, the events leading up to and following the assassination of JFK can be represented in a sequence pattern chart or timeline. Anticipation Guides and Advance Organizers To:
- provide strong guidance
- provoke critical thinking
- contribute frameworks for systematic reflection
- focus student attention on concepts that are central to understanding the information
The questions "What comes to mind when you think of democratic societies?" "Who makes the decisions in a democracy?" could help students generate initial associations that will assist in constructing understanding of what a democracy is and is not. Operational Definitions To define significant terms in ways that are content specific. The word "protocol" takes on different meanings in the areas of medicine, computer science, government etiquette, and treaty negotiations. Comparison Tables/Extended Matrixes/Venn Diagrams To identify, articulate, and illustrate similarities and differences according to important elements. A matrix could compare types of government (i.e., direct democracy, representative democracy, republic, monarchy, oligarchy, dictatorship) using the elements of who governs, how decisions are made, role of the citizen, and earliest examples. Classifications To assist students in grouping elements of the content into definable categories based on important attributes. Certain information concerning business can be classified into the categories of sole proprietorship, partnership, and corporation. Troubleshooting Lists/Tables To identify errors in student reasoning and common elements that can be misleading without careful investigation and attention to detail. An introduction to creating a lesson plan for an elementary classroom could highlight common errors in planning and thinking. For example, many novice teachers confuse learning goals with lesson objectives. Bias/Perspective Analysis To:
- shed light on the author's perspective
- help students broaden their thinking and stay open to other points of view
- explain the distinction between facts and opinions
An article written against stem cell research is prefaced with a statement outlining the belief systems of the author (if known) and the ways that the author uses facts to promote that perspective.
The second element that reveals the functional bond between information acquisition and knowledge construction is learner activity. That is because the ways that learners come to understand things is dependent on the activities that actively engage them and cause them to manipulate and examine information.
A particularly useful way to explore learner activity is through the research on situated learning. As a theoretical construct, situated learning contends that learning occurs as people engage in activities within a certain environment bound by social factors in that environment (Brown, Collins, and Duguid, 1989; Derry and Lesgold, 1996; Greeno, 1989, 1998; Greeno, Moore, and Smith, 1993; Lave and Wenger, 1991; Rogoff, 1990). Jonassen (1994) describes situated learning as occurring when students work on authentic and realistic tasks that reflect the real world. That is to say that knowledge is formed in part from the environment and the learner's interactions with the environment. McLellan (1996) explains situated learning this way: It "involves adapting knowledge and thinking skills to solve unique problems ... and is based upon the concept that knowledge is contextually situated and is fundamentally influenced by the activity, context, and culture in which it is used" .
Clearly, there is an important relationship between "knowing" and "doing." A Spanish proverb states it simply: "There is a difference between reading about bulls and being in a bullring." While each activity provides an opportunity to construct knowledge, the resulting knowledge differs significantly. We would expect a significant difference in the knowledge a learner might construct about bulls through each situation - researching bulls in a library or fighting them in a bullring. Often, when students learn in abstract ways, the knowledge that results is inert - it can be used to answer items on a multiple-choice test but it is not available to students when they try to solve a problem that requires that knowledge. For knowledge to be active - available and relevant rather than artificial, unrelated, and inert - learning must be situated in a meaningful context.
By situating learning in meaningful contexts, the learner's mental engagement - the "doing" - not only shapes what he or she will learn, but also how he or she will learn it. This is because the mental operations - processing tasks - that the learner uses to interact with information, specifically Web-based information, are critical (Jonassen, 1993). Therefore, educators who design effective online learning environments should base their design decisions on the learning goals they have for their students (Moss, 2000). Learning goals provide criteria for selecting task engagements that require and engender certain mental processes. For example, building an understanding of a topic through acquiring certain facts and terms is often a necessary first step in the learning process. If that is one of our learning goals, then the tasks we design should aid in developing comprehension of those terms and might engage students in the processes of categorizing, comparing, or defining. Learning facts is not a "bad" learning goal, but just one of a group of learning goals that define the nature and outcomes of the learning experience. By the same token, learning to apply new knowledge to unique contexts is a significant learning goal, provided students have developed clear understandings of fundamental concepts. To encourage students to extend and refine their knowledge, we might ask them to solve real problems that require them to consider important information and apply it in unique and sophisticated ways. The point of using learning goals to drive instructional design is not to identify certain goals and processes as better than others, but to design meaningful activities that will support learners as they make progress toward the identified goals.
Table 2 presents an illustrative sample of a learning goal paired with three different tasks or activities and the mental processes that each task fosters. The example provides a way of examining a goal and selecting the type of activity and mental engagement that will shape the way students come to know and understand the information with which they will interact. Notice that each of the three activities requires students to think carefully about the important aspects of a nuclear power plant, but for very different reasons, and in very different ways. The activities shape how the students come to know and understand the power plant. One activity is not better than the other two. Each task results in a different degree and way of knowing.
Table 2: How Task Engagement Influences Ways of Knowing
Learning Goal Task Engagement Mental Processes 1. The students will understand the important elements and dynamics of a nuclear power plant. Create a plan for the safest place to put a nuclear power plant in a specific city. Include reasons for your decision in your plan.
- decision making
- complex comparison
- constructing an argument
- analyzing perspectives
- seeking clarity
Design a lesson for 4th grade students to explain how a nuclear power plant operates. In the lesson, you must use a metaphor that will help students understand the workings of the power plant.
- constructing support
- decision making
- problem solving
Respond to a series of multiple-choice questions about the elements of a nuclear power plant and the roles of those elements.
The third element, context, further heightens the functional bond between information acquisition and knowledge construction. Considering context reminds us that learning does not occur in a vacuum. Learning is influenced by environmental factors including culture, technology and instructional practices. Bits of information, taken out of context and memorized, are meaningless and inert. This is because the context in which we ask our students to construct knowledge is unconnected to the real world and therefore helps to create knowledge that is not easily applied beyond the classroom. Knowledge is the combination of learning and information applied to a context. Knowledge has a dynamic quality and is defined by individuals in shared and coordinated interaction (Work Group of the American Psychological Association Board of Educational Affairs, 1997). Rather than existing independently, knowledge is embedded in the contexts in which it is learned (Greeno, Collins, and Resnick, 1996). For instance, we could learn a great deal more about dogs if we worked with dogs of different breeds, ages, and temperaments than if we only worked with only one dog. To extend that example, we could learn even more about dogs if we worked with a variety of them across settings - in the city, in the country, when other people were present, when other dogs were present, and when other animals, like cats and birds, were present. But those are just some of the contexts that would influence and expand our learning about dogs. What if we had a group of dog experts with whom we could discuss our understandings as we were learning? What if we could post to a bulletin board to discuss our observation that the Cairn Terrier has an extremely loud bark? Would the discussions that ensued influence our understanding? What if we were able to talk with someone privately through e-mail to discuss concepts that we did not understand or that we would like to clarify? Learning about dogs in a variety of contexts would extend the chances that we could apply what we learned about dogs to new contexts. In other words, the ability to apply newly constructed knowledge in new circumstances depends in part on the variety of circumstances in which we have learned or practiced the information or skill (Salomon and Perkins, 1989).
Part of what we do when we design an online learning environment is to engineer context. We do this in two interdependent ways. First, we arrange the learning activities and tasks to best advance understanding of the content (refer back to our discussion of learner activity). Second, we engineer the design of the environment itself. We arrange the information resources, communication options, and learning tools in ways that make sense given the learning goals. In other words, what we want our students to learn, and the activities and mental processes that we design to advance that learning, both influences and is influenced by the way we organize information resources, connections to the learning community, and access to technology tools. Figure 1 depicts these influences.
Figure 1: Learning Context Influences the Selection of and Connection to Online Resources
The learning context influences the learner's selection of information resources, technology tools, and conversations with certain members of the learning community. Depending on the nature of the learning activity, the nature of the learning goals, the culture and diversity of the learning community and the learner's prior knowledge, the learner may connect to some resources while choosing not to access others. The context also influences the learner to choose the type, quality and quantity, and the sequence of interactions with certain members of the learning community. Likewise, the context influences the learner's selections of information resources and the priorities that the learner places on accessing certain learning tools.
Often we are tempted to design online environments using every "button and whistle" at our disposal. The availability of technology options should not drive our design decisions. If it does, we are left with an environment that may be technologically advanced, but does little to advance learning. Several questions, all of which focus on the learning goals within the learning context, might prove helpful during the design decisions:
- What do I want the students to know about?
This is the content question. What are the concepts, skills, procedures and processes that are important?
- How do I want the students to know it?
This is the outcome question. Do I want my students to memorize facts? Do I want students to apply information? Do I want students to construct meaning through problem solving? Do I want students to construct meaning through collaborative inquiry?
- Who might the students talk with to learn those things in that way?
Will students talk with each other? Will students talk with experts? Will students talk with me?
- What forms of communication would be the most effective?
Will it be important to talk in real time? Is there an advantage to a threaded discussion that students can access at their convenience? Will online communication be informal? Are there times when I will require evidence to back assertions in order to establish a more scholarly and formal discourse?
- What tools are required to complete or might help my students complete the various activities and projects?
Will they need to use a spread sheet? Will they download PDF files? Will they need to use particular software packages?
Information Acquisition and Knowledge Construction: The promise of balance
Designing learning environments has too often been cast as a choice between rich content and meaningful opportunities to construct knowledge. What we have discovered is that knowledge is information combined with experience, context, interpretation, and reflection (Davenport, Long, and Beers, 1998). Knowledge is dynamic. It is what a knower knows and how he or she knows it. There is no knowledge without someone knowing it (Fahey and Prusak, 1998). Information and knowledge do not exist on opposites ends of a "versus". Rather, they work together in important ways as learners grapple with new content to make meaning. We must not design online learning environments as electronic repositories of information. Yet effective online learning environments cannot be devoid of resources. Learners must have information resources to use as they reconcile new information with their own prior knowledge of a topic. We can arrange online resources in ways that allow learners to grapple with tough questions and engage in controlled wandering - tapping information resources not in a prescribed arrangement, but as a natural compliment to problem-solving and inquiry. Our environments can encourage students to use mental processes like analysis, synthesis, and evaluation in the course of solving real and nonlinear problems that expand or add to their existing understanding. The real promise of a balanced approach is that instructors can create learning environments that require learners to use rich and challenging content in sophisticated and thought-provoking ways.
Versus Two: Student-centered versus teacher-centered learning
The artificial debate characterized in this "versus" is all too familiar. In fact, most of us can chant the rhyming form of the argument that touts the "guide on the side" as preferable to the "sage on the stage." One of the dangerous influences of this synthetic dichotomy is that many university educators feel compelled to abandon lecture, direction, and explanation both online and in face-to-face environments for fear of compromising their students' ability to learn.
At its heart, this "versus" grossly simplifies effective learning environments and ignores the ways that effective instructional strategies work together to support and enhance learning. The teacher-centered/student-centered "versus" reduces the teacher's role to a choice between being a controller or a facilitator. This forced choice obscures a myriad of options for teacher directiveness that ebbs and flows in response to the learning goals and the learning context. The choice then is not one of "either/or," but rather one of defining the learning goals. Once our learning goals are clearly in the crosshairs, we vary levels of teacher directiveness to support student progress toward those goals. Simply put, all responsive and responsible learning environments employ a combination of teacher- and student-centered strategies to ensure and monitor progress toward specific learning goals.
Figure 2 provides a "helicopter view" of the dynamics of learning environments and the reciprocal roles that teachers and learners play in those environments. It portrays four general forms of teacher/student directiveness. The figure is not meant to nominalize or quantify a teacher-centered environment or a student-centered environment. Rather, the figure provides a framework for discussing a learning-centered environment. As with any graphic depiction of dynamic complexity, the figure has inherent limitations that must be addressed. Though the figure attempts to represent an environment as multidimensional, it does not capture the ebb, flow, and fusion of varying degrees of teacher-centered and student-centered directiveness that exist as gradients among the four general forms. The figure is merely a diagram, a graphic representation of the give and take of power. In fact, it might be useful to compare the figure to a child's pinwheel that is still and motionless. By holding the pinwheel still, we can examine its various points and notice their distinct characteristics. Yet, to truly understand a pinwheel we must put it in motion, realizing that distinct points blur when the pinwheel whirs into action. The same can be said of Figure 2. It provides a way to examine and discuss elements that function in a blended whirl of activity.
Figure 2: The Four Quadrants of Teacher Directiveness
Yet, even with its inherent limitations, Figure 2 has utility for examining the nature of a balanced learning-centered environment. It shows four interdependent quadrants of teacher/student centered roles. In an online learning environment, as in face-to-face situations, there are instances when each of the four quadrants makes good instructional sense, based on the learning goal. In fact, we can map effective learning environments onto all four quadrants in an infinite variety of combinations and degrees, depending on the learning goals. The purpose of the figure is not to establish whether teacher-centered approaches are better than student-centered approaches, but rather to discover what combination and degrees of teacher/student directiveness best serve certain learning goals. In other words, the figure begs the question, "What combination of strategies produces the most effective learning-centered environment?" To answer that question, we can examine each of the quadrants to note both its potential for supporting learning goals and to determine ways that it joins other quadrants to create effective learning-centered environments.
Quadrant 1: Teacher as Director
In Quadrant 1, teacher directiveness is high while student directiveness is low. Effective teachers use this quadrant to establish, organize, and structure resources and infrastructure; set criteria for the quality of performance; establish methods for performance improvement; and establish goals for productivity. Through engineering tasks, the educator clearly defines roles and objectives while considering time factors, types of assignments, methods for timely student feedback, and ways to monitor student progress. In other words, a teacher works in Quadrant 1 when he or she is organizing resources in ways that will support student learning. For example, teachers can organize information to proceed from general to specific - to begin with the rule and then proceed to illustrative examples (Ausubel, 1977) - in order to facilitate comprehension of new or unfamiliar information. The teacher can share objectives and provide an overview of what is to come over the course of the learning experience.
In Quadrant 1, teachers provide direct instruction. For example, teachers can use questioning strategies to teach students how to ask good, thought-provoking questions in chats, on bulletin boards, and through e-mail messages with members of the online community. This is an important reason to direct student learning, since educational researchers argue that the ability to ask good questions and to know how to ask them might be the most important aspect of intelligence (Arlin, 1990; Getzels and Csikszentmihalyi, 1967; Sternberg and Spear-Swerling, 1996).
Quadrant 2: Teacher as Leading Learner
Quadrant 2 depicts a state of high teacher and high student directiveness. In this quadrant, the teacher engages students in setting goals for themselves and organizing their work, while providing students with high levels of socio-emotional support. The teacher functions a task leader purposefully dealing with obstacles to individual or group learning. A teacher in this quadrant uses questioning to stimulate and facilitate discussion. For instance, the teacher can use a variety of hard questions focused on tapping student comprehension, application, synthesis, analysis, and evaluation of information coupled with critical feedback to maintain effective learning (Berliner, 1987). In this quadrant, the student is also highly involved in directing the learning experience. In fact, in Quadrant 2, both the teacher and the students are working as equal partners to progress toward the learning goals. As students grapple with information, tasks, and mental processes, the teacher remains attentive to student diversity in areas of cognition, prior knowledge and skills. As the leading learner, the teacher is acutely aware of the role of individual differences in learning and guides discussions to focus on higher levels of reasoning and higher quality explanations (Hogan, Natasi, and Pressley, 1999).
Guided discovery (Brown and Campione, 1994) - a process where the teacher selects the information and tasks to help students reason with newly learned concepts - is a good example of a Quadrant 2 strategy. Using guided discovery, a teacher could provide students with graphic representations or photos of actual animal skulls representing various mammals. The teacher would then challenge the students to use information resources and discussions with other online learners to not only determine each animal's diet but also to defend their dietary determinations for each skull. In Quadrant 2, students can freely explore the limitations of what they are learning, and the teacher is vigilant and available to direct the process by providing purposeful, outward-looking task leadership. The teacher, mindful of the learning goal, encourages students to learn from their mistakes and gives effective feedback in a process that will benefit the students' behavior and learning.
Quadrant Three: Teacher as Facilitator
The third quadrant - high student directiveness and low teacher directiveness - focuses on the student's struggle with a problem. During problem solving the teacher supports learners in developing control of their own learning and problem solving in a domain. Here, students have a more central and active role in the learning as they regulate their learning and construct understanding (Davis, 1997; Nuthall and Alton-Lee, 1992; Pintrich and Schunk, 1996). During student-centered learning, the teacher's role can be viewed as one of perturbation or puzzlement. In other words, the teacher acts as a stimulus for the learning (Duffy and Cunningham, 1996).
Problem-based learning (PBL) is a perfect example of a Quadrant 3 learning process. Engaged in PBL activities, students act as professionals and confront problems as they occur - with fuzzy edges, insufficient information, and a need to determine the best solution possible by a given date. In problem-based learning, the traditional teacher and student roles change. The students assume increasing responsibility for their learning and more feelings of accomplishment, and the faculty in turn become resources, tutors, and evaluators, guiding the students in their problem-solving efforts.
Problem-based learning, a decidedly perfect example of a Quadrant 3 activity, is also a perfect context for examining how the quadrants overlap and work together. PBL curriculum consists of carefully selected and designed problems that demand from the learner the acquisition of critical information, problem-solving proficiency, self-directed learning strategies, and team participation skills. To design such a problem, the teacher begins in Quadrant 1, selecting the problem, articulating it, setting up the online environment to support the collaborative process and designing performance assessments. Here the teacher provides direct instruction while setting both expectations and parameter for the students. Using Quadrant 2, the teacher explains and demonstrates the problem-solving process, supporting students as they gain skill and proficiency. Incorporating Quadrant 3 strategies, the teacher facilitates PBL and empowers groups and individuals to work across time and distance. Throughout the learning experience, the teacher creates an atmosphere of trust and comfort through the use of Quadrant 4 strategies. The strategies both engender and support active learning and participation.
Quadrant Four: Teacher as Nurturer
In Quadrant 4, both teacher and student directiveness are low. Teachers in this quadrant exhibit enthusiasm for the content and learning tasks, make personal connections with their students, and provide encouragement and feedback aimed at fostering positive attitudes and perceptions of the learning climate. Working in Quadrant 4, the teacher attends to perceptions and attitudes. Even though most of what happens in this quadrant happens in a relaxed and informal fashion, it can be one of the most important quadrants of all. Setting a tone of enthusiasm, recognizing student interests, garnering student trust and modeling integrity and acceptance can go a long way toward helping students feel connected and "real" in a virtual class environment. Quadrant 4 strategies help students feel valued and connected to a real learning community as the teacher utilizes processes for establishing relationships and trust online, evaluating group cycles and applying techniques for pacing, leading and encouraging participation. When teachers establish environments of comfort and trust, they help their students move from understanding purpose to establishing productive action.
One of the most important student perceptions can be described in terms of the students' perceptions of task value (Marzano, 1992). Current educational research and theory indicate that students are more motivated when they believe that the tasks they are involved in are relevant to them personally and to their career goals. In fact, Keller (1983, 1984, 1987a, 1987b) reported that for students to feel motivated to participate in an online learning activity, they must not only perceive it as personally relevant, but they must also feel confident that they can perform effectively on the learning task and receive satisfaction from their engagement in the task.
Combining the quadrants: The promise of balance
It is not a matter of choosing between teacher-centered or student-centered strategies. One is not inherently better than the other. Each has its purpose and in combination each supports and compliments the other. The power of balance comes from recognizing that various combinations of student- and teacher-centered directiveness operate in a learning-centered environment. Quadrant 1 is useful for teaching new concepts and techniques, basic skills, facts, and procedures; setting standards; setting criteria; and defining learning tasks. Quadrant 2 has utility for extending and refining concepts, while Quadrant 3 encourages students to use knowledge meaningfully in problem-based and real-world situations. All learning depends on the attitudes and perceptions that are fostered and supported by Quadrant 4. The most effective online environments deftly combine all four quadrants, moving seamlessly among them to provide a meaningful range of learning experiences.
Conclusion: Finding liberation in balance - The metaphor of the Yin and Yang.
We can view the roles that various educational elements play in dynamic environments through the metaphor of the yin and yang. Although the yin and yang are opposites, they are not unrelated. In yang there is always a black spot of yin. In yin there is always a white spot of yang. They are mutually dependent opposites and they work together and function in balance. In this way, the yin and yang provide a guiding metaphor for online learning environment. Mindful of this metaphor, we can envision Web environments that comprise complex and interrelated elements that influence and support effective learning. Balanced environments capitalize on the forces of dependent opposition - forces derived from the interactions of seemingly opposite elements. In a balanced learning environment, an instructor can choose from and combine any number of strategies and techniques that will support students as they make progress toward identified learning goals.
Seeking balance is an act of conscious will that can be quite liberating. By deliberately avoiding the trap of the pointless polarization of instructional practices, we begin to fuel our online teaching lives with creative power. Freed from the need to separate practices by some artificial standard, we are able to focus on what matters most - learning. A balanced stance allows us to include and integrate a variety of strategies and approaches that can work together in a dynamic way to support student learning.
In this article, I have argued that artificial debates like the two "versus" examined, have commandeered discussions of learning on the World Wide Web. The most destructive by-product of our tendency to sort educational practices into "good" versus "bad" is that to do so forces our online teaching and design decisions into "either/or" frameworks that limit our options and hold our thinking hostage. In doing so, we expend enormous energy measuring what is right and wrong with inaccurate and simplistic yardsticks. Rather than devote another shred of energy pitting one educational practice or strategy against another, I have argued for a move toward a balanced approach to online learning environment design.
About the Author
Connie M. Moss is the Co-Director of the Center for Advancing the Study of Teaching and Learning (CASTL) and the Director of the Teaching as Intentional Learning (TIL) program at Duquesne University in Pittsburgh, Pa. Her research focuses on effective learning environments, belief formation, and teacher cognition.
The creativity of Rick Ragan, CASTL's multimedia and interface designer, is gratefully acknowledged for his contribution to the design of the figures presented in this article.
1. Roszak, 1986, p.87.
2. Derry and LaJoie, 1993, p. 5.
3. McLellan, 1996, p. 9.
M. Arlin, 1990. "Wisdom: The art of problem finding," In: R.J. Sternberg (editor). Wisdom: Its nature, origins, and development. New York: Cambridge University Press, pp. 230-243.
D.P. Ausubel, 1977. "The facilitation of meaningful verbal learning in the classroom," Educational Psychologist, volume 12, number 2, pp. 162-178. http://dx.doi.org/10.1080/00461527709529171
D. Berliner, 1987. "But do they understand?" In: V. Richardon-Koehler (editor). Educator's handbook: A research perspective. New York: Longman.
A. Brown, D. Ash, K. Nakagawa, A. Gordon, and J. Campione, 1993. "Distributed expertise in the classroom," In: G. Salomon (editor). Distributed cognitions: Psychological and educational considerations. Cambridge: Cambridge University Press, pp. 188-228.
A.L. Brown and J.C. Campione, 1994. "Guided discovery in a community of learners," In: K. McGilly (editor). Classroom lessons: Integrating cognitive theory and classroom practice. Cambridge, Mass.: MIT Press.
J.S. Brown. A. Collins, and P. Duguid, 1989. "Situated cognition and the culture of learning," Educational Researcher, volume 18, pp. 32-42. http://dx.doi.org/10.3102/0013189X018001032
P. Cobb, 2000. "Constructivism," In: A.E. Kazdin (editor). Encyclopedia of psychology. New York: Oxford University Press, volume 2, pp. 277-279.
T.H. Davenport, D.W.D. Long, and M.C. Beers, 1998. "Successful knowledge management projects," Sloan Management Review volume 39, number 2 (Winter), pp. 43-57.
R.B. Davis, 1997. "Alternative learning environments," Journal of Mathematical Behavior, volume 16, number 2, pp. 87-93. http://dx.doi.org/10.1016/S0732-3123(97)90018-3
S.J. Derry and S.P. LaJoie, 1993. "A middle camp for (un)intelligent instructional computing: An introduction," In: S.P. LaJoie and S.J. Derry (editors). Computers as cognitive tools. Hillsdale, N.J.: Erlbaum.
S. Derry and A. Lesgold, 1996. "Toward a situated social practice model for instructional design," In: D.C. Berliner and R.C. Calfee (editors). Handbook of educational psychology. New York: Macmillan Library Reference USA, pp. 787-806.
T.M. Duffy and D.J. Cunningham, 1996. "Constructivism: Implications for the design and delivery of instruction," In: D.H. Jonassen (editor). Handbook of research for educational communications and technology. New York: Macmillan Library Reference USA, pp. 170-198.
L. Fahey and L. Prusak, 1998. "The eleven deadliest sins of knowledge management," California Management Review, volume 40, number 3, pp. 265-276. http://dx.doi.org/10.2307/41165954
J.G. Greeno. 1989. "Situations, mental models, and generative knowledge," In: D. Klahr and K. Kotovsky (editors). Complex information processing. Hillsdale, N.J.: Earlbaum, pp. 134-181.
J.G. Greeno, 1998. "The situativity of knowing, learning, and research," American Psychologist, volume 53, number 1, pp. 5-26. http://dx.doi.org/10.1037/0003-066X.53.1.5
J.G. Greeno, A.M. Collins, and L.B. Resnick, 1996. "Cognition and learning," In: D. Berliner and R. Calfee (editors). Handbook of educational psychology. New York: Macmillan Library Reference USA, pp. 15-46.
J.G. Greeno, J.L. Moore, and D.R. Smith, 1993. "Transfer of situated learning," In: D.K. Detterman and R.J. Sternberg (editors). Transfer on trial: Intelligence, cognition and instruction. Norwood, N.J.: Ablex, pp. 99-167.
J.W. Getzels and M. Csikszentmihalyi, 1967. "Scientific creativity," Science Journal, volume 3, number 9, pp. 80-84.
K. Hogan, B.K. Nastasi, and M. Pressley, 1999. "Discourse patterns and collaborative scientific reasoning in peer and teacher-guided discussions," Cognition and Instruction, volume 17, number 4, pp. 379-432. http://dx.doi.org/10.1207/S1532690XCI1704_2
D. Jonassen, 1993. "Effects of semantically structured hypertext knowledge bases on users' knowledge structures," In: C. McKnight, A. Dillon, and J. Des Richardson, 1993. Hypertext: a psychological perspective. New York: Ellis Horwood.
D.H. Jonassen, 1994. Computers in schools: Mindtools for critical thinking. University Park: Pennsylvania State University Press.
Y.V. Karpov and J.D. Bransford, 1995. "L.S. Vygotsky and the doctrine of empirical and theoretical learning," Educational Psychologist, volume 30, pp. 61-66. http://dx.doi.org/10.1207/s15326985ep3002_2
J.M. Keller, 1983. "Motivational design of instruction," In: C.M. Reigeluth (editor). Instructional-design theories and models: An overview of their current status. Hillsdale, N.J.: Erlbaum.
J.M. Keller, 1984. "The use of the ARCS model of motivation in teacher training," In: K. Shaw (editor). Aspects of educational technology, volume 17. Staff development and career updating. New York: Nichols.
J.M. Keller, 1987a. "Strategies for stimulating motivation to learn," Performance and Instruction Journal volume 26, number 8 (October), pp. 1-7. http://dx.doi.org/10.1002/pfi.4160260802
J.M. Keller, 1987b. "The systematic process of motivational design," Performance and Instruction Journal volume 26, number 9 (November-December), pp. 1-8. http://dx.doi.org/10.1002/pfi.4160260902
J. Lave and E. Wenger, 1991. Situated learning: Legitimate peripheral participation. New York: Cambridge University Press.
R.J. Marzano, 1992. A different kind of classroom: Teaching with the dimensions of learning. Alexandria, Va.: Association for the Supervision of Curriculum Developement.
H. McLellan, 1996. "Being digital: Implications for education," Educational Technology (November/December), pp. 5-20.
C.M. Moss, 2000. "Professional learning on the cyber sea: What is the point of contact?" CyberPsychology and Behavior, volume 3, number 1, pp. 41-50. http://dx.doi.org/10.1089/109493100316210
G. Nuthall and A. Alton-Lee, 1992. "Understanding how students learn in classrooms," In: M. Pressley, K.R. Harris, and J.T. Guthrie (editors). Promoting academic competence and literacy in school.
R.D. Pea, 1985. "Beyond amplification: Using the computer to reorganize mental functioning," Educational Psychologist, volume 20, number 4, pp. 167-182. http://dx.doi.org/10.1207/s15326985ep2004_2
P.R. Pintrich and D.H. Schunk, 1996. Motivation in education: Theory, research and application. Columbus, Oh.: Merrill.
B. Rogoff, 1990. Apprenticeship in thinking: Cognitive development in social context. New York: Oxford University Press.
T. Roszak, 1986. Cult of information: The folklore of computers and the true art of thinking. New York: Pantheon Books.
G. Salomon, 1993. "On the nature of pedagogic computer tools. The case of the wiring partner," In: S.P. LaJoie and S.J. Derry (editors). Computers as cognitive tools. Hillsdale, N.J.: Erlbaum.
G. Salomon and D.N. Perkins, 1989. "Rocky roads to transfer: Rethinking mechanisms of a neglected phenomenon," Educational Psychologist, volume 24, pp. 113-142. http://dx.doi.org/10.1207/s15326985ep2402_1
J.R. Savery and T.M. Duffy, 1995. "Problem based learning: An instructional model and its constructivist framework," Educational Technology (September-October), pp. 31-38.
M. Scardamalia and C. Bereiter, 1989. "Intentional learning as a goal of instruction," In: L. Resnick (editor). Knowing, learning and instruction: Essays in honor of Robert Glaser. Hillsdale, N.J.: Erlbaum.
R.J. Sternberg and L. Spear-Swerling, 1996. Teaching for thinking. Washington, D.C.: American Psychological Association.
Work Group of the American Psychological Association Board of Educational Affairs (BEA), 1997. Learner Centered Principles. Washington, D.C.: American Psychological Association.
Paper received 11 December 2001; accepted 27 December 2001.
Copyright ©2002, First Monday
Finding Balance: The Vices of Our "Versus" by Connie M. Moss
First Monday, volume 7, number 1 (January 2002),