Educational Technology: Support for Inquiry-Based Learning
AbstractThis paper considers a wide variety of educational software resources and their educational effects in considering the questions: How can educational technology support children's learning? Are there different uses of educational technology that fit with various theories and types of learning? What are the emerging trends in educational technology that respond to new understandings of how students learn?
HOW CAN EDUCATIONAL TECHNOLOGY SUPPORT STUDENTS' LEARNING? Are there different uses of educational technology that fit with various theories and types of learning? What are the emerging trends in educational technology that respond to new understandings of how students learn? This paper investigates one approach to answering these questions, by considering a wide variety of educational software resources and their educational effects.
The number and variety of educational software titles available to schools and homes has increased dramatically over the last several years. Just the titles and sources of current programs fill an entire CD-ROM, The Educational Software Selector (TESS) (Epie Institute, 1991). To discuss educational software in its full scope, some organizational scheme is necessary. TESS uses an approach that sorts by academic content, grade level, and classroom organization. The categories used herein relate to the uses of educational software to support student learning.
Until recently, much of educational technology has been used to support the teaching and learning of basic skills such as arithmetic facts, spelling, and other topics that could be reduced to multiple-choice questions. However, recent research on cognitive growth and learning, building on the views of Dewey, Piaget, Vygotsky, and others, has led many educators to reconsider teaching approaches in general, and the ways technology is used to support student learning in particular. These new perspectives on student learning form the pedagogical basis of recent and newly emerging standards for mathematics and science teaching and learning. Although these standards documents differ in detail, they all have at their core a common view of the value of a particular kind of learning, which I call "inquiry-based learning." This paper focuses on inquiry-based learning for two reasons. First, because our current understandings of education highlight its importance, specifically as the most powerful mode in which students learn. Second, as our understanding of learning has evolved, so has our understanding of how technology can support learning; it has become apparent that technology is particularly well-suited to support inquiry learning.
This paper contains two major sections. The first section describes inquiry-based learning in some detail and technology's potential role in supporting it. This section also includes several general points about the ways in which technology and learning interact in schools, as well as inherent difficulties in assessing the results of introducing a combination of technology and inquiry into classrooms. The second section then presents categories of software organized around their relationship to inquiry-based learning. Besides identifying groups of software that have similar underlying positions with respect to inquiry, this section includes several specific examples that illustrate the kinds of thinking and problem solving that students might engage in while using this software.
INQUIRY-BASED LEARNING, WITH AND WITHOUT TECHNOLOGY
This section defines inquiry-based learning and describes key elements and characteristics, whether or not technology is used. It goes on to suggest ways in which technology can support inquiry-based learning, and closes with suggestions for evaluating the educational effects of this approach to teaching and learning.
Defining Inquiry-Based Learning
What is inquiry-based learning? There are as many specific answers as there are people to ask, but there are common themes to the descriptions that represent a core of belief about inquiry. The list below is loosely based on Nickerson (1988), but includes some additional thematic elements and some connections to technology.
Constructivism. The major claim of this theme is that learning is an active process, described as forming new mental models rather than as assimilating information. Students continually create their own mental models as they encounter new material. It is questionable if "passive learning" could even exist. Integral to the concept of constructivism is the notion that much of learning comes from grappling with complex problems, for which there may be multiple approaches. The interaction a learner has with others engaged in the task adds to the learning potential; language is the most important carrier of these inquiry-supporting interactions. Out of such experiences, learners build their own knowledge.
Importance of conceptual understanding, rather than procedural efficiency. Especially in math and science, much of the knowledge students are often expected to know is procedural; that is, how to follow particular rote recipes. If this knowledge is not situated in an understanding of how and why the procedures work, students may not be able to know when and how to use them. Conceptual understanding includes a much richer and more flexible array of knowledge that makes it possible for students to think deeply even without a procedure, to know when and how to apply proper procedures, and to interpret their results appropriately.
Responsiveness to what students already know. No student enters a class as an empty vessel. Education must take account of what students bring with them. Based on life and school experiences, every student has formed many ideas about math, science, social studies, writing, etc. Some of these pre-existing ideas are valuable bases for continued learning; others are wrong and would lead the student further into territory that is not educationally useful. Students' incorrect ideas have sometimes been called "misconceptions" and inquiry-oriented methods to help students reform their ideas into more correct conceptions have been designed. Technology can play a role in this regard by assisting teachers in understanding students' knowledge and current conceptions, as many pieces of software help students display their thinking and procedures in a more accessible form.
Connections to the world outside of schools. Research is beginning to show that one problem with school learning is that students often fail to connect it to what they have learned outside school. Students often bring knowledge to class that is directly relevant to what they are learning, but fail to see the connection. In response to this issue, some of the new curriculum efforts are focusing on the creation of authentic tasks which meet needs and goals that students either have already or might have in the future.
Furthermore, students often fail to see how the work they do in school is related to their lives at home. Parents can do much to support home-school connections, but research has documented most parents' lack of connection with their children's schools. Chris Dede (O'Neil, 1995) claims that "We know that the biggest single impact that we could make in the lives of many children would be to involve their parents more deeply in their learning" (p. 10).
Metacognition. Students need to know how to take responsibility for managing and monitoring their own thinking and learning activities. These kinds of skills (e.g., knowing when you have learned something or planning to use your most effective learning strategies to master some content) are sometimes called "metacognitive skills" because they require the students to examine their own learning practices. In an inquiry-based perspective, students need to reflect on the steps they take to generate questions about a new topic, how they collect information to help focus on a smaller set of questions, how they evaluate the relevance of the information, how they decide to what steps to take next, and how they communicate their conclusions. Unfortunately, most curricula do not explicitly call for a focus on metacognitive learning.
Lifelong learning. The students of today will need to learn throughout their lives. In the past, technology and jobs changed relatively slowly, but today's world can change practically overnight. Many of today's jobs require facility with technologies that didn't exist 20 years ago, and reeducation is the only way some people can continue to work at skilled jobs. Students need to prepare in school to continue to learn for the rest of their lives; in terms of inquiry, this means cultivating curiosity, knowing where learning resources might be, having experience with tacking complex problems, and knowing how to work with others in crafting approaches to difficult situations.
What does a classroom in which inquiry is taking place look like? Commonly, some or all of the following characteristics are present:
- Questions are, in general, complex.
- Answers to questions are open-ended.
- Most questions have more than one right answer or more than one way to get to a right answer or both.
- Students are assessed by how they get to the answer, as well as the answer itself.
- Discussion among students or between students and teacher is part of the process.
- Students have to plan and organize as part of their work on a problem.
- Communication takes place in multiple modalities and forms--both oral and written, pictorial, graphical, and symbolic.
- Teachers play a role as facilitators of learning, rather than as transmitters of information.
The descriptions above mention nothing about technology for, in fact, solid inquiry-based learning can occur without technology and often does. But technology can play a special role in supporting inquiry-based learning and in transforming classroom practice. To better understand the context in which technology can support inquiry-based learning, two important distinctions should be noted: technology can be viewed as the subject of instruction or as a tool for instruction, and can serve as an amplifier of traditional practice or as a transforming agent. These varying approaches are discussed below.
Learning with computers, not learning about computers. We distinguish between learning about computers (e.g., how to hook up a disk drive, what is the difference between RAM and ROM) and learning with computers. This paper focuses on learning with computers; that is, learning the topics of the curriculum (language arts, math, science, social studies, etc.) with computers as a pedagogical tool. This does not deny that students need to know how to attach peripherals, put in and use a digitizing card, be proficient in a programming language and so on. But except for a general introduction to the way the machine operates, students tend to pick up most of these skills naturally in the context of using computers to learn other subjects. To learn effectively with computers, a few skills (e.g., keyboarding) are necessary in advance. Some students may need to spend time focusing on these skills to avoid frustration. But even keyboarding is best learned in the context of using the computer for other tasks, so that it does not become a rote lesson without a purpose.
The answer to the central question, "Will technology have a significant effect on K-12 education?" can be determined only by asking a follow-up question: "How is the technology used by students and teachers?" Their experiences, in turn, are determined by the models of teaching and learning that underlie the instruction in their classrooms. Pedagogy is the key. When we look at the interaction between pedagogy and technology, the most obvious conclusion is: Traditional pedagogy isn't improved much by the addition of technology. Good pedagogy, on the other hand, can be made significantly more effective by appropriate uses of technology.
When learning with technology focuses on doing inquiry-based learning, the following approaches are commonly adopted in classrooms:
- Technology is viewed as a tool, much like a pencil or pen, but considerably more powerful.
- Use of the technology is primarily taught in the context of solving problems.
- Students help one another with the mechanics of the technology; in fact, in many classrooms, students are the local experts on technological details.
- Talk about and around technology is as important as the technology itself, just as talk about how one finds and uses information is as important as the information itself.
- Technology is used to augment communication by expanding audience (e.g., over networks and by producing hard copy) and expressive options (e.g., mixing graphs and words).
A more transformative way to use word processors would resemble ways in which adults use them - to take notes, to fashion individual phrases and sentences, to construct a final draft, and to revise by moving words, phrases, sentences, and paragraphs around. This learning process might be embedded in a social setting in which students comment on one another's papers (perhaps for publication) and revisions are made in response to others' suggestions. In this scenario, students' writing processes are changed in a significant way from a more traditional approach. The introduction of a real audience and purpose - as in publishing a class literary magazine - has transformative potential, as the writing process changes in response to the authenticity of purpose and audience. Word-processing technology makes this audience or purpose more accessible, but does not in and of itself provide or mandate it. That is the job of the teacher and the curriculum approach.
A final comment about the amplifier/transformer distinction: In classrooms that have already been "transformed" by curriculum innovations (e.g., the Writing Project), what might in other classrooms be considered a transformative use of technology might here be considered an amplification of the current curriculum. Therefore, in a classroom that has a serious commitment to the writing process, adding word processors would serve to amplify - in quite significant ways - the current classroom practice. The technology will do less to transform the curriculum approach in this setting than it would it a classroom still working with more traditional writing instruction. In applying the terms amplifier and transformer, therefore, we must always be clear about what is being amplified or what is being transformed. The use of each of these terms is relative to the choice of a starting point from which to proceed.
Understanding How Technology Has Affected Student Learning
Given that technology's effects depends on its uses, rather than simply on characteristics of the software, how do we assess and evaluate its effect? Teachers, principals, parents, and policymakers care deeply about the answers to this question. Such evaluations are often used to decide whether a technology program has been a success, to compare schools systems that have embarked on different technological paths, or to decide whether to continue to support a technological specialist, in addition to the traditional uses of assessment to compare students, teachers, and schools. At this general level of discussion, there are three important principles that reinforce the complexity of the task of measuring educational effect. Consider the following:
Educational change takes time and is a complex process. Although some educational change can be relatively rapid, inquiry-based reforms are especially likely to take significant amounts of time. Inquiry innovations that use technology require sufficient time for teachers to master the tools and the pedagogy to the extent that they can structure the classroom so that inquiry emerges. Research supports these insights. Most of the studies have found that changes in student learning as a result of some innovation take several years to become measurable. Some research reports that, with daily use of technology, it is at least a year before any changes are evident. Where educational goals are focused, relatively contained, and connected closely to assessment methods, changes can be seen in periods of one to two semesters (Herman, 1994). But where more significant restructuring is taking place, periods of several years are more realistic estimates for seeing significant changes in student learning.
Where major changes in pedagogy are involved, one needs to take into account the amount of time professional development requires, both for actual out-of-classroom activities such as workshops, study groups and in terms of the rate at which personal change (for that is what pedagogical change entails) takes place (see Grant, p. 72). The important point is that measuring student learning variables too early may suggest that little is happening - when in fact it is just too early in the process to see results.
Choices of assessment method - test scores, projects, portfolios - and content - facts, methods, inquiry - will determine what "changes" are observed and valued. Measuring changes in student learning based on technology use is a serious challenge. Besides the necessity of allowing sufficient time for change, there is the question of choosing an appropriate measure. In the past, often the only measure available was standardized tests. They are convenient because they are administered routinely, norms exist, and scores are reportable for students, classrooms, schools, districts, etc. These tests are predominantly multiple-choice (and thus easily scorable) and tend to focus on small, definable subskills and fact recall.
In the last decade or so, in parallel with the development of new standards, particularly for math and science learning, radically different approaches are being taken to assessment. Some of the work on both standards and assessment in math, for example, was in response to the observation that students in our educational system perform adequately on simple computational problems but stumble on problems that require them to figure out how to organize the operations rather than just carry out a designated set of steps. In general, the kind of test questions on which students do worst are those that require an understanding of the context of the question, not those that are straightforward arithmetic. A typical problem might be the following: "How many 60-pound dogs does it take to balance a 3,000-pound elephant?" (Mokros et al., 1994). Many students, lacking an understanding of the mathematics of the problem, try all four basic arithmetic operations using 3,000 and 60, but have no way of evaluating which of the four answers is correct!
Critics have pointed out that standardized tests reflect an earlier view of learning in which quick performance of short, repetitive tasks was the most important skill to measure. As the demands of the job market, our knowledge of the variety of people's intelligences (Gardner, 1983) and our view of schools' purposes change, these kinds of tests have become less relevant. Organizations such as the New Standards project, National Council of Teachers of Mathematics, and National Assessment of Educational Progress are all working on new styles of assessment that reflect changing educational values. Such tests, in general, ask more open- ended questions that require students to plan and organize a problem-solving approach, rather than answer a large number of multiple-choice questions. Scoring these tests, obviously, is more complex than machine-scoring of the older style of tests.
In general, the more closely an educational innovation (technological or not) is linked to the measures used to evaluate it, the more likely it is to show measurable results. Making this link is the easiest with very specific, out-of-context skills like "knowing the multiplication tables." But conceptual change, such as that implied by inquiry-based learning, is more slippery. Because the education we desire seeks the acquisition of a wide variety of capabilities: "domain-specific knowledge, generally useful cognitive skills, and the ability and desire to learn," (Nickerson, 1988, p. 3), the results are harder to measure. Thus, for inquiry-based learning in general, and that with technology in particular, statistical measures of effectiveness are often lacking. Furthermore, this is compounded by not having enough funding to carry out multiyear studies. Herman (1994) has suggested methods for more effective assessment strategies that include merging quantitative and qualitative methodologies, building and assessing theories of action, using process indicators as proxies for student outcomes, etc. This is the kind of work that will need to be expanded if we are to document how technology supports student inquiry.
What counts is what happens in the classroom, not what is written in the manual. And these may be quite different. In looking at the educational effects of technology, we must distinguish between the intention of an innovation - what its developers envisioned - and what really happens in a classroom. It should be no surprise that what actually happens with the same technology and the same curriculum differs from classroom to classroom. To be realistic about technology, we must keep in mind the variety of experiences that may take place with different teachers.
There is a complex relationship between the design of a technological innovation and what happens in a classroom. The developers have in mind some "idealization" of a technological innovation, embodied in its software and accompanying instructions for its use, which often include a large number of pedagogical assumptions. In using the software, however, each teacher creates a different realization, specific to his or her beliefs and implementation process. It is important to keep this "realization" and adaptation process in mind in evaluating any technological innovation; one central point of comparison is between the idea the developers tried to communicate and the innovation the teacher implemented (Bruce & Rubin, 1993). As one paper about the use of some computer-based writing tools in classrooms states, "The computer is the dependent variable." As such, it is subject to the pedagogy and beliefs of the teacher and to the specific circumstances of the classroom (Michaels, 1990).
These differences are particularly important in thinking about open-ended software that intends to support open-ended, student-centered activity; such software, by its very nature, cannot control what happens in the classroom. As always, it is the teacher who controls the way it is used. Thus, teachers who want to have classrooms in which all students are working on learning the same, identifiable skills, can just as easily use open-ended software as part of that traditional structure. One of the apocryphal (but true) stories told in the educational technology community is how many teachers developed worksheets to accompany LOGO®, software whose underlying philosophy and structure was dedicated to students' designing their own projects. These teachers in a sense turned the use of LOGO into the study of LOGO - and saw their educational goals as the answers to questions such as, "Write the command to make the turtle go forward and back 10 steps." This tendency to modify the intention of open-ended software is widespread in many schools, where there is tension between the old and the new ways of teaching, with pedagogical change occurring at the same time that technology is being introduced.
CATEGORIES OF SOFTWARE USE
Beyond these general descriptions, there is much more specific information about how technology can support inquiry in the classroom. Because different pieces of software support inquiry in different ways, the technology descriptions below are grouped into twelve categories, primarily by how they affect classroom practice. The discussion of each category includes a determination of how it does - or does not - support inquiry, a look at how the software might be used in support of inquiry-based learning, what classroom interactions might look like, and how and what students might be learning. In some cases, a more specific vignette is included to illustrate how the software-student interaction might proceed.
A general comment on these categories: It is difficult to categorize anything complex into a small number of mutually exclusive categories. Many of the pieces of software described below belong in the intersection of several categories; in fact, the best software combines characteristics from many categories and can greatly increase its power and effect in this way. In some ways, therefore, these categories describe characteristics of software that can be combined in many ways. Furthermore, educational uses of telecommunications technologies bring additional opportunities to extend computer usage in creative ways that support inquiry- based learning. These applications are not described in detail here, but can incorporate many features noted in this categorization. (For further discussion of a range of uses of telecommunications networks, see Berenfeld, 1996).
The categories are:
- Generic information handling tools
- Real-time data acquisition/MBL
- Educational games
- Cognitive tools
- Intelligent tutors
- Construction environments
- Virtual communities
- Information access environments
- Information construction environments
- Computer-aided instruction and integrated learning systems
Second, many of the pieces of software described below can be used in support of students' work on authentic, complex tasks. Tasks that involve research, communicating with experts, recording and representing information, presenting results, and persuading audiences reflect the kind of work students will engage in throughout their careers. These tasks are in general multidisciplinary and require collaboration, as are most tasks in real life. One such task might be to design a garden for the schoolyard and present the results to the rest of the school; this project would involve art, language arts, math, science, and, perhaps, even social science. Technology to support it could range from geometric analysis programs to drawing programs to the World Wide Web for finding information on plants and seeds to word processors for preparing the report.
Finally, this paper includes a special section on computer use in multicultural education because the topic of equity is of major importance. The categories of useful software are no different in multicultural classrooms, but certain uses have appealed to teachers as especially effective in allowing students to master complex technology and to feel they have found their "voices" through the special qualities of certain pieces of educational software.
1. Generic Information-Handling Tools
Almost everyone who has ever used a computer has used one of the basic information-handling tools: word processors, spreadsheets, databases, graphics packages, and page layout packages. Most adults who use computers in their jobs or at home use some or all of these tools. All these tools provide enormous flexibility for manipulating information once it is entered into the computer. Word processors can support flexible writing, in which multiple drafts are easy to construct, spelling and word choice can be supported by computer tools, and printed products have an "official" look that commands more serious reading by parents and friends. For some students, just the move away from handwriting to a more readable text is a significant boost in writing practice.
Data-handling software - spreadsheets and data bases - are similar in the flexibility they support. Students can see several different graphs of a data set in just a few minutes, expanding the ways they can conceptualize and understand their data. They can look at derived functions of numerical sequences and graph the results, allowing them to explore how the formula for a parabola is related to its graph or how a sine curve is built. Sophisticated students can use database and statistical functions to explore relationships among variables and to determine what might be an important parameter of an identified effect. With an appropriate curriculum, these tools can support inquiry as students explore complex problems, take data, find meaning in their data, and write about their findings. Most current word processors support the production of reports by allowing students to integrate words, graphs, and spreadsheets into a single document.
Many of these tools are used by real practitioners engaged in real problem-solving situations. To be most effective, use of the tools in schools should mirror as much as possible their use in real jobs. Examples of these "adult" tools often used in educational settings are: Microsoft Word®,Wordperfect®, Excel®, 1-2-3®, MacDraw®, PageMaker®, and FileMaker®.
The area of productivity tools has seen enormous growth over the last few years as computers have become less expensive and more powerful, and as more and more businesses provide workers with personal machines. This basic tool category could arguably be said to include three-dimensional visualization software (e.g., CAD), symbolic manipulation engines (e.g., Symbolica®), and sophisticated paint programs (Studio 8®). For high school students in particular, any of the new tools that are developed for the world of work may be relevant to learning in some subject. In most cases of using these adult tools, however, it takes a significant amount of time for students to learn the tool. If there are similar tools designed with simpler interfaces and a more scaled-down set of functions, it is often better to use them in schools. The trade-off to keep in mind here is the power of the tool compared with the overhead involved in students learning how to use it.
A second group of tools widely used in school are based conceptually on those used in out-of- school applications, but are tailored for educational purposes. To prepare software for an educational environment, the interface is simplified, the most complicated functions may be eliminated and more helpful instructions may be added. The Cruncher, for example, is a spreadsheet designed for elementary school students, and the Wonderful Writing Machine is a word processor for young students.
A third category of information-handling tools are those based on a completely different design than adult tools, because their designers believe that a different approach is more educationally appropriate. Tabletop, for example, takes a unique approach to databases by representing each data point individually rather than aggregating them, and by animating the process of constructing a graph. Consider a database of countries with information on the population, GNP, birth rate, average age, population, population density, etc. of each. In Tabletop, each country would be represented by an icon - say a small flag. The student can specify a scatterplot graph such as population by population density using a very simple interface. The flags then march into their appropriate positions along the two axes. The animation both captures students' attention and shows graphically how points are positioned on a two-dimensional graph. When the icons are all in place, the student can read the values of any of the other variables (e.g., birth rate) in a simple way, such as by labeling each of the flags with the value of this third variable.
Tabletop also includes some features that support inquiry in subtle but effective ways. One of these is the ability to build up a slide show of interesting data displays that students can use to show and discuss their work with other students or teachers. This feature supports the conversations that are so important to students becoming more practiced at inquiry. The slide show not only frees students from remembering all the details of intermediate steps, but provides illustrations for them to refer to in reflecting on and explaining their work later.
In addition, there are sometimes parts of these tools that are "strictly educational," software that demonstrates the meaning of a concept, but does not directly contribute to the functionality of the system. Statistics Workshop (Rosebery & Rubin, 1989), for example, is a statistical package that performs a subset of the functions a full-fledged statistics package would offer. But it also contains several explicitly educational parts. One, called "Shifty Lines," allows students to move a regression line on a scatterplot to see how different positions and slopes offer better or worse fits to data. Another, called "Stretchy Histograms," allows users to change a distribution and see how the mean and median change as a result. The picture below illustrates how feedback on mean and median of a distribution is given to the user as the distribution is modified.
One or more of the tools described in this section can form the basis for a curriculum innovation that enhances student learning. Even though each of the tools on its own may have potential for educational change, it is the combination of them in the context of a rich curriculum that produces real change. One example of this process is the Immigrant 1850 project (Walters & Gardner, 1990). Students had access to a core set of computer-based activities through which they adopted an immigrant family and simulated the complex decisions the family had to make in finding housing and a job. They used databases, spreadsheets, and word processors to calculate their expenses, keep diaries, choose jobs, decide on transportation, and see how their future turned out.
2. Real-Time Data Acquisition/Microcomputer-Based Labs
One of the most distinctive tools in the grab bag of educational software is real-time data acquisition technology - also called generically microcomputer-based labs (MBL). These various tools allow students to take data in real time from action in the real world, and to record and analyze it. Not only do students have the ability to investigate how the world works, but they also learn how certain phenomena translate into graphical representations. An MBL comes with a set of probes - each specified for a kind of measurement such as distance, heat, temperature, heartbeat. Through a uniform interface, each of these attaches to the computer, feeding information into spreadsheet and graphing programs. The power of the MBL derives from its connection with events in the students' world, with their motions, their heartbeats, their temperatures. The simultaneous perception of the real-world event and its representation on the computer can help students make sense of graphs and of the patterns they depict.
In one of the more common applications of a MBL, students learn how graphs of position, velocity, and acceleration are related and how they reflect different motions in the real world. For example, students might run at different speeds toward and away from a distance probe, creating a variety of graphs. They might then figure out how to match each graph with one of their motions, predict what velocity or acceleration graphs might look like or try to make a particular graph by moving in the appropriate way. With a temperature probe, students can investigate the relative temperature of parts of their bodies, the temperature of hot water as it cools, or the cooling curve of hot water insulated by different materials.
Microcomputer-based labs are a useful technology for elementary grades through college. In the years that MBLs have been used in universities, evidence has accumulated that students can gain a better understanding of difficult concepts such as the derivative through using MBL. MBL-based curricula for young children are now available as well.
A related set of tool-like programs are simulations, software that allows a user to change parameters and run a model to see the effect. Such software supports students' building and testing of hypotheses, interpretation of results, and subsequent revision and retesting. With Oregon Trail, for example, students play the role of the head of a family heading West to settle. Numerous obstacles and decision points arise on the way; different decisions about how much food to take, how many miles to go in a day, and how to ford a stream lead to different outcomes. The Search Series provides a variety of challenges - looking for oil, searching for treasure on an island, etc. - that students explore in teams. Each team decides on a navigational move, enters it into the computer, receives data about what happened, and spends some time plotting its next move. The Search Series is organized so that an entire classroom of students can use a single computer; one team enters its new parameters while the others decide on their next move and research the topics involved in the simulation.
Simulations differ from one another primarily in terms of the world that is simulated and the complexity of the underlying model. Sometimes the simulated world is the "real" one, as in predator/prey programs. In these, the educational goal is for students to understand what relationships govern the real-world behavior; that is, how the relative number of predators (e.g., foxes) and prey (e.g., rabbits) affect one another. Students learn underlying principles such as if the number of prey becomes very small, the number of predators will drop as well because they have insufficient food. They also learn what the mathematical forms look like that describe such behavior (e.g., exponential, and logarithmic curves).
Sometimes a simulation actually expands the world available to a student, because the world that is modeled is one that is otherwise inaccessible. RelLab (Horwitz & Barowy, 1994) is such an example. In this case, the educational goal is for students to learn about relativity, and the effects of motion at and beyond the speed of light. Obviously, no student can experience this phenomenon or experiment with it other than through a computer simulation; therefore, the technology serves a particularly valuable role.
Other simulations let students investigate an entirely imaginary world that behaves according to well-founded principles derived from real-world behavior. The very popular Sim series (SimCity, SimTown) is such an example. In each of these, students build a city (or town, etc.) of their own design, then "run" it as mayor, making decisions about building, spending money, raising taxes, etc. These are popular pieces of software, played frequently as games in students' homes. But the reasoning and planning that they encourage fits easily under the rubric of "inquiry." .
All the categories described above can be enhanced by the addition of multimedia; that is, computer-based video or audio. As these capabilities become more available and more affordable, the buying public will expect more sophisticated pictures and sounds to be a part of every piece of software. Of course, multimedia is not educational in and of itself. But, used well, it can help bring the world into the classroom in ways that are authentic, motivational, and deeply inquiry oriented. Unfortunately, many "educational" uses of multimedia just add "art" to text in the same way textbooks add illustrations to make the page look more interesting.
Multimedia makes the most of its educational potential when students actually use the medium as data (e.g., CamMotion), when they have to create an argument based on synthesizing different pieces of video (e.g., comparing Orson Welles and John Huston as directors, illustrated with clips of several of their movies), or when the video provides a context for a particularly interesting problem (e.g., Voyage of the Mimi, Jasper). Some particular combinations worth noting are data-collection tools that operate on multimedia (CamMotion), curricula that use video as an anchoring context (Jasper), and content-based multimedia "tours" that work in both school and informal settings such as museums (Palenque).
CamMotion is software developed as part of the VIEW (Video for Exploring the World) at TERC (Rubin, 1993). It allows students to collect data such as position, distance, and angle that changes over time. It allows a student to explore, for example, the flight of a ball thrown from one person to another or the position of a girl's legs as she does multiple cartwheels; the student clicks on the relevant spots on the screen, then composes a graph that corresponds to the motion. The student can then point to various parts of the graph and see the video that corresponds to that mathematical representation.
CamMotion can also be used with videos that students or teachers make. Taking videos can be combined with mathematical representations, for example, by having teams of students take videos that illustrate a particular graph. A graph of smooth deceleration, for example, might evoke videos of students sliding in their socks, a ball going up a ramp, a ball thrown into the air, a toy car at the end of its rubber band, a car stopping at a traffic light, a pendulum at the top of its swing. This software greatly extends the possibilities for student data collection and representation by making the visual and kinetic world of the student available as sources of data.
Jasper (Cognition and Technology Group at Vanderbilt, 1990) uses video to present a narrative situation that poses challenges or questions that the principal character needs to solve. Designed for middle school students, Jasper includes in the narration all the relevant information needed to solve the problem. The classroom interaction is heavily prescribed by the program to support active learning on the part of the students, supported by guided inquiry techniques on the part of the teacher. Here the video is a partner in the inquiry experience with the teacher. Much of the burden of setting up and shaping the problem-solving situation is on the teacher, but the video provides the opportunity for students to connect with the video, see salient problems in the characters' actions, and work on those problems with the information presented in the video. The video itself provides an experience that provides a common context for discussions between and among students and the teacher.
Palenque (Wilson & Tally, 1991) is a videodisc and accompanying software that allow students to explore a Mayan ruin in southern Mexico in an experience sometimes called "virtual travel." Slides, film, video, graphics, text, sound effects, and audio narration are all integrated on a single videodisc, designed to be totally student directed, rather than dependent on a teacher's instructional sequence and objectives. Students have simulated travel tools, such as a camera, a photo album, and a compass that allow them to navigate and collect snapshots of where they have been. An 8-year-old Mayan "specialist" provides informed commentary on the videotape.
Palenque was designed primarily as a prototype and has not been used much in school settings; therefore, we know little how it would interact with a school curriculum. Primarily, it provides us with an indication of how technology might offer information in a way that is compelling to individual users and fosters sense-making activities, rather than just browsing. Note that achieving this goal was difficult and required a multiyear development effort. In the end, it is a breath-taking experience to use Palenque, and its potential to be further developed and used escapes no one.
There has also been a huge explosion of educational CD-ROMs on the market that provide a set of images and short video clips on a single topic. Some examples (these are from Tom Snyder Productions, but there are many other similar offerings from other companies) are Rainforest Researchers, The Great Ocean Rescue, and The Great Solar System Rescue. The experience of using these is similar to the Jasper system described above; however, the curriculum and teacher support are more limited because these are packaged commercial products - the Jasper series is an ongoing research project that has continued to develop supporting materials.
Each of these is a simulation that involves students working in teams to get clues from the computer, deciding as a group on their next move, and then working again as a team to analyze the results of their decision and to plan their next action. The simulations are supported and extended by still clips, videos, and print materials.
5. Educational Games
Games are a large category of software, as can be seen from a quick look through any software outlet. Most games fall into one of two categories: action games that rely mostly on hand-eye coordination, and drill games that resemble automated flashcards with fancy scoring mechanisms and rewards. Some of the most well-known action games are the good old Pacman (and all its variations), Tetris (which has an added component of geometrical skill involved), and Brick-Out (which requires some strategy as well as straight shooting). One of the most common drill games is Math Blaster, in which the user has to shoot down facts like 3 + 4 by quickly typing an answer. Some of these drill games are popular in schools, where teachers use them for drill and as a "reward" for students, suggesting their high motivational power.
One may sometimes have difficulty deciding when a piece of software is a simulation or tool and when it is a game. Many of the most interesting games - and in particular, those that show up most frequently in schools - are simulations. Some of the most well known of these, which are described in detail above as simulations, are Oregon Trail and SimCity. As mentioned above, the main differences between these game programs and ones that are "officially" considered simulations are the amount of connection to curriculum supplied with the software and the role of a scoring system and "winning." For example, the Search Series is different from Oregon Trail mainly in that the former is built around educational content specifically designed to connect with curricula, and the latter trades off curricular content for entertainment value.
Other kinds of games also have significant educational content. The popular Where in the World Is Carmen San Diego? (a game in which players try to find Carmen by following geographical clues around the world), for example, supports students' learning about geography. The Most Incredible Machine invites students to create Rube-Goldberg machines that can get the ball in the basket, start the motor, for instance, by combining a wide variety of objects, gears, pulleys, etc.; this game supports students' general problem-solving and elementary physics abilities. A new game, The Incredible Logical Journey of the Zoombinis, creates a fantasy world in which students need to use reasoning in discrete mathematics to get a band of characters to Zoombini Town safely. The very popular Myst uses elegant video and sound to enhance a challenging adventure-type game that requires problem solving and arcane thinking.
One might safely say that much more work has to be done in the arena of games. A predominance of violence in the subject matter and action of most games still exists, which makes them more appealing to boys than girls. Many game designers spend more time on flashy rewards than on educational content. There are few games that require knowledge of algebra, fractions and decimals, or biology, for example, pinpointing a need for substantial development in the future.
6. Cognitive Tools
Cognitive tools are a varied group of software that take advantage of the power of the computer to present "concrete" representations of abstract concepts. The main components of cognitive tools are an underlying numerical model that can be changed by the user and a visualization of the behavior of this model that is determined by "running" the model with the user's choices of values. In some cases, the user's goal is to match a particular behavior of the model by changing numerical settings in the model. In others, the user must match a particular goal state by manipulating the representation itself. The Shifty Lines software described above is an example of the second kind of tool; students explore the best fit regression line by moving a line around on a scatterplot. The coefficients of the line and a measure of the sum of squares are represented numerically on the screen and change as the line is moved. The students' goal is to find the line for which the sum of squares of the residuals is smallest then to explore how deleting individual points affects the least-squares line.
An example of a tool with which students try to match a goal action by changing variables is the Envisioning Machine, a program designed to portray a graphical, dynamic simulation of an expert mental model of velocity and acceleration. With this software, the user manipulates a Newtonian World shown on one half of the screen in which an object is represented with velocity and acceleration vectors. The other half of the screen is taken up with an Observable World which shows a motion as normally viewed. The goal of the user is to match an Observable World motion by setting the appropriate velocity and acceleration vectors in the Newtonian world.
Teasley and Roschelle (1993) analyze a long episode of collaboration between two 15-year- old boys trying to create the motion of a ball being thrown up into the air, slowing down, and then falling by the force of gravity. It was the first problem they had encountered in which the velocity and acceleration vectors pointed in opposite directions. Early in the collaboration, the two boys agreed that the velocity vector had to point up, and the acceleration vector point down. They disagreed, however, on how to figure out the lengths of the two vectors. Through their discussion of how to set the initial speed so that the ball reached the appropriate height, both boys significantly improved their understanding of the interaction of velocity and acceleration. A reading of the transcript demonstrates that neither could have completed the task as successfully alone.
This incident shows that, although software can be a critical catalyst for learning, inquiry relies on more than just software. If each of the boys had worked alone on the same problem, they both would have learned much less. The conversation between them and their teacher's guidance in choosing the problem and making carefully chosen comments as they worked allowed the potential of the software to be realized. Software designers who understand these dynamics design their tools to support collaboration by including such elements as runnable models and visible goals.
Many cognitive tools also make use of linked representations, such as the line and the coefficients in Shifty Lines. We would normally expect the line to change when the user defined new coefficients. In this case, the opposite is true: the coefficients change when the line moves. This shift allows students to experience the concept of least-squares fit from a visual perspective and to carry out "what-if" experiments by direct manipulation of a graph.
These ideas are part of a software design movement that gives growing prevalence and importance to multiple linked representations. The growth of this kind of representation is due to both theories of multiple intelligences put forth by Howard Gardner (1983) and observations of students learning with such tools. The idea is that many concepts, particularly in mathematics, have representations in different modalities, pictorial, symbolic, numerical, graphical. The relationships among these representations are an important kernel of the knowledge students need to gain about the underlying concepts, as in mathematics, for example. In mathematics programs that use multiple linked representations, a parabola might be represented in an animation, an equation that specifies slope and intercept, a table of points, and a graph; but, if the student changes one of these, all the others will change in response. This introduces new task possibilities, such as "Change the slope and intercept of a line to get a certain table of points" or "Change the animation vectors to get a certain graph of a character's speed." Even though multiple linked representations are especially common in cognitive tools, they are becoming increasingly common in tools and games, because they provide effective support for inquiry in two ways. They provide the multiple paths to understanding that we know work for different students and make accessible the relationship between representations that foster the understanding of many scientific domains.
7. Intelligent Tutors: Sources of Scaffolding
Scaffolding is an educational term that reflects the physical object for which it is named. Scaffolding is a temporary support system provided by a teacher to help students accomplish a complex task. As the student becomes more accomplished, the scaffolding "fades," just as scaffolding on a building is taken down once the construction is complete. Scaffolding can be as simple as a teacher helping students do complex computational problems in steps and keeping track of the results for them. A more complex scaffolding might involve setting out a specific strategy for completing a research task. In both cases, the student will eventually have to do the task alone, and it is the teacher's job to withdraw his or her support as the student is able to work independently or with other students.
For years, artificial intelligence researchers who have tried to make computers "smarter" have dreamed of developing intelligent tutors that could scaffold students' learning, providing help just when it was needed. To accomplish this, such a system would understand students' answers, figure out what they understand and where they are having trouble, and decide what problem to pose next and what advice to offer, all without a scowl or recrimination: in short, serve as the "perfect" teacher. One argument that has been made in favor of such intelligent tutors is that this use of technology would give students individual attention in subjects in which there may not be enough teachers to go around.
Ideally, an intelligent tutor includes the knowledge that experts have in a domain (e.g., geometry), the ability to use and explain this knowledge, the tutoring ability that guides when and how to interact with the student, and some ability to understand what the student does and does not understand at a particular moment. These systems are often based on research that seeks to find the relationship between the rules that novices use and those that experts use. Designers then develop the software to help students acquire the rules they might be missing - and the strategy to use them.
The first program in the intelligent tutor style was Buggy (Brown & Burton, 1978), which could find patterns in errors students made in subtraction and was seen primarily as a way for teachers to learn how to do this kind of pattern search on their own. Since then, several topics have been popular subjects for intelligent tutor production: math (especially geometry and algebra), computer programming, and adult industrial training such as electronics testing (Lesgold et al., 1989). An example of such software is that of Anderson, who has written several tutors for high school geometry proofs. The figure below illustrates the way these tutors may be set up (Lajoie & Derry, 1993).
In this case, the given information that two triangles are congruent, that two line segments are congruent, and that two angles are congruent are all given on the bottom of the screen. The goal and a diagram of the givens are shown at the top. Suppose the student does not know what to do at this point in the proof. The intelligent tutor can give a hint, based on its understanding of the structure of the proof. In this case, the tutor might "realize" that the student needs to prove that triangles ACD and XWZ (the large ones) are congruent in order to show that angles ADC and SWZ are congruent and, as a result, that angles ADB and XWY are congruent. The first hint this tutor would offer is "Find proven part statements of triangles ACD and XWZ and use them to justify the congruence." If the student still had trouble, he or she could get the next hint: "Justify the congruence of triangles ACD and XWZ using the statements AC is congruent to XZ, DC is congruent to WZ, and angle DCA is congruent to angle WZX." If a student is unable to follow even the most directive hint, he or she may be told to ask the teacher for help (Koedinger & Anderson, 1989, 1990).
The scaffolding that such programs offer aims to provide students with more opportunity for inquiry by helping them to move ahead over potential sticking points and by managing some of the attention-draining details of complex problems. In some content areas, this strategy can work; in particular, well-defined, well-structured areas of knowledge, in which not only the knowledge but how to apply it, can be expressed in terms of rules. The geometry proof example above is well-suited, because both the geometry proof rules and strategies for applying them are easily coded in deterministic sequences. A danger, though, is that the program manages just those aspects of the task that are the heart of inquiry: deciding on the next step to pursue, ordering steps, exploring alternate inquiry paths. After all, doing proofs does at some level require planning the approach. In addition, more loosely defined subject areas, such as constructing appropriate representations for data, researching and describing the plight of Native Americans in the 1600s, or writing a communicative, persuasive letter, do not fit as well into an intelligent tutor structure.
Thus, the vision of intelligent tutors appears to be only partly fulfilled. As these systems have become more sophisticated, the gap between their knowledge of the subject matter (which can be quite good) and their effectiveness as teachers (which typically leaves much to be desired) has become increasingly apparent (Lepper et al., 1990). The original intent of providing computer-based scaffolding has merit, but it may have more potential when viewed as adjuncts to tools (as in the Tabletop example given earlier) that facilitate discussion among students and teachers.
8. Construction Environments
"Constructionism" is an educational philosophy that is an extension of constructivism; constructionism adds to the picture of learning an emphasis on students creating just about anything - stories, physical structures, computer games, drawings - with appropriate tools that require significant thought. As a theory of learning, it based on the belief that students learn best when they are designing and constructing objects (including computer procedures) of their own imagination and desire. The most famous example of environments in which students learn through creating their own objects is LOGO, a programming language created in the 1960s and championed by Seymour Papert (1993). LOGO and the companion Lego/LOGO (in which Lego toys are controlled through a special cable connected to a computer running LOGO) can be catalysts for experiences in which students learn mathematics, simple machines, gear principles, etc. However, when it was first introduced, LOGO tended to be used in situations with little guidance from a teacher. Unfortunately, this misunderstanding about how LOGO should be used led to experiences in which its educational potential was seldom realized.
Today, LOGO tends to be used in more directed settings, so that students' exploratory behavior is more likely to be guided. One LOGO application that contains considerable curriculum support can be found in the Investigations math curriculum, where a special version of LOGO called Geo-LOGO forms the basis for two-dimensional geometry units in Grades 3 through 5. These units approach traditional content in a nontraditional way. In third and fourth grades, students learn about rectangles through using LOGO to draw rectangles of different shapes, sizes, and orientations. Rather than memorizing a definition of the word "rectangle," they discover properties of rectangles by programming the computer to draw them.
The fact that opposite sides of a rectangle are the same length comes to life when one has had to figure out that if one side is drawn by FORWARD 30 (a command that draws a line 30 units long), the opposite side must have the same command (or the equivalent, e.g., FORWARD 15, FORWARD 15).
Another variation quickly gaining in popularity are MUDs (Multi-User Domains) and MOOs (Multi-User Domains with Object Orientation). These odd names refer to gaming environments that are built collaboratively over networks. A game grows by players adding interconnecting rooms constructed with tools that come with the game. Each player can also construct his or her own identity for a particular game, choosing an age, physical characteristics and possessions. To play, a participant visits rooms, asks questions about objects, picks up objects (if allowed by their creator), and possibly solves riddles. Sometimes passage to another room depends on the player having a certain collection of objects. To build a room, a player must use a kind of programming language to specify the appearance and behavior of objects in the room. These environments are more often than not used outside school, but the kind of building that they require of players is a sophisticated skill that could easily be harnessed in school.
MUDs and MOOs are not only construction environments; they are also communication environments. Much of the thrill for the player lies in watching other people maneuver through his or her room and trying to solve other people's riddles. The kind of communication that happens over networks in these games is one example of a much more widespread class of software that support connections between people over distance.
9. Virtual Communities
Ever since the Internet became available to the general public just a few years ago, its connections have hummed with personal, business, and educational messages. The World Wide Web, which carries pictures, sound, and videos along with text, has expanded the kinds of communication that can occur. There are many educational innovations that take advantage of these developments. I discuss them here in two groups: innovations that are primarily about communicating text and those that focus on sharing data. Of course, there are examples that involve both text and data as well as examples such as MUDs, that center on sharing constructions. Because about anything (that isn't too big) can be shared over the World Wide Web or the Internet, there could be many more categories, but these two foci are useful because they support a useful grouping and comparison of software.
Sharing Text: Communication Environments
Computers have been providing and supporting enriched communication environments for a considerable time. In the early 1980s, when word processors on microcomputers were beginning to appear in schools, the ease with which students could edit and publish their work made their writing more authentic. Educators realized that by using word processors their students could write with real purpose to a real audience, making the experience more genuine and engaging both writer and reader in a richer process. Current educators sometimes talk about "electronic communities" in which a common interest or project or both unites a set of geographically dispersed participants in a generative communicative structure.
The QUILL software (Bruce & Rubin, 1993) was a set of writing tools and environments developed in 1982-84. It included a library environment where students could share their writing with others, a mail environment which was a primitive e-mail system, and a planning tool in which students could construct and use planners that helped them organize their writing. The software was used in the context of curriculum influenced by the Bay Area Writing Project, which focused on the writing process and writing conferences. In line with the writing process emphasis, many QUILL classrooms published class newspapers, literary journals, or poetry collections. One school in a small village in Alaska even published a calendar that included the birthdays of every resident in the town, decorative drawings by the school children, and stories in both English and Athabascan. A not-surprising result of the QUILL field test: QUILL's success in fostering improvement in students' writing was related most closely to how well the suggested curriculum was implemented. Teachers who stuck to a more traditional approach to writing that emphasized grammar and allowed little opportunity for revision saw fewer gains in their students' writing.
Today, the opportunity for technologically enhanced communication environments is orders of magnitude greater than it was 10 years ago. The Internet and the World Wide Web provide potential audiences all over the world, across cultures and continents. But it has taken a while to get the social structure right. In the early days of using the Internet in education, teachers often set up pen pals for their classes in other states or countries. However, people soon discovered that the pen pal mode did not always work out well. There were never the right number of students in the two classrooms for a student-to-student match, and after the initial exchange of information, students often had nothing to talk about. Since then, other communication models have been developed. A common one is a centrally organized project uniting a small cluster of classrooms into an activity that gives focus and purpose to their communication. For example, AT&T Learning Circles (Riel, 1995) pull together a group of classrooms into a several months' long project, such as producing a collaborative newspaper. An editorial team for each page is composed of students from all four classrooms; they use the network to submit and discuss articles, respond to submissions by other authors, and lay out pages. The final product is interesting to all participating classrooms because it contains articles on local activities they recognize and articles about the other schools and students they have been getting to know. Notice how the success of such an activity depends as much on the social organization of the writing process within and across classrooms as it does on the software per se. It is also interesting to note that these kinds of computer uses - in which communication and writing are at the center - are some of the most popular with girls. The use of computers to start and develop interpersonal relationships is one that girls find particularly appealing (as do many boys).
Another social structure that works well is a "virtual forum," in which interested students share information through electronic mail or a bulletin board on a topic of mutual interest. If these bulletin boards are organized through a project, there may be experts - scientists, mathematicians, writers, artists, for example - involved, so that students can discuss their questions and share their work with adults who work in the profession. Such a connection with real-world audiences not only adds legitimacy to students' work, but also provides them with role models of people who use the skills students are developing in their daily work.
An active area of work right now is the attempt to include parents in these networked- based communications environments. Some of the more pedestrian uses of such an environment would be to keep parents informed of their students' homework assignments and attendance. But more interesting applications might be to involve parents in the same kinds of inquiry students are pursuing; that is, contributing to a history of the town or to a discussion of water quality issues. The more people in a community (network based or not) who are practiced at inquiry, the more it will be valued and supported.
Networking as Data Communication
Many educators have seen networks as important tools in providing more meaning for data collection. If values for data differ according to geography, then disseminated data collection and sharing allow students to discover interesting contrasts that they would not otherwise be able to see. National Geographic Kids Network® is one of the first and best-known examples of using networks to communicate data; it links students all over the United States and in a number of foreign countries to work collaboratively on science projects. In each project, students collect data and send them to a central source where they are combined with other data; the larger data set is then sent back to each school. The first two units of the Kids Network curriculum are Hello! (an introductory unit in which students share information about their pets) and Acid Rain (a science unit in which students collect, collate, and compare data about the acid content of water sources in their community). Other units examine weather, trash, solar energy, and nutrition. An evaluation of this curriculum-technology combination showed that students gained in their ability to organize, represent, and interpret data. They also gained in specific content areas related to their associating data with different locations, e.g., the ability to use latitude and longitude.
Global Lab is a project in which schools are connected worldwide to study and compare environmental data. This network also includes several earth scientists who consult on projects and on the interpretation of data. The GLOBE project (Global Learning and Observations to Benefit the Environment) is a similar endeavor that hopes to link students in more than 2,000 schools around the world in studying the earth's environment. Projects such as these are often called "telecollaborations" because they allow people to use telecommunications to collaborate across space and time. With appropriate curriculum and teacher support, these projects can support and extend inquiry by providing data, tools, experts, and audiences for student's scientific exploration.
10. Information Access Environments
The Internet, the World Wide Web, and a quickly growing number of reference CD-ROMs (e.g., Encarta and Compton's Encyclopedia) have provided students with seemingly infinite access to information and expertise. Some of the most zealous technophiles make the argument that because information is growing exponentially and teachers cannot know everything, connecting students to the primary sources of information is necessary for their education. Access to the resources of the Internet and the World Wide Web is one of the major arguments given for adding technology to schools.
Unfortunately, giving students unstructured access to the Internet is similar to letting them loose in the library - a lot more pedagogical structure is necessary for learning to happen. In the worst case, students can copy from the network into an online homework report; here the technology has simply made that process much easier than copying from a traditional encyclopedia ever was. Yet, we have all seen students who are excited by the ease of access in online environments, and by the video and audio that accompany many entries. The challenge is to turn this motivation into real learning to avoid burn-out through lack of content.
The educational structures that make the best use of these new resources are project-based learning, in which students are engaged in collaborative research they have helped to define. In these cases, students can use the Internet's information tools in the context of a larger goal, so that deciding which resources to use, how to find them, and what information to extract are all related to a project. In the context of such projects, the Internet also provides electronic communities in which scientists, historians, mathematicians, and others are willing to answer students' questions through programs such as Ask A Scientist and Ask a Mathematician to which schools can subscribe.
One problem that arises when students use network connections for research is that a text document is seldom the most appropriate structure for them to express their results. If they find drawings, pictures, or videos to support their statements, they will naturally want to include them. Several multimedia document programs for use in schools have appeared in the last few years (e.g., Mediatext and Hyperstudio), and they are bound to become more widespread as access to the Internet's multimedia resources continues to grow. Besides supporting the construction of multimedia documents, some of these tools allow students to put together hypertext documents in which each reader can read different parts of the document, according to interest, by following particular links. These uses are closely connected to the next category, information construction.
11. Information Construction
A focus on information construction comes from seeing students as constructors of their own knowledge, rather than as consumers of other people's knowledge. This category embraces a range of applications, from the use of a computer to make interactive multimedia reports to having students in a classroom create their own "encyclopedia": a classroom knowledge base recorded on the computer. The most well-known example of the latter approach is the Computer-Supported Intentional Learning Environments (CSILE) system (Scardamalia, 1989). In a CSILE classroom, one of students' main activities is using software that prompts them for ideas, facts, implications, for example, then for connections to other students' contributions. Embedded in the software are tools that help students structure and record their questions, approach, and results. In particular, students are asked to label the pieces of information (called "nodes") they enter as "problem," "my theory," or "new information." These labels help them notice, understand, and use the structure of an argument in building their collaborative database. This software differs from existing data sources (e.g., the Web) in that students create their own materials. Consequently, there is no temptation on students' parts to merely copy what they have read.
CSILE is a prime example of software whose use must be supported by the curriculum and the teacher. At first, students do not understand how to build their own knowledge base, nor do they distinguish between the various labels. The first weeks and months of using CSILE must be carefully scaffolded by the teacher so that the classroom database and the students' knowledge grow together.
12. Computer-Assisted Instruction and Integrated Learning Systems
Computer-assisted instruction and integrated learning systems were some of the earliest applications of computers to education. CAI's roots are in behaviorist theory and programmed instruction; it delivers drill-and-practice exercises on basic skills and immediate feedback on student performance, combined with either a teacher- or computer-delivered lesson on the topic. Because computers can hold large numbers of problems and can execute the simple logic for deciding on the next question, some CAI programs individualize instruction for each student. From a CAI perspective, students are seen as consumers of "facts" that can be delivered by machine as well as by teachers.
Because the content and format of CAI (with multiple choice, true/false, or fill-in-the- blank questions) is so similar to that found in standardized tests, studies of CAI often show student gains, especially if students have had frequent exposure to focused CAI over at least a semester to a year. However, there is less information about the effect of these CAI experiences on the development of other skills and understandings that new assessments are targeting. Because CAI is not designed to support inquiry activities, it would be inappropriate to measure its effect with performance-based assessment tools.
There are some additional concerns about CAI software. This kind of program is referred to as "drill and practice," but it is often colloquially called "drill and kill." Why? Because repeating a set of problems by rote may contribute little to students' intellectual development; in fact, it has the potential to kill their interest in the topic in question. Their engagement is often based on special effects rather than intellectual involvement. Their activity does not contribute to their ability to analyze more complex problems. For example, middle school students who had long before mastered simple addition and multiplication facts have been observed in their free time playing Math Blaster, answering questions far below their mathematical level, just for the sense of simple success and for the special effects.
Note that some CAI programs are marketed to homes as well as schools. Typing Tutor and Math Blaster are two that are frequently seen in students' homes. Catalogues are full of Math Blaster look-alikes that drill students on basic arithmetic. Parents even buy these for their children, thinking the software will help them in school. It is often hard to dissuade parents from doing this, because the software looks exactly like the tests parents remember from school - they are not aware of the changes in education encouraged by such movements as the NCTM standards for mathematics.
Integrated learning systems include both courseware and management software and run on networked hardware. They cover one or more curriculum areas across grade ranges, and usually include a management program that tracks and reports student progress. The more traditional integrated learning systems are in fact collections of drill and practice sequences in various areas and skill levels, similar to the CAI programs discussed above. Some of them are adaptive; that is, they present students with problems of differing difficulty depending on how well they have done on previous problems (Van Dusen & Worthen, 1995).
More recently, integrated learning systems have begun to add materials that require students to solve more complex problems that foster deep reflection and genuine understanding. Such integrated learning systems typically include software such as science simulations, as well as tools such as word processing programs, spreadsheets, graphing packages, and encyclopedias. These integrated learning systems are moving away from the traditional definition of computers as machines that offer the opportunity for programmed instruction and management and toward seeing the computer as a set of tools. Two major differences, however, between an ILS and a set of tools are that an ILS includes a highly structured and relatively inflexible curriculum and that it usually runs on dedicated hardware and thus may preclude any additional uses of the computers.
Although integrated learning systems are designed to have students work independently, teachers need to integrate ILS work with classroom activities for these systems to have a maximum effect on student learning. Integration with classroom activities can require considerable creativity in the ILS scenario. Even though the ILS is capable of "individualized" instruction, letting students function at different grade levels at the same time, teachers still have to deal with their students being at different levels in noncomputer class time. In fact, because students have been working on totally different problems during ILS time, whole class activities can be even more of a challenge than they might be otherwise. Teachers have to make use of the same kinds of techniques that are necessary in a classroom without computers - small group work and teachers working as facilitators and coaches rather than lecturers. Therefore, even in a computer-intensive, highly structured environment, we see one more example of theme: student learning depends on teachers and curriculum at least as much as on the hardware and software.
The following succinct conclusion about CAI and ILS comes from Jones et al. (1995, under review):
Closed electronic models such as the typical CAI and ILS that support traditional learner goals, curriculum, instruction, and assessment are fundamentally not much improved over the traditional models. New research on learning is saying that traditional models of learning and schooling, like dinosaurs, are not adaptive to the needs of modern society. To the extent these technologies support traditional teaching and learning, they are misaligned with educational reform and the needs of the 21st century. (p. 10)
A Final Note: Computers in Multicultural Education
Unfortunately, all these resources are not equally distributed. Equity is a problem everywhere we look in education as it relates to technology: students of lower-income families have less access to technology in school and often use it in more constrained ways; girls lag behind boys in math, science, and technology; students of color in primarily inner city schools are less likely to have access to computers outside school. In fact, access to information may become the new definition of educational equity (Office of Technology Assessment, 1995b). Computers are a double-edged sword in equity matters: they can be a new way for some students to have a voice and find expression for their talents, or they can add to the growing distance between the haves and have-nots.
In school, poor and minority students tend to use computers in less independent ways than upper middle-class white students, with ILS and CAI uses being more common than the tool- based approaches more affluent students enjoy. Being female is a disadvantage in either case; girls do not use computers as much either in or outside school, and their parents, when they do buy computers, often buy different kinds of software for their daughters than they do for their sons (Carol Edwards, personal communication, December 1995).
But there are several hopeful stories. The National Foundation for the Improvement of Education (1995) provided fellowships to several teachers who were interested in using computers in the service of multicultural education in classrooms that were inner city, primarily nonwhite students. Here are adapted excerpts from the story of one of those teachers:
Hazel Lockett teaches English at an urban junior high in East Orange, New Jersey. Her junior high has been designated an arts and music school. Most students are black, but more than a quarter of them were foreign born, from the Caribbean, Central America, South America, and Africa.
Ms. Lockett is convinced that the cultural differences among her students significantly affect how they learn. In particular, she noted that some of her students "want to blend in with the background when called on." She worked in her class to find ways to bring out these quiet students. Her main tools were expressive writing and the power of literature.
For her project, Ms. Lockett used Hyperstudio. She designed a project for a group of 20 students based on Kindred, a science fiction novel by Octavia Butler that tells the story of an interracial couple time-traveling to the South of 1850. Using Hyperstudio, students created a multimedia stack to illustrate the novel's themes around gender, race, power, and authority and to offer a resource for multicultural education for future seventh and eighth graders.
Ms. Lockett observed a marked change in the patterns of interaction among her students, both in and outside class. Racist jokes were less common and cooperation grew. Formerly quiet students found their voice and some grew significantly in self-confidence. She noted that the increased technological competence students felt helped them believe in their ability to learn.
She felt that the technology itself was helpful to several students who were not outspoken or came from cultures with different attitudes about oral speech. Oral class participation is a conventional avenue to success in American schools, but it is especially difficult for some students. Technology makes it possible to create a new classroom culture and new avenues of communication that are unlike either oral discussion or traditional kinds of written work.
The NFIE program is just a beginning, but it does point to some ways technology may be able to enhance multicultural education and give students who have less rich access to computers a chance to feel that computers are tools that they, too, can use in powerful ways.
IMPLICATIONS FOR STUDENT ASSESSMENT
The use of computers in student assessment is a large topic in and of itself. As performance assessment - which evaluates students based on the actual work they are doing in schools, rather than a specially designed test - becomes mode widely adopted, technology will become more important in supporting it. Sheingold and Frederiksen (1994) note five functions of technology that support new kinds of assessment and link them with educational reform:
- Supporting students' work in extended, authentic learning activities
- Creating portable, accessible copies of performances and replaying performances in multiple media
- Providing libraries of examples and interpretive tools
- Expanding the community of assessment participants
- Publishing selected student work and thus recognizing their accomplishments.
IMPLICATIONS FOR TEACHERS: TOOLS AND PROFESSIONAL DEVELOPMENT
Teachers are more likely to use computers effectively in their classrooms if they feel they are useful tools for their own work. Certainly, there are many ways in which teachers can use basic tools such as work processors, spreadsheets, drawing programs for their own purposes, both in and outside school. Spreadsheets are useful for record-keeping; word processors for everything from writing letters to parents to preparing materials for students. Using computer tools themselves allows teachers to realize the power of computers to serve their own needs and to become personally invested in their use.
Such straightforward uses can also grow into more dynamic classroom uses. Math teachers, for example, may start by preparing text materials with a word processor, but eventually they will want to write equations or draw graphs. They may begin to use symbol processors or graphing programs, just for the output. But it is impossible to use these kinds of tools without noticing how powerful they are; soon some teachers will see the tools' potential and move toward using them in more robust ways with their students.
The importance of allowing teachers access, time, and opportunity to make computers their own tools is emphasized by Chris Dede (in O'Neil, 1995):
One of the mistakes that we made in implementing educational technology was focusing first on students rather than teachers, because when the computers on students' desks are mysterious devices to teachers, it's unreasonable to expect effective integration into the curriculum.
The role of technology in professional development - whether or not technology is part of the school change - is growing as more teachers have access to Internet connections. Grant discusses this topic in detail; her paper deals with multiple ways technology can support professional development for teachers, including via distance learning, using videos to expand the realm of observation, creating electronic communities of learners, and supporting teachers' daily activities (see Professional Development in a Technological Age).
This paper suggests that there are many ways that technology can support inquiry-based learning. The richness, flexibility, and power of computers and their attendant technological kin offer valuable tools to support this approach to teaching and learning. However, as the paper makes clear, the most powerful variables are the teacher and the overall curricular goals of the school. Technology is only as powerful as the way it is used. The choice is up to the educators.
Berenfeld, B. (1996, April). Linking students to the infosphere. Technological Horizons in Education Journal, 23(9), 76-83.
Brown, J. S., & Burton, R. R. (1978). Diagnostic models for procedural bugs in basic mathematical skills. Cognitive Science, 2, 155-192.
Bruce, B. C., & Rubin, A. (1993). Electronic quills: A situated evaluation of using computers for writing in classrooms. Hillsdale, NJ: Lawrence Erlbaum Associates.
Edwards, C., National Foundation for the Improvement of Education. (1995, December). Personal communication.
Epie Institute. (1991). The latest and best of TESS, The educational software selector, 1991 Edition. Hampton Bays, New York: Author.
Gardner, H. (1983). Frames of mind. New York: Basic Books.
Herman, J. L. (1994). Evaluating the effects of technology in school reform. In B. Means (Ed.), Technology and education reform. San Francisco: Jossey-Bass.
Horwitz, P., & Barowy, W. (1994). Designing and using open-ended software to promote conceptual change. Journal of Science Education and Technology, 3(3).
Jones, B. F. et al. (1995). Plugging in: Choosing and using educational technology. Washington, DC: Council for Educational Development and Research, North Central Regional Educational Laboratory.
Koedinger, K. R., & Anderson, J. R. (1989). Perceptual chunks in geometry problem solving: A challenge to theories of skill acquisition. In Proceedings of the Eleventh Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Lawrence Erlbaum Associates.
Koedinger, K. R., & Anderson, J. R. (1990). Abstract planning and perceptual chunks: Elements of expertise in geometry. Cognitive Science, 14, 511-550.
Lajoie, S. P., & Derry, S. J. (1993). Computers as cognitive tools. Hillsdale, NJ: Lawrence Erlbaum Associates.
Lepper, M. R. et al. (1990). Self-perception and social-perception processes in tutoring: Subtle social control strategies of expert tutors. In J. M. Olson & M. P. Zanna (Eds.), Self-interference processes: The Ontario symposium (pp. 217-237). Hillsdale, NJ: Lawrence Erlbaum Associates.
Lesgold, A. M. et al. (1989). An intelligent tutoring system for electronics troubleshooting: DC-circuit understanding. In L. Resnick (Ed.), Knowing and learning: Issues for the cognitive psychology of instruction. Hillsdale, NJ: Lawrence Erlbaum Associates.
Michaels, S. (1990, Autumn). The computer as a dependent variable. In D. G. Lux (Ed.), Theory into Practice, 29(4).
Mokros, J. et al. (1994). Assessment of investigations in number, data, and space. [Unpublished manuscript]. Cambridge, MA: TERC.
National Foundation for the Improvement of Education (1995). Touching the future. [Annual report].
Nickerson, R. S. (1988). Technology in education in 2020: Thinking about the not-distant future. In R. S. Nickerson & P. P. Zodhiates (Eds.), Technology in education: Looking toward 2020. Hillsdale, NJ: Lawrence Erlbaum Associates.
O'Neil, J. (1995). On technology and schools: A conversation with Chris Dede. Educational Leadership, 53(2). Alexandria, VA: Association for Supervision and Curriculum Development.
Office of Technology Assessment (U.S. Congress). (1995a). Future visions: Education and technology. OTA-BP-169. Washington, DC: U.S. Government Printing Office.
Office of Technology Assessment (U.S. Congress). (1995b). Teachers and technology: Making the connection. OTA-EHR-616. Washington, DC: U.S. Government Printing Office.
Papert, S. (1993). The children's machine: Rethinking school in the age of the computer. New York: Basic Books.
Riel, M. (1995). The future of teaching. In Office of Technology Assessment (U.S. Congress). (1995a). Future visions: Education and technology. OTA-BP-169. Washington, DC: U.S. Government Printing Office.
Rosebery, A. S., & Rubin, A. (1989). Reasoning under uncertainty: Developing statistical reasoning. Journal of Mathematical Behavior, 8(2), 205-219. Norwood, NJ: Ablex Publishing.
Rubin, A. (1993, May). Video laboratories: Tools for scientific investigation. Communications of the ACM, 36(5).
Scardamalia, M. et al. (1989). Computer-supported intentional learning environments. Journal of Educational Computing Research, 5(1), 51-68.
Sheingold, K., & Frederiksen, J. (1994). Using technology to support innovative assessment. In B. Means (Ed.), Technology and education reform. San Francisco: Jossey-Bass.
Teasley, S. D., & Roschelle, J. (1993). Communication and collaboration: The role of talk in children's peer collaborations. In S. P. Lajoie & S. J. Derry (Eds.), Computers as cognitive tools. Hillsdale, NJ: Lawrence Erlbaum Associates.
Van Dusen, L. M., & Worthen, B. R. (1995, October). Can integrated instructional technology transform the classroom? Educational Leadership, 53(2). Alexandria, VA: Association for Supervision and Curriculum Development.
Walters, J., & Gardner, H. (1990). The development of education of intelligences. In F. Link (Ed.), Yearbook on intellectual development. Washington, DC: Curriculum Development Associates.
Wilson & Tally. (1991). Designing for discovery: Interactive multimedia learning environments at Bank Street College. In B. Means & K. Olson (Eds.), Technology's role in education reform: Findings from a national study of innovating schools. Washington, DC: Office of Educational Research and Improvement, U.S. Department of Education.
Dewey, J. (1916). Democracy and education: An introduction to the philosophy of education. New York: Macmillan.
Means, B., & Olson, K. (1995). Technology's role in education reform: Findings from a national study of innovating schools. Washington, DC: Office of Educational Research and Improvement, U.S. Department of Education.
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books.
Roschelle, J. (1986). The envisioning machine: Facilitating students' reconceptualization of motion. In S. P. Lajoie & S. J. Derry (Eds.), Computers as cognitive tools. Hillsdale, NJ: Lawrence Erlbaum Associates.
Rubin, A. (1991). Using computers in teaching statistical analysis: A double-edged sword. In K. Sheingold, L. G. Roberts, & S. M. Malcom (Eds.), Technology for teaching and learning. Washington, DC: American Association for the Advancement of Science.
Ruopp, R., Gal, S., Drayton, B., & Pfister, M. (1993). LabNet: Toward a community of practice. Hillsdale, NJ: Lawrence Erlbaum Associates.
Russell, S. J., Corwin, R., Mokros, J. R., & Kapisovsky, P. M. (1989). Beyond drill and practice: Expanding the computer mainstream. Reston, VA: The Council for Exceptional Children.
Van Dusen, L. M., & Worthen, B. R. (1992). Factors that facilitate or impede implementation of integrated learning systems. Educational Technology, 32 (9), 16-21.
Weir, S. (1992, January). Electronic communities of learners: Fact or fiction. Cambridge, MA: TERC.
Comments are visible to UTeachEng members only.