Problem-based multimedia software for middle grades science: development issues and an initial field study.

Recent advances both in the understanding of how students' learn (e.g., Bransford, Brown, & Cocking, 1999) and in formation technology have allowed several researchers to develop multimedia-based science instructional environments for students (Linn, 1998). This study reports on some of the design issues and a field test of one such research and development project. The design of the materials tested is based on the concepts of "anchored instruction" (Bransford, Sherwood, Hasselbring, Kinzer, & Williams, 1990; Cognition and Technology Group at Vanderbilt (CTGV), 1993a) and "flexibly adaptive instructional design" (Schwartz, Brophy, Lin, & Bransford, 1999a; Schwartz, Lin, Brophy, & Bransford, 1999b).

The instructional software used in the study was developed using video materials from a previous anchored instruction project that were then integrated into a Star.Legacy (Schwartz et al., 1999a, 1999b) software shell. Fifth grade students used the materials in small groups with each group working independently. Measurement instruments included a pretest and immediate and delayed posttests as well as classroom observations and student artifacts. Statistical analysis showed that students improved from pretest to both posttests with growth especially seen in two major conceptual areas. Thc study provides evidence of successful use of the STAR.Legacy software with younger children and provides directions for future study.

**********

Recent advances both in the understanding of how students' learn (Bransford, Brown, & Cocking, 1999) and information technologies have allowed several researchers to develop multimedia based science instructional environments for students (Linn, 1998). This study reports on some of the design issues and a field test of one such research and development project. Originally funded by the National Science Foundation (NSF), "The Scientists in Action (SIA) Series: A Generative Approach to Authentic Scientific Inquiry" project (ESI-93505 10) had as its initial objective to develop and test a set of four video-based "adventures" similar to previous work conducted in the area of middle grades mathematics (The Adventures of Jasper Woodbury, CTGV, 1993b). A detailed discussion of the development efforts and initial research studies may be found in the NSF final report (Sherwood. 2000) but a summary is provided for background.

Anchored Instruction

The main design approach used in the initial stages of the project was based on the idea of Anchored Instruction (Bransford et al., 1990, CTGV, 1993a). The anchored instruction approach represents an attempt to help students become actively engaged in learning by situating or anchoring instruction in interesting and realistic problem solving environments. Ideally, instruction could always take place in real world contexts. For example, it would be ideal if students learning to monitor the quality of rivers had easy access to rivers and could learn about them in that context. Often this is not possible. In many areas, schools have to hire a bus for a trip and can afford to go to the river only once a year. The realities of schooling would indicate a need to simulate such environments.

The simulated environments that have been developed under this approach have been designed to invite the kinds of thinking that helps students develop general skills and attitudes that contribute to effective problem-solving, in addition to acquiring specific concepts and principles that allow them to think effectively about particular domains (CTGV, 1992a, CTGV, 1990). Anchored instruction environments, like inquiry environments, do not propose to "directly" instruct students but provide a situation where learning can take place (Schwab, 1978). In many cases, anchored instruction environments have involved a progression from simulated "problem-based learning" to real life "project-based learning" (Barron, Schwartz, Vye, Moore, Petrosino, Zech, Bransford, & CTGV, 1998). For example, students may first work on a simulation of water quality (problem-based learning) and then go to an actual river as a capstone activity (project-based learning).

Anchored instruction also reflects constructivist theories (Bransford & Vye, 1989; Clement, 1982; Duffy & Bednar, 1991; Minstrell, 1989; Perkins, 1991; Scardamalia & Bereiter, 1991; Schoenfeld, 1989). According to a constructivist perspective, knowledge is actively constructed by learners through interaction with their physical and social environments and through the reorganization of their own mental structures (Cobb, Yackel, & Wood, 1992; Wheatley, 1991; Brown, Collins, & Duguid, 1989). Instead of having teachers "transmit" information that students then "receive," these theorists place a great amount of importance on having students become actively involved in the construction of knowledge. For instance, constructivist theorists want to assist students to construct and coordinate effective problem representations through the use of physical and symbolic models, through reasoning and argumentation, and through deliberate application of problem-solving strategies (Bransford & Stein, 1993; Brown, Collins & D uguid, 1989; Clement, 1982; Minstrell, 1989; Palinscar & Brown, 1984; Scardamalia & Bereiter, 1991; Schoenfeld, 1989). Anchored instruction is consistent with the assumption that constructivism is a theory of knowing rather than a theory of pedagogy. In any learning situation, the only recourse available to learners is to construct new knowledge based on current knowledge-this is true whether they listen to a lecture, read a text, or engage in hands-on inquiry (see Bransford et al., 1999; Schwartz & Bransford, 1998). Sometimes summary lectures are just what students need to move to a new level of understanding (Schwartz & Bransford, 1998). With high frequency, however, lectures, texts, and other attempts to help students learn by "telling" are ineffective because students are not prepared for the learning activities. Instead, they need opportunities to actively explore their own hunches, receive feedback, and modify their understanding as needed (CTGV, 1992b). Anchored instruction engages students in realisti c problem solving environments that allow them to make modifications to their current understanding.

More extended discussions of anchored instruction can be found in CTGV, 1990 and CTGV, 1992c. It is noted there that the general idea of anchored instruction has a long history and is related to ideas about project-based learning (Dewey, 1933), case-based learning (Gragg, 1940) and problem-based learning (Barrows, 1985; Williams, 1992). The use of anchors is also connected to the "situated cognition" arguments of Brown, Collins and Duguid 1989; Moore, Lin, Schwartz, Petrosino, Hickey, Campbell, Hmelo, and CTGV, 1994. Previous studies of anchored instruction have been conducted in a variety of domains including; literacy (Kinzer, Risko, Goodman, McLarty, & Carson, 1990; Kinzer, Risko, Vye, & Sherwood, 1988; Bransford, Kinzer, Risko, Rowe, & Vye, 1989); mathematics (CTGV, 1992a, 1993a, b, c), and science (CTGV, 1992c; Goldman, Petrosino, Sherwood, Garrison, Hickey, Bransford, & Pellegrino, 1996; Sherwood, Petrosino, Goldman, Garrison, Bransford, & Pellegrino, 1993; Sherwood, Petrosino, Lin, & GTGV, 1998). Some of the lessons learned about ways to increase the power of anchored instruction to produce flexible transfer are presented in Barron, Vye, Zech, Schwartz, Bransford, Goldman, Pellegrino, Morris, Garrison, and Kantor, 1995; CTGV, 1993a, 1994.

Flexibly Adaptive Instructional Design

Schwartz et al. (1999a, b), have put forward an argument for "flexibly adaptive instructional design" based upon the integration of four types of learning environments. These environments include:

1. Learner-centered environments that focus on knowledge, skills and attitudes that students bring to the learning situation.

2. Knowledge-centered environments that focus on knowledge that is organized around core concepts or big ideas that support subsequent learning in the disciplines.

3. Assessment-centered environments that help students' thinking to become visible so that both they and their teachers can assess and revise their understanding

4. Community-centered environments that capitalize on local settings to create a sense of collaboration-both among students and with other members of the community (1999a, p. 40, see also Bransford et al., 1999, p. 122).

They also noted that developing these kinds of instructional environments is a difficult task especially if they attend to each of the learning environments mentioned. They offered the argument that a software shell such as Star.Legacy (Schwartz et al., 1999a) promotes flexibly adaptive instructional design in two ways.

It helps teachers adapt complex curricula by including a model of inquiry that draws attention to each of the learning environments within a single software shell and that provides a framework for making pedagogically sound modification. It supports flexibility by including a suite of software tools that are simple to learn and use, and that make it easy to modify a given Star.Legacy. (p. 41).

This work, along with other studies (Vyc et al., 1998), influenced the developers of the original SIA materials to consider the revision of the materials into a Star.Legacy format. Using a slightly modified design from Schwartz et al. (1999a), a curricular unit was developed titled the "River of Life", which made use of the original video and text materials integrated into the Star.Legacy format. The original narrative video was broken into segments that are used to help student complete the challenges presented in the software. Text materials that had been part of student and teacher guides for the original videotapes were modified to fit within the Star.Legacy format and new materials, especially simulations, were developed to be part of the program.

The components of the resulting CD-ROM-based software will be described in more detail in later sections, but Figure 1 shows the introductory screen for the program. Students may choose either to "Meet the Legacy League," which is recommended when they first start the program or pick one of the three challenges represented by the numbered mountains at the top of the figure. The "Legacy League" is a group of "twenty-somethings" who have taken on the mission of trying to assist students to develop better attitudes toward learning and to provide them with strategies that might be helpful for the student to use as they tackle problems. The characters are designed to be meaningful to students in the middle grades, and are presented through stop animation with voice-over. Other episodes (under development) will also use the Legacy League characters.

FIELD STUDY

Study Participants

Permission was granted for the researchers to work with two classes of fifth grade students at a suburban elementary school in the Nashville, TN, area. The students were generally majority race students whose families could be described as middle class. Only two of the 42 students who used the materials were from ethnic minorities. The students were generally quite familiar with computers and needed little introduction to the general use of the software. Students were divided into groups of three students per computer and assigned a color code for their group and class (e.g. Yellow-1) resulting in seven groups in each classroom. Both Windows 95 [R] and Macintosh OS [R] computers were used by the various groups. Students stayed with one type of machine for the duration of the study.

Pretest

Before students were introduced to the software they were asked to complete a short (seven questions, 14 total points) pretest of multiple choice and written response questions that were designed to measure five areas of knowledge. The first area was to provide examples for the major classes of organisms that make up a river ecosystem (producers, consumers, decomposers) and what might be considered pollution in a river (two questions, seven points). Second, knowledge of what dissolved oxygen is and why it is important (one question, two points). Third, knowledge of what macroinvertebrates are and why they are important in studying river/stream pollution (one question, two points). Fourth, knowledge of what gas is the most abundant in air (one question, one point), and finally items to see if they could read simple line graphs (two questions, two points). Table 1 provides a summary of the pretest results.

Students were generally strong in being able to provide examples of general ecosystem components and pollution (65% correct) and had graph reading skills (87%) but had no prior knowledge of dissolved oxygen and macroinvertebrates and little knowledge of the fact that nitrogen is the most abundant gas in air (3%). Overall, students' correct responses were about at the 45% range. The results from the pretests were as might be expected. While general elements of ecosystems is a topic that is often taught in elementary science (and had been in both classes earlier in the year), knowledge about the role of dissolved oxygen and the indicator use of animals such as the macroinvertebrates is much less commonly studied. The results on the most abundant gas question were somewhat lower than expected but students' conceptions in this area are often incorrect (Posner, Strike, Hewson, & Gertzog, 1982).

Activities with Software

As has been mentioned, students were assigned to groups and these groups worked independently with the software. Before students moved to their computers a short discussion was presented by the classroom teacher or researcher about software problems, unclear wording, or other issues that might cause students problems as they worked through the software.

Figure 2 shows the main screen for the first of the three challenges presented in the software. The "Challenge Quest" is a video based presentation of a challenge that is organized around a "teachable agent," a character named "Billy Bashinal" who is a high school aged student. Billy and his lab partner, Suzie, are discussing the data they have collected on water quality for science class. Billy's attitude toward the project is "just do enough to get by" while Suzie is concerned about their conclusions. The Legacy League "detects" Billy's "bad learning vibes" and through "virtual reality" discusses with him some of his views on learning in general and some of the specifics in his report. They convince him that he has more work to do to cheek his conclusions. The video segment ends with a challenge to help Billy by learning about water quality and then "teaching" Billy.

Students proceed from the Challenge Quest phase to the "Generate Ideas" section, where they are asked to respond to some of the questions that are raised by the Legacy League to Billy. It is not expected that the students will have full or complete answers to the questions, but having them write their preliminary ideas allows them the opportunity to compare their initial ideas to their final answers. Students then have the opportunity to hear Legacy League characters present some "Multiple Perspectives" on some of the issues that are related to the challenge. These might be short "hints" such as "It takes awhile for changes in water quality to appear, make sure to look at data over several months," or interesting related questions such as, "Given how little oxygen is dissolved in water, could there be any water breathing mammals?"

Students then continue by going to the Research Resources component of the Legacy Cycle. This area is the one that students will spend the most time. It includes background information about the particular challenge, resources such as simulations, and weblinks. Several simulations were provided for the students under this area for this particular field trial. These included a simulation of a sampling for benthic macroinvertebrates (Figure 3, data tables/graphs for both macroinvertebrates and other water quality measures (Figures 4 and 5)) and a simulation of gas molecules in both air and water environments (Figures 6 and 7).

The next section of the Legacy cycle, Test Your Mettle, allows students the opportunity to test themselves about the knowledge that they need to help Billy. Items include an electronic "catalog" of items that are presented as ones that Billy might use to test for water quality. Students must decide if the item would be useful or not. They also are asked why they chose or did not choose the particular item. Feedback is provided for both correct and incorrect selections. Students also were asked to make a decision about the water quality of Billy's river by reviewing the macroinvertebrate data that Billy had collected. They must calculate the water quality index for each site sampled on the river and determine if the river was polluted.

In the final section of the Legacy cycle, Go Public, a decision was made that the public presentation be a limited one. Students had to take their answers to the Test Your Mettle activities and discuss them as a group with the teacher. If she was convinced that they had analyzed correctly the data from Billy's data collection activities, the students were given a password that allowed them to view a short video segment of Billy's interaction with Legacy League, showing that he had learned more about water quality. This gave the classroom teacher an opportunity to evaluate the progress made by the students in working on the challenge, and it prevented students from "rushing" through all three challenges without taking time to reflect on their work.

Students continued with challenges two and three in a similar manner, starting with a Challenge Quest video, again involving Billy and the Legacy League, and then working through the challenge using the Legacy cycle.

Posttest Results

Immediately after finishing all three challenges of the "River of Life," students were asked to take a 13-item multiple-choice test that had been designed to cover some of the major conceptual areas under study. Table 2 shows the results of a paired sample t-test for the 36 students that had both a pretest and immediate posttest. As can be seen, there was a statistically significant (p <.015) difference between the students on their pre and immediate posttest with students moving from approximately the 44% level to the 55% level for the percentage of correctly answered items.

In an additional analysis, the items on the posttest were grouped by their central concept. These included; items related to the use of macroinvertebrates as an indirect indicator of water quality (Items #1, 2, 3, 4, 5, 6), items related to the concept of dissolved oxygen (7, 8, 9,12) and near transfer items where concepts are used to predict outcomes (10, 11, 13). Descriptive results for these subtests are shown in Table 3.

These results would indicate that the students were better on items in regard to the use of macroinvertebrates as an indirect indicator of water quality and on some near transfer items where they had to use more than one concept as compared to their knowledge of the dissolved oxygen concept. Given the age of these students (5th-grade) this is not especially surprising. Students at this age have very poorly developed ideas of molecules, solutions, and the concept of gases (Posner et al., 1982).

Three days after all students had finished working with the software they were asked to complete the pretest again as a delayed posttest. Table 4 shows a paired sample t-test for the 38 students who had complete data. Statistically significant again (p<.001), the students' percentage correct values moved from approximately the 45% to the 60% percent correct level.

An item analysis revealed that almost all of the increase in scores came from students' better understanding of the importance of dissolved oxygen and macroinvertebrates to water testing, areas that they were especially poor in at the pretest. These items were in the form of questions that required the students to write a sentence or more. Reviewing these written responses was useful in helping to understand the depth of student understanding of these concepts. For example, student M did not answer either of the items on the pretest, but on the posttest she answered the dissolved oxygen question ("Why is the amount of dissolved oxygen important to know if you are studying a river to see if it is polluted?") with the sentence, "If there is too little dissolved oxygen it means the water is polluted." For the macroinvertebrates question ("What are macroinvertebrates and why are they useful to study when you are trying to see if a rivers is polluted?"), she answered, "Macroinvertebrates are living things that yo u can see with the naked eye. They are useful to study because if there are less macroinvertebrates then the river is polluted." While neither of these answers is completely correct (The river might be polluted by means other than ones that reduced dissolved oxygen and the type of macroinvertebrates should be determined in addition to the number), they show some understanding of the overall concepts and are a strong improvement over the pretest. Most answers by students for these items were of a similar nature, partially correct but not as fully developed as hoped for. However, these students were at the fifth grade level, at the lower end of the age levels that the software was designed for, and the expectation that their responses would be as full as eighth grade students is probably not realistic.

While showing growth of understanding in some of the central areas of the project, students did not appear to change their conception about the composition of air (less than 7% correct). They still clung to the idea that oxygen is the most abundant of the gases. Given the software's emphasis on the importance of oxygen to living systems and the relatively poor knowledge that students of this age have about gases these results were not especially surprising.

Classroom Observations

During the period that students were working with the software, the author and/or a graduate assistant kept field notes on student interaction with the software and the general classroom environment. As would be expected in a situation such as this that was both novel and of high production values, student interest remained very high. Students were so interested in working with the materials that the classroom instructor had to implement a system where students went to their computers as groups in an ordered manner (e.g., "Blue group may go to their computer") rather than all of the students rushing to the computers at once. Students also held quite animated discussions within their groups on aspects of the simulations, for example, identification of the macroinvertebrates found in the simulation samples.

There was substantial spread in the amount of time that it took for groups to complete the three challenges. One group finished in five class periods while another took twice as long (10 class periods). Most groups took between six and seven days to finish working with the software. Observers noted that students tended to move through the materials at a rate faster than was expected. The classroom instructor tried to reduce the speed by reminding students that questions posed in the various sections should be answered in their online notebooks and questions that required data to be graphed should be done with the provided hard copy blank graphs. An examination of the graphs of the various groups and the electronic notebook contents showed rather wide variation in the amount of material correctly graphed and the length and clarity of answers.

Some software modifications that provide more directed questions at certain points, especially related to the simulations, are planned for future versions. This point was especially noticeable in the "Air and Water" simulation (Figures 6 and 7) and the related question on the composition of air on the posttest. Students did not appear to understand the data tables on the left side of the screen and therefore continued in their misconception that oxygen is the most abundant gas in air. In retrospect, providing the tables with many different representations of the amount of various gases present is probably not appropriate for this age student. A partial alternative, being prepared for the next field study, would be to focus the students on the dynamic model of the systems but allow them to "freeze" the animation so that they could count the relative number of molecules to obtain an approximate percentage of the various gases that make up air. As would be expected in a field test of a relatively new piece of so ftware, the observers noted some technical "bugs" and minor design flaws. These will be corrected in later versions.

DISCUSSION

As with any quasi-experimental design where a formal control group is not in use, concerns are warranted about whether or not differences resulted from use of the intervention, maturation, or other untested variables. However, the relatively low knowledge level of the students at pretest on items of central importance to the study as compared to substantial increase in the immediate and delayed posttests gives some indication that students did develop some understanding of two central themes: the importance of dissolved oxygen in water ecosystems and the use of an indirect measure of water quality (benthic macroinvertebrates). This is consistent with earlier studies of anchored instruction environments (CTGV, 1992a; Kinzer et al., 1990, Goldman et al., 1996) and provides support for the general design of using contextually rich environments for instruction.

As a field study to exam design features, classroom implementation, user response, and conceptual understanding, the study has not only provided the development team with information about student understanding but also technical information about implementation and design issues that will be acted on in the next revision of the software. For example, observational data indicated that providing blank graphs and sample water quality calculations for students to assist them in plotting water quality indices are needed. Also, as previously mentioned, providing more guiding questions, especially in the areas where understanding appears to be weak, for example, composition of air, are needed and will become part of the later versions.

Finally, the study provided an additional test of the Star.Legacy design using students in much lower grade levels that previous work (Schwartz et al., 1999a). That work had involved undergraduate college students taking an educational psychology class. Working with elementary age students provides additional challenges given their less developed knowledge base and in some instances less than average reading ability.

While refinement and additional field-testing is needed, it appears that software designs based upon cognitive theory offer much promise for the future of instruction. In science instruction, many of the concepts that students are "taught" often do not appear to have much connection to student's previous knowledge and therefore knowledge gained is rapidly lost (CTGV, 1993a; Bransford et al., 1999). The use of problem-based instruction with technological tools, followed by project-based activities (both real and simulated) appears to offer a way to increase understanding and use of these concepts.

Table 1

Results of Pretest (N = 39)

Type of Question                      Mean  Stan. Dev.  Mean Percent
                                                          Correct

General Ecology Related (7 points)    4.54     1.67         65%
Dissolved Oxygen and                  0.00     0.00          0%
Macroinvertebrate Related (4 points)
Composition of Air (1 point)          0.03     0.16          3%
Graph Reading Skills (2 points)       1.74     0.50         87%
Total Test (14 points)                6.31     1.72         45%
Table 2

T-test on Pre and Immediate Posttest

Variable            N   Mean  Standard Dev  t-value  df  2-tail Sig.

Pretest             36  6.14      1.71       2.60    35     0.014
Immediate Posttest  36  7.19      2.69
Table 3

Mean Percentage Correct for Posttest Subtests (N=39)

Subtests                       Mean  Stan. Dev.  Mean Percent
                                                   Correct

Macroinvertebrates (6 points)  3.62     1.58         60%
Dissolved Oxygen (4 points     1.72     1.28         43%
Near Transfer (3 points)       1.92     0.64         64%
Table 4

T-test on Delayed Posttest

Variable      N   Mean  Standard Dev.  t-value  df  2-tail sig.

Pretest       38  6.26      1.72        6.00    37  .000
Delayed Post  38  8.34      2.73

Note

This material is based on work supported by the National Science Foundation under Grant ESI-9350510. Any opinions, finding, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

References

Barron, B., Schwartz, D., Vye, N., Moore, A., Petrosino, A., Zech, L., Bransford, J., & The Cognition and Technology Group at Vanderbilt (CTGV) (1998). Doing with understanding: Lessons from research on problem- and project-based learning. The Journal of the Learning Sciences, 7(3/4), 271-311.

Barron, B., Vye, N.J., Zech, L. Schwartz, D., Bransford, J.D., Goldman, S.R., Pellegrino, J., Morris, J., Garrison, S., & Kantor, R. (1995). Creating contexts for community based problem solving: The Jasper Challenge series. In C. Hedley, P. Antonacci, & M. Rabinowitz (Eds.), Thinking and literacy: The mind at work (pp. 47-71). Hillsdale, NJ: Lawrence Erlbaum.

Barrows, H.S. (1985). How to design a problem-based curriculum for the preclinical years. New York: Springer.

Bransford, J., Brown, A., & Cocking, R. (Eds.) (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.

Bransford, J., Kinzer, C., Risko, V., Rowe, D., & Vye, N. (1989). Designing invitations to thinking: Some initial thoughts. In S. McCormick, J. Zutrell, P. Scharer, & P. 0. Keefe (Eds.), Cognitive and social perspectives for literacy research and instruction (pp. 35-54). Chicago, IL: National Reading Conference.

Bransford, J., Sherwood, R., Hasselbring, T., Kinzer, C., & Williams, S. (1990). Anchored instruction: Why we need it and how technology can help. In D. Nix & R. Spiro (Eds.), Cognition, education, and multimedia (pp. 115-141). Hillsdale, NJ: Lawrence Erlbaum.

Bransford, J., & Stein, B.S. (1993). The IDEAL problem solver (2nd ed.). New York: Freeman.

Bransford, J.D., & Vye, N.J. (I 989). A perspective on cognitive research and its implications for instruction. In L. Resnick & L.E. Klopfer (Eds.), Toward the thinking curriculum: Current cognitive research (pp. 173-205). Alexandria, VA: The Association for Supervision and Curriculum Development.

Brown, J.S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher 18(1), 32-42.

Chi, M.T.H., Glaser, R., & Farr, M. (1991). The nature of expertise. Hillsdale, NJ: Lawrence Erlbaum.

Clement, J. (1982). Algebra word problem solutions: Thought processes underlying a common misconception. Journal of Research in Mathematics Education 13, 16-30.

Cobb, P., Yackel, E., & Wood, T. (1992). A constructivist alternative to the representational view of mind in mathematics education. Journal for Research in Mathematics Education, 19, 99-114.

Cognition and Technology Group at Vanderbilt (CTGV) (1990). Anchored instruction and its relationship to situated cognition. Educational Researcher, 19(6), 2-10.

Cognition and Technology Group at Vanderbilt (CTGV) (1992a). The Jasper Experiment: An exploration of issues in learning and instructional design. Educational Technology Research and Development, 40(1), 65-80.

Cognition and Technology Group at Vanderbilt (CTGV) (1992b). The Jasper Series as an example of anchored instruction: Theory, program description, and assessment data. Educational Psychologist, 27(3), 291-315.

Cognition and Technology Group at Vanderbilt (CTGV) (1992c). Anchored instruction in science and mathematics: Theoretical basis, developmental projects, and initial research findings. In R. Duschl & R. Hamilton (Eds.), Philosophy of science, cognitive psychology and educational theory and practice (pp. 244-273). New York: SUNY Press.

Cognition and Technology Group at Vanderbilt (CTGV) (1993a). Anchored instruction and situated cognition revisited. Educational Technology 33, 52-70.

Cognition and Technology Group at Vanderbilt (CTGV) (1993b). The Jasper Experiment: Using video to furnish real-world problem-solving contexts. Arithmetic Teacher: Mathematics Education through the Middle Grades, 4, 474-478.

Cognition and Technology Group at Vanderbilt (CTGV) (1993c). Toward integrated curricula: Possibilities from anchored instruction. In M. Rabinowitz (Ed.), Cognitive science foundations of instruction (pp. 3355). Hillsdale, NJ: Lawrence Erlbaum.

Cognition and Technology Group at Vanderbilt (CTGV) (1994). From visual word problems to learning communities: Changing conceptions of cognitive research. In K. McGilly (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 157-200). Cambridge, MA: MIT Press/Bradford Books.

Dewey, S. (1933). How we think. Restatement of the relation of reflective thinking to the educative process. Boston: Heath.

Duffy, T.M., & Bednar, A.K. (1991). Attempting to come to grips with alternative perspectives. Educational Technology, 31(9), 12-15.

Goldman, S.R., Petrosino, A.J., Sherwood, R.D., Garrison, S., Hickey, D., Bransford, J. D., & Pellegrino, J.W. (1996). Anchoring science instruction in multimedia learning environments. In S. Vosniadou, E. De Corte, R. Glaser, & H. Mandl (Eds.), International perspectives on the psychological foundations of technology-based learning environments (pp. 257-284). Hillsdale, NJ: Lawrence Eribaum.

Gragg, C.I. (1940, October 19). Because wisdom can't be told. Harvard Alumni Bulletin, 78-84.

Kinzer, C.K., Risko, V.J., Goodman, J., McLarty, K., & Carson, J. (1990). A study of teachers using videodisc anchors in literacy instruction. Paper presented at the 40th annual meeting of the National Reading Conference, Miami, FL.

Kinzer, C.K., Risko, V., Vye, N.J., & Sherwood, R.D. (1988). Macrocontexts for enhancing instruction. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA.

Linn, M. (1998). The impact of technology on science instruction: Historical trends and current opportunities. In B.J. Fraser & K. Tobin (Eds.), International handbook of science education (pp. 265-295). Dordrecht, The Netherlands: Kluwer.

Minstrell, J.A. (1989). Teaching science for understanding. In L.B. Resnick & L.E. Klopfer (Eds.), Toward the thinking curriculum: Current cognitive research (pp. 129-149). Alexandria, VA: The Association for Supervision and Curriculum Development.

Moore, J.L., Lin, X., Schwartz, D.L., Petrosino, A.J., Hickey, D.T., Campbell, O., Hmelo, C., & The Cognition and Technology Group at Vanderbilt (CTGV) (1994). The relationship between situated cognition and anchored instruction: A response to Tripp. Educational Technology, 34(8), 28-32.

National Research Council (NRC) (1996). National science education standards. Washington, DC: National Academy Press.

Palinscar, A.S., & Brown, A.L. (1984). Reciprocal teaching of comprehension fostering and comprehension monitoring activities. Cognition and Instruction 1(2), 117-175.

Perkins, D.N. (1991). What constructivism demands of the learner. Educational Technology, 31(9), 19-21.

Posner, G.J., Stricke, K.A., Hewson, P.W., & Gertzog, W.A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211-227.

Scardamalia, M., & Bereiter, C. (1991). Higher levels of agency for children in knowledge building: A challenge for the design of new knowledge media. Journal of the Learning Sciences, 1(1), 37-68.

Schoenfeld, A.H. (1989). Teaching mathematical thinking and problem solving. In L.B. Resnick & L.E. Klopfer (Eds.), Toward the thinking curriculum: Current cognitive research (pp. 83-103). Alexandria, VA: The Association for Supervision and Curriculum Development.

Schwab, J.J. (1978). Science, curriculum, and liberal education. Chicago: University of Chicago Press.

Schwartz, D.L., & Bransford, J.D. (1998). A time for telling. Cognition & Instruction. 16(4), 475-522

Schwartz, D.L., Brophy, S., Lin, X.D., & Bransford, J.D. (1999a). Software for managing complex learning: Examples from an educational psychology course. Educational Technology Research and Development, 47(2), 39-59

Schwartz, D.L., Lin, X., Brophy, S., & Bransford, J.D. (1999b). Toward the development of flexibly adaptive instructional designs. In C. Reigeluth (Ed.), Instructional design theories and models (Vol. II, pp. 183-2 13). Mahwah, NJ: Lawrence Eribaum.

Sherwood, R (2000). Final report: The 'Scientists in Action' series.' A generative approach to authentic scientific inquiry project (ESI-9350510). Arlington, VA: National Science Foundation.

Sherwood, R., Petrosino, A., Lin, X.D., & The Cognition and Technology Group at Vanderbilt (CTGV) (1998). Problem based macro contexts in science instruction: Design issues and applications. In B.J. Fraser & K. Tobin (Eds.), International handbook of science education (pp. 349-362). Dordrecht, The Netherlands: Kluwer.

Sherwood, R.D., Petrosino, A.J., Goldman, S.R., Garrison, S., Bransford, J.D., & Pellegrino, J.W. (1993, April). An experimental study of a multimedia instructional environment in a science classroom. Paper presented at the meeting of the American Educational Research Association, Atlanta, GA.

Wheatley, G. (1991). Constructivist perspectives on science and mathematics learning. Science Education, 73(l), 9-21.

Williams, S.M. (1992). Putting case-based instruction into context: Examples from legal and medical education. Journal of the Learning Sciences, 2(4), 367-427.

Vye, N.J., Schwartz, D.L., Bransford, J.D., Barron, B.J., Zech, L., & The Cognition and Technology Group at Vanderbilt (CTGV) (1998). SMART environments that support monitoring, reflection, and revision. In D. Hacker, J. Dunlosky, & A.C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 305-346). Mahwah, NJ: Lawrence Erlbaum.