Marcia Linn

Andy Disessa

Roy D Pea

Nancy B Songer

Marcia C Linni

Roy D Pea'

Nancy R Songtrj

Inform Standards f o r Science Ed~cation'.)'~

Keywords: Science, rechnoiogl,, models, standards

HAL is

This material is based ucon research supported by the National Science Foundation under grant RED-9155711. An!. op~nions. findings, :ind conclusions or iecommendation~ expressed in this pub1ic;ttion are those of the authors and not necessarily retlect the views of the National Science Fcunanrion.

A broad xray of organizations are parnciping in an effort to reform science education by sexr.2 science standards (Yationai Research Council. 1992: National Research Councli. :993: Yational Science Teachers Association. 199 1; Rutherford & Xhlgren. 1990). This effort has. at its core. a commitment to making science accessible to all students. not just future scientists (National Research Council. 1992: Yational Research Councii. 1993;Rutherford & Ahlgren. 1990) As participants in the leadership of the American Educational Research Association Speciai Interest Group on Education in Science and Technology (SIG-EST), we have rerlecteb on this process. In this paper \ye summarize some reactions to the documents that have emerged from the standard-setting process. We especially seek to identify insights from recent research that apply to the process of setting standards. After conuasting the current standard-based reform with the r e f o m s of the 1 9 6 0 ' ~ \re discuss;

(a) science course goals. t b) the social nature of science learning in general and equity in pmicuix. (c) instructional practices. and Id) the roie of technology.

Comparing Reforms

Although the current standard-settins efforts are targeted to all students and not just future scientists, the documents that are emerging from the process are renuniscent of the refoms of the 1960's and are. therefore. subject to the same limitations. The reforms of the 1960's were initiated primarily to incorporate modern scientific ideas into the cumcuium and to improve the inquiry skills of future scientists (Salinger. 1991: Science Manpo\ve: Project (Frederick L. Fitzpatrick: Director]. 1959: [START_REF] Welch | Twenty years of science curriculum development: .A look back[END_REF]). techno lo^^.

as a component of science was neslecred. dthough technological tools such as films bere emphasized as enhancements to instruction.

To illustrxe, Jerrold Zacharias. in setting the goals for the Physical Science Study Committee (PSSC), decided to devote ail of his attention to communicating modern scientific p-inciples. For example, in a biography of Zacharias. Goidstein ( 1992. p. 162) reports this summary of the PSSC view: "Modern physics was concerned with fundamer.tals. It had to d o with particles and the forces between them. and with their motions. not with pulleys and levers. llodern physics dealt with atoms and molecules. and witn stars and planets: the machines and engines that were central features of the existing physics courses Lvere important but only as special applications of the science.

On this there was the broadest agreement possible: if something had to be dropped for lack of :ize. it would be the applications. The fundamentals of the science musr remain."

This decision r'oc~s=d the cumcuium on future scienrists. .And as might have been expected. followlr;; :5e reforms of the 1960's the proportion of students taking advanced science remained : . ! t same (Salinger. 199 1 : Welch. 1979).

Even the innovat1i.s. zreative curricula of the 1960's w r e unsuccessfui in important ways. For exampie. students studying these materiais stiil often concluded that objects released from a cur:sd path would continue on a curved trajectory (hlcCloskey, 1983).

Even students cornpiering college courses at institutions iike MIT retain intuitive ideas that differ from those of expert scientists (disessa. in press). Given these diverse intuitions of stud en:^ completing physics courses. how can we make science more teachable and more izarnable?

It is widely believeb :hat the reform efforts of the 1960's Lvere limited in part because the natural scientists \.i ro led the reforms paid too little attention to the feedback they received from precciiege teachers [START_REF] Welch | Twenty years of science curriculum development: .A look back[END_REF]. Precoiiege teachers commonly complained that tne science materials developed by naturai scientists were too difficult and that students could not learn from them. In contrast. the natural scientists believed that if the teachers xere more effective, students would be able to learn the materials.

A major worry we nave is that emerging science standards describe cumculum that individuals who are now successful research scientists would have preferred when they were precollege students. Such a curriculum may be laudable for those who wish to become scientists. )'st, for the vast majority of students who do not aspire to be scientists. [here 1s 2x1 and convincing evidence that the current curricdum is flawed, uninteresting. fleet:r,,n. and fundamentally irrelevant (e.:.. [START_REF]Establishing a research base for science education: Challenges. trends. and recornmer,aations[END_REF].

A key question for :hose setting standards is how to measure these limitations. During the 60s. reforms recected the perspective of the natural scientists. A challenge to the standard setting grouu is to reexamine this decision and to incorporate the conrributions of precollege teachers and pedagogy experts. as well as those of natural scientists.

Considerable evidence from investigations in science classrooms suggests that both the science cumculum 2nd the role of the science teacher need reformulation (e.g., (disessa. 1992: Linn & Songer. 199 1; Pea &: [START_REF] Pea | Distributed multimedia learning environments: The collaborative Visualization Projecr[END_REF][START_REF] Songer | Learning science with a child-focused resource: .A case study of Kids as Global Scientists[END_REF].

In addition, the erxrzing science standards documents do not appear :o consider the current roles of tecixology seriously in either science or education. Fmdamental understandings of :::hnology are not represented. Tzchnological toois that could enhance learning 2 : : If scientific ideas. modes of thinking, and appiications to complex problems are not linked and related in the standards. how can we expect them to be linked and related in textbooks, teaching, and learning? How can citizens and students appreciate fundamental understandings without considering their appiications'? And. how can students understand the nature or science if the tension bst~veen fundamentrli research and applications of science is not continuously addressed'?

We c d l on groups setting standards to rethink the overall organization of the standards.

We believe that it is imperatiye that science. technology, the nature of science. and the application of science be linked. related, and sirnultaneouslv addressed in science courses. textbooks, and standards.

Incorporating Recent Research

As reform efforts turn from ; l focus on future s;izntists to a focus on a11 citizens. recent research on learning and instruction and recenr insights about the social nature of learning are extremely relevant. We discuss c a1 course goals. (b) the soclal nature of science learning. (c) instructional prmices. and (d) the role of technology.

Course Goals

We call on those setting the standards to adopt two criteria for the goals for science courses taken by most citizens. First. the centrai target should be a scientifically cultivated sense of the e v e ~d a y physical. biological. social. and political world rather than a schoolish version of professional science. Second. this means. in particular. that the cumculum should help students link scientific principles to improving their thinking about everyday phenomena and help students build a cohesive view of scientific knowledge.

Science entails a diversit). of expianatlox and models. Science instructior, or' [he past has concentrated on the most generai. :amprenensive. and precise models. \Ian>. of these models are couched in formai. algebraic ianguage. These models tend to 5s zbstract compared to the familiar forms o i z-,,er>.day experience. Students have a kzrd time understanding \vhat the models or isws zean, and a harder time applying ihtm to their personal scientific dilemmas. Rather than isolating and emphasizing the abstract perspective on science. we believe :he c ~n i c u l u m should encourage students to develop a repertoire of alternative models as well as an appreciation for science as a search for progressively more powerful models.

Modern psychology, cognitive science and artificial intelligence have elaborated our understanding of the power of alternative models of complex phenomena. particularly highlighting qualitative. heuristic a d approximate models. In addition. n e have come to understand that students. adults and scmtists employ many of these moaeis :n their everyday understandinz. So. these :wo rrends-expanding the repertoire of legitimate and powerful models. and uncovering thz richness in students' spontaneous modelsshould combine to alter the pedagogical agenda.

We expect students have many ideas to contribute. and we can be more p:ltient about waiting for the most sophisticated. abstract. "correct." and formally articulltted forms. We need to take a long-term perspective to see how, step-by-step, we can draw students' naive models out. refine and articulate them. This is a fundamental issue. since our educational system must focus on a broad range of students and not only on an elite who will learn science nith virtually an\, curr,culum. I r e need to be clever in designing intermediate models that are close enough to students' naive models that they seem familiar. plausible and uset'ul. yet can e\.oive naturally into more sophisticaxd forms.

Technological tools can enhance this process (e.g., [START_REF]The computer as learning partner: Can computer tools teach science[END_REF][START_REF] Pea | Augmenting the discourse of learning with computer-based learning environments[END_REF]). We begin with phenomenological models that may appear more descriptive than expiltnatory. limited in scope. or even incorrect in contrast to "deeper" forms. But this appearance may be deceptive. The first steps toward the deepest scientific understanding may be the most critical. By establishing a disposition to make sense of the science that is taught and the science that is experienced. we set students on rt trajectory that will nor culminate at the last formal science lesson. but rather zontinue as new scientific problems are identified in experience.

Alternative models for scientific events can be illustrated by considering perspectives on thermal events. Scientists use several alternative models to elucidate thermai zvents: moiecziar kinetic theory. a model of heat rlow. and specific computations or' changes in.

for exzmpie. calories and degrees. The heat rlow model. is often intuitively accessible :o stuaezts wno are trying to make sense of thermai events and readily simulated in the classroom r e.g, (Lewis & Linn. in press I.. Effec:i;.e teaching would seek a progression of alternative explanatory models to guide instrucrion and link principles and applications. Thus. in early elementary years. students might have a model that focuses on observable events such as (a) sweaters keep you Warner than tee shirts, (b) the same burner heats a small pot of water to boiling before a larger ?or of water at the same starting temperature. and (c) cutting up the hot lasagna into pieces will cool it faster. Middle school students might form descriptive principles about such phenomena as surface area and thermal equilibrium. By high school. students could be inrroduced to more sophisticated models including molecular kinetic theory. In addition. a major focus of the curriculum. if i t were taught this way, ~vould be on these alterxtive models and their relative usefulness to citizens and scientists. For exampie. moae!s helpful for wilderness survival might be contrasted with those helpful for materials science.

In fac: absrract scientific models are often insufficient for grappling with complex probiems. Scientists disagree on such topics as the risks and benefits of nuclear energy.

the reason dinosaurs became extinct, and the evidence for global warming. Educated adults have difficulty explaining why Styrofoam is better than aluminum foil for keeping a dnnk cold for lunch. or why a rough, white surfxe is better than a mirror for reflecting light fiom a flashlight to illuminate a room. There are teachable. powerful versions or scientific ideas that can help (a) transcend commonsense and na'ive models. (b) m&e better sense of the everyday world. and (c) provide a soiid path for those students who will become professional scientists. We advocate what we call an "alternative models" approxh to science instruction.

To achieve these goals and to clarify this alternative models perspective, we examine the October 1992 NRC Sampler (National Research Council. 1992) from this standpoint.

The tl:ernenrac crirric~~ium. The current NRC sampler starts with descriptive models of science. Students observe and describe the similarities and differences in objects that they 05sen.e naturally, such as leaves or trees.

The ziwnative models approach starts with a similar descriptive perspective. but adds a focus on integrating descriptive explanations and warranting conclusions. Students wouid be encouraged to a ~p i y explanations far more widei;; %an tr,ey commoni>l are in current elementary science courses and to seek systematic accounts of evenday scientific phenomena. For txampie. they might establish a series of materials based on their ability to keep a dnnk coid in 3 iunch box. They would comuiie information and then seek generaiizations. cornpanng metals to paper to cioth. for exampie. A descriptive model of insulators would therefore be accorded stature in the elres of students. In contrast, at least some perspectives on science education accord students descriptive models of science.

the status of misconceptions (e.g., Linn & Songer. 199 1: Smith. diSessa. 22 Roschelle. in press)

By labeling student ideas as misconceptions we criticize students for being accurate observers (Lewis & Linn. in press). Thus. in the eariv .rrades. students often describe phenomena in ways that could contradict the descriptions offered by scientists. They might say (ar obiects. ~vnen kicked. tend to go in the direction kicked. ib) objects in motion tend to come to rest. (c) sounds die out and (d'j tvooi warms >,ou up. The alternative models approach might elaborate students descriptive model of motion until students concluded that objects kicked with the same degree of force come to rest at different distances depending on other conditions like the surface on which the object travels.

Extensive evidence demonstrates that young students are capable of thoughtful generalizations (Carey. 1985). Yet the standards described in the sampler seem to imply that students are limited to description that lacks functional context or explanatory intent. This is an outmoded interpretation of developmental constraints that f ~i l s to acknowledge the intellectual ~vork of young students and is reminiscent of the nature study movement of the 1900s and the unguided -disco~mery activities of the 1980s (Holmes. 1903: Underhill. 1941).

The middle school crirricrii~ini. The YRC sampler recommendations for middle school differ substantiaily from the alternative models approach. The sampler suggests teaching 5th through 8th graders molecular models. mathematicai formulations for mechanics, and other abstract scientific esplanations. These models do not map directly onto students' observations and start many students on the path of memorizing rather than comprehending science. We recommend that these models be postponed to the 9th through 12th grades. and that. instead. in the 5th througn 8th grades. students focus on models that are more principled and mechanistic than those exountered in the early elementary grades. Students would describe the hearing and cooling of objects in terms of heat tlow. they ~vouid descrije elecmcity in terms of relative eiectricai power. and they would develop quaiitati\.e zodels for motion. The idea of a mechanism or an explanation would become a more cspiici: focus of the 5th through 8th grades and students would systematically compile :l,.iaence that warranted their observations and conjectures.

Students might disentangic t.hs effects of mass and surface area on the heating of objects.

but they would still focus on neat in a macroscopic fashion rather rhan in a microscopic fashion.

The high school curricrtiwn. In the 9th through 12th grades, students would encounter new level models that were more abstract and. in some courses. mathematically formal.

They would return to the same issues and problems that they faced in the middle grades and reinterpret the information and observations that they had using these new models.

The advantage of alternative nodels would now become very clear because students would see the progression from a descriptive to a mechanistic to an abstract explanation for the same event. Thus. they would understand a great deal about scientific investigation. and at the same rime. they would have a much richer. more qualitative understanding of everyday scientific phenomena than is achikvea in the typical cuniculum. This approach is reflected in the work of White on eiectricity (White &: Frederiksen. 1990); Linn on thermal events i l i n n , 1992), Minstrel1 in mechanics (Minstrell, 1982). Pea in optics (Pea. Supusic. &: Allen, in press), and Clement on mechanics (Clement. 1982).

Advarzrages of rlte airernarire models approach. The alternative models approach makes the inquiry skills described in :he sampler an integral part of science leaning rather than an additional topic. In e v e n scientific study students would be analyzing the nature of their own explanations and the evidence that they used to warrant their conclusions. In this sense. they ~vould be actlve participants in making sense of scientific phenomena just like scientists. Instead of trying to make sense of phenomena that they could not observe. students would be makinr sense of immediately observable phenomena up until at least the 9th grade.

The alternative models approach also has a tremendous advantage in fostering integrated understanding. By helping students contrast the various explanations that they themselves use for everyday scientific events. students are more likely to see the relevance of their own obsenations to science. Instead of encouraging students to distinguish their own observations from classroom science. which happens so often today, the cumculum \voula help students integrate these obsemarions with scientific principles. Rather than isolating idezs about scientific inquir).. students n,ouid seek evidence to warrant their own moaei 2nd to distinguish among models.

The greatest difficulty of an airerrmi\.= modeis approach is its demand on students.

Whereas abstract models introduced exiy in the curriculum cause students II .rear deal of trouble, alternative explanations ior complex and ambiguous phenomena dqending on the purpose of the explanation are. in fact. much more challenging. Severtheless. in our estimation. explaining complex and ambiguous e v e n d a ~. problems is also much more rewarding to students. In contrast. even when students gain a glimmer of understanding of abstract scientific models. they often fail to apply this information to eveqfday phenomena because they cannot map the abstract information onto obsened scientific phenomena (e.g., Gunstone. Gray. &L Searle. 1992). For example, using a molecular kinetic theory to explain why a metai spoon in boiling \\.ater feels hotter than a wooden spoon is far more complex than reiying on a heat-flow model. An a1tern;ltive models approach to understanding motion may start with phenomenological. approuimate models. and later add more abstracted models as an illumination or "reexpe:ience" of prior models. There are times when qualitative models are more useful than abstract models. And. as a result, the qualitative models end up supporting students as they attempt to make sense of more abstract models. They help students acquire an intermediate competence between intuitive beliefs and more sophisticated. rlbstract models.

lrzsrrrictional practices

The alternative models approach offers more support for the efforts to make sense of science familiar to precollege teachers and educated adults than do the modsis found in the typical science cumculum. Ttachers often construct views of themselves as purveyors of scientific information. yet this presents an immediate difficulty because few reachers have all the information that studenrs might \van[. The alternxive nodels approach changes the focus from one of providing infommion to one of supporting conjectures and seeking commonalities in evidence.

Precollege teachers take the role of fostering. facilitating. 2nd supporting students as they make sense of science. The locus of responsibilit>~ for scientific understanding remains primarily with the student. Just as we expect students to continuously refine 2nd reformulate their scientific ideas. so can we expect teachers to continuously refine and reformulate their ideas about how to teach science. Teachers are most et'r'ec;i\.e \\,hen they caz reflect. refine. and enhance their ~ractice rather than wnen they are constanti? evaiuared. criticized. and scrutinized.

There :s widespread belief that science teaching would be more effective if the teachers knew rzore science. This mav well be the case. However. the amount of science that teachers need to know should certainly not exceed that achieved by most scientists in our society. Those completing teacher preparation programs must be prepared to teach any science 2nd often science and mathematics. X realistic view of what can be learned is needed.

It appears inevitable that teachers will be responsible for helping students understand materiai that they themselves are also in the process of understanding. Furthermore. it is likely rnat teachers as well as students will hold descriptive and intuitive models of the phenomena relevant to the topics that they are teaching. We need methods for science instruction that take advantage of these descriptive and intuitive ideas that both students and teachers develop over the course of their lives. These are important accomplishments that need to be refined rather than ridiculed. It is both irresponsible and unrealistic to develop science standards that are unteachable (see Smith et al., in press).

Social .\' arure of Science Learning

The scientific work of gathering evidence and distinguishing among models for scientific phenomena is social in nature. In the workplace. research teams grapple with making sense of scientific evidence. Large coilaborations such as the Human Genome Project and the nigh energy physics groups are necessary for advance in many fields. .And. scientific disputes are a reputable investigtive tool for probing and refining bodies of evidence.

To engage students in the social aspects of science. the dilemmas must be personally meaningful. The alternative models approach, with its emphasis on linking scientific ideas to everyday phenomena makes the cuniculum more personally meaningful for students. Thus. the abstract models of morlon taught for frictionless surfaces in many middle grade science cumcula are in fact inadequate for explaining most naturallyoccumn,o phenomena. . & more sound and solid foundation for future instruction would be one ivhere students worked at the intersection between their observations and the deveiopment of a model of observed phenomena. Thus, students would focus on building a moaei to explain the obsemed phenomena. and then. on adjusting the model to the realities of [hex obsen-ations. Simiiarly. thz formal ~natnematicai modeis and abstract pnncipies of scienc: zre ciumsy when used to expiain most everyday tnzrinal events and many aspecs oi sound propagation and light trlinsmission 2s well. Thus discussions of alternative models. xplanations for naturaiiy-occumng everyday scientific phenomena. and a1ternati1.e forms of evidence reinforces for students the expioratory nature of science and provides a zreater appreciation of the broad range of scientific activity that exists in our society.

Our advocacy of an alternative models approach includes an emphasis on d e s i g n 4 f machines. of problem solutions, of explanations, and of investigations.

Role of Technolog!

Information technologies : : n also support the xiremati\,e modeis zpproach to instruction. Emerging standards. howe:.~:. are notoriously silent about the fact that information technologies play fundamer.:ai roles in scientific inquiry. Scientists use computers to illustrate models to explain :kieir observations. 2nd to display data for purposes of scientific visualization (Broaie et al.. 1992: Kaufmann & Smarr. 1993). Computer networks facilitate scientific 5iscussion senling as "collaboratories" (Lzderberg. Uncapher. & co-chairs. 1989) to support electronic communications. access to scientific data, and remote control of supercomputers and other technological tools (Finholt & Sproull, 1990: National Scisnce Foundation. 199 [START_REF] Wolff | The Macintosh scientific computing environment[END_REF]).

We believe that such tools m x t be integrated into science educarional practice from the earliest years. [START_REF] Hestenes | hlodeiing games in the Newtonian World[END_REF].

Indeed. great progress has bsen made in developing comprehensible but very senera1 computer environments in Lvnich students can approach science as scienrists do. by developing and refinin: rhsx own models (s.:.. These technologies can augment ciassroom investiganon and foster an alternative models approach to insrruction. Such toois suuport precollege ~eachers who seek to shift their role from provider of authoritative kno\viedge to inquiry guide (Blumenield et al.. 1991[START_REF] Ruopp | LabNer -Toward a communirv of uractice: The case of high school uhvsics teachers[END_REF]. Students a n use these tools to explore and compare their own scientific models.

Implications

At the onset we noted that standard-setting is challenging because. on the one hand. it seeks to change the cumculum to meet the needs of all students and. on the other hand, those setting standards seem inclined to reinvent the reform projects of the 1960's.

Broadening the audience for science requires accompanying changes in the goals. social interactions. and insuuctional practices of science.

For example, adults often remark that thev have led successful and rewarding lives without understanding a single scientific concept or principle. In efforts to provide science for all. this remark is a very telling one. Successful adults almost certainly have implicit models of everyday scientific phenomena and surprisingly powerful mechanistic understanding of complex and ambiguous scientific problems. These adults fail to see the connections between their ideas and the abstract, mathematically formal scientific ideas that form the current science cumculum. They feel that "fundamental" scientific understandings are esoteric and not relevant to their own lives. Simply spending more time and energy or more curricular effort teaching this s o n of disconnected science is unlikely to change the perception of science in the eyes of most citizens. Rather. the information relegated to the back of the textbook and the back of the standards books needs to come to the front and be linked to every topic.

We believe standards for science should stress the need for citizens to link their solid obsenmions and good descriptive models of scientific phenomena to fundamental scientific understandings to achieve reform. We fear a further bifurcation between scientific ideas of citizens and scientists: citizens may continue to take pride in their lack of understanding of textbook science and scientists may continue to ignore the pragmatic. powerful. and useful ideas that citizens haye achieved. We call for an approach to science instruction that reframes the question concerning the understanding of science and that credits citizens and students with insight and ingenuity when they make sense of everyday scientific phenomena.

We find that textbook science grabs odd fragments of the rich fabric of science and tries to prete~d they are sensible. or even necessary. We need to take Einstein more seriously when he says "Science is a refinement of everyday thinking" [START_REF] Einstein | Ideas and opinions[END_REF]. Currently.

we move sway too quickly from everyday thinking to abstract models.

We encourage those setting standards to encompass both the needs of research scientists and the needs of citizens. We believe it is possible. although difficult. to identify a f i r m foundation for both groups and to ensure that both future scientists and future citizens will receive a grounding in scientific ideas that is relevant to their everyday scientific lives. In addition, we believe that students need a model of scientific reasonins that encompasses both their own efforts at description and observation and the efforts of research scientists at the leading edge of investigation. This model will, of necessity. empnasize the social nature of scientific knowledge construction and focus on the alternative models utilized in all scientific endeavor. It will feature respect tor all citizens and emphasize the dangers of dismissing the opinions of those who are members of groups that have been underrepresented in science. This approach. we believe. reflects an understanding of the ways students make sense of science. It builds on the sense-making efforts of students starting from their f i s t obsenmions of the world and encourages students to reflect on their own descriptive scientific theories while at the same time inregating their own ideas with more powerful ideas presented in science classes. It emphasizes the technological advances of science and also provides opportunity to use modern technologies to make models dynamic and to test alternative models. We believe that the alternative models approach advocated here iviil greatly enhance scientific understanding and go a long ways towards encouraging all students to think scientifically.

  understanding and which are now integral to the research in the scientific community 1e.g.. see Office or Science and Tzchnoio~v -. Policy. 1991: Office or' Science and Technoioc~r -. Polic),. 19921 are not acknowledged or recommended. Modes of learnins and insuucaon tnat are plausible. possible. and have been demonstrated with technology are also negiecled. Furthermore, the science standards documents relegate what most citizens are likely to consider important in science :o "the back of the book." Applications of science as well as the nature of science are separated from "fundamental understandings" of science.

  Design problems frequently lead to effective scientific discourse. Students elaborate and refine their scientific models in the context of familiar or easily understood goals. Here the nature of science and the roie of technological advance is particularlv important. Introducing the concept of design and its social components early In the cumculum illustrates important aspects of how science ~~o r k s . Design exemplifies the scientific investigltion skills that students are likely to use in their lives and engages students in social intzr~ctions relevant to science. In advocating emphasis on the social nature of science Lve advocate. as well, respect for the diversity of views and opinions held by members of the classroom community. Recent reports and studies demonstrate that women students are often shortchanged in social settings cWellesley College Center for Research on Women. 19921. In our own science classroom studies we have seen opinions disregarded and student contributions dismissed on the basis of group membership (Agogino & Linn. 1993 >la>.-June: Linn ix Sonzer, 19911. Since fewer mPomen than men participate in careers in science. what seems to happen is that individuals. often unconsciously, expect less of women in scientific discussions. and are more likely to dismiss the opinions of Lvomen. The situation is further exacerbated by the social roles society has constructed for men and women. .Assertive discourse strategies that are sanctioned for men may backfire. when used by women. Thus. at the same time as we advocate encouraging students to engage in the social discourse of science. ~v e also advocate diligent attention to potentiai un~ntended consequences of such activities. Setting a goal of "science for air' creates an opportunity to ensure that ail students participate as respected members of the scientific classroom community.

  These tools are becoming Tore and more avaiiable to precollege students c Friedler. Nachmias, & Linn. 1990: L m . Sonzer, Lewis. & Stem, in press: Rubin. Bruce. Rosebery, & DuMouchel. 1088: Thornton & Sokoloff. 1990). For example. students can use spreadsheets to create roaels of scienrific concepts such as speed 2nd xxeleration

  [diSessa. Xbelson. cSr Ploger. 1991)..Many simulations mice possible "JVhat if ..." experiments to hyporhesize and examine relationships among variables. such as predator-prey populations in ecosystems, or optical effects of different materials on light propagation iPe2. i992: Richards. Barowy, & Levin. 1992). Programs for scientific visualizations in disciplines such as climatology, atmospheric science. and oceanography support high school students as they develop models to explain ziobal ~vaming, \$.eather patterns, and effects of physical geography on climate (Gorain & Pea. in press: Pea & Gomez, 1093).Electronic communication is also accessible to precollege studens. The National Geographic Society-KidsSet net~vorks tens of thousands of elementary school classrooms as they investigate local and national patterns of. for example. ac:d rain levels. Students are participating in collaborarive explorations of scientific phenomena (Levin. Riel.Miyake. 8:Cohen, 1987: li'aush & Levin. 1989).

  1 June: Office oi Science and Technology Policy. 1991: Office of Science and Technclocy .

	+	Policy. 1992:

.,? splrit o t our thinking and does nor necessaril!~ : ? : -x t :he views of SIC-EST. or any other orgmization.

We gratefully ackno\viecc? :he support of Yational Science Foundation Grant .\IDR-9253462 in work relateci *% rnis paper.

--E M E U Y . DAVIS R V W E . LOS AKGELES a -:.'ERSIDE . i&V D E W i:L% mhYCISC0 Enclosed is a copy of the final verslon ot the paper submitted to JSET. Please review i t and let me know if there are any glaring ommions or other problems. In addition, ~i there are any changes that need to be made in galley proofs, please d o r m me of those as well, and ! will make the c h a n ~e s when the galley proofs arrive.

The paper is slated to appear in the January 1994 issues of JSET, and congratulations to all of us for completing this task. As Andy noted in his final email, this may even make a difference which would be exciting.

I will also send a copy of the paper to the NRC standards setting groups since the paper so strongly reacts to their efforts. I mentioned it to Jim Greeno who let me know that the initial commentary that we sent had been extremely helpful to his group of the standards settins committee.

Also, please consider submitting papers to JSETs SIG;EST sectlon tor subsequent issues. Already, we have a paper from the COVE project which is currently under review. \Ire are expecting a paper soon from the hlultimedia Kiosk group, and we look forward to papers from all of you as well.


Tian Xia
email: tian.xia@insa-rennes.fr

Jean-Christophe Prevotet
email: jean-christophe.prevotet@insa-rennes.fr

Transparent Dynamic Management of Reconfigurable Accelerators in Virtualization Technology

This paper is intended to provide an abstract and transparent layer for virtual machines (VM) to access reconfigurable resources. The underlying infrastructure of partial reconfiguration management is hidden from the VMs. D-PR accelerators are presented as virtual devices, which are universally mapped in each VM space as ordinary peripherals. The framework automatically allocates D-PR resources dynamically according to a preemptive allocation mechanism. The evaluation of DPR management overheads demonstrates that our mechanism is implemented with low latency.

Introduction

Today, the concept of CPU-FPGA hybrid processor has become more and more popula. In this approach CPU and FPGA domains are tightly connected by dedicated interconnections, which makes it possible to enhance the traditional CPU virtualization with the dynamic partial reconfiguration (DPR) technology on FPGA. However, the exploitation of DPR-enhanced virtualization also brings up new challenges. In virtualization, guest OSs are executing in strongly-isolated environments [START_REF] Heiser | The role of virtualization in embedded systems[END_REF]. When DPR accelerators are shared by multiple virtual machines, the allocation of DPR resources and consistency of hardware tasks are critical problems to be solved.

There are some researches exploring DPR technologies with CPU computing, mostly in context of multi-process OSs [START_REF] Agne | Reconos: An operating system approach for reconfigurable computing[END_REF] or computing servers [START_REF] Knodel | Rc3e: Provision and management of reconfigurable hardware accelerators in a cloud environment[END_REF]. In this paper, we propose a dedicated management framework to provide efficient DPR resource sharing in virtual machine system.

Virtualization with DPR Management

Ker-ONE is a lightweight kernel that provides paravirtualization on small-scaled embedded ARM systems. Ker-ONE co-hosts multiple guest OSs in isolated virtual machines (VM) in the user level, which are managed by a virtual machine monitor (VMM). Ker-ONE provides only basic functions such as scheduling, inter-process communication (IPC) and memory management, and ends up with with a small trust computing base (TCB).The architecture of the KER-ONE virtual machine system is depicted in Figure 1. The features of Ker-ONE include:

• Isolated memory space for each VM. The allocation of physical resources can be performed by manipulating VM page tables to allow or forbid VM's access to specific memory spaces.

• Preemptive priority-based round-robin scheduler. In our case, the dedicated DPR resource manager service is given a higher priority than guest OSs, and will preempt other running components as soon as it's scheduled.

• IRQ-based simple IPC Channel, which allows VMs to send messages to other components.

In our system, DPR accelerators are implemented in pre-determined partial reconfiguration regions (PRR) in the FPGA fabric. We proposed a standard interface to all DPR accelerators, so that one PRR can be in multiplexed usage for different accelerators. Between the software and the DPR accelerators, we have introduced an intermediate layer composed by PR interfaces (IF). These IFs are mapped into the address space of VMs as different virtual devices. Each IF is exclusively associated to a specific virtual device in a specific VM. For a certain virtual device, it is mapped at the same address in all VMs, but is implemented with different IFs in lower layer. These IFs are in charge of connecting VMs with the DPR accelerators that actually performs the desired algorithm, so that VM is able to use the virtual devices as normal peripherals. An IF has two states, connected to a certain PRR or unconnected. When an IF is connected, it is considered that the corresponding virtual device is implemented in the PRR and that it is ready to be used. Being in the unconnected state means that the target accelerator is unavailable and the IF registers are mapped as read-only pages. When a VM attempts to use this virtual device by writing to its interface, this action will trap an page-fault exception and can be detected by the VMM. Since VMs' usage of DPR accelerators are independent, our system introduces additional management mechanisms to dynamically handle VMs' request for DPR resources.

In Figure 2 the proposed management mechanism is described. The Virtual Device Manager is a particular software service in an independent virtual machine domain, which aims at allocating DPR resources to VMs. In the static part of the FPGA, a PRR Monitor is created and is in charge of interconnections between IFs and PRRs, and dynamically monitoring DPR accelerators and search for available solutions of DPR resource requests.

Each time that a VM accesses an unconnected IF, VM-M immediately schedules Virtual Device Manager to handle this DPR resource request as Request (vm id, dev id, prio), which is composed of the VM ID, the virtual device ID and a request priority (i.e. calling VM priority). This request is posted to the PPR Monitor on the FPGA side to search for an appropriate allocation solution, which include different methods:

• Assign (prr id): directly allocates PRR (i.e. prr id) to VM. If device dev id is not implemented in this PRR, a Reconfig flag will also be added. • Preempt (prr id): no PRR can be directly allocated, but PRR (i.e. prr id) can be preempted and reallocated. If device dev id is not implemented in this PRR, a Reconfig flag will also be added. • Unavailable: this state means that currently no PRR is available. This unsolved request is then added to the searching list which PPR Monitor keeps searching for solutions. New solutions will be sent to Virtual Device Manager immediately.

Virtual Device Manager then performs the allocation according to the returned solution which may be per-

Evaluation

Our evaluation focuses on the DPR allocation latency, i.e. the delay that occurs before the accelerator is properly allocated and ready to start. This latency comes from several sources: page-table faults handling, IPCs, VM scheduling and Virtual Device Manager execution. According to the experiment measurements, overall overheads for allocation path can be estimated as in Table 1. It can be clearly noticed that direct allocations can be efficiently performed with 3µs latency, whereas in other solutions the system overhead remains still quite low and the major costs come from preemption and reconfiguration, which are inevitable in most DPR systems.

Figure 1 .

 1 Figure 1. The architecture of KER-ONE virtual machine system

2 Figure 2 .

 22 Figure 2. Overview of the DPR management framework in KER-ONE.

Table 1 . Overheads of DPR allocation

 1 In non-immediate solutions (i.e. Reconfig and Preempt), the allocation process can't be completed in one-shot execution, since it needs to wait for the completion of reconfiguration or preemption. In this case, Virtual Device Manager acknowledges VM software by releasing IPC messages, and leaves the PPR Monitor tracking these solutions on the FPGA side, which delivers interrupts to Virtual Device Manager when reconfiguration/prteemption is over.

	Methods	Overheads (µs)
	{Assign}	3.03µs
	{Assign, Reconfig.}	6.76µs + T RF CG
	{Preempt}	5.10µs + Tpreempt
	{Preempt, Reconfig. }	9.96µs + Tpreempt + T RF CG
	formed in several steps: (1) disconnect the target PRR
	from other IFs, and change the memory page as read-only
	in the corresponding VM; (2) connect it to the request-
	ing VM and update the memory page as read/write; (3)
	resumes the requesting VM to the interrupt location and
	continues running.

Conclusion

In this paper we have introduced a framework capable of DPR resource management in a virtual machine system. DPR accelerators are mapped as ordinary devices in each VM. Through dedicated memory management, our framework automatically detects the request for DPR resources and allocates them dynamically with low overheads.