\n(AAAS, 1993, at http:\/\/www.project2061.org\/\/<\/a><\/u>
\n
\n<\/a>and NRC, 1996, at http:\/\/www.nap.edu\/catalog\/4962.html<\/a><\/u>
\n). Third, faculty and students alike are interacting in new ways
\nafforded by digital technologies. Faculty and students have virtual
\ndiscussions related to course content, advice, and counseling in a
\nwide variety of times and places through via email, cell phones,
\npagers, and features of the web. Faculty and students now produce
\ndocuments with more information and in far more diverse formats as
\na result of desktop publishing, online libraries and databases, and
\nfile transfer capabilities. The pervasiveness of digital
\ntechnologies motivates a thorough review of technological impacts
\non curriculum and instruction in science teacher education.<\/p>\n
The following technology guidelines for science education are Technology should be introduced in the context of Technology should address worthwhile science with Technology instruction in science should take Technology should make scientific views more Technology instruction should develop students’ 1. The first principle is centered on the notion that technology This approach is backwards. Teaching a set of technology or If the purpose of technology in science teaching is to enhance Recent media coverage of the impacts of El Ni\u00f1o has made Such an activity supports the development of skills typically 2. Much has been learned about effective science instruction since Content-based activities using technology should be used in the Furthermore, activities involving technology should make It is clear from the Standards<\/i> (NRC, 1996) that “student Technological support for inquiry is not the implementation of The previously described El Ni\u00f1o project is an example of \u2026a Such criticism, while commonly applied to traditional curricular An extension of the El Ni\u00f1o activity that also Throughout this student-centered process, new teachers see While seeing science presented in an authentic context, new Modeling the use of technologies in the context of learning 3. Technology instruction in science should take advantage of Technology modeled in science education courses should take Studies have clearly documented the value of technological None of the students interviewed felt that computer experiences Another criteria for assessing instructional design tasks in Using technology to perform tasks that are just as easily or 4. Technology should make scientific views more Many scientifically accepted ideas are difficult for students to I would A large body of literature concerning misconceptions supports Appropriate educational technologies have the potential to make While the phenomenon is part of students’ everyday experiences, Within the context of this type of example, new teachers should An important consideration for all teachers when using 5. Technology instruction should develop understanding of the Despite Western society’s heavy dependence on technology, few Using technologies in learning science provides opportunities Computer modeling of chemical structures leads to the It is important to realize, however, that such understandings Furthermore, students can see how their questions fuel the Technologies are simultaneously tools for learning about science The draft guidelines in this paper have been synthesized from American Association for the Advancement of Science. (1989). American Association for the Advancement of Science. (1993). Baxter, G. P. (1995). Using computer simulations to assess Bell, R. L., Lederman, N. G., & Abd-El-Khalick, F. (in Borich, B. D., & Tombari, M. L. (1997). Educational Bybee, R.W. (1997). Achieving scientific literacy: From Cavalli-Sforza, V., Weiner, A. W., & Lesgold, A. M. (1994). de La Beaujardiere, J., Cavallo, J., Hasler, F., Mitchell, H., Fisher, B. W. (1997). Computer modeling for thinking about and Flick, L. B. (1989). “Probing” temperature and heat. The Flick, L. B. (1993). The meanings of hands-on science. Germann, P., & Sasse, C. M. (1997). Variations in concerns Goodrum, D. (1987). Exemplary teaching in upper primary science Kranzberg, M. (1984). The wedding of science and technology: A Lawson, A. E., Abraham, M. R., & Renner, J. N. (1989). A Lewis, E. L., Stern, J. L., & Linn, M. C. (1993). The effect Marx, R. W., Blumenfeld, P. C., Krajcik, J. S., & Soloway, Matthews, M. R. (1994 ). Science teaching: The role of Minstrell, J. (1982). Explaining the “at rest” condition of an National Research Council. (1996). National science education Novick, S., & Nussbaum, J. (1981). Pupils’ understanding of Palincsar, A. S. (1986). The role of dialogue in providing Pedretti, E., Woodrow, J., & Mayer-Smith, J. (1998). Rogers, L. (1997). New data-logging tools\u2014New Svec, M. T., Boone, W. J., & Olmer, C. (1995). Changes in Sabelli, N. (1992, April). Sharing multiple complementary Schwab, J. (1962). The teaching of science as enquiry. In The Shulman, L. S. (1987). Knowledge and teaching: Foundations of Spector, B., & Lederman, N.G. (1990). Science and Songer, C. & Mintzes, J. (1994). Understanding cellular Thornton, R. K. (1987). Tools for scientific Thornton, R. K., & Sokoloff, D. R. (1990). Learning motion Tobin, K., Treagust, D.F., & Frasier, B.J. (1988). An Wandersee, J.H., Mintzes, J.J, Novak, J.D. (1994). Research on Williamson, V., & Abraham, M. (1995). The effects of Wolpert, L. (1992). The unnatural nature of science. Why APPENDIX A What is El Ni\u00f1o?<\/b><\/span><\/p>\n Try to answer this question using the Internet. Here are some http:\/\/www.elnino.com\/<\/span><\/a><\/u> http:\/\/www.pmel.noaa.gov\/toga-tao\/el-nino-story.html<\/span><\/a><\/u> http:\/\/www.macontelegraph.com\/special\/nino\/html\/nino1mov.htm<\/span><\/a><\/u> http:\/\/members.aol.com\/windgusts\/ElNino.html<\/span><\/a><\/u> <\/a><\/b><\/p>\n APPENDIX B<\/span><\/b><\/p>\n ADDITIONAL EXAMPLES OF USING TECHNOLOGY TO Using Technology to Promote Relevancy<\/b><\/span><\/p>\n Technology-augmented activities should help students perceive The use of motion detectors to graph the position of a student Numerous school science topics can be used to model and resolve Using Technology to Promote Understanding of Scientific A national consensus has established the central role of inquiry 1986). Teachers must also be mindful of the limited experience One of the more difficult aspects of getting students engaged in The Internet offers more free-form opportunities for teachers to Using Technology to Promote Student-Centered Learning<\/b><\/span><\/p>\n A major goal of learning in science is to develop reflective, The TESSI project (Pedretti et al., 1998) integrated the use of instruction that would put the technologies in the hands of A majority of students interviewed in the TESSI study (Pedretti “The teacher always says we have to `learn to learn,’ it’s a In addition to reflecting on the importance of talk in learning <\/a><\/b><\/p>\n How can I tell if the 1997-98 El Ni\u00f1o has 1. First, go to the Regional Climate Center to locate data for http:\/\/www.wrcc.dri.edu\/rcc.html<\/a><\/u><\/p>\n 2. Next, find the average monthly temperature and precipitation Here’s a site where you can find monthly precipitation data for The Western Regional Climate Center is much better for our \u00b7 Select the state for which you want data \u00b7 Scroll down to Temperature in the left frame and select Temperature Listing”<\/p>\n \u00b7 Scroll down to Precipitation in the left frame and 3. Import the two data lists into Microsoft Excel (or a 4. Calculate a separate average for the temperature data for Hint: You might want to click on the 5. Graph three lines on a single graph:<\/p>\n \u00b7 Average + 1 standard deviation<\/p>\n \u00b7 Average -1 standard deviation 6. Where the El Ni\u00f1o year line falls outside your 1 <\/a>
\nintended to provide assistance in designing instruction and to
\nguide applications of technology to support science teacher
\neducation reform, as framed by Benchmarks for Scientific
\nLiteracy<\/i> (AAAS, 1993) and the National Science Education
\nStandards<\/i> (NRC, 1996). The Association for the Education of
\nTeachers in Science (AETS) joins other national associations of
\nteacher educators in mathematics, English, and social studies
\nthrough the National Technology Leadership Initiative to guide
\nthoughtful consideration for how best to use contemporary
\ntechnologies to enhance subject-matter focused educational goals in
\nthe preparation of teachers.<\/p>\nProposed Guidelines for Using Technology in the Preparation
\nof Science Teachers<\/b><\/span><\/h3>\n\n
\nscience content.<\/p>\n<\/li>\n
\nappropriate pedagogy.<\/p>\n<\/li>\n
\nadvantage of the unique features of technology.<\/p>\n<\/li>\n
\naccessible.<\/p>\n<\/li>\n
\nunderstanding of the relationship between technology and
\nscience.<\/p>\n<\/li>\n<\/ol>\n
\nTechnology should be introduced in the context of science
\ncontent.<\/b><\/span><\/p>\n
\nshould not be taught merely for its own sake in the preparation of
\nscience teachers. Features of technology should be introduced and
\nillustrated in the context of meaningful science. In other words,
\ntechnology should be presented as a means, not an end. This
\nprinciple has implications for teaching science content, as well as
\nfor science teacher preparation. For example, preservice teachers
\nin science education programs are often required to take a generic
\neducational technology course taught by an instructional technology
\nexpert. In this class, the preservice teachers are supposed to
\ndevelop a variety of technology-related skills, including the
\nability to use word processors, presentation software,
\nspreadsheets, and the Internet. Preservice teachers typically are
\nthen left to apply their newly developed technology skills to
\nteaching content in their subject area.<\/p>\n
\nsoftware-based skills and then trying to find scientific topics for
\nwhich they might be useful obscures the purpose of learning and
\nusing technology in the science classroom\u2014to enhance the
\nlearning of science. Furthermore, this approach can make science
\nappear to be an afterthought. Preservice teachers are, in essence,
\nleft to develop contrived activities that integrate a set of
\ndecontextualized instructional technology skills into the context
\nof their classroom.<\/p>\n
\nscience teaching and learning (rather than for the technology’s
\nsake alone), a different approach is necessary. For example,
\nteacher educators at Oregon State University and the University of
\nVirginia are collaborating on a project designed to teach Internet
\nand spreadsheet skills to preservice science and mathematics
\nteachers in the context of an exploration of the El Ni\u00f1o
\nweather phenomenon. Considering its impact on local weather and
\nclimate, El Ni\u00f1o holds both interest and relevance to the
\naverage student. Certainly, it has provided meteorologists and
\nclimatologists with a powerful framework for interpreting and
\npredicting weather patterns.<\/p>\n
\nit a familiar scientific topic for students of all ages. However,
\nfact and fiction became confused in the public’s eye as the media
\nbegan blaming El Ni\u00f1o for all sorts of natural and social
\nevents. This hype resulted in a variety of misunderstandings about
\nthe phenomenon. Thus, while most students are familiar with the
\nconcept, few can confidently discuss its causes and impacts.
\nPreservice teachers may be challenged, for example, to use Internet
\nresources to locate accurate information concerning the causes and
\neffects of El Ni\u00f1o (see Appendix A<\/a> ,
\n“What Is El Ni\u00f1o?” Background Resources).<\/p>\n
\naddressed in educational technology courses, including using the
\nInternet to locate relevant information and discriminating between
\nuseful and non-useful information. It also sets the stage for
\ndiscussion of the advantages and concerns of student use of the
\nInternet. Where it differs from the traditional approach is that
\nthese lessons are situated in the context of learning science.<\/p>\n
\nTechnology should address worthwhile science with appropriate
\npedagogy.<\/b><\/span><\/p>\n
\nthe emergence of science education as a field in the 1950s.
\nTeaching science for understanding, instead of for rote
\nmemorization, requires students to be active participants who are
\nengaged in asking questions, observing and inferring, collecting
\nand interpreting data, and drawing conclusions (AAAS, 1993; Bybee,
\n1997; Goodrum, 1987; Matthews, 1994; NRC, 1996; Tobin, Treagust,
\n& Frasier, 1988). In essence, teacher education courses should
\nemphasize methods for providing students with opportunities to
\ndo<\/i> science, in addition to learning the facts and concepts
\nof science.<\/p>\n
\nprocess of modeling effective science teaching for new teachers.
\nThus, appropriate uses of technology should enhance the learning of
\nworthwhile science concepts and process skills, as well as reflect
\nthe nature of science. This guideline and Guideline 1 are based on
\nthe same principle that science should be learned in a meaningful
\ncontext. Additional work has been done related to this important
\nguideline, and Appendix B<\/a><\/b> contains a
\nmore extended review.<\/p>\n
\nappropriate connections to student experiences and promote
\nstudent-centered, inquiry-based learning. Activities should support
\nsound scientific curricular goals and should not be developed
\nmerely because technology makes them possible. Indeed, the use of
\ntechnology in science teaching should support and facilitate
\nconceptual development, process skills, and habits of mind that
\nmake up scientific literacy, as described by the National
\nScience Education Standards<\/i> (NRC, 1996) and Project 2061<\/i>
\n(AAAS, 1993).<\/p>\n
\ninquiry in the science classroom encompasses a range of activities”
\n(p. 33) that are scaffolded by the teacher. Teachers scaffold
\nstudent engagement in inquiry by providing opportunities for,
\nobserving, collecting data, reflecting on their work, analyzing
\nevents or objects, collaborating with teacher and peers,
\nformulating questions, devising procedures, deciding how to
\norganize and represent data, and testing the reliability of
\nknowledge they have generated.<\/p>\n
\none application but a bundle of applications (Germann & Sasse,
\n1997). Consequently, teacher education courses must make
\nappropriate pedagogy visible through the complex interactions among
\nstudents and classroom technologies. Technology can support student
\ninvestigations and direct collection and presentation of data
\nthrough real-time data collection via microcomputer based
\nprobeware. PowerPoint or spreadsheet functions support
\npresentations that demonstrate the relationship between hypothesis
\nand data. Further manipulations of the display can help students
\nformulate conclusions based on data. For example, by examining
\nvarious graphical formats, students can be guided to think about
\nimplications by looking for trends, identifying categories, or
\nmaking comparisons. Through microteaching environments and
\nsupervised experience, new teachers should become aware of how
\napplications of technology help students share and collaborate in
\nbuilding their knowledge of science and scientific inquiry.<\/p>\n
\na project in a methods course for modeling the blending of
\nworthwhile science with appropriate pedagogy. Searching the Web to
\nlocate information about the El Ni\u00f1o phenomenon is a typical
\nway the Internet is used in K-12 and higher education classrooms.
\nNew teachers learn what science has to say about the concept of El
\nNi\u00f1o, as well as how to use the Internet to locate current
\ninformation. However, if teaching stops here, teachers do not
\ndevelop the appropriate pedagogy of scaffolding student
\nparticipation in scientific inquiry. Without the follow-through to
\ninclude inquiry, such an approach may be criticized for conveying
\nthe products of scientific investigation without due attention to
\nthe processes of how scientific knowledge is produced, and the
\ntentative nature of the knowledge itself. As Schwab commented in
\n1962, science is too commonly taught as<\/p>\n\n
\nnearly unmitigated rhetoric of conclusions in which the current and
\ntemporary constructions of scientific knowledge are conveyed as
\nempirical, literal, and irrevocable truths (in which students are
\nasked) to accept the tentative as certain, the doubtful as
\nundoubted, by making no mention of reasons or evidence for what it
\nasserts. (p. 24)<\/span><\/p>\n<\/blockquote>\n
\nmaterials, is just as appropriate to common usage of the Internet
\nin schools today.<\/p>\n
\nincorporates inquiry would start with students asking questions
\n(see Appendix C<\/a> , El Ni\u00f1o Project). Most
\nstudents are curious to know whether El Ni\u00f1o actually
\nimpacted local weather\u2014one aspect of this project in which
\nstudents also find relevancy. It turns out that historical and
\ncurrent weather data are available on the web, and students can use
\nthese data to support an answer to their question. They will not
\nfind the answer handed to them on a silver platter, however. Once
\nthey locate the data, they will find they need to organize and
\nmanipulate it so they can reach and support a conclusion.<\/p>\n
\nscience taught in a manner consistent with the way scientists do
\ntheir work. They ask a scientific question and devise a method for
\nanswering the question. They collect and organize data. They reach
\nconclusions based on that data, and they share their conclusions
\nwith their peers. Furthermore, by discussing the details of the
\ndata and the various approaches to analyzing the data, students
\nhave opportunities to consider the tentative nature of scientific
\nknowledge.<\/p>\n
\nteachers also learn to use web-based databases, import and export
\ndata sets, use spreadsheets to calculate summary statistics and
\nconstruct tables and graphs, and use word processing and\/or
\npresentation software. Thus a bundle of applications (Germann &
\nSasse, 1997) is learned in the context of appropriate inquiry-based
\nscience instruction.<\/p>\n
\nscience is critical in teacher education for another reason. A
\ncommon maxim in teacher preparation is that “teachers teach the way
\nthey were taught.” Experience has shown that few preservice
\nteachers are able to make the intellectual leap between learning to
\nuse technology out of context in their teacher preparation programs
\nand using it in the context of teaching science in the classroom.
\nTeachers need to see specific examples of how technology can
\nenhance science instruction in their content areas before they can
\nhope to appropriately integrate technology in their own
\ninstruction.<\/p>\n
\nthe unique features of technology.<\/b><\/span><\/p>\n
\nadvantage of the capabilities of technology and extend instruction
\nbeyond or significantly enhance what can be done without
\ntechnology. New teachers should experience technology as a means of
\nhelping students explore topics in more depth and in more
\ninteractive ways. An evaluation study of the Technology-Enhanced
\nSecondary Science Instruction (TESSI) project (Pedretti,
\nMayer-Smith, & Woodrow, 1998) documented the impact of
\ntechnologies integrated at many levels. A preservice methods course
\ncould critically examine the content and outcomes of this study as
\na way of applying unique features of technology for learning
\nscience. For example, students in TESSI classrooms ran virtual labs
\nand demonstrations using the technology to slow down the action and
\nrepeat complex activity. Students were able to rerun virtual force
\nand motion demonstrations and follow how each step was represented
\non the screen in graphical form. Students in the methods course
\ncould discuss how well these examples utilize unique technological
\nfeatures.<\/p>\n
\ncapabilities for enhancing the presentation of complex or abstract
\ncontent, such as computer visualization techniques (Baxter, 1995;
\nLewis, Stern, & Linn 1993). However, a concurrent concern is
\nthat novelty and sophistication of modern technologies might
\ndistract or even mislead students in understanding science concepts
\nthat are the target of instruction. Discussion in the methods class
\ncould continue with a critical look at technological applications
\nto assess whether their capabilities supported or detracted from
\nlearning opportunities. An objective of the TESSI project was to
\ndocument the roles and perspectives of learners, teachers, and
\nresearchers participating in the project (Pedretti et al., 1998).
\nOne hundred forty-four students were either interviewed or surveyed
\nafter completing one school year of physics or general science in
\nthe project. Classroom instruction involved student use of (a)
\nsimulations to extend understanding of physics concepts; (b) laser
\ndiscs, video tape, and CDs; (c) real-time data collection and
\ngraphical analysis tools associated with computer-interfaced probes
\nand sensors; (d) computer analysis of digitized video; (e)
\npresentation software; and (f) interactive student assessment
\nsoftware. A goal of instructional design was to employ technology
\nto enhance the teacher’s role in the classroom, not to replace it.
\nDiscussion of this study and others like it helps establish this
\ncentral goal that should be used in the assessment of instructional
\ndesign and implementation in teacher education courses.<\/p>\n
\nshould entirely replace the “doing” and “seeing” of actual
\nlaboratory or in-class demonstrations. They were clear in stating
\nthat computer technologies and hands-on lab experiences play a
\ncomplementary role, so that the actual event under study, such as a
\nwave propagating down a spring, can be perceived as a concrete
\nevent then analyzed by appropriate simulations. Cognizant of
\nbalancing technological enhancements with checks of student
\nunderstanding, the teachers designed study guides that kept
\nstudents mindful of instructional goals, integrated technology with
\nteacher-direct instruction, and prompted student self-evaluation
\nthrough small-group reviews and conferences with a teacher.<\/p>\n
\nmethods courses is that taking advantage of technology does not
\nmean using technology to teach the same scientific topics in
\nfundamentally the same ways as they are taught without technology.
\nSuch applications belie the usefulness of technology. Students in
\nthe Pedretti et al. (1998) study took tests on computers. The
\nsoftware was able to score and give general feedback more quickly
\nthan a teacher-scored test. More sophisticated, experimental
\nsoftware is being designed to provide structured guidance as
\nstudents analyze and interpret data (Cavalli-Sforze, Weiner, &
\nLesgold, 1994, http:\/\/advlearn.lrdc.pitt.edu\/<\/a><\/u>
\n). Through an Argument Representation Environment, the prototype
\nsoftware helps students construct and propose theories and guides
\nindividuals or groups in designing is experimental software
\nhighlights another issue for science methods instructors: Different
\ntypes of software will require different kinds of support for new
\nteachers. For instance, course activities and discussion should
\nguide new teacher understanding of the processes of coding and
\nlayering of data in ArcView in order to appreciate the scientific
\nmeaning in ArcView graphics (see http:\/\/www.esri.com\/industries\/k-12\/k-12.html<\/a><\/u>
\n
\n<\/a>). In taking advantage of the real-time graphing capabilities
\nusing probeware and computers, researchers have found that college
\nstudents preparing to be elementary teachers must be more carefully
\ntaught how to interpret graphs (Svec, Boone, & Olmer,
\n1995).<\/p>\n
\neven more effectively carried out without technology may actually
\nbe a hindrance to learning. Such uses of technology may convince
\nteachers and administrators that preparing teachers to use
\ntechnology is not worth the extra effort and expense when, in fact,
\nthe opposite may be true.<\/p>\n
\naccessible.<\/b><\/span><\/p>\n
\nunderstand due to their complexity, abstract nature, and\/or
\ncontrariness to common sense and experience. As Wolpert (1992)
\naptly commented,<\/p>\n\n
\nalmost contend that if something fits in with common sense it
\nalmost certainly isn’t science. The reason again, is that the way
\nin which the universe works is not the way in which common sense
\nworks: the two are not congruent. (p.11)<\/span><\/p>\n<\/blockquote>\n
\nthe notion that learning science is often neither straightforward
\nnor consistent with the conceptions students typically construct
\nfrom everyday experiences (Minstrell, 1982; Novick & Nussbaum,
\n1981; Songer & Mintzes, 1994; Wandersee, Mintzes, & Novak,
\n1994; among many others). Whether described as misconceptions or
\nsimply non-intuitive ideas in science (Wolpert, 1992), teachers are
\nfaced with concepts that pose pedagogical conundrums. New teachers
\nmay not even recognize that these instructional puzzles exist
\nunless they are made explicit through their teacher education
\ncourse work. Developing the skills for making scientific views more
\naccessible is an example of what Shulman (1987) called developing
\n“pedagogical content knowledge.” The profession of teaching,
\nShulman argued, may be distinguished from other disciplines by the
\nknowledge that teachers develop linking knowledge of content with
\nknowledge of instruction, knowledge of learners, and knowledge of
\ncurriculum. Developing new teacher awareness of the pedagogical
\ncontent knowledge domain and how to add to that knowledge is a
\ncentral goal of science teacher education.<\/p>\n
\nscientific concepts more accessible through visualization,
\nmodeling, and multiple representations. Secondary teachers may have
\nexperienced examples of these technologies in college science
\ncourses. Elementary teachers may have had limited experiences in
\ncollege science. Teacher education course work has the task of
\nproviding experiences and linking previous experience with
\ntechnologies whose purpose it is to provide representations of
\nconcepts that are difficult to represent in everyday experience.
\nFor example, kinetic molecular theory, an abstract set of concepts
\ncentral to the disciplines of physics and chemistry, may be easier
\nfor students to understand if they can see and manipulate
\nrepresentations of molecules operating under a variety of
\nconditions. Williamson and Abraham (1995) found support for this in
\ntheir investigation into the effectiveness of atomic and molecular
\nbehavior simulators in a college chemistry course. In this study,
\natomic\/molecular simulations were integrated into the instruction
\nof two groups of students, while a third group received no computer
\nanimation treatment. The two simulation treatment groups achieved
\nabout one half standard deviation higher scores on assessments of
\ntheir understandings of the particulate nature of chemical
\nreactions. The authors concluded that the simulations increased
\nconceptual understanding by helping students form their own dynamic
\nmental models.<\/p>\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/doppler.jpg\")
<\/a> Science education courses
\nshould challenge teachers to analyze their teaching experience for
\npedagogical conundrums, the concepts that are inherently difficult
\nto present to students and\/or difficult for students to understand.
\nOnce identified, the pedagogical task is to select appropriate
\nteaching strategies and representations of content to address these
\ntopics. Digital technologies are an important category of options
\nfor approaching these conundrums. For example, a familiar but
\nabstract science concept taught in secondary physical science
\nclasses is the Doppler effect. The Doppler effect is commonly
\ndefined as the change in frequency and pitch of a sound due to the
\nmotion of either the sound source or the observer (see Video 1<\/a> ).<\/p>\n
\nits explanation is neither easily visualized nor commonly
\nunderstood. This difficulty stems from the invisible nature of
\nsound waves and the fact that traditional representations are
\nlimited to static figures of the phenomenon, which by definition
\ninvolves movement.<\/p>\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/FlickHE9.jpg\")
<\/a> Computer simulations are
\nable to get past these limitations by simulating the sound waves
\nemitted by moving objects (see Video 2<\/a> ). Being able to see
\nrepresentations of the sound waves emitted by moving objects
\npresents new opportunities for understanding by offering learners
\nmultiple epresentations. Simulations also allow students to
\nmanipulate various components, such as the speed of the object, the
\nspeed of sound, and the frequency of the sound emitted by the
\nobject. Such interaction encourages students to pose questions, try
\nout ideas, and draw conclusions (see Appendix<\/a><\/u> D, Doppler Effect
\nSimulator and Activities).<\/p>\n
\nbe challenged to identify appropriate science pedagogy, as
\ndescribed in Guideline 2.<\/p>\n
\nsimulations as models for real phenomena is that, while simulations
\ncan be powerful tools for learning science, students must not
\nmistake a simulation \u2014meant to make a concept more
\naccessible\u2014for the actual phenomenon. Students must
\nunderstand that a sophisticated computer graphic for molecular
\nmotion, the Doppler effect, or any other phenomenon is still only a
\nmodel. Therefore, it is critical that preservice teachers be given
\nexplicit opportunities to reflect on the nature of scientific
\nmodels and the role they play in the construction of scientific
\nknowledge, as well as encouragement and examples for how to address
\nthese concepts in their own instruction (Bell, Lederman, &
\nAbd-El-Khalick, in press).<\/p>\n
\nrelationship between technology and science.<\/b><\/span><\/p>\n
\nteachers actually understand how technology is used in science. Nor
\ncan they adequately describe the relationship between science and
\ntechnology. For example, one of the most common definitions of
\ntechnology used in schools today is “applied science” (Spector
\n& Lederman, 1990). While this familiar definition seems
\nreasonable at first glance, it ignores the fact that the history of
\ntechnology actually precedes that of Western science (Kranzberg,
\n1984) and that the relationship between science and technology is
\nreciprocal (AAAS, 1989). A more appropriate understanding of
\ntechnology for inclusion in teacher education courses is the
\nconcept of technology as knowledge (not necessarily scientific
\nknowledge) applied to manipulate the natural world and emphasizes
\nthe interactions between science and technology.<\/p>\n
\nfor demonstrating to new teachers the reciprocal relationship
\nbetween science and technology. Extrapolating from technology
\napplications for classrooms, new teachers can develop an
\nappreciation for how advances in science drive technology, and in
\nturn, how scientific knowledge drives new technologies.<\/p>\n
\ndevelopment of new materials with numerous uses. In reciprocal
\nfashion, high quality computer displays and faster computers make
\npossible types of scientific work impossible before such advances.
\nThis leads to new ideas in science.<\/p>\n
\nare unlikely to be learned implicitly through using technology
\nalone. Rather, new teachers must be encouraged to reflect on
\nscience and technology as they use technology to learn and teach
\nscience., When using microscopes, whether the traditional optical
\nmicroscopes or the newer digital versions (see http:\/\/IntelPlay.com\/home.htm<\/a><\/u>
\n), teachers can be encouraged to think about how science influenced
\nthe development of the microscope and the microscope, in turn,
\ninfluenced the progress of science. For example, the modern
\ncompound microscope began as a technological development in the
\nfield of optics in the 17th century. The instrument created a
\nsensation as early researchers, including Antoni van Leeuwenhock
\nand Robert Hooke, used it to uncover previously unknown
\nmicrostructure and microorganisms. This new scientific knowledge
\nled to new questions. For example, where do these microorganisms
\ncome from? How do they reproduce? How do they gain sustenance? Such
\nquestions, in conjunction with advances in optics, led to the
\ndevelopment of ever more powerful microscopes, which in turn,
\nbecame the vehicles for even more impressive discoveries. The cycle
\ncontinues to modern times with the invention of the electron
\nmicroscope and its impact on knowledge in the fields of medicine
\nand microbiology.<\/p>\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/stener.jpg\")
<\/a> Microteaching and supervised
\npracticum experiences should help preservice teachers recognize
\nthat when students are making new discoveries of their own with
\nmicroscopes, they are well positioned to understand the reciprocal
\nrelationship between technology and science. For instance,
\nfifth-grade students who are recording video footage of
\nmicroorganisms with the digital microscope can easily appreciate
\nthe concept that new discoveries lead to new questions, as their
\ncuriosity is piqued by their observations of the miniature world
\nthat exists in a drop of pond water (see Video 3<\/a> ).<\/p>\n
\ndesire for new technologies, as they experience the limitations of
\nthe microscopes available to them. A skilled teacher can exploit
\nthe resulting “teachable moment” to encourage students to consider
\nhow their experiences with the technology relate to those of real
\nscientists.<\/p>\n
\nand examples of the application of knowledge to solve human
\nproblems .<\/i><\/b> When new teachers understand technologies
\nas a means of solving human problems, they can be made aware that
\ntechnologies come with risks as well as benefits. This feature of
\ntechnology should be represented in instructional objectives and be
\nvisible in lesson plans and other relevant assignments. For
\nexample, efficiencies of storage and retrieval of information have
\nthe associated risks of losing large quantities of data in damaged
\ndisks, system malfunctions, or incorrect actions on the part of
\nusers. Uses of technology in teacher education courses can
\nemphasize how technologies produce trade-offs, for instance,
\nbetween gaining more sources of knowledge through the Internet and
\nCDs while at the same time creating a greater expenditure of time
\nand effort sorting appropriate, high quality information.<\/p>\nSummary<\/b><\/span><\/h3>\n
\nknowledge of research, K-12 teaching experience, and teaching
\nexperience in science teacher education with technology. They have
\nbeen drafted to be consistent with national reform goals in science
\neducation by examining how these goals might be furthered through
\nthe use of modern technologies. Thoughtful reflection on and
\ndiscussion about these guidelines by a broad range of educators,
\nbased on knowledge of diverse areas of educational research and a
\nbroad base of teaching experiences, will deepen understanding of
\nhow technologies can improve science teaching and the preparation
\nof new teachers of science. Future revisions of the guidelines will
\nreflect the ongoing discussion in Contemporary Issues in
\nTechnology and Teacher Education<\/i> that this article is intended
\nto generate.<\/p>\nReferences<\/b><\/span><\/h3>\n
\nProject 2061: Science for all Americans.<\/i> Washington, DC:
\nAuthor.<\/p>\n
\nBenchmarks for science literacy<\/i> . New York: Oxford
\nUniversity Press: Author.<\/p>\n
\nhands-on science learning. Journal of Science Education and
\nTechnology, 4<\/i> , 21-27.<\/p>\n
\npress). Developing and acting upon one’s conception of the nature
\nof science: A follow-up study. Journal of Research in Science
\nTeaching.<\/i><\/p>\n
\npsychology: A contemporary approach. New York: Longman.<\/p>\n
\npurposes to practices<\/i> . Portsmouth, NH: Heineman.<\/p>\n
\nSoftware support for students engaging in scientific activity and
\nscientific controversy. Science Education, 78<\/i> , 577-599.<\/p>\n
\nO’Handley, C., Shiri, R., & White, R. (1997). The GLOBE
\nvisualization project: Using WWW in the Classroom. Journal of
\nScience Education and Technology, 6<\/i> , 15-22.<\/p>\n
\ncontrolling variables. School Science Review, 79<\/i> ,
\n87-90.<\/p>\n
\nComputing Teacher, 17<\/i> (2), 15-19. Reprinted in the Fourth
\nAnnual Conference Issue 1990-1991.<\/p>\n
\nJournal of Science Teacher Education, 4<\/i> (1), 1-8. Also
\nreprinted in Rezba, R. (1994). Readings for teaching science in
\nelementary and middle schools<\/i> . Dubuque, IA: Kendall\/Hunt
\nPublishing Company.<\/p>\n
\nand attitudes of science teachers in an educational technology
\ndevelopment program. Journal of Computers in Mathematics and
\nScience Teaching, 16<\/i> , 405-423.<\/p>\n
\nclasses. In K. Tobin & B.J. Fraser (Eds.), Exemplary
\npractice in science and mathematics teaching<\/i> . Perth: Curtin
\nUniversity of Technology.<\/p>\n
\nvery modern marriage. Technology & Science<\/i> . Davidson
\nCollege, NC, 27-37.<\/p>\n
\ntheory of instruction. National Association for Research in
\nScience Teaching Monograph<\/i> (No. 1).<\/p>\n
\nof computer simulations on introductory thermodynamics
\nunderstanding. Educational Technology,<\/i> 33, 45-58.<\/p>\n
\nE., 1997). Enacting project-based science. The Elementary School
\nJournal, 97<\/i> , 431-458.<\/p>\n
\nhistory and philosophy of science.<\/i> New York: Routledge.<\/p>\n
\nobject. Physics Teacher, 20<\/i> , 10-14.<\/p>\n
\nstandards<\/i> . Washington, D.C.: Author.<\/p>\n
\nthe particulate nature of matter: A cross-age study. Science
\nEducation, 65<\/i> , 187-196.<\/p>\n
\nscaffolding instruction. Educational Psychologist, 21<\/i> ,
\n73-98.<\/p>\n
\nTechnology, text, and talk: Students’ perspectives on teaching and
\nlearning in a technology-enhanced secondary science classroom.
\nScience Education, 82<\/i> , 569-589<\/p>\n
\ninvestigations. School Science Review, 79<\/i> , 61-68.<\/p>\n
\npreservice elementary teachers physics course. Journal of
\nScience Teacher Education, 6<\/i> , 79-88.<\/p>\n
\nrepresentations in teaching<\/i> . Paper presented at the meeting of
\nthe American Educational Research Association, San Francisco.<\/p>\n
\nteaching of science<\/i> (pp. 1-103). Cambridge, MA: Harvard
\nUniversity Press.<\/p>\n
\nthe new reform. Harvard Educational Review, 57<\/i> , 1-22.<\/p>\n
\ntechnology as human values<\/i> . Dubuque, IA: Kendall\/Hunt.<\/p>\n
\nrespiration: An analysis of conceptual change in college biology.
\nJournal of Research in Science Teaching, 31<\/i> , 621-637.<\/p>\n
\nthinking\u2014Microcomputer-based laboratories for physics
\nteaching. Physics Education, 22<\/i> , 230-238.<\/p>\n
\nconcepts using real-time microcomputer-based laboratory tools.
\nAmerican Journal of Physics, 58<\/i> , 858-867.<\/p>\n
\ninvestigation of exemplary biology teaching. American Biology
\nTeacher, 50<\/i> , 142-147.<\/p>\n
\nalternative conceptions in science. In D.L. Gabel (Ed.),
\nHandbook of Research on Science Teaching and Learning<\/i> . New
\nYork: Macmillan.<\/p>\n
\ncomputer animation on the particulate mental models of college
\nchemistry students. Journal of Research in Science Teaching,
\n32<\/i> , 521-534.<\/p>\n
\nscience does not make (common) sense<\/i> . Cambridge, MA: Harvard
\nUniversity Press.<\/p>\n
\n<\/span>WHAT IS EL NI\u00d1O? BACKGROUND
\nRESOURCES<\/span><\/b><\/p>\n![\"](\"flick_p23.gif\")
<\/b><\/p>\n
\nweb sites that might help.<\/p>\n
\nThis site briefly describes El Ni\u00f1o in laymen’s
\nterms.<\/p>\n
\nThis site provides more detailed and technical discussion of the
\nEl Ni\u00f1o phenomenon. It includes some very good graphics.<\/p>\n
\nThis site combines some basic information with a neat
\ndownloadable movie clip with sound.<\/p>\n
\nThis is another site that includes basic discussion of the El
\nNi\u00f1o phenomenon.<\/p>\n
\nADDRESS WORTHWHILE SCIENCE WITH APPROPRIATE PEDAGOGY<\/span><\/b><\/p>\n
\nthe relevance of science to their personal experiences. Students
\nare exposed to sophisticated computer representations of weather
\ndata every day through television weather reports. These reports
\nuse integrated displays of cloud patterns, moisture levels, wind,
\nbarometric pressure, and temperature. Often these representations
\ngo unappreciated or misunderstood. The Internet and desktop
\ncomputers can help students see the meaning of these data by
\nconnecting students with sources of real data representing weather
\nin their region of the country. Further programs offer
\nopportunities for students to contribute data as part of a larger
\npicture of national and global climate. The Global Learning and
\nObservations to Benefit the Environment (GLOBE) project is a
\nmultinational program of science education (de La Beaujardiere et
\nal., 1997). Students enter weather data, and graphical tools allow
\nthem to manipulate how the data from the region, country, or world
\nis represented (see http:\/\/www.globe.gov\/<\/a><\/u> ). The
\ninstructional sequence and outcomes might be outlined as follows:
\n(a) student experience is translated into weather measurements; (b)
\nstudents enter measurements into a worldwide Internet data base;
\n(c) students manipulate data and forge meaning under the guidance
\nof a classroom teacher; and (d) student understanding and
\nappreciation of personal experiences are enhanced.<\/p>\n
\nwalking toward or away from the detector helps students experience
\nan analytical expression of a common experience. Even at the
\ncollege level, this type of interactive learning tool enhances
\nstudent understanding of velocity and acceleration (Svec, Boone,
\n& Olmer, 1995; Thornton, 1987; Thornton & Sokoloff, 1990).
\nOther devices record temperature in real time and represent it on
\nthe screen as a thermometer or temperature versus time graph.
\nClassroom work demonstrates that students are better able to
\nseparate personal sensations of “hot” and “cold” from physical
\nmeasurements of temperature (Flick, 1989).<\/p>\n
\nsituations arising in the physical, biological, environmental,
\nsocial, and managerial sciences. The use of extended student
\nprojects formed the basis for Project-Based Science (PBS) that
\nfocused on student-designed problems and investigations (Marx,
\nBlumenfeld, Krajcik, & Soloway, 1997). PBS made extensive use
\nof software for accessing information and data manipulation to
\nsupport student work on complex problems. Teachers guided students
\nin identifying problems and carrying out procedures for addressing
\nthose problems. By focusing on the personal significance of
\nclassroom tasks, teachers, supported by computer tools for
\naccessing relevant information, helped students connect science
\nconcepts to their own lives.<\/p>\n
\nInquiry<\/b><\/span><\/p>\n
\nin science education. “Scientific inquiry is at the heart of
\nscience and science learning” (NRC, 1996, p.15). Use of technology
\nshould support student understanding of scientific inquiry and how
\nscientific investigations are conceived and conducted. Helping
\nstudents understand the meaning behind a scientific approach to
\nproblem solving requires developing student skills with forms of
\nscientific thinking. To accomplish this task, teachers must provide
\ninstructional scaffolding to support student thinking (while
\nremaining aware of developmental constraints (Palincsar,<\/p>\n
\nstudents have in systematically thinking through problems. Computer
\ntools are beginning to offer support for this type of complex
\ninstruction. A case study of a teacher proficient with a computer
\nmodeling program documented development of student thinking skills
\nnecessary for controlling variables (Fisher, 1997). The computer
\nmodel allowed students to isolate and control variables in ways
\nthat may be obscured in direct, lab experience, due to
\nuncontrollable variables or the untrained observational skills of
\nstudents. Another case study showed how software for logging and
\nmanipulating data encouraged students to reflect on the meaning of
\ndata and choose appropriate representations (Rogers, 1997). In the
\nhands of skilled teachers, modern information technologies can be
\ntools for focusing instruction and providing students with an
\ninteractive, educational environment for thinking about and doing
\nscientific investigations.<\/p>\n
\nscientific inquiry is posing questions that are meaningful to
\nstudents yet open to scientific inquiry. Texts often lead students
\nto think of inquiry as an algorithm, the mythic “scientific
\nmethod.” This is especially true if teachers do not mediate text
\npresentations with supplementary instruction about scientific
\ninquiry. If students cannot see the creative, problem-solving side
\nof scientific work, they often do not believe scientific
\ninvestigations are meaningful. Addressing this important
\nepistemological question was the goal of a project to develop a
\nsoftware environment for scaffolding scientific activity.
\nResearchers at the Learning Research and Development Center at the
\nUniversity of Pittsburgh have taken as their initial focus the
\ndevelopment of tools for displaying and evaluating scientific
\ncontroversies (Cavalli-Sforza, Weiner, & Lesgold, 1994). The
\nsoftware design effort is developing tools for the graphical
\ndisplay of arguments, evidence, and supporting knowledge. For
\nexample, interacting through a system of menus and graphical
\nrepresentations, students can seek evidence in support of a
\nparticular theory for the extinction of dinosaurs. The software
\nwill advise students of particular data, such as the fossil record,
\nand state why it supports or does not support a particular theory.
\nThe computer scaffolding acts as resource for students and an
\ninstructional tool for the teacher in developing student
\nunderstanding of the value of theories in posing scientific
\nquestions and the role of theories in establishing the meaning of
\ndata.<\/p>\n
\ndevelop student thinking skills that support inquiry. The display
\nof earthquake data on a world map can be used to guide students to
\nquestion why geographic locations form the patterns they do.
\nThrough discussion that develops understanding of how the data are
\ngathered and represented in the visual database, students can be
\nprompted to design investigations that lead them to seek related
\ndata, such as occurrences of volcanic activity (see, for example,
\nhttp:\/\/volcano.und.nodak.edu\/<\/a>
\nand http:\/\/gldss7.cr.usgs.gov\/neis\/bulletin\/bulletin.html<\/a><\/u>
\n
\n<\/a>.<\/p>\n
\nindependent learning in students. The focus on science as inquiry
\nimplies taking contemporary science education beyond teaching just
\nthe science processes of the 1960s and 70s. “Inquiry is a step
\nbeyond science as process. The Standards combine the use of
\nprocesses of science and scientific knowledge as they use
\nscientific reasoning and critical thinking” (NRC, 1996, p. 105). In
\na complete science education, students learn relevant bodies of
\nknowledge, ways to conduct scientific inquiry, and the nature of
\nscientific work. To accomplish this complex task, teachers must
\npromote learning cognitive and social skills that make instruction
\nmore student centered.<\/p>\n
\nmultiple technologies. Teachers in the project found that relevant
\nand meaningful use of these technologies required a “departure from
\nthe teacher-centered format which characterizes much of traditional
\nscience instruction” (p. 573). Observations of classroom
\ninstruction revealed high levels of teacher interactions with
\nstudents, including (a) teachers consulting in small group work,
\n(b) teachers directing the use of resources, and (c) purposeful
\ninstruction within the context of larger student projects. More
\nimportant were specific efforts by the teachers to design<\/p>\n
\nstudents. As a result of access to relevant technologies, revised
\ncurricula that took advantage of these technologies, and
\ninstructional designs in which technology played important but
\nsupporting role, student interviews and surveys suggested that
\nstudents gained a stronger sense of purpose and self-direction in
\ntheir classroom work. Students also found traditional materials,
\nsuch as texts, laboratory work, demonstrations, problem sets, and
\nfield work, valuable supplements to classroom learning. Technology
\nwas a catalyst for change, but the energy and direction of change
\ncame from the teachers working with students in new ways that put
\nstudents at the center of the instructional process.<\/p>\n
\net al., 1998) commented about learning and learning how to learn.
\nFor example, students noted the importance of talking with other
\nstudents.<\/p>\n
\nlittle weird but I guess it’s true because we’re learning how to
\nlearn on our own with the different materials that are available,
\nlike through other people. (Shelley, Physics 11, Fall 1995)” (p.
\n585)<\/p>\n
\nscience, 52% of students surveyed or interviewed mentioned the
\nstructure of instruction and teachers’ expressed intentions, and
\nhow these factors affected their approach to learning. These
\nstudents became aware of and acted on teacher goals for learning
\nresponsibility, independence, self-reliance, and problem-solving.
\nThese results may in part be attributed to capable students in high
\nschool science classes and to a large investment in new
\ntechnologies that has temporarily focused attention on these
\nclassrooms. The validity of educational innovations is always
\nlearned over time. TESSI is obtaining these results after 6 years
\nduration of the project and the participation of over 3,000
\nstudents. These effects are long after initial novelty has worn off
\nand after a broad cross-section of students have experienced the
\nprogram.<\/p>\n
\nEL NI\u00d1O PROJECT<\/span><\/b><\/div>\n
\nimpacted a particular region?<\/p>\n
\nthe region you are interested in.<\/p>\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/flick_p31.gif\")
<\/u><\/p>\n
\ndata. The SERC lists monthly averages for entire states.
\nhttp:\/\/water.dnr.state.sc.us\/climate\/sercc\/region_avg_info.html<\/a><\/u><\/p>\n
\nselect cities in several states:
\nhttp:\/\/www.ncdc.noaa.gov\/ol\/climate\/online\/coop-precip.htm<\/a>
\nl<\/u><\/p>\n
\npurposes, but only includes data for the western states.
\n\u00b7 Go to http:\/\/www.wrcc.dri.edu\/<\/u>
\nrcc.html.<\/a> This can be linked to from the Regional Climate
\nCenter site shown in step one.
\n\u00b7 Select Western U.S. Climate Historical Summaries http:\/\/www.wrcc.dri.edu\/climsum.html<\/a><\/u><\/p>\n
\n\u00b7 Select the individual station for which you want data<\/p>\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/flick_p33_1.gif\")
<\/p>\n
\n“Average” under “Monthly<\/p>\n
\nselect “Monthly Totals” under “Monthly Precipitation Listings”
\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/flick_p34_2.gif\")
<\/p>\n
\ncomparable spreadsheet). Since data sets on the Web are typically
\nnot saved in Excel format, you will usually find it necessary to
\nfirst save the data as a *.txt file before you try to open it in
\nExcel. Upon opening the data set in Excel, the program will provide
\na “Data Import Wizard,” which will help you properly format the
\ndata in a few easy steps.<\/p>\n
\neach month. Students will often want to compare the average
\ntemperature data for each month of the entire data set to that of
\nthe El Nino year. This is a good time to discuss the differences
\nbetween an average temperature and a normal temperature range. When
\ncomparing data that vary, it is important that the comparison
\nreflect the variability of the data. Therefore, comparing means
\nalone is not very useful. A better approach is to use some measure
\nof variability about the mean, such as standard deviation, if the
\ndata reflect a normal distribution. If the data distribution is
\nsignificantly skewed, it may be more appropriate to use upper and
\nlower quartile ranges about the median. The important point is that
\nthe comparison reflects the variability of the data, so that we are
\ncomparing a typical<\/i> temperature range to the El Nino year.
\nSo, for example, if the data are normally distributed, you could
\ncalculate the standard deviation for each month. Next, create a row
\nthat calculates the Average + One Standard Deviation, and a
\nseparate row that calculates the Average -One Standard
\nDeviation.<\/p>\n
\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/Flick_icon.gif\"){kind=icon}
button a couple times to decrease the number of decimal
\nplaces.<\/p>\n![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/flick_p35_table.gif\")
<\/p>\n
\n\u00b7 El Ni\u00f1o year in question (make two graphs, one for
\n1997 and one for 1998)
\nFor example, your 1997 graph might look like this: ![\"](\"https:\/\/citejournal.org\/wp-content\/uploads\/2016\/04\/flick_p36_table.gif\")
<\/p>\n
\nstandard deviation boundaries, you can say that the El Ni\u00f1o
\ntemperatures for that month were warmer (or colder) than about 70%
\nof your data. This may be enough to conclude that El Ni\u00f1o
\nhad an effect on that particular region, or you may decide that
\nstronger evidence is necessary. For instance, you may decide that
\nthe El Ni\u00f1o temperature must lie at least 2 standard
\ndeviations from the mean before you are willing to consider the
\ndifference significant). This is a good time to have a discussion
\nabout what it might take for scientists to conclude that El
\nNi\u00f1o had an effect.<\/p>\n
\n<\/span>APPENDIX
\nD<\/span>
\nDOPPLER EFFECT SIMULATOR AND
\nACTIVITIES<\/span><\/b><\/p>\n