Printable Version
Web Link - http://www.cur.org/Publications/AIRE_RAIRE/oregon.asp 


 
Data Driven Inquiry: Reforming the Teaching of Science 101 Through the Use of Instructional Technology 

Gregory D. Bothun, Department of Physics

University of Oregon
Eugene, OR 97403 

The integration of research into the general undergraduate curriculum can take a variety of forms. At the simplest level, it consists of a research professor who is the principal lecturer to a class of students. There seems to be an assumption that students will be molded and inspired by seeing and hearing a researcher. This means of integrating research into undergraduate education remains the dominant one at the University of Oregon, and perhaps at most research universities. At the most advanced level, integration of research refers to students who are earning course credit for doing research with faculty mentors. However, this scheme is very expensive to implement. The resource starved public university can’t come close to providing this kind of learning opportunity for all but a very small percentage of it’s total students. In between the simplest and most advanced levels of integrating research lies a vast continuum. 

In this chapter, we will demonstrate that technology and computer networks can be used to facilitate the integration of research into the curriculum, and provide details of an astronomy course in which students use actual data products. Despite the potential payoff, large-scale implementation of this course and similar courses has not occurred, because of a variety of barriers. Some of these barriers are perceptual, some are financial and many of them emerge from the effort to develop the course itself. I will address some of these barriers because they illustrate general difficulties research universities have with creating a range of learning environments for their students. 

The Scale of the Problem 

Before considering the potential that technology has to transform the teaching and learning experience, it is important to be grounded in reality. First, I want to outline the conditions at a typical public research university of 20,000 students. The university is mandated by the state to accept all reasonably qualified high school graduates. To graduate, students must take several general education courses, including four introductory science courses. If we assume that the average graduation time is ten semesters, then at any given time there will be 8,000 students enrolled in at least one general education science class, and many of these will be in Astronomy 101. 

Typically, an introductory science class for non-majors will enroll thousands of undergrads whose sole purpose is fulfilling a general education requirement. The typical class size is around 150-300 students, and can be higher. In my experience at the Universities of Washington, Michigan and Oregon, this class is an exercise in student seat time and student credit hours generated for the host department. One professor, together with a few TAs, teaches exclusively through lecture presentation and slide shows to the students. The students get their credits and move on. The opportunity to use these classes to actually teach the process of science and to instill science literacy in the students is wasted. As this chapter will show, technology offers a way out of this dilemma, but implementation on the required scale remains a challenge. 

Restructuring the Mass Lecture

A major obstacle towards effective implementation of pedagogical changes is our collective inability to admit the many deficiencies of the mass lecture course. Administrators often favor this sardine can method of instruction because it represents the lowest unit cost to the university. The suggestion that the students don’t really learn anything in this environment seems to carry little weight. Conversations with colleagues who teach these courses reveal another obstacle to change. Approximately 80 percent of the professors I have discussed this problem with believe that students are learning the material directly from the instructor, even when the instructor is speaking to 300 students at a time. Perhaps the meaning of “learning” is being confused with “absorbing.” The remaining 20 percent of instructors readily acknowledge that the mass lecture is a machine for generating student credit hours for their departments and that student learning is really not a primary goal. The first step towards pedagogical change is to be honest about the nature of these courses and the reason for their existence. 

Unfortunately, there is a lot at stake. For many university students nationwide, an introductory physics or astronomy course represents their last formal exposure to science. Because the lecture presentation of predetermined factual material is such a poor representation of science and its practice, not surprisingly, it tends to produce a scientifically illiterate general population with no interest in the process of science. As scientists and educators, we know that the ability to perform unbiased and accurate observations and experiments is crucial to scientific advancement, yet the primary teaching aid in introductory courses is a textbook that usually cannot communicate this vital aspect of science. The real nature of science is a discovery process, yet science is seldom taught in this manner. To teach science as a process, the student has to make an observation or perform an experiment, formulate a hypothesis, then test the predictive power of the hypothesis by performing new experiments. In this way the hypothesis (or model) is either refuted or refined. While physical resources are not available for the mass of students in introductory courses to engage in this practice, the use of robust simulation software is an adequate substitute and provides a dimension of learning that is sorely missing. We need to put the sense of discovery back into the scientific curriculum, and that can be done most practically by using software and simulation. 

Five Reasons why the mass lecture model is broken 

There are many deficiencies in the traditional mode of teaching a large lecture class. These deficiencies can be corrected by the preparation and delivery of a more dynamic, innovative and interactive curriculum that can be developed if adequate resources are provided. 

Student passivity: Because there is little direct contact between students and instructor, a large lecture class encourages passivity in the students. As a consequence, most of the students in these classes remain disinterested and do not gain an adequate understanding of the material. Research shows that students often have preconceptions and naive beliefs about scientific concepts that can prevent them from assimilating new concepts and knowledge. Students’ preconceptions and stereotypes are rarely, if ever, challenged in a lecture of an introductory science class, whose large class size precludes active engagement and experimentation. 

The problem with facts: The standard lecture involves transmission from expert to novice of established facts about the physical world. There is a critical need to engage our introductory science students with student-driven inquiry rather than facts. Memorizing facts and retrieving them appropriately at exam time is certainly not the same as understanding and appreciating the process of science. Getting real data and tools into the hands of students would allow them to duplicate the same steps that the real scientist undertakes in experimentation. 

The one size fits all problem: The lecture mode of presentation is poorly suited to the range of ways that students learn. Cognitive research identifies four distinct learning styles. Concrete learners use direct experience - doing, acting, sensing, and feeling. Abstract learners are skilled at analysis, observation and critical thinking. Active learners are best able to apply new information to facilitate tasks. Reflective learners prefer to think about new information. Traditional delivery-oriented education best serves abstract and reflective learners and denies or limits the active, hands-on, experimental approach that many students require. A single approach to teaching and assessment can lead to failure for many students who would be well served by more diverse approaches. Simulations that allow the students to make mistakes without feeling penalized provide learning opportunities that are effective for many students. 

The syllabus problem: In traditional classes where the instructor is the primary information source, students are led through the curriculum and the textbook to a predetermined outcome. Student success or failure depends on their ability to master or memorize the body of information presented in lectures or in the textbook. I call this syllabus addiction - the class is designed on the basis of a one page listing of topics, and the goal of the course is to get through the topics. Because of the widespread syllabus problem, it is no surprise that most students perceive science as a dry, static body of facts. Paring down the list of topics would make for a far more powerful learning experience if it allowed for student engagement and debate. Ideally, the student should be free to navigate through the course content, with the instructor as a guide and facilitator. At the leading edge of science a rich body of research results is emerging, technology is being pushed to its limits, and a lively debate is ongoing. While a course needs a solid base of reliable knowledge, it should also reflect the richness of active research and the exciting process of data acquisition leading to new knowledge. 

The isolation problem: Large lecture classes have very limited opportunities for cooperative learning. In an ideal world, students would break into small sections centering on experimentation and student-driven inquiry. While there are places where this is done (e.g. Eric Mazure’s work at Harvard) these are the rare exceptions rather than the ubiquitous rule. Of course, establishing a peer learning environment is expensive and few public universities have the necessary funds. Rising enrollments mean that class sizes are not likely to get smaller. In the lecture, students tend to be isolated from one another and therefore cannot benefit from peer learning and collaboration. Such isolation tends to reinforce the notion that students should compete rather than cooperate. In the conventional lecture there are few ways to encourage students to do research, work on projects and papers together, or even communicate with each other. The large lecture format precludes even questioning the material, and this leads ultimately to decreased motivation on the part of science educators who teach these classes. 

Instructional Technology as a Means to Improve Pedagogy

Each of the five ills associated with the mass lecture can be partially, or in some cases, completely mediated with the appropriate use of instructional technology. I will describe how the mass format of Astronomy 101 can be transformed into a real data-driven student learning experience by using software and simulations. Note that this new learning environment makes more work for the students, since the burden of learning shifts to them. Implementation of this scheme has mostly resulted in lower teacher evaluations, probably as a result of the increased workload on the students. However, I would argue that the scholarship of the class has greatly increased and, in the end, that should be the measure of effective teaching. 

Addressing the passivity problem 

Most of Astronomy 101 traditionally consists of showing “pretty pictures.” This is ironic, because astronomical images such as the latest and greatest image from the Hubble Space Telescope are not really pretty pictures, they are digital images with measurable features. Similarly, a spectrum of a star is not an image to be memorized, it is a digital collection of data that you can analyze. The heart of our curriculum reformation movement at the University of Oregon is the construction of data interfaces that allow the student to download and actually measure the data. Since this is done in the JAVA programming language, the very familiar Web browser is the only piece of software that the student has to use. 

We have constructed JAVA based engines that, among other things, allow students to: 

As a standard part of this course, students are forced to analyze real astronomical data. This is a significant amount of work, but it immerses the students in the data. Students work together in groups on activities in the form of standard homework assignments. Emphasis is put on how noise affects the data and the measurements that are made; we have some robust JAVA applets that simulate noise on a detector. The pedagogical goal is for the students to learn about noisy data, signal-to-noise ratios, sparse sampling and the realities of detection. We measure the students’ progress anecdotally by the numbers of e-mail messages asserting that the virtual apparatus is broken because it doesn’t return the same answer as the example in the noise-free textbook. 

By getting data products and an interface for measuring and analyzing the data into the hands of students, instructional technology goes a long way to remove passivity from the learning environment. Students now have to work directly with and think about the data. Interactive data driven exercises should be the main reason for adopting instructional technology as a standard part of any course. Spiffy lectures in PowerPoint, currently the most popular use of instructional technology, pale in comparison to what technology can really offer students. 

Perhaps the best way to illustrate this general approach is to describe in detail an astronomy course at the University of Oregon that focuses on stellar spectroscopy. To maximum technological and collaborative approaches to learning in this course, a wireless laptop classroom was constructed at the university. This classroom has moveable chairs and tables with 40 wireless laptop computers. Students work together in pairs or triplets. 

Our collection of Java applets is designed so that students can work with stellar data and simulations to understand stellar spectroscopy. In the discussion of the applets below, I have included some screen shots, but space limitations preclude showing all the referenced applets. That information, together with a direct link to the applet and lesson plan activity, can be found at http://zebu.uoregon.edu/2003/astr122.html 

An interactive astronomy course: understanding the elements in stellar spectra 

Applet I - Spectra of the elements: This is a relatively simple applet that allows the students to select a chemical element and display its spectra in a form similar to that in standard textbooks (Hydrogen is shown in Figure 1). Students can then highlight the spectral lines and read their wavelengths in units of Angstroms. Color-coding in the background shows students if the line is in the blue or red part of the optical spectrum. The applet shows only the astrophysically relevant spectra lines of an element so students can familiarize themselves with the element’s strongest spectral lines.

Figure 1: The atomic spectrum of Hydrogen is shown above a panel where spectra for other elements can be selected.

 
Applet II - Understanding atomic emission: In this applet, the learning goals are to demonstrate that atoms’ spectra are directly related to the photon emissions derived from specific energy level transitions and to learn that different atoms have different kinds of spectra. To accomplish this, the electrons of virtual atoms are assigned energy levels and probabilities for specific energy transitions. Students move the electron from a lower energy state to a higher one and observe its transition back to the ground state. Each transition between energy levels emits a photon of an indicated wavelength. In the screen shot below, the photon is emitted when the electron moves from level 5 to level 1. After moving the electron to the same level several times and observing the resulting transitions, students can determine which are the most probable and least probable transitions. This result can later be mapped onto spectral line intensity. 

Figure 2: The results of transitions of electrons between energy levels can be tested.


Applet III - The Recombination Line Spectrum: In this version, we activate the temperature control seen on the left side of the applet shown in Figure 2. The temperature control determines the number of ionizing photons among all the emitted photons. A counter at the bottom keeps track of the number of total photons emitted and the number of ionizing events. As ionized electrons recombine and cascade down to the ground state, a new recombination line spectrum is produced. Students are able to measure the relative line strengths of their recombination spectrum. They can then compare their results to real photo-ionization data. By selecting data from ionizing sources of different temperature, students can learn that the fraction of ionizing photons is a sensitive and non-linear function of temperature. 

Applet IV - Blackbody Radiation: This applet combines both theory and observation. Figure 3 shows a real stellar spectrum (in this example, a G2IV star) fitted with the standard astronomical set of BVR filter curves and the blackbody curve for an approximate temperature of 6500 K. As shown at the bottom of the figure, the indicated B-V and V-R colors are 0.52 and 0.24. Figure 4 shows the results when the same stellar spectrum is fitted with just the 6500 K blackbody curve. Here the values are B-V = 0.51 and V-R = 0.37. By carrying out this analysis for the whole range of main sequence stars, the students can directly measure how the colors deviate from the theoretical blackbody case, showing that stars are not perfect blackbodies and that in some temperature regimes stars are closer to blackbodies than in other temperature regimes. Hence this applet, which incorporates real stellar spectra, allows the students to measure the spectral shape of a virtually every kind of known star to see how that spectral shape maps to temperatures and observed stellar color. 

Figure 3: The spectrum of a G2IV star fitted with standard BVR filter curves and the blackbody curve for a selected temperature of 6500K.
 
 
Figure 4: The same G21V spectrum fitted with only the blackbody curve for a temperature of 6500K.

 
Applet V: Stellar absorption: The next step is to have students observe and measure the formation of a stellar absorption line spectrum. In the interface shown in Figure 5, a temperature of 9100K has been selected for this example star. The distributions of energies in the atomic level populations (e.g., electrons and photons) are controlled by the Boltzmann factor. Photons are seen to stream across the screen from the star at the left side. The color distribution of this emission is dictated by the black body curve, which builds up on the far right side of the screen. If the student increases or decreased the temperature, the color of the star’s emitted light will change. The gray vertical line represents a thin layer of hydrogen through which the photon stream passes; hydrogen selectively absorbs some photons. The resulting absorption line spectrum is shown as dark lines against the color continuum background, on the near right side. The intensity of the absorption spectrum builds up on the detector with time. By highlighting a line, students can measure the wavelength and intensity of the line, then determine line ratios and, more importantly, determine line strengths as a function of temperature. 

Figure 5: When photons from stars are absorbed by hydrogen, an absorption spectrum results.

 
Applet VI - Measuring equivalent width: In this step, students are able to measure the line strengths of the various stellar absorption lines that result from the presence of hydrogen, calcium, sodium, etc. In this interface the curves of absorption spectrum of two different stars can be plotted simultaneously. In this way, the student can qualitatively assess how the strength of the absorption lines varies from one type of star to another. In the case shown here, we are comparing the strength of the hydrogen H-beta line in an A star and a late F star. In the background, the dark line spectrum of hydrogen serves as a visual aid for the students in locating the hydrogen line. The resulting H-beta line strengths of the two absorption spectra, expressed as an Equivalent Width (a standard astronomical measurement of line strengths) are shown in the far right corner as 15.85 angstroms for the A star and 3.5 angstroms for the F star. Since the applet contains all known stars, a very robust set of measuring exercises can be designed for class activities.

Figure 6: Features of the absorption spectra of different stars can be compared.

 
Applet VII - The integrated light from galaxies: The light from each galaxy reflects the characteristics and numbers of its stellar population. This applet allows students to select up to six of the different spectral types of stars that they have encountered in the previous exercises, add together the spectra of the stars chosen, with different weights to account for their different numbers, and so produce an integrated spectrum of a real galaxy. This procedure is illustrated below. The top 4 spectra show the input stellar library. The fifth spectrum shows the sum of the input stellar library while the bottom spectra is that of a real galaxy. The straight line on the real galaxy and the composite galaxy are meant to gauge if the continuum (the slope from blue to red wavelengths) is reasonably well fit by the input stellar library. Through the use of this applet and the preceding ones, students use real data to study galaxy evolution in the same way that research scientists do. Different combinations of input stars can be used to model the lifecycle of galaxies from starbursts, to continuous star forming and, eventually, dead galaxies. In this way students have gone from studying elements and atomic processes to doing research into galaxy evolution, all in an interactive data-driven setting. Student no longer have to read and memorize that elliptical galaxies are old. Instead, students have discovered this for themselves using research-grade tools. Because we have 35 galaxies in our galaxy library, we can design a wide range of exercises for either introductory or advanced and graduate classes. This latter point is important. In general, the applets that we have developed can be used on multiple levels, from introductory to advanced. 

Figure 7: By combining spectra of different types of stars, students can design a model galaxy that can be compared to a library of real galaxies.

 
How does instructional technology improve on the lecture?

Addressing the facts problem: While instructional technology can facilitate a move away from facts and towards inquiry, student attitudes may still be the most difficult barrier to overcome. Students expect to learn material simply by memorizing the facts recited by the professor. They are quite uncomfortable with the notion that they are supposed to discover the facts themselves via a guided, interactive journey through data. Many students become frustrated and confused when confronted with the scientific reality that there are no clear answers. In this case, all that instructional technology can really do is to facilitate an avenue of inquiry - another mode of learning. Re-programming the students is at the heart of the science literacy issue. We can hope that improved teaching methodology at the K-12 level will eventually produce a population of undergrads that would rather question than memorize. 

Addressing the one size fits all problem: It is clear that the best learning occurs in a one-on-one environment. Indeed, the greatest amount of learning during the entire term probably happens when two or three students from a typical 300+ class wander into the instructor’s office and ask a real question. Clearly, the research university will never have enough resources to replace classroom learning with one-on-one learning, but instructional technology can address this problem. It is possible in principle to design and implement intelligent agent software that allows the individual user to customize a journey through the resources that make up the curriculum. The game-like nature of such a journey might even motivate the students more than the traditional lecture.

Addressing the syllabus problem: The Internet allows the student to interact with a diverse and distributed expert knowledge base. If used subversively, this expert knowledge base can greatly enhance the learning experience. For example, I give a series of lectures on the dwindling nature of the fossil fuel reserve and the likelihood that we only have 50 years worth of fossil fuel production on the planet. Then I direct the students to a number of other expert or knowledgeable web sites where they must find credible information to prove me wrong. The students are generally motivated by this kind of assignment. If well crafted, classes such as those in environmental science, can consist of a sequence of research experiences in which students put together disparate sources of information to synthesize a conclusion. Students learn the scientific method instead of the syllabus.

The syllabus problem exists because we collectively fail to define the learning goals for our general education classes. In my own case, I am no longer concerned that my students are exposed to fewer astronomical topics, because I know that they are actually doing science. My fundamental pedagogical goal is for them to learn the pivotal role of uncertainty in scientific inference. Making the students work with noisy data or noisy (virtual) detectors emphasizes this point far more elegantly than I could ever do in a lecture. 

Teaching collaborative learning: If undergraduate education does not promote collaborative learning experiences, it does not prepare students for the real word. The real world is an interdisciplinary team oriented environment in which individual team members are expected to make contributions to the overall project. However, we do not often teach Collaboration 101. Higher education needs to ask itself whether a focus on collaborative learning would make undergraduate education a more valuable experience. 

Instructional technology can greatly facilitate student-to-student communication. Team exercises can be built around data projects and network tools can assist the teams with their data analysis and reduction. This becomes a powerful learning environment built on peer-to-peer teaching and learning. When combined with group presentations in class, the students learn written and oral communication skills and develop their organizational skills. Although students initially do not like to work in groups, they usually come around during the term. While the beginning stages are highly dysfunctional, the end product is very satisfying. Generally, it is the perceived effect on their grade that makes students reluctant to participate in the group process - “What if I am in a bad group?” Once the grade hurdle is overcome, students typically enjoy the group-learning environment. 

I strongly believe that the obvious value of collaborative learning justifies the investment for deployment of instructional technology. The real world of scientific research is collaborative in nature. Any university department functions by collaboration. Collaboration is what we do in our professional lives all of the time. Why are we so reluctant to teach that way? A major learning outcome is the students’ newly acquired collaborative skill – a skill they are likely to retain long after the syllabus topics have been forgotten. 

Barriers to Implementation 

I have outlined the potential instructional technology has to integrate research into teaching and how it can be used as a tool to modify, or even greatly change, the nature of the general education science class. Despite the availability of instructional technology, the majority of these classes are taught the same way in 2003 as they were in 1953. While inertia on glacial timescales is part of the higher education landscape, there must be additional reasons why systemic reform in undergraduate general education is so difficult to implement. Based on conversations and interviews with the relevant players, the following barriers have come to light. 

Faculty entrenchment: Our faculty are here primarily to do research and the merit system rewards quality in research far more than quality in teaching. Without an understanding that there can be scholarship associated with teaching, this problem is unlikely to diminish. Because peer review is considered to be the coin of the realm when it comes to the evaluation of scholarly materials, we are unable to evaluate teaching scholarship. This must change. 

Administrative reluctance: From the fiscal point of view, the mass lecture is a wonderful tool - it represents the means of instruction with the lowest unit cost and any alternative approach would cost more, either in terms of time and money for course development or in terms of human resources. Lecture courses more than pay for themselves with the tuition dollars of the enrolled students. However, I believe that defending the large lecture because it is a wise fiscal instrument is tantamount to declaring that we are not interested in investing to improve the quality of general undergraduate education. Our mission should be to provide the students with a quality education.

Student passivity: Students are most definitely part of the problem. They put up with, and often prefer, spoon-fed knowledge. Few students are engaged in the learning process and fewer still take responsibility for it. I firmly believe that if students said that they wanted more collaborative work and better deployment of technology as part of their course curriculum, then the academic glaciers would move faster. One of the reasons that there are often large gaps between the RAIRE and AIRE schools derives from student passivity. The kind of passive student I have described above must be admitted by state law to a state research university, but not to private schools. Indeed, much of what I have written above must sound idiotic to faculty at private schools. The reality at state research universities is that the passive nature of the students largely defeats any attempt at active and collaborative learning. It is a real effort to overcome this passivity and such effort is never rewarded in the teaching evaluations. But, in the end, the effort is most definitely worth it. 

Limited infrastructure: There are important issues of infrastructure. The primary reason that the University of Oregon was able to experiment with the use of network technology as a means of integrating research into teaching was due to its excellent network infrastructure. By 1993 there was Ethernet to every faculty desktop. Two years later, all the classrooms were wired, as were the dorms. The access issue was solved before the instructional development effort began and we were able to avoid making fatal mistakes that would have turned faculty and students off forever. You can’t assign the students to use a networked data reduction tool if they don’t have easy access to the network. 

“Go away - it costs too much”: Of course, the greatest barrier is that the development of quality interactive electronic materials is time consuming and expensive. The commercial world offers us course management tools but very little in the way of tools for content development. Money can be found, but making instructional technology work in classrooms requires new organizational partnerships and new ways of looking at what a course should be. Ideally, development would be done by giving faculty members course release time to work with graphic artists, programmers and instructional designers to convert their static content into a dynamic, interactive and multi-faceted journey. To date, few if any universities have invested in the expertise and creativity of their own faculty to develop superior curriculum. 

Beware of Shovelware 

The final issue is the triumph of style over substance. Universities have clearly been under some pressure to become more hi-tech. One typical response is an on-line syllabus - Professor X takes his paper syllabus and posts it on the Web and student Y accesses the syllabus and prints it. The technology is used as a Xerox machine. I call this shovelware - we are converting content from one medium to another without taking any advantage of the unique characteristics of the second medium. 

This illustrates what I perceive to be the fundamental problem in the current use of instructional technology. Faculty try to stuff the existing courses into the technology rather than to use the technology to teach in a new manner. We are using instructional technology to just provide better course management tools. The unique aspect of the Web lies in its inherent interactivity and that’s where the development effort needs to be centered. The inherent interactivity of the web opens up whole new avenues and styles of teaching. It allows us to customize a curriculum around data products with which the students can interact. It provides the potential to create a simulation environment in which students can perform virtual experiments and analyses and make mistakes along the way without those mistakes being documented. It allows students to interact with the material in new and different ways that are quite difficult to properly assess. Most importantly, it can be used to facilitate group collaborative projects that build writing and presentation skills. 

Such uses of instructional technology represent a robust and responsible use of the new opportunities that network technologies provide. We can either embrace these new tools as a means for changing the learning environment or we can keep our heads in the sand, assuring ourselves that the way we have always done it will suffice. 

A post-production note: Currently this class is taught in a classroom of wireless laptop computers. This means that students do many of the exercises outlined above as in-class participatory learning with a focus on collaborative problem solving. 


The Institution

The University of Oregon was founded in 1972. It remains a traditional liberal arts college with a large residential population. Currently there are approximately 17000 undergraduates and 3500 graduates distributed among the College of Arts and Sciences and six professional schools. In addition, there are several interdisciplinary research institutes on campus that bring together faculty from different departments for joint research on a wide array of current problems. Total federal funding for the University of Oregon in FY 03 was 70 million dollars. The University also won the 1996 EDUCAUSE award for Campus Networking. 

In 1997 the University won one of the 10 NSF-RAIRE, awards based on its effort to use campus networking as a means of digitally integrating research into teaching. Funds from that award were used primarily for expanding curriculum development and the development of network tools that facilitate the integration of research into teaching, for faculty development training workshops and sub-grants to make the effort more widespread across the undergraduate curriculum and for small enhancements of the campus network and/or classroom infrastructure to improve access to the various network curriculum tools.


Acknowledgements

The author gratefully acknowledges generous funding from the National Science Foundation whose support has enable the creation of the content and curriculum discussed above. The author further acknowledges fruitful exchanges with other members of the RAIRE/AIRE forum that have resulted in an understanding that certain challenges are universal in nature.


Suggested Reading 

 

Copyright © 2003 Council on Undergraduate Research. All rights reserved.