Good science and business practices also yield positive educational results

April 1, 2004
The reliance of modern society on science and technology has created a serious and growing need for a large high-technology workforce and a technically literate population.

The reliance of modern society on science and technology has created a serious and growing need for a large high-technology workforce and a technically literate population. Nowhere is this clearer than in the area of optics. Furthermore, providing an effective science education for a large and diverse segment of the population is something no educational system has ever achieved (see Laser Focus World, December 2003, p. 47).

The following are some examples of how using familiar practices that have greatly enhanced the progress of optical science can also lead to progress in science education. These practices include using and building upon past research results, utilizing modern technology, and being guided by quantitative objective measurements of results. Although there are numerous useful facets of this, I mention only a couple of representative examples here.

1. When I select material and plan how it is to be presented in a class (or even in a technical talk), I make use of what research on cognition has revealed about the limitations of short-term memory and the problem of "cognitive overload." 1 Short-term memory can handle seven (give or take two) different items at any one time. If related items can be presented in a sufficiently coherent way, they are "chunked" together in memory and take up a smaller total allocation. Unfortunately, sufficient coherence in a student's understanding is seldom achieved without considerable explicit emphasis.

2. Using results of psychology and advertising research to motivate students to follow desired learning practices, I have been able to get students to spend up to two times longer on homework and to use that time more effectively. First, I spend considerable effort creating, or borrowing whenever possible, problems that both cover the desired physics concepts and are perceived by the students as having obvious significance outside the confines of the classroom. This is particularly easy to do with optics topics, since light and its uses surround us. Sadly, many instructors ignore basic human nature and assume that most students will be motivated to thoughtfully work through a difficult abstract problem, merely because there is the suggestion that at some point in the future this exercise will be worthwhile.

Second, my use of advertising strategy has an obvious impact when I survey the students and then announce to the class: "95% of the students who work in a collaborative problem-solving group say that this is very beneficial for their learning. Here is a typical student comment: 'Since I started working with a study group it is taking me less time to do my physics homework and I am learning so much more. I only wish I had started doing it sooner.' " The reason companies spend billions of dollars a year on this sort of advertising is that it works.

3. I also use a personalized electronic-response system (PERS) based on simple, inexpensive TV remotes that transmit a student's identity code and have five buttons (A thru E) that enable students to vote in response to multiple-choice questions in class. A computer records every response and provides a histogram of the accumulated responses for display. The psychological impact of the combination of individual accountability (the computer, and thus I, know what each student chose), knowledge of overall class response, and anonymity to peers is particularly valuable and makes this more useful than other real-time forms of student feedback and assessment. The students are more engaged in the material because they are continually responding to questions about it. Also the PERS provides ongoing feedback from the students to me and to the rest of the class as to how well they understand the material. When used properly, PERS can profoundly change the nature of the classroom and the student's expectation about learning the material.2

This became startlingly clear to me the first (of many) times a mixture of whoops and curses (depending on their respective PERS predictions) greeted the outcome of an introductory physics demonstration experiment I carried out in a large lecture. The number and quality (and gender balance) of unsolicited questions also goes up dramatically, which makes class much more fun. Now, instead of reciting a lecture to a group of bored and/or mindlessly scribbling students, I am having a conversation with them about physics. PERS also can provide ongoing data that is both enlightening and sobering.

I have been able to measure, for example, that information I simply tell the class, even with a visual cue, is retained by only 10% of the students 15 minutes later. In contrast, if that information is given in the context of a PERS question, so that they are invested in the answer, more than 90% of the students retain the information two days later. This is the case even though most of the class initially answered the question incorrectly. PERS also provides a natural mechanism for students to discuss questions and concepts, which can dramatically improve understanding and long-term retention.3

The use of PERS and other forms of collecting data on student learning (such as regular open-ended online questions and listening in on student collaborative problem-solving sessions) has made me realize how inadequate my traditional exam and homework questions were at probing students' conceptual understanding and their ability to "think like scientists." Like bad data in any science, these inadequate exam questions led me to faulty conclusions about my teaching effectiveness despite 20 years of experience. I have now found that basing my teaching practices and conclusions on good data and on past research is as effective for advancing teaching as it is for advancing optical sciences. I believe it is our best hope for achieving the science education system we need.

REFERENCE

  1. How people learn, NAS Press, Wash. D. C. (2000).
  2. M. Dubson and C. Wieman, (unpublished) www.colorado.edu/physics/EducationIssues/HITT/HITTDescription.html.
  3. C. Crouch and E Mazur, Am. J. Phys., 69, 970 (2001).
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Nobel laureate CARL WIEMAN is a member of the APS/AIP/AAPT Task Force on Undergraduate Physics, a member of the National Research Council Board on Science Education, and a professor of physics at the University of Colorado, 440 UCB, Boulder, CO 80309-0440; e-mail: [email protected].

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