FOOTNOTES

 

[1] Paper presented at the American Educational Research Association, New Orleans, April 26, 2000.

 [2]  The probability sample was a weighted sample with selection probabilities related to school size and the amount of computer technology present. Selection of the additional "purposive" sample schools was based upon extensive data gathering, including tabulation of schools participating in more than 50 reform programs and development of a "technology presence index" for all public schools in the United States, using data from Quality Education Data, Inc.

[3] Again, weights were used that were inversely proportional to selection probabilities of different teachers. [Further information about the sampling design can be found at http://www.crito.uci.edu/TLC. Principals and school technology coordinators also supplied information for the study.

[4] Teachers are weighted inversely to their probability of selection within their school, and for the probability sample, schools themselves are weighted inversely to their probability of selection.

[5] For more information on this scale and responses of the sample see Ravitz, Becker, and Wong (2000),  available on www.crito.uci.edu/tlc

[6] For more detailed information on teachers' responses with respect to teacher philosophy and practice see Ravitz & Becker, (1999).

[7] The first item contrasted the role of the teacher as learning facilitator in inquiry-based learning versus transmitter of information and procedural directions. A second item contrasted the primacy of "sense-making" with importance of transmitting the required curriculum.  A third item presented the choice between believing that motivation and student interest were more important than specific subject-matter versus believing that the textbook content in history, science, math, and language skills should "drive what students study."  A fourth item contrasted a teaching style with multiple activities incorporating the integration of diverse skills occurring simultaneously in the classroom with a whole-class model with short time-span tasks that "match students' attention spans and the daily class schedule."

[8] To operationalize the dichotomous construct "Highly Active Computer User," we employed a cutoff score for each of the three dimensions, setting the cutoff point according to a judgment of how important each dimension was for the underlying construct.  Specifically, teachers were judged to be Highly Active Computer Users if they were .25 standard deviations above the mean on Student Tool Use, .25 standard deviations above the mean on Teacher Use and Expertise, and no lower than .25 standard deviations below the mean on Frequent Simple Uses.  These cutoff points represented the top 24% of teachers on Student Tool Use, the top 41% on Teacher Use and Expertise, and the upper 54% on Frequent Simple Uses.  To meet the criterion for being labeled a "Highly Active Computer User," a teacher needed to pass all three cutoff points. 

[9] Of course, it is also true that many of the specific prompts used in the Pedagogy Index, in particular, are more relevant to the teaching of some subjects than others.  So some of the differences between teachers by subject is artificial.  Both "true" and "error" between-subject variance is handled by using within-subject-matter z-scores, as discussed in the text.

[10] For an alternative structure that encourages both the diffusion of good teacher practices and a form of accountability, see Riel, M., (1995). The future of teaching.  In Education and Technology: Future Visions , Commissioned Paper by the U.S. Congress, Office of Technology (Eds.) OTA-BP-EHR-169 Washington, D.C. Printing Office. Available online: ( www.wws.princeton.cgi-bin/byteserv.prl~ota/disk1/1995/9522/952206.PDF) U.S. Con-gress Office of Technology Assessment alphabetic listing of OTA reports (www.wws. princeton.edu:80/~ota/ ns20/pubs_f.html).