A STUDY OF SCHOOL DISTRICT/COMMUNITY ATTRIBUTES AND COMPUTER-RELATED EDUCATION POLICY IN PUBLIC SCHOOLS OF THE STATE OF MARYLAND

Using a survey methodology the study investigated the correlation between community and school district characteristics and the LEA's involvement with the instructional use of computers in Maryland's twenty-four (24) school districts. The investigation included interviews with staff professionals from the Maryland State Department of Education, and representatives from all twenty-four districts, as well as the review of national, state and school district reports and surveys.;There are four (4) statistically significant correlations between district and community characteristics and the LEAs' involvement in instructional computing: (1) The number of students in a district has a positive correlation to the number of subjects in which computers are used (R(,s) = 0.7498) and to the number of professional staff officially involved in supervising or coordinating instructional computing (R(,s) = 0.6187); (2) The Property Tax Rate in a community has a positive correlation to the number of subjects in which computers are used (R(,s) = 0.5122) and to the number of professional staff officially involved in supervising or coordinating instructional computing (R(,s) = 0.4272); (3) The Per Capita Income in a community has a positive correlation to the number of subjects in which computers are used (R(,s) = 0.5185) and to the number of professional staff officially involved in supervising or coordinating instructional computing (R(,s) = 0.4639); and (4) The percent of majority (i.e. white) students enrolled in a school district has a positive correlation to the percent of teachers who have received training in computing (R(,s) = 0.3602).;Study findings indicate a lack of accurate data on both the state and LEA level regarding instructional computing. These include: (1) Enrollment statistics relating patterns on racial and gender basis; (2) Number and type of courses in which computers are used as an instructional tool; (3) Accurate inventories of computer resources (both hardware and software); and (4) Revenue and expenditure data clearly attributable to instructional computing.