classroom              package:WWGbook              R Documentation

_c_l_a_s_s_r_o_o_m _d_a_t_a _i_n _C_h_a_p_t_e_r _4

_D_e_s_c_r_i_p_t_i_o_n:

     The Study of Instructional Improvement (SII; Hill, Rowan, and
     Ball, 2004) was  carried out by researchers at the University of
     Michigan to study the math achievement scores of first- and
     third-grade students in randomly selected classrooms from a
     national U.S. sample  of elementary schools.

_U_s_a_g_e:

     data(classroom)

_F_o_r_m_a_t:

     A data frame with 1190 observations on the following 12 variables.

     _s_e_x : Indicator variable (0 = boys, 1 = girls)

     _m_i_n_o_r_i_t_y : Indicator variable (0 = non-minority students, 1 =
          minority students) 

     _m_a_t_h_k_i_n_d : Student math score in the spring of their kindergarten
          year

     _m_a_t_h_g_a_i_n : Student gain in math achievement score from the spring
          of kindergarten to the spring of first grade (the dependent
          variable)

     _s_e_s : Student socioeconomic status

     _y_e_a_r_s_t_e_a : First grade teacher years of teaching experience 

     _m_a_t_h_k_n_o_w : First grade teacher mathematics content knowledge:
          based on a scale based composed of 30 items (higher values
          indicate higher content knowledge) 

     _h_o_u_s_e_p_o_v : Percentage of households in the neighborhood of the
          school below the poverty level 

     _m_a_t_h_p_r_e_p : First grade teacher mathematics preparation: number of
          mathematics content and methods courses

     _c_l_a_s_s_i_d : Classroom ID number

     _s_c_h_o_o_l_i_d : School ID number

     _c_h_i_l_d_i_d : Student ID number

_R_e_f_e_r_e_n_c_e_s:

     Hill, H.C., Rowan, B., and Ball, D.L. (In Press). Effect of
     Teacher's Mathematical Knowledge for Teaching on Student
     Achievement,  American Educational Research Journal, Learning
     Mathematics for Teaching (LMT) Project.

     West, B., Welch, K. & Galecki, A, Linear Mixed Models: A Practical
     Guide Using Statistical Software, Chapman Hall / CRC Press, first
     edition, 2006.

_E_x_a_m_p_l_e_s:

     attach(classroom)

     #### Boxplots for Figure 4.2
     classroom.first8 <- classroom[classroom$schoolid <= 8,]
     par(mfrow=c(4,2))
     for (i in 1:8) 
     {boxplot(classroom.first8$mathgain[classroom.first8$schoolid==i] ~ classroom.first8$classid[classroom.first8$schoolid==i],ylab="Mathgain", xlab="classid" )}

