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The Effect of Reading Comprehension and Problem So (1)

 2 (6)   =263.038, p<.01]. These findings show that in terms of the strategies used here, individuals with high and low problem  solving success can be separated with a discriminant function. In the next stage, Wilks’ Lambda equality of groups test  was checked to determine significance of separation efficiency of each independent variable and Table 18 shows the  findings. Journal of Education and Training Studies Vol. 5, No. 6; June 2017  56  Table 18. Wilks lambda equality of groups test  Scores  Wilks’ Lambda  F  Sd1  Sd2  P  Writing mathematical sentence  .615  173.596  1  277  .000  Looking for a pattern  .829  57.126  1  277  .000  Systematic listing strategy  .755  90.127  1  277  .000  Estimation and control  .654  146.439  1  277  .000  Backward studying  .970  8.574  1  277  .004  Drawing figures and diagrams  .849  49.228  1  277  .000  According to Table 18, when significance level of each independent variable separating individuals with high and low  problem solving success depending on the strategies they used is analysed, it is seen that writing mathematical sentence  [F (1-277) =173.596, p<.01], looking for a pattern [F (1-277) =57.126, p<.01], systematic listing [F (1-277) =90.127, p<.01],  estimation and control [F (1-277) =146.439, p<.01], backward studying [F (1-277) =8.574, p<.01], drawing figures and  diagrams [F (1-277) =49.228, p<.01] are significant. According to Çokluk (2012), as Wilks’ Lambda values converges to 1,  the effect of the strategies in separating the groups decreases. In this context, in terms of Wilks’ Lambda values, the  strategy with the least contribution to separation is seen to be backward studying while the one with the most  contribution to separation is seen to be “writing mathematical sentence” strategy. In the next stage, in order to determine  the strategies with the most contribution to separation, standardized discriminant coefficients and structure matrix  coefficients were analysed and Table 19 shows the findings. Table 19. Standardized coefficients for discriminant function and structure matrix coefficients  Scores  Standardized coefficients  Structure matrix coefficients  Writing mathematical sentence  -.153  -.624  Looking for a pattern  .328  .358  Systematic listing strategy  .672  .449  Estimation and control  .756  .573  Backward studying  -.024  .139  Drawing figures and diagrams  .168  .332  According to Table 19, it was determined that the strategy with the most contribution to separating students with high  and low problem solving success was “estimation and control” strategy (.756), followed by systematic listing (.672),  looking for a pattern (.328) and drawing figures and diagrams (.168) strategies respectively and that “backward  studying” and “writing mathematical sentence” strategies had a counter effect in separation.In terms of structure matrix,  it was seen that in separation, the variable with the most correlation with discriminant function was “writing  mathematical sentence” strategy but the correlation was negative (-.624). This finding enables us to see that as “writing  mathematical sentence” strategy is used more, the likelihood of appearing in the group with high problem solving  success decreases. The strategies increasing the likelihood of appearing in the group with high problem solving success  are seen to be estimation and control (.573), systematic listing (.449), looking for a pattern (.358), drawing figures and  diagrams (.332) and backward studying (.139). In the next stage, the case of problem solving strategies’ classifying  students with high and low problem solving success and Table 20 shows the findings. Table 20. Classification results obtained as a result of discriminant analysis  Low success  High success  Total  Group f  %  F  %  f  %  Low success  136  90.66  14  9.34  150  100.00  High success 19  14.73  110  85.27  129  100.00  Total accurate classifying percentage=88.17%  According to Table 20, it is seen that 136 out of 150 students with low success according to the problem solving  strategies they used were classified accurately and accurate classification rate for low success group was 90.66%. In  terms of the same case for students with high problem solving success, 110 out of 129 students were classified  accurately and accurate classification rate is seen to be 85.27%. Accurate classification rate of discriminant function  according to strategies is seen to be 88.17%. According to Kalaycı (2005), accuracy of classification depends on relative  chance and maximum chance criteria. In this study, the sampling consists of 279 students and 53.76% (150) of them  showed low success while 46.24% (150) of them showed high success in problem solving. Therefore, these values are  also chance values for both groups. As a result of analysis, the fact that accurate classifying percentage (88.17%) is  much higher than these two values enabled us to see that the obtained discriminant function achieved accurate  classification beyond classifying upon chance. tải về 434.01 Kb.Chia sẻ với bạn bè của bạn:

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