Traditional e-Learning system displays the same content to all the learners irrespective of their knowledge level and relevance. This paper concentrates on the investigation of the impact of learner's primary medium of instruction at school in understanding the content given to them in English and for designing an adaptive e-Learning system personalized to the learner. An appropriate statistical model has been developed to analyze the impact. The results implied that the medium of instruction (Regional language / English) at school has greater impact on the performance compared to the region (Rural / Urban) the students hailed from, when the same content is given to them in English. The interaction effect of medium of instruction and the demographics on performance evaluation system were analyzed. Based upon the significant gap in the performance between the rural regional language medium students and urban English medium students, the decision procedure rules for providing personalized content to the learner were developed.
Key Words: Adaptive e-Learning, Medium of Instruction, Multiple Regressions, Urban / Rural Capacity gap
[...] A Statistical Regression Model is used to validate the above hypothesis Impact of medium of instruction in understanding English The hypothesis of this experiment is that the urban / rural exposure to the student has greater impact than the primary medium of instruction at school, while understanding the content given to them in English Participants A heterogeneous group of 219 Undergraduate first year Engineering students both from Urban and Rural backgrounds (116 Urban and 103 students hailing from Rural areas) and with a combination of regional language and English as their primary medium of instruction at school (148 Regional Language and 71 English medium students), but with similar pre-requisite subject knowledge and having high level (all of them scored entry level Cut-Off marks between 170 to 190 marks out of 200 marks to get admitted into the Engineering degree programme). [...]
[...] D2 (Medium of Instruction) = ( 8.265 X (Cut-off Marks) = 0.660 )NS - Significance Level; - Significance Level; * - 10% Significance Level; NS - No Significance The equation is significant since F = 34.258 and the independent variables can explain the variation in performance to the extent of since R2 = From this it can be inferred that the medium of instruction plays a vital role in the resulting performance Regression (English Test Effect of Cut-off Marks and Place of Study) This model analyses the effect of Cut-off Marks and Place of Study on the performance in the English Test. [...]
[...] D1 (Place of Study) X (Cut-off Marks) = ( 1.817 = 1.782 D2 (Medium of Instruction) = ( 4.745 - Significance Level; - Significance Level; * - 10% Significance Level; NS - No Significance The equation is significant since F = 13.783 and the capability of the independent variables R2 = From the above equation it can be concluded that the Medium of Instruction is playing significant role in contributing to the performance than the Place of Study, and the Place of Study has minimal impact Conclusions and future work The findings from the above two experiments indicated that when content is offered in English, the medium of instruction at school is more significant compared to the region the student hailed from. [...]
[...] Equation: [ Y = 14.716 + 0.045 + 1.942 The ‘t' value obtained for Medium of Instruction and for the Cut-off Marks and its level of significance are given below. D2 (Medium of Instruction) = ( 5.930 X (Cut-off Marks) = 0.1 .727)* - Significance Level; - Significance Level; * - 10% Significance Level; NS - No Significance The equation is significant since F = 18.823 and R2 = 0.148 shows that Medium of Instruction and Cut-off Marks can explain only of variation in Test performance. [...]
[...] Table Technical Test Performance Medium of Study Residence No.of Students Technical Content Test Score - Avg % Tamil Tamil English English Rural Urban Rural Urban The hypothesis that the primary medium of instruction at school has greater impact than the urban / rural exposure to the student, while understanding the technical contents is validated Statistical Regression Model From Table 1 and 2 it is observed that the performance gap between Urban English Medium students and other categories are high to the extent of 10% difference in both English Test and Technical Test. [...]
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