Development of a Web-based System to Support Self-Directed ...

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Learning effectiveness was analyzed by giving the students exercises to work on in the lab setting. Table 4 shows the mean scores for technical skills, which included “operation of machines,” “selection of process parameters,” and “process planning,” before and after attending the microfabrication course with the implementation of the interactive web-based environments. The Experimental group (i.e., blended learning environment) achieved significant improvements in its scores for “operation of machines” (t = -5.046, p = 0.000), “selection of process parameters” (t = -3.613, p=0.001), and “process planning” (t = -3.778, p = 0.000), whereas the Control group (i.e., the conventional learning environment) has shown no significant improvements (see Table 4). In order to obtain more insight on the above quantitative findings, the 2-way ANOVA was used to analyze the students’ technical skills, which included “operation of machines,” “selection of process parameters,” and “process planning.” In the aspect of operation of machines, both the group effect and the pretest-posttest design have delivered findings that have been found to be statistically significant, as shown in Table 5, which indicates that a blended learning environment is instrumental in producing improved learning outcomes. Table 6 shows that the group effect has not been drastic (F = 1.147, p = .288,), while the pretest-posttest design generated noticeable effects (F = 8.936, p = .004), suggesting that in general, the students’ test scores have improved. However, the effects of a blended learning environment have not been found to be as drastic in the learning of the selection of process parameters, and this might have been associated with the technical obstacles encountered with the applied technique of virtual reality that have mainly concentrated on the simulations of operations of object, aside from the sequences of these operations. Table 5. Analysis of variance for operation of machines Source SS df MS F p Group 5.601 1 5.601 4.481* .038 Pre-Post-test 12.721 1 12.721 22.231** .000 Interaction 1.868 1 1.868 3.264 .075 Pre -post-test error subject 91.239 73 1.250 residual 41.772 73 .572 total 149 p < .05, p < .01 Table 6. Analysis of variance for selection of process parameters Source SS df MS F p Group 1.138 1 1.138 1.147 .288 Pre-Post-test 8.604 1 8.604 8.936** .004 Interaction 3.004 1 3.004 3.120 .082 Pre-Post-test Error subject 72.422 73 .992 residual 70.289 73 .963 Total 149 **p < .01 The lack in real-time presentations of the produced scientific results pose great hindrance in keeping students from adjusting the process parameters effectively for that they were unable to distinguish the varying machining outcomes produced by the different process parameters utilized. However, such technical issues may be greatly mitigated with the software and hardware technologies becoming more advanced in the future. In the aspect of the operation of machines, the analysis has illustrated that interactions have been taking place between the group effect and the pretest-posttest design (Table 7; F = 6.095, p = .016, interaction is significant P), which thus requires the analysis be scrutinized in a more precise manner. Nonetheless, the simple main effect of the group factor has demonstrated that the pretest scores produced by the Control group shares virtually no differences from that that was produced by the Experimental group, while the posttest scores suggest a tremendous amount of differences between the two groups (Table 8). Moreover, the simple main effect of the pre-post-test factor suggests that the conventional teaching techniques served little purposes in improving test scores amongst students in the 210
Control group (Table 9). Furthermore, the blended teaching environment has been statistically proven to be facilitating students in the Experimental group to deliver higher test scores (Table 10). Table 7. Analysis of variance for process planning source SS df MS F p Group 5.444 1 5.444 5.103* .027 Pre-Post-test 10.671 1 10.671 7.915** .006 Interaction 8.218 1 8.218 6.095* .016 Pre-Post-test Error subject 77.889 73 1.067 residual 98.422 73 1.348 Total 149 *p < .05, **p < .01 Table 8. The simple main effect of the Group factor Group N Mean Std. Deviation t p Pre-test Control group 30 7.2000 .96132 Experimental group 45 7.1111 1.36885 Post-test Control group 30 7.2667 .90719 **p < .01 Experimental group 45 8.1333 .99087 .308 .759 -3.836** .000 Table 9. The simple main effect of the pre-post-test factor - Control group Mean N S D t p Pre-test 7.2000 30 .96132 -.273 .787 Post-test 7.2667 30 .90719 Table 10. The simple main effect of the pre-post-test factor - Experimental group Mean N S D t p Pre-test 7.1111 45 1.36885 3.778** .000 Post-test 8.1333 45 .99087 **p < .01 Conclusions The objects of this study are the courses offered in microfabrication technology that have their concentrations on experimentations as well as on practical training. This study has developed a web-based system that is interactive to support self-directed learning of the MEMS technologies, which incorporated the developed web-based system with the courses in question. The blended methodology allowed for a balanced combination of the teacher-centered teaching approach and the student-centered one. As it has been found, most students preferred the blended style of learning, and that the learning performance delivered by the Experimental group showed significantly higher effectiveness of the instructions provided, in terms of teaching of microfabrication. The students generally provided positive feedback regarding the self-directed navigation of the web-based learning system while participating in microfabrication courses. Most students also considered the blended learning system to have been helpful when it comes to learning the technical operations that are relevant to microfabrication; it has enabled the students to learn such operations on the Internet on a persistent basis that familiarized them with microfabrication technologies. The web-based learning system that has been developed out of this study not only assisted students to operate the MEMS and the related manufacturing techniques, it also allowed for process planning to be achieved in cyberspace and was well-received by the students. In the field of technological education, although there had been researchers 211
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