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Tables' data analysis - Essay Example

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277 Students' responses were analysed using SPSS (version 16) software. The tables below provide a prime opportunity to study their results and use them for further learning purposes. Percentages of students who made each combination of responses from both tiers are summarised in table 1.
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Tables data analysis
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The sub-rows consist of the options for answers and the columns consist of the reasons for the answers. The items marked with an asterisk (*) represent those responses which are not only correct, but are explained rightly too. As in example 1, 70.5% of students selected the right answer and the right reason for their answer. All other values imply either a wrong answer, or the wrong reason, or both. The values in bold (in question 1, 14.1%) provide the percentage of students who answered wrongly and that percentage exceeds 10%.

Jian Wang (2006) stated that the role of teachers is perceived as a very strong one in mentoring students. This would also involve a reform minded teaching that would have many challenges. According to experts in the field, a substantial set of these alternative conceptions, i.e., a wrong answer set of more than 10%, is considered a significant alternative conception (Chandra, 2005). These significant alternative conceptions require further study into them, as these are mistakes made by a significant group, pointing to weak basic concepts.

If none of the wrong responses total more than 10%, there is no significant alternative conception, as in question 8. In some cases, when there is no response in a particular field, it is represented with a '-'. A surprising fact is that this quiz was taken by pre-service science teachers. Unfortunately, this shows us that even aspiring teachers are not always clear with their concepts, leading to the realization that "Teachers often subscribe to the same alternative conceptions as their students.

" as per a previous research, Alternative Conceptions, Concept Change, and Constructivism, These teachers, in turn would pass on the misconception, or alternate conception, to their students, causing a network of misinformed science students. These tables help professionals to avoid situations like those, by restricting the spread of these alternate conceptions.The above table gives us an insight into the percentage of students, who got the first part of the question right, but got the second part, the reason, wrong.

As a multiple choice question always has the possibility of chance (33% in most of these questions), this table helps getting a finer look at how often chance comes into play here. Getting one answer out of three is much easier than getting one answer out of six options. This is made evident by the drastic difference in percentages between students getting only the first part right and those getting both right. Another important aspect of this table is that it helps realizing how many students truly understand the underlying concepts behind the questions.

An answer can be answered with just a little knowledge, but actually explaining it poses a much bigger problem for students. There is an approximate average of 12% difference between the two percentages. This reflects not only chance, but also raw knowledge with a feeble conceptual base. Certain questions, namely 11 and 15, have no difference in the two percentages. These imply specific knowledge required for the question, possessed only by those who got the answers right. But most of the questions show an opposite

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