commit to user 52
process, while quantitative data were analyzed using a descriptive statistic technique.
a. Qualitative Data
In analyzing the qualitative data, the researcher used Anne Burns theory 1999: 156-160 said that in general, the data analysis process included
assembling the data, coding the data, comparing the data, building interpretations, and reporting the outcomes. The data provided the evidence for the statements or
assertions that were made about the research insights or outcomes. The following are the stages for analyzing qualitative data:
1. Assembling The Data
The first step is to assemble the data that have collected over the period of the research: field notes, journal entries, questionnaires, and so on. It is useful to
note down thoughts, ideas, or impressions that occurred during this initial examination. At this stage, broad patterns should begin to show up which can be
compared and contrasted to see what fits together. By scanning the data in this way, it begins the process of more detailed analysis by bringing up possible
patterns which can adopt or add.
2. Coding The Data
Some overall examination of the data, categories, or codes can be developed to identify patterns more specifically. Coding is a process of attempting
to reduce the large amount of data that may be collected to more manageable categories of concepts, themes, or types. With closed or ranked questions, I a
questionnaire for example, responses or behaviors may be assigned to a code relatively easily. Data analysis becomes much more messy and coding becomes
less clear cut when it is dealing with diary entries, classroom recordings or open- ended survey questions.
3. Comparing The Data
Once the data have been categorized in some way, comparisons can be made to see whether themes or patterns are repeated or developed across different
commit to user 53
data gathering techniques. It should be noticed sequences of data or identify relationships and connections between different sources of data. At this stage the
researcher should be able to map frequencies of occurrences, behaviors, or responses. The main aim at this stage is to describe and display the data rather
than to interpret or explain them.
4. Building Interpretations
This is the point where the researcher moves beyond describing, categorizing, coding, and comparing to make some sense of the meaning of the
data. This stage demands a certain amount of creative thinking as it is concerned with articulating underlying concepts and developing theories about why
particular patterns of behaviors, interactions, or attitudes have emerged. Discussing the data patterns and themes with other members in the research group
can be a catalyst for new discoveries or interpretations, as can noting down thoughts or insights as they occur and questioning what lies behind surface
description.
5. Reporting The Outcomes
The final stage involves presenting an account of the research for others. There are various way to report the research. a major consideration is to ensure
that the report sets out the major processes of the research, and that the findings and outcomes are well supported with examples from the data. the data in the
action research have been systematically collected and analyzed. This systematic aspect needs to be shown in a report. This means at the very least setting out and
discussing the original issue or questions that prompted the study, describing the contexts of the research, outlining the findings and providing data samples to
support them, interpreting how the findings relate to the context and suggesting how to the project has been fed back into practice or could lead to other areas for
research.
commit to user 54
b. Quantitative Data
Kategori