Due to the fact that the data I collected was large in scope because it included standardized test results, survey results, portfolios and field notes, I decided to sift through every piece of information that I had and put it into categories that then became groups (Burns, 1999). One group was related to the tests I applied; another group contained the survey results; another contained the field notes; and the last one contained the student portfolios which had the students’ work and results in the different inquiry-based tasks. After painstaking sifting, sorting and grouping, some of my research findings began to surface.
Since sorting into categories is one of the most important steps in the data analysis process and I had already grouped the events that took place during the implementation of the inquiry-based learning unit, I followed the steps described below in order to make sense of the data I collected. The main purpose was to start drawing out some theories and explanations in order to interpret the meaning of those trends, characteristics or features that became apparent (Burns, 1999).
Bearing in mind that this was an action research project, I knew I had to analyze the data, interpret it and develop a theory about what the data meant in order to improve my teaching practice in science classes while increasing the students’ autonomy awareness.
To shape the overall process of data analysis, I used the framework adapted from McKernan (1996). I started by assembling the data that I had collected over the period of my research: pre-test, pre-survey, students’ portfolios, field notes, post-test and post-survey. The initial questions that began my research project provided me a starting point for rereading the data which I scanned first of all in a general way.
I noted down thoughts, ideas and impressions that occurred to me during this initial examination of the information that I gathered especially from the field notes that I took throughout the intervention. At this stage, broad patterns began to show up which I thought could be compared and contrasted later on to analyze what fit together (Burns, 1999). Once I gathered all the data that I had collected through the data collection instruments I used I found that students:
• were more willing to start the class.
• enjoyed doing the experiments and watching the videos I played them.
• were attentive to the teacher instructions and read the instructions to perform some tasks.
• wanted to show the teacher their portfolios and their findings at home.
• searched for information on their own about the topics.
• included in their portfolios a good number of different items related to the systems of the human body.
• started asking more questions than they used to at the beginning of the unit.
• tried to find the answers to the questions on their own using their textbooks and materials from their portfolios.
• enjoyed working with their classmates in pairs and groups.
• participated actively in experiments and hands-on activities.
• were able to draw conclusions after inquiry activities.
• showed in their pre-test results that they didn’t know much about the systems of the human body even though they had studied this topic in previous years.
• showed in their post-test results improvement in their knowledge about the systems of the human body.
• showed in the pre-survey results that most of them preferred student-centered classes.
• showed in the pre-survey results that they did not feel very autonomous.
• showed in the pre-survey results that they were hesitant about their preferred learning styles.
• showed in the post-survey results that they felt more autonomous.
• showed in the post-survey results that they identified their preferred learning styles better.
Once there had been some overall examination of the data that I thought illuminated the question I was researching, I created categories related to inquiry-based learning and its effect on the students’ autonomy awareness and jotted a name for each one of them until I completed a list of categories (Burns, 1999). The objective was to reduce the amount of data that I had collected to more manageable categories of concepts, themes or types. The following are the categories for my data:
Category 1: Student-centered methodology vs. teacher-centered methodology
Category 2: Encouraging students to inquire
Category 3: Learning styles
Category 4: Learning autonomy
In order to move beyond describing, categorizing, coding and comparing to make sense of the data I had collected, I got to a point in the data analysis process that demanded a certain amount of creative thinking since it was time to articulate underlying concepts and developing theories about why particular patterns of behaviors, interactions or attitudes had emerged.
I came back to the data I had collected several times and I posed questions about it, rethought the connections among the data and developed explanations of the bigger picture underpinning my action research project (Burns, 1999). Then I discussed the data patterns and themes with some of the school’s science teachers trying to find new discoveries or interpretations.
Since sorting into categories is one of the most important steps in the data analysis process and I had already grouped the events that took place during the implementation of the inquiry-based learning unit, I followed the steps described below in order to make sense of the data I collected. The main purpose was to start drawing out some theories and explanations in order to interpret the meaning of those trends, characteristics or features that became apparent (Burns, 1999).
Bearing in mind that this was an action research project, I knew I had to analyze the data, interpret it and develop a theory about what the data meant in order to improve my teaching practice in science classes while increasing the students’ autonomy awareness.
To shape the overall process of data analysis, I used the framework adapted from McKernan (1996). I started by assembling the data that I had collected over the period of my research: pre-test, pre-survey, students’ portfolios, field notes, post-test and post-survey. The initial questions that began my research project provided me a starting point for rereading the data which I scanned first of all in a general way.
I noted down thoughts, ideas and impressions that occurred to me during this initial examination of the information that I gathered especially from the field notes that I took throughout the intervention. At this stage, broad patterns began to show up which I thought could be compared and contrasted later on to analyze what fit together (Burns, 1999). Once I gathered all the data that I had collected through the data collection instruments I used I found that students:
• were more willing to start the class.
• enjoyed doing the experiments and watching the videos I played them.
• were attentive to the teacher instructions and read the instructions to perform some tasks.
• wanted to show the teacher their portfolios and their findings at home.
• searched for information on their own about the topics.
• included in their portfolios a good number of different items related to the systems of the human body.
• started asking more questions than they used to at the beginning of the unit.
• tried to find the answers to the questions on their own using their textbooks and materials from their portfolios.
• enjoyed working with their classmates in pairs and groups.
• participated actively in experiments and hands-on activities.
• were able to draw conclusions after inquiry activities.
• showed in their pre-test results that they didn’t know much about the systems of the human body even though they had studied this topic in previous years.
• showed in their post-test results improvement in their knowledge about the systems of the human body.
• showed in the pre-survey results that most of them preferred student-centered classes.
• showed in the pre-survey results that they did not feel very autonomous.
• showed in the pre-survey results that they were hesitant about their preferred learning styles.
• showed in the post-survey results that they felt more autonomous.
• showed in the post-survey results that they identified their preferred learning styles better.
Once there had been some overall examination of the data that I thought illuminated the question I was researching, I created categories related to inquiry-based learning and its effect on the students’ autonomy awareness and jotted a name for each one of them until I completed a list of categories (Burns, 1999). The objective was to reduce the amount of data that I had collected to more manageable categories of concepts, themes or types. The following are the categories for my data:
Category 1: Student-centered methodology vs. teacher-centered methodology
Category 2: Encouraging students to inquire
Category 3: Learning styles
Category 4: Learning autonomy
In order to move beyond describing, categorizing, coding and comparing to make sense of the data I had collected, I got to a point in the data analysis process that demanded a certain amount of creative thinking since it was time to articulate underlying concepts and developing theories about why particular patterns of behaviors, interactions or attitudes had emerged.
I came back to the data I had collected several times and I posed questions about it, rethought the connections among the data and developed explanations of the bigger picture underpinning my action research project (Burns, 1999). Then I discussed the data patterns and themes with some of the school’s science teachers trying to find new discoveries or interpretations.
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