Simons (2009: 117) defines analysis as procedures, including coding, categorization, concept mapping and theme generation, which facilitate organization and interpretation of data in order to produce findings and an overall understanding of the case. According to Mugenda (2008:288), data analysis and interpretation help transform data into knowledge. Since the purpose of research is to develop knowledge, data analysis is critical in any research process.
Babbie posited that the purpose of data analysis was to discover the characteristics of data collected and patterns that point to a theoretical understanding of social life (2004:376) and so there was need to combine different data analysis approaches (Babbie & Mouton, 2001).
4.8.1 Qualitative Data Analysis
Qualitative data analysis seeks to identify patterns in data, behaviour, objects, phrases, or ideas that are subjectively identified and interpreted within the context in which they occurred (Leedy and Ormond, 2005: 96). According to Creswell (2007:150), qualitative data collection, analysis and report writing are not distinct processes, but rather are intertwined and take place concurrently throughout the study. Qualitative data that sought to measure the understanding, attitudes and perceptions of students, faculty and librarians was analysed through descriptive/interpretive techniques that included content analysis. This included data from questionnaires and interviews. After gathering the data, the researcher ensured that all the interviews that had been recorded were transcribed. The researcher then read through all the transcripts again, guided by the research questions and objectives, to identify themes describing what the respondents were saying. This included note-taking of preliminary thoughts that were being established.
Detailed analysis followed that included coding. Coding refers to the process of organizing material into groups before inferring meaning from the group (Kohlbacher, 2006). It included assigning headings to the sections that describe the themes that were based on the research questions. Leedy and Ormrod (2005:142) and Kohlbacher (2006) described this type of analysis that is based on themes as content analysis, which they referred to as “a detailed and systematic examination of contents of a particular body of data in order to identify patterns, themes or biases.” The detailed examination revealed concepts that would help present the information literacy learning experiences of fourth-year psychology students in Kenyan universities.
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Data from document analysis was analyzed manually; since there were only four forms filled in that were one page each (See Appendix V). Data from these forms was used to supplement data from interviews with librarians and lecturers.
4.8.2 Quantitative Data Analysis
According to Terre Blanche, Durrheim and Painter (2006: 188), quantitative data analysis is a technique that uses statistical methods to analyse research variables in order to describe data and interpret characteristics of populations under study. They observed that emphasis in quantitative data analysis is numeric data, using a variety of techniques. Large numerical data in quantitative analysis employ the use of software, including the Statistical Program for Social Sciences (SPSS), which make it easy to manipulate (Cohen, Manion and Morrison, 2011:604).
Sapsford and Jupp (2006:121) described SPSS as a computerised technique that assesses the correlation between variables and makes it easy to identify groups of variables that are highly correlated if they all measure the same thing. Leedy and Ormond (2005:97) and Teddlie and Tashakkori (2009) described the aim of quantitative data analysis as to reject or confirm a research hypothesis by drawing conclusions about the population under study.
The quantitative data from questionnaires and interviews in this study were analysed using the SPSS, version 20. Descriptive statistics including mean, mode, frequency, standard deviations and regression analyses were generated using SPSS. The function of descriptive statistics is to indicate characteristics that are common to the entire sample and summarize data on a single variable (Rubin & Babbie, 2008:520; Mertens, 2014:419). The data was also subjected to Factor Analysis, using SPSS. Somekh and Lewin (2005:345) define Factor Analysis as a quantitative research technique that identifies the general dimensions or concepts within a set of responses to questions and summarizes the variables into a smaller number of variables that can be interpreted more easily. In the case of mixed methodology, qualitative data is analysed separately and quantitative data also analysed separately (Teddlie & Tashakkori 2009; Creswell
& Plano-Clark 2007:128).
The mapping of research questions to data collection and analysis techniques presented in Table 4.4 will aid in the analysis of collected data.
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Table 4.4: Mapping Research Questions to Data Analysis Techniques Research question Questions addressed in data
collection instrument
Source of data Data analysis techniques What information
literacy learning experiences do the fourth-year
psychology students possess?
-Questions 7,8,11,14 in Appendix XI-interview schedule for librarians
-Question 9 in Appendix XII – interview schedule for lecturers -Questions 3,4,5,6,10 in
Appendix X- questionnaire for students
-Interview -Document review -Survey questionnaire
-Content analysis -Factor analysis using SPSS -Discourse analysis
What are the goals of the information literacy programme at the Kenyan
universities?
-Question 4 in Appendix XI – interview schedule for librarians -Question 9 in Appendix XII – interview schedule for lecturers
- Interview -Document review
-Content analysis
What pedagogical approaches are used to deliver information literacy to
psychology students?
-Question 7 in Appendix XI – interview schedule for librarians -Question 6,10, in Appendix XII – interview schedule for lecturers
- Interview -Document review
-Content analysis
What is the role of ICT in promoting the learning of
information literacy?
-Questions 5,6 in Appendix X- questionnaire for students -Questions 3,7 in Appendix XI – interview schedule for
librarians
-Question 6,8,10 in Appendix XII – interview schedule for lecturers
-Survey questionnaire -interview
-Content analysis
132 What are the
perceptions of fourth- year psychology students towards information literacy?
-Questions 2,12 in Appendix X- questionnaire for students -Questions 2,16 in Appendix XI – interview schedule for librarians
-Questions 2,17 in Appendix XII – interview schedule for lecturers
-Survey questionnaire - interview
-Content analysis -Factor analysis using SPSS -Discourse analysis
What are the challenges experienced by fourth-year
psychology students in learning
information literacy?
-Questions 9,10 in Appendix XI – interview schedule for librarians
-Question 12 in Appendix XII – interview schedule for lecturers
-Survey questionnaire - interview
-Content analysis