Data analysis methods

In line with the design of the research, the analytical procedures for mixed data analysis by Johnson and Christensen (2008, p. 555) were employed. This analysis was framed by the research questions (Onwuegbuzie & Leech, 2006), two of which (questions one and two) were constructed in a “parallel” way (Creswell & Plano-Clark, 2011, p. 184), i.e., to address the same concepts. In the following paragraphs, I discuss how I analysed the data in relation to each of the methods used.

3.3.2.1 Questionnaire

Quantitative data analysis was conducted in the light of the research questions. In other words, the quantification of data was used to explore EFL teachers’ (n=81) self-report on their use of ICT applications (first research question), their perceptions of the impact of various factors on their use of ICT including their TPACK (second research question), and the relationship between teachers’ demographic features and these aspects (third research question).

I used the SPSS software version 21 to analyse data. In order to prepare and analyse data properly, I consulted with a statistical expert at RMIT University in addition to regular meetings with my supervisors. First, all data from the 81 questionnaires was entered into an SPSS file. Then the data was checked for errors to detect any “values that fall outside the range of possible values for a variable” (Pallant, 2011, p. 40). For

example, for the gender variable, I assigned the code 1 for female and 2 for male. This was checked to make sure that no scores other than 1 or 2 for this variable were recorded.

94 Also, missing data were screened using frequency tables. These tables showed that missing data concentrated on some items such as ‘Web-based projects’ (Section 2 – ICT applications), ‘Students’ commitment to using ICT’ (Section 3 – Factors influencing teachers’ use of ICT) and ‘Teachers’ knowledge to select effective teaching strategies to guide student learning’ (Section 4 – Teachers’ TPACK). I further investigated this issue and discovered that this was caused by the misprint of these three items in some

questionnaire copies.

Three alternatives for treating missing data were considered: list-wise deletion, pairwise deletion and replacing with the mean. List-wise deletion can lead to eliminating important cases and can make the sample size unnecessarily smaller (Howell, 2012). Pairwise deletion can lead to different statistics with different sample sizes, so the results may not reliable (Howell, 2012). Replacing with mean may distort the results (Pallant, 2011). I weighed up the deletion of the variables and deletion of the cases with missing data, as well as the possibilities of having unreliable and biased results, and I chose not to use any of these alternatives. Instead, I followed the advice of Tabachnick and Fidell (1996) and dropped those three variables with concentrated missing values to retain the sample size of 81 and to avoid the loss of important data in the analysis. However, this omission is acknowledged as a limitation of this study.

The analysis of the questionnaire findings started with descriptive statistics such as percentages, mean score and standard deviation. These were obtained on the frequency of use of ICT application, on the level of impact of factors influencing EFL teachers’ use of ICT and on the teachers’ amount of TPACK to answer research questions one and two. Next, Spearman Rhos were calculated to examine the relationships between the listed factors that influenced teachers’ ICT use and their use of ICT applications, as well as between teachers’ TPACK and their use of ICT applications. Spearman Rhos were used

95 because the demographic variables and frequency of ICT use, level of impact of

influencing factors and amount of TPACK were not continuous variables in this study (Field, 2013; Pallant, 2011).

Before Spearman Rhos were calculated, exploratory factor analysis was run to reduce the number of items in the questionnaire, thus making it easier to explore the relationships (if any). Factor analysis is a group of techniques that can be used to “reduce a data set to a more manageable size while retaining as much of the original information as possible” (Field, 2013, p. 666). I decided that while there was extensive literature around the use of ICT applications in language instruction, factors influencing teachers’ use of ICT and teachers’ TPACK, little had been established about the relationships among these variables in the context of Vietnam’s higher education. Factor analysis was, therefore, selected as a means to explore possible relationships among ICT applications, factors influencing EFL teachers’ use of ICT and TPACK domains.

The sample size was 81 EFL teachers. This is considered small for factor analysis (Comrey & Lee, 1992), and I recognise that this is a limitation in my study. However, given that the population size was approximately 140, a sample size of 81 was a good rate of return. Moreover, as this is a study of Hanoi University where the EFL teachers used ICT in their instruction, this study was not concerned with “statistical generalisation from a sample to a population” (Cohen et al., 2011, p. 294). Instead, Hanoi University might be of importance “to catch significant features” (Cohen et al., 2011, p. 295) that might be present in other universities in Vietnam for ICT use. Finally, as the purpose of the study was to gain insight into EFL teachers’ ICT use in Hanoi University, it used a combination of various sources of data from a quantitative questionnaire and qualitative interviews, rather than solely relying on the questionnaire. As such, exploratory factor analysis was performed for exploratory purposes to assist in identifying possible trends and

96 associations among items that made up different constructs in the questionnaire, and the “conclusions [were]… restricted to the sample” only (Field, 2013, p. 674).

Finally, Spearman Rhos were also calculated to investigate relationships between the EFL teachers’ demographic features such as gender, years of teaching, age, main area of specialization and highest qualification and 1) their use of ICT applications, 2) their perceptions of the impact of the factors influencing their ICT implementation and 3) their TPACK. This was done to answer research question three.

3.3.2.2 Interviews

Qualitative data analysis was also conducted in light of the research questions. The data obtained from semi-structured interviews with the seven teachers were transcribed verbatim and coded through “topic coding” and “analytical coding” (Richards, 2005, p. 88). This process involved reading the transcripts carefully, and assigning “passage to topics or themes” (Richards, 2005, p. 92). For example, while reading the transcripts, if I saw the word “benefits of ICT” or “ICT is beneficial” or “ICT can help” in a passage, I would write “ICT benefits” in the margin. Then I created a table into which I cut and pasted all the passages with the same topic and organised them under the name of the topic. Next, I revisited the table and created “categories that express new ideas about the data” (Richards, 2005, p. 94). I then determined a name for the categories next to the passages in the margin. Then, a hierarchy of these categories was determined (Johnson & Christensen, 2008). Where necessary, I translated from Vietnamese into English those quotes from interviews that were of use for data analysis. These English translations were later verified by a NAATI-accredited professional translator (Appendix 11). In the end, this data was mixed with questionnaire data at the interpretation stage to provide a rich account of the EFL teachers’ use of ICT in classroom practice at Hanoi University.

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3.3.2.3 Strategies for merging data analysis

As discussed above, I merged data from the questionnaire and interviews in the

interpretation stage. In order to merge the data analysis, I used the strategy recommended by Fetters et al. (2013, p. 2142), which is using “narrative”. I used one approach in relation to narrative integration, the “weaving approach, [which] involves writing both qualitative and quantitative findings together on a theme-by-theme or concept-by-concept

basis” (Fetters et al., 2013, p. 2142). The merging of the data analyses was organised

using the research questions as an organising framework, followed by conclusions or explanations (Creswell & Plano-Clark, 2011). Thus, the integrated findings from

questionnaire and interviews were organised around ICT applications, factors influencing teacher use of ICT, teacher TPACK and the relationships between teachers’ demographic features and their use of ICT, their perceptions on the impact of factors and their TPACK. One theme on the complexity in teacher use of ICT emerged from the questionnaire and interviews was also discussed. In doing so, I hoped to use the “between-method

triangulation” (Denzin, 1989, p. 244) to have a rich picture on EFL teacher use of ICT in their classroom teaching at Hanoi University, Vietnam.