Data Analysis Process of the Acceptance Study

Descriptive statistics, Fisher's exact test, and content analysis were used to analyze the data collected from the Acceptance Survey and Self-efficacy Survey. The following four sections describe the analysis process.

(1) Descriptive Statistics for Acceptance Survey Questionnaire

The data analysis of the Acceptance Survey Questionnaire on the Acceptance Survey is a set of descriptive analyses that identified the main features of the data collected and summarized the data results from the online questionnaires. In other words, the data analysis of the Acceptance Survey Questionnaire used descriptive statistics to identify the main features of the collected data including summarizing the participants’ demographic, previous experiences of using ICT, and teachers’ acceptance of educational portals via perceived usefulness, and perceived ease of use. It addresses the RQ2-4.

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(2) Tests for Relationships among Teachers’ Responses

I used Fisher's Exact Test to analyze the data from the Acceptance Survey and Self- efficacy Interview since the sample size was small in the Acceptance Study. The Fisher’s Exact Test is preferred over the Chi-squared test when the expected value of any cell in the table is less than five, which is the case in these tests. The purpose of this analysis is to explore whether different teachers’ backgrounds affect their acceptance of the portals (RQ2-1), which variables influence teachers’ acceptance of the portals (RQ2-2), how teachers’ information-seeking behavior is related to acceptance of educational portals (RQ2-3) and whether there is a relationship between TCS and acceptance of educational portals (RQ2-5).

(3) Content Analysis Method Used

The reason for conducting the content analysis, on the interview survey data, is that content analysis is the “longest establish method for text analysis” to help researchers transform raw data into a standardized form; and researchers are able to judge, discover, and describe the meaningful data from participants’ answers (Kohlbacher, 2006). Similarly, Downe-Wamboldt (1992) stated that the goal of content analysis is “to provide knowledge and understanding of the phenomenon under study” (Hsieh & Shannon, 2005).

The data analysis of the Acceptance Survey Interview and Self-efficacy Interview uses content analysis. Content analysis provides a means to accurately obtain more meaningful information from the participants to support the research results. In other words, I used two approaches to analyze both interview data collections: (1) deductive – following already- determined set of codes (a priori) from theories/themes/variables, and (2) inductive – observing

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a phenomenon from the data set and merging in new codes where the codes/themes in the prior code set were inadequate, which involved grounded theory to summarize observations into categories. Grounded theory is an inductive approach to develop a systematic theory, since it begins with basic description, codes all data, extracts a series of codes from the collection set and then develops theoretical ideas (Walker and Myrick, 2006).

For the deductive approach, I used two approaches of qualitative analysis: directed

content approach and summative content analysis, which was proposed by Hsieh & Shannon

(2005): (1) directed content approach starts with a theory or relevant research to find guidance as to initial codes; and (2) summative content analysis involves counting and comparing (usually keywords or content) to interpret the context. Therefore, the directed content approach uses deductive categories to work with previously formulated theories and to highlight theoretical aspects from the data (Kohlbacher,2006). The summative content analysis approach for this study incorporated keyword frequency (for each occurrence of the identified keywords) in the text dataset and which explored keyword usage in the content text in order to make manifest latent content (Hsieh & Shannon,2005).

(4) Content Analysis Procedure

Having a directed content approach and a summative content approach assisted me to code teachers’ interview data set and answer the rest of research questions in this Acceptance Study. However, to make the coding reliable for categorizing data, it is necessary to have exhaustive categories that represent the data set (Stemler, 2001). Thus, this dissertation considered the use of grounded theory since “grounded theory endeavors to integrate the strengths inherent in quantitative methods with qualitative approaches”(p. 548); and it can “set

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out, gather data, and then systematically develop the theory derived directly from data” (Walker & Myrick, 2006, p. 548).

Overall, I have borrowed ideas from Kohlbacher (2006) merged with Walker and Myrick (2006) and Stemler (2001) (See section 2.4) to create my own content analysis procedure (Figure 11 below) that consists of two parts for the content analysis. Based on the audio recordings, sketches and notes that interviewers provided during their interview, the content analysis included two processes: (1) Teachers’ Transcripts Collection Process and (2) Data Content Analysis Process.

The Teachers’ Transcripts Collection Process began with the participants’ audio recordings and notes. To validate the transcript dataset, which included transcripts of each recording session and a summary, and to insure data reliability, the final stage of the Teachers’ Transcripts Collection Process was to send back all the transcripts to each participant for verification before continuing the Data Content Analysis Process.

The Data content analysis process included five stages as follows (Figure 11):

 Stage 1 had predetermined codes by following relevant theories and/or prior research as guidance for the initial codes (directed content approach).

 Stage 2 began to code with a predetermined set of codes (the initial codes) (summative content approach).

 Stage 3 used input from grounded theory when the preconceived categories did not match the observed data, in which case the categories which came from the theory were augmented by categories observed in the data. So, Stage 3 was information mergence by reading through transcripts again to link up cross- categories relationship, and if necessary, to merge the related concepts with

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existing categories or create new code or sub-code schema (directed content approach and grounded theory).

 Stages 4 used new coding categories as the final code agenda and counted the keywords again (summative content approach).

 Stage 5 interpreted and visualized the relationship of data collections.

Figure 11. The Content Analysis Content Process in the Acceptance Study

In analyzing the Acceptance Survey, I used existing theories (TAM and self-efficacy theory) to create key categories as directed content approach to function as the initial coding

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categories, and then I used ground theory to observe phenomena from the data set in order to augment and merge the new codes/themes into the a priori code sets. For counting the keywords, I used Atkasi.ti (a computer program) since it is equipped to help researchers identify complex phenomena and to locate, code, annotate and visualize complex relationships in the data. It was developed by Thomas Murhr at Technical University in Berlin (http://www.atlasti.com/ index.html).

The purpose of the Self-efficacy Interview is specifically to explore the relationship between TCS in three dimensions – Strength, Generalizability, and Magnitude to cross-check results from the Acceptance Survey (see Appendix F: Self-efficacy Interview transcripts). Thus, each of these dimension is analyzed by Bandura's original aspects (1994) with four main sources because these sources affect a person’s belief in performance of the specific proposed task. The four main sources are: (1) mastery experience (a person’s previous success and/or failure experiences), (2) vicarious experience (a person observation of others’ successes and/or failures), (3) verbal persuasion/social persuasion (a person has been persuaded by peers, colleagues, or others), and (4) affective arousal/emotional state (a person’s emotional states such as anxiety, stress, arousal, and mood states).

In summary, the data analysis of the Acceptance Survey interview and the Self-efficacy Interview were conducted using content analysis (Figure 11 above). They began with Teachers’ Transcripts Collection Process to create of a transcript from the interviewer and each participant was given the opportunity to make any corrections or additions s/he wanted in order to make data transcripts more reliable and valid before starting the Data Content Analysis Process. Also the Data Content Analysis Process considered the directed content approach and a summative content approach (from Hsieh & Shannon, 2005) and grounded theory (from Walker and Myrick,

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2006) in order to answer RQ2-2, RQ2-4, and RQ2-5 in this dissertation. The content analysis coding scheme is included as Appendix H.