4.2 Difficulties in the Preparation of Writing
4.2.2 Difficulties about data analysis
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research (i.e., deciding the population of sample and designing the instruments). Within the problems about instruments design, students had the troubles such as setting the time of the tests and proving the reliability and validity of instruments designed by themselves.
Similarly, the teachers also thought designing the instruments was the challenging part for students. In the teachers’ views, the concerns for students could be two: how to design the instruments to derive satisfactory answers of the research questions and how to ensure the reliability and validity of the data collected by using the instruments. As to the solution of the problems mentioned above, both the students and teachers believed reading papers or books and discussing with advisors to get more information about research design were good ideas.
4.2.2 Difficulties about data analysis 4.2.2.1 Students’ perspectives
Regarding the difficulties about data analysis, two types of difficulties can be derived from the obtained data: (a) selecting the types of analysis and (b) managing the data collected. The first challenge was about deciding the ways to analyze data. Claire and Ken both reported their concerns in choosing suitable kind of data analysis in order to answer their research questions. As Ken expressed, “I wanted to know whether students’
gender and vocabulary ability affect their choice of the vocabulary used. Should I use t-test or were there any other ways to help me attain the desired answers?” The expression from Ken suggested that the reasons resulted in such difficulty could be: several kinds of analysis could be adopted, not sure about what he desired to attain from analysis, and inadequate knowledge about each way of analysis.
Though deciding the way to analyze data, the second difficulty became how to handle the data at hand. This obstacle could be discussed from two domains: For the student who conducted qualitative research, she felt it was hard to decide the coding schemes, for there
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were lots of codes. Sherry, the only student who did a qualitative inquiry, noted that her difficulty was to find the codes which could be adopted as the coding schemes of her study. For the students conducted quantitative studies, most of them(except Fiona and Helen) thought managing the statistic software to do a specific analysis was a hard task because of the lacking knowledge about each type of analysis and the experience of manipulating the software. As Ken stated, “I wanted to get this results, and what could I do by using “Statistical Product and Service Solutions” (SPSS)? And there were many analyzing ways like Analysis of Variance (ANOVA), how to manage the software to do this analysis?” The following expression also showed Lynn’s concerns at that time:
I think it could be… what were the things I wanted to compare? I had to understand…
I want to proceed this [way of data analysis], and what were the things I had to compare? What did I anticipate? So for the statistical part…when I did not quite understand the t-test, I could not know what I should compare and what my anticipation was. (S2IN-Lynn-P5).
From the above statements, Lynn admitted that even though she adopted t-test as data analysis, she didn’t know how to choose the data to be compared and contrasted in this kind of analysis because she did not totally understand the core of t-test.
4.2.2.2 Teachers’ Perspectives
Consistent with students’ perceptions, the teachers also considered the difficulty students encountered in data analysis was choosing the analyzing ways which
corresponded to one’s focus of study. As professor C stated, “Students may have no ideas about the suitable ways to analyze data because the kinds of data analysis vary case by case. That is, students have to select the analyzing way based on their research questions.”
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Also, professor B indicated that students didn’t know what types of data analysis could help them get the answers of their research questions, for they lacked knowledge about statistics, saying:
Because basically [in] quantitative studies, you have to know what each way of analysis is, what’s its purpose? what is it used for and how to do it? But students encountered the problem as “whether I have to compare the two [data] or not, if yes, should I use t-test or anything else?” (A1IN-Prof. B-P7)
Students may hesitate to decide the types of data analysis to be used after collecting the data, for they did not totally understand the essence of each kind of data analysis in statistics. Delving into the reason why students lacked the understanding of the ways of analysis, it was that they attain common knowledge about each kind of analysis but didn’t know how to realize it in their studies. As professor B stated, “Because the statistics students learned was superficial, and they were not sure about the concepts (in statistics).
But I think it was because that the students did not read relevant studies (which adopted statistic analysis).”That is, to know how to relate specific data analysis to a certain type of inquiry, students need more examples by reading the papers with statistic analysis.
4.2.2.3 Advisor-advisee Pairs
From both teachers’ and students’ perspectives of the difficulties about data analysis, we found there was consensus in professors B and his advisee, Ken. In other words, both professors B and Ken thought deciding the way of data analysis was a problem. Ken finally selected the mixed way to analyze data because he attained professor B’s
suggestion. In professor B’s views, he also believed that students needed some advice and instruction, for their knowledge about statistics was insufficient. As to the other two pairs,
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there were no common points between the advisors and advisees. The reason could be the advisors were only impressed in the troubles most students met, but the present students did not have the same difficulties.
4.3.3.4 Coping Strategies 4.2.2.4.1 Students’ Perspectives
When facing the difficulties about data analysis discussed earlier, students cope with them via self. The self-regulated coping strategies contained attaining information from Internet, texts, and experts. For instance, Lynn tended to search for how others manage SPSS on the Internet. Another example came from Clair. She said she would search for the papers with similar research questions and see what types of analysis methods the authors adopted to answer their questions. For Ken, the resources used to deal with the problems in managing statistic software were books about statistics. As he sated,
When using the statistic [software to manage the data], I faced some difficulties. So you had to read books [to know] how to carry out statistics to derive the desired results. So I leaned statistics by myself, I couldn’t rely on others and the professors. I just learned it by myself. (S1IN-Ken-P22)
According to Ken, he believed it was the students’ own responsibility to familiarize the keys in each way of analysis and how to handle the software. Thus, he read books to acquire the knowledge about statistics.
Aside from dealing with the challenges by the internalized knowledge provided by self, the students also received aids from others. The people who provided assistance to the present students included colleges who had the experience of conducting quantitative studies and the experts of statistics. As illustrated by Lynn, “I asked the colleges who also
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used SPSS to analyze data and already completed their theses. I didn’t ask my graduate school classmates because they came back to work and we worked in different place
“Information disclosed from the statement was that the student participants may seek assistance from those available and thus their choices about whom to ask for help may depend on the context in which they face the challenge. Another student, Claire, said she went to the “Teaching Development Center” of her college and consulted the Ph.D.
students who mastered statistics. “I asked him how to manage the software and at the same time I made notes of the steps. Then I practiced it again when I came home,” she said. Furthermore, students discussed with their advisors to get more ideas about data analysis. As Ken expressed,
The problem was…… for example, how could I analyze data? I thought this[way]
was okay, for example, I thought it was okay to use t-test, but the teacher said, “Is this [way] okay? It’s more than that.” So I adjusted it, and see which way was better and tried a lot. In the end, it was a combination of all I’d experimented.
(S1IN-Ken-P18)
This evidence showed that Ken faced the difficulty in determining the kind of data analysis which was appropriate for his study. After receiving the advisor’s hints, he thought about more possible ways to analyze data and finally decided the type of data analysis to be taken in his study.
4.2.2.4.2 Teachers’ Perspectives
The same with students’ perceptions, the teachers also considered that students could cope with the difficulties by adopting the self -regulated strategies. Within the
self-regulated strategies, the provider of assistance could be self and others. Regarding
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self as the source of aids, the teachers thought the students could read texts to clarify their doubts in data analysis. For example, professor B suggested his students focus on the
“data analysis” section when reading others’ theses. By doing so, the students would gradually know what types of data analysis could be used to derive the answers of their research questions. Moreover, professor B thought students had to read some books relevant to statistics, for he believed that the students had inadequate knowledge about statistics. As he stated, “Students’ understanding about statistics was at the surface level.
Maybe this relates to each student’s background knowledge and the curriculum design of the ETMA program. I think what they can do is to enrich their knowledge by reading more.”
As for the assistance came originated from others, the teachers believed students could ask for the experts’ help. Professor A, for instance, said she would suggest her students consult other professors who mastered in statistics. As presented below:
If a student wants me [to be his advisor], I will tell him that what I can do for help and to what extent. Also, I will tell him what I am not good at. I will tell him I am not clear with the [ideas] about statistics. When you have statistical problems, you have to ask others, or I introduce others to you. But maybe you cannot attain too much information [about statistics] from me. (A1IN-Prof. A-P19)
In this except, professor A expressed that she could not answer the questions about
statistics for this is not her expertise. Thus, she would suggest the students ask the experts in statistics. Recalling the statistical difficulties encountered by the students in the present study, she mentioned that she never introduced one of the professors in the department of English to Lynn. In Lynn’s case, Lynn did not know how to manage SPSS when the number of participants differed between the pre-test and the post-test. Finally, she solved
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this problem by discussing with professor X, who was a master of statistics. In addition to introducing other professors to her advisees, professor A mentioned there were other human resources in the campus, saying: “I don’t know whether they know there was a statistical consultant in our school, but I will still ask them to contact this department.”
4.2.2.5 Summary
In short, the students commented that deciding the ways to analyze data and managing the data by using the statistic software were hard tasks. For the teachers, they believed students had problems about selecting the types of data analysis and this idea was the same with students’. To deal with these troubles, the students tended to cope it by self like reading information from typed texts and the Internet. Also, they needed more experienced research writers’ help, such as colleges, doctoral students, and their advisors.
Likewise, the teachers thought the students could find answers from material resources (e.g., books and papers) as well as human resources (i.e., excerpts of statistics).