科研助力 | （即将）读研究生的你，如何选择研究方法？
The following article is from 思飞学术 Author 思飞学术
Research underpins and informs our understanding and appreciation of all aspects of the world, and its insights lead to physical, social and personal growth and change. While, in itself, your research might not seem to make any immediate direct impact, over time, research-led insights, understanding and changes affect everything we do in society.
（Gina Wisker，《研究生科研手册》，p. 9）
Concerned with hypotheses testing
Concerned with generating theories
Uses large samples
Uses small samples
Data are highly specific and precise
Data are rich and subjective
Produces quantitative data
Produces qualitative data
Reliability is low
Validity is high
Generalises from sample to population
Generalises from one setting to another
Source: Adapted from Hussey and Hussey (2nd edn) (2003)
（Gina Wisker，《研究生科研手册》，p. 68）
What is Social Network Analysis?
Social Network analysis conceptualizes individuals or groups as ‘points’ and their relations to each other as ‘lines’. It is concerned with the patterns formed by the points and lines and involves exploring these patterns, mathematically or visually, in order to assess their effects on the individuals and organisations that are the members of the ‘networks’ formed by the interesting lines that connect them. It therefore takes the metaphorical idea of interaction as forming a network of connections and gives this idea a more formal representation in order to model structures of social relations. Treating a social structure as a network is the cornerstone of social network analysis. (p. 1)
What is Social Network Analysis?
Online research methods do not describe an approach to finding out about the internet, but rather they describe an approach to finding out about people and the social world they inhabit, using the internet. (p. 3)
Online research methods have now established a clear place in the social research methods canon. Researchers began to experiment online from the mid-1980s but it was only with the development of the internet as a mass form in the mid- to late 1990s that online research really began to develop as a field and to advance the methodological questions. This chapter has argued that there is a complex relationship between technology, the social use of technology and the strategies that researchers develop to examine these. This relationship forms one of the main themes of this book, as it examines the key features and debates that have emerged in the areas of online surveys, online interviews and focus groups, online ethnographies and online experiments. (p. 23)
What is Discourse Analysis?
This book provides an overview of discourse analytic research as a rich and interdisciplinary field which continues to change and develop in new directions.
One starting point is that discourse analysis usually refers to a research approach in which language material, such as talk or written texts, and sometimes other material together, is examined as evidence of phenomena beyond the individual person. （斜体为原文所有）(pp. 1-2)
What is Diary Method?
Diary method has arguably been the ‘poor relation’ of the methodological family in qualitative research, compared, for example to interviews … Yet, even a cursory search of the research literature published since 1990 reveals over 4,800 papers using diary method. Moreover, the method continues to provide researchers with a flexible tool for collecting rich data, especially in light of digital, web and social networking technologies.
Solicited diaries are diaries that people have been asked to keep for a particular reason, notably for research purposes. This approach, in which a participant records his or her thoughts, feelings and/or behaviours under the direction of an individual researcher, has been part of the researcher’s toolkit since the 1930s and is the main focus of the book. (pp. 1-3)
What is Qualitative Research?
In light of this contrast with quantitative social science, we can define ‘qualitative research’ along the following lines: a form of social inquiry that tends to adopt a flexible and data-driven research design, to use relatively unstructured data, to emphasize the essential role of subjectivity in the research process, to study a small number of naturally occurring cases in detail, and to use verbal rather than statistical forms of analysis. （斜体为原文所有）(p. 12)
What is Qualitative Interviewing?
Most text books will tell you that interviews range through a continuum, from structured, through semi-structured, to unstructured (or focused) interviews (Bryman 2001; May 1997). The structured interview is at the quantitative end of the scale, and more used in survey approaches. The rest of the scale, semi-structured and unstructured, is the area occupied by qualitative researchers, with the interviews characterized by increasing levels of flexibility and lack of structure. Many of the terms you will have discovered applied to qualitative interviewing appear in this part of the continuum, for example in-depth, informal, non-directed, open-ended, conversational, naturalistic, narrative, biographical, oral or life history, ethnographic and many more discussed in more detail in Chapter 3. The terms used for any particular interview type relate to the underlying philosophy and specific approach taken to research, discussed further in Chapter 2. (p. 3)
What are Qualitative Research Ethics?
…[E]nhancing ‘ethical literacy’ means more than learning how to achieve ethics approval. ‘Ethical literacy’ means encouraging researchers to understand and engage with ethical issues as they emerge throughout the process of research and not merely to view research ethics as something that is completed once a favourable opinion on a proposed research project has been granted by a research ethics committee. While it may be the case that some ethical issues can be anticipated prior to a study commencing, often ethical issues emerge as research proceeds, sometimes in unexpected and surprising ways. (pp. 1-2)
What is Quantitative Longitudinal Data Analysis?
The subject of this book is quantitative longitudinal data analysis, and it focuses on data that are collected in large-scale social surveys. The most universal definition of longitudinal social science data is any data that have a temporal (i.e. time) dimension. A rudimentary distinction is routinely made between cross-sectional designs, where data are collected at only one point in time, and longitudinal designs, where information is collected from the same units on multiple occasions. Temporal data can be collected in cross-sectional designs, and it is mildly misleading to assume that longitudinal analyses can never be undertaken with cross-sectional data. (p. 1)