Research Methodology Research Traditions What is research? Research is “the systematic approach to finding answers to questions.” “Questions” comes first – questions drive inquiry; questions will inform the kind of research we do. Quantitative and Qualitative research traditions Both are “empirical,” involving the collection of original data (from human subjects). Both are drive by identifiable conceptual and methodological assumptions. Research Traditions Quantitative research emphasizes: • the systematic measurement and quantification of variables • the statistical analysis of data • the use of mathematic models and causal inferencing Qualitative research emphasizes: • thick description of the interactions of individuals and interpretations of these interactions • heuristic (discovery oriented analysis of data) • leading to “grounded theory.” Research Traditions Assumptions about: 1. discovery 2. variables 3. data collection 4. data analysis 5. use of data Research Traditions Quantitative Qualitative Discovery There is a “T”ruth that can be discovered. Individuals socially construct meaning / “t”ruth, so truth is as relative as the number of individuals involved. Qualitative research is sometimes referred to as “interpretive,” for this reason. Research Traditions Quantitative Qualitative Variables Few, parsimonious – goal is to isolate a single variable so that causation can be established. Research Traditions Quantitative Qualitative Variables Parsimonious L. parsimonia "sparingness, frugality," from pars-, stem of parsi, perf. tense of parcere "to spare, save" + -monia, suffix signifying action or condition “Thick description.” Goal is to consider all variables that might be pertinent. Margaret Mead Claude Lévi-Strauss Hunter Thompson Research Traditions Quantitative Qualitative Data Collection Deductive: Researchers bring a theory to the study setting which is then tested in that setting. Inductive: Theory arises from data – hence “grounded theory” – grounded in data. Theories inform researchers’ preparation for study, but doesn’t lock them into particular ways of understanding. Competence data: •error recognition / correction •grammatical judgments •cord sorting Research Traditions Data Collection Performance Affective data: data: •questionnaires •reading aloud •matched-guise •completion techniques tasks •diary studies •elicited •focused imitation introspection •reconstruction •role plays •oral interviews •composition Research Traditions Quantitative Qualitative Data Analysis Statistical. Searching for statistically significant differences among samples around specific variables, in order to understand effects of interventions. Heuristic. Searching data variously (taxonomic analysis, semantic relationships [x is a kind of y, etc.]) in order to understand a specific culture. Research Traditions Quantitative Qualitative Use of Data By random sampling, generalize results from a small sample to a large population. Not interested in generalizability. Results inform further study and help build theory (our interpretive understanding of a cultural setting). Statistics 1. Descriptive Statistics The use of numbers to describe results. • mean = average scores (etc.) from all participants • SD = standard deviation ≈ average distance from the mean of all points in a data set Statistics 1 SD = 68 % of population (red) 2 SD = 95 % of population (red and green) 3 SD = 99 % of population (red, green, and blue) Statistics 1 SD = 68 % of population (green) 2 SD = 95 % of population (green and blue) 3 SD = 99 % of population (green, blue, and red) Statistics: Height of US Women 18–74 (n = 6,588) mean = 63.5 in. SD = 2.5 in. 61 in. 58.5 in. 66 in. 68.5 in. Statistics: Example Statistics: English Students 2.42 1.28 3.56 Statistics: ESL Students 2.30 1.43 3.17 Statistics: Example Statistics 2. Inferential Statistics Analysis of descriptive statistics. How do we know if the difference between two data sets (means, frequencies, correlations, and so on) is significant – i.e., attributable to something other than chance? A variety of tests used to determine significance: • Anova (analysis of variance) • chi-square • F-test • t-test • Pearson product moment correlation Statistics Significance – means “attributable to something other than chance.” Example: old teaching method v. new teaching method Experimental method semester-end test scores are significantly higher than control method tests If we have set up the study correctly, we may be able to conclude that the new method is the cause of higher student achievement. Statistics Probability. Significance is usually expressed in terms of probability, “p” – for example: p < .01 p < .05 refer to the probability that differences occurred through chance alone (as opposed to the influence of the experimental method). Statistics p < .01 means there is less than 1 percent probability that chance alone explained our result; there is more than 99 percent probability that something other than chance explained our result. p < .05 means there is less than 5 percent probability that chance alone explained our result; there is more than 95 percent probability that something other than chance explained our result. p = 0.026 means that our inferential analysis has determined there to have been a 2.6 percent probability that chance alone explained our result; and a 97.4 percent probability that something other than chance explained our result. Statistics: Example Statistics: Example So, while the results may be interesting … Statistics: Example … they are not significant – i.e., we can’t contribute them to anything other than chance. Research Traditions Quantitative Qualitative Research Methods Correlation studies Survey research Experimental research Case studies Ethnographic research Research Methods Correlation Studies (Quantitative tradition) Purpose: to understand relationships among characteristics. Issue: Correlation is NOT causation. Examples? Cancer clusters Research Methods Correlation Studies (Quantitative tradition) Analysis: Statistical, based on calculation of correlation coefficients. Research Methods Correlation Studies (Quantitative tradition) Analysis: Statistical, based on calculation of correlation coefficients. Research Methods Correlation Studies (Quantitative tradition) Example: Goldstein, L.M. (1987). Standard English: The only target for nonnative speakers of English? TESOL Quarterly, 21, 417-436. The author examined the use of African American English (BVE) among Hispanic students. She found that those who had extensive contact with African American students used features of BVE more than students with less contact. http://www.youtube.com/watch?v=kkcTpfcno-E Research Methods Survey Research (Quantitative tradition) Purpose: to learn about the characteristics of an entire group (population) by asking questions of a small component of that group (sample). Issue: Random sampling. Analysis: statistical, both descriptive (percentages, etc.) and inferential (i.e., looking at the relationships or correlations in the results. Research Methods Survey Research (Quantitative tradition) Example: Duran, R.P. (1987). Factors affecting development of second language literacy. In S.R. Goldman and H.T. Trueba (Eds.), Becoming literate in English as a second language (pp. 33-55). Norwood NJ: Ablex. The author surveyed Hispanic freshmen concerning their basic language characteristics, their own rating of their academic skills, and their SAT scores. As a result of correlation analyses, the author found a positive relationship between high self-ratings and high SAT scores. Research Methods Experimental Research (Quantitative tradition) Purpose: to establish a cause / effect relationship between an independent variable (IV; the cause agent) and a dependent variable (DV; the agent acted upon). Requires experiment and control groups and careful control of all but the IV so that causation (if any) can be established. Research Methods Experimental Research (Quantitative tradition) Issue: “true-ness” of experiment Control and Experimental Groups? Pre-Experiment No. Only 1 group, preand post-test structure Random Sampling No. Use of extant group Quasi-Experiment Yes. No. Use of extant groups True Experiment Yes. Yes. Research Methods Experimental Research (Quantitative tradition) Analysis: Inferential statistics to determine if difference between groups are significant – that is, caused by the IV, not by chance alone. Example: Carrell, P.L. (1985). Facilitating ESL reading by teaching text structure. TESOL Quarterly, 19, 461-481. The author found that teaching rhetorical structures to ESL freshmen resulted in improved ability to recall information in related texts. Research Methods Case Study Research (Qualitative tradition) Purpose: to focus attention on a single entity (or a very small number) in a naturalistic setting. Data is gathered through interviews, observations, diary accounts, text analysis, video / audio recording, etc. Analysis: heuristic, piecing together patterns in the data. Research Methods Case Study Research (Qualitative tradition) Example: Kravin, H. (1992). Erosion of a language in bilingual development. Journal of Multilingual and Multicultural Development, 13, 307-325. The author analyzed the bilingual development of a six-year-old Finnish-American child. The study is primarily concerned with the processes by which one of the child’s languages begins to dominate the other. The author speculated in conclusion that the subordination of Finnish in the child is the result of limited linguistic input in that language. Research Methods Ethnographic Research (Qualitative tradition) Purpose: to examine culture, society, schooling, etc. for the purpose of understanding the processes of acculturation, socialization, learning, etc. from the perspective of individuals in the setting. Data is gathered through interviews, observations, diary accounts, text analysis, video / audio recording, and participant observation. Analysis: heuristic, discovery oriented Research Methods Ethnographic Research (Qualitative tradition) Example: Hornberger, N.H. (1987). Bilingual education success, but policy failure. Language in Society, 16, 205-226. The author investigated bilingual education in a particular community in Peru through a two-year ethnographic study. Findings focus on the perceptions of the value of Spanish and Quechua among students and their families. • Are there male/female differences in how invitations are extended between native speakers? How does non-native speaker behavior compare? • Is there a sequence in which second language pronouns are acquired? If so, what is it? • Does practice with sentence-combining result in learners producing longer T-units in their classroom compositions? • What word-attack skills do learners naturally use when they encounter a word they don’t know? • Is there a relationship between the age at which second language instruction begins and the level of SL proficiency achieved?