Types of Research

1. Types of Research Lynn W Zimmerman, PhD

2. The Research Design • The overall plan for carrying out the research study • Blueprint for creating a strong research structure

3. Basic Applied • Basic research • Theoretical research dealing mainly with abstract ideas and constructs • Used to look at the underlying linguistic, psychological, or sociological mechanisms, the theoretical foundations, that might eventually be applied in the classroom • Applied research • Direct application to the teaching/learning situation • Deal with teaching methods, or immediate problems in the classroom

4. Qualitative Quantitative • Quantitative research • from the field of psychology with heavy emphasis on statistics to make generalizations from samples to larger populations • characterized by the use of numbers to represent its data • looking for data to support a specific point of view that they can then generalize to a larger population. • Qualitative research • originated largely with anthropologists and sociologists who rely heavily on verbal descriptions rather than numbers. • works to uncover information from information-rich samples. • Characterized by verbal descriptions of its data. • Assume that there are multiple perspectives on reality and the aim of research is to explore and document that diversity.

5. Qualitative Research • Data - words, pictures or objects • Inductive - derived from specific examples • Researcher discloses biases, values, and experiences that may impact interpretation of results • Gathers data through interviews, observations, content analysis, etc. • Design emerges as the study unfolds • Researcher may only know roughly in advance what he/she is looking for • Answers: What? Why? • Natural setting • Quotes, bar/line graphs, pie charts

6. The Role of Theory in Qualitative Research • Hypothesis generation • Grounded theory • Goal: to develop a theoretical hypothesis from descriptive data as the descriptive data accumulate from the ground up. • Develop grounded theory inductively based on the data rather than deductively derived from a predetermined hypothesis • Example: We may develop a hypothesis that says: Learners who actively participate will learn vocabulary from practice drills at a faster rate than those who do not.

7. Qualitative Research Strategies • Case studies • Ethnography • Conversational analysis • Protocol analysis

8. Case Studies • In-depth study of a specific phenomenon in the context in which it occurs and from the perspective of the participants. • Purpose: to shed light on the phenomenon, the processes, events, persons or things involved, such as programs, curricula, roles, and events • Narrows down to a case (an instance) to be intensively studied.

9. The Case Study Process • Determine the general research questions or problem • Focus the research questions • Design the study • Identify and recruiting participants • Conduct the study • Analyze data • Write it up

10. Case Study Example (Lam and Lawrence (2002) • Case study focusing on ‘changes in teacher and student roles in a computer-based project’ as a phenomenon in a single Spanish FL classroom. • Data collection: observations, focus groups, questionnaires, and interviews. • Researchers recognized that their findings were not necessarily generalizable. • However, believed they were valid to transfer important implications for teaching and for stimulating further research

11. Ethnography • From anthropology and the study of human social and cultural groups. • Longitudinal studies • Requires immersion in the research setting for an extended period of time. • In a school setting, usually takes one semester, often more. • Large quantities of information • Data gathered from a number of sources, notes from observations, field notes, interviews, collection of artifacts, transcriptions of video and audio recordings, etc. • Verbal data are examined for recurring themes; coded, reduced into groups of related information; organized into patterns • Research questions but do not formulate a preconceived hypothesis. May develop a hypothesis after all data processed

12. Thick Description • rich in detail and incorporating multiple perspectives • Interpretations and conclusions supported by detailed descriptions of context and procedures of the study using quotations from recordings, excerpts from interviews, and various documents to triangulate) for support.

13. Conversational Analysis • From sociology to analyze role of talk in interaction in social organization. • Researchers interested in what the talk means to the participants themselves. • Examine how participants orient themselves to the talk and to each other through the talk. • Context - the interaction itself, not outside factors such as gender, social relationships etc. • Collect data by recording natural interactions, not through interviews or narratives • Central unit of analysis = the sequence (no categorizing): How they take turns to achieve the interactional goal • Verbal and nonverbal communication is considered.

14. Protocol Analysis • From cognitive psychology • The think-aloud approach • Participants are recorded as they carry out a challenging task and talk about it as they do it • The recordings are transcribed and analyzed. • Often used to study the writing process

15. Quantitative Research Strategies • Useful for collecting large amounts of data- to generalize findings. • Data: numbers and statistics • Deductive - based on logical analysis of available facts (variables) • Documents the results using objective language • Uses tools, such as questionnaires or equipment to collect numerical data • Carefully designs all aspects of the study before collecting the data • Knows clearly in advance what he/she is looking for • Answers: How many? • Use a variety of statistical procedures to identify patterns and relationship in large sets of data • Can determine if findings are greater than random chance

16. Descriptive Statistics • Used to summarize sets of numerical data to save time and space. • Specific only for the given sample • 3 important areas in descriptive statistics: • shape of the data • how to describe the average • variance

17. Shape of the Data • Distribution of the data and its relationship to a normal curve (bell curve). • The shape of the distribution determines which types of statistical analysis can or cannot be applied to the data.

18. Describing the Average • Mean: adding all the scores and dividing by the number of scores. • Median: the middle point in the distribution tat divided the number of subjects in half • Mode: the most frequent score

19. Variance • Standard deviation: the average deviation of scores from the mean • Semi-interquartile range: estimates where the middle 50% of the scores are located in the data distribution (related to median) • Range: the distance from the lowest to the highest scores in the distribution

20. Inferential Statistics • Same as descriptive except the statistical program also tests whether the results observed in the sample are powerful enough to generalize to the whole population. • Looking for ‘statistical significance’ to draw some general conclusions • Inferential statistics procedures answer: • Are there relationships between variables? • Are there differences between groups of data?

21. The Null Hypothesis • There either is no relationship or that there is no difference between groups. • Example: A researcher wants to determine if extensive writing affects performance in descriptive writing among secondary students. Group A has extensive writing practice; Group B does not. • Null hypothesis: • There is no significant main effect for the nature of writing practice as a factor in the descriptive writing performance of secondary students.

22. Statistical Significance • Determines if a null hypothesis should be rejected or retained. • ]For a null hypothesis to be rejected as false, the result has to be identified as being statistically significant, i.e. unlikely to have occurred by chance alone. • Always the possibility that an observed effect would have occurred due to sampling error alone. • If the probability of obtaining a large difference between two or more sample means is the p-value, then can conclude that the observed effect reflects the characteristics of the population, not a sampling error

23. Research Methods • Questionnaires • collect a lot of responses • provide descriptive info – what something is like • test a hypothesis • Interviews • explore ‘why’ questions • produce breadth and depth • Observations • provide rich information on actual events • Documentation • support for questionnaires and interviews • identify an issue • provide evidence to test a hypothesis

24. References • Perry, Jr., F.L. (2005). Research in applied linguistics: Becoming a discerning consumer. Mahwah, NJ: Lawrence Erlbaum Associates. • Mackey, A. and Gass, S. (2012). Research methods in second language acquisition: A practical guide. West Sussex, UK: Wiley-Blackwell.