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Research design: The backbone of academic inquiry Peter Neff – Doshisha University Matthew Apple – Nara National College of Technology David Beglar – Temple.

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Presentation on theme: "Research design: The backbone of academic inquiry Peter Neff – Doshisha University Matthew Apple – Nara National College of Technology David Beglar – Temple."— Presentation transcript:

1 Research design: The backbone of academic inquiry Peter Neff – Doshisha University Matthew Apple – Nara National College of Technology David Beglar – Temple University Japan CUE Forum 2008 Olympic Memorial Youth Center November 1, 2008, 1:15 - 2:50 p.m.

2 Introduction: The importance of good research design Approaching the study Developing the study design Break for Q&A Designing the right instrument Implementing your design Conclusion Further Q&A Overview

3 Introduction: The importance of good research design

4 Poor design vs. Good design Poorly-designed study Hit on an idea, dive right in No background research Throw together a survey, give to a group of unwary participants Collect data, then ponder how to analyze Run to a colleague for help Fish around for most “interesting” findings Pray to get published

5 Poor design vs. Good design Well-designed study Hit on an idea, do background research Formulate relevant, specific, practical RQs Consider participants, context, data analysis in advance Decide/develop instrument; pilot and revise it Decide on appropriate pre/post-test instruments Plan stages and structure of data collection Prepare participants adequately …Then carry out the study

6 The importance of good design A well-designed study provides many benefits: – Demonstrates researcher knowledge – Ties the study to an underlying philosophy – Provides a clear path for the researcher(s) – Helps avoid mishaps of previous studies

7 The importance of good design Other benefits – Leads to more concrete results, more definitive conclusions – Improves chances of publication – Raises the status of SLA as a field of inquiry

8 A word about mixed methods designs The great quan-qual debate Mixed methods – the “best” of both worlds Add a qualitative component to a quantitatively-oriented study: – Participant interviews – Observational, audiovisual data – Open-ended survey questions Plan for qualitative analyses (text analysis, response coding)

9 Part 1 Approaching the Study

10 Approaching the study Hitting upon research ideas Review of the literature Formulating research questions

11 Hitting upon research ideas Identify the topic in a few words Reflect on “doability” of research – Can I research this? – Should I research this? – Am I interested in researching this? Review of the literature can help redefine and revise ideas

12 Identifying the topic: Hints for starting to narrow Pose a short question using “what” or “how” Write a short title that consists of one sentence under 12 words Ask a friend or colleague to read your topic and gauge their reactions Draft research questions to see if the topic can be adequately explored

13 A “researchable” topic “Can I do this in my current situation?” “Does this concern people at other institutions?” “Does this add to the current body of research related to this topic?” “Does this study contribute something from a unique perspective?”

14 Filtering “probably not so good” ideas: To boldly go where no research has gone before… (The “Star Trek” idea) My theory is clearly better than X (The “Steven Krashen is so wrong” idea) My classroom is totally unique (The “I don’t need theory” idea) This is a really cool technology / methodology / text book (The “I am primarily a teacher” idea)

15 Filtering ideas: A few hints Review research designs and statistical techniques Review teaching methods and overall SLA research results Evaluate access to potential study participants Plan time for material creation, study design, and implementation

16 Review of the literature Relate the study to continuing “dialogue” in current research Finding a “gap” in the literature Provide a framework for the importance of the study

17 Review of the Literature: Finding a “gap” in knowledge “We do not enough about X…” “This way of looking at X has never been done…” “This way of learning about X has not been duplicated in my context” “Previous research has inadequately explored X…”

18 Finding literature: Some hints Google Scholar using key words or researcher names Scour recent literature review articles Check for “cited” numbers online Get access to university databases Refer to recently published articles – After the year 2000 – During the previous 2 to 3 years Examine “outside the field” articles

19 Finding literature: Separating the wheat… “Top tier” journal articles Most-often-cited articles Recent articles Research articles (not reviews) Books / Edited book-articles Major international conference papers Dissertations / dissertation abstracts

20 …from the chaff “In-house” journal articles Articles from “proceedings” books Online journal articles with only.html versions Unedited books from small publishers Newspaper and magazine articles Web pages Anecdotal evidence Your own previous papers for an MA course

21 Research questions: A few useful guidelines Naturally flow from the literature review Strongly connected to the topic At least two or three (not one)… …but not five or six or more As specific as possible Directly concern variables in the study Do not contain yes/no question words

22 RQs: What not to ask “Is X true/false?” “Will X happen if…?” “Does X cause Y?” “What do participants think of X?” “Why does X happen?”

23 RQs: What to ask “What differences exist between…” “Compared to X, how does Y…?” “To what degree do X and Y differ…?” “When X is controlled for Y…, how does Z…?” “What are underlying patterns among…?” “To what degree does X predict Y?”

24 Part 2 Developing the Study Design

25 Research design Cross-sectional design: A design in which data are collected from a sample at only one point in time. Longitudinal design: A design in which data are collected at more than one point in time.

26 Randomized Control-Group Pretest-Posttest Design Experimental Group 1 T 1 Xa (Method a)T 2 Experimental Group 2 T 1 Xb (Method b)T 2 Control Group T 1 T 2

27 Randomized Control-Group Pretest-Posttest Design Reasonably strong conclusions can be reached about the effects of the treatments. Problem 1: Within session variation (e.g., different teachers or room conditions) may intervene. The solution? Randomly assigning participants, times, and places to the experimental and control conditions. Problem 2: The pretest may interact with the treatment. This potential problem is dealt with in the next design.

28 Randomized Solomon Six-Group Design Pretested (Random assignment)T 1 Xa (Method a)T 2 Pretested (Random assignment)T 1 Xb (Method b)T 2 Pretested (Random assignment)T 1 T 2 Unpretested (Random assignment) Xa (Method a)T 2 Unpretested (Random assignment) Xb (Method b)T 2 Unpretested (Random assignment)T 2

29 Randomized Solomon Six- Group Design This design amounts to doing the experiment twice –once with and once without pretesting. It is possible to know what effects, if any, are associated with pretesting. If the results of the “two experiments” are consistent, greater confidence can be placed in the findings.

30 Counterbalanced Design This design is useful when randomization is not possible and intact groups must be used. ReplicationXaXbXcXd 1ABCD 2BDAA 3CADB 4DCBC

31 Counterbalanced design The counterbalanced design rotates out the participants’ differences (e.g., one group has more aptitude or motivation than the other groups) by exposing each group to all variations of the treatment. Order-of-presentation effects are controlled. Primary weakness: The possibility of carryover effects from one treatment to the next exists. Allowing time between treatments can alleviate this problem.

32 Control-Group Time-Series Design Experimental Group 1 T 1 T 2 T 3 T 4 Xa (Method a)T 5 T 6 T 7 T 8 Experimental Group 2 T 1 T 2 T 3 T 4 Xb (Method b)T 5 T 6 T 7 T 8 Control Group T 1 T 2 T 3 T 4 T 5 T 6 T 7 T 8

33 Control-Group Time-Series Design This design allows the researcher to determine growth over time, and the effect of an intervention. The presence of a control group increases the trustworthiness of the results because the possibility of a contemporary event causing any gains can be determined.

34 Control-Group Time-Series Design This design can be extended by exposing the participants to the intervention on multiple occasions. This approach is more sensitive to partial gains in knowledge and tests the strength of the intervention more than once, thus giving the researcher a more accurate understanding of the effectiveness of the intervention. Experimental Group 1T 1 T 2 XaT 3 T 4 XaT 5 T 6 Experimental Group 2T 1 T 2 XbT 3 T 4 XbT 5 T 6 Control GroupT 1 T 2 T 3 T 4 T 5 T 6

35 Q&A Break

36 Part 3 Designing the Right Instrument

37 Instrument Design Commonly used instruments in SLA research – Scored tests – Rater scores – Surveys – Interviews Consider your eventual data analysis when developing instruments

38 Instruments - Scored tests Pluses Quantitative items (M/C, Cloze/C-tests) – Simple to score large # of participants – Easier to analyze Qualitative items (short answer, timed essays) – Good complement to quantitative scores – Can provide more in- depth assessment of participants’ abilities Minuses Quantitative items – Limited to one type of data Qualitative items – Take more time/effort to score – Rater bias

39 Instruments – Performance ratings An assessment of participants’ performance in an assigned task Tasks may include presentations, interviews, written essays Performances can be scored using a Likert-scale, a rubric, or holistically Usually scored by at least two “expert” raters; sometimes also by peers

40 Performance ratings Rating criteria should be concretely established with little ambiguity Avoid including too many (or too few) criteria for one performance task All raters should undergo a “normative” training session prior to assessment Use models to train raters Avoid single-score holistic ratings

41 Instruments - Surveys Often used for: – Collecting learner history data (L2 study experience, other background info) – Assessing participants’ attitudes towards a predetermined construct (language learning motivation, anxiety using the L2) – Determining reactions to an experimental treatment (teaching methods, innovative learning tasks)

42 Survey making For non-advanced learners – surveys should be in their L1 Build in redundancy - Include multiple questions for each concept area Questions should be simply worded – avoid negative or confusing wording Depending on the purpose of the survey, 20-40 items/session is a good range to shoot for

43 Survey making Any survey used in a serious study should be piloted in advance It is acceptable to make adjustments to an existing instrument Likert-scale items should usually have between 4 and 6 choices A few qualitative questions can provide a nice complement to quantitative instruments

44 Instruments - Interviews Interviews can provide an excellent qualitative component to a larger study It is not necessary to interview all participants – a subsample as small as 10-20% can be acceptable Use your best judgment on participants’ language ability – For intermediate-and-above learners, L2 interviews are often fine

45 Conducting interviews Inform students they are being interviewed, obtain consent Record unobtrusively “Warm up” the participants before getting into the heart of the interview Collect more data than you need

46 Validating Instruments

47 Instrument Validity The construct = The heart of the matter What construct do you wish to measure? How do you define the construct? What are its component parts? Do they form a unified whole?

48 Operationalizing the construct: The items Conceptualize the construct as a continuum: easy—difficult items and less able—more able persons. How have other researchers measured the construct? Write original or adapted items. Cover the estimated range of your participants. Write 50% more items than you intend to use. This will allow you to “cherry pick” the best items as well as items at various levels of difficulty.

49 Operationalizing the Construct: The Items More able | More difficult persons | items | x | item 1 xx | item 2 item 3 xxx | item 4 item 5 xxxx | item 6 item 7 item 8 xxxx | item 9 item 10 item 11 xxx | item 12 item 13 xx | item 14 x | item 15 | Less able | Less difficult Persons | items

50 Operationalizing the Construct: The Items After piloting the items, statistically analyze the results. Examine dimensionality, item difficulty, and item content. Select the best items to make an efficient, highly reliable instrument.

51 Part 4 Implementing Your Design

52 Implementing the design Including other researchers Practical issues Handling ethical concerns

53 Including other researchers in the study The nature of the researchers involved – Main researcher plus “helpers” – One researcher plus “other participants” The nature of the instructors involved – Teaching methods – Students taught – Course goals – University program goals

54 Working with other researchers Work with people you know and trust Establish a schedule early Define clear roles for each researcher Decide definite research goals prior to data collection Keep in regular contact The “band practice time” principle

55 Example research roles Head researcher / contact person Data entry specialist Statistician Interviewer Literature analyst Editor / proofreader

56 Heading off potential problems Explain study commitments prior to starting the study Agree on “ownership” prior to data collection and data entry – Who will keep the data? – Whose name comes first, second, etc.? Keep everyone aware of deadlines Include everyone in decision-making processed and data analysis

57 Things to avoid in group research People you don’t know Research groups larger than four or five members Using someone for language skills Involving others just to get more participants Forgetting to thank others for their assistance

58 Improving relations with research helpers Write clear instructions Thank profusely for their time and effort Offer to send copies of final research papers and/or results Offer to assist in future research Keep in touch after research ends

59 Practical Issues Timing of implementation Learning and research context Participant consent Financial considerations

60 Timing of the implementation Beginning, middle, or end of semester Day of the week Time of day Exams and exam preparation periods “Culture Festivals” or other club-related events “Open classes” or “parents’ day”

61 Learning and research context Differing course goals (I.e., listening class vs. reading class) Different major field of study Gender, age, year in school Number of class meetings Perception of the value of research by institution heads

62 Participant consent Always allow for “non-participation” choice from potential participants Write clear instructions for participants asking for their cooperation Ask co-researchers or helpers to briefly inform participants about their choice

63 Financial considerations Copies for questionnaires, exams, etc. Computer analysis software Mailing costs Interview travel costs Recording equipment Reference books Journal article costs

64 Heading off lack of cooperation problems Review requirements of the study – How many items in the questionnaire? – How many treatments? Recognize that students are busy, tired, etc. Plan to get between 30-50% more data than you need Try to get more data at a later date

65 Ethical Considerations

66 Ethical considerations Students should not be exploited just because they are there In theory, they should derive benefit (directly or indirectly) from the research Explain the basic purpose of your research before collecting data – 1-2 sentences should be fine It is also good to briefly explain this at the beginning of any survey instrument

67 Ethics - Consent Provide students with the chance to opt out of participation Verbal consent is usually acceptable for surveys, ratings, and test scores A written consent form may be necessary for more involved forms of participation (interviews, essay passages) When in doubt, check recent articles in well-known journals for guidance

68 Ethics – Other considerations The role of this study within your institution Potential gender, proficiency or other issues that may affect your data or conclusions Have a plan for anonymizing the data (and consider making this conspicuous on your instruments)

69 Conclusion

70 In conclusion… There are many factors to consider when embarking on a serious study Some points to take away… Most studies should fill a place (a “gap”) within the current academic dialogue Research questions should reflect continuity with the literature and should be specific Carefully consider the design setup which will work best with the participant groups and the research and analytical goals

71 In conclusion Further points… Different instruments work better in different circumstances. Choose those which best reflect your aims. Plan your analyses at the same time you are developing your instruments Develop and pilot instruments which can cover responses from a range of participants

72 In conclusion Even more points… Work with others who will be serious and committed, and then be an organized and conscientious leader Consider how practical, pedagogical, and institutional concerns may affect your study Do not forget current ethical guidelines for carrying out participant research

73 Good luck with your research! Thank you for listening

74 Q&A

75 For a copy of this presentation:

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