Motivation in a Homogenous IEP: The Big Picture

Lisa Levine, Paula WinkeMichigan State University

TESOL ConferenceMarch 23, 2013

We will

1.Give a brief overview of our research project:• Changes at MSU's ELC• Research questions• Method• Results• Discussion

2.. Talk about what our findings may mean for IEPs

like ours at MSU

3. Q & A

We won't be able to answer such questions as these (yet):• How can I increase my students' desire to learn

English?

• Why are there significant differences in attitudes toward

learning English among students of different

nationalities?

• Why won't they stop playing games on their cell phones

during class?

Michigan State University English Language Center Intensive English Program

200720130

100

200

300

400

500

600

700

800

900

IEP Students (approximate numbers)Full-Time Faculty(Including Continuing Special-ists)

Research Questions (Exploratory) 1. Are there any personal background characteristics, such as nationality or L1, that are associated with aspects of L2-learning motivation?

2. In addition, how does current living situation (English-speaking roommates, for example) relate to motivation?

   

  

Materials• Anonymous

Survey-Monkey administered survey, 4 versions:• Arabic• Chinese• English• Korean

18 Background Questions 48 L2-learning Motivation Questions

Sample items (1 – 6 Likert scale)

• When I am in class I volunteer as

much as possible.

• I am sure one day I will be able to

speak English well.

• Studying English is important to me

to gain the approval of others.

MOTIVATION

Sample items (multiple choice)

• What is your home

country?

• China

• Korea

• Saudi Arabia or other Arabic-

speaking country

BACKGROUND

Outside of class, who do you

spend most of your time with?

• Native speakers of your first

language

• Native speakers of English

• Native speakers of another

language

CURRENT CIRCUMSTANCES

Sample items (open-ended)

• What is your major?

• How old are you?

• What other foreign languages have

you studied?

Survey items related to “Linguistic self-confidence” (Factor 1)

Survey items related to “Ought-to L2 Self” (Factor 2)

Survey items related to “Imagined L2 Self” (Factor 3)

Survey items related to “Integrative attitude” (Factor 4)

Survey items related to “Language-learning anxiety” (Factor 5)

Survey items related to “Attitude Toward Native Speakers” (Factor 6)

Q11. It’s easy to become friends with native English speakers on campus.

Procedure

• Survey creation in Spring 2012

• Pilot (beta) testing in Summer 2012

• Survey Monkey forms created after factor analysis on spring alpha test data

• Survey given to new students in Fall 2012

75 students

262

students80 items

48 items

Participants (Just who were these learners?)

Arabic N=112

Chinese N=199

Other N=17

Korean N=9

Total N=337

Av. Age 26 (9.09) 19 (1.22) 21 (3.32) 30 (12.53) 22 (6.55)

Av. Residency in USA

1 yr 5 months 5 months 4 months 6 months

Male/Female 70/41 (37% F)

120/76 (39% F)

5/14 (74% F)

7/2 (22% F)

202/133 (40% F)

Notes. For age, within parentheses = SD. Not all 337 indicated their gender.

Data Analyses•1.Exploratory factor analysis to see how the 48 motivation items group (or divide up) into different aspects (factors) of motivation

•2.Comparison of means on the factor scores (t tests and ANOVAs) by L1 group

•3.Regression (prediction) analysis to see which background variables (length of time in USA, age, gender) predict motivation

21

How Factor Analysis Works

•Factor analysis runs correlations among the answered items to see what items are related—that is, what questions tap into the same underlying construct.

Item 1

Item 3

Item 2

Item 4

Item 5

Item 6

Item 7

Item 8

Item 9

Item 10

• After items are clustered together with other items that were answered in the same way, we can look at the items in the cluster and label the cluster—what is the theme of the cluster?

Factor 1

Factor 2

• Items that don’t correlate with any larger factor (that don’t fit into a cluster) can be dropped from further analysis or discussion.

L2 Self-Confidence

L2-Classroom Self

6 Factors that Emerged from the Data

Ought-to L2 Self2Q28. I should learn English or else people may think that I am a poor learner. (11 items)

L2 Self Confidence1 Q10. This semester, I think I am good at learning English. (5 items)

Imagined L2 Self3Q16. I can imagine myself being a person known as a fluent speaker of English. (4 items)

L2 Classroom Self4 Q24. When I am in English class, I volunteer answers as much as possible. (5 items)

Peer/Family Influ.5 Q12. I study English because close friends of mine think it is important. (2 items)

Attitude twrd NSs6 Q11. It’s easy to become friends with native English speakers on campus. (2 items)

Max. likelihood EFA. Each factor had an eigenvalue greater than 1. The items explained 47% of the questionnaire score variance.

6 Factors that Emerged from the Data

Ought-to L2 Self2

L2 Self Confidence1

Imagined L2 Self3

L2 Classroom Self4

Peer/Family Influ.5

Attitude twrd NSs6

Each individual in the database got an average score on each of these 6 aspects (or factors) of motivation.

We then looked for differences in group averages on the factor scores.

First, we looked to see if L1-background was associated with higher or lower scores on these motivation aspects (using ANOVAs).

6 Factors that Emerged from the Data

L2 Self Confidence1

Imagined L2 Self3

L2 Classroom Self4

Attitude twrd NSs6

L1-Arabic higher on this than any others.

L1-Chinese higher on this than any others.

L1-Chinese higher on this than any others.

Trend: L1-Korean lower on this than others.

So what does this mean? Does this mean that L1 Arabic speakers have a higher L2-self image?

And that L1-Chinese have a better view of their future-L2 selves and have a better view of themselves in the L2-classroom?

And that L1-Koreans have a lower attitude toward NSs?

Eeek! Maybe...

Or probably not... (?)

6 Factors that Emerged from the Data

Ought-to L2 Self2

L2 Self Confidence1

Imagined L2 Self3

L2 Classroom Self4

Peer/Family Influ.5

Attitude twrd NSs6

Second, we looked to see if other, more interesting background characteristics were associated with higher or lower scores on these 6 motivation aspects (using independent samples t tests if we compared 2 groups; ANOVAs if 3 or more groups):

• With your roommate(s), do you speak in your L1 or in English?

• Outside of class, in which language do you mostly speak? (see your handout)

6 Factors that Emerged from the Data

L2 Classroom Self4

• With your roommate(s), do you speak in your L1 or in English?

• On average, for those with roommates or housemates, those who wrote they spoke in the target language (English) at home also indicated they had a higher "classroom self-image" (M=3.75) than those who spoke their L1 at home (M=3.56). This difference was significant, t(275) = 1.96, p = .05. But the effect is small.

We thought this was interesting, so we looked at WHO is speaking with roommates in English by L1 and gender...

6 Factors that Emerged from the Data

Ought-to L2 Self2

L2 Self Confidence1

Peer/Family Influ.5

Attitude twrd NSs6

• Outside of class, in which language do you mostly speak?

• On average, those who wrote they spoke primarily in English outside of class indicated they had o a higher "L2 self image,"o lower "ought-to self," o higher "peer-family awareness,"

and o higher "attitude toward NSs"

than those who spoke their L1 outside of class. These differences were significant.

We used regression (prediction) analysis to test this model of motivation…

• Values are standardized coefficients (Betas). For age, the only significant predictor, B = -.107.

Length of time in USA

Age

GenderL2 Motivation

(with all six factors weighted

equally)

-.162, p = .006

-.025, p = .699

-.063, p = .288

These are correlated variables…What is interesting to us is that there is, in general, less variation and a downward trend in motivation with age.

• r = .20**

DiscussionThe theory of motivation, that it consists of various factors such as Ideal L2-Self, Imagined L2-Self, and Ought-to L2-Self (theories by Dornyei, 2005; Csizer & Dornyei, 2005; Csizer & Kormos, 2008; Dornyei (Ed.), 2013) holds with our data. (In other words, these theories of L2-motivation make sense to us in relation to our data.)

In particular, Csizer and Kormos (2009) stated this:

"Our model [of L2-learning motivation] indicates that for our participants, motivated behavior is determined not only by language-related attitudes, but also by the views the students hold about the perceived importance of contact with foreigners" (p. 166).

Discussion

• In our study, we think students regulated their motivation by acting on their perceived importance of contact with host-country nationals (Americans on campus) and their perceived importance of speaking in English outside of class.

• Higher indications of motivation were associated with 1. Living with native-English-speaking roommates2. More positive attitudes toward or experiences with

Americans on campus3. More English-speaking outside of class

DiscussionThis relates to research on study abroad & identity construction.

More contact with host-country nationals and more communication in the targeted language (be it with host-country nationals or with other internationals) helps shape self-perception (identity construction), attitudes, classroom behaviors, motivation, and (as reported by others) L2-learning outcomes.

Norton, B. (2001). Non-participation, imagined communities, and the language classroom. In M. Breen (Ed.), Learner contributions to language learning: New directions in research (pp.156- 171). Harlow: Pearson Education.

Perez Vidal, C., & Howard, M. (2012). Study abroad and language acquisition. International Journal of Applied Linguistics, 22(2), 279-280.

Kinginger, C. (2011). Enhancing language learning in study abroad. Annual Review of Applied Linguistics, 31, 58 – 73.

Kinginger, C. (2011). National identity and language learning abroad: American students in the post-9/11 era. In C. Higgins (Ed.), Identity formation in globalizing contexts: Language learning in the new millennium (pp. 147–166). Berlin: Mouton de Gruyter.

Q & A

• Do our findings resonate with your experience at other

IEPs?

• How do you think these data could be used to help IEPs

best meet student needs in the future?

• What further research directions do you think our data

suggest?

Thank you!

Lisa Levine: llevine@msu.edu Paula Winke: winke@msu.edu