KEFAD Volume 19, Issue 1, April, 2018

Corresponding Author: Selcan Kilis, Asst. Prof. Dr., Giresun University, Turkey, k1selcan@gmail.com, ORCID ID: 0000-

0001-5751-2363

Zahide Yıldırım, Prof. Dr., Middle East Technical University, Turkey, zahidey@metu.edu.tr, ORCID ID: 0000-0001-9095-

2977

*This research was conducted in the scope of doctoral dissertation study of the first author.

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Cite this article as: The citation information will be provided by KEFAD

http://kefad.ahievran.edu.tr

Ahi Evran University

Journal of Kırşehir Education Faculty

ISSN: 2147 - 1037

Metacognition within a Communities of Inquiry Questionnaire:

Validity and Reliability Study of Turkish Adaptation*

Selcan Kilis

Zahide Yıldırım

DOI:...................... Article Information

Received:04/08/2017 Revised:25/11/2017 Accepted:13/03/2018

Summary

This study aims to translate metacognition within a Communities of Inquiry questionnaire into Turkish and

administer its validity and reliability issues. Translation of the 26 items was completed by eight experts

separately and back-translated by two language experts. For pilot testing, data was collected from 304 students

enrolled in fully-online associate degree programs at a well-known public university in Turkey. The data was

analyzed using IBM SPSS AMOS version 21.0 via confirmatory factor analysis for its validity, and internal

consistency values via Cronbach alpha values for its reliability. Confirmatory factor analysis indicated acceptable

fit indices regarding validity, and Cronbach alpha values indicated a high level reliability. Therefore, the Turkish

Metacognition Within CoI Questionnaire may be used to measure learners’ metacognitive skills in collaborative

communities of inquiry. This study therefore fills a gap in the literature with the Turkish Metacognition Within

CoI Questionnaire for the use of Turkish researchers and educators in their studies and learning environment.

Keywords: Metacognition within Communities of Inquiry questionnaire, Validity, Reliability, Confirmatory

factor analysis

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Introduction

There has been rapid development in Internet and telecommunications technology in the 21st

century that has brought about a wide range of facilities in the field of education. Distance education

has gained a new dimension and online learning has started with these developments. Parallel to that,

new skills and competencies are required, both for the students and for their teachers in such learning

environments. Collaboration, social interaction and higher levels of critical-thinking skills gained

importance and are required for students to be able benefit from such learning environments. In order

to fulfill such requirements, Garrison, Anderson and Archer (2000) developed a framework that

guides effective online learning called Community of Inquiry (CoI). The underpinning of this

framework is providing effective online learning by constituting a community and increasing

collaboration and critical-thinking skills. It explains the educational experience with the intersection of

three constructs; namely, teaching presence, social presence, and cognitive presence. The creators of

this framework and many other researchers are still working on the components of the framework.

Metacognition is one of the hot topics in studies related with the CoI framework. It is defined “a

higher-order, executive process that monitors and coordinates other cognitive processes engaged

during learning, such as recall, rehearsal, or problem solving” (Tobias and Everson, 2009, p.108). It can

be defined basically as the awareness and ability of learners to take responsibility and control to

construct their meaning and confirm knowledge for critical thinking and inquiry (Akyol and

Garrrison, 2011).

The activation and development of metacognition is dependent upon learners who are

cognitively and motivationally engaged. Lajoie and Lu (2012) state that a “key mechanism in

improving metacognition or self-regulation is the ability to observe and listen to other perspectives”

(p. 46). In social metacognition, as described by Chiu and Kuo (2009), group members monitor and

control one another’s knowledge, emotions and actions; they agree or disagree with each other’s ideas

and influence each other’s actions through questioning or commands. The premise here is that sharing

and collaboration are important activities to develop and sustain metacognition (Brown, 1987; Larkin,

2009; Schraw, 2001; Wade and Fauske, 2004; White, Frederiksen, and Collins, 2009). This position leads

to the conclusion that a conceptual and analytical framework is needed in order to develop a

metacognitive construct consistent with a collaborative learning environment. Similarly, the challenge

with social models of self-regulated learning (SRL), as indicated by Hadwin and Oshige (2011), is that

“there is great diversity in where social is positioned in the [SRL] model” (p. 242). Therefore,

significant questions about the constructs and dynamics of metacognition in online learning contexts

remain unanswered.

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Related to the CoI framework and metacognition, some of the opinions voiced by researchers

are seen as controversial. Some authors suggest adding a new construct as learning presence to the

model (Shea et al., 2012). However, the developers of the framework disagree with the statement and

claim that metacognition is already inherent in the structure of the model (Garrison and Akyol, 2013).

They also suggest that research studies should continue around this issue. In order to make

metacognition construct clearer in the structure of CoI framework, and to help researchers measure

metacognition in CoI in a more concrete way, Akyol, Garrison, and Vaughan (2012) developed

metacognition (self & co-regulation) within a CoI instrument. Initially it was developed qualitatively,

derived based on the literature around metacognition and self-regulation (Akyol and Garrison, 2011).

The authors then developed a quantitative questionnaire in order to measure metacognition, which is

known to be difficult to assess through online transcription analysis of discussion posts. Its pilot

testing was conducted by Akyol et al. (2012). Validation process and tests of the instrument were

conducted by Garrison and Akyol (2013).

The original language of the instrument is English, and it consists of 26 five-point, Likert-type

(indicating 1-strongly disagree, 2-disagree, 3-neutral, 4-agree and 5-strongly agree) items in total. The

instrument consists of three subscales namely knowledge of cognition (KC) with eight items,

monitoring of cognition (MC) with eight items, and regulation of cognition (RC) with 10 items. The

items were formed based on the indicators of the three categories of metacognition construct

introduced by Akyol and Garrison (2011). The validity of the original instrument was administered

with 76 students (53 undergraduate, 23 graduate) at a large university in Canada. Factor analysis was

applied and oblique rotation for factor loadings was conducted. The findings indicated the three

factors in the instrument (Garrison and Akyol, 2013).

Method

This current empirical study aims to translate the Metacognition Within a CoI Questionnaire

into Turkish and report its validity and reliability issues.

Participants and Data Collection

An empirical study requires adequate sample size in order to conduct statistical analysis and

to obtain reliable results (Pearson and Mundfrom, 2010). After the translation process of the

instrument was complete, reliability and validity issues were assessed for the Turkish translated

version of metacognition within a CoI questionnaire.

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The data was collected face-to-face using a paper-based format from students enrolled to an

online associate degree program of a large public university in Adana, Turkey. The participants were

requested to respond to the instrument just prior to their final exam. In total, 444 students responded

to the instrument; however, 140 contained missing data and were therefore excluded from the

accepted data. The final number of respondents was 304 students. Participation was voluntary and all

information provided was treated as confidential.

Regarding the issues of adequate sample size, different opinions are evident in the literature.

According to Gorsuch (1983) and Kline (1994), the minimum required sample size to conduct

confirmatory factor analysis should be 100 subjects. Some authors stated minimum ratios of sample

size to the number of variables. Cattell (1978) suggested three to six subjects per variable while Hair,

Black, Tatham and Anderson (2010) presented at least five ratios. Everitt (1975) and Nunnally (1978)

recommended at least ten times as many subjects as variables. Regarding the adequacy of sample size,

based on the aforementioned recommendations, the minimum required sample size for the current

study should be 100 according to Gorsuch (1983) and Kline (1994), 52 based on Cattell (1978), 130 for

Gorsuch (1983), and 260 for Everitt (1975) and Nunnally (1978). In the current study, 304 students

participated in the data collection. This exceeds the various statements found in the literature, and

therefore the sample size was accepted as satisfactory to conduct confirmatory factor analysis.

Of the 444 students who responded to the instrument, 304 students’ responses were included

in the analysis. Of the 304 students, 174 were female and 136 were male; with four not declaring their

gender. Ages ranged from 18 to 42, with the majority (39%, n=120) aged 18-22, followed by 23-27 (24%,

n=73), 28-32 (20%, n=61), 33-37 (13%, n=40), and 38-42 (3%, n=10). Respondents’ disciplines included

Electronic Communication Technology (31%, n=93), Computer Technology and Programming (19%,

n=58), Pediatric Development (42%, n=128), and Accounting and Tax Practices (8%, n=25). Each of

these departments offered fully-online associate degree programs, with just the final exams conducted

face-to-face in controlled classroom conditions. More than half of the students were freshman (59%,

n=180), with the remaining as sophomores (41%, n=124).

Data Collection Instrument

In the current study, data was collected with the Turkish translated version of the

Metacognition Within CoI Questionnaire. The instrument was originally developed by Akyol et al.

(2012) as an English language instrument with 26 items in total; comprised of “knowledge of

cognition” (eight items), “monitoring of cognition” (eight items) and “regulation of cognition” (ten

items). The instrument was developed in a five-point, Likert-type response format indicating 1-

strongly disagree, 2-disagree, 3-neutral, 4-agree and 5-strongly agree. The original instrument was pilot-

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tested via factor analysis with 76 students (53 undergraduate, three graduate) at a large university in

Canada (Akyol et al., 2012).

For the current study, the instrument itself and permission to translate it to Turkish was

sought from the original developers of the instrument via e-mail. The original instrument was

translated into Turkish and back-translated to its original language of English within the scope of the

translation procedure outlined in this study. The Turkish translated version of the Metacognition

Within CoI Questionnaire was used in the data collection process to assess issues of validity and

reliability.

Translation Process

The aim of the current study is to adapt the Metacognition Within CoI Questionnaire to

Turkish and assess the validity and reliability features of the translated version of the instrument. In

the current study, the approach employed was back-translation method. Based on the literature

(Büyüköztürk, Uslu, and Akbaba Altun, 2017; Güngör, 2016; Hair, Black, Tatham, and Anderson,

2010; Tabachnick and Fidell, 2013), confirmatory factor analysis was applied in testing the translated

version of the instrument. Translation and back-translation of the instrument’s 26 items were

performed separately and sequentially.

As can be seen in Figure 1, which illustrates the translation process, the items were first

translated by the researchers and then separately by four independent experts who were each

experienced in the field and are proficient in English. The translated versions were then compared and

revised in a second phase. Next, the first revised version was sent to two experts considered more

experienced in the field who then separately translated the questionnaire into Turkish. In a third

phase, their translations were then compared by the researchers and any required changes applied to

form a second revised version. For the fourth stage, the Turkish version of the Metacognition Within

CoI Questionnaire was reviewed for content, conceptual equivalence of the items in two languages,

grammar and meaning by a professor whose focus has been cognitive and metacognitive constructs

for many years. Based on her feedback, the necessary changes were applied, and the final version of

the instrument was formed.

After the translation process was completed, the translated instrument was sent to two

modern language experts from the Department of English. The two language experts each performed

back-translation. The original and back-translated versions were then compared by the researchers in

order to be sure that the translation was correct and that each was a good fit in both directions. The

Turkish version of the Metacognition Within CoI Questionnaire is provided in the Appendix.

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Figure 1. Translation process

Data Analysis

The data was analyzed using IBM SPSS AMOS version 21.0 via Confirmatory Factor Analysis

(CFA) for its validity, and internal consistency assessed via Cronbach alpha values regarding its

reliability. CFA was considered the statistically appropriate way of testing the adapted instrument

(Büyüköztürk et al. 2017; Güngör, 2016; Hair et al., 2010; Tabachnick and Fidell, 2013) since it was not

developed from scratch, but rather an adaptation an existing instrument; hence there was no need to

conduct Exploratory Factor Analysis (EFA). Additionally, no items were added or removed from the

original instrument while adapting it to Turkish, hence almost perfect values were achieved from CFA

for its validity and reliability.

Before conducting the analysis, required assumptions were checked. In terms of minimum

adequate sample size, with 304 subjects’ responses, the sample size was deemed to be more than

adequate (Field, 2013; Guilford, 1954; Hair et al. 2010; MacCallaum and Widaman, 1999). Univariate

and multivariate normality were checked in AMOS using skewness and kurtosis values, and the data

were provided normality assumptions. Returned instruments containing missing data (n=140) were

eliminated from the data.

Results

The results are explained in two parts, in accordance with the aim of this study, first for

validity issues and then for reliability issues.

Results for Validity

In terms of validity checks, CFA was conducted via IBM SPSS AMOS version 21.0 to

investigate the construct validity. For the estimated model of the translated instrument, the goodness

of fit indices used in this analysis are χ2/df (Chi-Square/Degree of Freedom), Root Mean Square Error

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of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR), Goodness of Fit Index

(GFI), Adjusted Goodness of Fit Index (AGFI), Comparative Fit Index (CFI), and Tucker-Lewis Index

(TLI). The findings are presented in Table 1.

Table 1. CFA fit indices of Turkish metacognition within CoI questionnaire

Goodness of Fit

Statistics

Perfect Acceptable Original

Version

Translated

Version

χ2/df ≤3 ≤5 -- 2.25

RMSEA ≤.05 ≤.08 -- .06

RMR ≤.05 ≤.08 -- .05

SRMR ≤.05 ≤.08 -- .04

TLI ≥.95 ≥.90 -- .94

CFI ≥.95 ≥.90 -- .94

GFI ≥.95 ≥.90 -- .85

AGFI ≥.90 ≥.85 -- .83

NFI ≥.95 ≥.90 -- .89

*p<.01

According to the findings, with a χ2/df ratio value of 2.25, the translated instrument is

acceptable. The other goodness of fit values were found to be RMSEA=.06, RMR=.05, SRMR=.04,

TLI=.94, CFI=.94, GFI=.85, AGFI=.83, and NFI=.89. According to these values, it can be said that GFI,

AGFI, NFI observable fit values were slightly lower than acceptable value, however they are close to

acceptable fit values, while RMSEA, SRMR, and RMR fit values indicate a perfect or close to perfect fit

(Table 1). In other words, the obtained model indicated that the factors were confirmed by the data

(Çokluk, Şekercioğlu, and Büyüköztürk, 2010; Sümer, 2000; Tabachnick and Fidell, 2013).

The item-factor structure of the Turkish version of Metacognition Within CoI Questionnaire is

illustrated in Figure 2. As can be seen, all indicators of the observed variables KC, MC, and RC appear

to be almost equal based on their standard regression weights (factor loadings); which can be

interpreted as the correlation between the observed variable and the corresponding common factor.

The path diagram also shows the squared multiple correlation coefficients (R2) that describes the

amount of variance the common factor accounts for in the observed variables. For instance, the highest

amount of explained variance is for MC, with 72% of the variance in MC3. The lowest amount of

explained variance is for RC, explaining 41% of variance in RC4. Moreover, the correlations between

the common factors are displayed in the path diagram. The correlation shows a value of .89 between

KC and MC, .90 between MC and RC, and .86 between KC and RC.

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Figure 2. Item-factor structure of Turkish metacognition within CoI questionnaire

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Results for Reliability

For reliability testing, internal consistency was examined using the Cronbach alpha values for

each factor. The results are provided in Table 2.

Table 2. Reliability statistics for Turkish metacognition within CoI questionnaire

Factor Cronbach’s Alpha

Metacognition 0.94

Knowledge of Cognition (KC) 0.97

Monitoring Cognition (MC) 0.93

Regulation of Cognition (RC) 0.93

*p<.01

The coefficient alpha values for the factors of the instrument were found to range from .97 to

.93, and .94 for the whole instrument. All the factors have alpha values higher than .70 (Hair et al.,

2010) and are very close to 1.00. Therefore, all the factors showed almost perfect internal consistency.

Overall, the results of pilot testing indicated that the Turkish Metacognition Within CoI

Questionnaire (see Appendix) was proven as valid, reliable and acceptable.

Discussion and Conclusion

In the current research, the Metacognition Within CoI Questionnaire was translated and

adapted to Turkish, and then its validity and reliability was assessed through data collected from 304

students enrolled in fully-online associate degree programs of a well-known public university in

Adana, Turkey.

Confirmatory factor analysis showed that the fit values were found as χ2/df=2.45, RMSEA=.06,

RMR=.08, SRMR=.06, TLI=.89, GFI=.86, AGFI=.84, CFI=.90, and NFI=.80. It can be said that although

GFI observable fit value was slightly lower than the acceptable value, RMSEA, SRMR and AGFI fit

values indicated an acceptable fit and the other observable fit values indicated a perfect fit. According

to these values, it can be said that GFI, AGFI, CFI, TLI and NFI observable fit values were slightly

lower than acceptable value, but very close to good fit values while RMSEA, SRMR, and RMR fit

values indicated an acceptable and good fit.

The Cronbach alpha value for the whole instrument was found to be .94, with its three factors

ranging from .97 (knowledge of cognition) to .93 (monitoring of cognition, and regulation of

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cognition). Cronbach alpha values indicating internal consistency were very high. Also, as all three

factors have alpha values higher than .70, all factors therefore showed acceptable internal consistency

(Hair et al., 2010).

As a result, it can be said that the Turkish adaptation of the Metacognition Within CoI

Questionnaire has a high level of validity and reliability. The instrument is therefore a valid and

reliable tool in order to evaluate learners’ metacognitive skills in any kind of learning setting.

Researchers and instructors can use the questionnaire to reveal strengths and weaknesses.

As the original questionnaire had no Turkish version, this study fills a gap in the literature.

Additionally, many universities in Turkey have online education programs. It is important to facilitate

the metacognitive skills of online learners in order that they benefit from such learning environments.

This questionnaire helps both online instructors and designers of online learning environments

determine the metacognition of students and take appropriate actions in their practices. Subsequently,

Turkish researchers and educators may benefit from application of the Turkish adaptation of the

Metacognition Within CoI Questionnaire in their national learning settings.

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Appendix

Turkish Metacognition Within a Communities of Inquiry Questionnaire

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Bilişselliği Bilme

1. Öğrenci olarak güçlü yanlarımı biliyorum.

2. Öğrenci olarak zayıf yanlarımı biliyorum.

3. İyi derecede eleştirel düşünme becerisine sahibim.

4. İyi derecede problem çözme becerisine sahibim.

5. Hangi faktörlerin düşünme ve öğrenmemi geliştirebileceğini biliyorum.

6. Öğrenme sürecinin başındaki motivasyon durumumu biliyorum.

7. Başarı için sahip olduğum olanakları net bir şekilde biliyorum.

8. Öğrenme görevleriyle ilgili var olan bilgi ve deneyimlerimi biliyorum.

Bilişselliği İzleme

9. Görevlerin zorluğu hakkında değerlendirme yaparım.

10. Öğrenme süreci boyunca gösterdiğim çabamın farkındayım.

11. Öğrenme süreci boyunca düşünme seviyemin farkındayım.

12. Öğrenme süreci boyunca duygularımı sürekli denetlerim.

13. Öğrenme süreci boyunca ne anladığımı bilinçli bir şekilde

değerlendiririm.

14. Anladığımı doğrulamaya ihtiyacım olduğunda bunu fark ederim.

15. Dersteki diğer katılımcıların fikirlerine/ne anladıklarına/yorumlarına

dikkat ederim.

16. Bir ödeve nasıl yaklaştığımız hakkında düşünürüm.

Bilişselliği Düzenleme

17. İleri seviyede öğrenmeye ulaşmak için hedefler belirlerim.

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18. Öğrenme gayretimi artırmak için yaklaşımımda değişiklik yaparım.

19. Düşünmemi derinleştirmek için sorular sorarım veya bilgi talep ederim.

20. Kendimi ve dersin diğer katılımcılarını başarmak için zorlarım.

21. Dersin diğer katılımcılarının öğrenmesine yardımcı olmak için

önerilerde bulunurum.

22. Daha iyi anlamak için özel stratejiler uygularım.

23. Zorlukla karşılaştığım zaman yardım isterim.

24. Anlamada zorluk çektiğim zaman hedeflerimde veya stratejilerimde

değişiklik yaparım.

25. Stratejimi ödeve bağlı olarak değiştiririm.

26. Daha iyi anlamak için kaygılarımla baş etmeye çalışırım.