Same but different? Measurement invariance of the PIAAC motivation-to-learn scale across key socio-demographic groups

Abstract

BackgroundThe release of the (first round of ) PIAAC data in 2013 has drawn educational researchers' attention to a thus far neglected target group in education: adult learners. With respect to literacy, numeracy, and problem solving in technology-rich environments (ICT) skills, PIAAC data reveals differences across the participating countries (OECD 2013a). Going beyond cross-national comparisons, the general OECD report (OECD 2013a) and country-specific publications (e.g., Maehler et al. 2013; Statistics Canada 2013) provide in-depth analyses of specific population subgroup competencies that are relevant for researchers, educators, and policy-makers alike. These analyses show systematic skill differences across gender, age groups, level of education, and migration Abstract Background: Data from the Programme for the International Assessment of Adult Competencies (PIAAC) revealed that countries systematically differ in their respondents' literacy, numeracy, and problem solving in technology-rich environments skills; skill levels also vary by gender, age, level of education or migration background. Similarly, systematic differences have been documented with respect to adults' participation in education, which can be considered as a means to develop and maintain skills. From a psychological perspective, motivation to learn is considered a key factor associated with both skill development and participation in (further) education. In order to account for motivation when analyzing PIAAC data, four items from the PIAAC background questionnaire were recently compiled into a motivation-to-learn scale. This scale has been found to be invariant (i.e., showing full weak and partial strong measurement invariance) across 21 countries.Methods: This paper presents further analyses using multiple-group graded response models to scrutinize the validity of the motivation-to-learn scale for group comparisons. Results:Results indicate at least partial strong measurement invariance across gender, age groups, level of education, and migration background in most countries under study (all CFI > .95, all RMSEA < .08). Thus, the scale is suitable for comparing both means and associations across these groups. Conclusions: Results are discussed in light of country characteristics, challenges of measurement invariance testing, and potential future research using PIAAC data. Open Access© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Motivation to learn by age, education, and literacy skills among working-age adults in the United States

“…Women also are more likely than men to see education as a pathway to upward social mobility (i.e., economic gain; (Wlodkowski & Ginsberg, 2017). Overall, gender consistently has been included in education research (e.g., Gorges et al, 2017;Smith et al, 2015).…”

“…Recent studies have adopted the 4-item PIAAC MtL scale or a modified version and reported adequate psychometric properties with the middle-aged and older adults (Liu et al, 2019;Yamashita et al, 2019). Gorges et al (2017) further examined the psychometric properties of the There are two major reasons why MtL at the adult population level has been overlooked. First, to our best knowledge, nearly all studies focusing on MtL have used nonrepresentative or convenience samples (Gegenfurtner & Vauras, 2012).…”

“…First, to our best knowledge, nearly all studies focusing on MtL have used nonrepresentative or convenience samples (Gegenfurtner & Vauras, 2012). Some exceptions include studies using the PIAAC data (e.g., Gorges et al, 2016Gorges et al, , 2017Yamashita et al, 2019). Gorges et al (2017) conducted rigorous measurement invariance analysis and showed the comparability of the PIAAC-based MtL scale scores across gender (female and male); age (early working age 16-29, mid-life working age 30-49, later working age 50-65); education level (low, intermediate and high level); and immigration background (based on native language) among the U.S. population.…”

Post-educational motivation to learn cognitive skills in three European labour markets. A comparative analysis of the PIAAC

“…MtL is assumed to be formed with reference to learning activities in the school setting, but potentially also, among more mature workers, to additional vocational education on-the-job. Yet, despite this potential variance in how individuals interpret the concept of learning, the MtL-scale has been shown to be remarkably robust across different age groups and comparative contexts (Gorges et al 2016(Gorges et al , 2017. This research suggests that different age groups have a quite comparable interpretation of what 'learning' is, and that they relate to a similar phenomenon when responding about their MtL.…”

Analysing PIAAC Data with Structural Equation Modelling in Mplus

“…A CFA model assuming a single latent variable measured by the six item responses and treating these responses continuously resulted in a marginal fit to the data, χ 2 (9) = 516.4, p < 0.001, RMSEA = 0.074, CFI = 0.926, SRMR = 0.043. Gorges et al (2017) reviewed the theoretical anchoring of the six items in existing curiosity frameworks and argued that four items (I_Q04D, J, L, M) represented the construct. Moreover, evaluating the factor loadings revealed that items I_Q04B and I_Q04H showed lower values in comparison to the remaining items-this observation indicates that they represent what is shared among all items to a smaller extent.…”