Student Centred Learning (SCL) is a core point in the EHEA agenda. During the second part of the 20th century the European education systems have assumed the learning paradigm instead of the instruction’s (Altbach, 2002), an affair that meant considerable efforts (Heise & Himes, 2010). One of the main reasons for SCL was short-term change as a constant in the knowledge-based society and economy. In fact, the last research papers discussed how education systems may cope with change (Säfström, 2018).

In 2006, after the OECD implemented the Project DeSeCo in 90s, the EU (2018) wrote its own purpose on learning key competences for students to sustainably holding on the labour market. By then, eight generic competences were defined and one of them was ‘learning to learn’. This competence is supposed to impact on all the others and, after all, adapting to changes entails to make knowledge from information every time. This is to say, it implies learning to learn, which becomes a strategic skill for employability after bachelors’ programmes to the extent that labour market is linked to regular fluctuations.

Background

Europe's position on higher education is nothing new. SCL is based on a long history of research on self-regulated learning and learning strategies since the 80s and 90s to the present day. Among these studies, it may well be mentioned those of Bandura, Boekaerts, Pintrich, Winne and Zimmerman, for saying some of them. See the compilation works by Panadero (2017) and by Thoutenhoofd & Pirrie (2013) for a review.

Even before that, courses were held to learn categorization, interpretation and principle-application in the decade of the 60s (Taba, 1966). In that moment, metacognition grew in importance, but it was not until the end of the century that affective, motivational and social components were incorporated into the theoretical models. That is, the propose of the EU about the ‘learning to learn’ competence is strongly based on a really solid background, developed meticulously over the years.

Reference models for assessment

The 'learning to learn' competence has been established for assessment in several contexts; however, we took three research projects and an in-depth review as main references.

• The Project LEARN (Hautamäki et al., 2002) provided three chief dimensions about contextual and personal beliefs, and learning competences.
• The Project by the Centre for Research on Education and Lifelong Learning (CRELL) (Hoskin & Fredriksson, 2008) considered four previous instruments including that of the Project LEARN, but never got common European standards.
• The Project Tuning only set down procedures for assessing, but not reliable and valid instruments (González & Wagenaar, 2003).

The review by Stringher (2014) was especially useful, taking into account 40 definitions and 90 studies on learning to learn. Nevertheless, we though it is necessary to complete this competence with other elements, such as an ethical dimension which has not been included before. Moreover, the previous projects seemed to be unfinished or, at least, a common agreement for reliability and validation of an instrument is not overcome.

Aim and research question

Indeed –and regrettably–, scholars have not agreed yet what does this competence consist of, as noted when reading hand books on this topic (Deakin Crick, Stringher, & Ren, 2014). Therefore, the research problem here attached is the need for an operative, theoretical model and for an agreement. In this line, our Research Group on University Pedagogy, Teaching and Learning (GIPU-EA[1]) aimed to define one own model and to find an agreement. The model has five dimensions: cognitive, metacognitive, affective-motivational, social-relational and ethical.

[1] Funding details: National grants EDU2017-83284-R, Ministry of Economy and Business; and BOE-B-2017-72875, Ministry of Education, Culture and Sport.

Participants Bearing in mind the Working Groups to follow up the Bologna Process, we detected four key informants to conduct a content validation. The participants were professors (n=19), students (n=16), employers (n=14) and employees (n=18); and a smaller group of experts (n=6) was also inquired about. All participants (n=73) were found in three areas: Educational Sciences, Health Sciences or Engineering. Design Sampling was non-probabilistic and incidental, and the experts were carefully selected for their expertise. Instruments The informants rated the relevance of the contents of ‘learning to learn’ as provided in the GIPU-EA model. They filled in a 5-point Likert scale where eighteen general categories were attributed to each dimension: • Cognitive1. Effective information management. • Cognitive2. Oral communication skills. • Cognitive3. Written communication skills. • Cognitive4. ICT management. • Cognitive5. Critical and creative thinking. • Metacognitive6. Knowledge of oneself, of the task and tackling. • Metacognitive7. Planning, organization and management of time. • Metacognitive8. Self-evaluation, control and self-regulation. • Metacognitive9. Problem solving. • Affective-motivational10. Positive attitudes towards learning and improvement. • Affective-motivational11. Internal attributions. • Affective-motivational12. Self-concept, self-esteem and self-efficacy. • Affective-motivational13. Physical and emotional well-being and anxiety control. • Social-relational14. Social values. • Social-relational15. Positive attitudes towards cooperation and solidarity; relationships. • Social-relational16. Teamwork. • Social-relational17. Control of environmental conditions. • Ethical18. Values and attitudes. Procedure First of all, a systematic literature review was carried out to design an operative theoretical model, including the findings of previous research projects, reviews and other studies of interest that might help in designing our model (Gargallo, Suárez-Rodríguez, & Pérez-Pérez, 2009; Weinstein, Husman, & Dierking, 2002). After that, the groups of participants were blocked by type of informant and by area of knowledge to avoid information flows between subjects from different backgrounds as much as possible. Data analysis All the dimensions of the model were normally distributed, except ED (KS=.1.97, p=.001). For this reason, non-parametric tests were computed to figure out the agreement between subjects. Two grouping variables were settled for this part of the analysis: the type of informant and the area of knowledge. Inter-rater reliability was also computed as recommended by Viladrich, Angulo-Brunet, & Doval Diéguez (2017) for ordinal datasets. We made that decision due to ED had only one general componential category and, thus, λ scores could be obtained in individual factor analyses for the other dimensions. Therefore, the denominator for Omega coefficient was the product of the polychoric correlations multiplied by 2, and all by the number of levels in the scale.

The GIPU-EA model was highly rated and not only that, but error bars were also obtained based on standard deviations adapted to the normal curve multiplying by 1.96. This bars ensure that, with a confidence interval of 95%, the scores were anyhow in the highest mid of the scale. Inter-rater reliability was rather high, being always ω greater than 0.7. Although these factors could be obtained as a latent variable, a construct validation is not our purpose in this phase of the research. When designing an instrument, then it will be the moment for conducting confirmatory factor analyses and, based on them, assessing the validity of the construct. Before that, it is necessary to get a content validation and that is what we aimed in this study, with the subsequent limitations. Non-parametric tests showed no disagreement in any of the five dimensions, neither between subjects, nor between knowledge areas: cognitive (subjects x^2=0.221, p=.994, areas x^2=2.232, p=.313), metacognitive (subjects x^2=3.613, p=.461, areas x^2=1.738, p=.419), affective-motivational (subjects x^2=3.277, p=.513, areas x^2=2.389, p=.303), social-relational (subjects x^2=2.424, p=.658, areas x^2=5.801, p=.055) and ethical (subjects x^2=2.092, p=.719, areas x^2=0.302, p=.860). Differences between areas were only found in the Cognitive1 (x^2=6.76, p=.034), Cognitive5 (x^2=10.85, p=.004), Metacognitive6 (x^2=6.09, p=.047) and Social-relational15 (x^2=8.385, p=.015). Future studies should delve into ED for extracting different components in the model so that could be more likely to know the reliability of the relevance attributed to this whole dimension. The findings provide the definition of a validated model to be applicable in the European education systems.

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