Describing and Understanding the Role of Student Characteristics
Several studies have analysed the impact of student characteristics on success in higher education. The most studied variables are: (1) Cognitive skills, (2) Academic past, (3) Initial level of knowledge related to the domain that is the subject of learning, (4) Conceptions of knowledge and learning and (5) Personality characteristics.
(1) Cognitive skills. In France, (Morlaix and Suchaut 2012) studied the impact of information processing speed, working memory and inductive reasoning on the average score in the ﬁrst year of studies, at the end of the ﬁrst semester and at the end of the academic year. Noting that these variables do not have a direct impact, the authors concluded that their effect was probably felt earlier by contributing to the quality of prior schooling.
(2) Academic past. In the research conducted in the United States, the high school Grade Point Average (GPA) is an important predictor of success at university (Richardson et al. 2012). In the United Kingdom, A-level examinations are also predictors of success at university (Peers and Johnston 1994). In France, getting the baccalauréat and the marks obtained signiﬁcantly predict success in the ﬁrst year of university (Morlaix and Suchaut 2012). The same observation has been made in Switzerland (Atzamba and Petroff 2003).
(3) Initial level of knowledge related to the domain that is the subject of learning had an impact on the quality of learning achieved through both cognitive and motivational mechanisms. Cognitively, deep-learning strategies only proved effective if based on sufﬁciently robust knowledge (Bell and Kozlowski 2002). On a motivational level, (Hidi and Renninger 2006) and (Renninger et al. 2012) hypothesized that the development of structured knowledge in long-term memory, based on a given topic would promote further development of interest in the subject.
(4) Conceptions of knowledge and learning (4.1) Conceptions of learning must be distinguished from approaches to learning. The latter concern student activities in a situation, and as such are considered products of student-environment interactions (Entwistle and McCune 2004; Entwistle 2009). Conceptions of learning, in contrast, refer to different representations of what it means to learn. Marton et al. (1993) proposed a typology of these conceptions ranging from learning as acquiring knowledge to learning as self-transformation. Conceptions of learning influence learning approaches, that is to say, the strategies actually implemented in a situation, but consonance between the two levels is far from complete. Dissonant patterns appear frequently, especially a so-called positive dissonance combining a conception of learning as knowledge acquisition and the use of deep-learning strategies (Cano 2005). This positive dissonance is explained by characteristics of the learning environment that encourage students to develop a deep-learning approach. These research results, however, refer to traditional learning environments. They need to be veriﬁed in digital learning environments.
(4.2) Conceptions of knowledge and knowing. Hofer (2004), Hofer and Pintrich (1997) developed a model that organizes epistemic beliefs in four dimensions, each seen as a continuum between two poles: the certainty of knowledge, ranging from deﬁnitive to evolutionary; the simplicity of knowledge ranging from individual concepts added one to another, to concepts seen to be interrelated; the source of knowledge, ranging from it being transmitted by an external authority, to it being produced by the person him or herself; the justiﬁcation of knowledge, ranging from it being due to an authority, to it resulting from proof via a rigorous procedure. Automatically activated, epistemic beliefs would influence the goals constructed by the learner, the metacognitive processes and the choice of learning strategies (Muis 2007). The learner not only makes judgments about learning (Do I know?), but also makes what could be called epistemic judgments: How do I know? (Hofer 2004). The importance of these judgments can be seen in the trivialization of internet search, where queries using Google are in most cases the ﬁrst step of a literature search (Biddix et al. 2011). The learner is confronted with a multitude of information sources, the reliability of which needs to be assessed. In this regard, (Bråten et al. 2005: 154) note that “in open and global information networks, anyone can publish anything, and the difﬁcult task of checking the relevance and accuracy of information traditionally done by publishers, is now transferred to the students themselves”. Finally, the analysis in terms of structural equation modelling carried out by Cano (2005) in a survey of 1600 Spanish students conﬁrmed the direct and indirect influence (via learning approaches) of epistemic beliefs on school performance.
(5) Personality characteristics. One of the most influential characterisations of personality is the 'Big Five' model (Costa and McCrae 1992), so called because it organises personality in ﬁve traits: extraversion (active, sociable versus silent, shy); pleasantness (nice, cooperating versus nasty); conscientiousness (meticulous, applied versus disordered, distracted); emotional stability or neuroticism (calm, relaxed versus anxious, irritable); openness to experience (openness, curiosity versus conformity, conventional). In a research in the UK with Bachelor students, (Chamorro-Premuzic and Furnham 2008) observed that conscientiousness, and to a lesser extent openness to experience, have a signiﬁcant impact on academic success. The recent meta-analysis of the psychological correlates of academic achievement conducted by Richardson et al. (2012) conﬁrms that conscientiousness is signiﬁcantly associated with academic achievement. In contrast, openness to experience does not seem to exercise signiﬁcant influence. However, to our knowledge these features have not been linked to learning outcomes such as “the disposition to understand for oneself” (Entwistle and McCune 2013). In conclusion, as far as characteristics of students are concerned, it seems necessary to consider a whole range of features related to previous training experience, and the level of knowledge acquired to enter the program. This level can be assessed in various ways on the basis of past academic experience or, more speciﬁcally, via an initial assessment of knowledge about the area to be learnt. In addition, the impact of epistemic beliefs and conceptions of learning on the learning process now seems sufﬁciently documented through research for us to include them. With regard to personality characteristics, the results are more open to debate. What might appear as a personality characteristic influencing learning outcomes, namely conscientiousness, may turn out to be process variables. Being meticulous and focused on the goal could well be the effect of speciﬁc control strategies, called volitional strategies (or action control strategies) rather than the effect of personality characteristics. This is the conclusion reached by the recent meta-analysis of (Richardson et al. 2012). Eventually, two types of student population coexist in university programs: students coming directly from secondary education and adults returning to their studies. The previous learning experiences of the latter and the knowledge they have acquired, as well as their motives to engage in a new teaching program (Vertongen et al. 2009), are probably not without effect on their conceptions of learning and knowledge, as well as on their perceptions of the digital learning environment. These characteristics are likely to influence the learning outcomes. For quality management, a ﬁrst question would be: how does HE and particularly new offers such as MOOCs do take into account students individual characteristics?