Gender has a negative impact on SQ, and explains 9% of the SQ variance. The effect is negative because the female gender was coded as +1. On average, female students score lower on SQ than male students—a finding in agreement with E-S theory (Baron-Cohen, Wheelwright, Burtenshaw, & Hobson, 2007). A classical t-test (p < 0.01, t-test for equality of means, two-tailed) revealed that the size of the effect of gender on SQ is d = 0.56, which is consistent with the effect sizes found in literature (0.44, cf. Nettle, 2007)
The positive impact of systemizing on motivation to learn science reflects the intrinsic systematic approach of science to phenomena in the material world (Searle, 2004). It is crucial, however, to note that the disposition of systemizing has broader applications beyond the fields of science and technology, because systemizing can be applied to systems that can be found in many areas of daily life, such as, music, language, collections of objects, etc. (Baron-Cohen et al., 2005). Conversely, a truly scientific approach to nature includes more than systemizing, such as aspects of explanation or finding consensus in the scientific community (cf. Cobern & Loving, 2001). Therefore, it is reasonable to assume that a systemizing cognitive disposition fosters motivation to learn science (as the structural model suggests), rather than vice versa.
In contrast, empathizing had no effect on motivation in the structural model. This does not contradict previous research by Wheelwright et al. (2006) and Billington et al. (2007) that showed that, on average, humanities college students were empathizers. It would be inappropriate to conclude from this that empathizing should have a negative impact on motivation to learn science. For example, students who choose an STEM subject as one of their favorite subjects at the secondary educational level may nevertheless chose not to study STEM at the tertiary level (Holmegaard, Madsen, & Ulriksen, 2012). However, our results indicate that a converse effect, namely, a positive influence of empathizing on motivation, does not exist either.
It seems remarkable that the numerical pattern of causal factors is the same across all four countries, since the style of science teaching is very different in each of these countries. In Slovenian upper secondary school science education, frontal teaching dominates (EURYDICE, 2011). Swiss science education emphasizes hands-on science and experiments (Stern, Metzger, & Zeyer, 2009). Turkish science education leans toward a transmissive teaching style and infrequent use of science laboratories (Özden, 2007). Finally, in Malaysia one-way instruction techniques, rote learning methods, and teaching to test are common (Syed Zin & Lewin, 1993; see also Supporting Information). Nevertheless, we found no significant cross-cultural differences between these countries.
Cross-cultural Invariance of SQ
One of the most salient results of our study is the cross-cultural invariance of SQ and its impact on motivation. This has methodological and conceptual implications.
On a methodological level, our results are the statistically strictest confirmation of cross-cultural invariance so far. To our knowledge, this is the first cross-cultural test of the E-S theory using multiple group comparisons. An earlier study (Wakabayashi et al., 2007) used traditional inferential statistics (see limitations above). From a methodological point of view, metric invariance in multiple group comparisons is a fairly strong assertion, suggesting that the SQ questionnaire items operationalize a construct that is stable in all of the cultures tested. Indeed, a system in the E-S context is defined as an entity that takes inputs which can then be operated on in variable ways to deliver different outputs in a rule-governed manner (Baron-Cohen et al., 2003). Defined in this general way, systems can be found in various contexts (cf. Baron-Cohen, 2009). We interpret the metric invariance of the SQ construct as confirmation of the culturally independent epistemic core of this definition.
On a conceptual level, as previously noted, Baron-Cohen et al. rely on biomedical reasoning to explain the cross-cultural invariance of SQ and its dependence on gender. They summarize a large body of empirical research findings not only in psychology, but also in various bio-medical disciplines, such as neurology, anatomy, and endocrinology (Baron-Cohen et al., 2005).
However, (neuro-)biology cannot explain our central finding, that the impact of SQ on motivation is stable across cultures. We interpret this result in terms of an often neglected aspect of E-S theory. Indeed, researchers often overlook that, in addition to the epistemological dimension (“systemizing” and empathizing”), the theory includes an ontological dimension that differentiates between “physical things” as the objects of systemizing, and “mental states” as the goal of empathizing. Referring to philosophy of mind (cf. Searle, 2004), Baron-Cohen et al. (1999) define “physical things” as phenomena with an objective (“third-person”) ontology, while mental things are intentional phenomena with a subjective (“first-person”) ontology. The differentiation between third- and first-person ontology is universal (cf. Searle, 2004). We argue that it is this ontological differentiation that contributes to the stability of our overall model in a cross-cultural context.
More empirical and theoretical research is needed to better understand the conceptual essence of this new approach. Nevertheless, in the following section, we would like to infer some implications of our structural model for science teaching, with due caution.
Implications for Science Teaching
Firstly, our structural model suggests that emphasizing gender in motivational contexts of science teaching may be misleading, because its impact is only indirect and small. For example, various studies have tried to characterize girls who are motivated to learn science. Mujtaba and Reiss (2012) investigated the motivation of girls who intended to study physics post-16 against the gender trend in their classes. Archer et al. (2012) studied girls who strongly identified with science and science learning. Yet, all these girls may be high systemizers, and thus motivated to learn science independent of their gender. Indeed, Mujtaba and Reiss (2012) found few motivational differences towards science subjects between highly motivated girls and boys.
Likewise, many other factors related to science motivation may appear differently in the context of cognitive style. For example, autonomy, relatedness and belonging (Andersen & Nielsen, 2011), or the use of living animals in science lessons (Wilde, Hussmann, Lorenzen, Meyer, & Randler, 2012) may be good motivators for empathizers (who are interested in mental states), but less suitable for systemizers. Different utilities (Bøe, 2012) and school types (Gill & Bell, 2011) may indeed influence motivation to learn science, but through cognitive style, not gender.
According to our structural model, high systemizers are highly motivated to learn science. They are the non-cultural pendant to the potential scientists identified within a cultural paradigm by Aikenhead and colleagues—students that enjoy a smooth transition into the culture of science, without much help from teachers or school culture (Aikenhead, 2000). They may be those students who choose science for identity reasons, such as interests, self-realization, and fit with personal beliefs (Bøe, 2012). In the Swiss studies, we found that only 5% of our sample were high systemizers (Zeyer, 2012a); that is, high systemizers represent a relatively small proportion of an average upper secondary school student population.
Low systemizers, regardless of their gender, seem to be the important challenge to science teaching, because our model suggests, that, by their very cognitive disposition, they are less motivated to learn about physical things and are weak in systemizing. Low systemizers may be those students who perceive STEM as stable, rigid and fixed, and too narrow a platform for developing and constructing desirable identities, and consequently avoid these subjects (Holmegaard et al., 2012). Our structural model suggests that several strategies identified in the literature may be particularly suitable for improving low systemizers' motivation to learn science.
First, ontologically motivated strategies could be based on the assumption that low systemizers are alienated from physical things because they have had few opportunities to come in contact with them. Lack of opportunity is mostly seen in the context of gender (Alexander et al., 2012), but our findings suggest that it might a problem for empathizing boys as well. Notice that, when providing such opportunities, the fact that low systemizers do not have an intrinsic affinity for physical things must be taken into account. A range of educational strategies identified in the literature may help these students to overcome their reluctance, like special teaching activities, labs, field trips, collaborative projects (Bryan et al., 2011), fostering autonomy, relatedness and belonging (Andersen & Nielsen, 2011), preventing feelings of disgust and rejection (Randler, Hummel, & Wüst-Ackermann, 2012), knowledgeable, inspiring, enthusiastic, and caring teachers (Bryan et al., 2011), and family and friends that encourage them to study science (Mujtaba & Reiss, 2012). It can be assumed that these strategies, all of them targeting positive intentional dispositions towards science learning, are particularly helpful for low systemizers (not just girls), and are less important for high systemizers (see below).
Second, on an epistemological level, our structural model suggests that improving systemizing itself in low systemizers may also help. Low systemizers may be those students (not only girls) who associate science with “cleverness” and masculinity, and find physics a particularly difficult subject (Gill & Bell, 2011). Simple and effective teaching practices (Logan & Skamp, 2012) that focus on rule-guided, systematic thinking may foster systemizing ability. Hands-on science (Bryan et al., 2011) may turn out to be another particularly beneficial approach for empathizers, as this type of science teaching embodies systems in experiments and makes them accessible through activity (Swarat, Ortony, & Revelle, 2012).
Finally, a third approach to improving students' motivation to learn science questions our finding that empathizing cognitive style had no effect on motivation to learn science. Is it that science as a subject does not affect empathizing? Or is it the way science is taught in schools? How must science teaching be structured to meet the needs of empathizing students? From an ontological point of view, the solution seems to be simple: science teaching for empathizers must involve “mental states.” But what does this mean?
One strategy identified in the literature is to involve socio-scientific issues in science teaching, because, as Sadler (2004) and others point out, socio-scientific issues involve economic, social, political, and/or ethical considerations. Thus, socio-scientific issues could introduce first-person perspectives into science education. The same may hold true for context-based approaches. Bennett, Lubben, and Hogarth (2007) found evidence that context-based approaches motivate pupils in science lessons, and improve attitudes toward science in both girls and boys. Obviously, context-based teaching frequently involves understanding “mental states,” which is an area in which empathizers can excel, regardless of whether they are male or female.
In particular, health and environment, two often neglected contexts in science education (Zeyer & Dillon, 2012), offer rich first-person connotations (Zeyer, 2012b) that may help empathizers cross the borders into the culture of science. In science education research, health and medicine are frequently considered girls' contexts (Schreiner & Sjøberg, 2004; Bybee, 2012). It is an intriguing idea that, instead, they might be empathizers' contexts, attractive not only to empathizing girls, but also to (often-neglected) empathizing boys.
From the point of view of the structural model, most of these recommendations for science teaching are aimed at low systemizers, independent of their gender, while it is assumed that high systemizers “help themselves” in science education. Given that systemizers are a minority (5%) in an average science classroom, it is not surprising that, in science education research, their needs usually do not come to the surface. Strategies for “good” science teaching identified by traditional science education research may not be suitable for them.
It may be important to give them more freedom to choose what they learn. This strategy has been shown to generally enhance students' motivation to learn science (Vedder-Weiss & Fortus, 2011; Vedder-Weiss & Fortus, 2012). High systemizers may particularly appreciate it.