Estimated reading time: 20 minutes
Q. Lisa and Irina, thanks for joining me today. Lisa, can you first introduce yourself and tell me how you got here and how you fit into this SySTEM 2020 puzzle.
Lisa: My name is Lisa Marie Seebacher, I’m a social scientist working at the Center for Social Innovation, in Vienna. I’m located in the department of technology and knowledge which is working on STEAM and science learning, but also maker communities and citizen science, and we joined SySTEM 2020 to dive into science learning and the inequalities still existing in this realm.
Irina: My name is Irina Vana and I’m also working at the Center for Social Innovation as a sociologist but I am in the department for work and equal opportunities, which is dealing with different drivers of social inequality. In my department, we have done a lot of research on education especially formal education, so I was very happy to join the SySTEM 2020 team to do further research into learning in the non-formal learning space.
Q. What was ZSI focusing on specifically in SySTEM 2020?
Lisa: Our main task at ZSI was to explore the whole range of science learning experiences of young learners between the age of 8-21. Since science learning might happen potentially everywhere at any time, we came up with a toolbox of different methods to tackle different dimensions of science learning. One of the tools, which I led, was a longitudinal survey which was rolled out two times with the same group of learners in order to get an idea of where young learners learn, what they engage in on a regular basis, how science attitudes form, what parts of science they are interested in, what they think about the formal education system and how might their social background influence their science learning. Alongside this, we’ve also used more experimental tools, where we ran a series of small micro-surveys that are given within a set timeframe allowing us to see how time influences learning, and these micro surveys were led by Irina.
Q. You just explained two surveys there, so you had the one longitudinal survey, and then you did these micro surveys, which you called the experience sampling method (ESM). Can you explain a bit more how they differ essentially?
Irina: Most surveys provide a general vision of attitudes and a situation. Different to this, the ESM, which consist of a series of short questionnaires, measured the attitudes of young learners towards science and their daily activities in relation to a certain moment, so in our case questionnaires were sent out over four consecutive days before, during and after the participation in science learning workshops. From this, we hoped to measure the impact of time, mood, and social environments on STEAM learning.
Lisa: The longitudinal survey on the other hand was rolled out in 18 European countries looking at more general ways of science engagement and attitudes that are not so much time-dependent. We know from other former studies that social demographics might make a difference with regard to science attitudes, science engagement, and science learning forms that are pursued. We wanted to see whether educational capital, gender or age play a role in shaping these attitudes and engagement. These aspects were a large part of the longitudinal survey that the ESM did not delve into that much.
Irina: All these surveys and tools (not just the two surveys we are talking about here, but also the observation mapper, the self-assessment-tools, and the zines), really provided us with a good vision of how young learners experience science learning on a cognitive learning level, on a behavioural level, and on an emotional learning level.
Q. So, in essence, the work here is focusing on tools to assess the science attitudes of young learners. By doing this, we learn how they’re learning ecology – by that I mean, their physical, emotional, social, and cultural context – contributes to this attitude. So before starting this research, what kind of results did you guys expect?
Lisa: Using the learning ecology perspective that you were just mentioning and based on previous projects such as the Aspires project that was carried out in the UK context by Louise Archer and colleagues, and the SYNERGIES project carried out by John Falk and colleagues in the US context we definitely wanted to look into group-based differences as well to see if we would find similar findings in the realm of the wider European cross-national context. With that we specifically focused on the same approach pursued by Louise Archer and colleagues, that approach is a combined perspective of these factors, investigating the combined effect of educational capital and gender as well as age. Growing up in an academic family affects your idea of what science is and how other factors such as age-based differences and gender identities mix in, affecting a learner’s overall connection of science and how it really structures their learning ecology.
Q. Could you define “learning ecology for me”?
Lisa: The learning ecology is the whole learning environment of a person and is something that encompasses all the places that a person goes to in their daily lives that provides an influence/learning opportunity. A personal learning ecology evolves over time, related to, for example, the formal education system, learning happening in a museum and also learning happening more informally at home or at work. All of these realms are actually connected and form the learner’s ecology.
Q. What were some of the other most surprising results found throughout this research?
Irina: We hypothesised we would find fewer differences in social backgrounds or social capital in non-formal education than in formal education because there are less structured curriculums, which might support young learners to connect easier with the topics and activities.
However, what was surprising was that the actual differences seen here were the opposite. When we asked children “how much they like science lessons in school,” the social capital was not as strong of an influence as in the non-formal context.
Lisa: Yes, adding to that, as I said earlier we’ve put the focus on educational capital, gender and or age do play a role in shaping these learning ecologies. When looking at the science engagement we looked at groups based on these dimensions, as well as a combined perspective of age and gender – because gender stereotypes shape over time – and the combined perspective of educational capital and gender – because depending on educational capital gender stereotypes and gender identities might also affect the data differently. Based on these insights from existing studies we’ve taken on this lens and looked at all these different variables to see, does it make a difference in our case too? And with regard to the experience of the formal school system, we did not find any of these to make a difference. So, in terms of science engagement, it really seems that at this level school science seems to provide good access to all learners.
Irina: I think this is quite an interesting finding helping us to focus on how the non-formal and formal education could be better integrated and work together to overcome the barriers for young learners from less privileged backgrounds.
Lisa: However, what was interesting was the fact this was different when looking at general science attitudes and differences in educational capital.
Learners from highly educated families are way more likely to say that they enjoy science than learners from low educational backgrounds.
We also found gender disparities. We see that male learners from highly educated backgrounds are more likely to say so, whereas female learners from lower educated backgrounds are the least likely to say, “I enjoy science learning in general”. This is the interesting finding Irina was pointing at, but on the same hand, we do know from the learning ecologies perspective these realms are very much interconnected. It’s really interesting to see how these group identities interfere with one part of it, but not with the other.
Q. From the ESM’s perspective, the micro surveys, were there any surprising results?
Irina: I think what was most surprising for me is the way in which girls and boys learn about science-related topics. For example, female participants tend to share information on science topics with others that interest them more frequently than with boys. It appears that boys tend to perceive science learning as a more self-directed activity. Yet, those who do share information with others tend to share the information more frequently with friends and teachers. Girls, on the other hand, tend to share the information more frequently with their family members. One way of making sense of these differences could be that girls tend to ask for feedback, whilst boys rather tend to report on what they have learned. I think this difference seen in sharing information with others between girls and boys can help formal and non-formal educators to reflect on how different learners connect with science learning and to design activities accordingly.
Q. There was actually a part of your findings that said that female-identified learners tend to be more fascinated and more excited when thinking about science than male-identified learners. If that’s the case, why does that not translate to more females in STEM fields?
Irina: What we can draw from this is that being excited about a topic relates to the feeling that they learned something new. This is quite connected to the way how they perceive they are involved in science learning. If you have the feeling that you’re already on the topic and that you connect strongly with the topic it might not seem that exciting to you because you are already a little expert. Excitement is also connected to the feeling of learning something new, but it will help to get girls more involved in science. It might help to create new visions of what science learning is and in which different contexts it might happen – for example dancing through the street, or hearing your voice echo down a tunnel. Science is everywhere.
Q. Precisely! You mentioned a lot of topics that young learners were interested in e.g. medicine, genetics, neurology, astronomy, biology, and chemistry, as well as physics and engineering. You said this shows that young learners have a “rather narrow concept of science”, as these science topics correspond to the ones young learners are most interested in at school. How do we begin to widen that narrow view? Is that where the non-formal learning comes in and the science centres and the museums, or making that connection between the non-formal and formal a bit stronger?
Lisa: I think this is an important question and I think that it often starts with the formal system. I know that in the formal system you have a lot of guidelines and targets to meet. Nevertheless, it is important to broaden the idea of what science actually can be and how it can relate to everyone’s lives on a daily basis.
Empirically we do know that scientists are still imagined as brainy and also male. This picture of the male scientist is reproducible by children of six years old (see Hughes 2001, Archer et al. 2013).
However, it is not just about learning about non-male scientists but also seeing female, trans and non-binary scientists in other realms in non-formal science education. I am not saying everything needs to be pink to be more diverse and inclusive. But, we need better collaboration between the non-formal and formal system because our survey suggests that science lessons in school might seem more accessible than we expected. We should use this for further and stronger collaborations providing more accessibility and a broader picture of who actually does science.
Q. Yes, agreed, it’s not just a white male in a coat with crazy hair. It’s very important to change our representation so that younger learners have something to aspire to. Speaking of accessibility, Irina, with the ESM, you obviously used mobile phones to send the survey to. However, not all kids have a mobile phone. How did you work around that?
Irina: Well, I think the challenge was mainly a challenge with the workshop facilitators and not for us. We gave very clear instructions that children need to have their own mobile phones, but of course, this had an impact on who could participate, and we know that the facilitators approached this problem differently. However, we think COVID-19 changed things because quite a lot of children got access to mobile phones due to the lockdown situations and the situation of schooling. I think having a mobile phone or not having a mobile phone is not so much a question of the social background because parents with a higher educational background and with higher educational capital might restrain the children from using mobile phones, maybe even stronger than parents who have a lower educational capital. Yet, it still might be a question of age.
Q. Do you see this method being used in other instances, like in an evaluation part of a science centre?
Irina: I think actually that could be quite interesting, especially if you have multiple workshops, allowing you to get some information on how the participants feel about certain topics, allowing you to receive some input on how you could change your programme next time.
Q. Lisa, what was one striking result from the longitudinal survey?
Lisa: We clearly see:
that the educational capital of the parents is one of the best predictors for the educational path pursued by their children in many European countries until today.
The education system has the possibility to broaden career paths. This possibility needs to be actively sought to offer support to children from lower-educated households also.
Q. Following on with that train of thought of educational capital. In your report, you said that nearly “1/3 of our longitudinal surveyed learners engage at least weekly in art centred activities, such as playing music or singing in a choir, which can foster informal science learning and their interest in it”. How do we know that art-based activities foster this kind of learning?
Lisa: We do know that informal learning can happen potentially everywhere and at any time. For example, when you are learning to play the guitar you hold down the strings and you notice the sound getting higher and lower and so on. This is essentially physics that you are indirectly learning from an art-based activity. This is also true with other forms of activities such as dancing, where you can potentially learn a lot about your muscles, bone structure and body. A lot of activities actually are related to science, and we tested this in our surveys. We could see that those learners who regularly engage in art-based forms of science are more likely to develop a positive science attitude, fueling the recent discourse around STEM versus STEAM learning.
Q. Yay for art-based activities. You also mentioned that age remains a significantly impacting factor when looking at science attitudes. In your sample, you said that “learners who are aged between 15 to 17 years are more likely to develop a highly positive science attitude”. Can we that between 15 and 17 is the most important years that we should be focusing our attention on in schools and at centres?
Lisa: I do think that this very much relates to who actively participated in our research. To clarify, we surveyed young learners who participated in non-formal science learning activities that were organised by our practice partners, so science museums, science galleries, maker spaces. We know from the literature that science attitudes evolve over time. So as an eight-year-old, your science attitude might not be fixed. Louis Archer and colleagues say that from age 14 onwards your science attitude is more stabilized. I think our results confirmed that in a way saying that those learners who participate after age 14, really are into science because they are still participating in this science-related investigation.
Q. I guess they’ve already solidified their interest in science and are going to be more into it than the younger ones who are fresh into it. After having done this research are there any recommendations we can give to non-formal learning organisations?
Lisa: Offering different activities would be helpful, for example, there are a lot of museums pursuing an art-based and STEAM approach more. The ESM also showed that based on personal background and educational background, you might feel differently in group settings. There are learners from highly educated backgrounds who are more likely to feel sociable during workshops. Accommodating for those who don’t feel as comfortable in group settings is vital. It’s important to not lose sight that diverse learners also have diverse requirements and there is no one solution that might fit everyone’s needs.
Q. Is there anything else that you wish you could have looked at?
Lisa: I think something really important to pursue further is around the influence of ethnicity because, science is not only male-dominated, but it’s also quite white or related to racist stereotypes of who can and cannot do science. For example, learners from East Asia are often perceived as being particularly skilled, whereas Black students might be perceived the other way around, both being related to racist and stereotyped ideas lacking empirical evidence. We had to exclude a dimension of ethnicity in our study as it is quite difficult to operationalise in the European context. Ethnicity consists of several partially locally specific dimensions, we would have had to consider. However, even if you operationalise it’s not allowed in every EU country to ask specific questions thereof, e.g. a self-identification with a specific ethnic group in France, because ethnicity is such a sensitive category that is regulated by national statistic laws. In the future, this is really important work that needs to be looked into.
Q. How have these results influenced the outputs coming out of SySTEM 2020?
Lisa: For example, Eva Durall from Aalto University has written a white paper which is using our survey results as an empirical base to form recommendations to decision-makers to advocate for a more inclusive and equity-driven science education programme in the formal education sector and also in the non-formal realm. The white paper focuses on diversity, access and inclusion.
Q. You’ve been working on this project for almost three years. How has it been for you personally, what was challenging and what did you enjoy?
Lisa: For me, it was really great to be able to start working with the survey from the very beginning because it’s not so often the case that you can really design the way your data is collected from the very start. It was also really inspiring to work in this consortium where every one of us is really into making science learning more equitable and more accessible for everyone.
