Author: Saara Vainio, PhD researcher, Doctoral Programme of School, Education, Society and Culture, University of Helsinki.
Shaping Education for Globalised, Marketised and Individualised Future(s)
The aim of this essay is to analyse the concept of precision education governance (PEG) through the themes and suggested reading of Futureducation lecture series. First, I will briefly discuss about the current changes in education in terms of globalisation, marketization and the behavioural and life sciences and introduce the analytical concept of PEG. After that I will go through lecture themes i) privatisation and the reorganisation of the state responsibilities ii) transnational nature of education and decontextualisation of knowledge iii) digitalisation and digital education governance and iv) the increasing role of behavioural and life sciences in education and analyse how these themes reflect PEG and with which consequences. As a conclusion I will discuss what may have caused the rise of precision education governance and who gets to imagine the future of education.
New conceptual tools to understand changes
Education is often referred to be in crisis. However, there remain no clear consensus about what are the main concerns in education or what needs to be changed and for what. Global economic agencies and international organisations such as OECD, ILO, UNESCO and EU, are mostly worried that education, in its current mode, is unable to answer the needs and interests of the market and future megatrends, such as globalisation and digitalisation (Mertanen, Vainio and Brunila, in press; Hogan and Thompson, 2021; Cone and Brøgger, 2020). For example ‘tradition education’ which is often used from back-to-basics, teacher-centred conventional education, is often represented as being outdated or unable to deliver the needs of future workforce, increasing competition and social changes. Hence, many actors and stakeholders have argued that education needs to be transferred to meet the demands of rapidly changing technologies, globalisation and increasing skill demands by strengthening the collaboration with different stakeholders and edu-business partners (Ideland, 2020, Ideland, Jobér and Thompson, 2020; Heikkinen, 2018). It comes without saying that implicit in these demands are the economic imperatives, and the need to prepare children and young people with the skills and competences needed in future work force to optimise individual potentials for economic future building (Mertanen and Brunila, 2021; Vainio, Mertanen and Brunila, in process).
However, within the crisis discourse, other concerns have been expressed as well. Several critical scholars (i.a. Ball and Junemann, 2012; Ball and Youdell, 2009; Brunila et al., 2019; Cabanas and Illous, 2019; Cone, Lucas, and Brøgger, 2020, Ideland, 2020) are calling in to question for more critical and societal perspectives to understand changes and their consequences in profound way. FuturEducation lecture series provided an illustrative cross-cut of the current and future changes of education, where the usage of digital platforms, artificial intelligence and knowledge from the behavioural and life sciences are getting a foothold in education and similarly forming connections and networks of strengthening global governance and different private providers and EdTech businesses (Ideland, Jobér and Axelsson, 2021, Steiner-Khamsi, 2020; Sellar and Gulson, Youdell, Lindley, Shapiro, Sun and Leng, 2020). From this perspective, ‘the crises’ do not refer on the outdatednes of school or education but rather on changes that are followed by the ‘crises’ of education or implementations that are supposed to solve the problem of education. In other words, what becomes important from the perspective of this lecture series, is to problematize and scrutinize these changes, and aim for more profound understanding for why certain things are represented as ‘good solutions’ to deal with different societal and structural issues as well as diversities of societal life.
In our ongoing research project Futured, we have coined rise a new conceptual tool, precision education governance (PEG) which is helping to grasp the overlapping and ongoing future change in education governance. PEG is an umbrella concept developed in the pilot project Interrupting Future Trajectories of Precision Education Governance (FuturEd). The conceptualization enables scrutinizing and analysing ongoing and future changes in education and demonstrate the increasing tensions and powerful partnership networks between global, national and local actors, scientific research bodies, for-profit industries, and edu-tech businesses searching for ways to influence and shape education more thoroughly than ever. In our upcoming article Educating for the Future? Mapping the Emerging Lines of Precision Education (Mertanen, Vainio and Brunila, in press) we have taken a stance to conceptualise PEG through three distinct ‘lines’ of education governance which are a) the global and transnational nature of governance, b) the marketization, privatisation, digitalisation and datafication of education and c) the increasing role of the behavioural and life sciences in education. When scrutinizing PEG in terms of this lecture series, I see that the PEG provides simultaneously the context for analysing changes in education as well as the theoretical framework enabling us to ask why, how and in which ways certain things occur and are constructed as ‘good practices’ or ‘good intentions’ in education and more widely.
In this essay, I analyse each lecture theme in separate chapter from the perspectives of PEG. In the first chapter I discuss about the privatisation of education based on Malin Ideland’s presentation under the headline the reorganisation of the state responsibilities which demonstrates the marketization, privatization, digitalization and datafication of education (second line). The second chapter is about the increasing transnational nature of education governance and the decontextualisation of knowledge based on Gita Steiner-Khamsi’s presentation Evidence-based policy and surplus of data which represents the increasing global and transnational nature of education governance (first line). In the third chapter digitalization and digital education governance I discuss about the role of bid data and algorithmic thinking in education as a part of digitalisation and privatisation of education governance (second line) based on Sam Sellar’s lecture. Finally, I talk about the increasing role of cognitive science in teacher education based on Deborah Youdell’s lecture as a form of behavioural and life sciences in education (third ‘line’).
Privatisation and reorganisation of the state responsibilities
The popular narrative of schools not been updated or capable of adequately preparing students for either future roles in society or the job market is becoming hegemonic in global and national contexts (e.g. Kuhl, Soo-Siang, Guerriero and van Damme, 2019). Especially in Sweden, this narrative concerns the decreasing results in international large-scale assessments, increasing segregation along the lines of ethnicity and social class as well as poor and inefficient learning environments with a shortage of qualified teachers (e. g. Hultén, 2019). Malin Ideland, Anna Jobér and Thom Axelsson (2020) discuss in theirs article ‘Problem solved!! How edupreneurs enact a school crisis as business possibilities on how the growing apparatus of different non-profit and for-profit actors are offering solutions for the assumed school crisis. Authors point out how the crisis narrative have created a reflexive policy space, and political imaginary where market solutions could contribute to a better school. Privatisation and multilayer public-private-partnerships (or private/public state work how authors call it) in Swedish education field are providing superficial cures, like ‘magic bullets’ to problems that are actually bigger societal and structural issues. In other words, the private sector solutionism is suggested to provide over simplified notion of cost-effective causality, where schools are, for example, raising achievement or raising national standards if individuals, institutions and systems will follow a simple prescribed recipe (also Loughland and Thompson 2016). This causality again, creates private edupreneurs a certain niche, with opportunities for interventions and resetting the epistemological terms for practices and policy.
By utilizing Carol Bacchi’s (2009, 2012) What’s the problem represented to be research method, Ideland, Jobér and Axelsson analysed through two different fields on how edupreneurs are taking part in defining societal issues and similarly offering solutions to complex societal and educational issues. For example, companies may raise concerns about the ‘poor’ digital competences of students. This may raise concerns, not actually about the student but rather teachers who are not prepared to teach in a modern digitalized schools. In this way the ‘problem’ of teacher’s competences is defined in public debate and private experts and edupreneurs are called for help to solve this ‘problem’ (see also Ideland, 2020; Player-Koro, Bergviken and Selwyn, 2018). Also ‘the lead teacher reform’ is an example of a policy reform based on decentralized problem solving. Through the lead teacher reform a number of commercial actors appeared in the market to help teachers to become more research-based in their work and to use research to make teaching more efficient. According to authors, these companies are offering precisely shaped methods for developing skilled teachers and so called ‘lead teachers’ who will, for example, achieve excellent results with all students, support cohesion and understanding; lead learning unwaveringly forward, make the learning process visible, give every student a voice; create a classroom atmosphere for and cherish all students’ rights to a good education. It comes without saying that these premises are not only highly optimistic but also responses to commonly recognized problems. In other words, this means that the private edupreneurs implicitly take part in the problematisation process, foremost through offering a solution to problems represented to be in the public debate (segregation, messy classrooms, poor learning results). In this way, companies redeem their legitimacy in political discourses as rational actors and practical necessities by creating ‘need’ for different services (Ideland, Jobér and Axelsson, 2021).
In bigger picture, the engagement with edupreneurs in public state work is an illustrative manifestation of the greater state development that has taken place in the transition from the so-called old mode of government to the new governance. This means that the old government led-hierarchies have been rearticulated to follow new demands related to market-driven ideas of competitiveness, production of human capital and efficiency, which again, has reshaped the modes and procedures of education policy actions (Jessop, 1998, 2002; Brown, 2015, Ideland, Jobér and Axelsson, 2021). To understand how it contributes to the crisis narratives, the suggested article illustrates how private companies accompany policy making by offering seemingly effective solutions to already existing problems, which also makes the public/private state work seem attractive and the policy reforms are enacted as sort of ‘business ideas’. In this way, the public/private state work has not only blurred the boundaries between public, private and third sectors, but also involved a regulatory mechanism, which enables different, market-based, institutional and charitable coalitions reform education policy functions (Ball and Youdell, 2009; Jessop, 2002; Rhodes, 1996, 1997). This refers that education governance is increasingly differentiated as ’self-organizing and interorganisational networks’ complementing markets and hierarchies as governing structures and exercising control through problematisation and solutionism.
However, it is also important to point out, like Ideland acknowledged in her lecture, that in order to critically understand engage with marketization of education we need to understand more of the personal and societal benefits of market solutions. It is obvious, that what market offers for schools, is addressed up in certain seductive language. The market solutions are designed to be easily digested, simply actioned and provide reassurance like Loughland and Thompson (2016) stated. This obviously can have positive effect, like denial of the pessimism and the focus on finding solutions (solutionism). Hence, the market rationalities do not just penetrate on public policy making or education practices, but it rather involves more profound reorganisation of the state, the welfare system and public policy discourses. In neoliberal order, the private providers are seen as ‘saviours’ of the public, being able to provide better quality and solutions for commonly recognized issues. Hence, one important feature of precision education governance is that the states acts as a powerful instrument of decentralisation (Brown, 2015, 2019) taking place through active policy interventions that equip privatisation and marketization. This means that the old welfare structures are replaced with aims to support production of the societal functions and policy outcomes by actions lead interaction with local government, labour and educational authorities, the voluntary sector, the private sector and non-governmental organizations (Ball, 2013, 2016: Ball and Youdell, 2009). Hence, underlying in the crisis narrative is possibly to encourage many and varied arrangements for coping with social problems, remove state responsibilities of education and to distribute educational services among several actors and sectors. Hence, at the same time, the agreements, rights, obligations and responsibilities between the state and the citizens are renewed (Brunila, 2009; Julkunen, 2005).
Transnational nature of education and decontextualisation of knowledge
As it’s been demonstrated previously, national education systems and institutions are increasingly governed through assemblages formed by global and local actors and their interests and agendas (Lingard, 2013; Niemann and Martens, 2018). In the last decades, intergovernmental organisations, such as OECD, WTO, UNESCO and European Union are becoming influential actors in national policy formation. Although the IGO’s does not have ‘direct’ power over nation states, their influence shows even in nation-state’s policy making (Rautalin, Alasuutari and Vento, 2019; Candido, Granskog and Lai, 2020; Euan and Morris, 2016). The governing throug IGO’s is rather persuasive than controlling. They aim to define norms, standards and rules through so called ‘soft governing’ or ‘soft policy-making that works through discourses; it is about persuasion, guidelines and suggestions for political action, and which skips over the parliamentary decision-making traditionally attached to politics (Cone and Brøgger, 2020; Alexiadou, 2007; Lange and Alexiadou, 2007; Wallace and Bendit, 2009). In this sense, the normative power is legitimated by information, and ideas and norms on how territories and populations are to be governed and which kind of actions and decisions are seen as ‘rational’, and others as ‘unrealistic’ or ‘impossible’ (see Ball and Junemann, 2012).
In this chapter, my focus is on one power node in global education governance, OECD, which is claimed be a great ‘knowledge broker’ or producer in the national policymaking (Niemann and Martins, 2018). However, the fact that OECD have become more active in policy model formation in discursive means, the union still have no direct power to wield over nation-states, but rather the given impression is that OECD have competence to intervene in domestic politics by providing evidence on a basis for policy making (Rautalin, Alasuutari, and Vento, 2019) Gita Steiners-Khamsi’s lecture (and the suggested reading) was illustrating in a sense that it shed light on the OECD’s role in providing seemingly neutral evidence for different political decision making and this way governing member countries ‘from the distance’. Steiner-Khamsi raised an issue of the ‘surplus of evidence’ referring on the selective use of knowledge as evidence when policy actors are justifying their political decision(s). She also acknowledged in her article (Steiner-Khamsi, 2021) that OECD is the founder of policy knowledge that ranks at the top in evidence-based policy making which operates with numbers and draws on international comparisons to enforce a political program of accountability (see also Lingard, 2013; Sellar and Lingard, 2013; Martens and Wolf, 2009). The surplus of evidence as a part of OECD’s governing logic takes place through statistics, scores, ranking, and benchmarks based on international comparisons or on comparisons over to classify, reduce, simplify, and make visible certain kinds of knowledge. In this sense, the ‘evidence’ are generative in the way the construct reality, as they ‘diagnose’ failing and monitor national developments and advice the global solutions of a particular kind for national reforms (Ydesen, 2019).
Steiner-Khamsi refers on Baeks (2020) notion of ‘expertise seeking arrangements’ which describes the dilemma on policy making in the era of surplus of evidence: where and how do policy makers seek advice for policy analysis, evaluation, and formulation? Illustrating with the topology of Eyal (2019, 102) she describes four strategies of structural coupling of science and knowledge. The first one takes a standpoint where science is purified from politics by pursuing “mechanical objectivity” (Eyal, 2019, 115), as reflected in references to scores, rankings, numbers, impact evaluations, and quantifiable comparisons. Second strategy underlines inclusion and that science should be acknowledge as politics, but politics in other means (Latour, 1984). The third strategy decouples science from politics and generate ‘gate-keeping mechanisms designed to maintain an artificial scarcity of expertise’ (Eyal, 2019); which are typically academic associations (academy of sciences) or professional associations that claim exclusive expertise and advise the government. The fourth and final strategy of outsourcing represents another functional differentiation process. It decouples science from politics to the extent that it delegates research and policy formulation to outside groups, think-tanks, or semiprivate entities. (Baeks, 2020.)
The references to OECD studies belongs to the first category, underlying the seemingly objective basis for knowledge formation. In education, we are currently witnessing a phase in education governance, where OECD is given legitimacy to translate concepts such as wellbeing, skills, teaching, education, and citizenship into measurable and calculatable indicators (Williamson and Piattoeva, 2019; Sellar and Lingard, 2013), and show their impact on for example, economic distribution and production. This ‘evidence’ has a great normative effect on national and international policy making in terms what are the main objectives and purposes of education, how the teaching should be planned and conducted to serve the data structures and numeric assessment, and what are the right feelings, desires and hopes attached to education (see also Sellar, 2013). Through this ‘evidence’ OECD has gained influence and placed itself as an autonomous policy advisor and standard setter, as a systems that produce, independent of the state, evidence.
However, this idea of objectivity and evidence should questioned. The OECD is known for cultivating buzzwords such as human capital, knowledge based economy or future skills and competences which are circulating around global and local networks and constructing reality where certain solutions are seen as self-evident and ‘mandatory future investments’ which will eventually contribute on economic growth (Rinne, Kallo and Hokka, 2004; Sellar and Lingard, 2013). Rather that talking about objective truth, the production of reality in OECD political discourses could be announces as decontextualisation of knowledge and evidence. Decontextualisation refers here on mechanism, where the knowledge producer replaces itself to be autonomous and objective, detached from the surrounded societal, economic and political ties (Saari, 2016). Similarly, the tendency of OECD to seduce its audience with measurable predictions of human behaviour (skills and competences) and its connections to numbers (economy), removes these concepts and imperatives from greater societal, political and ideological context. In this sense, rather that talking about neutral interpretation about the connections of behaviour and economy, the question may be more about interpreter of evidence by selecting from the marketplace of ideas those that are in line with the organisations values and principles and also ‘to be sold and rationalised’ in terms broader political program of accountability. In this sense, the transformation from data to evidence rests on a selection process that reflects the frame of reference or broader discursive orientation of the predefines goals. It is thus no surprise that the attempts to future-proof global governance of education, digitalisation and marketization seem to take the front stage (Steiner-Khamsi, 2021; Mertanen, Vainio and Brunila, in press).
Digitalisation and digital education governance
It’s been estimated that EdTech industry is one of the most rapidly growing industries in across the globe with the premises of improved future learning outcomes, inclusion and great profits (Williamson, Eynon and Potter, 2020). Like Malin Ideland outlined in her lecture, entering of private corporations to the ‘the pedagogy markets’, have been particularly aggressive in Sweden. Private companies usually offer efficient solutions to improve teaching and learning by providing hardware, software and professional development for schools (Ideland, Jobér and Axelsson 2021). However, digitalisation may involve much more that just recalibration of traditional classroom arrangements, but also more complex changes in terms of global and local educational governance. Learning platforms are not just neutral platforms for learning new information but they also collect behavioural and personal data from students to be used in governance or in advertising purposes (Saltman, 2020; Sellar and Gulson, 2021; Williamson, 2020, 2021ab). For example O’Neil (2017) and Zuboff (2019) have utilized how Tech companies such as Google, Microsoft, and Facebook, are not only offering precise tools to enhance education and learning, but are also mining their users personal information to further sell to advertisers and by utilising big data and algorithms both steer and predict people’s behaviour.
Similar foundations on data driven governance was given in lecture by Sam Sellar. Drawing from a case example of the work of policy analysis unit “the Centre” within Australian state education department, he explines how cloud platforms are used as a part of the Centre’s business intelligence strategy to improve tactic public decision making regarding education as well as school enhancement. Cloud platforms are designed to capture data from different sources, like census, student achievements, behavioural patterns and where the data is standardized, modelled and produced out as ‘reports’ and different models and visualisations to support political decision in municipalities and individuals schools. In this way, “the Centre” wishes to become an information centric rather that data centric providing seemingly neutral and objective information for governance (Sellar and Gulson, 2021).
By drawing examples from Sam Sellar’s lecture and the suggested reading (Gulson and Sellar, 2019; Sellar and Gulson, 2021), I will illustrate how business intelligence is used to support decision making in different educational dimensions. In Australia, the schooling is constitutionally a state and territory responsibility, which makes it important that the schools are placed in line with infrastructural demands. This is why the future demands for schools is anticipated through Demographic data collected by the Australian census. At the core of BI predictive modelling; which means the data on school location and size, are run through simulations that can be used to anticipate the infrastructure needs. In this way it can be anticipated, which areas will be in high demand of schools in the next decades. Hence, through predictive analysis, different sources of data like census and demographics can be translated as information such as anticipations which are again used in public policy making like where municipalities place their schools.
Second example draws from Sellar’s and Gulson’s fieldwork focused on Business intelligence in explanatory study of assessment data in Australian National Assessment Program – Literacy and Numeracy (NAPLAN). In this pilot project, the data of student test achievement at the early state is examined and sampled to predict later school performance. The pilot project of NAPLAN has premised to predict student performance from 7 years to 12 years, in order to anticipate possible failures so that the teachers could focus more support for those who will possibly be ‘in need’ in future. The premises with algorithmic thinking rests in optimization, which means data analysis could be used as a future looking evidence which could also improve student and future outcomes (Sellar and Gulson, 2021).
These examples are illustrative in a way the show how algorithmic thinking and data analysis are rapidly taking foothold in education governance. This again changes the ways we think about education, knowledge or being a teacher or student. In market speeches the premises given to AI is to help human decision making, to help teachers and educational professionals to enhance learning on class room and support those in need. In this sense, the platforms and algorithmic thinking is presented as autonomous, fair, equal and impartial, neutral and value-free, providing sort of rational evidence in police making or teaching and learning (see also Williamson, 2021ab; Perrotta, et at., 2021). However, it should be acknowledged that before this data becoming ‘information’ or ‘evidence’ it involves complex decisions of standardization and an asset of instrumentalised values and self-evidences or sometimes just lucky coincidences. Like Sellar and Gulson illustrated, the data analytics are sometimes applied to range of areas in multiple domains whit certain level of indeterminacy (e.g. ‘no idea where we’re going to go or what we’re going to find’) and end up finding solution with an inference of trial and error. This indeterminancy is feeding into decision making and policy changes which may be problematic (see also Gulson and Sellar, 2019).
It can be seen that algorithmic thinking also changes the role of a teachers and a student. AI is supposed to help teachers to make better pedagogical decisions which also raises question of the possible declining the professional position of a teacher (see also Carlo, Gulson, Williamson and Witsenberger, 2021; Ideland, 2020). It is importantly to acknowledge that the AI in education do not just operates separate from human action, but the governance is rather synthetic by nature, as it combines human and artificial cognition combining data analytics, algorithmic decision making, artificial intelligence to human rationalities, values and practices. Concerns arise when cognitive load of human thinking is changing when automated algorithms are allowed to guide for unconscious thinking by creating by new values and conditions for thought (Bakker, 2015). In this sense, there remains a danger that students and student performance becomes an instrument of optimization (Parisi, 2017). Which again may have causes in terms of the decision making of education professionals, for example teachers and other leading heads of policy making.
The increasing role of behavioural and life sciences in education
When talking about education, the question often comes to learning. However, there still remains no clear consensus on how to conceptualize learning within the field of educational sciences. Across different sub-fields of education the focus of learning research can be for example i) on the structures, systems and practices that shape and constrain the possibilities for learning and what learning is taken to be (Youdell, 2011; Ball, 2013), ii) in curriculum, pedagogy and assessment of learning process and outcomes (James and Pollard 2012) or iii) in educational psychology, cognition or even neurology of learning process happening in the brain (Cohen Kadosh and Dowker, 2015). In recent decades, nationally and internationally governments and education policy makers have raised concerns about education – that, education is not delivering what it is supposed to deliver in terms of efficiency and cognitive capacities to future work force requirements. In this sense, the educational sciences are becoming increasingly shifted to examine different aspects of learning and learning process. Significant example of these changes can be seen due the work of OECD and the ‘New Science of Learning” which aims to translate learning as neutral, transferrable processing of information that happens in the brain (Kuhl, Lim, Guerrioro, van Damme, 2019).
This shift towards cognition-and neuro aspects on in learning is filled with promises that cognitive, behavioural, psychic, emotional, neurological insights would allow something ‘new’ to educational sciences with the application of basic knowledge of brain functionality. Within these discourses, student emotion, skills and different ‘psychological’ competences such as cognitive abilities from attention, to procession capacities, innovation and learning are becoming even more important when understanding teaching and learning (see Know, Williamson and Bayne, 2020; Huang, King and Lee 2020; Shapiro and Hanslmayr 2014). In her lecture Deborah Youdell gave us an idea about how the cognitive neurosciences have been reframing learning and school education. With her thematic framework she illustrates how learning can be understood and optimised through the application of knowledge from the basic science of cognitions and the brain. With this science of learning cognitive neuroscience concerning for example attention and working memory is combined with neuroscience, which again is inspecting the brain development, structures, functions, and connectivity (Shapiro and Hanslmayr, 2014; Lenz Taguchi, 2018, 242). Within cognitive neuroscience the aspect of brain functionality in expected to provide ‘new explanatory framework’ to examine individual learning process. For example, in neuroscience learning can be understood as a biological processes of the body and the brain which forms neural circuits, which consists and functional connectivities of the synapses. (Koizumi, 2012.)
From the cognitive science perspective learning can be inspected from electrical activity in the brain and beating hearts to metabolic pathways within cells and movements across membrane (Koizumi’s 2012, 320 cited by Lenz Taguchi in review, 10). In this way learning can be inspected recording electrical activity in the across the membrane during learning process, or using mobile mass spectrometry to generate biochemical profiles in learners’ and teachers’ exhaled breath. Tracing the bodily responses is seen to provide insight information about the cognitive processes and mental stages that occur during learning. In this sense, the cognitive neuroscience of learning translates learning into somewhat measurable and observable processes (Huang, King and Lee, 2020) that make measurable changes in individual’s brain.
In Youdells’ lecture she illustrated how the cognitive neuroscience is important part of Early Career Frame (ECF) work in teacher training in the UK. For example cognitive neuroscience, especially concerned with attention and working memory, is believed to have particular potential for helping in understand learning in education context. As demonstrates in a report of Cognitive science in class room (Perry, Jørgensen, Cordingley, Shapiro and Youdell, 2021), some strategies like retrieval practice, interleaving, spaced learning, schemes and managing misconception are believed to attend to working memory and cognitive load. The EFC standards invite teachers to avoid overloading working memory by reducing distractions, breaking complex material into smaller steps as well as taking into account pupils prior knowledge how much new information to introduce (Perry et al. 2021).
It is obvious that the ‘neuro’ approach within education have generated rich insight into the ways in which learning is situated and constituted in a way that traditional disciplines—like humanities and social science—are unable individually to understand. Youdell agreed that it must be useful that teachers have some working knowledge about the learning principles. However, as Youdell and colleagues stated at the report (Perry et al., 2021), there are still serious gaps and limitations in the applied evidence base, uncertainties about the appliability of specific principles across subjects and age ranges and challenges of implementation in practice. For example, disconnects between the basic cognitive science and applied cognitive science put to work in classroom environments demonstrates the possibly limited framework. In systematic review there are still mixed result about the usability of this knowledge and which teachers should be more aware of. Drawing from our suggested reading Youdell and colleagues make important notion that learning in class room is a phenomenon produced through the intra-action of different dimensions like the acquisition of knowledge and skills and the capacity to use these, pedagogic approaches, materials relations, institutional structures systems and practices, engagement and experience in the classroom, modes of recognition and misrecognition; feelings flowing through learning encounters and circulating in classrooms; morphological and functional connectivities of the synapses that form neural circuits, cognitive capacities of attention, memory formation and retrieval; brain wave oscillations, metabolic pathways within cells and biochemical movements across membranes which should all be taken account when discussing about learning (biosocial education) (Youdell et al. 2020; Youdell and Lindley, 2019).
It is obvious that the increasing behavioural and life sciences in education rises from a greater debate of what is the role of education or training in societal perspective. The promises of behavioural and life sciences is to make education to become more calculable, predictable, efficient and individualised than before so that the full economically-driven potential and vitality of students and individuals could be realised. Translating learning into measurable processes (Huang, King and Lee, 2020) that happens in a brain and can be measured through brain functions, enables education to measured and compared through different techniques and best practices (Hart, 2016; Williamson and Piattoeva, 2019; Youdell, Lindley, Shapiro, Sun and Leng, 2020). Hidden in these premises is that education could be translated as a detach commodity or product that could be sold to different teacher, student and school providers (Knox, Williamson and Bayne, 2020). In this body of research, we see that the different lines from behavioural and life sciences to marketization and privatisation all come together and work towards common aims.
Conclusion: who gets to imagine the future of education?
In this essay I have demonstrated how precision education governance operates in practice through the examples of Futured lectures and suggested reading. It is important to notion, that even these three lines of precision education governance might look different in both scope and context, they still share similar rationalities and aims (Mertanen, Vainio and Brunila, in press). In other words, these ‘lines’ demonstrate different multi-layered phenomena, that are closely connected and constantly strengthening each other and working with a common aim. For example, privatisation and digitalisation would not be possible without strengthening transnational and global governance which have enabled education governance to be transferred further from the responsibilities of nation states to different partnership networks and private industries. Similarly, new stakeholders and paradigmatic solutions have strengthened the role of behavioural and life sciences in education, for example in terms of psychologisation (Vainio and Brunila, in process; Vainio, Mertanen, Brunila, in process). So in this sense, examining precision education governance through ‘the lines’ enables us to look at them together as different parts of the same conversation: what is the role and purpose given to education, who or whom is it serving and with which consequences?
Taking into account that education is always in crisis, is the political rhetoric surrounding the crisis discourse strengthened in last decades. Education, in its current ‘traditional’ mode, is represented to be unable to respond the challenges of the future society. Hence, the key argument is that precision education governance redeems its position in global and national policy by providing seemingly efficient ‘solutions’ to presumably existing problems or problems that we might face in an upcoming, yet-to-be-possible future. In other words, the premises of precision education governance is to make education objectively better in terms of efficiency, transferability, productivity and working live equivalency. Within the popular narrative of austerity politics, these objectives are not ranking at the top for national systems could struggle for (Ideland et al., 2020). In this sense, ‘the better future’ becomes possible, only if and when governance of education is decentralised to several sectors and multi-layered public-private-collaborations which are also serving their own interests for example in terms of digitalisation or behavioural and life sciences.
Hence, the key concerns of education are somehow placed not only in a present moment, but also to the future. What remains silent in this conversation is that who gets to imagine the future and the future needs of society. In recent decades, different stakeholders and networks of actors are increasingly taking a foothold in educational future building and similarly constructing utopias and dystopias where education is somewhat expected to react (Mertanen and Brunila, in process; Robertson, 2005, 2021). This may explain why the need for change has become so hegemonic in political debate. Different stakeholders and especially economic unions constantly create this need for future change, to the extent they are capable of providing rational solutions. This is how imaging the future of education is becoming to follow vicious circle: the problems are ‘created’ in interaction with local government, labour and educational authorities, the voluntary sector, the private sector and non-governmental organizations, where all stakeholders are expected to express their concerns. Additionally, ‘problems’ are brought in a political debate and fitted in a frames they are possible to solve ‘together’ in multidimensional and layered collaboration with different organisations, charities and partners. When thinking this way, it might be easier to understand how digitalisation, privatisation, globalisation and behavioural and life sciences are becoming hegemonic discourses with material consequences. Similarly, they have settled certain norms concerning ideal subjectivities as well as hopes and desired for the future. What remains silent in this conversation, again, is that ‘education’ has somewhat loosen its credibility to imagine its own future and drifted into a dead end where it constantly tries to seek justification for its existence.
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