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Critically analysing EdTech investors’ logic in business discourse

by Javier Mármol Queraltó

This blog is based on a presentation to the 2021 SRHE Research Conference, as part of a Symposium on Universities and Unicorns: Building Digital Assets in the Higher Education Industry organised by the project’s principal investigator, Janja Komljenovic (Lancaster). The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. The project introduces new ways to think about and examine the digitalising of the higher education sector. It investigates new forms of value creation and suggests that value in the sector increasingly lies in the creation of digital assets.

In the context of the current SARS-COVID-19 pandemic, the ongoing process of digitalisation of education has become a prominent area for social, financial and, increasingly, (critical) educational research. Higher education, as a pivotal social, economic, technological and educational domain, has seen its activities drastically affected, and Universities and the multitude of people involved in them have been forced to adapt to the unfolding crisis. HE researchers agree both on the unpreparedness of countries and institutions faced by the pandemic, and on its potential lasting impact on the educational sector (Goedegebuure and Meek, 2021). In as much as educational technologies (EdTech) have been brought to the fore due to their pivotal role in the enablement and continuation of educational practices across the globe, EdTech companies and investors have also become primary financial beneficiaries of these necessary processes of digitalisation. The extensive use and adoption of EdTech to bridge the gap between HE professionals and students due to the application of strict social distancing measures has been welcomed by investors as an opportunity for EdTech to establish themselves as key players within an educational landscape under a process of assetisation (Komljenovic, 2020, 2021). Investors and EdTech are scaffolding new digital markets in HE, reshaping the conceptualisation of universities, HE and the sector itself more generally (Williamson, 2021; Komljenovic and Robertson, 2016). In this brief entry, I focus on EdTech investors’ discourses, owing to the potential of such discourses to shape the future of educational practices broadly speaking.

Within the ‘Universities and Unicorns’ ESRC-funded project, this exploratory research (see full report) aimed at unveiling the ideological uses of linguistic, visual and multimodal devices (eg texts and charts) deployed by EdTech investors in a variety of texts that have the potential, due to their circulation and goals, to shape public understandings of the role of Educational Technologies in the unfolding crisis. The research was conducted deploying a framework anchored in Linguistics, specifically cognitive-based approaches to Critical Discourse Studies (CL-CDS; eg Mármol Queraltó, 2021b). A central assumption in this approach is that language encodes construal: the same event/situation can be alternatively linguistically formulated, and these can have diverse cognitive effects in readers (Hart, 2011). From a CL-CDS perspective, then, texts can potentially shape the way that the public think (and subsequently act) about social topics (cf Watters, 2015).

In order to extract the ideologies underlying discourse practices carried out by HE investors, we examined qualitatively a variety of texts disseminated in the public and semi-private domains. We investigated, for example, HolonIQ’s explanatory charts, interviews with professionals and blog entries (eg Charles MacIntyre, Alex Latsis, Jan Lynn-Matern), and global financial reports by IBIS Capital, BrightEye Ventures, and EdTechX, among several others. Our main goal was to better understand how EdTech investors operationalised discourse to shape the imageries of the future in the relationship between HE institutions, EdTech and governance. In line with CDS approaches, we examined the representations of social actors in context using van Leeuwen’s (2008) framework, and more in line with CL-CDS, we also operationalised the analysis of metaphorical expressions indexing Conceptual Metaphors, and Force dynamics. Force-dynamics is an essential tool deployed to examine how the tensions between actors and processes within business discourse are constructed (see Oakley, 2005).

Our study yielded important findings for the critical examination of discourse processes within the EdTech-HE-governance triangle of influences. In terms of social actor representation (whose examination also included metaphor), the main findings are:

  • EdTech investors and companies are rendered as opaque, abstract collectives, and are positively represented as ‘enablers’ and ‘disruptors’ of educational processes.
  • Governments are rendered as generic, collective entities, and depicted as necessary funders of process of digital transformation.
  • Universities or HE institutions are mainly negatively represented as potential ‘blockers’ of processes of digital transformation, and they are depicted as failing their students due to their lack of scalability and flexibility.
  • Individuals within HE institutions are identified as numbers and increasing percentages within unified collectives, students routinely cast as beneficiaries in ‘consumer’ and ‘user’ roles, while educators are activated as ‘content providers’.
  • Metaphorically, the EdTech sector is conceptualised as a ‘ship’ on a ‘journey’ towards profit, where HE institutions can be ‘obstacles along a path’ and the global pandemic and other push factors are conceptualised as ‘tailwinds’.
  • The EdTech market is conceptualised as a ‘living organism’ that grows and evolves independent of the actors involved in it. The visual representations observed reinforce these patterns and emphasise the growth of the EdTech market in very positive terms.

The formulation of ‘push’ and ‘pull’ factors is also essential to understand the discursively constructed ‘internal tensions’ within the sector. In order to examine these factors, we operationalised Force-dynamics analysis and metaphor, which allowed us to arrive to the following findings:

  • Push factors identified by investors driving the EdTech sector include the SARS-COVID19 global pandemic, the digital acceleration being experienced in the sector prior to the pandemic, the increasing number of students requiring access to HE, and investors’ actions aimed at disrupting the EdTech market.
  • Pull factors encouraging investment in the sector are conceptualised in the shape of financial predictions. The visions put forward by EdTech investors become instrumental in the achievement of those predictions.
  • The representation of the global pandemic is ambivalent and it is rendered both as a negative factor affecting societies and as a positive factor for the EdTech sector. The primary focus is on the positive outcomes of the disruption brought about by the pandemic.
  • Educational platforms are foregrounded in their enabling role and replace HE institutions as site for educational practice, de-localising educational practices from physical universities.
  • Students and educators are found to be increasingly reframed as ‘users’ and ‘content providers’, respectively. This discursive shift is potentially indicative of the new processes of assetisation of HE.

On the whole, framing business within the ‘journey’ metaphor entails that any entities or processes affecting business are potentially conceptualised as ‘obstacles along the path’, and therefore attributed negative connotations. In our case, those entities (eg governments and HE institutions) or processes (eg lack of funding) that metaphorically ‘stand in the way of business’ are automatically framed in a negative light, potentially affording a negative reception by the audience and therefore legitimising actions designed to remove those ‘obstacles’ (eg ‘disruptions’). EdTech companies and investors are represented very positively as ‘enablers’ of educational practices disrupted by the SARS-COVID19 pandemic, but also as ‘push factors’ in processes of digital acceleration within the ‘speed of action is speed of motion’ metaphor. In the premised, ever-growing EdTech sector, those actors and processes that ‘slow down’ access to profits (or processes providing access to profit) are similarly negatively represented. The conceptualisation of the SARS-COVID-19 global pandemic in this context reflects ‘calculated ambivalence’. This ambivalence was expected, as portraying the pandemic solely as a relatively positive factor for the HE sector would be in extreme detriment to EdTech investors’ activities. Our findings reflect that, while the global pandemic is initially represented as a very negative factor greatly disrupting societies and businesses, those negative impacts tend to be presented in rather vague ways and in most occasions the result of the disruption brought about by the pandemic is reduced to changes in the modality of education experienced by learners (from in-person to online education). We have found no significant mention of social or personal impacts of the pandemic (eg deaths and scenarios affecting underrepresented social groups), where the focus has been mainly on the market and the activities within it. Conversely, while the initial framing of the pandemic is inherently negative, we have seen in several examples above that the pandemic is subtly instrumentalised as a ‘push factor’, which serves to accelerate digital transformation and is hence a positive factor for the EdTech sector. In a global context of restrictions, containment measures and vaccine rollouts, it is especially ideologically relevant to find the pandemic instrumentalised as a ‘catalyst’, or as an important player in a ‘experiment of global proportions’. Framing the pandemic in such ways detaches the audience from its negative connotations, and serves to depict EdTech companies and investors as involved in high-level, complex processes that abstract the millions of diverse victims to the pandemic. Ultimately, in the ‘journey’ towards profit, the SARS-COVID-19 is a desired push factor, also realised as a ‘tailwind’, which facilitates the desired digital acceleration.

On the whole, our research demonstrated that social actor representation and the distinction between push/pull factors are crucial sites for the analysis of EdTech discourse. EdTech’s primary focus is on the positive outcomes of the disruption brought about by the pandemic. In this context, educational platforms are foregrounded in their enabling role and replace HE institutions as site for educational practice, de-localising educational practices from physical universities. Subsequently, students and educators are found to be increasingly reframed as ‘users’ and ‘content providers’ respectively. We argue that this subtle discursive shift is potentially indicative of the new processes of assetization of HE and reflects more broadly a neoliberal logic.

Javier Mármol Queraltó is a PhD candidate in Linguistics in Lancaster University. His current research deals with the multimodal representations of discourses of migration in the British and Spanish online press. He advocates a Cognitive Linguistic Approach to Critical Discourse Studies (CL-CDS), and is working on a methodology that can shed light on how public perceptions of social issues might be influenced by both the multimodal constraints of online newspaper discourse and our shared cognitive capacities. He is also interested in the multimodal and cognitive dimensions of discourses of Brexit outside the UK, news discourses of social unrest, and the marketisation/assetisation processes of HE.


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Understanding the value of EdTech in higher education

by Morten Hansen

This blog is a re-post of an article first published on universityworldnews.com. It is based on a presentation to the 2021 SRHE Research Conference, as part of a Symposium on Universities and Unicorns: Building Digital Assets in the Higher Education Industry organised by the project’s principal investigator, Janja Komljenovic (Lancaster). The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. The project introduces new ways to think about and examine the digitalising of the higher education sector. It investigates new forms of value creation and suggests that value in the sector increasingly lies in the creation of digital assets.

EdTech companies are, on average, priced modestly, although some have earned strong valuations. We know that valuation practices normally reflect investors’ belief in a company’s ability to make money in the future. We are, however, still learning about how EdTech generates value for users, and how to take account of such value in the grand scheme of things.


Valuation and deployment of user-generated data

EdTech companies are not competing with the likes of Google and Facebook for advertisement revenue. That is why phrases such as ‘you are the product’ and ‘data is the new oil’ yield little insight when applied to EdTech. For EdTech companies, strong valuations hinge on the idea that technology can bring use value to learners, teachers and organisations – and that they will eventually be willing to pay for such benefits, ideally in the form of a subscription. EdTech companies try to deliver use value in multiple ways, such as deploying user-generated data to improve their services. User-generated data are the digital traces we leave when engaging with a platform: keyboard strokes and mouse movements, clicks and inactivity.


The value of user-generated data in higher education

The gold standard for unlocking the ‘value’ of user-generated data is to bring about an activity that could otherwise not have arisen. Change is brought about through data feedback loops. Loops consist of five stages: data generation, capture, anonymisation, computation and intervention. Loops can be long and short.


For example, imagine that a group of students is assigned three readings for class. Texts are accessed and read on an online platform. Engagement data indicate that all students spent time reading text 1 and text 2, but nobody read text 3. As a result of this insight, come next semester, text 3 is replaced by a more ‘engaging’ text. That is a long feedback loop.


Now, imagine that one student is reading one text. The platform’s machine learning programme generates a rudimentary quiz to test comprehension. Based on the students’ answers, further readings are suggested or the student is encouraged to re-read specific sections of the text. That is a short feedback loop.


In reality, most feedback loops do not bring about activity that could not have happened otherwise. It is not like a professor could not learn, through conversation, which texts are better liked by students, what points are comprehended, and so on. What is true, though, is that the basis and quality of such judgments shifts. Most importantly, so does the cost structure that underpins judgment.


The more automated feedback loops are, the greater the economy of scale. ‘Automation’ refers to the decoupling of additional feedback loops from additional labour inputs. ‘Economies of scale’ means that the average cost of delivering feedback loops decreases as the company grows.


Proponents of machine learning and other artificial intelligence approaches argue that the use value of feedback loops improves with scale: the more users engage in the back-and-forth between generating data, receiving intervention and generating new data, the more precise the underlying learning algorithms become in predicting what interventions will ‘improve learning’.


The platform learns and grows with us

EdTech platforms proliferate because they are seen to deliver better value for money than the human-centred alternative. Cloud-based platforms are accessed through subscriptions without transfer of ownership. The economic relationship is underwritten by law and continued payment is legitimated through the feedback loops between humans and machines: the platform learns and grows with us, as we feed it.


Machine learning techniques certainly have the potential to improve the efficiency with which we organise certain learning activities, such as particular types of student assessment and monitoring. However, we do not know which values to mobilise when judging intervention efficacy: ‘value’ and ‘values’ are different things.


In everyday talk, we speak about ‘value’ when we want to justify or critique a state of affairs that has a price: is the price right, too low, or too high? We may disagree on the price, but we do agree that something is for sale. At other times we reject the idea that a thing should be for sale, like a family heirloom, love or education. If people tell us otherwise, we question their values. This is because values are about relationships and politics.


When we ask about the values of EdTech in higher education, we are really asking: what type of relations do we think are virtuous and appropriate for the institution? What relationships are we forging and replacing between machines and people, and between people and people?


When it comes to the application of personal technology we have valued convenience, personalisation and seamlessness by forging very intimate but easily forgettable machine-human relations. This could happen in the EdTech space as well. Speech-to-text recognition, natural language processing and machine vision are examples of how bonds can be built between humans and computers, aiding feedback loops by making worlds of learning computable.


Deciding on which learning relations to make computable, I argue, should be driven by values. Instead of seeing EdTech as a silver bullet that simply drives learning outcomes, it is more useful to think of it as technology that mediates learning relations and processes: what relationships do we value as important for students and when is technology helpful and unhelpful in establishing those? In this way, values can help us guide the way we account for the value of edtech.

Morten Hansen is a research associate on the Universities and Unicorns project at Lancaster University, and a PhD student at the Faculty of Education, University of Cambridge, United Kingdom. Hansen specialises in education markets and has previously worked as a researcher at the Saïd Business School in Oxford.


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Beware efficiencies! Assetisation as the future defraying of costs savings in the present

by Kean Birch

This blog is based on a presentation to the 2021 SRHE Research Conference, as part of a Symposium on Universities and Unicorns: Building Digital Assets in the Higher Education Industry organised by the project’s principal investigator, Janja Komljenovic (Lancaster). The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. The project introduces new ways to think about and examine the digitalising of the higher education sector. It investigates new forms of value creation and suggests that value in the sector increasingly lies in the creation of digital assets.

What makes learning more efficient? And what makes teaching more effective? According to EdTech providers and their champions, it is the digital transformation of higher education. The consulting company Gartner – which releases regular EdTech industry reports – defines this transformation as a shift from a ‘collectively-defined’ quality model in which universities provide their services – theoretically – to anyone, to a model in which quality is personally defined and delivered at scale through MOOCs or other means. In fact, Gartner emphasize the importance of EdTech providing scalable technologies for ensuring ‘cost effective education for the benefit of society’. And this seems to be the concern of many EdTech firms themselves; they aim to provide technologies that make life and work more efficient and effective for higher education institutions, managers, faculty, students, and staff.

But what does this actually mean?

I am part of a project, led by Dr Janja Komljenovic, looking at how value is increasingly being created in the higher education sector through the transformation of ‘things’ into digital and other assets – it could be students’ data, it could be research, it could be lectures, and so on. Part of our concern about these changes is the way they can end up reconfiguring societal, public, or commonly held resources as private assets from which companies can exact an economic rent. An important reason for examining this assetisation process is to analyse exactly how things are turned into private assets as a way to open them up to public scrutiny, and political intervention, should we so desire. While assets are constituted by legal forms, like property rights, and technical changes, like digital rights management, they are also the result of broader narratives about how we should or should not understand the world. Epistemic justifications matter. The World Economic Forum highlights what I mean here. They support the deployment of education technology as a way to “create better systems and data flows”. And this means more efficient and effective learning and teaching. But, what does efficiency and effectiveness mean in the case of higher education?

As we have interviewed EdTech providers in our project, we have noticed how they emphasize ‘efficiency’ as one of the key contributions of their technology, where this seems to be equated with producing an outcome at lower cost, whereas this is understood – in common sense terms – as doing something ‘better’ than before. It is important to see how the concept of efficiency is enrolled in the transformation of higher education into a range of assets. Assetisation in higher education depends on the development and promotion of a set of analytics that can identify efficiencies, understood as cost savings that someone or some institution can benefit from. Key to this assetisation process is the characterisation of efficiency as a common-sense goal for universities, managers, faculty, students, staff, and governments; in fact, efficiency can appear to be the very thing that education technologies are turning into an asset. For example, making it cheaper for students to study by enabling them to rent their textbooks, rather than have to buy them. Or making it cheaper for universities to pay subscription only for those electronic texts – or even parts of those texts – that are actually read and used by their staff and students. But this raises an important question: how do EdTech companies make money, if they are simply reducing costs all around?

EdTech companies look to the future for their success. Assets are temporal entities, entailing the creation of a stream of future revenues that can be capitalised in the present, thereby enabling investors to put a value to them that does not depend on being profitable now, or even generate significant revenues now. Efficiencies in the present often end up as defrayed costs in the future as those cost savings today compound into increased revenues for someone (eg EdTech) in the future. The future revenue expectations of EdTech companies come from the illusion of efficiency as cost savings at this point in time; for example, students can save on textbooks now but will be induced to subscribe to lifelong learning resources, or their personal data might be exploited in the future in multiple ways, or their reading habits will be used to sell something to universities, or any manner of revenue generating schemes. Someone is paying in the future.

EdTech companies have to make money somehow, and how they make money is the interesting question. Ideas about the current and future state of higher education and EdTech matter as they provide imaginaries of what is possible and desirable, which we discuss in this report. Claims to efficiency are part of how they make money; they are part of the way that EdTech companies construct new asset classes out of universities and their students, faculty, and staff. Interrogating how these supposed efficiencies are monetised is critical for getting a grip on the implications of EdTech for higher education in the longer term. It is essential we analyse this dynamic now to allow for timely public scrutiny, democratic debate and social intervention.

Kean Birch is Associate Professor at York University, Canada. He is particularly interested in understanding technoscientific capitalism and draws on a range of perspectives from science & technology studies, economic geography, and economic sociology to study it. More specifically, his research focuses on the restructuring and transformation of the economy & financial knowledges, technoscience & technoscientific innovation, and the relationship between markets & natural environments. Currently, he is researching how different things (e.g. knowledge, personality, loyalty, etc.) are turned into ‘assets’ & how economic rents are then captured from those assets – basically, in processes of assetisation and rentiership.


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Mapping financial investment flows in digital higher education: a focus on data-rich operations

by Janja Komljenovic

This blog is based on a presentation to the 2021 SRHE Research Conference, as part of a Symposium on Universities and Unicorns: Building Digital Assets in the Higher Education Industry organised by the project’s principal investigator, Janja Komljenovic (Lancaster). The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. The project introduces new ways to think about and examine the digitalising of the higher education sector. It investigates new forms of value creation and suggests that value in the sector increasingly lies in the creation of digital assets.

Universities worldwide are increasingly interested in digital technologies and how they can support higher education. A recent study by the European University Association found that most European universities are already using or planning to use data-rich products and services, such as artificial intelligence, machine learning, learning analytics, big data, and the internet of things (see Figure 18 on page 36). Indeed, it is precisely these data-rich operations that are central to the idea of the disruptive potential of education technology (edtech), as argued by my colleague, Javier Mármol Queraltó, in the recent UU project report. The discourse of investors and edtech companies promises thoroughly improved higher education based on personalisation, automation and efficiency. But how deliverable are these promises? Who innovates in the space of data-rich operations, for which services and for which users? Who profits? These are some of the questions we address in the Universities and Unicorns project, which aims to understand forms of value and ways of creating it in digital higher education. In this blog post, I will address three possible trends that can be identified from the interim findings of our quantitative analysis. But before proceeding to discuss these trends, I will contextualise our analysis.

We used Crunchbase to build three databases covering 2,012 edtech companies, 1,120 investors in edtech, and 1,962 edtech investment deals. We identified those relevant to the higher education sector, and our data reflects the state of the sector as of July 2021. Based on this analysis, we identified four key service models in the higher education edtech industry. First, the business to business (B2B) model includes digital platforms serving universities and companies, such as virtual learning environments. Second, the business to customer (B2C) model includes platforms targeting individuals directly. Third, the business to business to customer (B2B2C) model serves institutions that use or further develop the platform to reach individuals, such as Massive Open Online Courses (MOOC) or Online Programme Management platforms (OPM). Finally, the business to the customer to customer (B2C2C) model includes platforms that connect individuals, such as skills and knowledge sharing platforms. B2B2C and B2C2C platforms, in particular, act as the kind of infrastructural intermediaries that are so popular in other sectors of our social and economic lives.

Our analysis found that half of all investment went into B2B platforms, followed by investment into B2C, while B2C2C and B2B2C together received just under a quarter of all investment. However, platforms with the fastest pace of increasing investment are those targeting individuals directly or through intermediation, ie B2C and B2C2C models. This might indicate emerging parallel or alternative higher education products and services that compete with traditional university provision, especially in the context of lifelong learning.

Digital platforms that say they incorporate data-rich operations in their products and services are not the priority area for investors. While we noticed an increasing investment in data-rich platforms, it was still only less than a quarter of all investment going into innovating such products. Nevertheless, we identified three possible trends that are especially worthy of our attention: (1) data-rich operations are being innovated largely in B2B platforms; (2) there is notable unevenness in terms of the location of edtech companies and investments in those platforms who innovate in data-rich operations; and (3) there might be potential for monopolies in data-rich innovation. Let’s delve into each of these possible trends.

Almost all investment in the companies developing data-rich operations in their platforms went to the B2B service model. Looking only at higher education institutions as the target customer, already half of the investment supports data-rich innovation. Most of that went into platforms that act as the institutional digital backbone, indicating that the intention might be to support all institutional functions beyond teaching with data-rich operations, such as artificial intelligence, machine learning and various kinds of analytics beyond learning analytics. There seems to be a trend towards data-rich digital ecosystems at universities that harvest all user and other data in the near future.

There is high unevenness in where the investment in data-rich platforms is allocated. Regarding the number of companies, 239 in our database declare that they offer data-rich operations on their platforms. Almost half of those (101) are based in the USA, 21 in the UK and 19 in India. Companies based in Africa are entirely missing from the list. In terms of investment amounts, 88% of all investment in companies offering data-rich services in their platforms went into companies based in the USA, 3% each to those based in Norway and the UK, and 6% to the rest of the world. The discrepancy between the number of companies and investment size indicates that investment amounts are higher in the USA than elsewhere in the world.

Finally, if we compare different indicators of investment in companies that innovate data-rich solutions for higher education institutions, we notice interesting dynamics. Looking at the money raised, half of B2B investment went into those companies with a platform that included data-rich operations. But this is only 30% of deals and 25% of companies. This indicates that the concentration of investment in data-rich operation platforms for higher education institutions goes into a smaller number of companies who get higher investments. We wonder if this signals potential for monopolies in the future. Moreover, if we compare granted patents, we notice that a higher percentage of companies offering data-rich solution platforms own patents (30%) versus those offering other kinds of service or product platforms (10%). Digital platforms are typically still protected by a licence, but that differs from a more restrictive patent protection. We wonder if such discrepancy in patent share might indicate black-boxing of data-rich operations in higher education?

Our research on digitalising higher education is showing the complex impact of digital technology and datafication on the sector. This impact includes potential positive and supportive measures, but also many potentially worrying trends. However, further research is needed into these trends and the role of different actors, particularly financial investors and edtech companies. Please follow our project in which we will share the findings from this further work as it unfolds.

Janja Komljenovic is a Senior Lecturer and co-Director of the Higher Education Research and Evaluation at Lancaster University in the UK. She is also a Research Management Committee member of the Global Centre for Higher Education with headquarters at the University of Oxford. Janja’s research focuses on the political economy of knowledge production and higher education markets. She is especially interested in the relationship between the digital economy and the higher education sector; and in digitalisation, datafication and platformisation of knowledge production and dissemination. Janja is published internationally on higher education policy, markets and education technology.


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The Digital Tutor: Digital Tools, Relationships and Pastoral Support in Higher Education

by Jodie Pinnell and Sukhbinder Hamilton

If navigating higher education in recent times has taught us anything, it is that digital technology for teaching and learning is no longer an ‘option’ but imperative for an accessible and inclusive learning environment. With the sudden response to Covid-19 leading to remote online approaches overnight, some professionals in higher education have been thrust into a new digital world, and in survival mode, this has naturally prioritised its potential for pedagogy. Unsurprisingly, research has investigated digital technology and pedagogy thoroughly (Williams, 2012), but outside of the remit of formal counselling (Situmorang, 2020) and distance learning (Hilliam and Williams, 2019), the potential for digital tools for pastoral support has yet to be thoroughly explored. This gap in research prompted us to see how digital tools can benefit personal tutors, and more importantly, how these tools can aid relationships, in a climate where students and academic staff find themselves more disconnected than ever before.

Working in the capacity as senior lecturers, predominantly for undergraduate Childhood Studies programmes, the ‘digital awakening’ brought about by Covid-19 has been a welcome development in our practice. For us, it has paved the way for new approaches, new thinking and ultimately innovations in all areas to support students. Even before the unexpected impacts of Covid-19, we had identified a gap in our personal tutor practice at level 4, a crucial time for students to feel supported as they settle into the first year of their undergraduate degrees. For context, within a study skills module, students are allocated a designated academic ‘personal tutor’ to address academic and personal matters. Whilst this module design has historically allowed for a holistic approach to study skills and pastoral support, it has relied on students being confident enough to approach their personal tutors to articulate needs, something that many were often reluctant to do independently.

The nature of the personal tutor and tutee relationship within higher education is one conducted in a climate which is growing ever more ‘consumerist’ in nature; with inflated expectations for ‘value for money,’ and rhetoric defining students as customers (Modell, 2005). With increasing student numbers (Yale, 2019), it is notable that more and more students are demonstrating wellbeing issues (Universities UK, 2020). The personal tutor is the first point of contact for students to discuss concerns, and with a focus on emotional wellbeing through individualised support, the personal tutor role can be increasingly compared to that of a counsellor (Jorda, 2013). A supportive relationship with a personal tutor in the first year of a degree can prepare students for more challenging times (Brinkworth et al, 2009), and in managing transitions, provides a familiar face and a door to knock on. Giving ownership to the student to share information with their tutor is needed, especially where personal or sensitive issues need to be discussed, and the student signposted to necessary services is required.

Despite this, it has been found that students can struggle to understand the role of their personal tutor (Ghenghesh, 2018, p 571), and with diverse student needs, tutors are pressured to help at all costs, with support not appropriately suited to the confinement of ‘office hours’ (Jorda, 2013, p 2595). Other challenges span a general lack of effective tutor training or the ability to meet increasingly complex student needs (Lochtie et al, 2018). With growing workloads, academics already have a plethora of ‘hats’ to wear (Knight, 2002), with competing demands in other areas, causing a conflict for a role that cannot necessarily be time bound.

Within this consumerist culture, and with a focus on the personal tutor role (and its challenges), we decided to do something different. A Google form asking pastoral questions was forwarded to first year students at the start of the academic year, giving them the opportunity to provide a written background about themselves. Without knowing this would prompt a research project and prove to be valuable, the form aimed to ‘break the ice’ between tutor and student, to remedy reports that some students struggled to open up. Without an opportunity for students to discuss their needs, the correct support is difficult to provide. The form’s questions included; How are you currently feeling about enrolling at the university? What are your hopes and fears regarding university life, and the course? What do you expect from the tutors? And importantly (and most effectively) the request to ‘Finish this sentence… I wish my tutor knew…’ (Schwartz, 2016). All answers were collated in a spreadsheet, and tutors were able to find their tutees’ answers through a search function. The aim of the forms was to give personal tutors an insight into the student’s world without requiring them to initiate conversations in a ‘cold’ meeting with a stranger, ‘fast-tracking’ a relationship between personal tutors and their tutees. The form was completely optional and formed the basis of the first tutorial meeting between tutors and students, giving some background, but ultimately allowing students to outline issues that they may struggle to articulate in the first instance.

Following the success of this approach, a second form was issued at the end of the year, with questions about the effectiveness of using the initial form. Both ethical clearance and student consent were sought to publish the findings. All responses from the students who agreed to participate were collated in one single document, and with rich findings two papers emerged, one focusing on the role of the tutor, and the other on the impact of Covid-19, but with threads of student wellbeing and a sense of belonging running through both.

It’s safe to say that the findings have made a real impact on our practice. Firstly, the value of the forms for relationship development were clear, with snapshots illustrating that it allowed students to reflect on how they are feeling and to raise any concerns they had. Linked to wellbeing, the approach meant that students could discuss mental health issues and their home life situations, without needing to ‘physically disclose something to a stranger.’ Linked to expectations surrounding the personal tutor role, it was clear that students saw their tutors as the first person they felt ‘comfortable’ with, and they expected them to learn about their names and backgrounds. Qualities of a tutor were clearly identified as ‘respect,’ ‘empathy’ and ‘trustworthiness,’ and at level 4, this was largely characterised by the transitions associated with first year study. Anxiety, relief, wellbeing and the impact of Covid-19 were threaded through these findings, leading back to the role of the tutor primarily for support.

So, what’s next? For practice, the continued use of the digital forms will remain an integral part of our pastoral strategy but rolled out across other year groups also. The value of the personal tutor role needs to be reiterated across the team and plans are afoot to provide in-house training. This is not just a useful step to take within our establishment but should be the case for higher education in general as it is imperative for successfully supporting students as a first point of contact. Further research is needed in the area of digital tools for pastoral care and their potential for fast-tracking relationship development and ‘breaking the ice.’ Working towards the goal of creating an inclusive learning environment starts with relationships, and with the rise in remote working, we can rely on digital tools to help, harnessing their perceived unlimited potential to enhance the student experience.

Jodie Pinnell is a Senior Lecturer, Course Leader and Senior Tutor in the School of Education and Sociology at the University of Portsmouth. She is a Senior Fellow of the Higher Education Academy UK. Follow Jodie on Twitter @jodieEdu

Dr Sukhbinder Hamilton is a Senior Lecturer in the School of Education and Sociology at the University of Portsmouth. She is a Co-Convenor for ‘The Women’s Workshop Sociological Collective,’ and a Fellow of the Higher Education Academy UK. Follow Sukh on Twitter @sukhhamilton1

References

Brinkworth, R, McCann, B, Matthews, C and Nordström, K (2009) ‘First-Year Expectations and Experiences: Student and Teacher Perspectives’, Higher Education 58 (2) 157–173. https://DOI:10.1007/s10734-008-9188-3  

Ghenghesh, P (2018) ‘Personal Tutoring From the Perspectives of Tutors and Tutees’, Journal of Further and Higher Education, 42 (4), 570-584. DOI: https://10.1080/0309877X.2017.1301409

Hilliam, R and Williams, G (2019) ‘Academic and pastoral teams working in partnership to support distance learning students according to curriculum area’, Higher Education Pedagogies, 4 (1) 32-40 https://doi.org/10.1080/23752696.2019.1606674

Jorda, JM (2013) ‘The Academic Tutoring at University Level: Development and Promotion Methodology Through Project Work’,  Social and Behavioral Sciences 106 (1) 2594- 2601

Knight, P (2002) Being a Teacher in Higher Education  Buckingham: SRHE Open University Press

Lochtie, D, McIntosh, E, Stork, A, and Walker, BW (2018) Effective Personal Tutoring in Higher Education. Critical Publishing

Modell, S (2005) ‘Students as Consumers? An Institutional Field‐Level Analysis of the Construction of Performance Measurement Practices’ Accounting, Auditing & Accountability Journal 18 (4) 537-563 https://doi.org/10.1108/09513570510609351

Schwartz, K (2016) I Wish My Teacher Knew: How One Question Can Change Everything for Our Kids Da Capo Lifelong

Situmorang, D (2020) ‘Online/Cyber Counseling Services in the COVID-19 Outbreak: Are They Really New?’ Journal of Pastoral Care and Counseling 74(3) 166–174

Universities UK (2020) Coronavirus (Covid-19) https://www.universitiesuk.ac.uk/covid19

Williams, J (2012) Technology Education for Teachers BRILL

Yale, AT (2019) ‘The Personal Tutor-Student Relationship: Student Expectations and Experiences of Personal Tutoring in Higher Education’, Journal of Further and Higher Education, 43 (4), 533-544, https://doi.org/10.1080/0309877X.2017.1377164


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Dupery by Design

by Petar Jandrić

Since the election of a number of right-wing populist governments across the world, there have been increasing concerns that fake news in online platforms is undermining the legitimacy of the press, the democratic process, and the authority of sources such as science, the social sciences and qualified experts. The global reach of Google, YouTube, Twitter, Facebook, and other platforms has shown that they can be used to spread fake and misleading news quickly and seemingly without control. In addition to their power and reach, these platforms operate, and indeed thrive, in what seems to be an increasingly balkanised media eco-system where networks of users will predominantly access and consume information that conforms to their existing worldviews. Conflicting positions, even if relevant and authoritative, can be suppressed, discredited or overlooked as a result of filter bubbles and echo chambers.

Digital technologies have contributed to the prolific spread of false information, encouraged ignorance in online news consumers, and fostered confusion about how to determine fact from fiction. These same technologies have, however, permitted marginalised voices to be heard (transgender and autistic communities, victims of street harassment, for example), encouraged diversity, facilitated error detection and investigative accountability, and challenged privilege and prejudice. This opens up myriad questions such as:

  • How are online platforms designed to exploit particular vices such as close-mindedness, epistemic nihilism, insouciance, etc. and contribute to the power and dissemination of deception?
  • Deception: what is it? Is there anything peculiar about the times in which we live that should raise special concerns about the proliferation of fake news, lies, bullshit and other such vices online?
  • How do our individual and collective epistemologies interact with digital technologies to produce deceit?
  • How can we counter epistemic vices online, and protect ourselves and our institutions from their potentially baneful effects?
  • Can deception ever be justified? Is there anything to be learned from mass propaganda and deceit in other historical periods?

The epistemology of deceit in a postdigital era

To address these and related questions, Alison MacKenzie, Jennifer Rose, and Ibrar Bhatt have edited a book The Epistemology of Deceit in a Postdigital Era: Dupery by Design. The book offers strong theoretical and philosophical insight into how digital platforms and their constituent algorithms interact with belief systems to achieve deception, and how related vices such as lies, bullshit, misinformation, disinformation, and ignorance contribute to deception. This inter-disciplinary collection explores how we can better understand and respond to these problematic practices.

Continuing editors’ earlier work in the Special Issue of Postdigital Science and Education, ‘Lies, Bullshit and Fake News Online: Should We Be Worried?’, the contributors to the collection discuss the diverse ways in which deception is a pervasive feature of our communicative lives. Among the issues explored are how the design and infrastructure of digital platforms enable (or disable us from distinguishing between) what is true and truthful; fake or real; informative, disinformative or misinformative, malinformative, and other such information disorders. The scale of the dupery impacts on human rights, individual freedoms and dignity, agency and autonomy, in addition to the harms mentioned above.

The role of higher education is critical within this context, as universities have traditionally been regarded as sites of epistemic authority where knowledge is created and disseminated through the work of academics and theoretically grounded systems of teaching. Recent trends have shown that universities market the idea that an education through them will create ‘future-ready’, ‘globally-aware’ and ‘critically-thinking’ graduates, equipped with the relevant skills and knowledge to deal with issues facing our modern world, including public health crises, climate change and conflict.

The book was launched at a successful SRHE event held on 16 March 2021, in which editors, authors, and more than 100 members of the public engaged in a vivid discussion.

What is next?

These days, there is really interesting research taking place in different fields about post-truth and online deceit. Closer to higher education, and interesting example is Michael A Peters, Sharon Rider, Mats Hyvönen, and Tina Besley’s popular book Post-Truth, Fake News: Viral Modernity & Higher Education, which discusses the meaning and purpose of higher education in a ‘post-truth’ world.

Aided by a unifying postdigital theoretical framework which holds that human beings are systematically embedded in digital infrastructures, Alison MacKenzie, Jennifer Rose, and Ibrar Bhatt in The Epistemology of Deceit in a Postdigital Era: Dupery by Design make a unique contribution by reaching interdisciplinary boundaries to explore, examine and counter online deception, and analysing the power of social platforms and their role in the proliferation of epistemic harms. This line of inquiry is in its early days, and it will be very interesting to see where it will develop in the future.

Petar Jandrić is a Professor at the University of Applied Sciences in Zagreb (Croatia), Visiting Professor at the University of Wolverhampton (UK), and Visiting Associate Professor at the University of Zagreb (Croatia). His research interests are focused to the intersections between critical pedagogy and information and communication technologies. He co-authored the chapter ‘Scallywag Pedagogy’ with Peter McLaren (Chapman University, California) in Post-Truth, Fake News: Viral Modernity & Higher Education. pjandric@tvz.hr