Digital Negotiations in Student Migration:
Infrastructures and Impact
by Rohan Pai, Sameer Bajaj, Amrita Nanda, Supratik Mitra and Kavya Narayanan
At a Glance
The India-Germany student migration corridor reveals a fundamental contradiction in digital migration governance: while the number of Indian students migrating to Germany has doubled over the last five years with Indian students currently forming the largest international community on German campuses, the digital infrastructure designed to support them creates new forms of exclusion and surveillance. Analysis of 12+ interconnected systems demonstrates how students' personal data flows through multiple jurisdictions with minimal transparency or agency.
Lay of the Land
Background
Student cross-border mobility
International student mobility has surged from 2 million globally in 2000 to over 6.4 million in 2021 (UNESCO Institute for Statistics), becoming a major component of global migration since WWII. The number of people choosing to migrate for higher education is known to increase much faster than aggregate global migration.
What drives this migration?
1. The global transition to a post-industrial knowledge economy
In a majority of cases, education is not often cited as a primary driver of migration. Instead:
Knowledge advantage: The global shift to a post-industrial knowledge economy links economic prospects with education. Nations prioritize cultivating well-educated, highly skilled, flexible workforces as critical assets for economic prosperity (She and Wotherspoon). In the last year, Canada, UK, Australia, and Germany adjusted immigration policies to attract highly skilled labour for critical domestic industries.
International students are ideal workers: Those with temporary residence status are seen as suitable for domestic workforce integration due to recognized qualifications, country-specific experience/skills, and social connections gained through host country higher education. This allows low-income country migrants to move to high-income countries seeking greater financial prospects.
2. A knowledge economy designed to uphold Western hegemony
The transnational education industry operates within a knowledge economy designed to uphold Western dominance. Global North institutions have historically promoted Western education as superior quality and offering opportunities unavailable in the Global South. In fact, of 6.4 million international students in 2021, 5 out of 7 were enrolled in high-income countries; 60% of international students came from middle-income countries, with China representing 16% and India 8%.
The Creation of Migration Infrastructure
In this way, individuals who can afford it purchase knowledge capital needed for global marketplace success, incentivizing states and institutions to create supporting migration infrastructures.
Düvell and Preiss define migration infrastructures as multidimensional systems consisting of:
Migration infrastructures significantly influence trajectory and decision-making in international student migration. University reputation, scholarship availability, living costs, employer-university interactions, labour market considerations, residency/citizenship prospects form critical infrastructural levers. These are executed through organized structures (administrations, businesses, NGOs) that create resources and knowledge to mediate migration processes based on priorities set by the global knowledge economy.
The advent of digital migration infrastructure
Migration infrastructures are increasingly digitalized today with technology-mediated decision-making processes, adding new dimensions to international student migration.
Higher education institutions globally market programs through websites, email, social media, online test courses and use AI-driven surveillance tools to monitor student activity
Education consultancies/intermediaries provide information on immigration, residence permits, and financing during the application stage
State digitize key instruments like travel visas and amend data protection guidelines to advance policy goals
Finally, international students also create online channels and social media groups to share lived experiences, build support networks, and inform potential migrants about their journey
The university as a site of surveillance
However, drastic digitalisation in this context has many implications, with higher education institutions across the world risking evolution into sites of surveillance and control.
“As higher education institutions are viewed as the sites of control to uphold the post-industrial knowledge economy, they are incentivised to cooperate with state authorities who wish to control population inflows based on their requirements. Decision-making for migration management is dictated by state intentions, and this is perpetuated by higher education institutions closely monitoring and tracking student movement and behaviour within their campuses. Eventually, international students remain tied to pre-existing power structures that undermine their lived experience in the host country.”
While surveillance through border technologies is extensively documented, the evolution of higher education institutions into digital state-like entities that track student movement through mandated data collection is an emerging trend that raises significant concerns about the privacy and autonomy of international students.
This is carried out through data collection, assessment, and evaluation of students, with a history of ‘state spying, recruitment and surveillance’ and sharing personal data for security purposes.
Civil society organisations in Germany highlight the use of various technologies within the classroom and on university premises. During the COVID-19 pandemic, some German universities began to use proctoring software to monitor students taking their exams, raising concerns about the software violating fundamental rights by processing a large amount of personal data, including identity, location, videos of movements, and the student’s room. While the GDPR contains provisions to prevent misuse of video surveillance in schools, the threat of constant identification through cameras can exacerbate the existing power structures between a Global North institution and a Global South immigrant.
These instances have been observed in other institutions in the Global North, such as in UCLA when administrators proposed using facial recognition software for security surveillance on campus. In response, Fight for the Future ran facial recognition technology on more than 400 photos of UCLA faculty members and athletes and found the software incorrectly matched 58 of those with photos in a mugshot database—majority of those misidentified by the database being people of colour.
More recently, as student demands for universities to divest from financial investments in Israel’s ongoing offensive have taken the form of protests, facial recognition technologies and social media monitoring tools have been used extensively by law enforcement officials deployed on university premises.In the United States, 1,900 people on at least 43 college campuses were arrested at pro-Palestine protests. It is reported that in the past, at least 37 colleges have used Social Sentinel, a social media monitoring tool to surveil student protesters on campuses.
There is a lack of visibility into how the data collected by institutions at different points of the journey is stored, shared with other stakeholders and used in turn to govern the international student community. Law enforcement offices have a history of disproportionately deploying surveillance technology against marginalised communities, effectively blurring the lines between border security, immigration control, law enforcement and higher education institutions. The freedom of expression of individuals belonging to marginalised groups is constantly curtailed through nefarious data sharing practices amongst these entities.
The India-Germany corridor
Our research aims to unpack these questions on the implications of digitalisation and data-driven decision-making by narrowing it down and examining student migration within the Indo-German corridor. As international student migration is witnessing an upward trend globally, the India-Germany corridor has developed into a major site of interest.
An evolving regulatory environment
The GDPR, the EU AI act, the Interoperable Europe Act, the convening of the Eurodac group, the database infrastructure being implemented through the EU Agency for large-scale IT systems (eu-LISA), and the Entry/Exit System (EES)—an automated IT system for the registration of travellers from third-countries yet to come into force, will have strong intersections with the journey of a student migrating to Germany from India. Together, these frameworks will shape how a student’s personal data is collected, processed, and shared across EU systems (from visa application and biometric registration to border crossings and residence permits). They will also determine what automated decision-making tools can be used in their migration process.
Migration management of the 'undesirable migrant'
There are concerns around the ability of such systems to manage migration without discriminating against marginalized populations.
States treat migrants and asylum-seekers differently based on origin country, using visas and data infrastructure to exclude those deemed undesirable
Global travel ease is functionally divided along North-South lines; while Visa-free travel has been expanded between Global North states and within regional regimes like EU’s Schengen Area, tight Global North visa regimes limit options for large portions of world’s population, preventing the fulfillment of mobility aspirations
Citizens of Organization for Economic Cooperation and Development (OECD) member countries have gained mobility rights while similar rights for other regions have stagnated or decreased, particularly for citizens from African countries
These regulations being deliberated by state actors display the possibilities for datafication that have emerged through digitalisation and automation of migration control, putting into question the veracity of these systems to fairly manage the cross-border mobility of migrants and asylum-seekers through digital migration infrastructures.
Growing skills shortages in Germany and its focus on attracting skilled labour
Demographic shifts in Germany—an ageing population and low birth rate, are feeding into a growing skills shortage, with the Federal Government being prompted to take proactive measures to offset this trend. The German-Indian Migration and Mobility Agreement 2022, marks this shift in the Federal Government’s outlook towards attracting skilled labour, with a focus on implementing legal processes and policy measures to incentivise the movement of qualified young Indians to Germany.
As a result, numbers of Indian students migrating to Germany have doubled over the last five years; Indian students are now the largest international community on German campuses—a trend reinforced by developing digital migration infrastructures within an evolving regulatory environment.
State control over mixed migration
Transnational education as a product of the Western-led knowledge economy has roots in discrimination, control, and imperialist bordering practices against international students. State efforts to control population inflows through apparatus historically used in international student migration play a role in shaping mixed migration journeys.
The perils of seamless data sharing
“As denoted by our survey, 55% of migrants who studied in Germany reported that lack of information regarding how entities are processing personal data is proving to be a major point of concern for international students as it renders them vulnerable to arbitrary action from these entities. This could have far-reaching implications based on the identity of the migrant—often a critical factor in determining how international students are treated by institutions surveilling them.”
Large-scale digital infrastructure such as the Visa Information System, are supported by institutional mechanisms that enable seamless data sharing across multiple stakeholders. These processes are expedited by the ability to screen migrants and asylum seekers who are considered undesirable by the state, using information they have derived through a techno-political assemblage of multiple databases.[64]
For instance, the European Commission’s Migration and Home Affairs department has recently reached a political agreement to facilitate the flow of air passengers entering the Schengen area:
A. Setting a mandatory list of Advanced Passenger Information (API) data to be collected by air carriers from passengers on all flights to, from and within the EU.
B. Collecting data using “automated means” to increase the “reliability and efficiency of data collection”,
C. and the central management of data flows through an “EU-LISA router” that will “replace the current system of multiple connections between air carriers and national authorities,”to form a GDPR-compliant interoperable system.
Through a Community Lens
The student migration journey is mediated by a sequence of digital touchpoints. From research and application through acceptance, visa processing, travel and local registration, students interact with an array of formal and informal systems. How they move through this landscape varies by socio‑economic background, digital literacy and social capital.
The Journey Map Explained
The journey map illustrates the student migration process as a series of interconnected phases, highlighting the digital systems, both formal and informal, that students navigate. The map is divided into three main stages: the Application Phase, the Journey itself, and the Stay/Integration phase.
Application Phase
This initial phase is dominated by “Information Bundles.” Students gather and prepare the necessary documents and data for their applications.
Formal Systems: Students interact with official channels like the German Academic Exchange Service (DAAD), language centers, and the uni-assist portal. They take language proficiency tests (IELTS) and handle official correspondence.
Informal Systems: Simultaneously, students rely heavily on informal digital networks. They use platforms like Facebook groups, YouTube channels, and WhatsApp communities to seek advice, share experiences, and access information not readily available through formal sources. These channels serve as crucial support systems for navigating the complexities of the application process.
The Journey
This stage focuses on the formal migration process, moving from visa application to arrival in Germany.
Visa Application: The process starts with the visa application system (VIS), which involves biometric identification and document submission. Students also interact with formal systems for obtaining an acceptance letter from a university and their official registration certificate.
Initial Settlement: Upon arrival, students are met with a new set of digital and administrative hurdles. They must open a blocked bank account, obtain a local SIM card, and secure internet connectivity. The map also highlights the role of university and student academies in providing support and information.
Stay/Integration
This final phase represents the student’s life in Germany, with a continued reliance on digital infrastructures.
Digital Systems and Integration: Students continue to engage with systems for digital payment and digital education. These platforms are essential to manage daily life, from paying for services to participating in online classes. These systems, while offering convenience, can also pose challenges related to data privacy and surveillance.
A journey riddled with barriers
Throughout the journey, students face various barriers, such as a lack of reliable information, high costs, and language-related difficulties. Informal digital networks and information bundles are critical for students to successfully navigate the formal bureaucratic and digital systems.
The categorization, configuration and homogenization of the international student
As highlighted by Cranston and Esson, the digitalisation of borders allows states to use digital systems to exert control at the unitary level, enabling them to categorise individuals crossing the border.
The categorisation of the ‘international student’ is carried out using criteria informed by government policies and administrative capacity.
Institutional forces then further reinforce these categories (such as regulations to automate border data collection, or mandates on universities for those eligible to be sponsored for visas)
Higher education institutions adopting the terminology of ‘overseas’ and ‘home’ as fee categories further emphasise the role that geographical location, or residency, has in producing the international student as a population category.
This further undermines the identity of the student migrant, failing to acknowledge that international students are not a homogenous population. They are prone to internal tensions due to differing types of mobility, country contexts, and socioeconomic backgrounds.
Such a regime leaves student migrants vulnerable to the expectations of immigration authorities.
From the perspective of the state, this is a highly effective biopolitical technique for migration management because, “to secure a student visa, the individual has little choice but to ensure their declared aspirations and subsequent actions align with the visa conditions, that is, map onto what immigration authorities deemed constitutive of an ‘international student’”
The categorization, configuration and homogenization of the international student
The receiving state configures the mobile subject regarding health, wealth, labour/leisure, and risk, ensuring the individual is capable of learning in a specific language, is financially self-sufficient, and poses a low risk to the health and security of the nation. Information like this is pre-programmed into digital screening systems to ensure these criteria are being met by student migrants.\
The universalist conceptualization situates all international students as a homogenous group with access to and prior knowledge of proscribed digital technologies and undermines social inequities; students from the Global South often do not have the prerequisite knowledge to engage with such opaque digital systems and negotiate how their information is being collected*.
Therefore it is not just a question of how technology is deployed in migration infrastructure but who it is trying to protect from “risk”, who it is more welcoming for, and what aspects of the migrant it chooses to recognise.
*Sue Timmis & Patricia Muhuro (2019) De-coding or de-colonising the technocratic university? Rural students’ digital transitions to South African higher education, Learning, Media and Technology, 44:3, 252-266, DOI: 10.1080/17439884.2019.1623250
Resistance of categorization
Nevertheless, these categorisations see resistance from students due to their self-perceived identity that may not completely align with the categorisation tendered by higher education institutions—prompting them to rely on other forms of digitally-mediated communication that serve their specific needs (for instance, through community social media groups).
Along the Periphery
Drawing on IOM’s Determinants of Migrant Vulnerability, which frames vulnerability as the product of individual, household, community and structural factors, along this corridor, vulnerability gathers at the edges of formal institutional structures, in the gap between how legible students are to institutions and how little they can negotiate that legibility.
Asymmetric legibility
Student migrants are made vulnerable by being made hyper-visible within these systems. A dense chain of collection across the DAAD, uni-assist, the Goethe-Institut, ETS, Passport Seva, the Visa Information System and PNR records assembles biometric, financial, academic and locational traces into data doubles that travel ahead of the student. Students have minimal visibility into how these systems interconnect, or who reads them.
Limitations in agency
Even inside a mature data-governance jurisdiction, agency is limited. Contesting a practice (exam-proctoring software that films a student’s room, for example) risks discriminatory treatment and might foreclose options for recourse.
Risks of a homogenized identity
International students, as explained earlier, are not a homogenous category. Socioeconomic background, region, prior schooling and language proficiency determine who can afford intermediaries, absorb costs and navigate German-language bureaucracy. The visa-conditional category, like the ‘overseas/home’ fee binary, flattens this difference. The international student is thus forced into a performance of an idealised, self-sufficient and low-risk subject.
Economic status
Solvency is a precondition of entry. The blocked account and proof of self-sufficiency mandate financial standing as eligibility. Banking, income and scholarship data captured during application stages further feed the assemblages that financial institutions and authorities use to read a student’s capability and mobility. For those who are debt-financed, issues that arise with frozen accounts or delayed visas may further travel through enrollment and shape their integration experience.
Unequal access to community resources
Resisting institutional categorisation, students lean on community social media groups for information that may not be easily available or accessible through formal channels. These information bundles are protective but are also stratified in access; access to such groups and the information available within them further tends to splinter along language, region and institution. Access to these spaces is more complicated for those without the right connections, or from less-represented geographies, who end up receiving less reliable guidance than peers who arrive already networked.
Discrimination
Migrant experiences along this corridor are shaped by a pervasive fear that asserting one’s data rights will invite worse treatment.
For these students, then, vulnerability is entrenched through the impossibility of contesting use of their data. They are maximally legible being biometrically enrolled, financially profiled and tracked across borders with their data retained for years and yet remain least able to see, correct or refuse how that data is read and used.
Vulnerability in these ways is produced at the intersection of the knowledge economy, biometric bordering, data assemblages and socio-economic hierarchies.
Across Data and the Digital
This section explores the interlinkages between digital migration infrastructures in both countries, and how these affect the migratory trajectories of Indian students moving to Germany for higher education. An added emphasis has been placed on deconstructing the data flows that have been observed when students interact with digital migration infrastructures in their journey, to inform readers about the implications it could have on the migrant when stakeholders have access to information about migrants through various data sources.
Regulators
Government departments and agencies with the legal power to regulate migration, issue documentation and enforce immigration laws.
Eg: Germany’s Federal Ministry of Education and Research (BMBF); Federal Office for Migration and Refugees (BAMF); State level education ministries; Immigration authorities, EU institutions, European Commission, European Parliament, EU-LISA for migration IT systems; European Data Protection Board for GDPR
Facilitators
Well funded, large scale organisations providing protective services, legal aid and humanitarian assistance through formal programs or channels
Eg: UNESCO, OECD, IOM shaping global student mobility norms, data collection and policy frameworks
Service Providers
Formal businesses or institutions providing commercial services to people on the move, although it need not be exclusive to them, which requires data collection or identity verification.
Eg: Vendors of proctoring software, facial recognition tools, campus security systems, ed-tech platforms, education Institutions (admissions offices, international student services, campus administration)
Advocacy
Organisations primarily focus on providing legal aid, representation, rights and policy advocacy for people on the move.
Eg: Student advocacy groups
Community Actors
Community or bottom up organisations which are created by people on the move as systems of care.
Eg: WhatsApp and Facebook groups
Research Organisations
Organisations or institutes which conduct research about or with people on the move enabling further movement towards improved living conditions.
Eg: Migration studies scholars, higher education researchers, data governance experts
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The following information should inform readers about the type of digital interactions that take place, and the data-sharing practices and agreements associated with these infrastructures. This sheds light on how data flows between institutions are used to make decisions regarding the treatment of international students in the host country:
Entity
Data Collected
Mapping Data flows and Interactions
German Academic Exchange Service (DAAD)
The DAAD supports the internationalisation of German universities, promotes German studies and the German language abroad. It is a registered association and its members include German institutions of higher education and their student bodies. DAAD relies on a network of Regional Offices, Information Centres and Information Points with coverage in more than 70 countries, to provide applicants up-to-date information on educational institutions and programs in Germany.
Personal Data: Name, Email address, Country of origin, Country of residence, Current level of education, Subject area, Age, Gender, Graduation year, How you became aware of the DAAD, IP address Non-Personal Data: Date and time of access, Duration of visit, Operating system, Volume of data sent, Type of access, Domain name
The DAAD website includes social media plug-ins that collect information upon user engagement. Social media websites can connect user information to accounts and track IP addresses. Google Analytics is used, with data stored on Google servers in the United States. Third-party cookies used by other providers can display adverts or integrate social media content. External data recipients: Processors for improving technical infrastructure; Public bodies (e.g., prosecutors, courts, fiscal authorities) for legal reasons; Private bodies based on consent or mandatory requirements. Data processing in third countries has verification and guarantees through EU-US Privacy Shield or agreements. DAAD’s cookie data is erased after 7 days unless exceptional circumstances apply. Third-party providers, social media platforms, and public institutions in Germany and third countries can add to student data assemblages. Students have minimal knowledge of other data sources and their impact.
Uni-assist
For international prospective students, uni-assist offers a central point of contact for applying to universities in Germany. Its core responsibility is the evaluation of international student applications and determining their eligibility for target universities. Uni-assist operates its own IT development department, which develops in-house software solutions to support the highly specialised application processes, and ensures seamless interfacing with all common university systems.
Personal Data: Name, Address, Telephone number, Email address, Banking details, Financial income data, Scholarship information, Educational records, School transcripts, References, Language proficiency (TOEFL or IELTS) provided through ETS Non-Personal Data: None identified
The website uses Matomo (formerly Piwik) software. Matomo saves a cookie on the user's device; data collected is analysed under a pseudonym. IP address is anonymised before processing; deleted after 3 months. User’s application documents deleted after 3 years. Public authorities and offices have access. A connection to YouTube servers is only established when a user engages with embedded YouTube videos. Payment data transmitted to service providers; may transfer to online payment services, financial institutions, banks, and credit card companies. Accounting-relevant data deleted after 10 years. Certain data may be transmitted to the applicant's country of origin or outside EU/EEA. Students have limited agency in knowing who tracks their movement. Financial institutions may use data assemblages to measure financial capability and mobility.
German Language Centres (Goethe Institut)
The Goethe Institut is a leading provider for German language courses and examinations globally, supported by the German Federal Foreign Office, non-profit foundations and companies in Germany and the EU.
Personal Data: Name, Email ID, Course, User-generated content, Third-party payment information. Non-Personal Data: None identified.
Data processing by third parties within EU/EEA. Data collected by cookies is anonymised and deleted after the session ends. Data stored in central management systems accessible to Goethe network; blocked after contract ends except for legal retention. Payment data accessible to commissioned banks/service providers. Google Maps features may transfer data outside EEA. External service providers include Mailchimp and Web Beacon. Google Maps can access locations integrated into Google systems potentially not GDPR-compliant.
Educational Testing Service (ETS)
ETS is the world's largest private educational testing and assessment organisation, provider of TOEFL and GRE.
Personal Data: Biometric data (fingerprint, photo, voiceprint), writing samples, test types, school affiliation, degree info, demographic data, registration records, test records, purchase history, order info, audio/video recordings. Non-Personal Data: None identified.
Personal information shared with service providers, telecom providers, payment processors, auditors, and government agencies. Biometric identifiers disclosed to cybersecurity firms/law agencies. Data used for research (anonymised or pseudonymised). Tracking tools include pixel tags, canvas fingerprinting, mouse tracking, keystroke analytics. ETS websites/servers in the U.S.; information transferred to U.S. and other countries. Despite anonymisation, data is accessible to both state and private actors.
Passport Seva Kendra
The Passport Seva Project in India, implemented via PPP with Tata Consultancy Services, retains core functions like verification, granting and issuing of passports under the Ministry of External Affairs.
Personal Data: Biometric data, proof of age, residence, nationality, family details, criminal history. Non-Personal Data: None identified.
Government agencies can access data under due process. The site does not use cookies. It provides limited information about collected data or interactions with other systems.
Visa Information System (VIS)
The VIS is a central IT system linking national systems in the Schengen Zone, storing biometric data for 59 months and accessible to law enforcement.
Personal Data: Biometric and demographic data, passport ID, bank statements, university acceptance information. Non-Personal Data: None identified.
Data is accessible to border and law enforcement authorities to verify identity and visa authenticity. Asylum authorities have limited access to determine responsible EU States. Europol may request access for terrorism or crime cases. The system profiles individuals from third countries.
Air Ticketing Platform (Passenger Name Record)
Under EU regulations, governments can retain PNR data for a maximum of five years, to allow law-enforcement officials to access it if necessary. The regulations state that after six months, the data is masked out or anonymised.
Personal Data: Name, demographics, payment info, travel agency details, passport, visa, frequent flyer data, travel itinerary, seat/meal preferences. Non-Personal Data: None identified.
PNR data can be accessed by travel agents and governments and stored in CRS/GDS. In the U.S., it is stored in ATS-P for 15 years. It can be re-personalised per EDRi research. Governments can retain PNR data for up to 5 years for law enforcement; it is masked after 6 months.
Residents' Registration Office (Bürgeramt)
Students must register their residence here upon arrival in Germany.
Personal Data: Passport, rental contract, housing confirmation, registration form, bank details. Non-Personal Data: None identified.
Data is governed by GDPR, HDSIG, and TMG. Cookies are deleted after the session. Matomo is used for analytics, with data anonymised.
Local Immigration Office (Ausländerbehörde)
Issues Student Residence Permit Card valid for one to two years.
Personal Data: Name, demographics, passport, visa, housing, bank details, university letter. Non-Personal Data: Date/time of visit, browser, pages, IP (anonymised).
Uses Matomo and temporary cookies. No profiling or advertising. Data is shared only when legally required. Users can request information, erasure, correction, or objection.
Health Insurance Provider
Health insurance is mandatory; students under 30 can enrol in public insurance.
Personal Data: Name, demographics, passport, medical records, bank details, university acceptance, registration. Non-Personal Data: None identified.
Operates under GDPR and Federal Data Protection Act. Data is encrypted using SSL.
Bank Account Provider
To open a German bank account, having a residence permit and a city registration letter is mandatory. Students must create a blocked account before arrival.
Personal Data: Name, demographics, passport, visa, IBAN, university letter. Non-Personal Data: None identified.
Data is transferred to Deutsche Bank AG and not shared unless necessary. Browser encryption and electronic identifiers are used for protection.
SIM Card Provider
The identification process can be completed using the passport and German address either online via video chat or at a German post office (Post-Ident).
Personal Data: Name, contact, passport, bank account. Non-Personal Data: None identified.
Uses ReadSpeaker, social media plug-ins, and commissioned data processors. Data is processed in the EU/EEA; exceptional cases may involve third countries with GDPR safeguards.
Student Networks and Social Media
These community-led infrastructures provide accessible peer support through groups like WhatsApp and Facebook, helping students navigate migration processes and democratise knowledge.
Not specified.
Operate informally; enable exchange of localised, experience-based knowledge, creating inclusive digital ecosystems that mitigate information asymmetry.
Mapping digital infrastructures
By studying the digital journey map, we developed a framework that explains the interactions of students with digital migration infrastructures, the resulting data assemblages and data infrastructures, and the decision-making process that is dictated by stakeholders in these positions. The digital infrastructures mapped in the case of international students moving from India to Germany can be categorised into formal and informal digital migration infrastructures.
Formal migration infrastructure consists of systems that are primarily deployed by state, higher education institutions and private sector actors. These are usually preceded by legal or regulatory backing to manage migration, and provide student migrants with key sources of information to aid in mediating the journey. Examples include the Visa Information System, Air Passenger Information System, Passenger Name Records, German Academic Exchange Service (DAAD), Uni-Assist, German Language Centres, standardised testing institutions, health insurance and residence permit authorities among others at different stages of the journey.
Informal migration infrastructure consists of systems that can be deployed by a wide range of actors, but the foundation of these technologies remains community-oriented or community-led. These can be used by students as a form of resistance against impositions made by formal migration infrastructures, to derive further visibility into information that is gatekept by formal institutions. Examples include, but are not limited to, social media groups on Facebook, WhatsApp and Reddit, YouTube channels that act as student guides, and clubs and societies originating within the universities.
The creation of data assemblages
and migration infrastructures
The infrastructure created by these systems consists largely of state institutions and some private actors. While it sheds light on flows of people, it also aids profiling, forecasting, and conceptualising migration, which is cause for concern. Thus, state institutions accumulate power through the generation of data, control of access to data, and the merging of various data, but also through their analysis and interpretation. In this way, data assemblages can be combined for control of data and its interpretations for stronger technological capacity.
The international student as a user and data subject
The international student who continues to occupy the category of the user becomes a data subject whose rights are dependent upon their behaviour within the digital infrastructure.
The creation of such opaque infrastructure offers minimal visibility to international students into how their data is being processed and creates vulnerabilities in protecting themselves from the negative effects of imposed visibility and action from these entities.
The creation of data doubles
The evolution of digital migration infrastructures depicts how they are no longer created to only record migration flows or are limited to a single stakeholder. They are extensible through data assemblages, and the formation of data infrastructures envisioned by various stakeholders with differing logic for understanding and controlling migration.
These digital infrastructures and the implications of the data they collect and operationalise cannot be understood in isolation, and it is important to analyse how these systems engage with one another through constant data sharing.
The outcome is a multiplicity of data flows working towards differing ends depending on the stakeholders' intent and accessibility to the data.
State institutions dominate international student migration infrastructure, exemplified by centralized systems like the Visa Information System that coordinate with various actors mediating the migration journey..
The digital migration infrastructure is conceptualised to reinstate the intra-government policies through the different institutions and bureaucracies, creating digital personas or data doubles of the international student.
These personas can be constantly surveilled and analysed, giving limited agency to the international student to negotiate how their data will be used and by whom. To ensure the digital persona meets the criteria set by the state, generating constant digital flows becomes important.
The categorization, configuration and homogenization of the international student
As highlighted by Cranston and Esson, the digitalisation of borders allows states to use digital systems to exert control at the unitary level, enabling them to categorise individuals crossing the border.
The categorisation of the ‘international student’ is carried out using criteria informed by government policies and administrative capacity.
Institutional forces then further reinforce these categories (such as regulations to automate border data collection, or mandates on universities for those eligible to be sponsored for visas)
Higher education institutions adopting the terminology of ‘overseas’ and ‘home’ as fee categories further emphasise the role that geographical location, or residency, has in producing the international student as a population category.
This further undermines the identity of the student migrant, failing to acknowledge that international students are not a homogenous population. They are prone to internal tensions due to differing types of mobility, country contexts, and socioeconomic backgrounds.
Such a regime leaves student migrants vulnerable to the expectations of immigration authorities.
From the perspective of the state, this is a highly effective biopolitical technique for migration management because, “to secure a student visa, the individual has little choice but to ensure their declared aspirations and subsequent actions align with the visa conditions, that is, map onto what immigration authorities deemed constitutive of an ‘international student’”
The receiving state configures the mobile subject regarding health, wealth, labour/leisure, and risk, ensuring the individual is capable of learning in a specific language, is financially self-sufficient, and poses a low risk to the health and security of the nation. Information like this is pre-programmed into digital screening systems to ensure these criteria are being met by student migrants.\
The universalist conceptualization situates all international students as a homogenous group with access to and prior knowledge of proscribed digital technologies and undermines social inequities; students from the Global South often do not have the prerequisite knowledge to engage with such opaque digital systems and negotiate how their information is being collected*.
Therefore it is not just a question of how technology is deployed in migration infrastructure but who it is trying to protect from “risk”, who it is more welcoming for, and what aspects of the migrant it chooses to recognise.
*Sue Timmis & Patricia Muhuro (2019) De-coding or de-colonising the technocratic university? Rural students’ digital transitions to South African higher education, Learning, Media and Technology, 44:3, 252-266, DOI: 10.1080/17439884.2019.1623250
Resistance of categorization
Nevertheless, these categorisations see resistance from students due to their self-perceived identity that may not completely align with the categorisation tendered by higher education institutions—prompting them to rely on other forms of digitally-mediated communication that serve their specific needs (for instance, through community social media groups).
An emerging state-private sector nexus
Additionally, digitalisation has paved the way for private sector companies to collect critical, personal data on their systems about individuals crossing the border through advanced technologies that are key components of immigration enforcement today. These systems are opaque, and there is negligible information available on how they process data, who they share it with, and for how long and what purposes they store it for.
The other side of the coin: Defining information bundles
While student migrants interact with a range of formal and informal infrastructures that exist across the journey from application to integration, each individual’s experience differs based on their context (first-generation learners, language barriers, choice of program) and socioeconomic background. To accommodate these differences in access to digital infrastructure, we categorise an individual’s use of a set of digital systems as their information bundle—a digital bundle of information sources includes the sources that a person relies on repeatedly and does not include occasional visits to a new site.
Conceptualising usage of digital infrastructure as information bundles helps to view digital systems from the individual’s perspective, providing us insights on how each migrant’s activity may differ.
For instance, an individual who comes from an urban, English-speaking background might not be required to provide standardised tests to prove language proficiency, and may rely on education consultancies to complete parts of their application. However, a student from a rural, non-English speaking background may have to rely heavily on WhatsApp communities to translate information on websites and help them understand mandatory processes in the absence of acquaintances who have travelled to Germany before. When international students move across national borders, they often do not automatically make the digital move to new sources of information. Many international students do not always make a corresponding digital move and continue to rely on previously established bundles of information sources.
Student Networks and Social Media
These community-led and community-oriented infrastructures are built around ethics of support, providing aspiring international students with the agency to negotiate with information asymmetry in infrastructure deployed by the state and other high education institutions. Examples include WhatsApp and Facebook groups. These groups are more accessible, though in some cases, membership relies on existing social and economic capital. ‘Study in Germany’ Facebook and WhatsApp groups provide constant support throughout the different phases of the journey with discussions of the pros and cons of Germany, the various types of universities in Germany, the admission requirements, and employment outcomes.
These groups have also been successful in providing localized knowledge and specific information about visa officers and organizing important papers and finances. Some members offer 1-on-1 assistance and support for a small fee—resembling traditional consultants—and also have YouTube channels, where they provide insights into the lifestyle and experience of living in Germany. The groups thus create an accessible network that helps provide new information through national networks, which aid integration (for example, insurance, permits, accommodation, etc.). The networks these groups create democratize aspiration and knowledge by making previously gatekept information more accessible, helping overcome apprehension and isolation created by administrative systems and increasing mobility for people who may have not been able to access it in the past.
How do data assemblages and information bundles differ?
Information bundles refer to the set of formal and informal digital infrastructures used by any individual during the migration journey. These are highly visible to the migrant user, and they retain the agency to pick which systems they choose to interact with during the process, unless they are acting due to existing legal mandates like in the case of border technologies. Data assemblages are produced as exhaust from the interactions between student migrants and digital systems, and these are only visible to stakeholders deploying, maintaining and governing these systems. International students have minimal clarity about how their data is stored and shared among these assemblages, unless this information is published in the public domain by actors deploying this infrastructure. A set of data assemblages form a data infrastructure, and these are used by stakeholders to make decisions pertaining to migration management.
Within our Framework
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The Migration Infrastructure Assessment allows us to analyze migration corridors in relation to each other and categorize them as nascent, emerging or mature based on:
How their digital and offline infrastructure is designed and governed (State of Digital Infrastructure, Governance of Digital Infrastructure)
How they enable community participation (Community Agency)
How communities access information and engage with narratives (Information Landscape)
It assesses corridors on the state of their digital infrastructure, how such infrastructure is governed, the state of community agency, the nature of their policy environment and information landscape.
Insights from this study reveal that while digital and data governance infrastructure along India-Germany student migration channels are emerging, policies and safeguards for student migrants are still nascent.
Entity
Nascent
Emerging
Mature
State of Digital Infrastructure
Prevailing technocratic systems use advanced surveillance technologies in universities, but undermine social, spatial, historical, and cultural complexities, creating digital systems which are exclusionary and that offer easier access to information and opportunities to students belonging to the Global North.
Governance of Digital Infrastructure
While the GDPR contains provisions to prevent misuse of video surveillance in universities, the threat of constant identification through monitoring and proctoring technologies can exacerbate the existing power structures between a Global North institution and a Global South immigrant.
Community Agency
Community-oriented infrastructures are built around ethics of support, providing aspiring international students with the agency to negotiate with information asymmetry in infrastructure deployed by the state and other high education institutions.
Examples include WhatsApp and Facebook groups. These groups are more accessible, though in some cases, membership relies on existing social and economic capital.
Policy Environment
Digital systems and larger infrastructure created or remodified are touted by nation-states as efficient and increasing security. However, they have enabled the rise of technocratic institutions imbued with coloniality which view international students—especially from the Global South—with suspicion.
State of Digital Infrastructure
State efforts to control population inflows through apparatus historically used in international student migration play a role in shaping mixed migration journeys. Transnational education as a product of the Western-led knowledge economy has roots in discrimination, control, and imperialist bordering practices against international students.
The Path Forward
Stakeholder Type
Problem Area
Action/Responsibility
More Details
Regulators
The GDPR contains multiple provisions that give the data subject access to how their personal data is being processed, shared, used and stored. For instance, the adopted framework for interoperability between EU information systems in the field of borders and visa, is not just a bringing together of European security architecture, but the merging of various EU law and policy objectives, such as border checks, asylum, immigration, and police and judicial cooperation.
As pointed out by StateWatch, the EU legislator's move to make large-scale IT systems interoperable has raised questions about their governance and the ways to safeguard fundamental rights in this context.
Mandating data collection and sharing in this manner leaves international students vulnerable to institutions making decisions about them based on information available on these systems.
Create avenues for negotiation in digital and data regulation
Adding a layer of choice for the data subject, that allows them to prevent institutions from accessing data under the interoperable framework unless approved by the data subject, could provide migrants agency over which institutions they choose to share their data.
Regulators
AI used as part of EU large-scale databases in migration, such as Eurodac, the Schengen Information System, and ETIAS will not have to be compliant with the Regulation until 2030. This comes as a serious threat to immigrants, who are already vulnerable to the inherent biases in these AI systems towards marginalised groups.
Create avenues for negotiation in digital and data regulation
Regulators will immediately need to reconsider the implications of such a stance on immigrants whose data is being stored in these systems for migration management.
German Academic Exchange Service (DAAD)
University premises have become an extension of the state. Such practices not only infringe on students' privacy rights but also contribute to a sense of alienation, particularly for those who already feel vulnerable in a foreign country. The pervasive monitoring can stifle free expression and discourage students from fully participating in campus life, out of fear that their movements and activities are being scrutinised.
Institutionalise an autonomous entity that conducts oversight on the use of surveillance technologies on university campuses and classrooms
To prevent surveillance and tracking from higher education institutions, institutionalising an autonomous body for oversight can add a layer of protection for international students and create a separation between state and higher education institutions.
The German Academic Exchange Service (DAAD) that is keen on promoting higher education in the country, can house this initiative as part of their commitment to create better outcomes for international students.
German Academic Exchange Service (DAAD)
The homogenisation of a diverse, foreign student body into a single category, 'international student', severely undermines the varying socio-economic positions they come from. By failing to recognise these distinctions, institutions not only overlook the specific support and resources that some students might need but also perpetuate a one-size-fits-all approach that can exacerbate inequities and hinder the true potential of international education
Enable student collectives to negotiate with university administrators for recognition of various identities under the 'international student' category
By enabling student collectives that are formed to represent diverse groups to engage with the university administration, higher education institutions can begin to address the unique needs and challenges faced by different segments of the international student body.
These collectives can provide valuable insights and advocate for tailored support systems, such as financial aid programs, digital literacy resources, and cultural acclimatisation activities that reflect the varied backgrounds of students.
Additionally, fostering a more nuanced understanding of the international student experience can help create a more inclusive and supportive campus environment.
To make this possible, it would be required to prevent unlawful social media tracking as these informal channels form the backbone for student collectivisation in the digital age.
Behind the Research
We adopted an evidence-based, mixed-methods approach to track the journey of the student migrant from India to Germany. We primarily deconstructed data flows in migrant interactions with digital migration infrastructures. As the conceptualisation of migration infrastructures is still evolving, we aim to advance this discourse through our framing that brings together previously established concepts related to information bundles, data assemblages and data infrastructures. This study is anchored on these conceptual frameworks, and is complemented by research on digital migration infrastructures in the context of student mobility in the Indo-German corridor.
The following methods were employed for the study:
Desk Research
SECONDARY
Expert Interviews
PRIMARY
Field Exploration
PRIMARY
Analysis
AUGMENTING
Literature Review of academic and policy documents on digital migration systems
Expert Interviews with researchers and practitioners in digital migration
Online Surveys that collected information about student interaction with digital infrastructure in the application and integration phases of their journey. An entire section of the survey was dedicated to breaking down data-related experiences, covering the agency to negotiate with institutions that are collecting data, and the participant’s understanding of their data-related rights provisioned through the GDPR.
System Analysis of data flows and governance practices
Acknowledgements
We would like to thank our survey respondents for taking the time and effort to provide valuable insights through the online questionnaire. We are also really grateful for Dr Sazana Jayadeva and Dr Derya Ozkul, for their inputs during the course of our research.
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