University of Liverpool: From Fragmented Tools to Pedagogical Trust
University of Liverpool: From Fragmented Tools to Pedagogical Trust
How the University of Liverpool moved from fragmented AI experimentation to trusted, curriculum-aligned student support.
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Location
Merseyside, England
Institution type
Higher Education
Background
Background
The University of Liverpool, founded in 1881, is a Russell Group research-intensive institution located in the heart of Liverpool, UK. With over 27,000 students and a global reputation for research and innovation, Liverpool offers a broad range of undergraduate and postgraduate programmes across its faculties.
The University of Liverpool, founded in 1881, is a Russell Group research-intensive institution located in the heart of Liverpool, UK. With over 27,000 students and a global reputation for research and innovation, Liverpool offers a broad range of undergraduate and postgraduate programmes across its faculties.
At the centre of Liverpool's educational innovation sits the Centre for Innovation in Education (CIE). A team dedicated to supporting colleagues across the university in enhancing the student experience through curriculum design, digital education and pedagogical leadership. CIE actively runs pilot programmes to establish need and demand for digital innovation, working in partnership with academic staff and students to trial new platforms and new ways of teaching and learning.
At the centre of Liverpool's educational innovation sits the Centre for Innovation in Education (CIE). A team dedicated to supporting colleagues across the university in enhancing the student experience through curriculum design, digital education and pedagogical leadership. CIE actively runs pilot programmes to establish need and demand for digital innovation, working in partnership with academic staff and students to trial new platforms and new ways of teaching and learning.
Challenge
Challenge
As generative AI tools became increasingly embedded in student life, the University of Liverpool faced a challenge familiar across the sector: how to harness AI in a way that was pedagogically sound, institutionally controlled and genuinely beneficial to students, rather than simply permitting the use of tools that operated outside the university's academic framework.
As generative AI tools became increasingly embedded in student life, the University of Liverpool faced a challenge familiar across the sector: how to harness AI in a way that was pedagogically sound, institutionally controlled and genuinely beneficial to students, rather than simply permitting the use of tools that operated outside the university's academic framework.
CIE had observed growing experimentation with AI tools across faculties, but previous attempts to integrate disparate solutions had faced consistent barriers:
CIE had observed growing experimentation with AI tools across faculties, but previous attempts to integrate disparate solutions had faced consistent barriers:
Friction in Adoption
Friction in Adoption
AI tools that required separate logins, unfamiliar interfaces or additional onboarding created resistance among both students and staff, limiting genuine engagement.
AI tools that required separate logins, unfamiliar interfaces or additional onboarding created resistance among both students and staff, limiting genuine engagement.
Lack of Academic Trust
Lack of Academic Trust
General-purpose AI tools offered no mechanism for academic staff to shape, restrict or align outputs to their specific module content. This raises concerns about academic integrity and the quality of support students were receiving.
General-purpose AI tools offered no mechanism for academic staff to shape, restrict or align outputs to their specific module content. This raises concerns about academic integrity and the quality of support students were receiving.
Data Sovereignty
Data Sovereignty
There was a growing institutional concern about student interaction data being processed and harvested by external providers with no formal relationship with the university, data that held significant value for improving teaching practice.
There was a growing institutional concern about student interaction data being processed and harvested by external providers with no formal relationship with the university, data that held significant value for improving teaching practice.
"Our previous experimentation with 'disparate' AI tools often faced hurdles with student friction and pedagogical trust. We needed something that felt like a genuine part of the learning environment, not another system to log into."
"Our previous experimentation with 'disparate' AI tools often faced hurdles with student friction and pedagogical trust. We needed something that felt like a genuine part of the learning environment, not another system to log into."
Will Moindrot
Educational Developer
Solution
Solution
The CIE identified Plato as a partner that could address these challenges directly. Unlike general-purpose AI tools, Plato is purpose-built for higher education, integrating natively with Canvas, the university's existing VLE, and allowing academic staff to shape the tool's behaviour at programme and module level.
The CIE identified Plato as a partner that could address these challenges directly. Unlike general-purpose AI tools, Plato is purpose-built for higher education, integrating natively with Canvas, the university's existing VLE, and allowing academic staff to shape the tool's behaviour at programme and module level.
Plato gave students access to curriculum-aligned academic support through: course-specific Q&A, flashcard generation and revision aids. All grounded in materials approved by their lecturers. Academic staff retained full control over the tool's outputs, restricting responses to approved content and defining Plato's role within each module's pedagogy.
Plato gave students access to curriculum-aligned academic support through: course-specific Q&A, flashcard generation and revision aids. All grounded in materials approved by their lecturers. Academic staff retained full control over the tool's outputs, restricting responses to approved content and defining Plato's role within each module's pedagogy.
Critically, all student interaction data remained within the institution, giving Liverpool the ability to use aggregate insights to drive immediate teaching improvements, rather than allowing that value to be captured by external providers.
Critically, all student interaction data remained within the institution, giving Liverpool the ability to use aggregate insights to drive immediate teaching improvements, rather than allowing that value to be captured by external providers.
Insights
Insights
Plato saw significant engagement across the cohort, with students actively seeking personalised academic support, particularly during assessment periods or when traditional support was unavailable. The pilot proved the demand for course-aligned AI support at scale, and highlighted Plato's ability to extend staff capacity without compromising pedagogical integrity.
Plato saw significant engagement across the cohort, with students actively seeking personalised academic support, particularly during assessment periods or when traditional support was unavailable. The pilot proved the demand for course-aligned AI support at scale, and highlighted Plato's ability to extend staff capacity without compromising pedagogical integrity.
Crucially, the analytics generated gave academic staff immediate, actionable insight into student understanding, closing the feedback loop in real time.
Crucially, the analytics generated gave academic staff immediate, actionable insight into student understanding, closing the feedback loop in real time.
2,500
students in cohort
53%
signup rate
40%
activity out-of-hours
23,000+
questions asked
The quantitative results reinforce the value of Plato as more than just a support tool. As Will Moindrot notes, the ability to customise Plato at a module level proved particularly impactful.
The quantitative results reinforce the value of Plato as more than just a support tool. As Will Moindrot notes, the ability to customise Plato at a module level proved particularly impactful.
Rather than operating as a generic AI system, Plato can be shaped to reflect the specific pedagogy of each lecturer, adapting its tone, scope, and role within student interactions. This level of control allows staff to integrate Plato meaningfully into their teaching practice, aligning it closely with course objectives and delivery.
Rather than operating as a generic AI system, Plato can be shaped to reflect the specific pedagogy of each lecturer, adapting its tone, scope, and role within student interactions. This level of control allows staff to integrate Plato meaningfully into their teaching practice, aligning it closely with course objectives and delivery.
“Plato is a powerful resource for scaling curriculum-aligned support while maintaining pedagogical integrity and institutional control.”
“Plato is a powerful resource for scaling curriculum-aligned support while maintaining pedagogical integrity and institutional control.”
Will Moindrot
Educational Developer
From an institutional standpoint, the data generated through student interactions represents a significant strategic asset. Will highlights the importance of retaining and leveraging this insight internally, enabling universities to continuously improve teaching and student support based on real usage patterns. By capturing this feedback loop, institutions can make more informed decisions about curriculum design, while ensuring that the value created through student engagement remains within the university rather than being lost to external platforms.
From an institutional standpoint, the data generated through student interactions represents a significant strategic asset. Will highlights the importance of retaining and leveraging this insight internally, enabling universities to continuously improve teaching and student support based on real usage patterns. By capturing this feedback loop, institutions can make more informed decisions about curriculum design, while ensuring that the value created through student engagement remains within the university rather than being lost to external platforms.
"The insights provided by the Plato analytics have been really useful. We've been able to gather a sense of what questions students are asking, identify standout topics or materials that might need extra guidance, and respond to emerging trends quickly.
Compared to gathering student feedback at the end of a module, students can see changes being made rapidly to shape their learning."
"The insights provided by the Plato analytics have been really useful. We've been able to gather a sense of what questions students are asking, identify standout topics or materials that might need extra guidance, and respond to emerging trends quickly.
Compared to gathering student feedback at the end of a module, students can see changes being made rapidly to shape their learning."
Laura Blundell
Educational Developer
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Book a demonstration call to find out more about Plato.
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