AI-driven big web redesign: two case studies in Italian universities

Abstract

This paper explores the challenges of web redesign in Public Administration (PA), particularly within universities. Universities often struggle with fragmented online presences due to distributed editorial models and diverse communication needs across research, education, and dissemination activities. Limited resources further restrict investment in upskilling staf and adopting modern technologies. Open source solutions, though cost-efective, are often chosen without considering user experience. We present a methodology that combines user-centered design, Artificial Intelligence (AI), and ”radical collaboration” to achieve a future-proof and scalable redesign. Starting from a case study of a major web redesign project at an Italian university (2014-2020) involving hundreds of websites and over 200 content editors, the paper details the process, including a large-scale content audit using AI, single sourcing with AI-powered content transformation, and user experience (UX) testing with data visualization. This approach resulted in a unified, user-centric online presence and garnered recognition, including the ForumPA award for best innovator. The paper concludes by discussing the applicability of this methodology to other PA institutions facing similar challenges.

1. Introduction

This work addresses the topic of web redesign for Public

Administration (PA), which typically constitutes a largescale institution often tasked with managing a multitude of websites and touchpoints aimed at diverse audiences, and governed by a distributed editorial model, frequently lacking central coordination. This scenario is particularly pronounced within the context of universities, whose communication needs usually respond to three centrifunation activities [ 1 ]. Devising a unified communication strategy is therefore a very challenging problem that is compounded by the limited specialized internal resources typically available within universities. This usually leads such institutions to create a disaggregated online presence, supported by technologies with limited scalability. users [ 2 ]. In this paper, we move from our experience where some of the authors faced the wicked problem of redesigning a plethora of hundreds of websites that were left abandoned and unmanaged for years and where more than 200 content editors were contributing without any coordination [ 3 ]. We illustrate our methodology based on user-centered design, artificial intelligence (AI), and radical collaboration and explain how it allowed us to approach the problem of large-scale web redesign in a principled way that is future-proof and scalable. We CEUR

ceur-ws.org redesign all touchpoints and how this approach can be pletely disconnected, reachable only and not always, by applied to other existing realities. search engines. This condition is clearly observable by looking at Figure 1, where we show the structure of one of the major components of the UniGe website panorama, 2. A big web redesign for UniGe studenti.unige.it, before the redesign process. It is eashomepage and education ily noted that the graph has a highly entropic structure, websites displaying subgraphs composed only of PDF files, cliquelike components of pages all connected to one another, Established in 1481, UniGe has a long history of aca- and disconnected subgraphs which are only reachable demic excellence and innovation. The university enrolls through search engines. about 3000 faculty and staf and it ofers more than 200 Content was in even worse condition: incomplete undergraduate and graduate programs across various or redundant, outdated, self-contradictory, systematidisciplines, including arts, sciences, engineering, law, cally drafted in an involuted form and with bureaucratic economics, medicine, and more, attracting tens of thou- and sectorial language, incomprehensible to the users sands of students every year. UniGe’s major web redesign to whom they are addressed. In the context of such a project launched in 2014 in sync with and in support of transformation project, the evolutionary web redesign the university’s strategic goals at the time, summarized mode works as long as it is free to scale up. But when the by the five keywords of the governance vision: simplifi- complexity of the domain or intervention reaches signification, participation, welcoming, integration and growth. cantly increased complexity, a technological and process Simplification guided the redesign work from the very paradigm shift is required. Without this, the resources beginning. The starting point is to let the communica- and procedures in use up to that point prove wholly intion system deal with inherent content complexity and adequate to handle the complexity involved. The risk is present the users with selected information that is defined the indefinite absorption of all available resources, resultby their unique profile. Participation materialized in the ing in the intervention not being successful [ 6 ]. In the system of content single-sourcing, which made possible context of a complex socio-technical system, such as a the coexistence of central editing and distributed editing. large PAs, this leads to a waste of public resources and Welcoming consisted in adopting the user-centered de- the realization of inadequate outcomes. Paradoxically, it sign approach that guided the entire project: from user also fosters internal resistance to change, manifesting as research to user profiling. Integration proved to be one a rejection of a goal—user experience—that is now seen of the biggest challenges. It first originated from the as entirely alien to the culture of PAs. adoption of the principle of decoupling of the backend and frontend [ 4 ] and the principle of headless develop- 3. AI-driven big web redesign ment(Koenig, 2018). It then guided us to develop a middleware layer, which allowed for the coexistence of new methodology and legacy systems and enabled data interconnection [ 5 ]. Lastly, growth was the result of design activities In this section we describe the methodologies employed geared toward substantial change in the services ofered to tackle the redesign issue according to the pipeline to students. The aim here was to build an experiential rep- illustrated in Figure 2. The redesign process starts from utation based on improving the UX rather than forcibly a large-scale website whose structure is highly entropic. pursuing a transformational facade. Borrowing methods from design and computer science,

The first interventions required by the new governance we combine quantitative and qualitative approaches to were a feasibility study and an assessment of the efort achieve a multidisciplinary future-proof solution capable needed to redesign the UniGe’s website in light of the of adapting to diferent users’ needs whose result is a keywords of the new strategic vision. An in-depth anal- newly designed website that maximizes findability and ysis revealed a common situation among Italian PAs: the maintainability over time. website structure mirrored the institution’s ambiguous internal processes. It was, in fact, a multi-site. The home- 3.1. Design and interdisciplinarity page was the cohabitation space for an inordinate num- The first condition for a successful redesign is an evober of pages that make up a multitude of independently lution of the radical collaboration approach [ 7 ]: in fact, managed websites supported by diferent technological when dealing with the UniGe use case, the first author solutions. Overall, this panorama of websites lacked a conducted the design and prototyping phases in a multiunified design and even more so a cohesive Information disciplinary group, involving faculty with diverse experArchitecture (IA). Webpages were linked in a maze of tise and other stakeholders within the university. This cross-references, with entire sections forgotten and com- led to the subsequent structuring of a small, permanent multidisciplinary group consisting of designers, devel- constraints, eventually involving compartments of the inopers, process analysts, copywriters and data scientists. stitution even quite distant from those directly involved As the complexity and project burdens grew, the pro- in service delivery [ 8 ]. totyping group evolved into the permanent radical collaboration group, eventually becoming a design group 3.2. Network Analytics and AI for as well. At the same time, the group’s traction also exlarge-scale web redesign panded: the design research driving the original initiative increasingly needed data and the ability to analyze it to The process of an efective web redesign that is more interpret the complexity of the socio-technical context profound and radical than a “Face Lift” usually starts and to guide design action. This, in turn, continued to with a thorough content audit of the entire existing set exert a profound influence on technological choices and of pages. This process is time-consuming and cannot the choice of questions to be answered in the data. The be done manually if the number of pages ranges in the second condition necessary to achieve change in com- order of tens of thousands - a typical figure for large-scale plex settings, designed and built around the ascertained websites. This was the main reason that guided us into needs of users, is to have the deep and ongoing support leveraging AI approaches to understand the structure of governance. In a PA or complex entity, services and of the existing website, and define the optimal IA by processes are interconnected and depend - to name just categorizing the existing content. a few factors - on the people sustaining them, the organizational models, the technological infrastructure, the operational practices, the available skills, the investments in reskill and upskill, human resource recruitment and management policies, the regulatory environment, and the financial situation. These are all mutually conditioning factors, and as the size of the institution grows, they grow more than proportionally, until they generate a system of constraints and cascading repercussions involving the entire institution. The human-centered design or redesign of a service impacts this system of interconnected

Statistical testing to assess large-scale website struc

ture The statistical analysis of the existing website starts by considering the website as a directed network of documents (nodes) connected through hyperlinks (edges). One example is represented in Figure 1, where the main structure of the studenti.unige.it (mid-2017) is depicted. By exploiting network analytics [ 9 ], we explored the distributions of the in-degree and out-degree, that are the number of in-coming links, and the number of out-going links, respectively. We argue that the scale-free property, that characterizes the World-Wide-Web as a whole [ 10 ], is no longer evident for specific sub-categories of websites. Particularly, we defined a method that could be used to better characterize topological properties deriving from diferent generative principles: central or peripheral. The first category is typically characterized by a strong central control in the design and evolution of the IA and content generation. Conversely, the last the struggle typical of traditional content management systems to handle the ever-changing regulations, information overload, and new digital technologies that large organizations face [ 14 ]. The system highlights the importance of human-centered design throughout the content management process. It is designed to be user-friendly and easy to learn, even for non-technical users. This ensures that content creators can focus on creating highquality content, rather than struggling with the technology. This process resulted in the publication of a new set of federated websites whose structure and content were the result of the entire pipeline just described. Figure 4 illustrates its hierarchical structure. 3.4. Assessing results through data visualization category is completely user-guided and its evolution is likely to be random [ 11 ]. This method may be used to trace and monitor the evolution over time of the website content also according to the editorial model in use: a few people that are allowed to write anywhere in the website and tightly control the structure or a multitude of contributors that are allowed to write based on collaborative editing and community moderation. The result on the UniGe website denoted a combination of central and peripheral editorial strategies that, over time, led to a chaotic arrangement, confirming the need for a profound redesign.

Topic Modeling to infer an optimal Information

Architecture We then proceeded by defining an AIdriven approach to define the optimal IA. Specifically, we exploited topic modeling methods [ 12, 13 ] to identify how many topics were discussed on the website and visualize how the pages often presented multiple unrelated topics, leading to a confusing UX. The result of such an experiment on studenti.unige.it is visualized in Figure 3, where the fuschia squares represent the topics and the blue dots represent the pages. Even at first glance, it is clear that many pages are linked by two or more topics, with a central cluster of pages connected to up to 5 topics.

To assess the overall usability of the newly designed website and the efectiveness of the entire procedure, we resorted to a set of UX tests conducted on a sample of 60 students divided into two groups ( = 22.7 ), with the purpose of comparing the usability of the corsi.unige.it website, designed with the methods above, and of studenti.unige.it, which historically UniGe uses to communicate with its students. Each user must answer three questions related to a course of study, navigating exclusively on one of the two sites. The questions were the following. Question A: Is there an exam to enroll in the 3.3. AI-based component management Business Administration BSc? What does it consist of? system Question B: When is the deadline for Erasmus+ application? Question C: Find where to ask for an internship in To implement a new strategy for content creation and car design as a MSc student in Design. management, we devised a system that exploits single The exercise was deemed successful if the subject corsourcing and AI methods to transform information into rectly answered the question at the end of the search. structured and reusable data, making it easier to create, Researchers evaluated the efectiveness of the site by maintain, and update content across multiple channels measuring the number of clicks and the time taken to and user profiles. For example, a single piece of informa- complete the exercise, with each question allotted a maxtion can be automatically tailored to the needs of diferent imum response time of 600 seconds. There were three audiences, such as students, faculty, and staf. The sys- potential outcomes: correct, partially correct, or incortem also integrates with machine learning methods for rect answers. The vertical bubble chart in Figure 5 shows image recognition and automatic translation, further re- the result of the UX test. Each circle corresponds to a ducing the burden on human editors. This overcomes

of implementing the newly redesigned system in the Time (s) university procedures. Thus, human-centered design ap#SuCclciecksss Score proaches and codesign and shared prototyping activities Success Rate have proved invaluable allies in gaining consensus, incorporating the knowledge and skills of all stakeholders into Table 1 the design process, and disseminating the culture of UX. Median time, median number of clicks, median success score, However, splitting the design-driven digital innovation and global success rate between the two websites over the project into autonomous modules was necessary three questions. This behavior, as predicted by [ 15 ], is to be expected when working within complex organizations to step up in the UX maturity model, particularly if the starting point is user and is arranged along the vertical axis according to the bottom of the ladder, i.e. absent or limited UX. In this the number of clicks. The diameter is proportional to case, besides working on technological improvements, the time required to perform the exercise while the color the institution must focus on a profound cultural change represents its success (correct answer, partially correct, that supports UX knowledge and data awareness. incorrect).

Table 1 shows how on average users performance on studenti.unige.it was significantly worse than on 4. A new challenge: PhD corsi.unige.it. In particular, in the case of corsi.unige.it, Programme at PoliMi three out of four users answer correctly with just a few clicks and in a short time, with a success of 75 percent, while less than one in ten users responds correctly using studenti.unige.it. Although our experience was successful in achieving the objective we set in the beginning, this was not without hiccups and obstacles. In particular, a strong resistance to change was observed at the moment Our successful experience in UniGe resonated across several national outlets and was presented in several news channels and conferences [ 14, 16 ] and culminated in winning the ForumPA award for best innovator [ 17 ]. The exposure we received from these initiatives allowed us to get in touch with other realities that were facing similar issues as the ones we faced in UniGe. In this line, we were able to begin a tight-knit collaboration with the Department of Design at Politecnico di Milano (PoliMi), where the Design PhD Programme at PoliMi was facing the problem of redesigning their website. The PhD Programme in Design at PoliMi is the largest PhD design course in Italy, with almost 90 PhD students enrolled.

Their goal was to devise a system that could allow for an optimal presentation of the research activity carried on by the PhD alumni and candidates as well as a website that could describe procedures to potential new students (admission procedure, courses requirements, etc.) and stakeholders. Our involvement since the very beginning of the redesign process, allowed us to adopt the methodology defined for UniGe. Together, we identified the major pain points from their old websites, mainly consisting of a lack of automation, an inactive homepage, and a content strategy that did not leverage single-sourcing, user profiling, or structured information. The result was a set of websites that penalized the research eforts. Applying our methodology allowed us to identify the root of these ineficiencies. In particular, PhD procedures lack a connection between the legacy data, processes and the website content. Also, in research dissemination pages, the existing data structure does not account for the interactions among researchers and therefore it is dificult to keep up-to-date and coherent. Currently, the project is focusing on designing a data-driven system which may enhance the usability of the websites through refining the quality of the underlying information structure. A primary objective is to establish an architecture capable of robust automation. This architecture aims to convert natural language and simple information about researchers’ activity in structured data. By exploiting legacy data in a seamless flux, the system reduces maintenance efort at the bare minimum and keeps data in sync and up to date.

Also, the system will behave by considering research as the result of heterogeneous networks of people and topics. In doing so, the data produced by the research eforts become structured and easily reusable across diferent touchpoints.

5. Discussion and Conclusion

Our experience with two large scale universities, suggests that Italian academia still lacks concrete strategies and methods to tackle the ever increasing amount of information a PA faces today. Particularly in the context of web redesign, we defined a methodology that goes beyond a shallow visual redesign in favor of a new methodology where existing data is first used to guide the definition of an optimal IA and then structured to feed the touchpoints based on single-sourcing, interoperability, and user profiled approach. Our methodology exploits design thinking principles, User-Centred Design methods, agile programming, prototyping and innovators (young fearless developers and designers) to define a new way of thinking about information and how to distribute it across complex organizations. The result is a system that is able to govern a multitude of diferent and interconnected websites thanks to AI, Natural Language Processing and data management principles.

Academia represents a unique type of PA, tasked with the crucial responsibility of not only accumulating vast knowledge but also efectively sharing it with the broader public. However, like many PAs, academia tends to exhibit a conservative stance toward digital advancements, often resisting change and clinging to outdated methods. Rather than embracing true innovation, there’s a tendency to equate progress with simply digitizing existing processes. This approach typically prioritizes documents over recognizing the central importance of data, which should serve as the foundation for all operations, particularly within sprawling institutions characterized by numerous interconnected yet autonomous departments.

Acknowledgments

A. Barla is part of the RAISE Innovation Ecosystem funded by the Recovery and Resilience Plan (NRRP) (ECS00000035)

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