Evolution of University CTO Offices in the age of hyper-automation of Higher Education
The CTO’s Office manages Enterprise Architecture, defining the overall vision and strategy for the University’s IT. It fosters collaboration with diverse stakeholders to align technology initiatives with the University’s mission, ensuring the adoption of the most effective technological direction. This is achieved through a three-pronged approach focusing on people, processes, and portfolio management. The CTO office should assess the maturity of technology trends in alignment with the institution’s current strategy, and utilize combinations of these trends to inform and navigate digital investments aimed at achieving university objectives. It needs to secure leadership endorsement by demonstrating how the university strategy, risk management, and potential consequences of inaction regarding these trends align with: enhancing the evolving student experience, adapting to new workforce or employment or entrepreneurial trends, streamlining operational efficiency and establishing a flexible technology infrastructure. Also, before selecting a hyperautomation technology, collaborate with stakeholders to define precise business objectives by: assessing the current situation, identifying opportunities for redesigning business processes and predicting the impact on business value resulting from automation.
#: Facilitate the achievement of the University’s mission and business objectives by establishing robust technology governance models and decision-making frameworks aligned with both University and IT strategies. Evaluate the present condition of your institution by examining the alignment between institutional strategy, priorities, and the existing IT and talent ecosystem. The primary critical objective pursued through investments in digital technology was to “achieve excellence in learning, teaching and research experience”, “enhance operating margins” and “enable a rise in revenue” amidst forecasted increase of IT budget, coinciding with inflationary pressures affecting the expenses. Digital strategies in higher education prioritize enriching the experiences of staff and students over solely pursuing financial gains or cost-saving objectives. Amid financial challenges, institutions will maintain their focus on budget allocations. Often perceived as a cost center, IT faces scrutiny for cost reduction, particularly when its alignment with the institutional mission is not clearly demonstrated.
#: Foster the adoption of shared services across University to enhance operational efficiency and reduce costs. Digital technology investments will incorporate the potential of AI to boost productivity and enhance the efficiency of institutional administration, teaching, and research. The evolution of technology towards secure, cloud-based environments empowers research, enhances connectivity, and offers greater flexibility.
By 2028, the proportion of higher education Chief Information Officers (CIOs) prioritizing enhanced operating margins as the primary digital technology investment goal is expected to increase to 65%, a significant rise from 32% in 2024.
#: Collaboratively develop the University IT strategy with the concerned stakeholders and groups, document the approach in white papers. Work closely with institutional leaders to integrate the business value of IT and its impact on outcome metrics into every new digital technology investment, highlighting both nonfinancial and financial benefits.
Hypothesis: The institution’s Student Information System (SIS) will evolve beyond being a single solution from one vendor, which is heavily customized and challenging to maintain. The next-generation SIS will be composed of a federation of core and point solutions integrated across various locations.
#: Strengthen the foundation of Enterprise Architecture (EA) through the use of recognized frameworks like TOGAF, ITSM, IT-CMF, DevOps, and Agile, providing guidance to key stakeholders such as the Technology Leadership Council (TLC) and Enterprise Architecture Committee (EAC).
#: Offer business , application, data and technology architecture services to other research and education units, assisting in modeling system architecture capabilities and provisioning environments to drive operational effectiveness and strategic alignment.
Organizational digital transformation and the implementation of new digital instructional methods are being considered as potential remedies for ongoing shortages of teachers, staff, and IT talent in the emerging technology sector. The integration of AI in higher education entails technical and organizational considerations, encompassing hardware, software, data management, personnel, security, and privacy. AI’s substantial processing demands and data storage needs pose affordability and accessibility challenges, especially in resource-limited settings. This may exacerbate shortages in qualified personnel and hinder training opportunities due to constrained hardware and infrastructure. These multifaceted issues underscore the necessity for comprehensive planning and resource allocation to ensure successful AI integration in higher education, as discussed further in the section on AI and sustainability.
#: Support business leaders in identifying and capitalizing on new opportunities, partnering with them to develop transformational models for achieving successful business outcomes. Assess the influence of generative AI on digital strategy by advising leadership on potential applications, risks, and lasting effects. Implement agile strategy and execution practices by ensuring effective communication of priorities, targeted exploration of emerging technologies, and emphasis on metrics that align with strategic objectives. Mitigate risk by maintaining a balanced approach, incorporating both AI pilots and governance measures alongside a broader portfolio of IT investments that align with current organizational requirements. How to Pilot Generative AI? How to Choose an Approach for Deploying Generative AI? Hype Cycle for Generative AI? Use-Cases & Perspectives: Generative AI for Education?
Shifts in demographic projections and their potential effects on enrollment are introducing uncertainty to institutions and posing challenges to traditional delivery models, particularly those dependent on revenue from international students. In response to the trend of lifelong learning, new delivery models are emerging, characterized by an increase in fully online programs and flexible degree pathways. The transition to hybrid models will be gradual and will demand ongoing institutional commitment. While certain institutions have deliberately opted for either a fully campus-based or online approach, many others have not yet defined a clear stance on learning, teaching, and operational methods. Institutions are still in the process of defining the concept of hybrid learning, using different terms like “hyflex,” “blended learning,” and “online learning” in their strategies and plans. By 2027, a majority of higher education institutions, specifically 60%, are projected to embrace a hybrid operating model that integrates both physical and virtual capacities in order to fulfill their institutional mission.
#: Engage with peer institutions to introduce and advocate for significant technical initiatives through participation in consortia. Boost the university’s ability to swiftly develop new programs and delivery methods by forging partnerships with external providers offering credentials and short courses, while also collaborating closely with internal registrar and academic affairs teams.
Higher Education and Research Institutes – Enterprise Architecture Framework (Based on HERM)
I: Strategy, Planning and Governance
1: Strategy : Strategic Vision Development, Strategic Plan Management, Business Horizon Scanning, Strategic Plan Development, Strategic ReportingCorporate Performance Management
2: Planning: Business Capabilities and Benefits Management , Programme & Project Management, Organisational Design, Change Portfolio Management, Enterprise Architecture, Quality Management
Monitor the business value derived from automation by evaluating its impact on aspects such as: revenue growth, cost reduction, avoidance of expenses, error minimization, optimization of resources, enhanced compliance and risk mitigation, and improved satisfaction among students, faculty, and employees.
3: Governance: Risk MgtRisk Management, Compliance Monitoring & Reporting, Policy & Regulation Management, Internal Audit & Reporting, Business Continuity Management
Use Case Prism: Higher education institutions (HEIs) have implemented protocols for AI transparency and accountability. This entails providing clear insights into AI utilization, data origins, and decision-making procedures. For instance, the Australian National University initiated the Autonomy, Agency, and Assurance Innovation Institute (3A Institute) to promote responsible AI advancement. The institute has crafted frameworks and standards for AI accountability, encompassing ethical facets, safety measures, and human-centric values in AI systems (Australian National University, no date). Such transparency fosters trust among students, faculty, and the broader community, ensuring the conscientious deployment of AI in educational and research settings.
Use Case Prism: Ensuring academic integrity amidst the proliferation of AI tools is imperative for higher education institutions (HEIs). HEIs must devise policies to uphold fair and ethical academic standards, encompassing plagiarism prevention, AI-generated content detection, and judicious use of AI in student evaluations. Tec de Monterrey (Mexico) exemplifies this approach, issuing directives on ChatGPT usage, fostering discussions on its ethical application, and outlining protocols for misuse. Similarly, Abu Dhabi University (UAE) has provided guidelines, faculty training, and plans for integrating GPT-4 into university systems to uphold academic integrity.
Use Case Prism: Ensuring research ethics amidst AI integration is crucial. HEIs must establish protocols to ensure ethical AI use in research, covering privacy, data security, bias mitigation, and transparency. This upholds ethical standards and ensures AI-driven research aligns with ethical principles. Institutions like the University of Helsinki (Finland) exemplify proactive measures by forming AI ethics committees to oversee ethical implications. These committees, comprising multidisciplinary experts, evaluate AI projects, enforce ethical guidelines, and advocate responsible AI practices (University of Helsinki, no date). Such initiatives are pivotal in fostering ethical AI integration within research and teaching contexts.
II: Teaching and Learning Capabilities
1: Student Enrolment & Admission Management 2: Academic Administration 3: Curriculum Management 4: Student Attraction & Recruitment 5: Alumni Engagement 6: Student Completion & Graduation 7: Student Administration 8: Student Support & Wellbeing Management 9: Teaching & Learning Delivery 10: Student Assessment
1: Student Enrolment & Admission Management: Programme Enrolment , Module Selection Management, Student Induction Management, Student Application Management, Offer, Acceptance & Quota Management
Encourage investment in the overall student experience by actively collaborating with students, faculty, and professional services to identify and implement improvements that enhance educational pathways. AI-based applications are now aiding prospective students in admission procedures, akin to how chatbots assist with administrative tasks and learning. These applications streamline complex admission processes with admission chatbots. Users appreciate the anonymity AI provides, enabling them to ask questions freely.
Use-Case Prism: The Higher Colleges of Technology (HCT) in the UAE implemented an AI-based Intelligent Course Advisor to assist students in making informed decisions about elective courses. By leveraging accurate data, the recommendation engine matches student interests and capabilities with suitable elective choices, resulting in improved academic advising quality and on-time graduation rates for a larger number of students.
Use-Case Prism: For instance, the University of Cape Town employs a chatbot for admission and orientation, addressing topics like connectivity challenges and financial aid. Queries beyond the chatbot’s abilities are directed to live agents for assistance.These algorithms excel at determining a student’s affordability, potentially boosting enrollment rates. However, they lack provisions for unforeseen expenses or emergencies.
Use-Case Prism: Predictive algorithms are employed to identify at-risk incoming students by analyzing factors such as prior academic performance from the same high schools. At an undisclosed US university, a 20% rise in enrollment occurred after an AI system flagged under-prepared students and provided additional preparatory measures like summer courses, tutoring, specialized classes, and counseling. Similarly, Georgia State University in the USA used these indicators to offer a seven-week summer session to select students, resulting in a 90% success rate in completing their first year.
2: Academic Administration
2: Academic Administration : Academic Policy & Regulation Management, Academic Year Scheduling , Timetabling Management,
Use Case Prism: The University of Canberra in Australia has introduced AI chatbots to assist with IT inquiries for students and HR queries for staff. Similarly, Deakin University offers a student application providing personalized information such as upcoming deadlines, voice-activated reminders, library bookings, and reading suggestions based on enrolled courses, as well as campus event updates. In Peru, Continental University has deployed ContiBot, a chatbot serving over 60,000 students across four campuses, delivering real-time academic information on schedules, grades, and other relevant data.
3: Curriculum Management
3: Curriculum Management : Curriculum Retirement Management, Curriculum Design , Curriculum Change Management, Professional Accreditation , Professional Learning (Staff) , Curriculum & Resource Development, Curriculum Performance Management
Generative AI possesses the capability to produce personalized learning resources, curriculum materials, and instructional content customized to the unique needs and preferences of educators. Generative AI can support educators in the development and maintenance of curricula by automating the production of diverse learning materials, including textbooks, lecture notes, assignments, quizzes, multiple-choice questions (MCQs), and test papers, customized to the requirements of individual courses and educational goals. Leveraging AI in higher education enables educators to generate a wide range of questions spanning various difficulty levels, learning objectives, and subject matters. Employing Generative AI in higher education empowers educators to efficiently condense complex information into succinct summaries. Leveraging advanced Natural Language Processing (NLP) capabilities, Generative AI can thoroughly analyze and comprehend lengthy texts, extracting key concepts and summarizing pertinent details with precision. Consider a scenario where a professor needs to condense a dense, 50-page document for an upcoming lecture. Instead of dedicating hours to manually distilling the information, the professor can leverage a Generative AI tool. Upon inputting the text, the Generative AI algorithms meticulously analyze the document, discerning crucial events, figures, and themes. Subsequently, the tool generates a succinct and coherent summary, seamlessly integratable into the lecture.
4: Student Attraction & Recruitment : Scholarship & Bursary Management, Prospective Student Engagement , International Student Recruitment , Domestic Student Recruitment , Student Recruitment Agent Management
As the perceived value of a higher education degree undergoes examination, students are increasingly seeking tangible returns on their investment of time and money. While global instability and economic downturns traditionally push students towards higher education, the widening skills gap and volatile job market present challenges in attracting new students to the industry. In today’s intricate and competitive landscape, universities face numerous challenges. University leaders rely on CIOs to implement transformative initiatives that address sector-specific concerns like student recruitment, retention, and academic achievement.
Alumni Engagement, Student Completion & Graduation , Student Administration
5: Alumni Engagement : Alumni Relationship Management , Alumni Event & Campaign Management, Benefactor Management
6: Student Completion & Graduation: Graduation Event Management, Graduation Record Certificate Management, Non-Academic Achievement Management, Graduation Eligibility Management
Blockchain Credentials: Blockchain technology enables secure and tamper-proof recording and verification of academic credentials, such as degrees, certificates, and transcripts. By issuing credentials on a blockchain, institutions ensure their authenticity and facilitate seamless verification by employers and other institutions, reducing the risk of credential fraud and simplifying the credentialing process.
7: Student Administration : Enrolment Status Management, Student Record & Details Management, Programme Transfer Management, Student Mobility , Student Exceptional Factors Misconduct / Appeal Management, Student Financial Administration
8: Student Support & Wellbeing Management
8: Student Support & Wellbeing Management : Career & Employability Engagement Mgt , Academic Skills Development, Academic Advice Management , Student Financial Advice, Student Engagement & Retention , Housing Advice , Personal Tutor Provision , Student Health & Wellbeing , Disability Support Management, Personal Learning Management
Generative AI platforms offer round-the-clock personalized support, providing timely interventions and fostering interaction tailored to individual wellness requirements. By leveraging AI, virtual communities and engagement circles can be enhanced, serving as valuable supplements to face-to-face interactions, particularly in situations of illness or geographic isolation.
AI can aid recent graduates in their job search by offering various support services, such as resume building, skill matching with job requirements, and salary negotiation insights. For instance, AI can enhance resumes based on job specifications and highlight key details from resumes and LinkedIn profiles to optimize job applications.
Use Case Prism: AI has found application in extracurricular training, notably in activities like mock job interviews. Duke University in the USA has embraced AI-mediated services for this purpose. These services involve analyzing video recordings of participants and providing feedback on various aspects such as vocal delivery, keyword usage, and non-verbal communication. Such feedback proves beneficial for all types of future interviews, especially those conducted virtually, where AI systems similar to those used in training exercises may analyze or directly conduct the interviews.
Use Case Prism: Despite the widespread adoption of predictive AI-driven early warning systems, students’ perceptions of such tools are often overlooked. A study by Universitat Oberta de Catalunya (Spain) evaluated students’ experiences with their university’s predictive system, which forecasts course failure risk using past academic data, represented by a traffic light system (green, amber, red). Surprisingly, students with high initial technology expectations showed decreased acceptance post-use. This highlights the need for improved student support and training, or a gradual introduction of advanced technologies to ensure user adaptation
9: Teaching & Learning Delivery
9: Teaching & Learning Delivery : Presence Based Teaching, Non Presence Based Teaching, Teaching & Learning Content Management, Student Placement Management (External Programs)
By the year 2028, more than 70% of educational materials, including teaching resources, research outputs, and student-generated content across all educational levels, will be created with assistance from generative artificial intelligence. Universities that enhance their processes and utilize data to swiftly adjust curriculum and introduce new programs will gain a competitive edge compared to those resistant to change.
The evolution of the classroom refers to the ongoing changes in educational environments, instructional methods, and learning technologies. This evolution encompasses shifts in physical classroom design, teaching practices, and the integration of digital tools and resources to enhance the learning experience. It also includes adaptations in pedagogy to meet the needs of diverse learners and prepare students for the demands of the modern world. Overall, the evolution of the classroom reflects investments to create dynamic, engaging, and student-centered learning environments that foster critical thinking, collaboration, and lifelong learning skills. Typically, these investments have taken the form of technologies to enable: lecture capture, synchronous video streaming and collaboration, fixed-focus cameras, evolving to the use of classroom cameras to follow and capture video of instructors and sometimes students in the class, enhanced audio, including beam-forming microphones in the classroom to capture student participation in the room and share it with remote participants and knowledge sharing via digital whiteboards and document cameras.
“LXP” stands for “Learning Experience Platform.” LXPs are solutions created to promote and facilitate learner-driven exploration of training content and selection of learning materials. A Learning Experience Platform (LXP), also referred to as a peer learning experience platform, consolidates both internal and external learning resources. It employs artificial intelligence (AI) and machine learning (ML) to analyze learning data, offering users a tailored, intuitive experience. Typically delivered via Software as a Service (SaaS), LXPs aim to enrich individual learning interactions and engagement by: personalizing learning experiences, curating content, providing AI-driven recommendations and training, offering a gamified user experience and expanding the breadth of available content. Key functions of a Learning Experience Platform (LXP) include: Tailoring the learning journey: LXPs utilize artificial intelligence (AI) and machine learning to personalize the learning experience for each learner, offering content suggestions based on their interests, ambitions, and progress. Facilitating self-guided learning: LXPs empower learners to take control of their learning by allowing them to choose what, when, and how they want to learn. Encouraging teamwork: LXPs promote collaboration among learners by providing platforms for idea sharing, questioning, and feedback, fostering a sense of community. Advocating continuous learning: LXPs support ongoing learning by enabling learners to access educational content anytime, anywhere, and on any device. Key features of an LXP include: Personalization: LXPs leverage AI and machine learning to customize the learning experience for each learner, suggesting content based on their preferences and progress. Self-guided learning: LXPs empower learners to direct their own learning journey, giving them control over their learning process. Collaboration: LXPs facilitate collaboration among learners, allowing them to share ideas, ask questions, and provide feedback to one another. Continuous learning: LXPs promote continual learning by providing access to educational content at any time and from any location. Content curation: LXPs curate content from various sources, both internal and external, to help learners find relevant and engaging material. Social learning: LXPs enable social learning by providing tools for learners to connect with each other and share knowledge. Preference and behavior analytics: LXPs collect data on learner engagement, progression, and performance, which can be used to improve the design and delivery of learning content. As the LXP market evolves, we can expect to see the introduction of additional innovative features and functionalities.
Benefits of an LXP for enterprise training include: Maximizing individual interests and talents: LXPs empower learners to explore content based on their own interests and training needs, leading to highly motivated learning and the discovery of unique potentials, ultimately driving organizational improvement. Heightened engagement: LXPs enhance learner engagement by providing personalized and interactive learning experiences. Better learning outcomes: LXPs improve learning outcomes by offering access to a wide range of content and encouraging learners to direct their own learning. Cost reduction: LXPs reduce costs by decreasing the need for instructor-led training and offering a more efficient training delivery method. Improved compliance: LXPs enhance compliance by monitoring learner progress and ensuring training obligations are met. To maximize the impact of an LXP, learners can: Discover content aligned with interests and objectives: LXPs suggest content based on previous learning activities, personal interests, and goals. Monitor progress and maintain motivation: LXPs track progress and provide feedback to keep learners motivated. Collaborate with fellow learners: LXPs facilitate collaboration on projects, idea exchange, and inquiries. Connect with subject matter experts: LXPs help learners discover subject matter experts who can address questions and offer guidance.
LXPs typically offer learners broader access to a variety of formal and informal learning content beyond what’s available in traditional Learning Management Systems (LMS). Acting as content aggregators, LXPs host material from various internal and external sources, enabling learners to explore a wide range of resources, including blog posts, articles, videos, podcasts, and e-learning courses. Through AI-driven personalized recommendations, users can discover relevant content, including third-party resources from the internet, to develop diverse skills. The platform’s course aggregation feature provides access to different learning modalities, such as synchronous, asynchronous, self-paced, live instructor-led, or virtual instructor-led courses. Providing LXPs can aid universities in appealing to nontraditional learners by enhancing the learning experience, fostering personalized engagement, and cultivating skills that align with the demands of the workforce.
Online Learning Platforms: Emerging technologies have revolutionized the delivery of education through online learning platforms. These platforms offer a wide range of courses, including massive open online courses (MOOCs), allowing students to access educational content from anywhere with an internet connection. This flexibility has increased access to education for learners worldwide, including those in remote areas or with busy schedules.
Generative AI tools possess the capability to create and organize course materials, aiding educators in crafting personalized learning resources, quizzes, and lesson plans with greater efficiency. This enhancement in productivity allows educators to allocate more time towards enhancing their teaching techniques and actively engaging with students. Content generated by Generative AI has the potential to expedite the creation of captivating materials for both students and faculty.
Additionally, it allows assets to adapt to various global settings and can be disseminated in multiple languages. Investments from vendors and venture capital have resulted in a surge of Generative AI products, which are now integrated directly into productivity tools for tasks such as content creation, research assistance, and presentation development. Faculty members are increasingly investigating the substantial capabilities of Generative AI tools to generate images, presentations, videos, and curricula, despite ongoing unresolved copyright concerns. These tools are emerging within current productivity tools and educational platforms, including learning management systems, as well as from new providers of Generative AI products. As GenAI tools become ingrained in the education sector, concerns about the quality and validity of content may arise due to rapid growth. In the short run, critical thinking and insight will be crucial for maintaining institutional credibility amidst the proliferation of GenAI-generated content in teaching and research.
There are various APIs that offer valuable functionalities for higher education institutions: Tagger: Automatically tags content with relevant keywords, creates custom taxonomies, performs deep text analysis, and integrates seamlessly with content management systems and search engines. VideoSkimmer: Enables rapid skimming through videos, generates accurate transcripts, extracts keywords, provides precise video summaries, and handles long videos asynchronously. Translator: Facilitates language translation with automatic source language detection, customizable translations, support for various file formats, and real-time translation processing. Transcriber: Efficiently transcribes audio content into text, supports various audio formats, allows customization of transcriptions, handles large volumes of audio, and provides timestamps for spoken words. Summarizer: Generates concise text summaries, allows customization of length and type of information, supports various text formats, and processes large amounts of text content. QuestionGenerator: Automatically creates multiple-choice, open-ended, and true/false questions tailored to specific needs, processes diverse data types, and supports various file formats. AccessibilityChecker: Identifies accessibility gaps in educational content, ensures compliance with WCAG standards, generates Voluntary Product Accessibility Templates (VPAT), and enhances content accessibility without manual testing
Adaptive Learning : Adaptive learning systems use data analytics and artificial intelligence (AI) to personalize the learning experience for each student. These systems analyze students’ learning patterns, preferences, and performance to provide tailored content, pacing, and support. By adapting to individual needs, adaptive learning technologies enhance student engagement and improve learning outcomes. There are certification programs are increasingly available through secondary education systems, either integrated into existing classes, offered via specialized programs, or indirectly promoted to students who wish to acquire these skills independently. The surge in enthusiasm and expansion of AI and GenAI technologies are expected to drive the need for job-specific skills among prospective employees, requiring the capability to swiftly update these skills in response to the rapid evolution of these technologies.
In the coming years, personalized learning powered by GenAI is expected to become commonplace in education, rather than a rarity. AI systems will not only assist in adaptive learning but also forecast learning results, predict challenges students may face, and propose proactive remedies. AI will grant us access to a diverse range of exercises, case studies, and learning materials precisely adjusted to fundamental knowledge. Furthermore, AI will analyze different metrics, such as student engagement and emotional reactions, facilitating the creation of individualized educational experiences tailored to each learner’s specific needs and goals.
Virtual and Augmented Reality (VR/AR): VR and AR technologies create immersive learning experiences that simulate real-world environments or add virtual elements to the physical world. In higher education, VR/AR applications are used for virtual laboratories, field trips, simulations, and interactive visualizations, enhancing student understanding and engagement in complex subjects like science, engineering, and medicine. There is a shifting perspective on academic integrity and assessment, where educators are beginning to assess the learning process as much as the final outcome. Demonstrating comprehension through explanation, discussion, and evidence is also gaining importance. Interest is growing in the creation of AI-driven avatars with behaviors guided by GenAI, fueling the advancement of virtual reality (VR) and augmented reality (AR) academic simulations.
AI-based platforms offer the potential to enhance argument formation and contextual learning by simulating discussions. For instance, learners could engage with virtual historical figures like Robespierre, Socrates, or Locke to deepen their understanding of topics like the French Revolution, logic, truth, or classic liberalism. Additionally, when combined with XR/VR technology, learners can immerse themselves in historical scenarios to foster critical thinking and gain firsthand perspectives. The integration of generative AI in these contexts has the capacity to significantly elevate critical thinking and analysis skills beyond current levels.
Use-Case Prism:Imperial acknowledged that students encounter few life-threatening emergencies during their training but must still be thoroughly prepared to handle such situations upon graduation. The simulation provided effective and scalable learning, being reused annually.
Artificial Intelligence and Machine Learning: AI and machine learning technologies are transforming various aspects of higher education, including student admissions, personalized tutoring, predictive analytics, and administrative tasks. AI-powered chatbots provide instant support to students, virtual assistants help instructors with grading and course management, and predictive analytics identify at-risk students early for intervention.
Use Case Prism: AI facilitates customized learning in Biotechnology and language acquisition fields, enhancing efficiency and performance especially in a multi-disciplinary domains. For example, Japanese students using AI for English learning outperforming peers confirms AI’s efficacy. However, AI’s skill application varies significantly, emphasizing the need to comprehend its nuanced use across diverse educational settings.
Artificial Intelligence and Machine Learning: AI and machine learning technologies are transforming various aspects of higher education, including student admissions, personalized tutoring, predictive analytics, and administrative tasks. AI-powered chatbots provide instant support to students, virtual assistants help instructors with grading and course management, and predictive analytics identify at-risk students early for intervention.
Use Case Prism: AI facilitates customized learning in Biotechnology and language acquisition fields, enhancing efficiency and performance especially in a multi-disciplinary domains. For example, Japanese students using AI for English learning outperforming peers confirms AI’s efficacy. However, AI’s skill application varies significantly, emphasizing the need to comprehend its nuanced use across diverse educational settings.
Remote Collaboration Tools: Concurrently, there is a rapid increase in staff and student expectations for user-friendly, personalized access to content and collaboration tools. This trend urges universities to leverage both existing and emerging technologies to innovate their learning, teaching, and research strategies. Remote collaboration tools, such as video conferencing, collaborative document editing, and virtual whiteboards, have become essential for online and hybrid learning environments. These tools enable synchronous and asynchronous communication, collaboration, and group work among students and instructors, bridging geographical barriers and facilitating active learning experiences.
Generative AI models excel at swiftly and precisely translating text from one language to another. Additionally, they can generate alternative formats like audio, braille, or simplified language. These translation capabilities simplify the creation of multilingual learning materials and accommodate students with visual impairments, dyslexia, cognitive challenges, or diverse linguistic backgrounds. Furthermore, educators can harness Generative AI for automated transcription and captioning. By leveraging pre-trained language models, they can initiate live transcription, closed captioning, and transcription in various formats.
Furthermore, AI tools can automate content sharing across multiple platforms and personalize email marketing campaigns to ensure the timely delivery of relevant content to the appropriate audience. Additionally, AI aids in the creation of visually appealing representations of research data, enhancing audience understanding and engagement.
Use-case Prism: One example of a university using AI transcription tools in online calls or conferences is Stanford University. They utilize AI-powered transcription services to provide real-time captioning and note-taking during virtual meetings, lectures, and events. This technology helps ensure accessibility for all participants and provides accurate records of discussions that can be distributed afterward.
Gamification and Serious Games: Gamification techniques and serious games integrate game elements, such as competition, rewards, and storytelling, into educational activities to increase motivation, engagement, and retention. Gamified learning platforms, educational apps, and simulations make learning more interactive, enjoyable, and effective, especially for digital-native generations. Incorporating Generative AI into higher education empowers educators to create virtual labs and simulations with unparalleled ease and sophistication. This integration facilitates the automatic generation of realistic 3D environments, interactive scenarios, and dynamic simulations that accurately replicate real-world phenomena.
Use Case Prism: The Wharton School at the University of Pennsylvania offers immersive alternate reality courses, facilitated by Wharton Interactive. These courses provide personalized, game-based experiences with tailored feedback, resulting in improved knowledge retention. Currently, over 200 educators from 95 countries utilize these courses.
10: Student Assessment: Assessment Delivery,. Student Results Management, Assessment Marking & Feedback , Assessment Administration
Generative AI: Generative AI, a subset of machine learning, learns from input samples to produce new content. Examples include ChatGPT from OpenAI and Bard from Google, both trained on extensive text data to generate human-like text responses. GenAI software, includes text generators, is founded on large language models (LLMs) like Generative Pre-trained Transformer (GPT). LLMs, a subset of natural language processing (NLP), specialize in language-related tasks. GenAI software is capable of generating text, audio, or image-based responses to inquiries, encompassing complex tasks such as summarizing research papers, translating languages, and generating creative content like emails, blog posts, news articles, and scientific papers. These responses often closely resemble, and sometimes even mirror, human writing and language.
Institutions were earlier implementing policies that discourage and possibly penalize the submission of assessments entirely generated by Generative AI. However, there is also an acknowledgment of the necessity to cultivate risk awareness and AI literacy among students, preparing them for professions where Generative AI tools will be prevalent. Educators are shifting their perspectives on student utilization of Generative AI. Initially focused on detecting plagiarism and cheating, educators now promote responsible use of Generative AI among students. They aim to now raise the awareness and literacy level of these tools and foster reflective practices to enhance critical thinking skills.
Educators now have the capability to utilize ChatGPT for expedited grading of assignments, delivering feedback, organizing classes, maintaining student records, addressing student inquiries, and supplying supplementary learning materials as needed. Automated assessment, grading, feedback, and translation tools powered by artificial intelligence (AI) are merging to support adaptive learning methods and improve the student learning journey. The growing involvement of students with GenAI, coupled with the emergence of tools that conceal AI content detection, will hasten the advancement of plagiarism detection mechanisms in the near future. Over time, there’s an expected transition from assessments solely reliant on information to a broader approach emphasizing knowledge and inquiry.
Use Case Prism: Grammarly, a tool for correcting spelling and grammar, is widely used by students for academic assignments, with 72% reported to use it weekly according to a 2012 survey. While universities may recommend Grammarly, students should be cautious when submitting work to plagiarism checkers like Turnitin. Turnitin’s AI detector can identify content generated by AI tools, potentially leading to plagiarism accusations based on similarity scores. Faculty members at West Texas A&M University have three choices regarding student use of generative AI. They can opt for a total ban, allow it under certain circumstances, or permit its use with appropriate attribution.
Data Analytics and Learning Analytics: Data analytics and learning analytics tools analyze vast amounts of educational data, including student performance, behavior, and engagement metrics. These insights help institutions identify trends, measure learning outcomes, and make data-driven decisions to improve teaching methods, curriculum design, and student support services.
Use-case Prism: AI serves a vital function in recognizing students at risk of dropping out by assessing their profiles for vulnerability indicators. This empowers higher education institutions (HEIs) to proactively intervene and prevent dropout. Through AI analysis of aggregated data, HEIs can identify early academic underperformance linked to higher dropout probabilities. For instance, Pontificia Universidad Javeriana de Cali in Colombia achieved 93% accuracy in identifying such correlations using AI-driven analysis of aggregated data.
User-Case Prism: Analyzing data such as student engagement logs in online learning environments can guide interventions aimed at lowering dropout rates and boosting retention rates in higher education institutions (HEIs). These insights can prompt early interventions by academic advisors. Although AI assists in gathering and analyzing students’ behavioral patterns, faculty and staff bear the responsibility of implementing tailored interventions, especially in student affairs. For example, the University of Trás-os-Montes e Alto Douro in Portugal launched the EDU.IA project to enhance tutoring activities through the application of data analytics and AI. The tutoring program employs predictive algorithms to gauge the probability of individual student dropout, allowing proactive planning and support for those identified as at risk. Historical academic records spanning fifteen years are compiled in a data warehouse, feeding inference algorithms that predict future academic outcomes based on current and past student grades. HEIs, such as the University of Canterbury in New Zealand, utilize these predictive signals to initiate early interventions by academic advisors.
III: Research Capabilities
1: Research Opportunity & Planning 2: Research Training and Delivery 3: Research Publications & Impact 4: Research Administration and Improvement
1: Research Opportunity & Planning 2: Research Training and Delivery 3: Research Publications & Impact 4: Research Administration and Improvement
1: Research Opportunity & Planning : Research Opportunity Analysis, Research Prioritisation, Collaborative Opportunity Management, Research Programme Development, Research Funding Identification, Research Funds Management
2: Research Training and Delivery: Researcher Training & Development, PGR Student Skills Development, Research PGR Supervisor Development, Output Management, Research Production, Research Dataset Management
Leveraging Generative AI in higher education can greatly support educators in their research pursuits. Equipped with trained Machine Learning (ML) models, educators can streamline literature reviews and data analyses. These models efficiently sift through extensive academic papers, books, and online resources to formulate hypotheses and propose potential research avenues. Generative AI also aids in crafting research proposals, abstracts, and even initial drafts of scholarly articles. Additionally, it visualizes data, generates graphs, and conducts statistical analyses, simplifying complex research tasks. Although Generative AI holds promise for accelerating research and idea development, concerns arise about generating inaccurate or misleading content and the appropriateness of altering established methodologies. It is essential to evaluate appropriate Generative AI models, acknowledge their use, and consistently validate research sources to maintain research integrity.
Use Case Prism: Researchers from Delft University of Technology, École Polytechnique Fédérale de Lausanne, and the German Aerospace Centre collaborated using ChatGPT-3 to co-design a robot for crop harvesting. They engaged in two phases: ideation with ChatGPT suggesting technical specifications, and human optimization and construction. The process facilitated interdisciplinary connections, enhancing accessibility to fields like robotics. However, there are risks of bias and oversimplification. The team emphasizes ethical and socially empowering AI use. This approach offers potential for interdisciplinary research but demands careful consideration of ethical implications.
3: Research Publications & Impact: Research Publication Management, Research Output Reporting, Manage Research Relationships, Commercialise Research Outcomes, Non-Commercial Research Impact Management
Once data collection wraps up, AI steps in to aid researchers during the writing phase. While some scholars report success with tools like ChatGPT for producing well-structured or standard abstracts, provided precise instructions, others note substantial drawbacks when relying on it for writing support. AI tools offer various potential applications during the drafting and dissemination stages of research. They can aid in error identification within manuscripts, detecting plagiarism, false statistical outcomes, or undisclosed data. Additionally, AI tools can enhance text coherence by recognizing similar-sounding paragraphs or sentences. Moreover, researchers can utilize AI-powered tools to streamline reference tracking and management, with some applications enabling instant reference generation from diverse sources.
AI tools facilitate translation between various languages, potentially enhancing equity by broadening access to knowledge produced in different languages. Additionally, these tools support researchers in publishing work in languages other than their primary working language (language multiplier imapct or effect). AI can streamline the sharing of research findings by identifying optimal posting times on social media platforms, maximizing their reach to relevant audiences.
Use Case Prism: The editors of the journal Accountability in Research proposed a policy in January 2023, allowing authors to use NLP systems like ChatGPT for generating content. However, authors must disclose and describe their use of these systems, taking full responsibility for factual and citation accuracy. These disclosures should be included in the Methodology section and references, and authors are provided with a template to submit generated text as supplementary material.
User Case Prism: Higher education institutions worldwide are actively contributing to the development of AI tools for language translation. For example, Kyrgyz Technical University supports a project for a Kyrgyz language voice assistant. Similarly, the University of Helsinki manages the OPUS project, compiling multilingual content for translation models and the Indian Institute of Technology Madras offers translation models for over 20 Indic languages.
4: Research Administration and Improvement: Research Programme Performance Management, Research Quality Management, Researcher Performance Management, Research Compliance Management, Research Infrastructure Management
Use-case Prism: RMIT University in Australia leveraged supercomputing to advance its research endeavors. Previously, researchers faced challenges in running computational-intensive simulations due to the technical expertise needed to establish cost-effective solutions. By partnering with Amazon Web Services (AWS) to create the RMIT and AWS Cloud Supercomputing Hub (RACE Hub), a cloud-based research support system, RMIT has facilitated digital innovation in research and fostered new partnerships between industry, government, and academia.
IV: Commercial Capabilities
1: Commercial Sourcing & Engagement 2: Commercial Delivery & Monitoring
1: Commercial Sourcing & Engagement: Commercial Opportunity Identification, Commercial Market Analysis, Commercial Opportunity Assessment, Commercial Partner Engagement, Commercial Partner Integration & Transition
2: Commercial Delivery & Monitoring: Commercial Activity Output Management, Commercial Activity Issue Management, Commercial Activity Exit Management, Commercial Contract Performance Management, Commercial Activity Reporting, Commercial Contingency Planning
V: Enabling Capabilities
1: Government, Public & Stakeholder Relationships 2: Promotions Management 3: Supporting Services 4: Human Resource Management 5: Information & Communication Technology Management 6: Library Management 7: Information Management 8: Legal Services 9: Facilities & Property Management 10: Finance Management 11: Accommodation Management
1: Government, Public & Stakeholder Relationships: Government Relationship Management, Industry Relationship Management, Other Tertiary Institution Relationship Management, Media Relations Management, Internal Stakeholder Relationship Management, Public Relationship Management
2: Promotions Management: Brand Management, Campaign Management, Event Management, Market Research, Marketing Management, Merchandising
3: Supporting Services: Food & Retail Management, Religious Support, Sport & Recreation Management, Venue Management, Child Care Management,Health Care Management, Printing Management, Internal Communications, Complaint & Compliment Management
Poor university experience affects recruitment, retention, and overall institutional achievement. Universities will more closely integrate every aspect of the student learning and support journey to provide a comprehensive experience that aligns with student expectations. This holistic approach is crucial in fostering a sense of community within the university.
4: Human Resource Management: Workforce Planning, Staff Recruitment, Talent Management, Remuneration & Entitlements Management, Workforce Relations Management, Staff Engagement, Occupational Health, Employee Performance Management, Training & Development, Workforce Reporting, Employee Support, Staff Record & Details Management, Staff Absence Management
5: Information & Communication Technology Management: Infrastructure Lifecycle Management, Application Lifecycle Management, ICT Service Support, Digital Communication Management, Identity & Access Management, High Performance Computing, End User Computing
SIS stands for Student Information System. It is a software application used by educational institutions to manage student-related data and information. SIS platforms typically include functionalities such as student enrollment, registration, grades, attendance tracking, scheduling, and academic records management. These systems play a crucial role in streamlining administrative processes, facilitating communication between students and faculty, and ensuring accurate and efficient management of student data throughout their academic journeyEnhancing the quality of teaching and learning remains a . key objective for many higher education institutions. Institutions are increasingly focused on gaining deeper insights into student needs and are developing new technological solutions to meet these needs.
Composable ERP refers to an approach in enterprise resource planning (ERP) where modular, interchangeable components are utilized to build a flexible and adaptable system tailored to specific business needs. Instead of relying on a monolithic ERP system, composable ERP allows organizations to select and integrate individual components or “building blocks” to create a customized solution. These components can include core ERP functionalities such as finance, human resources, and supply chain management, as well as specialized modules or third-party applications. Composable ERP aims to enhance agility, scalability, and innovation by enabling organizations to rapidly respond to changing business requirements and incorporate emerging technologies. Transforming ERP systems is vital for overall business transformation. Outdated administrative systems pose increasing technological and financial challenges. To ensure resilience and future readiness, universities and colleges must embrace an ERP approach that integrates evolving business needs with dynamic technology strategies. Composable ERP prioritizes value delivery, adapting to new technologies, mindsets, and practices. Understanding new business processes and merging strategy, practice, and tools is essential for achieving quantifiable benefits. The role of ERP applications is shifting towards enhancing enterprise capabilities across the institution. Composable ERP focuses on outcome-driven objectives, prioritizing flexibility, data centrality, and stakeholder engagement. Institutions are transitioning beyond traditional ERP solutions, crafting modern technology platforms that integrate legacy or new SIS alongside various digital capabilities.
Use-case Prism: At CQUniversity (CQU) in Australia, the focus was on enhancing the student digital journey experience. By consolidating over 50 separate systems, CQU created a personalized, real-time view of essential academic information for students. This approach allowed students to manage academic and administrative tasks promptly, resulting in improved satisfaction and overall experience.
Use-case Prism: Migrating to the cloud at Universitat Oberta de Catalunya (UOC), Barcelona. The UOC, a fully online university, recognized the challenge of supporting increased enrollments with a costly and inefficient data center. After a review of infrastructure, scope and project plans, successful migration to the cloud cut recurring costs, saved onpremises infrastructure costs, reduced complexity and enabled additional student enrollment growth.
6: Library Management: Library Collection Access Management, Library Collection Resource Management, Art/Museum Collection Management, Library Membership Management
Higher education institutions need to prioritize digital transformation of their learning models and streamline operations using cutting-edge technologies to provide cohesive experiences for both staff and students. Furthermore, they should explore innovative possibilities by incorporating advanced technologies like augmented or virtual reality to revolutionize educational approaches. These technologies can facilitate virtual experiments, virtual visits to historical sites, interactive case studies, or even virtual museum exhibitions.
Use-Case Prism: HEIs are incorporating AI into library services to enhance student support and resource management. This includes deploying online chatbots on library websites to address student inquiries and utilizing AI to analyze digital collections, identify topics and entities, add metadata, and facilitate non-textual searches. One example is the AI tool HAMLET (How About Machine Learning Enhancing Theses?), which employs machine learning to create experimental interfaces for MIT’s thesis collection.
7: Information Management: Information Search & Discovery, Information & Data Security Management, Information Collection Management, Copyrigh Management, Knowledge Management, Information & Data Management, Information Analytics, Records Management , Enterprise Content Management, Business & Operational Reporting
Since 2020, the higher education sector has experienced a significant rise in both the frequency and severity of cyberattacks. Limited security resources and the complexity of the continually evolving security solution market present challenges in adequately preparing for and responding to these threats and attacks. According to the Microsoft Security Intelligence site, the education sector ranks among the most impacted industries by threat activity.
Use-case Prism: Enhancing cybersecurity at the University of Westminster in London, UK involved gaining a comprehensive understanding of vulnerabilities across 7,000 on-premises, mobile, and cloud assets. Transitioning from reactive to proactive security approaches resulted in substantial reductions in vulnerabilities and provided timely insights, significantly accelerating response times.
8: Legal Services: Contract Management , Legal & Legislative Compliance, Dispute Resolution, Legal Advisory
9: Facilities & Property Management: Estate Development & Management, Campus Security, Space Utilisation, Property Maintenance, Environmental Management, Campus Parking, Health & Safety, Mail Management, Commercial Tenancy, Vehicle Management
Higher education institutions are under growing pressure to develop, implement, and uphold sustainability initiatives within their physical campuses. These initiatives often involve monitoring student presence and space utilization, minimizing carbon emissions by shutting down unused buildings during the day, and educating students about responsible consumption and recycling practices. The need for adaptable spaces will prompt universities to reassess their strategies concerning people, infrastructure, and technology. Achieving this will necessitate coordination across the university, a task that is frequently challenging. Investing in a well-equipped space that doesn’t align with the learning and teaching strategy would result in wasted resources.
Use-case Prism: The National University of Singapore (NUS) installed solar-powered Wi-Fi to enhance device connectivity across campus while aligning with sustainability objectives. This initiative replaced traditional power sources with wireless solar access points, resulting in environmental and social benefits, cost savings, and an improved experience for both staff and students.
10: Finance Management: Procurement & Purchasing Management, Budget Management, Treasury Management, Income Management, Insurance Management, Asset Management, Financial Reporting, Taxation Management, Expenditure Management, Supplier Management, Financial Advisory
Institutions face substantial societal pressure to cut costs and enhance, or in some instances demonstrate, the value of a degree. CIOs must show the financial advantages of digital technology investments, or they risk facing budget cuts for IT and a lack of support for new projects and initiatives. Institutions facing financial difficulties will seek to boost revenue by altering cost structures, expanding enrollment, and attracting additional research funding. The trend of institutions discontinuing programs is expected to become more widespread. To reduce unnecessary operating costs, there will be a heightened focus on sourcing, procuring, and managing efficient vendor relationships.
11: Accommodation Management: Accommodation Allocation, Accommodation Facilities Management, Accommodation Incident & Emergency Response, Accommodation Departure & Turnaround Management, Private Sector Housing Management
References and Suggested Readings
1: https://www.goskills.com/Resources/Technology-business-learning
2: https://www.goskills.com/Resources/learning-experience-platforms
3: https://www.tituslearning.com/what-is-a-learning-experience-platform-lxp/
4: https://joshbersin.com/2019/03/learning-experience-platform-lxp-market-grows-up-now-too-big-to-ignore/
5: https://www.imperial.ac.uk/news/246674/advancing-healthcare-education-clinical-practice-with/
6: https://virtualspeech.com/blog/vr-education-example-use-cases
7: https://www.emerald.com/insight/content/doi/10.1108/ACI-03-2022-0069/full/html
8: https://www.emerald.com/insight/content/doi/10.1108/ACI-03-2022-0069/full/html
9: https://www.ey.com/en_gl/insights/strategy/can-digital-approaches-help-improve-student-outcomes
10: https://www.bcg.com/publications/2021/investing-in-education-technology
11: https://www.elsevier.es/en-revista-journal-innovation-knowledge-376-articulo-evaluate-drivers-for-digital-transformation-S2444569X23000604
12: https://www.salesforce.org/wp-content/uploads/2022/07/edu-guide-higher-education-digital-marketing-maturity-assessment-070622.pdf
13: https://www.jisc.ac.uk/guides/digital-transformation-in-higher-education
14: https://link.springer.com/article/10.1007/s10639-021-10739-1
15: https://www.oecd.org/pisa/Evaluating-Global-Digital-Education-Student-Outcomes-Framework.pdf
16: https://www.cisco.com/c/dam/assets/docs/digitizing-higher-education.pdf
17: https://www.universitiesuk.ac.uk/what-we-do/policy-and-research/publications/financial-sustainability-uk-universities
18: https://tech.ed.gov/ai-future-of-teaching-and-learning/
19: https://www.universitiesuk.ac.uk/sites/default/files/field/downloads/2024-01/pwc-uk-higher-education-financial-sustainability-report-january-2024.pdf
20: https://research.chalmers.se/publication/535715/file/535715_Fulltext.pdf
21: https://www.vu.edu.au/about-vu/news-events/news/the-ai-revolution-in-higher-education
22: https://www.sciencedirect.com/science/article/pii/S2666920X24000225
23: https://www.technologynetworks.com/informatics/news/more-than-a-third-of-students-use-ai-bots-373193
24: https://www.harbingergroup.com/blogs/generative-ai-in-higher-education-importance-use-cases-integration/
25: https://www.w3.org/WAI/standards-guidelines/wcag/
26: https://unesdoc.unesco.org/ark:/48223/pf0000385877
27: https://aws.amazon.com/ai/generative-ai/
28: https://theprairienews.com/33002/features/generative-ai-vs-ai-tools-in-higher-education/
29: https://er.educause.edu/articles/2023/8/integrating-generative-ai-into-higher-education-considerations
30: https://www.bcg.com/publications/2023/five-ways-education-can-leverage-gen-ai
31: https://unesdoc.unesco.org/ark:/48223/pf0000386670
32: https://russellgroup.ac.uk/media/6137/rg_ai_principles-final.pdf
33:https://www.gallup.com/topic/higher-education.aspx
34: https://itbrief.com.au/story/how-universities-can-compete-in-the-future-digital-economy
35: https://www.mckinsey.com/industries/education/our-insights/how-technology-is-shaping-learning-in-higher-education
36: https://www.mckinsey.com/industries/education/our-insights/new-global-data-reveal-education-technologys-impact-on-learning
37: https://itbrief.com.au/story/how-universities-can-compete-in-the-future-digital-economy
38: https://medium.com/@tylerjewell/wso2-named-a-leader-in-forresters-api-management-2018-wave-1aa7c79a3c38
39: https://www.cuit.columbia.edu/ea
40:https://core.ac.uk/download/pdf/200266856.pdf
41:https://www.ucisa.ac.uk/Events/2021/November/Global-HE-Capability-Model/Event-Other-Info-List/Recording-and-presentations
42: https://www.ucisa.ac.uk/Groups/Enterprise-Architecture-Group/HERM
43: https://www.youtube.com/watch?v=xjvriiOdI6U&t=1s
44:https://www.sap.com/india/industries/higher-education-research.html
45: https://www.sap.com/documents/2016/03/164c70d0-627c-0010-82c7-eda71af511fa.html
46:https://www.youtube.com/watch?v=b0EDY846trU
47:https://www.youtube.com/watch?v=9xiNDThr54w
48:https://www.youtube.com/@UCISA
49:https://www.education.gov.in/state-private-universities
50:https://www.ugc.gov.in/universitydetails/university?type=0wBmFB1Rb4JGVzq9UP/iOg==
51:https://ahduni.edu.in/
52:https://www.linkedin.com/pulse/university-higher-education-how-integration-can-meet-student-pascoe/
53: https://nicea.nic.in/sites/default/files/Draft_UEAF_Report_v7.5_0.pdf
