Tag: Hype

  • Higher Education Inquirer : University of Phoenix’s “TransferPath” App: Convenience or Marketing Hype?

    Higher Education Inquirer : University of Phoenix’s “TransferPath” App: Convenience or Marketing Hype?

    The University of Phoenix has launched TransferPath, a mobile app promising prospective students a quick estimate of how many previous college credits might transfer toward a Phoenix degree. At first glance, it sounds like a win: upload your transcripts, get a pre-evaluation, and move faster toward completing your degree. The EdTech Innovation Hub article covering the launch presents the app as an unambiguously positive innovation—but a closer look raises serious questions.

    The EdTech piece reads more like a press release than investigative reporting. It offers no insight into how pre-evaluations are calculated, whether faculty are involved, or how often initial predictions align with final credit acceptance. Without this transparency, students risk developing false confidence and making financial or academic decisions based on incomplete or misleading information.

    The app also reflects the asymmetry of power between institution and student. While marketed as a convenience, it is ultimately a recruitment tool. The University of Phoenix controls which credits are accepted, and the app’s messaging may funnel students into its programs regardless of whether other paths would better serve their educational goals.

    Missing from the coverage is context. Phoenix’s history as a for-profit institution has drawn scrutiny over retention rates, student debt, and degree outcomes. Presenting TransferPath without acknowledging this background creates a misleading narrative that the app is purely a student-centered innovation. Equity concerns are similarly absent. Students without smartphones, stable internet, or digital literacy may be excluded or misled. There is no evidence that the app serves all students fairly or that its credit predictions are accurate across diverse educational backgrounds.

    TransferPath may indeed offer some convenience, but convenience alone does not equal value. Prospective students deserve clarity, honesty, and rigorous evaluation of how tools like this actually function. They need more than marketing optimism—they need realistic guidance to navigate the complexities of credit transfer, institutional incentives, and long-term outcomes.

    Until such transparency and accountability are provided, TransferPath risks being more of a recruitment gimmick than a meaningful step forward in higher education.

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  • Beyond Hype and Fluff: Lessons for AI from 25 Years of EdTech

    Beyond Hype and Fluff: Lessons for AI from 25 Years of EdTech

    • This blog is by Rod Bristow is CEO of College Online which provides access to lifelong learning, Chair of Council at the University of Bradford, Visiting Professor at the UCL Institute of Education, Chair of the Kortext Academic Advisory Board and former President at Pearson.

    I am an advocate for education technology. It is a growing force for good, providing great solutions to real problems:

    • Reducing teacher workload through lesson planning, curriculum development, homework submission and marking, formative assessments, course management systems and more;
    • Improving learning outcomes through engaging, immersive experiences, adaptive assessments and the generation of rich data about learning;
    • Widening access to content and tools through aggregation platforms across thousands of publishers and millions of textbooks; and
    • Widening access to courses and qualifications for the purpose of lifelong learning using online and blended modes of delivery.

    Products and services that solve these problems will continue to take root.

    All that said, we have not seen the widespread transformation in education that technology promised to deliver, and investors have had their fingers burned. We could argue this results from unrealistic expectations rather than poor achievement, but there are lessons to be learned.

    According to HolonIQ:

    2024 saw $2.4 billion of EdTech Venture Capital, representing the lowest level of investment since 2015. The hype of 2021 is well and truly over, with investors seeking fundamentals over ‘fluff’.

    From HolonIQ

    The chart says it all. Steady growth in investment over the last decade culminated in a huge peak during Covid. Hype and ‘fluff’ overtook rational thinking, and several superficially attractive businesses spiked and then plummeted in value. In education, details and evidence of impact (or efficacy) matter. Without them, lasting scale is much harder to achieve.

    The pendulum has now swung the other way, with investors harder to convince. Investors and entrepreneurs need to ask the question, ‘Does it work?’ before considering how it scales. If they do, they will see plenty of applications that both work and scale, and better-educated investors will be good for the sector.

    One of the biggest barriers to scale is the complexity of implementation with teachers, without whom there is little impact. Without getting into the debate about teacher autonomy, most teachers like to do their own thing. And products which bypass teachers, marketed directly to consumers, often struggle to show as much impact and financial return.

    Will things be different with AI? The technology, being many times more powerful, will handle much greater flexibility of implementation for teachers than we have seen so far. AI has even greater potential to solve real problems: widening access to learning, saving time for teachers and engaging learners through adaptive digital formative assessment and deeply immersive learning experiences through augmented reality.

    But risks of ‘over-selling’ the benefits of AI technologies are potentially heightened by its very power. AI can generate mind-boggling ‘solutions’ for learners which dramatically reduce workload. Some of these are good in making learning more efficient, but questions of efficacy remain. Learning intrinsically requires work: it is done by you, not to you. Technology should not try to make learning easy, but to make hard work stimulating and productive if it is to sustain over the long term.

    There is a clear and present danger that AI will undermine learning if high-stakes assessments relying on coursework do not keep pace with the reality of AI. This is a risk yet to be gripped by regulators. There is also little evidence that, for example, AI will ever replace the inspiration of human teachers, and those saying their solutions will do so must make a very strong case. Technology companies can help, but they can also do harm.

    New technologies must be grounded in what improves learning, especially when unleashing the power of AI. This is entirely possible.

    There are many areas of great promise, but none more so than the enormous expansion in online access to lifelong learning for working people who are otherwise denied the education they need. There are now eight million people (mainly adults) studying for degrees online and tens of millions of people taking shorter online skills courses. Opening access to lifelong learning to everyone remains education’s biggest unmet need and opportunity. Education technologies can be ‘designed in’ to the entire learning experience from the beginning, rather than retrofitted by overworked teachers. Widening access to lifelong learning could deliver a greater transformation to the economy and society than we have seen in 100 years.

    Learning tools and platforms are one thing, but what do people need to learn in a world changed by AI? Much has been written about the potential for technology and especially AI to change what people need to learn. A popular narrative is that skills will be more important than knowledge; that knowledge can be so easily searched through the internet or created with AI, there is no need for it to be learned.

    Skills do matter, but these statements are wrong. We should not choose between skills and knowledge. Skills are a representation of knowledge. With no knowledge or expertise, there is no skill. More than that, in a world in which AI will have an unimaginable impact on society, we should remember that knowledge provides the very basis of our ability to think and that human memory is the residue of thought.

    Only a deeper understanding of learning and the real problems we need to solve will unleash the huge potential for technology to unlock wider access, a better learning experience and higher outcomes. To simultaneously hold the benefits and the risks of AI in a firm embrace, we will need courage, imagination and clarity about the problems to be solved before we get swept up in the hype and fluff. The opportunity is too big to put at risk.

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  • Don’t believe the hype: the Government and state school admissions to Oxford University

    Don’t believe the hype: the Government and state school admissions to Oxford University

    • HEPI Director, Nick Hillman, looks at the latest row on admissions to the University of Oxford.

    In a speech on Friday, the Minister for Skills, Baroness Smith, strongly chastised her alma mater, the University of Oxford, for taking a third of their entrants from the 6% of kids that go to private schools.

    In a section of the speech entitled ‘Challenging Oxford’, we were told the situation is ‘absurd’, ‘arcane’ and ‘can’t continue’:

    Oxford recently released their state school admissions data for 2024.

    And the results were poor.

    66.2% – the lowest entry rate since 2019.

    I want to be clear, speaking at an Oxford college today, that this is unacceptable.

    The university must do better.

    The independent sector educates around 6% of school children in the UK.

    But they make-up 33.8% of Oxford entrants.

    Do you really think you’re finding the cream of the crop, if a third of your students come from 6% of the population?

    It’s absurd.

    Arcane, even.

    And it can’t continue.

    It’s because I care about Oxford and I understand the difference that it can make to people’s lives that I’m challenging you to do better.  But it certainly isn’t only Oxford that has much further to go in ensuring access.

    This language reminded me of the Laura Spence affair, which produced so much heat and so little light in the Blair / Brown years and which may even have set back sensible conversations on broadening access to selective higher education.

    I wrote in a blog over the weekend that the Government are at risk of forgetting the benefit of education for education’s sake. That represents a political hole that Ministers should do everything to avoid as it could come to define them. Ill-thought through attacks on the most elite universities for their finely-grained admissions decisions represent a similar hole best avoided. Just imagine if the Minister had set out plans to tackle a really big access problem, like boys’ educational underachievement, instead. The Trump/Harvard spat is something any progressive government should seek to avoid, not copy.

    The latest chastisement is poorly formed for at least three specific reasons: the 6% is wrong in this context; the 33.8% number does not tell us what people tend to think it does; and Oxford’s current position of not closely monitoring the state/independent split is actually in line with the regulator’s guidance.

    1. 6% represents only half the proportion (12%) of school leavers educated at independent schools. In other words, the 6% number is a snapshot for the proportion of all young people in private schools right now; it tells us nothing about those at the end of their schooling and on the cusp of higher education.
    2. The 33.8% number is unhelpful because 20%+ of Oxford’s new undergraduates hail from overseas and they are entirely ignored in the calculation. If you include the (over) one in five Oxford undergraduate entrants educated overseas, the proportion of Oxford’s intake that is made up of UK private school kids falls from from something like one-third to more like one-quarter. This matters in part because the number of international students at Oxford has grown, meaning there are fewer places for home students of all backgrounds. In 2024, Oxford admitted 100 more undergraduate students than in 2006, but there were 250 more international students – and consequently fewer Brits. We seem to be obsessed with the backgrounds of home students and, because we want their money, entirely uninterested in the backgrounds of international students.
    3. The Office for Students dislikes the state/private metric. This is because of the differences within these two categories: in other words, there are high-performing state schools and less high-performing independent schools. Last year, when the University of Cambridge said they planned to move away from a simplistic state/independent school target, John Blake, the Director of Fair Access and Participation at the Office for Students, confirmed to the BBC, ‘we do not require a target on the proportion of pupils from state schools entering a particular university.’ So universities have typically shied away from this measure in recent times. If Ministers think it is a key metric after all and if they really do wish to condemn individual institutions for their state/independent split, it would have made sense to have had a conversation with the Office for Students and to have encouraged them to put out new guidance first. At the moment, the Minister and the regulator are saying different things on an important issue of high media attention.

    Are independently educated pupils overrepresented at Oxbridge? Quite possibly, but the Minister’s stick/schtick, while at one with the Government’s wider negative approach to independent schools, seems a sub-optimal way to engineer a conversation on the issue. Perhaps Whitehall wanted a headline more than it wanted to get under the skin of the issue?

    we do not require a target on the proportion of pupils from state schools entering a particular university

    John Blake, Director for Fair access and participation

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  • Beyond the AI Hype: Strategic AI Implementation in Higher Education

    Beyond the AI Hype: Strategic AI Implementation in Higher Education

    The buzz around AI in higher ed is undeniable. The topic dominated conference discussions at ASU + GSV, with nearly every booth, breakout, and keynote referencing AI somehow. When AI gets tossed around so often, it can be hard to differentiate between what’s real and what isn’t.  

    While the transformative promise of AI is exciting, successful AI implementation requires more than fast adoption. The more important question is: How can institutions move from ideas to impact? 

    The reality is that achieving meaningful results with AI requires more than just purchasing the latest tool. That’s often the easiest part, but it can also be a trap. Tool and tech procurement, absent a well-informed implementation strategy, can add to your technical debt. It’s critical to look beyond the buzzword and first define where you want your institution to be in the future. With your north star in place, you can determine how AI can play a role in a holistic solution. 

    Operationalizing AI for Real Impact 

    Many discussions around AI for higher ed focus on its evolving capabilities to generate content, automate tasks, engage and support students, and handle other critical functions. But what is the impact you’re looking to make, and how are you going to measure the return on investment? Those questions tend to be missing from higher ed’s ongoing AI conversation. Don’t implement tactics (or tools) until you know their role in your broader tech strategy. Too often, there is a heightened sense of urgency to implement and not enough focus on the complexities of weaving these tools into the intricate fabric of an institution. There is no easy button in AI. 

    Trying to catch the AI hype without having a strategic AI implementation plan is like buying state-of-the-art lab equipment before you’ve decided what type of science courses you are going to offer.  Effective integration involves significant change management, process design, and ongoing investment.  

    For example, many schools already use AI-powered agents to assist with student recruitment by answering prospects’ questions and suggesting next steps. These bots can scale engagement significantly — but to be effective, they require meticulous training, constant monitoring, and attentive human oversight to ensure the interaction is aligned with a school’s culture and values. As technology evolves, the operational model must adapt. Without constant care and feeding, AI tools can become outdated, provide incorrect information, or fail to align with the institution’s unique voice and mission. Remember, technology and tool outputs are only as good as the inputs.  

    And the investment isn’t just the initial software cost. The investment also includes ongoing commitment to deployment, integration, training, and ensuring the technology drives the desired outcomes. Many underestimate this operational heavy lifting in the rush to adopt AI, yet it’s the linchpin for success. 

    Start with Strategy, Not Just Software 

    A more effective, pragmatic approach to AI implementation in higher education begins by identifying the institution’s core challenges and strategic objectives. 

    Are you focused on reversing enrollment declines? Improving student retention rates? Enhancing support services? Increasing operational efficiency? By defining your goals and measurable key performance indicators (KPIs) from the outset, you’re in the best position to strategically evaluate how AI — alongside other data, technology, and talent resources — can contribute to a solution that supports the entire student lifecycle. 

    Without this clarity, institutions risk spending significant resources without achieving tangible returns. It’s about focusing efforts, perhaps starting with a contained, controllable area where impact can be carefully monitored and measured, rather than attempting to boil the ocean. 

    Leveraging AI Strategically 

    Currently, many institutions are grappling with important discussions around AI ethics, academic integrity, and preventing misuse by students to cheat. It’s important not to get stuck there. Students who want to circumvent rules will find a way. AI is simply the newest tool. Focusing excessively on policing AI use means missing the boat on its strategic potential. 

    The real opportunity lies in leveraging AI across the entire student lifecycle — from recruitment and enrollment to engagement, support, and retention. AI can personalize outreach, provide 24/7 advising support, identify at-risk students earlier, and automate administrative tasks, freeing up staff for higher-value interactions. It will almost certainly be part of effective solutions, but it shouldn’t be the only part. 

    The Indispensable Human Element  

    In the race to apply AI, we must not forget the crucial role of human intelligence (HI). AI tools, even sophisticated ones, require human oversight. They must train on the correct data and the institution’s values, mission, and unique persona.   

    Humans are essential for guiding AI, correcting its inevitable errors and ensuring its outputs align with institutional standards. Furthermore, education remains a fundamentally human endeavor. While AI can enhance efficiency and scale, it cannot replace true empathy, mentorship, and social-emotional connection, which are vital to student success and belonging. The most effective approach combines the power of AI with the irreplaceable value of human talent — a synergy Collegis champions through its focus on data, tech, and talent. 

    Moving Fast, But Moving Smart 

    The desire to rapidly adopt AI in higher ed is understandable. However, a rushed implementation without a clear strategy is likely to falter. Stepping back to define objectives, plan the integration, and establish metrics is the best way to accelerate the path to meaningful impact. 

    This more deliberate, strategic approach enables institutions to harness AI’s power effectively, ensuring it serves their unique mission and drives measurable results. It’s about moving beyond the hype and focusing on the pragmatic steps needed to make AI work for higher ed, creating sustainable value for the institution and the students it serves. The journey requires careful navigation, a focus on operational reality, and often, a partner who understands how to bridge the gap between potential and practice. 

    Innovation Starts Here

    Higher ed is evolving — don’t get left behind. Explore how Collegis can help your institution thrive.

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  • AI in Education: Beyond the Hype Cycle

    AI in Education: Beyond the Hype Cycle

    We just can’t get away from it. AI continues to take the oxygen out of every edtech conversation. Even the Trump administration, while actively destroying federal involvement in public education, jumped on the bandwagon this week.

    Who better to puncture this overused acronym than edtech legend Gary Stager. In this conversation, he offers a pragmatic perspective on AI in education, cutting through both fear and hype. Gary argues that educators should view AI as simply another useful technology rather than something to either fear or blindly embrace. He criticizes the rush to create AI policies and curricula by administrators with limited understanding of the technology, suggesting instead that schools adopt minimal, flexible policies while encouraging hands-on experimentation. Have a listen: