Category: Data

Three-quarters of global study decisions determined by cost

International students are increasingly looking for affordable destinations and alternative programs rather than give up on study abroad due to increasing costs, a new ApplyBoard survey has shown.

While 77% of surveyed students ranked affordable tuition fees as the most important factor shaping study decisions, only 9% said they planned to defer their studies based on these concerns, according to a recent student survey from ApplyBoard edtech firm.

“Students weren’t planning to wait for things to change,” said ApplyBoard senior communications manager Brooke Kelly: “They’re considering new destinations, adjusting which programs they apply to, and accepting that they have to balance work with study, but they’re still planning to study abroad,” she maintained.

Just over one in four students said they were considering different study destinations than originally planned, with Denmark, Finland, Nigeria and Italy the most popular emerging destinations.

Additionally, 55% of students said they would have to work part-time to afford their study abroad program.

After affordability, came employability (57%), career readiness (49%), high-quality teaching (47%), and program reputation (45%), as factors shaping student decision-making.

With students increasingly thinking about work opportunities, software and civil engineering topped students’ career choices, with nursing as the second most popular field. Tech fields including IT, cybersecurity, and data analysis also showed strong interest.

What’s more, interest in PhD programs saw a 4% rise on the previous year, while over half of students were considering master’s degrees, indicating that students are increasingly prioritising credentials and post-study work opportunities.

[Students are] considering new destinations, adjusting which programs they apply to, and accepting that they have to balance work with study, but they’re still planning to study abroad

Brooke Kelly, ApplyBoard

The study surveyed over 3,500 students from 84 countries, with the most represented countries being Nigeria, Ghana, Canada, Pakistan, Bangladesh and India.

Given its share of international students, it should be noted that China is absent from the top 10 most represented countries.

As students’ priorities shift and currencies fluctuate, “diversity will be key to mitigate against increased volatility and to ensure campuses remain vibrant with students from all around the world,” said Kelly.

Meanwhile, institutions should increase communication about scholarships and financial aid, offer more hybrid learning experiences and highlight programs on different timelines such as accelerated degrees, she advised.

While alternative markets are on the rise, 65% of respondents said they were only interested in studying in one of the six major destinations, with Canada followed by the US, UK, Australia, Germany and Ireland, in order of popularity.

Despite Canada’s international student caps, the largest proportion of students said they were ‘extremely’, ‘very’ or ‘moderately’ interested in the study destination, highlighting its enduring appeal among young people.

While stricter controls on post study work were implemented in Canada last year, in a rare easing of policies, the IRCC recently said that all college graduates would once again be eligible for post study work.

This change, combined with the fact that international students can still be accompanied by their dependants while studying in Canada, is likely to have contributed to it maintaining its attractiveness, according to Kelly.

Source link

April 4, 2025
What the End of DoED Means for the EdTech Industry

The Fed’s influence over school districts had implications beyond just funding and data. Eliminating The Office of Education Technology (OET) will create significant gaps in educational technology research, validation, and equity assurance. Kris Astle, Education Strategist for SMART Technologies, discusses how industry self-governance, third-party organizations, and increased vendor responsibility might fill these gaps, while emphasizing the importance of research-backed design and implementation to ensure effective technology deployment in classrooms nationwide. Have a listen:

Key Takeaways

More News from eSchool News

In recent years, the rise of AI technologies and the increasing pressures placed on students have made academic dishonesty a growing concern. Students, especially in the middle and high school years, have more opportunities than ever to cheat using AI tools.

As technology trainers, we support teachers’ and administrators’ technology platform needs, training, and support in our district. We do in-class demos and share as much as we can with them, and we also send out a weekly newsletter.

Math is a fundamental part of K-12 education, but students often face significant challenges in mastering increasingly challenging math concepts.

Throughout my education, I have always been frustrated by busy work–the kind of homework that felt like an obligatory exercise rather than a meaningful learning experience.

During the pandemic, thousands of school systems used emergency relief aid to buy laptops, Chromebooks, and other digital devices for students to use in remote learning.

Education today looks dramatically different from classrooms of just a decade ago. Interactive technologies and multimedia tools now replace traditional textbooks and lectures, creating more dynamic and engaging learning environments.

There is significant evidence of the connection between physical movement and learning. Some colleges and universities encourage using standing or treadmill desks while studying, as well as taking breaks to exercise.

This story was originally published by Chalkbeat. Sign up for their newsletters at ckbe.at/newsletters. In recent weeks, we’ve seen federal and state governments issue stop-work orders, withdraw contracts, and terminate…

English/language arts and science teachers were almost twice as likely to say they use AI tools compared to math teachers or elementary teachers of all subjects, according to a February 2025 survey from the RAND Corporation.

During the seven years I served on the Derry School Board in New Hampshire, the board often came first. During those last two years during COVID, when I was chair, that meant choosing many late-night meetings over dinner with my family.

Tags classrooms, data, Department of Education, deployment, design, districts, edtech, Education, education technology, educational technology

Want to share a great resource? Let us know at submissions@eschoolmedia.com.

Source link

April 3, 2025
Capability for change – preparing for digital learning futures

Digital transformation is an ongoing journey for higher education institutions, but there is something quite distinctive about the current moment.

The combination of financial uncertainty, changing patterns of student engagement, and the seismic arrival of artificial intelligence is pointing to a future for higher education learning and teaching and a digital student experience that will certainly have some core elements in common with current practice but is likely in many respects to look rather different.

At the moment I see myself and my colleagues trying to cling to what we always did and what we always know. And I really do think the whole future of what we do and how we teach our students, and what we teach our students is going to accelerate and change very, very quickly now, in the next five years. Institutional leader

Our conversations with sector leaders and experts over the past six months indicate an ambition to build consistent, inclusive and engaging digital learning environments and to deploy data much more strategically. Getting it right opens up all kinds of possibilities to extend the reach of higher education and to innovate in models for engagement. But future change demands different kinds of technological capabilities, and working practices, and institutions are saying that they are hindered by legacy systems, organisational silos, and a lack of a unified vision.

Outdated systems do not “talk to each other,” and on a cultural level as departments and central teams also do not “talk to each other” – or may struggle to find a common language. And rather than making life easier, many feel that technology creates significant inefficiencies, forcing staff to spend more time on administrative tasks and less on what truly matters.

I think the problem always is when we hope something’s going to make it more efficient. But then it just adds a layer of complexity into what we’re doing…I think that’s what we struggle with – what can genuinely deliver some time savings and efficiencies as opposed to putting another layer in a process? Institutional leader

In the spirit of appreciative inquiry, our report Capability for change – preparing for digital learning futures draws on a series of in depth discussions with leaders of learning and teaching, and digital technology, digital experts and students’ union representatives. We explore the sorts of change that are already in train, and surface insight about how institutions are thinking in terms of building whole-organisation capabilities. “Digital dexterity” – the ability to deploy technology strategically, efficiently, and innovatively to achieve core objectives – may be yet another tech buzzword, but it captures a sense of where organisations are trying to get to.

While immediate financial pressures may require cutting costs and reprofiling investment, long term sustainability depends on moving forward with change, finding ways, not to do more with less but to do things differently. To realise the most value from technology investment institutional leaders need to find ways to ensure that across the institution staff teams have the knowledge, the motivation and the tools to deploy technology in the service of student success.

How institutions are building organisational capability

Running through all our conversations was a tension, albeit a potentially productive one: there needs to be much more consistency and clarity about the primary strategic objectives of the institution and the core technology platforms and applications that enable them. But the effect of, in essence, imposing a more streamlined “central” vision, expectations and processes should be to enable and empower the academic and professional teams to do the things that make for a great student experience. Our research indicates that institutions are focusing on three areas: leadership and strategy; digital capabilities of institutional staff; and breaking down the vertical silos that can hamper effective cross-organisational working.

A number of reflections point to strategy-level improvements – such as ensuring there is strategic alignment between institutional objectives for student success, and technology and digital strategies; listening to the feedback from students and staff about what they need from technology; setting priorities, and resourcing those priorities from end to end from technology procurement to deployment and evaluation of impact. One institutional leader described what happens when digital strategies get lost in principles and forget to align with the wider success of the organisation:

The old strategy is fairly similar, I imagine, to many digital strategies that you would have seen – it talks about being user focused, talks about lean delivery, talks about agile methodologies, product and change management and delivering value through showing, not telling. So it was a very top level strategy, but really not built with outcomes at its absolute core, like, what are the things that are genuinely going to change for people, for students? Institutional leader

Discussions of staff digital capabilities recognised that institutional staff are often hampered by organisational complexity and bureaucracy which too often is mirrored in the digital sphere. One e-learning professional suggested that there is a need for research to really understand why there is a tendency towards proliferation of processes and systems, and confront the impact on staff workloads.

There may also be limits to what can reasonably be expected from teaching staff in terms of digital learning design:

You need to establish minimum benchmarks and get everyone to that place, and then some people will be operating well beyond that. You can be clear about basic benchmark expectations around student experience – and then beyond that you need to put in actual support [such as learning design experts] to implement the curriculum framework. E-learning professional

But the broader insight on staff development was around shifting from provision of training on how to operate systems or tools to a more context-specific exploration of how the available technologies and data can help educators achieve their student success ambitions. Value is more systematically created across the organisation when those academic and professional teams who work directly with students are able to use the technology and data available creatively to enhance their practice and to problem solve.

Where data has been used before it’s very much sat with senior colleagues in the institution. And you know it’s helped in decision making. But the next step is to try and empower colleagues at the coal face to use data in their day to day interventions with their students… How can they use the data to inform how they support their students? Institutional leader

Decisive leadership may be successful in setting priorities and streamlining the processes and technologies that underpin them; strong focus on professional development may engage and enable institutional staff. But culture change will come when institutions find ways to systematically build “horizontals” across silos – mechanisms for collaborative and shared activity that bridge different perspectives, languages and disciplinary and professional cultures.

Some examples we saw included embedding digital professionals in faculties and academic business processes such as recruitment panels, convening of cross-organisation thinking on shared challenges, and appointment of “change agent” roles with a skillset and remit to roam across boundaries.

Technology providers must be part of the solution – acting as strategic partners rather than suppliers. One way to do that is to support institutions to pilot, test, and develop proof of concept before they decide to invest in large-scale change. Another is to work with institutions to understand how technology is deployed in practice, and the evolving needs of user communities. To be a great partner to the higher education sector means having a deep understanding not only of the technological capabilities that could help the sector but how these might weave into an organisation’s wider mission and values. In this way, technology providers can help to build capability for change.

This article is published in association with Kortext. You can download the Capability for change report on Kortext’s website. The authors would like to thank all those who shared their insight to inform the report.

Source link

March 31, 2025
Check-in on Administrative Bloat, 2025 Edition

Check-in on Administrative Bloat, 2025 Edition

It’s been a little over five years since I took a serious dive into the question of “administrative bloat,” which apparently exists everywhere but in the statistics. Still, always good to check assumptions every once in a while, and I thought five years was long enough to make a new look at the data worthwhile. So here goes:

Let’s start by reviewing what we can and cannot know about staffing at Canadian universities. StatsCan tracks the number of permanent ranked faculty pretty accurately through its University and College Academic Staff Survey (UCASS), and in a loosey-goosier fashion through the Labour Force Survey. The latter gives much higher numbers than the former, as shown below in Figure 1, which compares the number of “ranked” academics from UCASS with the number of permanent, full-time academics from the LFS.

Figure 1 – Full-time Academic Staff Numbers According to LFS and UCASS

StatsCan also tracks the total number of employees—both salaried and hourly—in the university sector using the Survey of Employment, Payroll and Hours (SEPH). However, in theory, if you subtract the number of FT academic staff from the number of total staff, you should be able to get the total number of non-academic staff, right? Well, unfortunately, this is where the discrepancy between UCASS and LFS runs into some problems. In Figure 2, I show the implied number of non-academics using both methods. The growth rates are different because of the difference in observations in the early period, but the two estimates do both converge on the observation that there are about 130,000 non-academic staff at Canadian universities, or about two and a half times the complement of academic staff.

Figure 2 – Implied Non-Academic Staff Numbers using SEPH, LFS and UCASS

So, that’s evidence of bloat, right? Well, maybe. Personally, what I take from Figure 2 is that either (or both) the LFS numbers and the SEPH numbers are probably flaming hot garbage. There’s simply no way that the number of non-academic staff has increased by 170% in the past twenty years, as a combination of the SEPH and LFS data suggests. For reasons that will become apparent shortly, I also have serious doubts that it’s increased by 85% either, as the combination of SPEH and UCASS suggests. Because there is a second set of data available to look at this question, one that shows expenditure on salaries, and it shows a much different picture.

The annual FIUC survey shows how much money is spent on wages for ranked academics as well as how much is spent on non-academics (it also shows wages for instructional staff without academic rank,” but I exclude this here for ease of analysis). Over the past three years, it is true that non-academic salary mass has risen, and academic ones have not (score for the bloat theory!), but looked at with a 25-year lens, Figure 3 shows that the rate of increase is about the same (score one against).

Figure 3 – Total Expenditures on Salaries by Employee Group, in millions of $2023

Basically, the salary data in Figure 3 tells a completely different story than the SEPH/LFS/UCASS data in Figure 2. All you do is divide the spending data by the implied headcounts to see what I mean (which I do below). Figure 4 shows the implied change in average academic pay and average A&S pay, dividing total FIUC pay by the UCASS academic staff numbers and the A&S staff numbers implied by subtracting the UCASS numbers from the SEPH numbers, i.e., the orange line from Figure 2. To believe both sets of data, you have to believe that average academic salaries have increased substantially while average salaries for non-academics have declined substantially.

Figure 4 – Change in Implied Average Pay, Academic Staff vs. A&S Staff, 2001-02 = 100

In Figure 4, the blue line representing academic salaries is more or less consistent with the long-term trend in salaries we have seen by looking at salary survey data (which I last did back here): significant growth in the 00s and much slower growth thereafter. There are no staff salary surveys to use for comparison, but let’s put it this way: when people talk about “bloat” in non-academic staff positions, they normally mean it in the sense that the bloat is coming from expensive A&S staff, overpaid A&S staff, etc. For Figure 4 to be true, the growth in staff numbers would need to come almost entirely from more junior, less well-paid staff. It’s not impossible that this is true, but it’s not consistent with the general vibe about bloat, either

So who knows, really? There’s a lot of contradictory data here, some of which argues strongly in favour of the bloat argument, but quite a bit of which points in the other direction. Better data is needed to answer this question probably isn’t forthcoming.

Meanwhile, we can take one last look at A&S expenditure data. We can check to see if the pattern of A&S salary expenditures across university operating functions has changed over time. As Figure 5 shows, the answer is “a little bit.” Central Administration now takes up 25% of total A&S salary expenditures, up from 22% 20 years ago. Student services and external relations are up much more sharply in proportional terms, but since they were both starting from a low base, they don’t impact the overall numbers that much. Libraries, physical plant, and non-credit instruction are the categories losing share.

Figure 5: Share of Total A&S Salary Mass by Function, Canadian University Operating Grants, Select Years

And there you have it: more data than you probably needed on administrative bloat. See you back here again in 2030.

Source link

March 26, 2025
Professional services staff need equal recognition – visibility in sector data would be a good start

Achieving recognition for the significant contribution of professional services staff is a collaborative, cross-sector effort.

With HESA’s second consultation on higher education staff statistics welcoming responses until 3 April, AGCAS has come together with a wide range of membership bodies representing professional services staff across higher education to release a statement warmly welcoming HESA’s proposal to widen coverage of the higher education staff record to include technical staff and professional and operational staff.

By creating a more complete staff record, HESA aim to deliver better understanding of the diverse workforce supporting the delivery of UK higher education. AGCAS, together with AHEP, AMOSSHE, ASET, CRAC-Vitae, NADP and UMHAN, welcome these proposals. We have taken this collaborative approach because we have a common goal of seeking wider recognition for the outstanding contributions and work of our members in professional services roles, and the impact they make on their institutions, regions, graduates and students.

A matter of visibility

Since the 2019–20 academic year, higher education providers in England and Northern Ireland have had the option to return data on non-academic staff to HESA. However, this has led to a lack of comprehensive visibility for many professional services staff. In the 2023–24 academic year, out of 228 providers only 125 opted to return data on all their non-academic staff – leaving 103 providers opting out.

This gap in data collection has raised concerns about the recognition and visibility of these essential staff members – and has not gone unnoticed by professional services staff themselves. As one AGCAS member noted:

Professional service staff have largely remained invisible when reporting on university staff numbers. Professional services provide critical elements of student experience and outcomes, and this needs to be recognised and reflected better in statutory reporting.

This sentiment underscores the importance of the proposed changes by HESA, and the reason for our shared response.

Who is and is not

A further element of the consultation considers a move away from the term “non-academic” to better reflect the roles and contributions of these staff members and proposes to collect data on staff employment functions.

Again, we collectively strongly support these proposed changes, which have the potential to better understand and acknowledge the wide range of staff working to deliver outstanding higher education across the UK. The term non-academic has long been contentious across higher education. While continuing to separate staff into role types may cause issues for those in the third space, shifting away from a term and approach that defines professional services staff by othering them is a welcome change.

As we move forward, it is essential to continue fostering collaboration and mutual respect between academic and professional services staff. Challenging times across higher education can create or enhance partnership working between academic and professional services staff, in order to tackle shared difficulties, increase collaboration and form strategic alliances.

A better environment

By working in this way, we can create a more inclusive and supportive environment that recognises the diverse contributions of all staff members, ultimately enhancing outcomes for all higher education stakeholders, particularly students.

Due to the nature of our memberships, our shared statement focuses on professional services staff in higher education – but we also welcome the clear focus on operational and technical staff from HESA, who again make vital contributions to their institutions.

We all know that representation matters to our members, and the higher education staff that we collectively represent. HESA’s proposed changes could help to start a move towards fully and equitably recognising the vital work of professional services staff across higher education. By expanding data collection to include wider staff roles and moving away from the term “non-academic”, we can better understand and acknowledge the wide range of contributions that support the higher education sector.

This is just the first step towards better representation and recognition, but it is an important one.

Source link

March 26, 2025
Student experience is becoming more transactional – but that doesn’t make it less meaningful

It seems that few can agree about what the future student experience will look like but there is a growing consensus that for the majority of higher education institutions (bar a few outliers) it will – and probably should – look different from today.

For your institution, that might look like a question of curriculum – addressing student demand for practical skills, career competencies and civic values to be more robustly embedded in academic courses. It might be about the structure of delivery – with the Lifelong Learning Entitlement funding per credit model due to roll out in the next few years and the associated opportunity to flex how students access programmes of study and accrue credit. It might be a question of modality and responding to demands for flexibility in accessing learning materials remotely using technology.

When you combine all these changes and trends you potentially arrive at a more fragmented and transient model of higher education, with students passing through campus or logging in remotely to pick up their higher education work alongside their other commitments. Academic community – at least in the traditional sense of the campus being the locus of daily activity for students and academics – already appears at risk, and some worry that there is a version of the future in which it is much-reduced or disappears altogether.

Flexibility, not fragmentation

With most higher education institutions facing difficult financial circumstances without any immediate prospect of external relief, the likelihood is that cost-saving measures reduce both the institutional capacity to provide wraparound services and the opportunities for the kind of human-to-human contact that shows up organically when everyone is co-located. Sam Sanders

One of the challenges for higher education in the decade ahead will be how to sustain motivation and engagement, build connection and belonging, and support students’ wellbeing, while responding to that shifting pattern of how students practically encounter learning.

The current model still relies on high-quality person to person interaction in classrooms, labs, on placement, in accessing services, and in extra-curricular activities. When you have enough of that kind of rich human interaction it’s possible to some extent to tolerate a degree of (for want of a better word) shonky-ness in students’ functional and administrative interactions with their institution.

That’s not a reflection of the skills and professionalism of the staff who manage those interactions; it’s testament to the messiness of decades of technology systems procurement that has not kept up with the changing demands of higher education operational management. The amount of institutional resource devoted to maintaining and updating these systems, setting up workarounds when they don’t serve desired institutional processes, and extracting and translating data from them is no longer justifiable in the current environment.

Lots of institutional leaders accept that change is coming. Many are leading significant transformation and reform programmes that respond to one or more of the changes noted above. But they are often trying – at some expense – to build a change agenda on top of a fragile foundational infrastructure. And this is where a change in mindset and culture will be needed to allow institutions to build the kind of student experiences that we think are likely to become dominant within the next decade.

Don’t fear the transactional

Maintaining quality when resources are constrained requires a deep appreciation of the “moments that matter” in student experience – those that will have lasting impact on students’ sense of academic identity and connection, and by association their success – and those that can be, essentially, transactional. Pete Moss

If, as seems to be the case, the sector is moving towards a world in which students need a greater bulk of their interaction with their institution to be in that “transactional” bucket two things follow:

One is that the meaningful bits of learning, teaching, academic support and student development have to be REALLY meaningful, enriching encounters for both students and the staff who are educating them – because it’s these moments that will bring the education experience to life and have a transformative effect on students. To some degree how each institution creates that sense of meaningfulness and where it chooses to focus its pedagogical efforts may act as a differentiator to guide student choice.

The second is that the transactional bits have to REALLY work – at a baseline be low-friction, designed with the user in mind, and make the best possible use of technologies to support a more grab-and-go, self-service, accessible-anywhere model that can be scaled for a diverse student body with complicated lives.

Transactional should not mean ‘one-size-fits-all’ – in fact careful investment in technology should mean that it is possible to build a more inclusive experience through adapting to students’ needs, whether that’s about deploying translation software, integrating assistive technologies, or natural language search functionality. Lizzie Falkowska

Optimally, institutions will be seeking to get to the point where it is possible to track a student right from their first interaction with the institution all the way through becoming an alumnus – and be able to accommodate a student being several things at once, or moving “backwards” along that critical path as well as “forwards.” Having the data foundations in place to understand where a student is now, as well as where they have come from, and even where they want to get to, makes it possible to build a genuinely personalised experience.

In this “transactional” domain, there is much less opportunity for strategic differentiation with competitor institutions – though there is a lot of opportunity for hygiene failure, if students who find their institution difficult to deal with decide to take their credits and port them elsewhere. Institutional staff, too, need to be able to quickly and easily conduct transactional business with the institution, so that their time is devoted as much as possible to the knowledge and student engagement work that is simply more important.

Critically, the more that institutions adopt common core frameworks and processes in that transactional bucket of activity, the more efficient the whole sector can be, and the more value can be realised in the “meaningful” bucket. That means resisting the urge to tinker and adapt, letting go of the myth of exceptionalism, and embracing an “adopt not adapt” mindset.

Fixing the foundations

To get there, institutions need to go back to basics in the engine-room of the student experience – the student record system. The student system of 15-20 years ago was a completely internally focused statutory engine, existing for award board grids and HESA returns. Student records is now seen as a student-centric platform that happens to support other outputs and outcomes, both student-facing interactions, and management information that can drive decision-making about where resource input is generating the best returns.

The breadth of things in the student experience that need to be supported has expanded rapidly, and will continue to need to be adapted. Right now, institutions need their student record system to be able to cope with feeding data into other platforms to allow (within institutional data ethics frameworks) useful reporting on things like usage and engagement patterns. Increasingly ubiquitous AI functionality in information search, student support, and analytics needs to be underpinned by high quality data or it will not realise any value when rolled out.

Going further, as institutions start to explore opportunities for strategic collaboration, co-design of qualifications and pathways in response to regional skills demands, or start to diversify their portfolio to capture the benefits of the LLE funding model, moving toward a common data framework and standards will be a key enabler for new opportunities to emerge.

The extent to which the sector is able to adopt a common set of standards and interoperability expectations for student records is the extent to which it can move forward collectively with establishing a high quality baseline for managing the bit of student experience that might be “transactional” in their function, but that will matter greatly as creating the foundations for the bits that really do create lasting value.

This article is published in association with KPMG.

Source link

March 25, 2025
Policy Proposals Lack Clarity About How to Evaluate Graduates’ Additional Degrees

Title: Accounting for Additional Credentials in Postsecondary Earnings Data

Authors: Jason Delisle, Jason Cohn, and Bryan Cook

Source: The Urban Institute

As policymakers across both parties consider how to evaluate postsecondary outcomes and earnings data, the authors of a new brief from the Urban Institute pose a major question: How should students who earn multiple credentials be included in data collection for the college that awarded their first degree?

For example, should the earnings of a master’s degree recipient be included in the data for the institution where they earned their bachelor’s degree? Additionally, students who finish an associate degree at a community college are likely to earn higher wages when they complete a bachelor’s degree at another institution. Thus, multiple perspectives need to be considered to help both policymakers and institutions understand, interpret, and treat additional degrees earned.

Additional key findings include:

Earnings Data and Accountability Policies

Many legislative proposals would expand the use of earnings data to provide further accountability and federal aid restrictions. For example, the House Republicans’ College Cost Reduction Act, proposed in 2024, would put institutions at risk of losing funding if they have low student loan repayment rates. The brief’s authors state that the bill does not indicate if students who earn additional credentials should be included in the cohort of students where they completed their first credential.

The recently implemented gainful employment rule from the Biden administration is explicit in its inclusion of those who earn additional credentials. Under the rule, students who earn an additional degree are included in both calculations for their recent degree and the program that awarded their first credential.

How Much Do Additional Credential Affect Earnings Data?

Determining how much additional credentials affect wages and earnings for different programs is difficult. The first earnings measurement—the first year after students leave school—is usually too early to include additional income information from a second credential.

Although the entire data picture is lacking, a contrast between first- and fifth-year earnings suggests that the number of students earning additional degrees may be very high for some programs. As an example, students who earn associate degrees in liberal arts and general studies often have some of their quickest increases in earnings during these first five years. A potential explanation is because students are then completing a bachelor’s degree program at a four-year institution.

Policy Implications: How Should Earnings Data Approach Subsequent Credentials?

In general, it seems that many policymakers have not focused on this complicated question of students who earn additional degrees. However, policy and data professionals may benefit from excluding students who earn additional credentials to more closely measure programs’ return on investment. This can be especially helpful when examining the costs of bachelor’s programs and their subsequent earnings benchmarks, by excluding additional earnings premiums generated from master’s programs.

Additionally, excluding students who earn additional credentials may be particularly valuable to students in making consumer and financial aid decisions if the payoff from a degree is extremely different depending on whether students pursue an additional credential.

However, some programs are intended to prepare students for an additional degree, and excluding data for students who earn another degree would mean excluding most graduates and paint a misleading picture.

To read the full report from the Urban Institute, click here.

—Austin Freeman

If you have any questions or comments about this blog post, please contact us.

Source link

March 3, 2025
Embracing a growth mindset when reviewing student data

Key points:

In the words of Carol Dweck, “Becoming is better than being.” As novice sixth grade math and English teachers, we’ve learned to approach our mid-year benchmark assessments not as final judgments but as tools for reflection and growth. Many of our students entered the school year below grade level, and while achieving grade-level mastery is challenging, a growth mindset allows us to see their potential, celebrate progress, and plan for further successes amongst our students. This perspective transforms data analysis into an empowering process; data is a tool for improvement amongst our students rather than a measure of failure.

A growth mindset is the belief that abilities grow through effort and persistence. This mindset shapes how we view data. Instead of focusing on what students can’t do, we emphasize what they can achieve. For us, this means turning gaps into opportunities for growth and modeling optimism and resilience for our students. When reviewing data, we don’t dwell on weaknesses. We set small and achievable goals to help students move forward to build confidence and momentum.

Celebrating progress is vital. Even small wins (i.e., moving from a kindergarten grade-level to a 1^st– or 2^nd-grade level, significant growth in one domain, etc.) are causes for recognition. Highlighting these successes motivates students and shows them that effort leads to results.

Involving students in the process is also advantageous. At student-led conferences, our students presented their data via slideshows that they created after they reviewed their growth, identified their strengths, and generated next steps with their teachers. This allowed them to feel and have tremendous ownership over their learning. In addition, interdisciplinary collaboration at our weekly professional learning communities (PLCs) has strengthened this process. To support our students who struggle in English and math, we work together to address overlapping challenges (i.e., teaching math vocabulary, chunking word-problems, etc.) to ensure students build skills in connected and meaningful ways.

We also address the social-emotional side of learning. Many students come to us with fixed mindsets by believing they’re just “bad at math” or “not good readers.” We counter this by celebrating effort, by normalizing struggle, and by creating a safe and supportive environment where mistakes are part of learning. Progress is often slow, but it’s real. Students may not reach grade-level standards in one year, but gains in confidence, skills, and mindset set the stage for future success, as evidenced by our students’ mid-year benchmark results. We emphasize the concept of having a “growth mindset,” because in the words of Denzel Washington, “The road to success is always under construction.” By embracing growth and seeing potential in every student, improvement, resilience, and hope will allow for a brighter future.

Latest posts by eSchool Media Contributors (see all)

Source link

February 17, 2025
Fun with Participation Rate Data
Just a quick one today, mostly charts.

Back in the fall, StatsCan released a mess of data from the Labour Force Survey looking at education participation rates—that is, the percentage of any given age cohort that is attending education—over the past 25 years. So, let’s go see what it says.

Figure 1 shows total education participation rates, across all levels of education, from age 15 to 29, for selected years over the past quarter century. At the two ends of the graph, the numbers look pretty similar. At age 15, we’ve always had 95%+ of our population enrolled in school (almost exclusively secondary education, and from age 26 and above, we’ve always been in the low-tweens or high single digits. The falling-off in participation is fairly steady: for every age-year above 17, about 10% of the population exits education up until the age of 26. The big increase in education enrolments that we’ve seen over the past couple of decades has really occurred in the 18-24 range, where participation rates (almost exclusively in universities, as we shall see) have increased enormously.

Figure 1: Participation rates in Education (all institutions) by Age, Canada, select years 1999-00 to 2023-24

Figure 2 shows current participation rates by age and type of postsecondary institution. People sometimes have the impression that colleges cater to an “older” clientele, but in fact, at any given age under 30, Canadians are much more likely to be enrolled in universities than in colleges. Colleges have a very high base in the teens because of the way the CEGEP system works in Quebec (I’ll come back to regional diversity in a minute), and it is certainly true that there is a very wide gap in favour of universities among Canadians in their mid-20s. But while the part rate gap narrows substantially at about age 25, it is never the case that the college participation rate surpasses the university one.

Figure 2: Participation Rates by Age and Institution Type, Canada, 2023-24

Figure 3 shows college participation rates by age over time. What you should take from this is that there has been a slight decline in college participation rates over time in the 19-23 age range, but beyond that not much has changed.

Figure 3: College Participation Rates by Age, Selected Years, 1999-2000 to 2023-24

Figure 4 uses the same lens as figure 3 only for universities. And it’s about as different as it can be. In 1999, fewer than one in ten Canadians aged 18 was in university: now it is three in ten. In 1999, only one in four 21 year-olds was in university, now it is four-in-ten. These aren’t purely the effects of increased demand; the elimination of grade 13 in Ontario had a lot to do with the changes for 18-year-olds; Alberta and British Columbia converting a number of their institutions from colleges to universities in the late 00s probably juices these numbers a bit, too. But on the whole, what we’ve seen is a significant increase in the rate at which young people are choosing to attend universities between the ages of 18 and 24. However, beyond those ages the growth is less pronounced. There was certainly growth in older student participation rates between 1999-00 and 20011-12, but since then none at all.

Figure 4: University Participation Rates by Age, Selected Years, 1999-2000 to 2023-24

So much for the national numbers: what’s going on at the provincial level? Well, because this is the Labour Force Survey, which unlike administrative data has sample size issues, we can’t quite get the same level of granularity of information. We can’t look at individual ages, but we can see age-ranges, in this case ages 20-24. In figures 5 and 6 (I broke them up so they are a bit easier to read), I show how each province’s university and college participation rates in 2000 vs. 2023.

Figure 5: University Participation Rates for 20-24 Year-olds, Four Largest Provinces, 2000-01 vs. 2023-24

Figure 6: University Participation Rates for 20-24 Year-olds, Six Remaining Provinces, 2000-01 vs. 2023-24

Some key facts emerge from these two graphs:

The highest participation rates in the country are in Ontario, Quebec, and British Columbia.

In all provinces, the participation rate in universities is higher than it is for colleges, ranging from 2.5x in Quebec for over 4x in Saskatchewan.

Over the past quarter century, overall postsecondary participation rates and university participation rates have gone up in all provinces; Alberta and British Columbia alone have seen a decline in college participation rates, due to the aforementioned decision to convert certain colleges to university status in the 00s.

Growth in participation rates since 2000 has been universal but has been more significant in the country’s four largest provinces, where the average gain has been nine percentage points, and the country’s six smaller provinces, where the gain has been just under five percent.

Over twenty-five years, British Columbia has gone from ninth to second in the country in terms of university participation rates, while Nova Scotia has gone second to ninth.

New Brunswick has consistently been in last place for overall participation rates for the entire century.

Just think: three minutes ago, you probably knew very little about participation rates in Canada by age and geography, now you know almost everything there is to know about participation rates in Canada by age and geography. Is this a great way to start your day or what?
Source link
February 12, 2025
Student Aid in Canada: The Long View

Note: this is a short version of a paper which has just appeared in issue 72:4 the Canadian Tax Journal. How short? I’m trying for under 1000 words. Let’s see how I do.

Canadian student aid programs existed in scattered forms since just after World War I but became a “national program” when the Dominion-Canadian Student Aid Program (DCSAP) was created in 1939. Under this program, the Government of Canada provided block cash grants to provinces who administered their own scholarship programs which provided aid based on some combination of need and merit. The actual details of the program varied significantly from one province to another; at the time, the government of Canada did not place much importance on “national programs” with common elements.

In 1964, this DCSAP was replaced by the Canada Student Loans Program (CSLP)—recently re-named the Canada Student Financial Assistance Program (CSFAP). This has always been a joint federal-provincial enterprise. But where the earlier program was a block grant, this program would be a single national entity run more or less consistently across all provinces, albeit with provincial governments still in place as responsible administrative agencies able to supplement the plan as they wished. Some provinces would opt out of this program and received compensation to run their own solo programs (Quebec at the program’s birth, the Northwest Territories in 1984 and Nunavut in 1999). The others, for the most part, built grant programs that kicked in once a student had exhausted their Canada Student Loan eligibility.

Meanwhile, a complimentary student aid program grew up in the tax system, mainly because it was a way to give money to students that didn’t involve negotiations with provinces. Tuition fees plus a monthly education amount were made into a tax deduction in 1961 and then converted to a tax credit in 1987. Registered Education Savings Plans (RESPs), which are basically tax-free growth savings accounts, showed up in 1971.

Although the CSLP was made somewhat more generous over time in order to keep up with rising student costs, program rules went largely unchanged between 1964 and 1993. Then, during the extremely short Kim Campbell government, a new system came into being. The federal government decided to make loans much larger, but also to force provinces in participating provinces to start cost-sharing in a different manner—basically, they had to step up from a student’s first dollar of need instead of just taking students with high need. Since this was the era of stupidly high deficits, provinces responded to these additional responsibilities by cutting the generosity of their programs, transforming from pure grants to forgivable loans. For the rest of the decade, student debt rose—in some cases quite quickly: in total loans issued doubled between 1993 and 1997.

And then, everything went into reverse.

In a series of federal budgets between 1996 and 2000, billions of dollars were thrown into grants, tax credits and a new program called “Canada Education Savings Grants,” which were a form of matching grant for contributions to RESPs. Grants and total aid rose; loans issued fell by a third, mainly between 1997 and 2001 (a recovering economy helped quite a bit). Tax expenditures soared, which due to a rule change allowing tax credits to be carried forward meant either students got to keep more of their work income or got to reduce their taxes once they started working.

Since this period of rapid change at the turn of the century, student aid has doubled in real terms. And nearly all of that has been an increase in non-repayable aid. Institutional scholarships? Tripled. Education scholarships? Quadrupled. Loans? They are up, too, but there the story is a bit more complicated.

Figure 1: Student Aid by Source, Canada, 1993-94 to 2022-23, in thousands of constant $2022

For the period from about 2000 to 2015, all forms of aid were increasing at about inflation plus 3%. Then, in 2016, we entered another period of rapid change. The Governments of Canada and Ontario eliminated a bunch of tax credits and re-invested the money into grants. Briefly, this led to targeted free tuition in Ontario, before the Ford government took an axe to the system. Then, COVID hit and the CSFAP doubled grants. Briefly, in 2020-21, total student aid exceeded $23 billion/year (the figure above does not include the $4 billion per year paid out through the Canada Emergency Student Benefit), with less than 30% of it made up of loans.

One important thing to understand about all this is that while the system became much larger and much less loan-based, something else was going on, too. It was becoming much more federal. Over the past three decades, provincial outlays have risen about 30% in real terms; meanwhile, federal ones have quadrupled. In the early 1990s, the system was about 45-55 federal-provincial; now, it’s about 70-30 federal. It’s a stunning example of “uploading” of responsibilities in an area of shared-jurisdiction.

Figure 2: Government Student Aid by Source, Figure 1: Student Aid by Source, Canada, 1993-94 to 2022-23, in thousands of constant $2022

So there you go: a century of Canadian student aid in less than 850 words. Hope you enjoyed it.

Source link

February 4, 2025