|
|
|
|
|
|
|
By Paul Vandenberg , Kirsty Newman , Milan Thomas
Digital technologies and EdTech could play a role in addressing the learning crisis underway in Asia and the Pacific.
A learning crisis affects many developing countries in Asia. Millions of children attend school but are not learning enough. They cannot read, write, or do mathematics at their grade level, and yet they pass to the next grade, learning even less because they have not grasped the previous material. The magnitude of the crisis is staggering: in low- and middle-income countries more than half of children are not learning to read by age 10.
At the same time, there is an emerging revolution in learning brought on by digital technologies . These are collectively referred to as educational technology or EdTech . The coincident emergence of a problem in education and a new approach to learning naturally makes us ask how one may be a solution for the other.
Edtech may be one part of the solution – but it should be a means not an end. Our guiding principle should be to first diagnose what is going wrong in a system and then identify which solutions are best suited to solve those problems.
Some causes of the learning crisis are well understood. The poor quality of teaching is a key factor. Teachers often lack subject knowledge and have not had adequate training. There are ways in which technology could address this – and so EdTech may be equally valuable in teaching teachers as it is in teaching students. By offering distance learning, EdTech can provide in-service training or combine online and in-person training (blended learning).
There is also evidence that teachers need better incentives. The idea is that that they can teach well but are not motivated to do so. It is not clear how EdTech can address this problem. Digitized school management systems could better track teacher performance (by tracking their students’ performance) and then linking to pay or other incentives. However, the main need is to design the incentive system; digital applications may only make that system more efficient.
Computer-assisted learning is the direct means by which EdTech can help students. It can be seen as a partial solution for two fundamental learning crisis problems: addressing students at different learning levels and completing the syllabus. A classroom contains students with a range of baseline learning levels and teachers are often incentivized to teach to the upper stratum, leaving many students behind. Furthermore, teachers are pressured to cover the syllabus by year’s end. They move on to new material even if students have not mastered previous lessons. This also leaves students behind.
The solution to both problems is, of course, more tailored teaching, but a teacher is hard-pressed to provide one-on-one tutoring to 30 or 40 kids. EdTech might help provide one-to-one instruction (e.g., one student to one tablet) so pupils can learn at their own level and pace. The evidence from rigorous assessments (largely in the United States) is that packages that use artificial intelligence to adjust to a student’s level can improve results, especially in math.
However, we need to be cautious. Most of the evidence comes from contexts in which the quality of teaching is already quite good and is much above the average in developing countries. Digital systems can also help increase the efficiency of formative assessment and make it more likely that such assessment will be conducted. Tracking of students’ learning, through data collection and analysis, can help to better monitor a student’s learning level and provide level-appropriate teaching and remediation.
Computer-assisted learning is the direct means by which EdTech can help students.
Edtech software, introduced in conjunction with other reforms, holds some promise. One notable success is Mindspark in India , which improves math and Hindi learning. It has been evaluated as an after-hours supplement and combined with human teaching assistance. More assessments of programs would be helpful.
There is also evidence that low-tech interventions for “teaching at the right level" can also have large impacts on learning. Careful analysis is needed to determine whether high-tech or low-tech solutions are best, given that low tech is less costly, and finance is a constraint in poor countries.
The COVID-19 pandemic has given a big push to EdTech. We can learn from these experiences but need to keep them in context. EdTech is being used to overcome the need to social distance. Teachers are teaching by video but not necessarily teaching better than when standing in front of a classroom. Zoom fatigue is a problem. More mass open online courses are being offered and are being taken up – but much of this is not for basic education and therefore does not address the learning crisis.
Supporting EdTech solutions comes with four caveats. First, new initiatives need to be well-designed to address specific weaknesses. Low-quality teacher training delivered partially online is no better than low-quality in-person training. The same applies to computer-assisted learning.
Second, computer-assisted learning is often used in schools or in after-hours programs at or near schools. Delivering as distance learning is trickier. It requires hardware and connectivity at home, which is not available to children in low-income households in developing countries and even developed ones.
Third, EdTech programs used outside normal classroom hours adds to the time children spend learning. This is good but it is not always clear whether the benefits are coming from EdTech, per se, or simply more time spent learning. Nonetheless, gamification and other techniques may make children want to spend more time learning.
Finally, let us keep in mind that good learning outcomes can be achieved without EdTech. Developed countries got results before the advent of EdTech. So too did good schools in developing countries.
To be effective, EdTech must address key causes of the crisis and be part of a larger package of reforms. Those reforms include teacher training, incentives, monitoring, teaching at the right level, remediation for underperforming students, and others.
Digital technologies have changed our lives in many ways, mostly for the good. EdTech could do the same by playing a role in addressing the learning crisis.
Published: 23 July 2021
Never miss a blog post. Get updates on development in Asia and the Pacific into your mailbox.
Adb blog team, browse adb.org, other adb sites.
ADB encourages websites and blogs to link to its web pages.
Giving compass' take:.
We connect donors to learning resources and ways to support community-led solutions. Learn more about us .
Systemic issues in funding drives education inequality and has detrimental effects primarily on low-income Black and Brown students. These students receive lower quality of education which is reflected through less qualified teachers,not enough books, technologies and special support like counselors and disability services. The lack of access to fair, quality education creates the broader income and wealth gaps in the U.S. Black and brown students face more hurdles to going to college and will be three times more likely to experience poverty as a American with only a highschool degree than an American with a college degree. Income inequality worsens the opportunity for building wealth for Black and Brown families because home and asset ownership will be more difficult to attain.
Read the full article about solutions for education inequality by Jermeelah Martin at United for a Fair Economy.
Our education funding system is broken. we can fix it., learning policy institute, nov 21, 2022, the funding gap between charter schools and traditional public schools, may 22, 2019.
Become a newsletter subscriber to stay up-to-date on the latest Giving Compass news.
Donate to Giving Compass to help us guide donors toward practices that advance equity.
© 2024 Giving Compass Network
A 501(c)(3) organization. EIN: 85-1311683
Livelihoods
Health and nutrition
Climate and environment
Emergencies
Gender equality
Policy and advocacy
View all countries
View all publications
View all news
What we stand for
Our history
Why partner with Concern?
Public donations
Institutions and Partnerships
Trusts and foundations
Corporate donations
Donations over £1,000
How money is spent
Annual reports
How we are governed
Codes and policies
Supply chain
Through to 2
Hunger crisis appeal
Donating by post and phone
Corporate giving
Emergency support
Concern Philanthropic Circle
Donate in memory
Leave a gift in your will
Wedding favours
Your donation and Gift Aid
Volunteer in Northern Ireland
Volunteer internationally
London Marathon
London Landmarks Half Marathon
Skydive for Concern
Start your own fundraiser
Charity fundraising tips
FAST Youth Ambassador
Knowledge Matters Magazine
Global Hunger Index
Learning Papers
Where we work
Research and reports
Latest news
Our annual report
How we raise money
Transparency and accountability
Donate today
Donate to Concern
Partner with us
Campaign with us
Buy an alternative gift
Other ways to support
Events and challenges
Schools and youth
Our Northern Ireland shops
Knowledge Hub
Knowledge Hub resources
Children across the UK are heading back to school in the coming weeks. However, 250 million children around the world will be left out of the classroom. Revised for 2024, here are 10 of the biggest problems facing education around the world.
Education can help us end poverty. It gives kids the skills they need to survive and thrive, opening the door to jobs, resources, and everything else that they need to live full, creative lives. In fact, UNESCO reports that if all students in low-income countries had just basic reading skills, an estimated 171 million people could escape the cycle of poverty . And if all adults completed their secondary education, we could cut the global poverty rate by more than half.
So why are 250 million children around the world currently out of school? We aren’t at a loss for reasons after the last few years. Here are the top 10 problems facing education in 2024.
Conflict is one of the main reasons that kids are kept out of the classroom, with USAID estimating that half of all children not attending school are living in a conflict zone — some 125 million in total. To get a sense of this as a growing issue, in 2013, UNESCO reported that conflict was keeping 50 million students out of the classroom. Last year alone, 19 million children in Sudan were out of school due to renewed conflict.
Education is a lifeline during a conflict, protecting children from forced recruitment and potential attacks, while giving them a sense of normalcy in times that are anything but. It’s also a critical element in reducing the chance of future conflicts in certain areas. However, despite international humanitarian law, schools have become targets of attacks in many recent conflicts. Many parents have opted to keep their children at home as a result. However, these are not easy years to make up. According to UNESCO, the first two years of the Syria crisis erased all the country's educational progress since the start of the 21st century. Recovering these missed years also takes more time and effort, with many Syrian children requiring psychosocial care that hinders a "normal" learning curve. Unfortunately, as conflicts become more protracted, they are also threatening to create multiple lost generations.
Violence can also carry over into the classroom. One UN study found that, while 102 countries have banned corporal punishment in schools, that ban isn’t always enforced. Many children have faced sexual violence and bullying in the classroom, either from fellow pupils or faculty and staff.
Children will often drop out of school altogether to avoid these situations. Even when they stay in school, the violence they experience can affect their social skills and self-esteem. It also has a negative impact on their educational achievement. Concern has addressed this head-on in Sierra Leone with our Safe Learning Model .
Climate change is another major threat to education. Extreme weather events and related natural disasters destroy schools and other infrastructure key to accessing education (such as roads), and rebuilding damaged classrooms doesn’t happen overnight.
Climate change also affects children’s health, both physical and emotional, making it hard to keep up with school (and at times making it hard for teachers themselves to focus on delivering a quality education). With climate change linked so tightly to poverty, it also leads families to withdraw their children from school when they can no longer afford the fees or need their children to contribute to the household income.
In agricultural communities, the harvest is both a vital source of food and income. During these periods, children are often required to skip school to help their families harvest and sell crops. Sometimes they'll be out of school for weeks at a stretch. Families who make their living from farming may also have to move around if they have herds that graze, or to harvest crops planted in different areas. This is also disruptive for children and their education.
When governments are dysfunctional, public servants aren’t paid. That includes teachers. In some countries, teachers aren’t paid for months at a time. Many have no choice but to quit their posts to find other sources of income or are moved to other districts.
As a result, schools often struggle to find qualified teachers to replace those who have left. But, without qualified teachers in the classrooms, children suffer the most. In sub-Saharan Africa, the World Bank estimates that the percentage of trained teachers fell from 84% in 2000 to 69% in 2019 (with no updates yet as to how the pandemic may have affected these numbers). The World Bank adds that teachers in STEM are especially hard to come by in low-income countries.
Although many countries provide free primary education, attending school still comes at a cost. Parents and caretakers often pay for mandatory uniforms and other fees. School supplies are also necessary. These costs alone can keep students out of the classroom.
According to UNICEF, adolescents are twice as likely to be out of school compared to younger children. Globally, that means one in five students between the ages of 12 and 15 is out of school. As children get older, they face increased pressure to drop out so that they can work and contribute to their family income.
One solution we’ve adopted at Concern is to help those who didn't complete their education learn many of the things they missed out on, including financial literacy, business management, and vocational skills.
In many countries around the world, girls are more likely to be excluded from education than boys. This is despite all the efforts and progress made in recent years to increase the number of girls in school. According to UNESCO, up to 80% of school-aged girls who are currently out of school are unlikely to ever start. For boys, that same figure is just 16%. This rate is highest in emergency situations and fragile contexts.
Many schools have no toilets (let alone separate bathrooms for boys and girls). This usually means more missed days for girls when they get their period. The World Bank estimates that girls around the world miss up to 20% of their school days due to period poverty and stigma.
Girls may also be pressured to drop out of school to help out their family, as we mentioned above with regards to taking a job. However, in many countries where Concern works, they may also be forced out of school to get married. Girls who enter into an early or forced marriage usually leave school to take care of their new families. According to the UN, 33% of girls in low-income countries wed before the age of 18. Just over 11% get married before the age of 15. In most instances, marriage and having children mean the end of a girl’s formal education.
We learned this the hard way with COVID-19. Even if the student body is healthy, they may be kept out of school if an epidemic has hit their area. Teachers might get sick, and families with sick parents may need their children to stay home and help out. Quarantines often go into effect.
The 2014-16 West African Ebola outbreak was a severe problem for education in countries like Liberia and Sierra Leone . Ebola put the education of 3 million children in these countries on hold. As a response, we worked with the governments of both countries to deliver lessons by radio. We also trained community members to work with small groups of children on basic reading and maths. As schools reopened, we shifted our focus to helping children get back into classrooms safely, but many kids still had a lot of catching up to do.
Even if a child goes to school in the town where they were born and grew up their entire life, they may face a language barrier in the classroom between their mother tongue and the official lingua franca used in education systems. In Marsabit county, Kenya , the first language for most children is Borana. Once students start school, they must learn two new languages to understand their teachers: Swahili and English.
UNESCO estimates that 40% of school-aged children don’t have access to education in a language that they understand. This is especially difficult for students who have migrated to a new country, such as Syrian refugee children being hosted in Türkiye : Not only do they have to switch from Levantine Arabic to Turkish, but they also have to learn an entirely new alphabet.
This dovetails with literacy, another key issue in education. If a student struggles with reading (even in their mother tongue), it can have a ripple effect on their ability to learn in all other subjects. Many students drop out if they feel like they can’t keep up, either due to the quality of the teaching or to a special accommodation they need for their learning that can’t be made.
Concern’s work is grounded in the belief that all children have a right to a quality education. We integrate our education programmes into both our development and emergency work to give children living in extreme poverty more opportunities in life and supporting their overall well-being. Our focus is on improving access to education, improving the quality of teaching and learning, and fostering safe learning environments
We've brought quality education to villages that are off the grid, engaged local community leaders to find solutions to keep girls in school, and provided mentorship and training for teachers. Last year alone, we reached 1.1 million people with education programmes across 10 countries.
Learn more about Concern's education programmes.
Share your concern.
What are the major problems facing american education today, the top 10 education problems in america and possible solutions.
America’s education system has come under fire from many different angles in recent years. Some say that our students are not being given the opportunities they need to be successful in a globalized world. Others maintain that our teachers are not receiving the proper training and support they need in order to be effective educators.
No matter where you stand on the issue, it is clear that there are many problems with America’s education system.
In this blog post, we will take a closer look at the top 10 education problems in America and explore possible solutions.
Table of Contents
1. lack of access to quality education.
One of the biggest problems facing America’s education system is the lack of access to quality education. This issue is especially prevalent in low-income and rural areas.
According to a National Center for Education Statistics report, only 60% of low-income students attend schools that offer a full range of academic courses.
This means that many students are not being allowed to take classes in subjects like science, technology, engineering, and math (STEM). This lack of access can have a major impact on a student’s ability to succeed in school and in life.
Solution: One way to solve this problem is to provide more funding for low-income schools. This would allow these schools to offer a broader range of courses and programs and hire more qualified teachers.
Another solution is to create more online schools. Online high schools have more flexibility in their curriculum . This can provide students with a better education than they would receive at a traditional public school.
Another serious problem facing America’s education system is the high dropout rate. According to a report from the National Center for Education Statistics, the dropout rate in the United States was 3.8% in 2017.
This means that nearly one in four students do not finish high school. The dropout rate is even higher for certain groups of students, such as low-income students and students of color.
Solution: One way to solve this problem is to provide more support for at-risk students. This could include mentorship programs, tutoring services, and financial assistance.
Another solution is to create alternative schools for students who are not thriving in a traditional school setting. These schools could offer a more flexible curriculum.
Another problem facing America’s education system is educators’ lack of cultural competency. This issue is especially prevalent in schools that serve a diverse student body.
Many teachers are not adequately trained to teach students from different cultures and backgrounds. As a result, these students may feel isolated and discouraged in school.
Solution: One way to solve this problem is to provide more training for educators on teaching diverse students. This training should include cultural competence, classroom management, and effective teaching strategies.
Another solution is to create more culturally diverse learning environments. This could be done by hiring a more diverse staff, incorporating a multicultural curriculum, and offering bilingual education programs.
One of the most controversial issues in America’s education system is standardized testing . These tests are used to measure student achievement and compare schools against each other.
However, many critics argue that these tests are not an accurate measure of student learning. They also place undue stress on students and teachers.
Solution: One way to solve this problem is to reduce the emphasis on standardized testing. This could be done by eliminating high-stakes tests or using them for diagnostic purposes only.
Another solution is to create alternative assessments that are more authentic and student-centered. These could include portfolios, projects, and presentations.
The other solution is to provide more support for students, teachers, and administrators who are under pressure because of standardized testing. This could include counseling services, professional development opportunities, and stress-reduction programs.
Another major problem facing America’s education system is inadequate teacher training. Many teachers are not adequately prepared to teach their subject matter, especially in high-need areas like math and science. As a result, students are not receiving the quality education they deserve.
Solution: One way to solve this problem is to provide more funding for teacher training. This would allow teachers to receive the proper education and certification they need to be effective educators.
Another solution is to create more incentives for teachers to pursue further education and professional development. This could include financial bonuses or paid time off for attending conferences and workshops.
One of the most pressing problems facing America’s education system is the unequal distribution of school funding. Property taxes are the primary source of funding for public schools, but this method disproportionately benefits wealthier communities.
As a result, schools in low-income areas often lack the resources they need to provide a quality education for their students.
Solution: One way to solve this problem is to increase federal funding for education. This would provide more money for schools in low-income areas.
Another solution is to redistribute funding from wealthy school districts to low-income school districts. This would help to level the playing field and provide all students with the resources they need to succeed.
Inequality is a big problem in America’s education system. According to a report from the National Center for Education Statistics, there are significant disparities in educational outcomes between different groups of students.
For example, Hispanic and African American students are more likely to drop out of school than white students. In addition, students from low-income families are more likely to have lower test scores and be less likely to go to college.
This inequality can significantly impact a student’s ability to succeed in school and in life.
Solution: One way to solve this problem is to provide more support for students from disadvantaged backgrounds. This could include tutoring, mentorship programs, and financial aid.
Another solution is to improve the quality of education in schools that serve these students. This could be done by providing more resources, hiring better teachers, and offering more challenging coursework.
One of the biggest problems facing America’s education system is the lack of parental involvement. According to a report from the National Center for Education Statistics, only about half of parents said they were very involved in their child’s education in 2015.
This can lead to a number of problems, including lower grades and test scores, higher dropout rates, and less engagement in school.
Solution: One way to solve this problem is to encourage parents to be more involved in their child’s education. This could be done through various methods, such as parent-teacher conferences, school-wide events, and classroom volunteering.
Another solution is to provide resources and information to parents about how they can help their children succeed in school.
Another big problem facing America’s education system is the use of ineffective teaching methods. In many cases, teachers are not properly trained to teach their students effectively.
As a result, students are often not learning the material as well as they could be. In addition, many schools do not use data-driven instruction, which means that they are not tailoring their teaching methods to the needs of their students. This can have a major impact on student achievement.
Solution: One way to solve this problem is to provide more training for teachers. This could include workshops, online courses, and mentorship programs.
Another solution is to use data-driven instruction. This means using data to identify the needs of students and then tailoring instruction to meet those needs. This can help to ensure that all students are receiving the best possible education.
Bullying is a serious problem in America’s schools. According to a report from the National Center for Education Statistics, 20.2% of high school students are bullied at school each year. This can lead to feelings of isolation , depression, and anxiety. It can also adversely affect students’ academic performance.
Solution: One way to solve this problem is to create a more positive school climate. This could be done by implementing anti-bullying policies and providing support for victims of bullying.
Another solution is to educate students about the effects of bullying and how to prevent it. This could be done through classroom lessons, assemblies, and counseling sessions.
Online learning can be the best solution to the problems facing America’s education system. Online learning offers several advantages over traditional classroom instruction, including the ability to tailor instruction to the needs of individual students, more flexible scheduling, and increased access to resources.
In addition, online learning can help to improve parental involvement and provide more support for students from disadvantaged backgrounds.
As the world becomes more globalized, it is crucial for students to receive a quality education that will prepare them for the workforce. Online learning can provide students with the skills they need to succeed in a variety of careers.
Additionally, online learning can help to close the achievement gap by providing all students with equal access to resources and instruction.
Although there are many problems with the American education system, we believe that each problem can be solved. We have outlined 10 of the most pressing issues and possible solutions.
However, this is only a starting point. We need your help to make a change. Contact High School of America today to learn more about how you can get involved in making a difference for future generations.
Together, we can provide every student in America with an excellent education and give them the opportunity to achieve their dreams.
No related posts.
What issues have the potential to define—or re define—education in the year ahead? Is there a next “big thing” that could shift the K-12 experience or conversation?
These were the questions Education Week set out to answer in this second annual “10 Big Ideas in Education” report.
You can read about last year’s ideas here . In 2019, though, things are different.
This year, we asked Education Week reporters to read the tea leaves and analyze what was happening in classrooms, school districts, and legislatures across the country. What insights could reporters offer practitioners for the year ahead?
Some of the ideas here are speculative. Some are warning shots, others more optimistic. But all 10 of them here have one thing in common: They share a sense of urgency.
Accompanied by compelling illustrations and outside perspectives from leading researchers, advocates, and practitioners, this year’s Big Ideas might make you uncomfortable, or seem improbable. The goal was to provoke and empower you as you consider them.
Let us know what you think, and what big ideas matter to your classroom, school, or district. Tweet your comments with #K12BigIdeas .
Out-of-school learning is often more meaningful than anything that happens in a classroom, writes Kevin Bushweller, the Executive Editor of EdWeek Market Brief. His essay tackling the relevance gap is accompanied by a Q&A with advice on nurturing, rather than stifling students’ natural curiosity. Read more.
Many teachers may have lost faith in the system, says Andrew Ujifusa, but they haven’t lost hope. The Assistant Editor unpacks this year’s outbreak of teacher activism. And read an account from a disaffected educator on how he built a coalition of his own. Read more.
Forty years since students with disabilities were legally guaranteed a public school education, many still don’t receive the education they deserve, writes Associate Editor Christina A. Samuels. Delve into her argument and hear from a disability civil rights pioneer on how to create an equitable path for students. Read more.
Staff Writer Corey Mitchell explains the inclusion problem at the heart of bilingual education. His essay includes a perspective from a researcher on dismantling elite bilingualism. Read more.
There’s agreement that we have a dysfunctional standardized-testing system in the United States, Associate Editor Stephen Sawchuk writes. But killing it would come with some serious tradeoffs. Sawchuk’s musing on the alternatives to annual tests is accompanied by an argument for more rigorous classroom assignments by a teacher-practice expert. Read more.
Drawing on his personal experience growing up in an Air Force family, Staff Writer Daarel Burnette II highlights emerging research on military-connected students. Learn more about his findings and hear from two researchers on what a new ESSA mandate means for these students. Read more.
Racial and economic segregation remains deeply entrenched in American schools. Staff Writer Denisa R. Superville considers the six steps one district is taking to change that. Her analysis is accompanied by an essay from the president of the American Educational Research Association on what is perpetuating education inequality. Read more.
Assistant Editor Sarah D. Sparks looked at the research on teaching consent and found schools and families do way too little, way too late. Her report is partnered with a researcher’s practical guide to developmentally appropriate consent education. Read more.
Are education leaders spending too much time chasing the latest tech trends to maintain what they have? Staff Writer Benjamin Herold explores the innovation trap. Two technologists offer three tips for putting maintenance front and center in school management. Read more.
Some colleges are rewriting the admissions script for potential students. Senior Contributing Writer Catherine Gewertz surveys this changing college admissions landscape. Her insights are accompanied by one teacher’s advice for navigating underserved students through the college application process. Read more.
Want to know what educators really think about innovation? A new Education Week Research Center survey delves into what’s behind the common buzzword for teachers, principals, and district leaders. Take a look at the survey results.
A version of this article appeared in the January 09, 2019 edition of Education Week as What’s on the Horizon for 2019?
Edweek top school jobs, sign up & sign in.
Top 8 modern education problems and ways to solve them.
| September 15, 2017 | 0 responses
In many ways, today’s system is better than the traditional one. Technology is the biggest change and the greatest advantage at the same time. Various devices, such as computers, projectors, tablets and smartphones, make the process of learning simpler and more fun. The Internet gives both students and teachers access to limitless knowledge.
However, this is not the perfect educational system. It has several problems, so we have to try to improve it.
Personalized learning is the most popular trend in education. The educators are doing their best to identify the learning style of each student and provide training that corresponds to their needs.
However, many students are at risk of falling behind, especially children who are learning mathematics and reading. In the USA, in particular, there are large gaps in science achievements by middle school.
Solution: Address the Needs of Low-Achievers
The educators must try harder to reduce the number of students who are getting low results on long-term trajectories. If we identify these students at an early age, we can provide additional training to help them improve the results.
In 2016, there were over 17,000 state secondary school children in the UK being taught in classes of 36+ pupils.
Solution: Reduce the Number of Students in the Classroom
Only a smaller class can enable an active role for the student and improve the level of individual attention they get from the teacher.
Today’s generations of students love technology, so the teachers started using technology just to keep them engaged. That imposes a serious issue: education is becoming an entertainment rather than a learning process.
Solution: Set Some Limits
We don’t have to see education as opposed to entertainment. However, we have to make the students aware of the purpose of technology and games in the classroom. It’s all about learning.
The students are overwhelmed with projects and assignments. There is absolutely no space for internships and volunteering in college .
Solution: Make Internships and Volunteering Part of Education
When students graduate, a volunteering activity can make a great difference during the hiring process. In addition, these experiences help them develop into complete persons. If the students start getting credits for volunteering and internships, they will be willing to make the effort.
Due to the fact that technology became part of the early educational process, it’s necessary for the parents to observe the way their children use the Internet at home. They have to help the students to complete assignments involving technology.
What about those parents who don’t have enough time for that? What if they have time, but want to use it in a different way?
Solution: Stop Expecting Parents to Act Like Teachers at Home
The parent should definitely support their child throughout the schooling process. However, we mustn’t turn this into a mandatory role. The teachers should stop assigning homework that demands parental assistance.
Although we transformed the educational system, many features of the curriculum remained unchanged.
Solution: Eliminate Standardised Exams
This is a radical suggestion. However, standardised exams are a big problem. We want the students to learn at their own pace. We are personalizing the process of education. Then why do we expect them to compete with each other and meet the same standards as everyone else? The teacher should be the one responsible of grading.
Can we really expect all teachers to use technology? Some of them are near the end of their teaching careers and they have never used tablets in the lecturing process before.
Solution: Provide Better Training for the Teachers
If we want all students to receive high-quality education based on the standards of the system, we have to prepare the teachers first. They need more training, preparation, and even tests that prove they can teach today’s generations of students.
A third of the employers in the UK are not happy with the performance of recent graduates. That means the system is not preparing them well for the challenges that follow.
Solution: More Internships, More Realistic Education
Practical education – that’s a challenge we still haven’t met. We have to get more practical.
The evolution of the educational system is an important process. Currently, we have a system that’s more suitable to the needs of generations when compared to the traditional system. However, it’s still not perfect. The evolution never stops.
Author Bio: Chris Richardson is a journalist, editor, and a blogger. He loves to write, learn new things, and meet new outgoing people. Chris is also fond of traveling, sports, and playing the guitar. Follow him on Facebook and Google+ .
Tags: solutions
You have full access to this open access article
There is a long-standing lack of learner satisfaction with quality and quantity of feedback in health professions education (HPE) and training. To address this, university and training programmes are increasingly using technological advancements and data analytic tools to provide feedback. One such educational technology is the Learning Analytic Dashboard (LAD), which holds the promise of a comprehensive view of student performance via partial or fully automated feedback delivered to learners in real time. The possibility of displaying performance data visually, on a single platform, so users can access and process feedback efficiently and constantly, and use this to improve their performance, is very attractive to users, educators and institutions. However, the mainstream literature tends to take an atheoretical and instrumentalist view of LADs, a view that uncritically celebrates the promise of LAD’s capacity to provide a ‘technical fix’ to the ‘wicked problem’ of feedback in health professions education. This paper seeks to recast the discussion of LADs as something other than a benign material technology using the lenses of Miller and Rose’s technologies of government and Barry’s theory of Technological Societies, where such technical devices are also inherently agentic and political. An examination of the purpose, design and deployment of LADs from these theoretical perspectives can reveal how these educational devices shape and govern the HPE learner body in different ways, which in turn, may produce a myriad of unintended– and ironic– effects on the feedback process. In this Reflections article we wish to encourage health professions education scholars to examine the practices and consequences thereof of the ever-expanding use of LADs more deeply and with a sense of urgency.
Student facing dashboards: one size fits all.
Explore related subjects.
Avoid common mistakes on your manuscript.
Effective feedback has long been recognised as a fundamental catalyst for effective learning (Butler & Winne, 1995 ; Hattie & Timperley, 2007 ). However, learners in higher and health professions education (HPE) are consistently dissatisfied with feedback and report feedback provision as insufficient, a notion that is consistently disputed by supervisors and that many interventions to improve feedback delivery have not been wholly successful in rectifying (Boud & Molloy, 2013 ; Carless, 2006 ; Deeley et al., 2019 ; Ossenberg et al., 2019 ).
Progress in educational technologies and learning data analytics offer new opportunities to structure and deliver personalised feedback efficiently to learners. Indeed, over the last few decades, the higher education literature has been characterised by critical commentary and research on how educational technologies have the potential to, and are already, reconfiguring relationships between lecturers and students, and altering the learning behaviour of student learning itself (Kitto, 2003 ). In higher and health professions education, the potential of educational technologies such as learning analytics, machine learning and artificial intelligence (AI) is treated with optimistic caution (Kitto et al., 2024 ). But what is largely absent from this literature is a theorization of the nature of such technological tools in terms of their larger role in the organization of social order, and more specifically, in the conduct of health professions education itself.
Our focus in is on one specific learning technology, that of student-facing, technology-mediated, learning analytics dashboards (LADs). As a Reflections contribution, this paper does not adhere to the traditional scientific format of introduction, methods, results and discussion. Rather it represents a summary of many discussions held over time, with reference to a wide literature and the many considerations we have grappled with as part of developing and implementing a LAD locally.
LADs are positioned within the literature as a feedback intervention (Clow, 2013 ), usually presented as: “single displays that aggregated different indicators about learners, learning processes and or learning contexts into one or multiple visualizations”, so the information can be monitored at a glance (Schwendimann et al., 2017 ). At its most basic, a LAD employs descriptive analytics to provide an overview of a learner’s progress whereas a state-of-the-art LAD (at the time of writing this paper) integrates multiple data sources (e.g., assessment, attendance, clinical skills checklists data, etc.) and multiple analytical levels (e.g., (Few, 2007 ); see also (Boscardin et al., 2018 ), and discussed further later).
To illustrate what we mean by a LAD, we have drawn upon a combination of figures and descriptions found in the literature and ‘case study’ examples we created from an amalgam of possible LAD design possibilities (see Fig. 1 for an example of a LAD).
An example Learning analytics dashboard (LAD) in medical education that presents a comprehensive, visual overview of student progress (Boscardin et al., 2018 )
For learners, LADs are posited to facilitate self-reflective learning through visualization, highlighting key performance moments and often comparing individual performance to class averages (Susnjak et al., 2022 ). For instructors, LADs construct insights into learners’ performance and progress, aiding academic advising and study plan development (Gutiérrez et al., 2020 ). Some LADs also employ predictive, machine learning algorithms to detect potentially problematic behaviours indicative of being at-risk and generate academic recommendations, such as remediation suggestions based on identified academic issues. At the institutional level, data gathered from a LAD could aid in the customisation of educational strategies that would meet regulatory or accreditation needs. In short, by integrating multiple data sources and analytical levels about student performance LADs are meant to provide a deeper understanding and better facilitation of students’ learning processes, enhance communication, support decision-making, and improve academic outcomes for both learners and instructors (Bodily & Verbert, 2017 ; Masiello et al., 2024 ). In short, LADs provide, or are purported to provide, high quality feedback.
In general, the LAD literature has been quite limited, focusing on dashboard architecture and components (Bodily et al., 2018 ), design and technical considerations, and the lessons learned in implementation (Durojaiye et al., 2018 ; Herodotou et al., 2019 ); the needs and ways of linking dashboard content and visualization and learning science concepts to improve the accuracy and effectiveness of LAD (Sedrakyan et al., 2019 ; Teasley, 2018 ); and, in health professions education (HPE), the development and implementation of a LAD (Boscardin et al., 2018 ). While there are some recent exceptions in the wider literature (e.g., (Paulsen & Lindsay, 2024 ), taken as a whole, this body of research to date tends to frame the promise of LADs in an instrumental mechanistic manner, as an efficient and rather benign technological approach to feedback (Banihashem et al., 2022 ). There is little to no critical analyses of what role and effects a LAD might have on learner performance and learner relationships with their peers, instructors or the educational institutions in which they are enrolled. Rather the literature has a seductive tone, suggesting LADs can provide all the promises of a ‘technical fix’ (Robins & Webster, 1989 ) underpinned by a belief that ‘wicked’ (Rittel, 1973 ) educational problems like feedback (Deeley et al., 2019 ) can be resolved through the application of a technological artifact (that is, a LAD) without any unintended consequences.
We attempt to address this gap in the literature using the lens of the technological society (Barry, 2001 ). Using Barry’s heuristic framework as a conceptually coherent means by which to explore the relationships between LADs and the governing of medical education, we open discussion as to the role and effects LADs might have, how they might act directly on the student and instructor(s).
First, we outline the concept of the Technological Society and link this to the explicit agenda of encouraging self-governance of medical students through information technology, in this case LADs. We will show how using this conceptual framework can serve to unpack the potential impact of the assumptions behind, design of the functions and deployment of LADs on medical student populations. Specifically, we will consider how a LAD, as a technical device, acts as a political technology (see later) in the shaping of the learning relationship between technology, student and lecturer, and the downstream effects this reshaped relationship may have on student behaviour. Before doing so, we reflect on our interest in this topic.
Positionality “reflects the position that the researcher has chosen to adopt within a given research study” (Savin-Baden & Major, 2013 , p.71). It influences both how research is conducted, its outcomes, and results (Rowe, 2014 ). The study was initially developed from ongoing, local discussions about introducing programmatic assessment (PA) (Schuwirth & Van der Vleuten, 2011 ) into a medical undergraduate degree programme (an MBBS) and presenting the assessment information collected from various sources to learners via a LAD. As part of this process, we accessed a wide range of literature about LADs, and were surprised at its lack of criticality and theorization.
We considered our positions and relationships with this literature and our early stage “on-the-ground” experiences of developing a LAD for local purposes (which at the time of the drafting of this article was yet to be completed and evaluated) continually and critically in view of: our disciplinary backgrounds (psychology but working in medical education [JC], sociology [SK], engineering [ON], English [MC]), levels of knowledge and perspectives on assessment and feedback in health professions education and learning analytics. For example, a large part of ON’s role was to support the development and implementation of LADs locally, so she brought much understanding of the possibilities and limitations of learning analytics and visualisation thereof. JC, MC and SK had less technical expert knowledge and more “etic”, critical views.
The relationship between information technologies and governing contemporary western societies has been widely explored. More than 30 years ago, inspired by the ideas and works of Michel Foucault on the operations of power in modern society, Peter Miller and Nikolas Rose (Miller & Rose, 1990 ; Rose & Miller, 1992 ) alluded to the infrastructural nature of information technologies through an exposition of the nature of political rationalities and technologies of government. Political rationalities are the discourses where power is exercised and where moral justifications are made for the exercise of that power (Rose & Miller, 1992 ). When a problematic aspect of governing is identified (e.g., student dissatisfaction with feedback quality and quantity), political rationalities are translated into technologies of government that shape sectors of society into desirable, implementable forms (Miller & Rose, 1990 ). Through these technologies, authority seeks to “shape, normalize and instrumentalize the conduct, thought, decisions and aspirations of others” (Miller & Rose, 1990 , p.8) while reaching their own objectives and desires (e.g., designing the LAD in a certain way to direct how feedback is delivered, how learners interact with the dashboard in order to acquire knowledge and skills to become competent professionals in the workplace).
Andrew Barry’s concept of the Technological Society places information technology at the centre of governing, where citizens must now actively use and interact with technology to maximise their choices and demonstrate mastery and self-responsibility over the conduct of their lives (Barry, 2001 ). Using this lens, a LAD is conceptualised as being inherently political, and functions as a technology of governing in the Foucauldian sense of creating the conditions of possibility in which individuals can conduct themselves (Foucault, 1991 ; Hamann, 2009 ). Positioning an LAD in a technology society highlights its dual nature, it is both:
‘…a technical device, conceived of as a material or immaterial artefact, and a technology, a concept which refers not just to a device in isolation but also to the forms of knowledge, skill, diagrams, charts, calculations and energy which makes its use possible’ (Barry, 2001 , p.9) (see also (Akrich, 1992 ; Deleuze, 1988 )).
This notion of technical devices as instrumental material objects which have technological capacities (governmental) and their mutability when translated into action, has been utilised to study socio-technical configurations of educational delivery, use by faculty, and reception and use by students within the higher education sector. These studies have found unintended effects of technological devices ranging from: purportedly unethical behaviour of students in the learning and assessment process, re-organisation of the relationship between student, faculty and the university, ironic performances of student freedom in association with educational technologies, and at times adverse re-representation of student behaviour and concomitantly the construction of student subjectivity (i.e., ‘good’ or ‘bad’) (Kitto, 2003 ; Kitto & Higgins, 2003 , 2009 , 2010 ; Kitto & Saltmarsh, 2007 ). For example, think of the advent of online education within the higher education sector in the late 1990s. Designed to democratise education by overcoming the tyranny of distance and to facilitate lifelong learning amongst adult learners, online education was position as a solution to many changes in society impacting the delivery of higher education: threats of globalization, the increase in use of information technologies to deliver education, emphasis on life-long learning, changes in the demographics, and needs/choices of students. Formerly disenfranchised learners (full-time workers, rural impoverished populations) were now being positioned to access top ranked tertiary education more cost effectively at a distance and in their own time frames (Robins & Webster, 2002 ). However, while such technical devices can enact political programs at a distance, they can also act produce outcomes that act against their intended political objectives (Barry, 2001 ). In the online education sector this took the form of the rise of disreputable ‘digital diploma mills’ (Noble, 1998 ), leading to reputational damage which still plagues the sector on a global scale.
LADs supposedly offer a holistic view of a learner’s progress, consolidating visualised assessment data points on a one-stop information learners’ hub (Boscardin et al., 2018 ). The claim is that a LAD facilitates learners and educators to better understand individual learner performance by incorporating assessment (summative and formative), attendance, clinical skills checklist data, and so on. Having the ability to visualise connections between competencies and assessment ostensibly also allows for customisation of educational strategies based on accreditation needs (Chan et al., 2018 ). This capacity is made possible through the different levels of learning analytics include descriptive, diagnostic, predictive, and prescriptive analytics, each offering unique insights into data patterns and facilitating informed decision-making. We discuss these different levels of learning analytics in turn.
The most common, and simplest function and form of feedback is descriptive analytics. For example, (Han et al., 2021 ) developed a student dashboard that informed students about their engagement levels and interactions with peers. Diagnostic analytics supposedly adds an extra dimension to descriptive analytics by offering insights into why something occurred, typically by discerning patterns and trends within the data. For example, (Aljohani et al., 2019 ) presented an LAD that utilized log data from a Learning Management System (LMS) to uncover student behavioural patterns and attitudes. It compared each student’s engagement level with that of their peers, offering personalized learning statistics along with comparisons to class averages and top-performing peers, to promote self-awareness and aid in performance assessment.
Applying a technological society lens to these functions highlights the manifestation of three political functions and techniques of government: (1) in a technological society the notion that students, via technological means, are expected to interact in a self-governing way is a core political rationale, (2) through this interaction they are expected to come to know themselves, through technological intermediaries, in order to be able to work on themselves, (3) to do this they must direct that interaction by placing themselves in an extended web of connections with other people, institutions and forms of knowledge (Barry, 2001 ). In this case, the LAD already places them within such a web of connections through the combining of diagnostic and descriptive functions. Supposedly high-fidelity data about a student’s performance is analysed, compiled, (re)represented in visual form to show individual performance and how their progression sits in relation to a class of students (see Fig. 2 ).
In this respect, a LAD contains all the hallmarks of a Foucauldian panopticon, an ‘electronic panopticon’ (Kitto, 2003 ):
It refers individual actions to a whole that is at once a field of comparison, a space of differentiation and the principle of a rule to be followed. It differentiates individuals from one another…. It measures in quantitative terms and hierarchises in terms of value the abilities, the level, the ‘nature’ of individuals. It introduces, through this ‘value-giving’ measure, the constraint of a conformity that must be achieved.. it compares, differentiates, hierarchises, homogenizes, excludes. In short, it normalizes. (Foucault, 1977 , p.182–183).
Individual - Cohort comparison presented in a hypothetical LAD
A LAD could be designed to simultaneously provide this type of a ‘normalising gaze’ to enable representatives of the medical school to work on student interventions when needed, and for the student, to give a picture of their ‘normality’ within their cohort (See Fig. 2 ). The LAD, or more accurately the data presented by the LAD, could act as the starting point for intervention by the school, by the student themselves in isolation, or in partnership with one another to improve the student performance.
This notion of the construction of panoptic techniques in education via technical means to normalise student populations is a well-worn scholarly path (Foucault, 1977 ; Kitto, 2003 ). What is new here is when seen through a Technological society lens, the problematic aspect of the combination of panoptic techniques under the conditions of governing via information communication technologies in a Technological Society becomes apparent. Now, multiple forms of data are connected to provide a ‘diagnosis’ not only of performance in student examinations, but of levels of interactivity within their curricular activities and with the LAD itself. Are the students completing all their activities? Are they interacting with enough frequency with the LAD (made visible by student log data) - as a demonstration of being a good interactive technological student-citizen seeking self-improvement? (see Fig. 3 ).
Student log data and completion rates visualised via a hypothetical LAD
LADs are not simple techniques of a disciplinary society in the Foucauldian sense (you must do this). In a governmental technological society, they are advanced liberal technologies that seek to create self-governing capacities of students (you may do this) through regulated choices. The conditions of possibility for optimal self-governance (Rose, 1993 ), are provided by LADs by managing and moulding learners in specific ways. How the LADs data is used by those who govern is, of course, dependent on the local cultural and structural idiosyncrasies of the medical school itself (predilections of leaders, accreditation pressures etc.). Think for instance, of remediation sessions recommended for ‘recalcitrant’ students for not completing the skills checklist. The threshold for recommending such, and precisely what is recommended, will differ from institution to institution: governing via technical means is always context bound (Barry, 2001 ).
Two more functions - predictive and prescriptive analytics - provide a further layer of complexity, making LADs something more than a simple panoptic technique to shape student population and individual behaviour. They are also saturated with ways of thinking about how to provide the optimal conditions for the student-citizen to self-govern, which these student-citizens must learn to navigate to properly self-govern.
Under advanced liberal government, the ‘free’ citizen ironically, is always bound in time and space within assemblages of governing that set standards to evaluate their performance as well as that of institutions (think medical school accreditation standards and practices). This requires a system of navigation for the individual/institution to properly self-govern, it requires expertise and experts:
Certain, civilised modes of conducting one’s existence are identified as normal, and simultaneously to be bound to those ‘engineers of the human soul’ who will define the norm and tutor individuals as the ways of living that will accomplish normality. (Rose, 1999 , p.76).
With predictive and prescriptive analytics, this relationship becomes quite complex. Predictive analytics uses current or past data to inform future outcomes– often through machine learning algorithms. Rather than simply presenting raw log data, many dashboards process this information using machine learning models or algorithms to provide insights (Afzaal et al., 2021 ; Gutiérrez et al., 2020 ). For example, Herodotou et al. ( 2019 ) used LMS log data to predict student assignment submission and course completion, and to identify those considered “at risk” (see also (Gutiérrez et al., 2020 ; Mavrikis et al., 2019 )) (the last being a constant pre-occupation in advanced liberal societies).
Prescriptive analytics aims to provide solutions for determining what actions should be taken. They tend to utilise predictive analytics to infer potential actions leading to positive outcomes, often in the form of recommendations based on data collected from various sources such as LMS. Examples include real-time recommender-type dashboards introduced by (Bodily et al., 2018 ) and (Sansom et al., 2020 ).
As previously mentioned, a key aspect of advanced liberal ways of rule in technological societies is to enact programmes of government that can create the conditions of possibility for individual active and self-responsiblized comportment (Barry, 2001 ). What is interesting in the above description of the predictive and prescriptive functions of a LAD and its design as a technology of governing is that it seemingly sets up the foundation for a contradictory interplay between two key diagrams of social organisation, that of a panopticon (Foucault, 1977 ) and oligopticon (Latour, 2005 ). As previously outlined, the panopticon is a political technology that serves to individualize and normalize through a system of continual clear surveillance, characterized by classification and judgement. It governs populations by instilling compliance and optimize the capacities of the individual to maximize their social and economic utility (Rose, 1999 ). The panoramic view of the panopticon (and the knowledge of its existence by the observed) is in stark opposition to the oligopticon, which consists of multiple narrow views of a complex and connected landscape that can be made blind by the smallest disruption (Gad & Lauritsen, 2009 ). Inherently fragile, “they see much too little… but what they see, they see it well… sturdy but extremely narrow views of the (connected) whole are made possible—as long as connections hold (Latour, 2005 , p.181). In an information technology context, the success of oligopotic ‘surveillance is the result of situated, cooperative work that involves humans and nonhumans. Effective surveillance is not established by an individual actor but is accompanied by a network’ (Gad & Lauritsen, 2009 , p.53).
The fragility of these connections when the LAD is deployed as a mechanism of feedback is everpresent. Let’s look more closely at the rationale behind the communication channel or feedback mechanism of LADs. The aim is enhancing personalized learning through the full or partial automation and streamlining of feedback processes. Usually, the goal is to institute this longitudinally throughout a programme of learning, such as through a medical degree, with the potential for expansion to the residency level (postgraduate) and the selection process. The idea is that this would provide a representation of one’s medical education journey, aiding students in understanding themselves and their educational needs. This is characteristic of a technology of governing in a Technological society where the political rationality behind the key mechanism of organizing the activities of individual citizens, is self-directed lifelong learning that is supported by “constant forms of feedback” that are technologically mediated (Barry, 2001 ). But like all technologies of governing, it is a ‘congenitally failing operation’ (Miller & Rose, 1990 ) and thus, “different problems of context or locale or knowledge will have to be taken into account” (Barry, 2001 , p.16).
A LAD can visualise connections between competencies and assessment (see Fig. 2 ). While a tantalising proposition for educators, this assumption fails to examine who or what is making the connections that form the visual displays from which students can become ‘experts’ of themselves. The power of the display is made manifest by algorithms interpreting the data and imputing meaning onto the connections which are, through interaction with dashboard, subsequently situated within the body of the student by the student themselves and at times, with assistance by faculty in the form of feedback. This is a complex socio-technical assemblage in that it contains relationships between bodies and machines that can act as multiple translation points in different moments within multiple forms of feedback performances, such as– (1) individual student interacting with the LAD to ‘assess’ their performance and interpret automated feedback (2) clinical instructor interacting with the LAD to ‘assess’ the student’s performance and engage in a further interpretation of the automated feedback (3) student and instructor interacting together with the LAD to construct a shared meaning of the visual displays of ‘assessment’ of performance and automated recommended learning needs.
In socio-material terms the performance of these socio-technical assemblages creates a representation of the student’s bodily performance, but as ‘social agents [students] are never located in bodies and bodies alone’ (Law, 1992 , p.382–384), they are cyborgs, human and non-human hybrids (Harraway, 1991 ) that are stabilized and ‘purified’ (Latour, 1993 ) as human or technical in different points in time and space. Often they are ‘purified before [we] even have the chance to interrogate their hybridity’ (Michael, 1998 , p.134) This directly effects how the translation and interpretation of human practices via databases which are abstractions from actual bodily practices (see (Lyon, 2001 ), are shaped and used in the process of governing populations and the training of individuals within Technological Societies (Barry, 2001 ; Deleuze, 1992 ; Poster, 1990 ). If the student’s performance is an outcome of an array of bodies, representational devices such as databases, textual and visual displays, alongside actual in situ offline performances (which are not accounted for in LADs), then the challenge is about where exactly is the student’s performance located? And who, in the event of failure, is responsible– the machine or the human?
In practice within, for example, a medical school context, we argue that this will likely be resolved in interaction, through configurations of the ‘microphysics of power’ (Foucault, 1977 ) in the performance of the relationship between the student, LAD and instructor. The LAD is deployed to stand in as the medical school’s mediator of judgement, which on occasion is supplemented by an instructor’s interpretation of it. The data displayed is the student. But what of the role of algorithm generating the connections between different forms of data that further construct the student’s performance? Is this a new ‘expert’ Rose ( 1999 ) within advanced liberal Technological Societies? Within the mainstream LAD literature this aspect of LADs seems to be ‘blackboxed’ (Akrich, 1992 ; Callon, 1990 , 1992 ; Callon & Latour, 1982 ; Callon & Law, 1989 ), normalized to the point where it is just a natural part of the ecology of a health professions educational infrastructure that is transfer ready. This is an issue of:
‘…no matter how controversial their history, how complex their inner workings, how large the commercial or academic networks that hold them in place, only their input and output count’ (Latour, 1987 , p.3).
In the case of the LAD in health professions education, input is interactivity (the diagram of social organization in technological societies (Barry, 2001 ) of the student, and output is the calculation of their learning performance. As an aside, maybe this kind of input and output is feasible with straightforward events (e.g., attended class) but we are challenged to see how complex, situated and interpretive learning processes such as interprofessional education and professionalism could be ‘flattened’ into quantifiable and comparable measures with any degree of fidelity.
In essence, in instances of the full automation of the feedback function in the LAD the role of ‘expert’ in advanced liberal Technological society is being delegated to the automated feedback functions, to non-human algorithms divorced of interpretation informed by context. The calculation of student performance and its representation in the visual displays coupled with recommendations is a ‘blackbox’ that the student, by themselves, cannot unpack (see example Fig. 4 ). The source and veracity of the learning recommendations cannot be questioned, cannot be negotiated with. In the context of a near future where Artificial Intelligence (AI) becomes central to the interpretation of data displayed on the LADs, the problematic situation of the unquestionable and unnegotiable recommendations of LADs could be compounded by the possibility of AI hallucinations relayed to student and instructor, in the form of questionable learning remediation recommendations.
Hypothetical LAD Feedback Visual Display
From where we stand, full automation of the LAD feedback in medical education could produce three potential outcomes. Firstly, as outlined by Kitto et al. ( 2024 ) depending on the stage of education and training, learners may be more predisposed to LAD types of machine learning guidance (think transitioning into first clerkship years in UGME). Faced with the anxiety and uncertainty around the impossibility of mastery over constantly evolving healthcare knowledge and skills, uncertainty about their own gaps, knowledge, and uncertainties around variations in clinical instructor styles of practice and teaching, students looking for certainty in ways to progress through their degree may rush to uncritically embrace LAD guidance. To combat this tendency, inserting the socio-cultural context of health professions student learning could be a way to strengthen the connection between the LAD learning recommendations and compliance amongst students. The question is how to do this in a high-fidelity way, how can this be built into the LAD as a socio-technical assemblage? Given the ‘hallucination’ concern, teaching students how to account for the possibility of errors in the form of hallucinations and other shortcomings of nascent machine learning tools to avoid erroneous learning behaviour (Kitto, 2024 ) and in this case, avoid complying with mis-informed LAD learning recommendations, is critical. But in the case of the deployment of fully automated LAD learning recommendation algorithms (unmediated by humans), it is an impossibility as the source of guidance generated out of LADs is blackboxed, opaque and immutable.
Secondly, and conversely, there is the possibility of a breakdown in trust within student populations and the possibility of, “critical questioning [being] more likely to happen if the student has been given an underlying reason to be a little distrustful of the classifier” (Kitto et al., 2018 , p.455). We suggest that this more than likely to occur within the learning analytics community which has yet to pursue the question of not only how classification schemas can shape worldviews and order human interactions in some ways, and simultaneously disorder them in others, but also in terms of how imperfect a classifier in and of themselves can be (see (Bowker & Star, 2000 ). In other words, in the case of lived reality of a student’s learning performance being mis-aligned with the calculations made by the LAD, their lived experience may trump LAD judgments and recommendations and lead to mistrust and non-compliant learning behaviours.
Thirdly, when data and analytics are regarded and lauded as neutral, objective and “as evidence of what will happen” (Prinsloo, 2017 ), students learn that there is only one version of reality when what data analytics provide is only one of many representations of reality. This is particularly problematic in health professions education given the weight that has already been allotted to evidence-based decision making in the field of medicine and healthcare. Outside the fields of medicine and healthcare, critics already recognise that transposing evidence-based management to education is limiting:
On the research side, evidence-based education seems to favor a technocratic model in which it is assumed that the only relevant research questions are questions about the effectiveness of educational means and techniques, forgetting, among other things, that what counts as ‘effective’ crucially depends on judgements about what is educationally desirable. On the practice side, evidence-based education seems to limit severely the opportunities for educational practitioners to make such judgements in a way that is sensitive to and relevant for their own contextualized settings (Biesta, 2007 , p.5).
A health professions education facilitated by a technocratic approach to learning could exacerbate the positivist tendency inherent in evidence-based medicine and possibly reduce the student’s horizon of critical inquiry. Instead of relying on data and metrics to produce an ‘objective’ representation of reality (also referred to as a representationalist view), we could look to “a transactional view of evidence, data and analytics [which] acknowledges the incompleteness, the limitations and the possibility that the insights generated from analytics are, at best, provisional” (Prinsloo, 2019 ).
So, drawing on our knowledge of the literature and the reflections presented to this point, what are we to make of this type of analytics-driven feedback? Whether automated or partially automated, LADs must be understood by all stakeholders as inherently imperfect and, as such, all stakeholders, especially students, should be empowered to engage productively with data-driven feedback rather than just being passive recipients (Kitto et al., 2018 ). The question then is: how are the conditions of this student ‘empowerment’ in relation to LADs to be constructed? Any contemplation of questions such as these must be addressed with the knowledge that, ‘technology both creates systems which close off other options and generates novel, unpredictable and indeed unthinkable, options (Callon, 1992 ).
These caveats should drive us toward doing more thoughtful empirical research in this topic area. Clearly, the situated performances of different LADs will produce different representations and content, different pedagogical and infrastructural conditions, and constraints. These nuances do matter: our point is that design, context and performance of a LAD will have predictable and unpredicable (un)intended effects. Therefore, there is a pressing need for empirical and critical analyses of the role and effects a LAD might have on learner performance and learner relationships with their peers, instructors or the educational institutions in which they are enrolled, and the implications of particular manifestations of a LAD thereon.
We have put forward one way to map out the educational effects through an explicit recognition of the LAD as situated within a Technological Society, a society that is information technology dense and highly political. When designing an LAD for health professions education, one must think beyond the technical and instrumental and consider one’s role in the designing of people, in this case healthcare professionals. These are now technological citizens, expected to be lifelong learners capable of operating in information technology dense healthcare systems, able to receive constant feedback and adapt. Grappling with the precariousness of the use of technical means to produce feedback systems that create an interactive type of citizen is, and will continue to be, a ‘wicked’ problem requiring constant reflection.
In conclusion, we finish with a final argument that the core and ongoing question concerning feedback does not concern the creation of a ‘technical fix’ to the problem of more feedback (which students and educators often mistakenly cry out for), rather our attention should be focused on the nature, timing and deployment of appropriate feedback to the learner and their learning situation. Even more crucially, the creation of feedback content and systems must be designed in a way that is cognisant of their potential myriad unintended learning consequences, in order to be able to try and delimit them when and where possible. We suggest that looking through the lens of a Technological Society can help us this agenda whereby artefacts such as LADs can be more critically and deliberately engaged technically and politically in the construction of future healthcare professionals.
No datasets were generated or analysed during the current study.
Afzaal, M., Nouri, J., Zia, A., Papapetrou, P., Fors, U., Wu, Y., Li, X., & Weegar, R. (2021). Explainable AI for data-driven feedback and intelligent action recommendations to support students self-regulation. Frontiers in Artificial Intelligence , 4 . https://doi.org/10.3389/frai.2021.723447
Akrich, M. (1992). The de-scription of technical objects. In W. E. Bijker, & J. Law (Eds.), Shaping technology- building society: studies in sociotechnical change . The MIT Press.
Aljohani, N. R., Daud, A., Abbasi, R. A., Alowibdi, J. S., Basheri, M., & Aslam, M. A. (2019). An integrated framework for course adapted student learning analytics dashboard. Computers in Human Behavior , 92 , 679–690. https://doi.org/10.1016/j.chb.2018.03.035
Article Google Scholar
Banihashem, S. K., Noroozi, O., van Ginkel, S., Macfadyen, L. P., & Biemans, H. J. A. (2022). A systematic review of the role of learning analytics in enhancing feedback practices in higher education. Educational Research Review , 37 , 100489. https://doi.org/10.1016/j.edurev.2022.100489
Barry, A. (2001). Political Machines: Governing a Technological Society (1st ed.). Bloomsbury Publishing. https://www.bloomsbury.com/ca/political-machines-9780485006346/
Biesta, G. (2007). Why what works won’t work: Evidence-based practice and the democratic deficit in Educational Research. Educational Theory , 57 (1), 1–22. https://doi.org/10.1111/j.1741-5446.2006.00241.x
Bodily, R., & Verbert, K. (2017). Review of research on student-facing learning analytics dashboards and educational recommender systems. IEEE Transactions on Learning Technologies , 10 (4), 405–418. https://doi.org/10.1109/TLT.2017.2740172
Bodily, R., Ikahihifo, T. K., Mackley, B., & Graham, C. R. (2018). The design, development, and implementation of student-facing learning analytics dashboards. Journal of Computing in Higher Education , 30 (3), 572–598. https://doi.org/10.1007/s12528-018-9186-0
Boscardin, C., Fergus, K. B., Hellevig, B., & Hauer, K. E. (2018). Twelve tips to promote successful development of a learner performance dashboard within a medical education program. Medical Teacher , 40 (8), 855–861. https://doi.org/10.1080/0142159X.2017.1396306
Boud, D. J., & Molloy, E. K. (2013). What is the problem with feedback? In D. J. Boud, & E. K. Molloy (Eds.), Feedback in higher and Professional Education . Routledge.
Bowker, G. C., & Star, S. L. (2000). Sorting things out: classification and its consequences . The MIT Press. https://direct.mit.edu/books/book/4738/Sorting-Things-OutClassification-and-Its
Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research , 65 (3), 245–281. https://doi.org/10.3102/00346543065003245
Callon, M. (1990). Techno-economic networks and irreversibility. The Sociological Review , 38 (S1), 132–161. https://doi.org/10.1111/j.1467-954X.1990.tb03351.x
Callon, M. (1992). The dynamics of techno-economic networks. In R. Coombes, P. Saviotti, & V. Walsh (Eds.), Technological Change and Company Strategies: Economic Change and Sociological Perspectives ,. Harkort Brace Jovanovic. https://www.bibsonomy.org/bibtex/2ccf1a61d75413be35c245fa22187faf1/referrator
Callon, M., & Latour, B. (1982). Unscrewing the big Leviathan: How actors macro- structure reality and how sociologists help them to do so. In K. Knorr-Cetina, & A. V. Cicourel (Eds.), Advances in social theory and methodology . Routledge.
Callon, M., & Law, J. (1989). On the construction of sociotechnical networks: content and context revisited. In Knowledge and Society: Studies in the Sociology of Culture Past and Present (Vol. 8, pp. 57–83). https://search.gesis.org/publication/csa-sa-90V3768
Carless, D. (2006). Differing perceptions in the feedback process. Studies in Higher Education , 31 (2), 219–233. https://doi.org/10.1080/03075070600572132
Chan, T., Sebok-Syer, S., Thoma, B., Wise, A., Sherbino, J., & Pusic, M. (2018). Learning analytics in medical education assessment: The past, the present, and the future. AEM Education and Training , 2 (2), 178–187. https://doi.org/10.1002/aet2.10087
Clow, D. (2013). An overview of learning analytics. Teaching in Higher Education , 18 (6), 683–695. https://doi.org/10.1080/13562517.2013.827653
Deeley, S. J., Fischbacher-Smith, M., Karadzhov, D., & Koristashevskaya, E. (2019). Exploring the ‘wicked’ problem of student dissatisfaction with assessment and feedback in higher education. Higher Education Pedagogies , 4 (1), 385–405. https://doi.org/10.1080/23752696.2019.1644659
Deleuze, G. (1988). Foucault . U of Minnesota. https://books.google.ca/books?id=BpDgCBgfnwUC
Deleuze, G. (1992). Postscript on the societies of control. October , 59 , 3–7. https://www.jstor.org/stable/778828
Google Scholar
Durojaiye, A. B., Snyder, E., Cohen, M., Nagy, P., Hong, K., & Johnson, P. T. (2018). Radiology Resident Assessment and Feedback Dashboard RadioGraphics , 38(5), 1443–1453. https://doi.org/10.1148/RG.2018170117
Few, S. (2007). Dashboard confusion revisited. Perceptual Edge Visual Business Intelligence Newsletter , 1–6.
Foucault, M. (1977). Discipline and punish: the birth of the prison (1st Americ). Pantheon Books.
Foucault, M. (1991). Governmentality. In G. Burchell, C. Gordon, & P. Miller (Eds.), The Foucault effect: studies in governmentality, with two lectures by and an interview with michel foucault . University of Chicago Press. https://press.uchicago.edu/ucp/books/book/chicago/F/bo3684463.html
Gad, C., & Lauritsen, P. (2009). Situated surveillance: An ethnographic study of fisheries inspection in Denmark. Surveillance & Society , 7 (1), 49–57. https://doi.org/10.24908/ss.v7i1.3307
Gutiérrez, F., Seipp, K., Ochoa, X., Chiluiza, K., De Laet, T., & Verbert, K. (2020). LADA: A learning analytics dashboard for academic advising. Computers in Human Behavior , 107 , 105826. https://doi.org/10.1016/j.chb.2018.12.004
Hamann, T. H. (2009). Neoliberalism, Governmentality, and Ethics. Foucault Studies , 37–59. https://doi.org/10.22439/fs.v0i0.2471
Han, J., Kim, K. H., Rhee, W., & Cho, Y. H. (2021). Learning analytics dashboards for adaptive support in face-to-face collaborative argumentation. Computers & Education , 163 , 104041. https://doi.org/10.1016/j.compedu.2020.104041
Harraway, D. (1991). Simians, cyborgs and women: The reinvention of nature . Free Association Books.
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research , 77 (1), 81–112. https://doi.org/10.3102/003465430298487
Herodotou, C., Rienties, B., Boroowa, A., Zdrahal, Z., & Hlosta, M. (2019). A large-scale implementation of predictive learning analytics in higher education: The teachers’ role and perspective. Educational Technology Research and Development , 67 (5), 1273–1306. https://doi.org/10.1007/s11423-019-09685-0
Kitto, S. (2003). Translating an electronic panopticon Educational technology and the re-articulation of lecturer-student relations in online learning. Information Communication & Society , 6 (1), 1–23. https://doi.org/10.1080/1369118032000068796
Kitto, S., & Higgins, V. (2003). Online university education: liberating the student? Science as Culture , 12 (1), 23–58. https://doi.org/10.1080/0950543032000062254A
Kitto, S., & Higgins, V. (2009). Pedagogical machines: ICTs and neoliberal governance of the university . Nova Science.
Kitto, S., & Higgins, V. (2010). Working around ERPs in technological universities. Science Technology & Human Values , 35 (1), 29–54. https://www.jstor.org/stable/27786193
Kitto, S., & Saltmarsh, S. (2007). The production of ‘proper cheating’ in online examinations within technological universities. International Journal of Qualitative Studies in Education , 20 (2), 151–171. https://doi.org/10.1080/09518390600923792
Kitto, K., Shum, B., S., & Gibson, A. (2018). Embracing imperfection in learning analytics . 451–460. https://doi.org/10.1145/3170358.3170413
Kitto, S., Cleland, J., & Yng, N. Y. (2024). Slowing down when you should’: optimising the translation of artificial intelligence into medical school curricula. Singapore Medical Journal , in press .
Latour, B. (1987). Science in action: How to follow scientists and engineers through society . Harvard University Press. https://books.google.ca/books?hl=en%26lr=%26id=sC4bk4DZXTQC%26oi=fnd%26pg=PA1%26dq=Latour,%26B.+(1988)+Science+in+Action:+How+to+Follow+Scientists+and+Engineers+Through+Society+ots=WdeLypdaQz%26sig=fyTpY65HQKftv96AVyMx9LrsX0ov=onepage%26q%26f=false
Latour, B. (1993). We Have Never Been Modern . Harvester Wheatsheaf. https://books.google.ca/books?id=TzQAPY8-S7UC
Latour, B. (2005). Reassembling the social: An introduction to the actor-network theory . Oxford University Press. https://philpapers.org/rec/LATRTS
Law, J. (1992). Notes on the theory of the actor-network: Ordering, strategy, and heterogeneity. Systems Practice , 5 (4), 379–393. https://doi.org/10.1007/BF01059830
Lyon, D. (2001). Surveillance Society: Monitoring Everyday Life (1st edition). Open University Press. https://www.amazon.ca/SURVEILLANCE-SOCIETY-Monitoring-Everyday-Life/dp/0335205461
Masiello, I., Mohseni, Z. (Artemis), Palma, F., Nordmark, S., Augustsson, H., & Rundquist, R. (Eds.). (2024). A current overview of the use of learning analytics dashboards. Education Sciences , 14 (1), 82. https://doi.org/10.3390/educsci14010082
Mavrikis, M., Geraniou, E., Gutierrez Santos, S., & Poulovassilis, A. (2019). Intelligent analysis and data visualisation for teacher assistance tools: The case of exploratory learning. British Journal of Educational Technology , 50 (6), 2920–2942. https://doi.org/10.1111/bjet.12876
Michael, M. (1998). Co(a)gency and the car: attributing agency in the case of the road rage’’’. In B. Brenna, J. Law, & I. Moser (Eds.), Machines, Agency and Desire (pp. 125–141).
Miller, P., & Rose, N. (1990). Governing economic life. Economy and Society , 19 (1), 1–31. https://doi.org/10.1080/03085149000000001
Noble, D. F. (1998). Digital diploma mills: The automation of higher education. Science as Culture , 7 (3), 355–368. https://doi.org/10.1080/09505439809526510
Ossenberg, C., Henderson, A., & Mitchell, M. (2019). What attributes guide best practice for effective feedback? A scoping review. Advances in Health Sciences Education: Theory and Practice , 24 (2), 383–401. https://doi.org/10.1007/s10459-018-9854-x
Paulsen, L., & Lindsay, E. (2024). Learning analytics dashboards are increasingly becoming about learning and not just analytics - a systematic review. Education and Information Technologies . https://doi.org/10.1007/s10639-023-12401-4
Poster, M. (1990). The Mode of Information: Poststructuralism and Social Context . University of Chicago Press. https://www.amazon.ca/Mode-Information-Poststructuralism-Social-Context/dp/0226675963
Prinsloo, P. (2017). Fleeing from Frankenstein’s monster and meeting Kafka on the way: Algorithmic decision-making in higher education. E-Learning and Digital Media , 14 (3), 138–163. https://doi.org/10.1177/2042753017731355
Prinsloo, P. (2019). A social cartography of analytics in education as performative politics. British Journal of Educational Technology , 50 (6), 2810–2823. https://doi.org/10.1111/bjet.12872
Rittel, H. W. J. (1973). Dilemmas in a general theory of planning. Policy Science , 4 , 155–169. https://link.springer.com/content/pdf/10.1007/BF01405730.pdf
Robins, K., & Webster, F. (1989). The technical fix: Education, computers, and industry . Palgrave Macmillan.
Robins, K., & Webster, F. (2002). The virtual University? Knowledge, markets, and management . Oxford University Press.
Rose, N. (1993). Government, authority and expertise in advanced liberalism. Economy and Society , 22 (3), 283–299. https://doi.org/10.1080/03085149300000019
Rose, N. (1999). Powers of Freedom: Reframing political thought . Cambridge University Press. https://www.amazon.ca/Powers-Freedom-Reframing-Political-Thought/dp/0521659051
Rose, N., & Miller, P. (1992). Political Power beyond the state: Problematics of government. The British Journal of Sociology , 43 (2), 205. https://doi.org/10.2307/591464
Rowe, W. E. (2014). Positionality. In M. Coghlan, & Brydon-Miller (Eds.), The Sage Encyclopaedia of Action Research . Sage.
Sansom, R. L., Bodily, R., Bates, C. O., & Leary, H. (2020). Increasing Student Use of a Learner Dashboard. Journal of Science Education and Technology , 29 (3), 386–398. https://doi.org/10.1007/S10956-020-09824-W
Savin-Baden, M., & Major, C. H. (2013). Qualitative Research: The essential guide to theory and practice (1st editio). Routledge. https://www.amazon.ca/Qualitative-Research-essential-theory-practice/dp/0415674786
Schuwirth, L. W. T., & Van der Vleuten, C. P. M. (2011). Programmatic assessment: From assessment of learning to assessment for learning. Medical Teacher , 33 (6), 478–485. https://doi.org/10.3109/0142159X.2011.565828
Schwendimann, B. A., Rodríguez-Triana, M. J., Vozniuk, A., Prieto, L. P., Boroujeni, M. S., Holzer, A., Gillet, D., & Dillenbourg, P. (2017). Perceiving learning at a glance: A systematic literature review of learning Dashboard Research. IEEE Transactions on Learning Technologies , 10 (1), 30–41. https://doi.org/10.1109/TLT.2016.2599522
Sedrakyan, G., Mannens, E., & Verbert, K. (2019). Guiding the choice of learning dashboard visualizations: Linking dashboard design and data visualization concepts. Journal of Computer Languages , 50 , 19–38. https://doi.org/10.1016/j.jvlc.2018.11.002
Susnjak, T., Ramaswami, G. S., & Mathrani, A. (2022). Learning analytics dashboard: A tool for providing actionable insights to learners. International Journal of Educational Technology in Higher Education , 19 (1), 12. https://doi.org/10.1186/s41239-021-00313-7
Teasley, S. D. (2018). Learning analytics: Where information science and the learning sciences meet. Information and Learning Sciences , 120 (1/2), 59–73. https://doi.org/10.1108/ILS-06-2018-0045
Download references
This project did not receive any funding.
Authors and affiliations.
Lee Kong Chian School of Medicine, Nanyang Technological University, HQ Building, Novena Campus, 11 Mandalay Road, Singapore, 308232, Singapore
Simon Kitto, H. L. Michelle Chiang, Olivia Ng & Jennifer Cleland
National Healthcare Group (NHG), Singapore, Singapore
Jennifer Cleland
You can also search for this author in PubMed Google Scholar
JC conceived the work and developed the preliminary idea through discussions with SK. MC and ON made substantial contributions to the design of the work with ON providing technical expertise on the functions of a LAD. JC and SK led paper drafting with MC and ON contributing to drafts as these progressed and critically reviewing drafts. All authors approved the final version and agreed to be accountable for all aspects of the work.
Correspondence to Jennifer Cleland .
Competing interests.
The authors declare no competing interests.
Publisher’s note.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .
Reprints and permissions
Kitto, S., Chiang, H.L.M., Ng, O. et al. More, better feedback please: are learning analytics dashboards (LAD) the solution to a wicked problem?. Adv in Health Sci Educ (2024). https://doi.org/10.1007/s10459-024-10358-8
Download citation
Received : 10 March 2024
Accepted : 02 July 2024
Published : 26 August 2024
DOI : https://doi.org/10.1007/s10459-024-10358-8
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative
West texas a&m is offering embedded associate degrees starting this fall.
1:30 AM on Aug 28, 2024 CDT
College debt is suffocating. Students take on lifelong commitments too burdensome for degrees that may not have substantial value. That, in turn, diminishes the integrity and worth of the higher education enterprise in the eyes of students, their families, and the general public.
This is unacceptable.
Contributing to the problem is the overall dropout rate, which studies suggest is up to 40% among students who take on debt , according to the National Center for Education Statistics. That’s at four-year universities. In community colleges, fewer than 1 in 5 community college students graduate in three years with a two-year degree, according to Forbes.
Traditionally, the expectation for higher education has been “in at 18, out at 22.” That’s increasingly less common as demographics and aspirations change, but too often, elected officials, bankers and university leadership still cling to that model.
Get smart opinions on the topics North Texans care about.
By signing up you agree to our Terms of Service and Privacy Policy
At West Texas A&M University, we know that model must be more flexible. Life is never predictable, and sometimes, our students aren’t able to finish their bachelor’s degree while following that four-year plan. That’s why this fall, we will begin offering associate degrees to students who complete 60 hours — 42 hours of core curriculum and 18 hours of courses within their major.
West Texas A&M is the first university in Texas to offer what we call the “embedded” associate degrees. The first embedded associate degree in mathematics will be mailed before Christmas. Seven other embedded associate degrees will be awarded in May 2025.
The university-conferred associate degrees are certifications of progress. There are no graduation ceremonies planned; the degree is simply mailed to every student when they meet the requirements of 60 credit hours, the halfway mark of the baccalaureate degree. Importantly, these are not intended as terminal degrees. They are intended for people who aspired to attain a bachelor’s degree but were forced to put a pause on their education. At West Texas A&M, we are working to address real student needs.
The embedded associate degree will not compete with community colleges. According to the American Association of Community Colleges, the opposite is true. Tuition and fees at two-year institutions are one-third the cost of those at four-year institutions, and this plan does not change that. The embedded associate degree is a bonus, not the endgame.
Do university-conferred associate degrees provide benefits? Certainly. They offer a clearly defined point to pause their education when, as they say, life gets in the way. Students with an associate degree earn $938 a week, according to the U.S. Bureau of Labor Statistics , while those who have only some college credits earn $877 per week. And if they then return to school and complete a bachelor’s degree, they can expect to earn $1,305 per week. These are clear emotional and economic benefits.
This approach has already been tested in Colorado, where 2021′s Higher Education Student Success legislation offered senior universities the ability to confer associate degrees to students with 70 credits. Students who have paused their education have an associate degree that both benefits them in the workforce and encourages them to persist until they attain their bachelor’s degree.
Higher education is almost always a value proposition. At West Texas A&M, our leadership seeks new ways to address the challenges of educational debt, changing student demographics, increased life pressures on students and lack of degree completion. Our school’s goal is to enrich human satisfaction, instill a sense of accomplishment, and impact economic development for our region and, indeed, for the state of Texas.
This embedded associate degree program is a crucial step in that direction and a way of redefining excellence in higher education.
Walter V. Wendler is president of West Texas A&M University.
We welcome your thoughts in a letter to the editor. See the guidelines and submit your letter here . If you have problems with the form, you can submit via email at [email protected]
Walter V. Wendler
IMAGES
COMMENTS
9. Parent engagement. When school went remote, families got a better sense of what their children were learning. It's something schools can build on, if they can make key cultural shifts. Read ...
During an Education Week K-12 Essentials forum last week, journalists, educators, and researchers talked about these challenges, and possible solutions to improving equity in education.
We focused on neuroscience, the role of the private sector, education technology, inequality, and pedagogy. Unfortunately, we think the four biggest problems facing education today in developing countries are the same ones we have identified in the last decades. 1. The learning crisis was made worse by COVID-19 school closures.
10 Challenges Facing Public Education Today. The bad news is that the demands and pressures on our schools are growing. The good news is that the nation is finally looking to educators for solutions. By: Brenda Álvarez, Tim Walker, Cindy Long, Amanda Litvinov, NEA staff writers. Published: August 3, 2018. First Appeared In NEA Today August 2018.
Esther Care, Patrick Griffin. Among global education's most urgent challenges is a severe lack of trained teachers, particularly female teachers. An additional 9 million trained teachers are ...
Big Ideas in Education Special Report Big Ideas to Solve New and Persistent Challenges in Education September 1, 2023 In the 2023 edition , our newsroom sought to dig deeper into new and ...
The Seekers. Meet eight current students and recent graduates who experienced or identified problems in education — and are now working on solutions to help others. In the education world, it's easy to identify problems, less easy to find solutions. Everyone has a different idea of what could or should happen, and change is never simple ...
In rural India, nearly three-quarters of third graders cannot solve a two-digit subtraction problem such as 46 minus 17, and by grade five — half still cannot do so. The world is facing a learning crisis. While countries have significantly increased access to education, being in school isn't the same thing as learning.
22 January 2020 Introduction. I nequity is perhaps the most serious problem in education worldwide. It has multiple causes, and its consequences include differences in access to schooling ...
As of March 28, 2020, the COVID-19 pandemic is causing more than 1.6 billion children and youth to be out of school in 161 countries. This is close to 80% of the world's enrolled students. We were already experiencing a global leaning crisis, as many students were in school, but were not learning the fundamental skills needed for life.
Education in Americans problems are very complicated, and there is not one big solution that can fix all of them at once, but little by little we can create a change. — Lilly Smiley, Hoggard ...
With the closing of schools, the COVID-19 pandemic has revealed many of the injustices facing schoolchildren across the country, from inadequate internet access to housing instability to food insecurity. The Gazette interviewed Bridget Long, A.M. '97, Ph.D. '00, dean of the Harvard Graduate School of Education and Saris Professor of ...
As Marilyn Cochran-Smith and Susan L. Lytle discuss in their book Inquiry as Stance: Practitioner Research for the Next Generation, teacher inquiry is a process of questioning, exploring, and implementing strategies to address persistent classroom challenges.It mirrors the active learning process we encourage in students and can transform recurring problems into opportunities for growth.
The coincident emergence of a problem in education and a new approach to learning naturally makes us ask how one may be a solution for the other. ... The solution to both problems is, of course, more tailored teaching, but a teacher is hard-pressed to provide one-on-one tutoring to 30 or 40 kids. EdTech might help provide one-to-one instruction ...
Concretely, the first solution would be to reduce class distinctions among students by doing away with the property tax as a primary funding source. This is a significant driver for education inequality because low-income students, by default, will receive less. Instead, the state government should create more significant initiatives and ...
The 2014-16 West African Ebola outbreak was a severe problem for education in countries like Liberia and Sierra Leone. Ebola put the education of 3 million children in these countries on hold. ... We've brought quality education to villages that are off the grid, engaged local community leaders to find solutions to keep girls in school, and ...
Top 10 Educational Problems and their Solutions. 1. Lack of Access to Quality Education. One of the biggest problems facing America's education system is the lack of access to quality education. This issue is especially prevalent in low-income and rural areas.
Tweet your comments with #K12BigIdeas . No. 1: Kids are right. School is boring. Daryn Ray for Education Week. Out-of-school learning is often more meaningful than anything that happens in a ...
Problems of practice can hold your students back from achieving educational success. Codesign is a collaborative design process that allows educators to come together to analyze problems of practice and propose solutions to address them. Demystifying Jargon: How Codesign can help everyone to speak the same language.
January 30, 2022 at 6:00 a.m. EST. correction. A previous version of this story incorrectly said that 39 percent of American children were on track in math. That is the percentage performing below ...
Problem: Outdated Curriculum; Although we transformed the educational system, many features of the curriculum remained unchanged. Solution: Eliminate Standardised Exams. This is a radical suggestion. However, standardised exams are a big problem. We want the students to learn at their own pace.
To get the latest information on the ongoing problem of chronic absenteeism, the authors conducted a survey of school districts and interviewed leaders of districts who are members of the American School District Panel (ASDP). The ASDP is a research partnership between RAND and the Center on Reinventing Public Education.
Problem Statement. What can be done to improve the state of civics education among the general populace? Possible Solutions. ... "The need for civic education in 21 st-century schools," Brookings Policy 2020 (posted on brookings.edu on June 4, 2020). The websites for iCivics (icivics.org) and CivXNow (civxnow.org) contain a vast collection ...
There is a long-standing lack of learner satisfaction with quality and quantity of feedback in health professions education (HPE) and training. To address this, university and training programmes are increasingly using technological advancements and data analytic tools to provide feedback. One such educational technology is the Learning Analytic Dashboard (LAD), which holds the promise of a ...
Student behavior problems, cellphones in class, anemic pay and AI-powered cheating are taking their toll on America's teachers. Many are demoralized or leaving the profession.
Contributing to the problem is the overall dropout rate, which studies suggest is up to 40% among students who take on debt, according to the National Center for Education Statistics. That's at ...
The value of making access to third-level education easier is undermined if standards are falling. The consequences for the wider economy and graduate job prospects must also be considered.
Two executive directors have recently joined UC Berkeley's College of Computing, Data Science, and Society (CDSS) to lead pioneering centers that actualize AI solutions for healthcare and climate change. Sarah Jones, executive director for the Bakar Institute of Digital Materials for the Planet and Ted Robertson, executive director for the Center for Healthcare Marketplace Innovation, were ...
Three Companies Selected To Provide Solutions to the Problem of Communications in an Electromagnetic Environment (EMI) to the DoD. Mountain View, CA (August 21, 2024) — Current global conflicts highlight the decisive impact uncrewed systems (UxS) have on the battlefield. Access to low-cost, secure components from the domestic and allied ...