Featured Articles on OnlineEducation.com

Amongst many perks of working for some of the country’s top employers is help with paying for college. Today’s forward-thinking organizations realize the advantages of investing in their human assets. They value employee satisfaction and the future profitability of employees with the skill sets and knowledge to advance their market position.

Mathematics, applied mathematics, and statistical modeling are integral to quantitative literacy, STEM education, and to the data-driven information technologies that have penetrated every sector of our economy.

The explosion in technologies, methods, and online tools for elementary school teachers has been both beneficial and overwhelming. On the one hand, access to ideas from teachers across the globe has never been faster or easier, allowing educational professionals to pick and choose from an infinite buffet of options; on the other, it can be difficult to feel the rain when one is in the ocean. In other words, with the dizzying wealth of resources, how can elementary teachers ensure that they’re investing their time in the time-tested, web-based tools and applications to create the optimal benefit for their students?

Students in lower grades are generally expected to need more help than older students in middle and high school to support their education through online learning models. However, given the ocean of resources available online, it can be difficult for students even in higher grade levels to search for material on subjects they are still in the process of learning.

Two new surveys of artificial intelligence utilization by college students have recently appeared, and their results mirror each other in significant respects. Unlike several previous studies, both surveys suggest that students are now moderately to highly engaged with using generative AI in their coursework. However, both surveys also suggest much lower confidence among students that they possess sufficient AI knowledge and skills.

The educational technology landscape (edtech) in the United States is dynamic and multifaceted, with abundant opportunities yet fraught with challenges. Digital transformation is reshaping the educational landscape, and edtech companies are increasingly integrated into learning systems—with a massive market value projected to reach $421 billion by 2032.

College course materials are likely to appear very different within the next few months if they’re available online as web or mobile application content. That’s because of new federal regulations requiring public colleges across the nation to make such content accessible to all students.

College affordability remains one of the most controversial and hotly debated issues in American higher education. Yet even as headlines focus on tuition spikes, student loan forgiveness, and free college proposals, the pricing decisions by college administrators can influence potential students long before they apply.

Edtech is providing important solutions to education providers and students globally, and is gaining speed in developing regions of the world, such as Africa. A Microsoft startup accelerator recently announced its acceptance of 12 African startups into its program. Meanwhile, countries on the continent such as Morocco began launching venture capital (VC) funds backing edtech startups and opportunities.

As AI assistants become embedded across education and technical work, a quiet but consequential inflection point is emerging: for the first time, productivity is scaling faster than learning. A new study from Anthropic reveals a striking tension at the heart of AI adoption.

While remote learning has often been lauded as an avenue for educational opportunities across socioeconomic levels, others are not so sure the surge of big tech’s involvement in online education is positive. Professors Spiros Protopsaltis and Sandy Baum argue online coursework has contributed to increasing gaps in educational success across socioeconomic groups while failing to improve affordability.

Given that the pandemic may have already accelerated the disruption of the traditional college business model, there is a critical need for students and employers to be able to verify and back educational background and expertise from various institutions and programs. The initial technological darling of the financial and cryptocurrency world, blockchain, may provide the best contender to meet this need.

Higher education institutions are increasingly expected to support students in developing higher-order thinking skills, such as creativity and critical thinking, and technical knowledge, to better respond to labor market demands and contribute to innovation in society.

The education technology sector is experiencing a renewed wave of activity as artificial intelligence continues to reshape classroom learning, administrative workflows, and student engagement models. Investments in edtech startups globally have seen a 290 percent total funding growth over the last five years.

While distance education has existed since the nineteenth century when correspondence courses arose in Western Europe, there are still questions about online learning’s effectiveness and a generalized feeling that it’s not the same as a traditional brick-and-mortar experience. For prospective online students, one major concern is how future employers will view a degree achieved online.

Extended reality (XR) technologies are arriving in homes and classrooms without clear guidelines for use by certain users. Parents and clinicians working with neurodivergent children face decisions about when, how, and whether to introduce VR headsets as tools for learning, therapy, or social connection.

The edtech industry and online education as a whole are brand new fields. This is mainly due to advances in technology, such as the internet, streaming, and cloud computing. However, the concept has roots that date back centuries.

The onset of the novel coronavirus pandemic was also a shock to many educational institutions globally—but what impact, if any, did it have on Calbright’s online model in its nascent stages?

The U.S. Department of Education uses a standardized formula to calculate Pell Grant awards based on a student’s and their family’s financial need. The Department determines ability to pay for college—expressed as the student’s Expected Family Contribution or EFC—solely through financial data reported on an online form known as the Free Application for Federal Student Aid, or FAFSA.

Online education gives students the freedom to work their school work around their existing obligations that can’t be put on the backburner. While an adult may not be able to drop all of their responsibilities to pursue a new degree full time at a traditional campus, they may be able to pursue new skills during their off-hours.

A group of articles recently emerged in the press on a surprising topic. These stories explore how significant numbers of college and graduate students don’t want to return to classrooms again as if it were 2019. Instead, they prefer to continue with online education as they did during the pandemic.

When a college student chooses to enroll in an on-campus program instead of an equivalent program offered online, that student also chooses to pay America’s fastest-growing college expense. And that particular expense probably isn’t the one that the student expects would be growing so rapidly.

Schools are introducing artificial intelligence faster than they are deciding how it should be taught. Districts approve platforms, teachers experiment with generative tools, and students quickly learn how to prompt systems for answers. Most public debate centers on access, guardrails, and technical capability. Far less attention is given to who defines what students are meant to understand about artificial intelligence in the first place.

While the current COVID-19 pandemic is challenging in a multitude of ways, there is a silver lining to be gleaned in the educational world: it is forcing learning institutions that have lagged behind the digital revolution to quickly come up to speed.

Artificial intelligence is quickly becoming a central driver of economic development. Governments around the world are exploring how AI can improve public services, guide policy decisions, and respond to complex challenges such as food security and healthcare delivery. Yet the ability to use artificial intelligence effectively depends on something far less visible than the models themselves: the infrastructure that allows these systems to function.