In close with a dedicated force in our field who believes in the power of education to shape lives. 

INTERVIEW | by Victor Rivero

As CEO of Savvas Learning Company, Bethlam Forsa leads up a global next-generation K-12 learning solutions provider that recently acquired Outlier, an edtech startup that has created a portfolio of high-quality online college-level courses enabling high school students to earn dual credit while never having to leave their school building. A leader whose career in education and publishing spans over two decades, Bethlam has guided Savvas to deliver award-winning product lines. The Savvas Realize digital platform won the 2024 EdTech Digest Cool Tool Award for Learning Management System Solution. The company’s enVision Mathematics and SuccessMaker: Foundations of High School Math were named EdTech Cool Tool Award finalists in the Math Solution and the Personalized Learning Solution categories, respectively. Bethlam was also recently named the Most Influential Thought Leader in EdTech by the 2024 CODiE Awards. In this EdTech Digest exclusive, hear why she first became drawn to the work of education, how she defines an oft-used phrase, and her thoughts on technology’s role in—and what the future of—learning might look like.  

What prompted you to first become involved with technology and learning?

I was drawn to this work because I fundamentally believe in the power of education to shape lives. The best way to make a difference in the world is through a quality education. To do this, all of us at Savvas have dedicated ourselves to supporting educators by developing innovative, high-quality learning solutions that enable all students to succeed. Early in my career, I realized that education technology, when leveraged effectively, could revolutionize the way students learn, just as it has empowered us in our everyday lives. We’ve long been a leader in the digital transformation of K-12 education, including our pioneering use of adaptive technology to provide personalized learning solutions that help educators meet the needs of all learners. Our learning management system, Savvas Realize, — it’s earned more than a dozen edtech innovation awards, including one from EdTech Digest — has been widely recognized as a game-changing platform known for driving innovation and exemplifying the best in edtech solutions. It’s an exciting time to be in the edtech industry. Technology will continue to significantly impact education, especially with the advent of generative AI and the possibility of it taking personalized learning to new heights.

‘It’s an exciting time to be in the edtech industry. Technology will continue to significantly impact education, especially with the advent of generative AI and the possibility of it taking personalized learning to new heights.’

How do you define “next-generation learning,” and why?

There is a simple truth in education that student engagement leads to student achievement. For us, next-generation learning is about combining the power of advanced technology with research-based pedagogy and compelling content to deliver interactive, real-world learning experiences that spark student engagement and drive student achievement. Another important aspect of next-generation learning is enabling differentiated instruction to meet the needs, skills, and interests of individual learners, making education personalized, relevant and engaging to each student. We know that the traditional, one-size-fits-all approach doesn’t work for all learners. That is why at Savvas we make it our mission to design flexible learning solutions that enable teachers to tailor instruction to each student’s distinct learning style and pace, ensuring that they receive personalized support and challenges that align with their abilities and goals. The educators and students who use our learning solutions deserve nothing less.

What does “proven pedagogy” mean to you and the team behind Savvas?

We take great pride in developing the highest-quality instructional materials available in today’s educational marketplace. Proven pedagogy is the very foundation of this. What it means to me, and all of us at Savvas, is that we develop research-based, standards-aligned learning solutions that incorporate the most current educational best practices coupled with compelling, relevant, and accurate content — all developed by dedicated teams of authors who are experts in their fields, working in conjunction with top editors, academic consultants, and teacher reviewers. In order to create our high-quality, evidence-based curriculum, we adhere to strict editorial standards and a rigorous product development process.

‘In order to create our high-quality, evidence-based curriculum, we adhere to strict editorial standards and a rigorous product development process.’

In the end, the gold standard for us is ensuring that the educational solutions we provide our customers prove to be efficacious and improve the educational outcomes and opportunities for all learners. As such, we believe that rigorous research should include multiple studies, creating a large body of research supporting an educational solution. For us, this involves continuously conducting research to measure the effectiveness of a product, as well as gain insights into educators’ experiences in the classroom. We partner with educators and school districts nationwide to constantly evaluate and test our instructional materials and drive development of evidence-based learning solutions. Our extensive research, combined with the feedback we receive from educators and teachers who use our programs, helps inform every step of our product development process, from pedagogy and instructional design to usability and efficacy in the classroom. Our goal is to ensure we deliver the most effective learning solutions that make a positive impact so that every student — no matter where they come from or which school they are in — has an opportunity to achieve their full potential.

What are some important guiding elements involved in helping students become productive contributing adults?

I believe it is important that we impart in young students the skills to help them thrive not just in the classroom but in life. Critical thinking, problem-solving, collaboration, teamwork, and other soft skills are essential for preparing students to navigate the complexities of adulthood. Likewise, encouraging curiosity and a love for lifelong learning can equip students with the mindset they’ll need to continuously adapt and grow.

As a next-generation K-12 education leader, Savvas develops instructional materials that make learning relevant to students’ lives and prepare them for college and career. Our programs challenge students to think more deeply and analytically about what they’ve read, giving them the tools to become critical thinkers and effective communicators, which is especially important in today’s fast-paced digital world. I think it’s important to also provide educators solutions that build upon the strong foundation of knowledge and life skills that they’ve taught their students by delivering personalized pathways to support college and career readiness for their high schoolers. Giving students the ability to “try on” college and earn valuable credit through dual-enrollment courses or take career technical education (CTE) classes to launch their careers is a critical next step to helping high school students become productive adults.

‘Giving students the ability to “try on” college and earn valuable credit through dual-enrollment courses or take career technical education (CTE) classes to launch their careers is a critical next step to helping high school students become productive adults.’

What trends are you looking at (AI, others) with the ‘future of learning’ in mind? And what does that look like to you—what do you see in the next couple of years for Savvas, for learning generally?

We are actively developing ways to use generative AI to create time-saving tools for teachers to reduce their burdensome administrative tasks, such as grading assignments and lesson planning. This will help make their jobs easier and alleviate some of the causes that have led to teacher burnout, allowing them to do what they love most: instructing students.

We are also leveraging AI to generate even more robust data-driven insights to differentiate instruction and enhance the adaptivity of our learning solutions. Another major focus of ours is using AI-powered tools to develop highly sophisticated and, most importantly, reliable “tutorbots” or “coaches” that can provide real-time feedback to students to improve their writing and math skills. The idea is that we want students to get better at literacy and math, and with machine-learning capabilities we can now give them in-the-moment, constructive critiques of their work that can guide them to become stronger at writing and math.

These are just some of the ways we are incorporating AI into our learning solutions. The use of generative AI in K-12 education is going to grow rapidly as more use cases are identified. Looking ahead, I think generative AI offers the potential to provide a deeply personalized learning experience like we’ve never seen before. It will bring to market new solutions to solve real world problems for teachers and learners in ways that were not previously possible. However, like with any new technology, the use of AI’s capabilities as a classroom tool must be pedagogically sound and implemented responsibly, with clear guardrails for its use that prioritize safety, integrity, and efficacy, above all else. Lastly, we must ensure that we keep teachers and students at the center of whatever learning solutions we create. AI may help revolutionize learning but it will never replace the teacher.

Anything you care to add or emphasize concerning edtech, the future of learning, or anything else regarding tech’s role in learning?

Edtech will continue to have a significant role in the future of learning. There’s no doubt about that. However, what I think is really important to point out is that edtech is also now reimagining learning for the future.

‘Edtech will continue to have a significant role in the future of learning. There’s no doubt about that. However, what I think is really important to point out is that edtech is also now reimagining learning for the future.’

We all know it’s vitally important that we prepare today’s students with the skills they will need to be successful in college and the workforce. According to the U.S. Department of Education, 70 percent of jobs will soon require education or training beyond high school. Yet only two in 10 high school students believe they are career-ready, according to a 2021 survey by the Ewing Marion Kauffman Foundation.

Dual-enrollment courses can help fill the gap in college and career readiness by allowing students to simultaneously earn course credit for both high school and college while also exploring career pathways and learning skills needed in the job market. However, logistical challenges in the way these courses have been traditionally offered have often posed barriers to students. For example, in many cases students have long needed to travel to a nearby college — if one even exists in their community — to take a college-level dual-enrollment course. 

By utilizing technology, we can eliminate those barriers. Through our acquisition of Outlier, we are now able to offer the millions of students we serve the opportunity to experience the rigor of college courses through high-quality, online dual enrollment courses. Credit for these courses come from the University of Pittsburgh, a top 50 school, and are highly transferable. Since Outlier’s cinematically produced courses are offered asynchronously, students can take them virtually — in the comfort of their own school, at a time that fits conveniently into their high school schedule. What’s really exciting about these state-of-the-art Outlier offerings is that students, no matter where they live, can experience college-level courses taught by professors from Harvard, MIT, NYU and other first-rate institutions without the hassle of leaving their building or missing other classes. There’s nothing else like it on the market that makes earning college credit while in high school so accessible for students, jump-starting learning for their future. Outlier technology is the future of learning, happening now.

—

Victor Rivero is the Editor-in-Chief of EdTech Digest. Write to: victor@edtechdigest.com

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AI-powered conversations can reduce belief in conspiracy theories by 20%. Researchers found that AI provided tailored, fact-based rebuttals to participants' conspiracy claims, leading to a lasting change in their beliefs. In one out of four cases, participants disavowed the conspiracy entirely. The study suggests that AI has the potential to combat misinformation by engaging people directly and personally.

This is a comprehensive Learning Management System (LMS) that enhances the educational experience. The digital platform connects educators, students, and parents to facilitate interactive and engaging learning. It provides an app and webpage user-friendly interface for educators to efficiently create, manage, and deliver educational content. Administrators can effortlessly set up classes and curriculums, add users, and assign content, whether it is custom or pre-existing. Students can access this content, complete assignments, and track their progress. Students and teachers can use a stylus on the app to write directly on the assignment. It also has a helpful writing feature to display work. Part of its real value is actually quite basic: it allows efficient communication between teachers, students, and parents.

EdQuill was developed by a team with Ushapriya Ravilla to address the evolving needs of modern education. EdQuill aims to improve the teaching and learning experience, reduce administrative burdens on educators, and foster greater parent involvement in students’ education. It is available to educational institutions, learning centers, tutors, and educators. Access EdQuill by signing up for a free trial or scheduling a demo with EdQuill’s expert representatives.

In two short years, EdQuill has helped over 100 educators impact more than 2,000 students nationwide. Using the platform led to a 40% decrease in printing costs and increased productivity in administrative tasks for 100% of teachers. For these reasons and more, EdQuill earned a Cool Tool Award (finalist) for “Best Classroom Management Solution” as part of The EdTech Awards 2024 from EdTech Digest. Learn more. 

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Archipel Academy was born as the Managed Learning Services business line of Schouten & Nelissen. As learning consultants, the people behind it become very familiar with the challenges in the Learning & Development community and in 2019 their founder and CEO Omar Fouab decided to make learning more personal, more impactful and more accessible.

That is how their Learning Management System with LXP capabilities (Learning tracks and skill management) and the biggest content marketplace in Europe was born. Since then, they kept adding features to keep their customers as well as employees everywhere fit for future: the “search & book” function is AI-driven, learners can access an AI-powered job coach that helps them further develop in their current role or grow towards a different position, engagement is kept high through the use of gamification and more recently they added in-real-time learning through the Archi chatbot.

All of these developments have at their core the company’s strong motivation to keep employees and organizations what they call “fit for future.”

Since becoming their customer, VodafoneZiggo has managed to achieve the following numbers:

• Employees followed an average of 2.3 trainings/ year/ per person, which is 4x more than before
• 31% decrease in voluntary resignation
• In 2022 savings of 1.5 milion euros on learning costs, excluding the 5 administrative FTEs that were repurposed to focus on high-level people strategy
• Becoming an employer of choice- with 1 in 3 people applying at VodafoneZiggo doing so because of the learning culture
• Filling 60% of vacancies from within and adressing knowledge gaps through learning

 

For these reasons and more, Archipel Academy was named “Best All-in-One Learning Platform” as part of The EdTech Awards 2024 from EdTech Digest. Learn more. 

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New research reveals that large language models (LLMs) like ChatGPT cannot learn independently or acquire new skills without explicit instructions, making them predictable and controllable. The study dispels fears of these models developing complex reasoning abilities, emphasizing that while LLMs can generate sophisticated language, they are unlikely to pose existential threats. However, the potential misuse of AI, such as generating fake news, still requires attention.

Synergy Student Information System empowers districts to do more, saving time and money while helping to improve efficiency and educational outcomes. Some of the benefits of this system include: 

Deep Functionality – All the data and process management functionality districts expect from a world-class SIS, extending beyond traditional SIS boundaries to deliver greater value.

TeacherVUE Portal – Powerful classroom management and communication tools that make everyday tasks faster and easier for teachers, along with a powerful gradebook.

Exceptional Data Access for Reporting and Analysis – Robust tools for reporting, analyzing data, identifying issues and trends, and ensuring that stakeholders get the information they need to solve problems and support student learning.

Highly Configurable – Extensive configuration options out of the box, with Synergy Technology Development Toolkit available to be licensed by districts along with Synergy source code for rapidly developing custom applications that are fully integrated to the SIS.

Data Security – The highest level of privacy and security in compliance with FERPA and HIPAA requirements, with full field-level security systemwide, and Edupoint is a signatory of the Student Privacy Pledge.

Custom Data Validation and Rules Engine – Safeguards to preserve data integrity and eliminate redundancies platformwide.

Easy to Use – Intuitive and easy to use and personalize from day one – even for beginners – reducing training costs and minimizing inefficiency while users get up to speed.

Edupoint is focused on K-12 student data management and boasts a 99.5% renewal rate. For these reasons and more, Synergy from Edupoint Educational Systems is a Cool Tool Award Winner for “Best Student Information System Solution” as part of The EdTech Awards 2024 from EdTech Digest. Learn more.

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The edtech ecosystem can be complex for educators to navigate, often requiring different platforms for student data and instruction, with tech integration and usability varying widely. The Savvas Realize learning management system (LMS) offers a flexible and dynamic platform that meets all of a district’s needs, from central office tools to classroom curriculum across all grade levels and disciplines.

Savvas Realize is the engine that powers Savvas Learning Company’s many high-quality, evidence-based, and interactive K-12 learning solutions and state-of-the-art assessment tools. The single sign-on platform allows teachers to access everything they need, from standards-aligned content and customizable assignments to rich student data and powerful class-planning tools. Featuring cutting-edge adaptive technology, it provides data-driven insights to help teachers differentiate instruction and personalized, interactive content to foster student engagement, all on one easy-to-use platform.

Unlike LMSs retrofitted from higher-ed platforms, Realize was developed exclusively for K-12 applications. A trailblazer of LTI-A integration, Realize offers plug-and-play interoperability with 30+ edtech tools educators use most, including Google Classroom, Canvas, and Schoology.

Inspired by input from educator users and updated to be better than ever, Savvas Realize delivers even greater simplicity, shareability, and interoperability. The platform’s seamless integrations and time-saving tools give educators faster access to their most important tasks, helping them to manage lesson plans, assist with grading, and reduce paperwork — making for less stress and administrative work and more time with students.

Savvas Realize is a game-changing platform that has been widely recognized for driving innovation and exemplifying the best in edtech solutions. Most recently, Savvas Realize earned a Cool Tool Award (Winner) for “Best Learning Management System” as part of The EdTech Awards 2024 from EdTech Digest. Learn more. 

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For years, Nvidia has dominated many machine learning benchmarks, and now there are two more notches in its belt.

MLPerf, the AI benchmarking suite sometimes called “the Olympics of machine learning,” has released a new set of training tests to help make more and better apples-to-apples comparisons between competing computer systems. One of MLPerf’s new tests concerns fine-tuning of large language models, a process that takes an existing trained model and trains it a bit more with specialized knowledge to make it fit for a particular purpose. The other is for graph neural networks, a type of machine learning behind some literature databases, fraud detection in financial systems, and social networks.

Even with the additions and the participation of computers using Google’s and Intel’s AI accelerators, systems powered by Nvidia’s Hopper architecture dominated the results once again. One system that included 11,616 Nvidia H100 GPUs—the largest collection yet—topped each of the nine benchmarks, setting records in five of them (including the two new benchmarks).

“If you just throw hardware at the problem, it’s not a given that you’re going to improve.” —Dave Salvator, Nvidia

The 11,616-H100 system is “the biggest we’ve ever done,” says Dave Salvator, director of accelerated computing products at Nvidia. It smashed through the GPT-3 training trial in less than 3.5 minutes. A 512-GPU system, for comparison, took about 51 minutes. (Note that the GPT-3 task is not a full training, which could take weeks and cost millions of dollars. Instead, the computers train on a representative portion of the data, at an agreed-upon point well before completion.)

Compared to Nvidia’s largest entrant on GPT-3 last year, a 3,584 H100 computer, the 3.5-minute result represents a 3.2-fold improvement. You might expect that just from the difference in the size of these systems, but in AI computing that isn’t always the case, explains Salvator. “If you just throw hardware at the problem, it’s not a given that you’re going to improve,” he says.

“We are getting essentially linear scaling,” says Salvator. By that he means that twice as many GPUs lead to a halved training time. “[That] represents a great achievement from our engineering teams,” he adds.

Competitors are also getting closer to linear scaling. This round Intel deployed a system using 1,024 GPUs that performed the GPT-3 task in 67 minutes versus a computer one-fourth the size that took 224 minutes six months ago. Google’s largest GPT-3 entry used 12-times the number of TPU v5p accelerators as its smallest entry and performed its task nine times as fast.

Linear scaling is going to be particularly important for upcoming “AI factories” housing 100,000 GPUs or more, Salvator says. He says to expect one such data center to come online this year, and another, using Nvidia’s next architecture, Blackwell, to startup in 2025.

Nvidia’s streak continues

Nvidia continued to boost training times despite using the same architecture, Hopper, as it did in last year’s training results. That’s all down to software improvements, says Salvator. “Typically, we’ll get a 2-2.5x [boost] from software after a new architecture is released,” he says.

For GPT-3 training, Nvidia logged a 27 percent improvement from the June 2023 MLPerf benchmarks. Salvator says there were several software changes behind the boost. For example, Nvidia engineers tuned up Hopper’s use of less accurate, 8-bit floating point operations by trimming unnecessary conversions between 8-bit and 16-bit numbers and better targeting of which layers of a neural network could use the lower precision number format. They also found a more intelligent way to adjust the power budget of each chip’s compute engines, and sped communication among GPUs in a way that Salvator likened to “buttering your toast while it’s still in the toaster.”

Additionally, the company implemented a scheme called flash attention. Invented in the Stanford University laboratory of Samba Nova founder Chris Re, flash attention is an algorithm that speeds transformer networks by minimizing writes to memory. When it first showed up in MLPerf benchmarks, flash attention shaved as much as 10 percent from training times. (Intel, too, used a version of flash attention but not for GPT-3. It instead used the algorithm for one of the new benchmarks, fine-tuning.)

Using other software and network tricks, Nvidia delivered an 80 percent speedup in the text-to-image test, Stable Diffusion, versus its submission in November 2023.

New benchmarks

MLPerf adds new benchmarks and upgrades old ones to stay relevant to what’s happening in the AI industry. This year saw the addition of fine-tuning and graph neural networks.

Fine tuning takes an already trained LLM and specializes it for use in a particular field. Nvidia, for example took a trained 43-billion-parameter model and trained it on the GPU-maker’s design files and documentation to create ChipNeMo, an AI intended to boost the productivity of its chip designers. At the time, the company’s chief technology officer Bill Dally said that training an LLM was like giving it a liberal arts education, and fine tuning was like sending it to graduate school.

The MLPerf benchmark takes a pretrained Llama-2-70B model and asks the system to fine tune it using a dataset of government documents with the goal of generating more accurate document summaries.

There are several ways to do fine-tuning. MLPerf chose one called low-rank adaptation (LoRA). The method winds up training only a small portion of the LLM’s parameters leading to a 3-fold lower burden on hardware and reduced use of memory and storage versus other methods, according to the organization.

The other new benchmark involved a graph neural network (GNN). These are for problems that can be represented by a very large set of interconnected nodes, such as a social network or a recommender system. Compared to other AI tasks, GNNs require a lot of communication between nodes in a computer.

The benchmark trained a GNN on a database that shows relationships about academic authors, papers, and institutes—a graph with 547 million nodes and 5.8 billion edges. The neural network was then trained to predict the right label for each node in the graph.

Future fights

Training rounds in 2025 may see head-to-head contests comparing new accelerators from AMD, Intel, and Nvidia. AMD’s MI300 series was launched about six months ago, and a memory-boosted upgrade the MI325x is planned for the end of 2024, with the next generation MI350 slated for 2025. Intel says its Gaudi 3, generally available to computer makers later this year, will appear in MLPerf’s upcoming inferencing benchmarks. Intel executives have said the new chip has the capacity to beat H100 at training LLMs. But the victory may be short-lived, as Nvidia has unveiled a new architecture, Blackwell, which is planned for late this year.