What’s New in Knewton Alta – May 2020

Wiley is committed to a culture of continuous improvement with Knewton Alta, which is why we are always engaging instructors and students to gather feedback and optimize the learning experience moving forward.

As always, we are very cautious with our product releases to ensure minimal disruption during the semester, while continuing to provide an ever-improving experience for you and your students.

Below you will find information on enhancements made to Knewton Alta during the month of May. If you haven’t looked at Knewton Alta in a while, you’re missing something special.

Improved Student Context and Visibility into Assignment History

This update will help students (and instructors) to better understand their performance on an adaptive assignment and path to mastery, while providing transparency into the type of work that has been completed.

Learn more on how instructors can monitor student progress here.

Learn more about how students can track their own progress here.

Improved Course Copy Functionality

Getting started is now easier than ever!

Our team has been head-down looking for opportunities to make improvements to the course building experience in preparation for Fall. A number of usability improvements have shipped in the past month and we’re topping it off with a boost to copying courses. When copying a Knewton Alta course, instructors now have more options to configure their new course such as setting your institution or changing the dates as they are creating it so you can hit the ground running.

Doubling Down on Grading Accuracy!

A large percentage of Knewton Alta questions are free response, especially in our math courses, and we’ve just released a new update to our answer parsing service to provide better symbolic equivalence checking.

Students submit answers in a variety of complex — but equivalent — formats, and our new parsing engine leverages the active development community around sympy, a python-based computer algebra system, to better catch tricky cases where complex student answers may not appear to match the format that a subject matter expert would use.

Check out the Knewton Blog each month to see the improvements we’ve made to Knewton Alta.

Knewton launches altapass, an all-access pricing option, making alta even more affordable for students

With altapass, students can access multiple alta courses within a single subject area for $79.95; Knewton lowers price of a single-course alta subscription to $39.95

New pricing options available to students for Fall 2019

NEW YORK — Jan. 15, 2019 — Knewton, the world’s leader in AI-driven teaching and learning, today launched altapass, an all-access pricing offer for alta, the company’s adaptive learning courseware for U.S. higher education. With altapass, students can access multiple alta products across a single subject area for up to two years, and for unlimited use, for $79.95. Additionally, Knewton has reduced the price of a single-course alta subscription from $44 to $39.95.

By introducing the new pricing options, Knewton is making alta even more affordable and accessible, helping to put achievement within reach for the students who need it most.

Students wishing to purchase altapass for Fall 2019 may do so beginning Aug. 1 at Knewton.com. Students may still purchase access to a single alta course via monthly subscription for $9.95 per month.

At launch, altapass will be available across all 36 alta products in the following subject areas:

Knewton brings alta to scale with altapass

Knewton’s effort to make alta more accessible and affordable comes one year after the product’s successful introduction in the U.S. higher education market. Launched in January 2018, alta was used by instructors at more than 250 colleges and universities during the Fall 2018 term.

“It’s clear that we have something special with alta. Now, we’re making it even more affordable and accessible, so that the students who need alta the most can benefit from its impact on learning outcomes,” said Brian Kibby, CEO of Knewton. “We’ve turned the cost structure of our company into a competitive advantage — not just for Knewton, but for students looking for better results at an affordable price.”

“By keeping alta’s pricing simple and consistent across subject areas, we’re taking a lot of the mystery out of the cost of course materials for students. We’re also making alta more affordable for the high number of students who are using alta in more than one course in a single subject area,” said Heather Shelstad, Knewton’s VP of Marketing. “We’re giving students the power to decide which purchasing plan is right for them, and helping them save money no matter which option they choose.”

Knewton releases new insights into student usage, engagement and performance with alta

To provide fresh insight into how alta makes an impact on learning outcomes, Knewton’s data science team released a series of findings regarding student usage, engagement and performance during the Fall 2018 term. They include:

Knewton recently published the results of an independent study of alta’s effectiveness led by the Center for Research and Reform in Education at Johns Hopkins University. The study’s findings drew a link between alta and improved student performance across student ability levels, classrooms and institutions.

“Knewton is an outcomes company,” added Kibby. “While access and affordability represent a key part of alta’s value proposition, there’s nothing more important than its ability to deliver results for students and instructors. We’re going to keep challenging ourselves to set a new standard for transparency regarding those results.”

What’s new in alta for 2019

There are a lot of things that set Knewton apart as a company. One of the most important for our customers is our culture of continuous improvement.

Leaving well enough alone? It’s just not in our DNA.

That’s why, since we launched alta in 2018, we’ve been pounding the pavement, asking every student and instructor we can get in front of how we can make their alta experience better. Our goal: making an even bigger impact on learning outcomes by continually optimizing their alta journey.

Of course, improving the experience of students and instructors requires more than just listening. It takes action. That’s why, over the summer, we began releasing a series of features and enhancements that address the feedback we received.

Below, you can find a handy guide to all of the enhancements we’ve made to alta since launch. If you haven’t taken a look at alta over the past few months, perhaps it’s time for a fresh look.

General improvements for instructors

New functionality and product design makes alta more powerful — and useful — than ever.

Enhancements to alta’s LMS integration

Making learning more accessible is one of the key reasons why we built alta. By enhancing alta’s learning management system integration capabilities, we’re taking accessibility to new heights.

(Even better) Service and support

We’re setting a new standard for the customer experience by bringing service and support into the 21st century.

Testing and assessment enhancements

We’ve made a number of improvements to how instructors prepare and deliver quizzes and exams in alta — and given students new ways to prepare for their exams.

Content enhancements

We’ve made a number improvements to alta’s content with the goal of providing a deeper, more flexible learning experience that leads to better outcomes.

If you have questions about any of alta’s newest features, you can always reach out to us at support@knewton.com. A Knerd will get in touch with you ASAP to walk you through what’s new and answer any questions you may have.

Wishing everyone in our Knerd community lots of success in the semester ahead!

Johns Hopkins University analysis draws link between Knewton’s alta and improved student outcomes

Earlier this year, Knewton presented an efficacy analysis of alta, Knewton’s adaptive learning courseware for higher education, developed by our data science team. From our perspective, the results of our internal analysis strongly suggested a causal link between alta and improved student performance.

Because even the best-intentioned researchers can introduce unconscious biases when making analytical choices, we knew that our in-house analysis could only be part of the story of alta’s effectiveness. As a data science team comprised largely of academics, we have a deep appreciation for the value of independent reproduction of scientific results.

To get a fresh, unbiased perspective on alta’s impact, we shared our fully anonymized Fall 2017 data with the Center for Research and Reform in Education at Johns Hopkins University (JHU). More specifically, we asked JHU to assess the impact of demonstrating concept proficiency by completing alta assignments — as well as alta usage in general — on student outcomes like quiz and test scores, future assignment completion and retention.

Key findings

To gain an understanding of the study’s key findings and conclusions, we invite you to read JHU’s complete analysis of alta’s impact on learning outcomes.

Knewton’s commitment to impact and transparency

These analyses — performed by different teams, in different ways, and across different time periods — represent both a fundamental piece of scientific research and are key to our efforts toward transparency and continuous, data-driven improvement.

Now, the conversation around alta’s impact must expand to include things like direct feedback from instructors, student surveys, user research, and case studies from a variety of classroom settings. There’s a lot of work to be done!

While conducting a conversation that, by design, never ends is in some ways daunting, it keeps us connected to the experiences and results of our users. And from that perspective alone, this endeavor has been a valuable one.

Saving Money with Beautiful Soup and Hashing

Back in the summer of 2017, Knewton’s alta images had an expensive problem. Whether the images were of parabolas, molecules, or supply and demand curves, they were all missing two important things: alt text and long descriptions.

Why do our images need alt text and long descriptions?

As part of being ADA Compliant, alta’s images need alt text and long descriptions to make the images accessible to screen readers. This is important so that our blind or visually impaired students can use assistive technology like screen readers to interact with our visual content.

An accessible image needs alternative text (alt text) and possibly also a long description, which the screen reader can read out to the user. Alternative text is typically brief (we limit ours to 255 characters) and should always be included on accessible images. Long descriptions are used to describe more complex images, like a detailed diagram.

Alt text and long descriptions are added to images via HTML attributes. Here’s an example image:

Fluffy gray cat belonging to a coworker.

Let’s say that the HTML tag for this image is:

<img src="cat.jpg" alt="Fluffy gray cat" longdesc="cat.html"/>

By including alt and longdesc attributes in the image tag, screen readers can read out “Fluffy gray cat” and the contents of cat.html to the user.

The idea is that a visually impaired student can get all the information they need about an image via its alt text and long description. Take this image for example:

This figure shows two curves. The first curve is marked in blue and passes through the points (negative 1, 2), (0, 1), and (1, 1 over 2). The second curve is marked in red and passes through the points (negative 1, 3), (0, 1), and (1, 1 over 3). Attribution: Image by OpenStax Intermediate Algebra is licensed under Creative Commons Attribution 4.0 International License. Download for free here.

This image’s alt text is very specific:

This figure shows two curves. The first curve is marked in blue and passes through the points (negative 1, 2), (0, 1), and (1, 1 over 2). The second curve is marked in red and passes through the points (negative 1, 3), (0, 1), and (1, 1 over 3).

(Note: Due to limitations there are no alt text and long descriptions for images in this blog post, but we’ve included image captions as an alternative for screen readers.)

Unsurprisingly, writing alt text and long descriptions for thousands of images gets expensive fast. If there were only a way for us to not start from scratch…

Scrape OpenStax, save money

A good chunk of Knewton’s content is curated from the open source OpenStax textbooks.

Greg, our Senior Manager of Content, was staring at OpenStax textbooks online — as senior managers of content are wont to do — when it hit him: OpenStax includes alt text with their images. We could scrape out alt text from OpenStax and match them with the images used in our courses! To Greg, this sounded like an ideal Hack Day project.

Knewton holds “Hack Days” a few times a year, in which Knerds (the Knewton employees) get to work on whatever project we wanted. For the August 2017 Hack Day, Greg and I teamed up to make his OpenStax-scraping, money-saving dream happen. Our solution had two steps:

  1. Scrape OpenStax textbooks for images and their associated alt text.
  2. Associate the scraped alt text with their images in our content management system’s database.

Finding images with Beautiful Soup

Conveniently, each OpenStax textbook has a downloadable zip, containing all of the textbook’s HTML and image files.

I wrote a Python script to walk through all the directories of the unzipped book, looking for HTML files. Then it became a straightforward application of Beautiful Soup, a popular Python HTML parser.

>>> import codecs
>>> from bs4 import BeautifulSoup
# file_path is an HTML file's path
>>> page = codecs.open(file_path, 'r', 'utf-8')
>>> soup = BeautifulSoup(page.read(), 'html.parser')
>>> image_tags = soup.find_all('img')

Notice how simple it is to find all img tags. Once I got the HTML content, I just needed two lines:

  1. Create a “soup” using the HTML.
  2. Use the soup’s find_all method.

For each tag in image_tags, Beautiful Soup makes it easy to extract the altand src attributes.

>>> tag
<img alt="Cute puppy" src="puppy.jpg"/>
>>> tag['alt']
'Cute puppy'
>>> tag['src']

The alt attribute contains, well, the alt text. The src attribute contains the file path to the image, which will be used in the next section.

Matching up images with hashing

Now that I have scraped all the alt text in an OpenStax book, I need to match them up with images in our content management system (CMS). This is where hashing comes in: two identical images have the same hash, while two different images have different hashes. If an alt text’s corresponding OpenStax image has a hash that matches the hash of an image in our CMS, then we can apply that alt text to that image in the CMS.

In Python, hashing an image is a matter of using the image’s file path (which was scraped with Beautiful Soup) to read the image’s bytes, and then feeding the bytes into one of Python’s built-in hashing algorithms.

>>> import hashlib
>>> with open(image_path, 'rb') as image:
...     image_bytes = image.read()
>>> hashlib.sha1(image_bytes).hexdigest()

That hash there is of this image below. Try hashing it yourself with the same hashing algorithm and you should see the same result. (This is assuming that the image’s compression has not changed since this post’s publishing.)

Cartoon illustration of a laptop.

What about the long descriptions?

You’ll notice that I glossed over long descriptions in the last few sections. Did we scrape for that at all? Yes and no. OpenStax image tags do not have longdesc attributes. However, we did end up repurposing many OpenStax alt texts as long descriptions because they were so detailed and, well, long.

We also did not use every OpenStax alt text verbatim, as our team of subject matter experts sometimes improved upon them or shortened them to fit within our 255 character limit.

How much money did we save?

We haven’t calculated exactly how much money we saved (we’ve been busy building out alta instead 😉). But if we do a back-of-the-envelope calculation:

Therefore, thousands of images times tens of dollars per image equals tens of thousands of dollars saved! Not too shabby for a hack day project that I coded in a day.

What’s new in alta for Fall 2018

Ahh, the dawn of a new academic year. When the slate is wiped clean and we are given a new opportunity to help students achieve their goals.

There are new courses to be taught. Fresh faces in your classroom. Great new alta features just waiting to be used. With that in mind, we thought we’d provide a handy round-up of everything that’s new in alta for the Fall 2018 term.

If you have any questions, please reach out to us — we’ll have a knerd get in touch with you ASAP to walk you through what’s new and answer any questions you may have.

Now, on to the enhancements!

In-app support via chat

Ever wanted support to feel a little less like sending a message in a bottle and a little more like a two-way conversation with a friend? Check out alta’s new support chat feature (that we think represents the most advanced support infrastructure in the industry):

What does all of this add up to? More immediate responses, more proactive support, and an elegant support experience that’s on par with what you’ve come to expect from alta.

Courses and sections

Have you ever wished that you could manage multiple sections of your alta course — while keeping all the core elements consistent?

With our Courses and Sections update, you can create sections based on your original alta course. Alta will carry over the original course learning objectives, content, and settings to the new sections. (Instructors teaching the new sections may add coursework or modify due dates for homework, but don’t worry: the important stuff will stay the same.)

Courses and Sections is kind of a big deal, so we’ve dedicated an entire blog post to it. If you have questions or would like to learn more, we recommend checking it out.

Improved adaptivity in non-quantitative courses

After gathering feedback from instructors and analyzing how students performed using alta in their Economics courses, we recognized an opportunity to improve the student learning experience.

Over the summer, we released updates to how our adaptive engine measures student progress toward mastery in non-quantitative courses. We’ve also made the learning objectives in these courses more granular to allow us to help students gain proficiency with greater precision.

Desmos graphing questions in for Math, Econ and Stats products

We’re always seeking new ways to present content and assessment in order to help students achieve mastery. That’s why we’re proud to announce that alta products in Math, Economics and Statistics will feature graphing questions from Desmos.

Desmos provides a powerful platform for presenting assessment questions in the form of a graph. The flexibility of Desmos allows us to deliver higher-order comprehension questions and provide better support for graphing questions.

Expect between 25-50% of content within each alta product in these subject areas to feature Desmos.

…and content updates across the board

While we’re continually refining alta’s content to make sure that it’s effective in helping to improve learning outcomes, over the summer, we completed a front-to-back sweep of our content to make sure that everything is in tip-top shape.

Think of it as a little “summer cleaning,” if you will.

There are lots of things to love about alta, and chief among them is the fact alta is always getting better. You can expect to hear more from us soon about the next set of exciting enhancements to alta.

In the meantime, we wish everyone the best of luck with your alta journey this semester!

The New Chalk: How Machine Learning Can Benefit Higher Education

Machine learning, AI and other algorithmic technologies have long promised to enhance the learning experience for college instructors and students.

But what can these technologies actually deliver? What’s required to implement them effectively? And how can they operate in a way that’s both equitable and transparent?

Andrew Jones, a data scientist here at Knewton, joined a panel discussion hosted by EdSurge this week in NYC that sought to answer some of these questions.

The panel, which included a group of educators and education technologists, covered a range of issues, including how machine learning technologies are perceived by students, specific areas where machine learning can make an impact on learning, and the barriers that must be overcome for this technology to be implemented successfully.

When asked to suggest the tough questions that instructors should ask before implementing machine learning technologies in their classroom, Andrew urged instructors to push for greater transparency into how a company’s algorithms work. “Asking what is being optimized for, and why, can give you a sense of [whether a tool] is focused on student outcomes, or whether it is about getting a prediction that’s right more often,” he said.

Toward the end of the session, the focus shifted to instructors themselves — and the role they will play in courses that increasingly feature machine learning technologies, such as virtual assistants

Andrew underscored the central role of the instructor, saying: “I’d rather see machine learning reach the level of chalk.”

You can find a full recap of the event over on EdSurge.

Connecting our Knerds: Day of Knerdvocate Collaboration

Earlier this summer, Knewton hosted its first national Knerd Camp, bringing together adopters from across the country to discuss all things alta with our staff knerds.

Knewton’s “knerdvocates” played a key role in making the meeting a success. Knerdvocates are educators who use alta to drive student success in their own courses and help others do the same in theirs through peer coaching, best practices, and thought leadership.

During the 2-day Knerd Camp, instructors were able to experience the day in the life of a Knewton Knerd in New York City. Sharing Knewton’s vision of “putting achievement in reach for everyone,” attendees discussed their teaching challenges, offered advice, and collaborated with each other and staff Knerds on even better ways to help students using alta. They also got the behind-the-scenes view into the data science behind alta, and enjoyed a preview of the newly enhanced interface with the Knewton team of technology product developers, data scientists, and support team.

Instructor, Shawn Shields commented, “I really learned a lot from this event in terms of how it works and hearing others’ experiences and best practices. I ended up with quite a few good ideas from others that I can modify and add to my course,confirming how important it is to give educators opportunities for peer-to-peer coaching in a comfortable, positive setting.

Passion was also a recurring theme, with Knerdvocates becoming inspired by the passion of the Knerd learning community–”I loved the opportunity to talk with the Knerds who were so passionate about what they do…{….}. the Knerds genuinely care about what they do. You can’t fake that kind of passion and dedication,” indicated instructor, Melanie Yosko

Knerd Camp was rounded out with a cruise on the Hudson to visit New York City’s famous trademarks and dinner at the suitably named tapas restaurant, alta.

Building on the success of our first national Knerd Camp, Knewton is planning to expand the program with a series of regional Knerd Camps for instructors who are interested in learning more about alta. Keep your eyes open for one in your area.


Knewton secures $25 million in funding, fueling company’s efforts to put achievement in reach for all learners with Alta

TriplePoint Capital joins company’s existing investors in providing funding to accelerate the growth of Alta

NEW YORK, August 21, 2018 — Knewton, the world’s leader in adaptive learning products and technologies, has closed its latest financing round, which includes up to $25 million in capital. Knewton plans to use the funding to scale Alta, the company’s adaptive learning courseware for higher education, which has established strong momentum since its debut in the U.S. market in January 2018.

The financing round is led by TriplePoint Capital with a debt facility of up to $20 million. Knewton’s existing investors — which include Accel, Atomico, Bessemer Venture Partners, FirstMark Capital, First Round Capital, Founders Fund and Sofina — invested an additional $5 million.

“Knewton’s adaptive learning platform has long been the envy of the ed-tech industry. By putting it directly in the hands of students and instructors with Alta, we’ve figured out how we can make the biggest impact on improving student outcomes,” said Brian Kibby, CEO of Knewton. “With this investment, we will bring Alta to scale while developing new ways of using our technology to enable true data-driven teaching and learning throughout the course experience.”

“What Knewton has accomplished with Alta in less than eight months is remarkable. We’re excited to support Knewton’s effort to put Alta into the hands of every college student in the U.S.,” said Jim Labe, CEO of TriplePoint Capital.

Higher ed instructors are making the switch to Alta

Since its launch in January 2018, Alta has received an overwhelmingly positive response from instructors in the U.S. higher education market, with many instructors opting to choose Alta’s combination of dynamic adaptivity and unparalleled insights into student performance, and high quality, openly available expertly-developed content over traditional textbook and digital homework offerings.

Alta delivers a personalized learning experience for students by harnessing the power of Knewton’s adaptive learning technology. In 2017, Knewton invested in making Alta accessible to all learners, achieving WCAG 2.0 AA-level ADA compliance across Alta’s technology, content and user experience. By leveraging high quality, openly available content, Knewton is able to offer Alta to students for only $44 per course.

Knewton expects that more than 250 colleges and universities will be using Alta during the Fall 2018 term.

“I chose Alta because it levels the playing field for students. It provides support so that I can engage all students in the classroom,” said Donna Jean, associate professor of chemistry, Park University. “If a student is struggling with mathematical problems, Alta quickly diagnoses that and presents the student with instruction geared towards those knowledge gaps.”

“Alta is the first personalized learning system I’ve used that truly delivers on the promise of adaptive technology by continually measuring students’ proficiency levels and providing feedback designed to help them achieve mastery,” said Andrew Moore, department chair and assistant professor of mathematics at National Louis University. “With Alta, students don’t have to wait for their next diagnostic or for me to provide them with that feedback — they receive it immediately.”

For the Fall 2018 term, Knewton will offer 36 Alta products in courses across mathematics, economics, chemistry and statistics, including seven products developed exclusively to support math corequisite curriculum redesign initiatives.

For students, alta delivers learning that lasts

Alta is designed to help students master the learning objectives covered in their course.

To measure Alta’s impact on mastery, Knewton analyzed the results of more than 10,000 students who used Alta in 2017. The findings revealed:

As part of Knewton’s commitment to transparency regarding Alta’s effectiveness, the company is collaborating with Johns Hopkins University’s Center for Research and Reform to measure the effectiveness of Alta in helping students achieve mastery. Knewton plans to release the findings of Johns Hopkins University — which were developed independently of Knewton’s own analysis presented above — in the months ahead.


About Knewton

Knewton puts achievement within reach for everyone through adaptive learning technology and products that deliver personalized and lasting learning experiences. Educators, schools and universities, and education companies around the world use Knewton to power and provide digital courses that dynamically adapt to each student’s unique needs. More than 15 million students around the world have used Knewton-powered courses to date. Knewton was founded in 2008 and is headquartered in New York City.

About Triple Point Capital

TriplePoint Capital is a Sand Hill Road-based global financing provider to high growth venture capital-backed companies throughout their lifespan, providing customized debt financing, leasing and direct equity investments. TriplePoint provides unparalleled levels of creativity, flexibility and customer service to serve as the primary debt financing provider for leading venture capital-backed companies in the technology, cleantech and life sciences sectors and is the only debt provider equipped to meet the unique needs of high growth venture-backed companies at every stage of their development. For more information, visit www.triplepointcapital.com.

Media Contact


(415) 323-0850


Knewton’s UX Research Practice Gears Up for Back-to-School

As back-to-school season approaches, Knewton is diligently working on powerful new feature releases and product updates. And Knewton’s User Experience Research (UXR) practice supports this work by incorporating instructor and student feedback through a host of research methods.

We vet draft experiences with users, identify issues, iterate, and validate potential solutions. And this is all often before a single line of code is written for a new feature release or product update.

Knewton UXR recently conducted efforts to inform an upcoming alta feature that allows course coordinators to create and manage multi-section courses. We wanted to first understand educators’ current practice, and then swiftly iterate and validate draft designs in light of user feedback. In doing so, by the end of our process, we could come to a useful and usable solution.

We approached research through:

  1. Focus Group
  2. 1:1 Interviews
  3. Persona Development
  4. Rapid Iterative Testing and Evaluation

Focus Groups & 1:1 Interviews

Prior to initiating design work, we took a step back and conducted remote focus groups and 1:1 interviews to understand how coordinators across the country currently create multi-section courses. What does this process look like for them? Where do issues arise? How do Learning Management Systems come into play? This early research provided our cross-functional team with a deeper knowledge of users’ needs and goals.

Persona Development

We used information gleaned from early research sessions to create a course coordinator persona. User goals were defined here, giving teams common language to talk about relevant problems — and how to best solve them.

Rapid Iterative Testing and Evaluation

As the design team started building out a draft experience, UXR hosted 1:1 remote usability testing sessions with course coordinators (users and potential users) across the country. We screen-shared semi-functional draft designs, turned over control of the keyboard and mouse, and asked participants task-oriented and open-ended questions. Because stakeholders (design, product, engineering) were observing each session, we quickly identified design issues, iterated in-between sessions, and validated potential solutions with subsequent users.

What We Learned

What are some things we learned in our multi-section course research? Well…A LOT! But, sometimes the most memorable findings are the ones that are those ‘aha’ moments — the ones where we watch users go through a potential workflow and an imaginary lightbulb goes off for us.

We immediately consider an easier way for users to accomplish a task. Designs are revised and further validated.

One example of an ‘aha’ moment within our research involved ‘auto-save’ during educators’ process of building out coursework. Auto-save seems harmless enough, right? But employing auto-save within the complex task of building out coursework for a multi-section course didn’t seem to give users enough confidence that their work was indeed being saved. Designs were revised and the issue was alleviated.

Another compelling finding involved course Initialization links — what instructors would need to click within a workflow to make the course section ‘start.’ Early draft designs did not seem to make enough distinction between this link and additional content on the same screen. Again, designs were revised to more overtly highlight where users should navigate to initialize the course.

Effectively Leveraging UXR for Educators

Using a multi-method research approach provided our cross-functional team with a solid understanding of user needs prior to any design work, and the flexibility to improve designs in-between research sessions.

Upon concluding our design research, we came away away with an experience we’re confident is useful and usable, and can be put into development for our customers.

Thanks to Michael Mancuso.