Anthology Together 23 Conference Notes
Continuing post-acquisition improvements at Blackboard, but will it affect the market?
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July is typically the busiest month for LMS user conferences, and over the past few weeks we've attended D2L Fusion in Anaheim (for Brightspace), Anthology Together in Nashville (for Blackboard Learn), and InstructureCon in Denver (for Canvas). Today’s newsletter will be on Anthology Together. [Full-page audio link]
The Anthology conference, held from July 17-19, marked the second gathering since Blackboard ceased operating as a standalone company and transformed into a brand for a product line. We previously covered this transition and its impact last year. This year, the atmosphere was remarkably positive, not only among company officials and staff but also among attendees and clients. From the conference's standpoint, the integration seemed significantly improved – the branding was robust, and there was a stronger sense of Anthology coming together as a cohesive company.
Learn Ultra Ten Years On
In terms of anniversaries, this was also the ten-year milestone since the announcement of Blackboard Learn Ultra. This became part of the lens through which we viewed the conference.
The past year has been eventful for Blackboard, as they delivered more than 200 new features. This accomplishment reflects Anthology's leadership investing in the platform to accelerate feature development. Consequently, many feature gaps between Learn Original and Learn Ultra have been narrowed, which was crucial for establishing credibility as an LMS contender.
What stood out was not just the number of added features but the extent to which these enhancements were driven by customer input. There has been a noticeable shift in how Anthology listens to clients, which had been a historical weakness for Blackboard. This positive change was emphasized not only by Anthology executives, but more importantly by customers themselves, even during unscripted side conversations.
However, the big question for me is whether these improvements have come too late. It has been a decade since Learn Ultra was announced, a considerable amount of time in technology, even in EdTech. During this prolonged wait for feature parity with Learn Original, many customers sought alternative solutions. While some real positive signs and announcements have been made, Anthology still needs to demonstrate their commitment to not being caught flatfooted again. They must act promptly to address any future feature gaps that may arise.
Adoption & migration
There was a sense in which through the conference the company was almost trying to will customers to make the move from Learn Original to Learn Ultra. There were many sessions on the topic of migration and how colleges and universities had made the move. While the US has been slower in this adoption compared to other global regions, Anthology reported that 35% of active courses are now on Learn Ultra. The company has invested in creating dedicated adoption leads, an adoption toolkit with templates, and a workshop in a box, as well as a bulk course conversion tool released in June. Additionally, they established a Learn Ultra User Group for customers in the past six months.
These adoption tools and toolkit make a lot of sense, and our conversations with clients revealed that they were very much needed in the past and are being used and appreciated now. But it begs the question of why was all this not done before. A long time before. Most of these types of resources should be table stakes when trying to get customers to go from one version of an application to the next. Waiting so long to do so is perplexing, especially given the non-trivial nature of within-Blackboard migrations in the past, for example the migration from the legacy WebCT LMS to Blackboard 9.1.
New Product Announcements
A striking feature of the conference was the number of live demonstrations and the detail on product improvements that Anthology showed in roadmap sessions. This openness contrasted with some previous years where details were sparse. There were several new features announced, many of which are likely to have a meaningful impact, for example the completely rebuilt grade book which they see as a contender to leapfrog the Canvas’ SpeedGrader. This tool will come with a more flexible approach to grading, including the ability to grade by student, by question, or a mix of both, as well as other features such as the ability to group similar responses and provide bulk feedback. In Learn Ultra there will be greater options for personalized learning pathways based on enhanced release conditions.
Generative AI Approach
When it comes to product, the big announcement was the integration of generative AI into the platform. Anthology is using AI to power several new components within Learn Ultra, including an accessibility checker, a holistic student overview, progress tracking, and course building tools.
We got the best look at the course building tools and this seems to be the core feature that attracted the most attention by educators. The tool was developed within their Trustworthy AI Framework and in conversation with customers. It will allow instructors to quickly design the basic outline of a course, add custom AI-driven graphics (powered by Unsplash), and add quiz questions based on course content. Customers described themselves as cautiously optimistic about the new AI capabilities.
I have a couple of concerns, one about the usefulness of the tool and the other about cost. On one level I can see the attraction of a feature that gets to the heart of the teaching and learning enterprise and promises to save faculty time. From the demo, it seems that at its core what the AI tool does is take a topic and suggest modules that could make up a course. I am not sure that this is where instructors are going to need help or where they even want help. I would argue that most people who find themselves needing to design a course can probably come up with a rough outline off the top of their heads based on their knowledge of the field. What they tend to be more interested in with initial course design is how other instructors in other places have structured their courses – they want to see other people’s syllabi (and one of the cruel inadvertent consequences of widespread LMS use is that other people’s syllabi are now harder to find).
Where a AI-based design tool might make more sense is to automate instructional design capabilities such as helping instructors make linkages between desired outcomes and course content and activity, or recommending interventions such as assessments or exercises. Anthology has plans to automate tasks like embedded knowledge checks and to enhance course design in their 6 months+ roadmap, but the design especially seems to be more about templating. I am not sure how a wider variety of templates is really using the power of AI. What I am talking about may be beyond what generative AI can currently do, but that is what is needed in a course builder - not a cheat sheet for module topics or a template library.
A second concern I have is about cost - and I note that this concern goes across the LMS market. Anthology has said that the AI tools will carry no additional costs, but other EdTech vendors such as Duolingo and Khan Academy have described the fairly steep costs associated with using ChatGPT in their products. Duolingo passes this cost on to users and Khan Academy has plans to do so.
I have no doubt there will be steep costs associated with the inclusion of AI in Blackboard Learn Ultra (and other LMS products). Given Blackboard’s recent history of giving users too little storage and then charging customers for storage overages, I think it is reasonable to assume that institutions might see additional charges for the AI tools, especially if usage is heavy. Some might argue that the storage overages originated under different ownership, but we have not seen any meaningful change in direction under Anthology on this topic.
On a more positive note, I was impressed by Anthology’s loudly-stated public commitment to not using AI for plagiarism detection. I may have broken out of my analyst role for just a second and applauded that last point in the Roadmap session.
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