Upcoming LMS Users Conference Coverage
Publication plans, a slowdown in the market, and (bingo!) generative AI
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Over the past three weeks, Glenda Morgan, Jeanette Wiseman, and I have tag teamed to attend the D2L Fusion, Anthology (Blackboard) Together, and Instructure Canvas users conferences. This year we wanted to release the posts after the last of them, which we expect to do over the next week. With this being the first year with our premium newsletter On EdTech+, we also would like to avoid duplicate content, and to do so we will publish each post with free content above a paywall break followed by content for premium subscribers. [Full-page audio link]
Before we get to those posts, I’d first like to comment on two topics that were relevant at the conferences but span the LMS market. Namely, a market slowdown and the early views of how generative AI is being deployed.
LMS Market Slowdown
One topic that was under the surface yet still apparent at all three conferences is that the academic LMS market is slowing down again. There are fewer Requests for Proposals (RFPs) and tenders out right now, and this trend can be seen in the data from our friends at ListEdTech:
The data come from North America, but the trend can be seen in Europe and other global regions. After a spike in 2020 due to the pandemic-driven school closures, the activity has been trending down. This trend roughly aligns with ListEdTech’s RFP-based predictions.
I don’t think this slowdown means that the LMS is becoming less important - far from it - but rather due to other market forces. There are still RFPs in progress, but the last big one (with hundreds of thousands of students and multiple campuses) was CUNY. There is also an active tender for enabling agreements for four Nordic countries - Sweden, Iceland, Denmark, and Finland. But overall activity is down.
Some of the drivers of this trend:
Improvements in Anthology (Blackboard) Learn leading to increased retention rates without an RFP involved (i.e., re-signing for Learn);
The general improvement of the big four solutions (Instructure Canvas, D2L Brightspace, Anthology Learn, and Moodle) leading to fewer we’ve got to change now situations; and
Other factors that we are studying more before offering commentary.
What is not happening in our opinion, however, is LMSs becoming commodities. We have market consolidation behind the big four, and we have a slowdown in RFPs / tenders, but that does not mean that switching from one vendor to another has no impact on how a college or university offers its virtual presence through an LMS (obviously for face-to-face augmentation, hybrid, and fully online modalities). In fact, I would argue that the primary vendors are differentiating in strategy. Commodities are fungible, and switching suppliers of this type will not lead to significant usage differences (typically just in pricing and availability). LMSs are not fungible, and vendor migrations can impact a college or university’s usage of the tool significantly - the vendors are differentiated.
One of the areas where we saw differentiation at the recent LMS users conferences is the approach to generative AI.
What was common (and in a good way) is that D2L, Anthology, and Instructure have all started frameworks, or sets of principles, to guide their work with generative AI. You can find D2L’s Responsible AI Principles, Anthology’s Trustworthy AI Approach, and Instructure’s AI Guiding Principles at the links.
However, the AI initial implementations seen at the conferences differ in approach.
D2L showed an AI tool to generate formative assessment questions in the course design workflow, subject to course design edits and approval. The company also described tools for improved contextualized help and a partnership with CopyLeaks for AI content detection. All three announcements were relatively subdued, and I think the formative assessment usage is the most significant, partially as D2L’s emphasis on content creation is increasing.
Anthology (Blackboard) showed new tools for AI-based course structure design, along with a number of smaller use cases such as image creation, test question suggestions, improved student overviews and progress tracking, and accessibility checking. Anthology is taking more of a holistic approach on many fronts.
Instructure emphasized their partnerships and learning ecosystem, and the biggest announcement was their work to integrate Khan Academy’s new tool Khanmigo. There were also references to course design tools, but the bigger emphasis was more of a research lab approach. Instructure shared multiple AI usages in research (with no productization promises and no roadmap dates), with several use cases getting into tricky areas such as automated student feedback and outcomes alignment with standards.
We’ll cover these announcements and (quasi) demos in our upcoming posts, but the point here is the differences. Point solutions focused on content creation vs. holistic multi-usage vs. partnership and research. The personalities of the companies, and therefore their generative AI strategies, are quite different.
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