Those challenges ARE challenging.
Let me start by saying that when I first became aware of OER (2014 or so) it was clear that cost alone was not going to be enough to drive colleagues away from high costs texts. I certainly had the experience of this, trying to convince them. In a 2015 newsletter I wrote for the Committee on Computers in Chemical Education
Who ordered that?
If it is a college textbook, the professor. Publishers market their books to faculty, rather than to students who purchase them. . . . Textbooks are marketed and in great part selected based on the services that the publishers offer to faculty including such “traditional” features as publishers’ representatives, desk copies, solution manuals, test banks and slides and more modern apps including online homework systems.
I’ve spoken about this at many conferences since.
Today, certainly for STEM, the driver for faculty adoption is not textbook costs but the availability of online homework system. Cliff Lalonde and J Caldwell at BC Campus did a survey on the cost to students of commercial homework systems which average $80 Canadian per course per semester.
To meet this challenge LibreTexts, with co-sponsorship from the California Education Learning Lab, has built an open, online homework system, ADAPT which can be used self-standing or incorporated into our LibreTexts. It can handle questions from WebWork, ImathAS, H5P or QTI repositories. Working with Learnful, LibreTexts built an open H5P Studio to support ADAPT as well as the textbooks. (YouTube workshop on ADAPT).
Translation is another issue. In 2017, I began to look at the geographic distribution of LibreTexts users and was quite surprised. About 60% came from countries where English was a language learned in school. Students could obviously use the English language texts but they would be helped if those materials were available in languages that they grew up speaking.
We built the Polyglot Engine to translate books into other languages taking advantage of the uniform formatting in LibreTexts. Using Amazon’s AI translation app all 1000+ texts on our Bookshelves have been translated into Spanish and Ukrainian and about 50 texts into a sampling of other languages including French, Portuguese, Swahili, Arabic, Hindi and Chinese. In principle this can now be done for any pair of the 81 languages that the Amazon Translate neural machine translation service handles.
These translations from English language texts are useable, but not perfect. We urgently welcome anyone who will help editing, curating and improving them.