Cambridge University Press & Assessment has acquired CogBooks, the pioneering online learning technology company and leader in adaptive courseware, as it looks to help shape the future of education in an increasingly digital, post-COVID world.
The move will put Cambridge at the forefront of adaptive learning by bringing its renowned teaching and learning content and global reach together with CogBooks’ expertise in the field, its established platform and courseware.
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Tennessee State University (TSU), recognized as an accredited historically black college or university (HBCU), partnered with CogBooks to boost underrepresented student enrollment in their agriculture program, paving the way for diverse learners to discover fruitful careers in the agriculture industry. Working together, we created a multi-course curriculum with the help of high school and college instructors from around the country.
CogBooks sat down with John C. Ricketts, PhD, Professor and Extension Specialist Agricultural and Environmental Sciences at TSU to discuss their enrollment challenges and the role our adaptive learning platform played in the solution.
The number of courseware options available to higher education increases each year. While more options can be a good thing, it makes it difficult for instructors to find the best courseware for their needs.
Assessing courseware can be a lengthy endeavor. Most instructors begin their search by identifying courseware options available for courses they teach. Then they confirm which options work with their school’s learning management system. Only then are they able to evaluate the quality of the courseware’s content and user experience. Ideally, instructors will also want to factor in the courseware’s cost to the student.
This search and assessment method still leaves many considerations unaddressed. That’s potentially problematic. Courseware plays a critical role in attracting, retaining, and supporting students.
Fortunately, there is a new way to find and compare courseware options.
Adaptive courseware is used successfully across diverse higher education settings. Enterprises including philanthropic organizations such as the Bill & Melinda Gates Foundation have supported studies evaluating the equity and learning outcomes benefits of adaptive courseware and The Association of Public & Land-Grant Universities has gone as far as developing an Accelerating Adoption of Adaptive Courseware initiative. Adaptive courseware, while nearly two decades in maturity, continues to be a hot topic of discussion at industry conferences year after year.
Despite the growth in usage, availability, outcomes, impact on equity and capabilities of adaptive courseware, some instructors continue to have reservations regarding a concern adaptive courseware is like “teaching on auto-pilot.”
The reality of teaching with some adaptive courseware could not be more different.
In 2020, CogBooks surveyed higher education instructors who use our adaptive courseware. We explored how the courseware performed for themselves and for their students, how instructors felt about using it and sought opinions on the content and its ease of use.
Now, we are sharing how your fellow instructors evaluated CogBooks adaptive courseware. Using their feedback can help determine if CogBooks adaptive courseware is suitable for your class.
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Part 4 of our 4 part series on big data in learning.
Big data has led to big changes in statistics. One could argue that our existing paradigm has been rendered impotent in many cases by big data.
Historically it has been difficult and largely impossible to gather all data in a target audience or domain. We were taught that sampling data is the way to go, and then to avoid selection and sample bias, we avoid self-selection or snowball samples and randomize. All of this assumed scarcity of data.
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Part 3 of our 4 part series on big data in learning.
Learning data can be harvested at ten different levels. The included inverted pyramid shows a hierarchy of levels from which data can be harvested. Note that it moves through different categories, but, in general, it describes the move upwards towards big data, as each level does, potentially, include those below.
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Part 2 of our 4 part series on big data in learning.
Let’s start with a dose of reality: education and training have always coveted data. But in any honest appraisal of this data collection, we have to admit that it is largely the wrong data. There has historically been too much focus on start and end point data. All dull inputs and outputs. What we need to focus on is the cognitive improvement of the learner. Included are five examples of data, mostly superficial, that account for the vast bulk of the data collected in education and training.
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Part 1 of our 4 part series on big data in learning.
Big Data, at all sorts of levels in learning, reveals secrets we never imagined we could discover. It reveals things to you, the user, searcher, buyer, and learner. It also reveals things about you to the seller, ad vendors, tech giants, and educational institutions. Big data is now big business, where megabytes mean megabucks. Given that less than 2% of all information is now non-digital, it is clear where the data mining will unearth its treasure—online. As we do more online, searching, buying, selling, communicating, dating, banking, socializing, and learning, we create more and more data that provides fuel for algorithms that improve with big numbers. The more you feed these algorithms, the more useful they become.
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CogBooks is releasing new platform enhancements this month that dramatically improve how institutions, instructors and their students will benefit from the use of its online adaptive courseware. With ease-of-use, instructor agency, data transparency and student motivation in focus, CogBooks’ latest release delivers exciting enhancements to customers.
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