Key points:
- Not all learning technology is created equal
- 6 steps for effective learning analytics
- 5 things to look for in a course materials partner
- For more news on learning technologies, visit eCN’s Teaching & Learning hub
For decades, educational technology investments in higher education have followed a predictable pattern: Improve the teaching, and learning will follow. Institutions have poured resources into technologies that power training programs, aim to spark pedagogical innovation, and introduce sophisticated instructional design. The technology that has arguably made the biggest splash–online learning–has succeeded primarily by making education less expensive, more flexible, and easier to scale. Yet for all of these advances, we’ve largely missed a critical question: Are we actually helping students learn more effectively and efficiently?
The answer is that we’ve focused on the wrong priorities. Our edtech investments have overwhelmingly focused on the instructor side of the equation while overlooking the learners themselves. There’s a massive, untapped opportunity to apply technology where it matters most: helping students develop the skills and remove the barriers that will improve their ability to learn.
We need to acknowledge an uncomfortable truth: Learning is not the inevitable byproduct of teaching and instruction. Teachers are like personal trainers, but to see results, students still need to do the exercise. This isn’t to diminish the importance of good teaching. Technology can certainly help present information in more intuitive and engaging ways. But learning requires far more than the passive ingestion of information, no matter how beautifully that information is packaged or delivered.
Real learning demands that students actively engage with material in productive ways. They must struggle with complex ideas, revise their understanding of concepts, and apply new knowledge to solve problems. While instructors and technology can help support this cognitive work, they can’t replace it. It must happen in the student’s mind. Institutions must find ways to equip, empower, and encourage students to do the work necessary to learn.
The two types of cognitive friction
That struggle that students must undergo for learning to take place is what I like to call “productive friction.” Understanding the difference between productive and unproductive friction is crucial to making edtech investments that actually improve student learning.
Academic research on learning describes productive friction as the desirable difficulty that’s necessary for learning to occur. Just as exercise is necessary to improve strength and endurance, learning requires the neurological process of forming new connections. Technologies that remove productive friction, such as using generative AI to write an essay for you, actively harm learning by doing the cognitive work students need to do themselves.
Unproductive friction, by contrast, consists of barriers that prevent students from engaging in that necessary cognitive work. For example, there are administrative tasks in note-taking that don’t contribute to learning itself, which could be more efficiently completed by AI. Students whose first language isn’t English may struggle under the cognitive load of operating in another language, which makes comprehending learning material a more overwhelming process. Neurodivergent students might not be able to benefit from traditional instructional methods. Technologies that remove these barriers don’t undermine learning. They facilitate it.
The retention crisis demands better learning tools
The case for investing in learning-focused technologies isn’t just pedagogical. It’s an existential challenge for higher education. According to the Education Data Initiative, 22.3 percent of first-year students drop out within twelve months. These students face serious consequences: College dropouts earn 35 percent less income than degree holders. At a time when federal funding faces dramatic cuts and higher education institutions are under pressure to improve graduation and employability rates, student success and retention has become crucial for financial survival. Every student who drops out represents not just a personal tragedy, but lost tuition revenue that institutions can ill afford.
This is where technology that reduces unproductive friction can make a real difference. Consider AI-supported notetaking: Speech-to-text tools for captions and transcription remove the bottleneck of having to simultaneously capture and process lecture content. Critically, students still need to identify what’s important in those notes and determine how to use that information–that’s productive friction. In another example, AI translation can help non-native English speakers access course content in their first language, removing a language barrier while retaining the need for the student to understand and apply concepts. Further, AI-generated quizzes based on course content and student notes can provide personalized practice opportunities that help students identify gaps in their understanding. When thoughtfully designed and deployed, AI-powered solutions can remove barriers to learning, personalize the learning experience and boost learner confidence.
Buyer beware
Here’s where higher education leaders must exercise caution. Not all learning technology is created equal, and the edtech market is crowded with solutions that sound promising but lack evidence that they truly work.
Ideally, vendors should be able to demonstrate with hard data from independent sources that their technologies have a statistically significant impact on learning outcomes. Startups and smaller companies, of course, may not be able to supply this kind of data, and setting a hard standard of evidence could cut higher ed off from valuable innovations. So, at minimum, edtech products should be able to articulate how they make learning better, not just how they facilitate an activity. The conversation should start with an understanding of what makes learning harder than it needs to be, and a technology solution should remove these barriers. Institutions are encouraged to try it and analyze the results themselves.
Just as important, institutions must scrutinize whether tools inadvertently remove productive friction. Technologies that automatically summarize notes might seem helpful, but research shows that the act of synthesizing information is critical for learning. Similarly, generative AI tools that essentially complete assignments for students remove the very cognitive work that produces learning.
Buying technology for technology’s sake helps no one–not students, not faculty, and certainly not institutional outcomes.
A path forward
To ensure students succeed, higher education must shift its edtech investment strategy toward proven technologies focused on improving learning by removing unproductive friction. This means moving beyond the teaching-centric view that has dominated for decades, and asking different questions:
- What barriers prevent our students from engaging deeply with course material?
- What skills do they lack that would help them learn more effectively?
- How can technology remove obstacles without removing the cognitive work that learning requires?
By making this shift, higher education can improve retention, increase student graduation rates, and build a more sustainable financial model. More importantly, institutions can fulfill a fundamental mission: helping students learn. The technology exists. The research exists. What’s needed now is the will to look past the edtech blind spot and invest and believe in the students themselves.
Dave Tucker is the CEO and founder of Genio. With over 15 years’ experience in higher education technology, he has driven the development of award-winning products, helping students to overcome common learning challenges and support independent learning across the globe.
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