I had a great conversation with a group of graduate students recently. These amazing young women are digging in, learning, and figuring out what is next for their careers. During our chat, one pulled out their last lit review assignment.
It would be an understatement to say I was shocked.
In today’s evolving academic landscape, the importance of traditional literature reviews as a skill for graduate students may diminish (and probably should, if I am honest). With the vast availability of digital resources and sophisticated search engines, students (and researchers) now have quick access to an immense volume of scholarly articles and research papers. As a result, the need to spend extensive time and effort on conducting literature reviews has significantly reduced.
As graduate students increasingly focus on specialized areas of study, their time might be better spent mastering advanced research methodologies and data analysis techniques (especially those that harness AI) rather than dedicating substantial effort to focusing on what already exists.
If we are going to actualize the human effort, maybe it’s time to use our collective tools to see what these future researchers can dream up (not just what they can replicate).
Understanding the process, the indicators of quality, and the essential lessons of literature reviews might be good enough. With emerging tools pushing content of open-access journals and publications in real-time, there may be some value in letting go of the old and troubleshooting the new.
Speaking of new, if you haven’t yet seen Elicit, take a minute and check it out. Here’s a screen recording that I captured for a colleague recently.
While literature reviews were once considered a fundamental skill for graduate students, the emergence of new tools challenges the necessity of dedicating extensive time and effort to such a time-consuming task. What would academic advisors say if those young ladies used Elicit to develop the basis for their lit review, then wrote up their findings based on analytics and summaries? Highlighting additional notes that the AI did not identify seems more worthy than reconstructing what AI can so systematically complete.
I hope they will be excited to see what the next generation can do.
Even though the graduate students I was with are the example I am using, it may be time for all of us responsible for cultivating the next generation of talent and leadership to open our eyes and see how we can better empower innovation and specialized contributions to respective fields by changing some of our practices and opening the door to use time and energy a little differently.