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Why Modern Graduate Students Are Nothing Like Their Parents' Generation: Learning - or not - in the Information Age
Volume 3: Learning - or not - in the Information Age
I’m glad you’re joining me again as we discuss the metacognition of the Information Age’s graduate students. Most importantly, we want to know how their learning differs from that of their instructors, who were likely educated before or in the earlier stages of the Information Age.
Last week, we discussed what was different about these new learners; this week, I’d like to examine the fallout of their differences. Some questions we’ll consider are:
What new learning styles have developed?
What are some learning disadvantages for students who have always had information at their fingertips?
How might we adapt our teaching styles to them?
New learning styles in the Information Age
Education delivery within graduate programs has undergone profound changes through digital evolution.
Consider that 85% of students report increased use of video chatting technologies—a statistic reflecting tool adoption and a fundamental shift in learning environments [1].
66% of students prefer digital textbooks to physical ones, while 67% choose digital assessments over traditional paper examinations [1].
Medical graduate students particularly gravitate toward microlearning—brief, focused educational segments lasting 5-15 minutes that match typical adult attention capabilities [1]. Preference for shortened learning sessions isn't merely coincidental but grounded in brain science: neuroimaging research confirms that focused attention naturally wanes after 10-15 minutes [1]. Microlearning thus represents a biologically appropriate educational approach rather than simply following a trend.
Research indicates 66% of students used AI tools during a recent semester to support their academic pursuits, with 20% accessing resources like ChatGPT ten times or more [2].
The Metacognition Gap for Information Age Learners
Artificial intelligence now serves as a cornerstone of modern educational approaches. These systems create personalized educational pathways tailored to individual learning patterns. However, they are also a source of considerable frustration to coaches (perhaps like myself) who want to convince students to read their textbooks rather than rely on AI answers for the questions that will likely be on their next exam. AI has notable drawbacks and makes numerous mistakes, and despite being impressive technology, it still cannot master the subtleties and nuances of human communication. I don’t know what the future holds, but at present, no AI can convey material or challenge students like a talented, experienced instructor.
Notably, AI doesn’t “teach” anything, no more than a textbook does. It is an information-delivery system; it is up to students to teach themselves the material by processing it. That task is a significant concern for students of the Information Age. If material is always as available as a good WiFi connection, when must they ever “learn how to learn?”
A modern student may not feel the pressure to memorize information—that’s one thing—but at some point, learning is more than memorization. Finding information online is great, except that it stops the process of knowledge fairly low on Bloom’s Taxonomy: AI delivers information; if a student reads it, they absorb knowledge, and if the student processes it, perhaps comprehension is achieved. Application, analysis, synthesis, and evaluation are interactive processes that must occur internally to form long-term memory and understanding.
In fairness, most students comprehend this already, or if not, they catch on fairly quickly. However, when students struggle and come to me for coaching, I find them needing to jump this hurdle ever more frequently. A constant source of information is not the equivalent of learning. The solution is not much different from a student twenty years ago who had trouble absorbing all the info from voluminous textbooks, except for one thing. Many AI-reliant students assume that AI is a superior solution because it is more advanced. Yet the proper solution remains the same as always: they must employ metacognition. They must learn how to learn.
Adapting classrooms and labs to the Information Age
Contemporary learners expect educational experiences aligned with their digital lives. These preferences extend beyond simple convenience; they prefer its adaptability, which allows students to engage with materials on their schedule and progress according to individual needs. Most of you readers have probably adopted changes into your teaching and coaching styles that incorporate our digital lives. Here are a few examples:
Classroom dynamics have evolved through collaborative digital tools. Platforms like “Top Hat” enable educators to embed live quizzes and discussions directly into lectures, offering immediate insight into student understanding [2]. The program “Hypothes” facilitates group annotation and allows readers to experience direct engagement with medical literature [2].
Digital shifts present challenges alongside their benefits. Research confirms that dividing attention across multiple digital platforms impairs concentration and working memory, ultimately affecting academic performance measures [3]. As is the case with those who work entirely online from home or comprise their social lives of digital interactions, the reduced face-to-face interactions in digital learning environments can foster feelings of disconnection.
Perhaps most importantly, we must convey to learners and instructors that they are approaching the material from different mindsets. With this understanding, we can better accommodate one another.
Conclusion
Finding equilibrium remains essential. Evidence suggests that blending digital technologies with traditional classroom elements offers more benefits than completely replacing one approach with another [4]. So, let’s take today’s blog as an example. I used AI as a tool to write it. I tasked it with finding articles about how the Information Age is changing medical teaching environments. It delivered four articles and a summary of each. Now, if I had simply “cut and pasted” what AI brought me, I wouldn’t have had a thoughtful interaction with the material, nor would I have considered the implications of the knowledge. So I believe that this has been a “blending” of AI tools with traditional writing elements. I’d be interested to know your thoughts, so post a comment if you wish!
As always, I hope you’ll join me next week. We’ll wrap up our discussion about teaching the students of the Information Age.
Here, by the way, are the articles that my AI bot fetched for me:
[2] - https://blogs.iu.edu/citl/2023/07/19/collaborative-learning-technologies-for-graduate-instructors/
[3] - https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-018-0096-z
[4] - https://blog.acceleratelearning.com/digital-education-vs-traditional-education
Why Modern Graduate Students Are Nothing Like Their Parents' Generation: Learning - or not - in the Information Age
Volume 3: Learning - or not - in the Information Age
I’m glad you’re joining me again as we discuss the metacognition of the Information Age’s graduate students. Most importantly, we want to know how their learning differs from that of their instructors, who were likely educated before or in the earlier stages of the Information Age.
Last week, we discussed what was different about these new learners; this week, I’d like to examine the fallout of their differences. Some questions we’ll consider are:
What new learning styles have developed?
What are some learning disadvantages for students who have always had information at their fingertips?
How might we adapt our teaching styles to them?
New learning styles in the Information Age
Education delivery within graduate programs has undergone profound changes through digital evolution.
Consider that 85% of students report increased use of video chatting technologies—a statistic reflecting tool adoption and a fundamental shift in learning environments [1].
66% of students prefer digital textbooks to physical ones, while 67% choose digital assessments over traditional paper examinations [1].
Medical graduate students particularly gravitate toward microlearning—brief, focused educational segments lasting 5-15 minutes that match typical adult attention capabilities [1]. Preference for shortened learning sessions isn't merely coincidental but grounded in brain science: neuroimaging research confirms that focused attention naturally wanes after 10-15 minutes [1]. Microlearning thus represents a biologically appropriate educational approach rather than simply following a trend.
Research indicates 66% of students used AI tools during a recent semester to support their academic pursuits, with 20% accessing resources like ChatGPT ten times or more [2].
The Metacognition Gap for Information Age Learners
Artificial intelligence now serves as a cornerstone of modern educational approaches. These systems create personalized educational pathways tailored to individual learning patterns. However, they are also a source of considerable frustration to coaches (perhaps like myself) who want to convince students to read their textbooks rather than rely on AI answers for the questions that will likely be on their next exam. AI has notable drawbacks and makes numerous mistakes, and despite being impressive technology, it still cannot master the subtleties and nuances of human communication. I don’t know what the future holds, but at present, no AI can convey material or challenge students like a talented, experienced instructor.
Notably, AI doesn’t “teach” anything, no more than a textbook does. It is an information-delivery system; it is up to students to teach themselves the material by processing it. That task is a significant concern for students of the Information Age. If material is always as available as a good WiFi connection, when must they ever “learn how to learn?”
A modern student may not feel the pressure to memorize information—that’s one thing—but at some point, learning is more than memorization. Finding information online is great, except that it stops the process of knowledge fairly low on Bloom’s Taxonomy: AI delivers information; if a student reads it, they absorb knowledge, and if the student processes it, perhaps comprehension is achieved. Application, analysis, synthesis, and evaluation are interactive processes that must occur internally to form long-term memory and understanding.
In fairness, most students comprehend this already, or if not, they catch on fairly quickly. However, when students struggle and come to me for coaching, I find them needing to jump this hurdle ever more frequently. A constant source of information is not the equivalent of learning. The solution is not much different from a student twenty years ago who had trouble absorbing all the info from voluminous textbooks, except for one thing. Many AI-reliant students assume that AI is a superior solution because it is more advanced. Yet the proper solution remains the same as always: they must employ metacognition. They must learn how to learn.
Adapting classrooms and labs to the Information Age
Contemporary learners expect educational experiences aligned with their digital lives. These preferences extend beyond simple convenience; they prefer its adaptability, which allows students to engage with materials on their schedule and progress according to individual needs. Most of you readers have probably adopted changes into your teaching and coaching styles that incorporate our digital lives. Here are a few examples:
Classroom dynamics have evolved through collaborative digital tools. Platforms like “Top Hat” enable educators to embed live quizzes and discussions directly into lectures, offering immediate insight into student understanding [2]. The program “Hypothes” facilitates group annotation and allows readers to experience direct engagement with medical literature [2].
Digital shifts present challenges alongside their benefits. Research confirms that dividing attention across multiple digital platforms impairs concentration and working memory, ultimately affecting academic performance measures [3]. As is the case with those who work entirely online from home or comprise their social lives of digital interactions, the reduced face-to-face interactions in digital learning environments can foster feelings of disconnection.
Perhaps most importantly, we must convey to learners and instructors that they are approaching the material from different mindsets. With this understanding, we can better accommodate one another.
Conclusion
Finding equilibrium remains essential. Evidence suggests that blending digital technologies with traditional classroom elements offers more benefits than completely replacing one approach with another [4]. So, let’s take today’s blog as an example. I used AI as a tool to write it. I tasked it with finding articles about how the Information Age is changing medical teaching environments. It delivered four articles and a summary of each. Now, if I had simply “cut and pasted” what AI brought me, I wouldn’t have had a thoughtful interaction with the material, nor would I have considered the implications of the knowledge. So I believe that this has been a “blending” of AI tools with traditional writing elements. I’d be interested to know your thoughts, so post a comment if you wish!
As always, I hope you’ll join me next week. We’ll wrap up our discussion about teaching the students of the Information Age.
Here, by the way, are the articles that my AI bot fetched for me:
[2] - https://blogs.iu.edu/citl/2023/07/19/collaborative-learning-technologies-for-graduate-instructors/
[3] - https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-018-0096-z
[4] - https://blog.acceleratelearning.com/digital-education-vs-traditional-education
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