Month: December 2025

The Decline in Reading Activities – Does it matter?

Lately, I have encountered several essays that examine possible connections between the claims that “few people, including students, read books anymore” and “the declining percentage of individuals moving through our educational systems who are competent readers” (see links to several of these articles included at the end of this post). To attract a general audience, this decline in reading proficiency is often framed as a concern for future international economic competitiveness. What caught my attention in this unexpected batch of essays was the claim that researchers had failed to provide evidence that differences in time spent reading, and more specifically in reading lengthy works, resulted in improved reading skills and related intellectual benefits. In several of these articles, it was claimed that such relationships had not been proven. I had to move beyond these secondary sources to primary sources to understand the bases for these claims, and then to explore further on my own to determine whether I agreed. Is the lack of interest in books a serious problem?

The low rate of reading proficiency in the U.S.

Reading skills are declining and this trend has been ongoing for years. This decline is evident in multiple tests used to assess reading skills, with the most attention likely given to the NAEP (National Assessment of Educational Progress), which compares the performance of U.S. students with that of students from other nations. Implications for economic productivity and international competitiveness are sure to catch the attention of the general public and politicians. 

The pattern of decline among U.S. students is notable: over the years, the less proficient have declined year by year, whereas the most skilled have not shown this trend and score at roughly the same level on the tests used to track reading skill. Among other issues, this means that the range of competence educators must address within a single grade level is increasing, thereby complicating instruction. Multiple factors potentially associated with this trend have been identified and such claims have provided ideas for remediation. Most of you have likely heard of the “science of reading” controversy, which in recent years has prompted greater emphasis on phonics. Screen time is often cited as a culprit in many areas, including reading. Recently, absenteeism has risen at an alarming rate and it seems logical that missing school for many days means students miss instruction. There are likely multiple causes for a general academic trend and these causes interact in ways that defy simple solutions. 

Recent changes in reading proficiency broken down by initial level of functioning.

Reading Skill and Reading Activity

Daniel Willingham, an educational expert I often cite, proposes a more straightforward explanation in claiming that the “main differentiating factor” between strong and weak readers is “the volume of reading they do,” because that’s how they build both reading skills and a rich background knowledge. The mention here of background knowledge should not be overlooked and requires a little more detail. Studies that differentiate background knowledge from reading skill demonstrate that background knowledge is more critical in predicting differences in what readers understand from what they read. Put another way if good and poor readers are also differentiated by what they already know about a topic (e.g., good readers with poor existing knowledge, poor readers with good existing knowledge), the difference in background knowledge is the better predictor of understanding and retention. So, what Willingham argues is that the amount of reading has a unique importance, possibly ignored in other discussions of the development not just reading skill, but the more general impact of reading as a component of learning more generally. 

It is not that time spent reading and its relationship has been ignored (see Allington & McGill-Franzen). Attempts to track the amount of reading students and adults spend have been recorded with great diligence. How many minutes, how many books, whether the reading is on a digital device or paper, how many books are available in the home, how frequently does an individual visit a library, does a family subscribe to a newspaper, and similar variables have been quantified and related to reading skill and potential moderating variables such as family income. These variables consistently relate to measures of reading skill, and because these measures of activity seem to be in decline, have been argued as possible causes of poorer reading skills.

Causal Relationship Between Activity and Performance

Allington and his colleague raise an interesting point as have other scholars I have recently read about why the amount of reading has not received more attention. Allington makes an observation that blames reading researchers, which I find interesting. He claims that researchers have difficulty explaining the observed relationship between time spent reading and reading skill, because this relationship has seldom been tested experimentally. This position should be presented to mean that the observed relationships are correlational. How can it be known if more reading alone builds reading skill when the data could also be interpreted to argue that more capable readers enjoy reading and read more? Why might this matter? Allington notes that elementary school reading instruction focuses far more time on skill development than on extended reading. Extended reading, often called free reading, allows students to use school time to read independently and would include basal reader time and library books.

Just to be clear, there are many topics of interest to scientists in other fields that involve limited “manipulative” research. When investigating factors we believe have negative consequences, scholars seldom create the unfavorable circumstances to determine whether those harmful consequences follow. Sometimes, potential causal relationships are analyzed through correlational techniques because the causes cannot be manipulated or would be extremely expensive to manipulate. 

Allington does provide two counterexamples to the claim that the amount of reading, and in these examples, the reading of books, cannot be manipulated. The first example involves the gifting of books to randomly selected children through existing programs (e.g., the Dolly Parton Imagination Library) and the subsequent administration of follow-up assessments. The second employed a similar approach, focusing on the “summer slide” in reading performance among children from low-income families. Again, in selecting participants at random and comparing the selected group with non-selected individuals based on a gifted home library for the summer on a follow-up assessment. In both cases, greater access to books was associated with higher reading proficiency scores. The random assignment of access to the gifted books allows for a more persuasive argument for causality.

Voluntary vs Required, Intensive vs Extensive

The topic I have presented here has a number of subtopics that are relevant, but examining these issues should probably be pursued in other posts. The voluntary vs required distinction relates to reading set in a formal education setting or pursued without direction outside of the classroom. Voluntary reading at any age has consequences. The difference between intensive and extensive reading is relevant to a variety of issues that relate to reading for different purposes (research papers, technical manuals vs books) differ in potential benefits. When it comes to the amount read, does a number of shorter pieces generate the same impact as a book, or are there unique skills involved when persistence is required, and relevant pieces necessary for understanding are spaced over greater units of time?  This issue is relevant to the different type of reading most of us might do online.

Resources

Academic sources:

Allington, R. & McGill-Franzen, A. (2021). Reading volume and reading achievement: A review of recent research. Reading Research Quarterly, 56, S231-S238.

Abdurakhmonova, Z., & Pardayeva, R. (2025). Exploring intensive and extensive reading. International Conference on Culture & History. 1(3), 34-38.

Gioia, D. (2008). To read or not to read: A question of national consequence. Diane Publishing.

Willingham, D. T. (2017). The reading mind: A cognitive approach to understanding how the mind reads. John Wiley & Sons.

News sources addressing the decline in the popularity of reading books

Kids Rarely Read Whole Books Anymore 

Whole books or excerpts: Which does the most to promote reading ability –

Novels vs. excerpts: What to know about a big reading debate 

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What does the role of revision in classroom note-taking research offer PKM advocates? 

Most of what I write about PKM and Second Brain focuses on relating the vast body of high-quality research on academic note-taking to what many of us do outside the classroom as independent learners. The nonclassroom use of notes and related strategies for making and using notes has been termed Personal Knowledge Management (PKM) by those offering self-improvement advice. The PKM area is driven mainly by common sense. I cannot find focused research to inform this transition, but I have been investigating classroom note-taking and studying for decades and now focus on synthesizing findings from one area to support or evaluate strategies in the other. 

The classroom research primarily focuses on the interrelated tasks of taking and reviewing notes, and, more recently, on handwritten versus keyboarded notes. With PKM, there is a greater emphasis on continually revisiting stored notes. This topic has not been emphasized in the research with classroom notes, but some studies do exist and it is this more minimal area I want to explore in this post. Again, the advantage is in the research evaluating efficacy and what cognitive processing is enabled or encouraged in modifying original notes in various ways. 

I now primarily focus on note-taking on a digital device. While studies have focused on whether handwriting is superior for initial learning, approaches that encourage a deeper look at your notes reveal a powerful consensus that transcends the medium: there is unique value in notes that involve not just how notes are taken, but in how notes are revised.

This insight provides a critical link between academic research on learning and the practical strategies of Personal Knowledge Management (PKM). If your goal is to move beyond simply collecting information to actively building a knowledge base, you must embrace the often-overlooked middle stage of note-taking: revision and restructuring.

The Three-Stage Model: Beyond Capture and Review

Traditional study advice often reduces note-taking to two phases: recording during a lecture or reading and reviewing before an exam. However, classroom-oriented research by Luo et al. (2016) and Flanigan et al. (2023) suggests a more productive, three-stage process: recording, revision, and review. This intermediate revision stage is where the magic happens – where passive information capture transforms into active knowledge construction.

The research on this topic is compelling. A study by Cohen et al. (2013) demonstrated the causal role of a note-restructuring intervention in improving student learning. Students who were required to restructure and reorganize their notes, summarize the main point, and elaborate on a detail performed significantly better on exams. The researchers concluded that this process was essential for students to “make information one’s own, by processing it, restructuring it, and then presenting it in a form so that it can be understood by others (or by oneself at a later point).” 

Sounds very similar to the pitch for PKM strategies. Revision isn’t just about neatness or completion; it’s about deepening understanding through elaboration, incorporating entirely missed ideas, and creating retrieval cues that activate deeper memory networks.

From Note-Taking to Note-Making

In the world of PKM, a distinction is often made between note-taking (the act of recording external information) and note-making (the act of processing that information into a new, personalized, and connected knowledge item). The revision stage is precisely where you transition from a passive note-taker to an active note-maker.

PKM methodologies, such as the Zettelkasten, emphasize that a permanent note should be able to stand alone, expressed in your own words, and contain enough context to be meaningful without referring back to the original source. This is a direct parallel to the restructuring intervention that required students to summarize the main point and elaborate on a detail.

When you revise a note in an academic setting, you are performing the cognitive work that drives learning: elaboration (connecting new ideas to what you already know), organization (clarifying underlying structure and identifying themes), and synthesis (cross-referencing the new idea with other sources). Without this deliberate revision, you risk falling into a common trap: mistaking familiarity for understanding. Most learners fail to organize their notes after class because they recognize the content and mistakenly assume they have mastered it. Active processing, often based on concepts such as generative processing, is the focus of much research. 

The Longhand Advantage in Revision

The handwriting versus keyboard comparison recurs in studies of revision. Some, but not all, studies contradict my assumptions about the advantages of a digital approach.  Flanigan et al. found that longhand note-takers added three times as many complete ideas to their notes during revision compared to computer note-takers, and twice as many partial ideas. These researchers argue that handwriting engages deeper cognitive processing during initial recording, making those notes more effective retrieval cues when revisited later.

However, the digital environment isn’t without its strengths. Research by Cojean and Grand (2024) found that students who take notes on a computer are more likely to reformat their notes during revision. The ease of manipulating text digitally encourages a strategy where transcription is prioritized during capture, and the deeper work of reformulation and organization is deferred until the revision stage.

In a modern PKM system, this deferred processing is not a weakness, but a feature. Digital tools make it effortless to refactor (break long notes into smaller, single-idea notes), link (create hypertext connections between related ideas), and organize (file processed notes into multiple collections). The digital environment transforms revision from a tedious manual task into a fluid, creative act of knowledge gardening.

Making Revision Your PKM Habit

Those offering practical advice for students seem to recommend a structured approach to the revision stage. Treat it as a non-negotiable part of your workflow, not an optional step before an exam. Here are three practical revision strategies:

The “Foot” and “Socks” Method: Immediately after capturing a new note, summarize the main point in a concise “foot” (like a title or summary field) and elaborate on a key detail in the “socks” (the body of the note). This forces immediate processing and mirrors the Cohen et al. intervention.

The Atomic Note Refactor: If your initial note is a long transcription, dedicate time to breaking it down into smaller, single-idea notes. Write each new note in your own words and link it to at least one other existing note in your system. This practice creates the interconnected knowledge web that makes PKM powerful.

The Cross-Reference Check: When revising, actively search your existing notes and collections for related concepts. Link your notes back to original sources to resolve ambiguities and provide context. Make an effort to relate lecture content to what appears in your textbook. This is the moment to create connections that integrate new information into your existing knowledge structure, moving beyond simple storage to true knowledge management.

Schedule dedicated revision sessions, ideally spaced throughout your learning timeline rather than clustered after completion. Consider handwriting your first draft or deeply processing material before digital capture to maximize the depth of your initial notes. Make note revision an ongoing habit, integrated into your learning cycles rather than a single end-of-lesson task.

Conclusion

By making revision a deliberate and structured part of your note-taking, you stop merely collecting information and start actively building a powerful, interconnected knowledge base that supports long-term learning and creative work. The research is clear: revision elevates note-taking from passive transcription to active knowledge building. It transforms fragmented jottings into complete, interconnected ideas ready for recall and application.

For anyone committed to lifelong learning and effective Personal Knowledge Management, understanding and embedding the practice of careful, thoughtful revision into your workflows will create richer, more useful knowledge bases – helping you learn smarter, not just harder. Classroom studies encourage a structured approach and often control such activities through assignments. Independent learners must take personal responsibility to produce similar results. The missing link in your note-taking isn’t the tool you use or the speed at which you capture—it’s the intentional work of revision that transforms information into true personal knowledge.

References

Cohen, D., Kim, E., Tan, J., Winkelmes, M. (2013). A note-restructuring intervention increases students’ exam scores. College Teaching 61(3), 95-99.

Cojean, S., & Grand, M. (2024). Note-taking by university students on paper or a computer: Strategies during initial note-taking and revision. British Journal of Educational Psychology, 94(2), 557-570.

Flanigan, A. E., Kiewra, K. A., Lu, J., & Dzhuraev, D. (2023). Computer versus longhand note taking: Influence of revision. Instructional Science, 51(2), 251-284

Luo, L., Kiewra, K. A., & Samuelson, L. (2016). Revising lecture notes: how revision, pauses, and partners affect note-taking and achievement. Instructional Science, 44(1), 45-67.

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