Our Notes Leave too Much to Say: Investigating Note-Taking Practices

and Technological Tools in Academia

Yannic Jäckel

, Daniel Schiffner

and Jan Schneider

DIPF, Leibniz-Institut für Bildungsforschung und Bildungsinformation,

Rostocker Straße 6, 60323 Frankfurt am Main, Germany

Keywords:

Note-Taking, Academic Writing, Knowledge Management, Information Gathering, Critical Reading.

Abstract:

This paper explores the role of note-taking as a critical, yet under-researched, practice in academic scholarship,

focusing on how researchers organize, synthesize, and reuse their notes in the context of knowledge produc-

tion. While previous technological advancements such as large language models (LLMs) have transformed

aspects of academic writing, fundamental cognitive tasks—such as capturing and synthesizing information

through note-taking—remain relatively unchanged. Drawing from existing research, we highlight how poor

or ineffective note-taking practices in both students and early-career researchers can lead to inefﬁcient work

processes and diminished synthesis of knowledge. Our study involves a small-scale survey of academic re-

searchers to examine their note-taking techniques, tool usage, and strategies for synthesis. Our ﬁndings reveal

that many researchers employ unstructured methods, such as the Sentence and Outline Methods, and lack

formal training in effective note-taking. Furthermore, despite the availability of advanced digital tools, most

participants continue to rely on familiar word processors, often limiting the reusability and efﬁcacy of their

notes. We argue that structured methods and better tool utilization could signiﬁcantly enhance academic

writing and synthesis. The paper suggests that future research should focus on developing note-taking tools

tailored to researchers’ needs, enabling more effective synthesis and the reuse of notes. Such tools could po-

tentially integrate with LLMs to reduce the time spent on repetitive tasks and improve the quality of scientiﬁc

output. This shift could lead to a paradigm where notes evolve from simple memory aids to valuable data that

contributes directly to scientiﬁc advancement.

1 INTRODUCTION

Research and scientiﬁc advancement further the col-

lective understanding of phenomena in any given so-

ciety, writes Michel Foucault in his famous work "The

Order of Things" (Foucault, 2020). Karl Popper ar-

gues that what researchers do is make statements on

phenomena in the world(Popper, 2010). Thomas S.

Kuhn enters prior knowledge into the mix in argu-

ing that researchers need to ﬁrst acquire a Paradigm

through study and understanding of textbooks, before

being able to conduct science (Kuhn and Hacking,

2012). Methods, axioms and inﬂuential prior research

need to be known in any given ﬁeld, before one can

become a researcher oneself.

https://orcid.org/0000-0001-8065-5768

https://orcid.org/0000-0002-0794-0359

https://orcid.org/0000-0001-8578-6409

The abstract was written with support of ChatGPT 3 on

the basis of the Introduction, Discussion and Conclusion of

this paper.

If we consider the education of new scholars, re-

searchers and scientists, we see these arguments in

practise. Students learn from lectures, discussions,

presentations, seminars and a plethora of other for-

mats. They learn from the written and spoken word

of their peers and teachers. But the delivery of knowl-

edge is not the most crucial part of learning. In

following Bloom’s taxonomy of learning, we argue

that in order to create scientiﬁc advancement, a re-

searcher must ﬁrst remember, understand, apply, anal-

yse and evaluate knowledge, they acquired previously

through reading, discussion or other means (Krath-

wohl, 2002).

To facilitate these steps, we derive that synthesis

through notes, can be considered a major factor in

prior learning, much in alignment with Kuhn’s ob-

servations on how researchers acquire their Paradigm

(Kuhn and Hacking, 2012). Note-taking can act as

a second brain or "external storage" (Mosleh and

Baba, 2013; Pitura, 2023; Mueller and Oppenheimer,

2014), which facilitates recollection in its simplest

Jäckel, Y., Schiffner, D. and Schneider, J.

Our Notes Leave too Much to Say: Investigating Note-Taking Practices and Technological Tools in Academia.

DOI: 10.5220/0013218600003932

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 17th International Conference on Computer Supported Education (CSEDU 2025) - Volume 2, pages 493-503

ISBN: 978-989-758-746-7; ISSN: 2184-5026

493

form. Notes can be analysed and revised, a process

also known as synthesis (Qian et al., 2020).

As for application, note-taking, should be consid-

ered an exercise in academic writing, which we con-

sider in itself to be among the most fundamental skills

any researcher or scholar will use in their career in

academia. However, with more and more capable

LLMs, a focus on the mere mass-production of sci-

entiﬁc publications, as we see today, can certainly be

considered obsolete.

Following from these arguments, we say that

notes are the de facto bedrock of any scientiﬁc work.

Qian et al. consider them to be building blocks in a

sense making process (Qian et al., 2020), which in

itself is, as argued, fundamental to science.

However, from anecdotal evidence, we observed

that not many researchers seem to be trained in note-

taking. In this paper, we want to provide a baseline

and explore how researchers in academia take and

use their notes, with a speciﬁc focus on the employed

note-taking techniques and strategies.

1.1 Note-Taking as an Integral Part of

Research and Synthesis

The practise of note-taking itself is age-old and be-

gan, according to

Sl˛ezak-

Swiat, with annotations in

margins to better interpret a text. While the prac-

tise of these in-source annotations can be traced as

far back as 500CE (cf. (

Sl˛ezak

Swiat, 2022)), dig-

ital note-taking, according to Joanna Pitura’s recent

overview on the subject, started with the use of word-

processors and developed into speciﬁc note-taking

software like ’Evernote’ or ’RoamResearch’ (Pitura,

2023). Notes and marginalia can be found to be so en-

compassing that they can even serve as publications of

their own. One such example is Wittgenstein’s "Über

Gewißheit" (On Certainty), which he could not ﬁnish

before his death in 1951 (Wittgenstein, 2020). It was

nevertheless published and, despite its fractured ap-

pearance, it allows an interesting view into his thought

process and renders them as understandable as other

scientiﬁc publications. The same happened to J.R.R.

Tolkien’s work The Silmarillion, which was also pub-

lished unﬁnished after his death.

While the publication of notes, may – as in

Wittgenstein’s case – lack, a well-structured reading

experience, the practise of note-taking offers many

beneﬁts, even beyond scholarly ﬁelds, as note-taking

aids in decision-making and problem-solving. It also

improves (academic) writing and information reten-

tion (Deniozou et al., 2020; Pitura, 2023;

Sl˛ezak

Swiat, 2022). It does so mostly through the process

of encoding knowledge, i.e. writing down informa-

tion in your own words, often by hand (

Sl˛ezak

Swiat,

2022; Pitura, 2023; Mosleh and Baba, 2013; Mueller

and Oppenheimer, 2014)). Qian et al. argue that

note-taking, is a scholarly primitive. It forms the ba-

sis of synthesis, which itself is the basis of produc-

ing new knowledge and scientiﬁc advancement from

previous sources (Qian et al., 2020). Note-taking is

part of a (scientiﬁc) discourse (

Sl˛ezak

Swiat, 2022),

notes are purpose-driven if used for scientiﬁc writ-

ing, and should not be mere documentation (Fix and

Dittmann, 2008; Pitura, 2023). Effective note-taking

can speed up the process of scientiﬁc writing tremen-

dously. Fix and Dittmann argue that well-executed

notes, will allow for the construction of a text without

reading the corresponding primary sources again (Fix

and Dittmann, 2008), thus providing an ever-growing

collection of building blocks for further construction

of texts that pertain to the same discourse.

In practise, however, Qian et al. found that their

participants often had to return to their sources, cor-

recting misunderstood parts in their notes, or ﬁnd-

ing their notes inadequate (Qian et al., 2020), indi-

cating less well-executed notes. The fact that other

studies found students to be having trouble taking ef-

fective (especially digital) notes (Fix and Dittmann,

2008;

Sl˛ezak

Swiat, 2022; Mueller and Oppenheimer,

2014), indicates a greater, systemic issue.

In 2024, Kathleen Carroll provided an overview of

the state of research on the beneﬁts of note-taking and

what cognitive functions it applies in students (Car-

roll, 2024). Concerning digital note-taking, speciﬁ-

cally, Joanna Pitura published an overview in 2023.

It provides a comprehensive study on (digital) note-

taking and tool usage in students and early career re-

searchers. She analysed the beneﬁts and usage of spe-

ciﬁc tools and techniques in use by her target group

(Pitura, 2023).

Touching on a similar subject, Mueller and Op-

penheimer conducted a study in 2014, in which they

analysed whether students performed better at tak-

ing lecture notes using a laptop or long form writ-

ing (Mueller and Oppenheimer, 2014). They found

that students using a laptop were prone to transcrib-

ing part of the lecture verbatim, which lead to ineffec-

tive notes and poor recollection (Mueller and Oppen-

heimer, 2014). Mueller and Oppenheimer argue that

due to laptops allowing for more words to be writ-

ten in a given time span, they encourage ineffective

note-taking (Mueller and Oppenheimer, 2014). Ver-

bal interventions proved ineffective in mitigating the

behaviour (Mueller and Oppenheimer, 2014). How-

ever, we argue that a lack of training on on-the-spot

sythesis may also adequatly explain the lack of per-

formance, as opposed to the use of technology itself.

CSEDU 2025 - 17th International Conference on Computer Supported Education

494

Long form writing necessitates this synthesis due to

the constraints Mueller and Oppenheimer identify. If

students were properly trained beforehand to treat a

laptop the same way as they would pen and paper,

they may not have fallen for the temptation of mind-

lessly transcribing. Umberto Eco mentions a similar

effect in 1977, when he reminds his readers to not

simply photocopy texts and then consider them read

(Eco, 2015). Reliance on a photocopier alone, instead

of reading and synthesising, leads to poor understand-

ing of the subject and poor performance in writing.

While note-taking and its apparent beneﬁts are

well understood in the work of students, research con-

cerning note-taking as a scholarly practise in aca-

demic work is poorly examined and its inﬂuence

on synthesis and knowledge production is under-

researched (Qian et al., 2020; Carroll, 2024; Pitura,

2023; Deniozou et al., 2020), (Mosleh and Baba,

2013), (Pitura, 2023). Qian et al. performed in 2020

a small-scale qualitative study on ﬁrst-year PhD stu-

dents in their research group, where they researched

how their participants performed sense-making and

synthesis (Qian et al., 2020). In the process of this

study, some insights were gained on how the partic-

ipants used notes and digital tools to facilitate syn-

thesis. However, their conclusion was the same that

was hinted at earlier in the introduction. Their par-

ticipants repeatedly had to return to their sources to

correct their notes, rendering them ineffective (Qian

et al., 2020). They also identiﬁed a lack of tools and

proper training (Qian et al., 2020).

The research presented suggests that issues con-

cerning poorly executed notes present themselves

in students (Mueller and Oppenheimer, 2014) and

researchers alike (Qian et al., 2020), suggesting a

knock-on effect from poor or ineffective training.

1.2 Contribution

The contribution of this paper is to understand how

note-taking is done in academia and explore whether

the systematic issues observed with students are also

presented with our target group. To facilitate this,

we undertook a small-scale survey to achieve a base-

line understanding of the situation. We aim to un-

derstand how notes are used among our participants.

We also aim to identify how note-taking strategies

are employed and how structured the process of note-

taking is in our participant’s day-to-day work. We

also aim to corroborate our ﬁndings with ﬁndings

from previous research. In doing so, we aim to fur-

ther increase the understanding of systematic issues

that present themselves in the practise of note-taking

in researchers and scholars and, if issues present it-

self, offer ideas on how they could be solved in further

research.

2 SURVEY

To see, whether any of the aforementioned issues

were present or prevalent in Academic research, we

conducted a survey in note-taking techniques and

strategies.

The survey (see Appendix for the survey ques-

tions) was inspired by an overview on note-taking

methods and strategies by Mosleh and Baba, pub-

lished in 2013 (Mosleh and Baba, 2013). As they

implied that these techniques were widely used in

academia, we deemed them a good selection for our

survey. Furthermore, they were the only encom-

passing overview we found. The methods outlined

by Mosleh and Baba can also be found in multiple

educational web-portals, such as for example https:

//e-student.org.

The techniques and strategies, Mosleh and Baba

provide, range from less structured methods like the

Sentence Method, or Outline Method where note-

takers write their thoughts and other information as

unstructured sentences, or as indented sentences be-

low a topic respectively, to well-structured, tabular

methods like Two-Column-Reading or the Cornell

Method, where note-takers write down notes, cues

and reasoning in speciﬁc columns or partitions on a

page. (Mosleh and Baba, 2013).

In Two-Column Reading, note-takers split the

page into two columns. One of them contains the in-

formation taken from the currently read text, while

the other contains thoughts and reasoning on the note

taken ((Mosleh and Baba, 2013)).

The Cornell Method structures notes in three

columns, containing a cue word, the thoughts of a

note-taker when the cue was encountered and a sum-

mary of the page of notes, is also mentioned by Pitura

as an example for digital note-taking (Pitura, 2023).

Another well-structured method we selected was

not in Mosleh and Baba’s overview. In Four Column

Reading, note-takers split a page into four columns.

One contains a quote or paraphrase the note-taker has

encountered, the second column contains the number

of the page, where the quote or paraphrase was taken

from. The third column contains the reasoning of the

note-taker, as to why they selected the quote or para-

phrase and how it pertains to their research question.

A fourth column contains information on where the

speciﬁc information is to be used in an article or other

form of scientiﬁc text (Király et al., 2023).

Other structured methods also include the REAP-

Our Notes Leave too Much to Say: Investigating Note-Taking Practices and Technological Tools in Academia

495

method (Mosleh and Baba, 2013), where information

is read, encoded, annotated and pondered, i.e. notes

are taken (encoded), collated in any way (annotated)

and synthesised (pondered). Furthermore, mapping

methods, such as mind maps and charting methods,

where information is encoded into a table or a spread-

sheet (Mosleh and Baba, 2013) can be considered

structured as well.

The survey was designed with 20 mostly yes/no

or multiple choice questions (see Appendix). Only a

few questions allowed for open-ended ’other’ options.

The answers to the open-ended options were encoded

by hand for analysis. The language chosen for the

survey was English.

The survey was hosted on a LimeSurvey platform,

hosted by a German research institute. Participants

were invited using Messengers, Chatrooms, Social

Media and E-Mails. It was not recorded where par-

ticipants currently work. This was considered of lit-

tle interest, and would possibly have allowed for the

identiﬁcation of individuals. No personal data was

recorded, rendering the survey anonymous.

2.1 Findings

The target audience of our study was considered to be

active researchers in academia. The link to the survey

was distributed using emails and Social media chan-

nels. In total 33 participants completed the question-

naire.

To better understand where participants were in

their academic career, we asked their current position

(Q. 1). Three options were given: Predoc, i.e. PhD

candidates, graduate students and the like, Postdoc

and Professor. To better identify cohorts, these terms

will be used from this point on to refer to the respec-

tive groups outlined in 1

Table 1: Career stages of participants.

Career stage Number of participants in cohort

Predoc 20

Postdoc 9

Professor 4

Total 33

We hoped to get a better understanding of note-

taking techniques in speciﬁc ﬁelds, so we asked par-

ticipants in what academic ﬁeld they currently work

(Q. 3). The results were distributed with a long tail,

thus not usable for statistic evaluation, beyond ob-

serving what ﬁelds were present. The two biggest co-

horts were Computer Science (N=6) and Psychology

(N=9). However, the spread included a wide range of

academic ﬁelds such as Art History, History, Archival

studies, Linguistics and Education among others.

Since we also wanted to allow a wider, interna-

tional group to participate. Our participants were

mostly of German nationals, or persons having re-

ceived their academic education in Germany. Thus,

the question concerning where academic education

was received (Q. 2) did not yield any valuable in-

sights.

2.1.1 Reading and Note-Taking Strategies

The question most relevant to the goal of this paper

was what reading and note-taking strategies were em-

ployed by participants and gave the aforementioned

techniques as options. (Q. 11) Since we expected

multiple techniques to be employed by a single par-

ticipant, multiple answers were allowed. ’None of the

Above’ excluded all other answers. We found that

overall, none of the very structured methods were em-

ployed widely.

In Predocs (N=20), only three methods could be

considered popular. These were the Outline- (N=7),

Mapping- (N=5) and the Sentence Method (N=4).

Postdocs (N=9) used slightly more structured

methods in using Outline Method (N=2), Two-

Column Reading (N=2) and the Sentence Method

(N=3).

Among Professors (N=4) no real trend could

be observed, but Outline Method (N=2), Mapping

Method (N=2) and Sentence Method (N=2) were the

most prevalent.

Among all groups, ’None of the above’

Predocs

=8, N

Postdocs

=2, N

Prof essors

=1), was used

frequently as well. This indicates that a not insigniﬁ-

cant portion of our participants do not use, or do not

know of, the techniques we proposed as answers.

2.1.2 Digital vs. Print, Screen Inferiority

Since previous research indicated a strong screen in-

feriority effect for academic reading and note-taking

(

Sl˛ezak

Swiat, 2022), we decided to include questions

on reading habits. When asked about whether par-

ticipants predominantly read their sources in print or

on screen (Q. 5), most participants, through all co-

horts, stated that they read their academic texts ei-

ther on screen (N

Predocs

=8, N

Postdocs

=3, N

Prof essors

=2)

or both on screen and paper, or they could not

say (N

Predocs

=6, N

Postdocs

=4, N

Prof essors

=2). Only

a minority stated to read on print-outs (N

Predocs

=6,

Postdocs

=6, N

Prof essors

=0).

Furthermore, we asked whether participants pre-

ferred handwritten notes or used word-processors or

wrote notes directly in text (annotations) or used ded-

icated note-taking software. (Q. 6). The use of word

CSEDU 2025 - 17th International Conference on Computer Supported Education

496

processors and handwritten (long form) notes is most

prevalent, as can be seen in table 2.

Table 2: Distribution of note-taking habits.

Predoc Postdoc Professor

Handwritten

notes

13 6 3

Word proces-

sor

13 5 2

Annotations 5 4 1

Dedicated

Software

1 2 1

As a follow-up question, we asked participants

whether they preferred handwritten notes on paper, or

took them using digital means (Q. 7). Almost all par-

ticipants, through all cohorts, stated they made hand-

written notes on paper. Even those who made hand-

written notes digitally, also made paper notes (3).

Table 3: Distribution of handwritten notes on paper vs. on

screen (Multiple Answers allowed).

Predoc Postdoc Professor

Handwritten

notes on

paper

12 5 2

Handwritten

notes on

screen

7 2 2

Both 6 1 2

Total 13 6 3

We also asked whether annotations (notes directly

in the source material) were used and whether they

were taken on paper or digitally (Q. 9). The results

can be seen in table 4

Table 4: Distribution of annotations on paper vs. on screen.

Predoc Postdoc Professor

Annotations

on paper

3 2 1

Annotations

on screen

4 3 1

Both 1 1 1

Total 5 4 1

2.1.3 Tool Usage

Among our participants, dedicated note-taking soft-

ware was only widely used in the professor (N=2)

cohort. Among Predocs (N=1), and Postdocs(N=2),

dedicated note-taking software was not widely used.

(See table 2).

The software in use was Evernote (N=2), Obsidian

(N=2), Roam Research/LogSeq (N=2) and Google

Keep (N=1).

Overall, the most widely used tool were word pro-

cessors. Among them, Microsoft Word (N=13) was

the most commonly used, with the Google Suite be-

ing a distant second (N=3).

2.1.4 Quality of Notes

To assess the quality of notes that our participants

took, the question was posed whether participants did

publish their notes (Q. 16). The reasoning behind

this question was that if participants published their

notes, we could assume that they had faith in their

notes and would hold them to a high quality standard.

Furthermore, we assumed that researchers who pub-

lished their notes considered them as research data to

be reused and shared. The vast majority (N=29) did

not publish their notes, with only a very small number

(N=4) publishing them. (see table 5)

Table 5: Question: Do you publish your notes?

Predoc Postdoc Professor

Yes 3 1 0

No 17 8 4

To further assess the perception of the quality of

the notes participants took, we asked for reasons why

the participants choose not to publish their notes (Q.

18). Since multiple of the offered reasons might ap-

ply, multiple answers were allowed. As seen in table

6, most participants considered their notes to be pri-

vate. However, quite a large number of participants

(N=13) voiced concerns that their notes may (also)

contain errors. Only a small minority stated that their

notes were useless due to being idiosyncratic (N=4).

Interestingly, a small number of participants stated

that they did not publish their notes because they may

contain cues for further research by others.

Table 6: Reasons why notes would not be published.

Predoc Postdoc Professor

My notes are

private

13 6 3

My notes may

contain errors

7 3 3

They may

contain cues

for further

research

3 1 1

They would not

make sense to

others

2 2 0

Our Notes Leave too Much to Say: Investigating Note-Taking Practices and Technological Tools in Academia

497

2.1.5 Note Usage

Since reasoning and other meta-information may be

encoded with different schemas, we also asked if

note-takers wrote their own reasoning, reading strat-

egy and mental disposition (Qs. 12–14). Király et

al. argue that they all can inﬂuence the note-takers

perception and argumentation during critical reading

(Király et al., 2023).

We also wanted to evaluate how our participants

used their notes in their writing process (Q. 19). Since

notes can be used as building blocks to scientiﬁc texts

or as memory aids, we posed whether our participants

used them as such. We also asked if participants in-

cluded their own reasoning in their notes. Since not

many participants employed structured note-taking

techniques that included reasoning by default (N=2),

this question is of particular interest.

The majority of participants (N=23), through all

cohorts, claimed to include their own reasoning in

their notes, with only a minority not including their

reasoning in their notes (N

Predocs

=7, N

Postdocs

=1).

Among these participants, only the Mapping

Method (N=1) was used as an example of a structured

note-taking method. The remaining distribution of

techniques used by participants who, do not include

their reasoning, can be seen in table 7. None of the

methods compel the note-taker to include reasoning.

Table 7: Note-taking methods employed by participants not

including their own reasoning.

Predoc Postdoc

Outline Method 1 1

Mapping Method 1 0

Sentence Method 3 1

None of the above 3 0

Furthermore, participants were asked if they used

their notes as memory aids or text snippets. Since

both usages may coexist, multiple answers were al-

lowed. The category ’both’ is calculated from the an-

swers, to allow for better analysis. An open-ended

option was given, but no comment was provided by

most participants who choose it. These answers were

ignored as invalid (N

Predocs

=1, N

Postdocs

=1). One an-

swer was given as ’I use my notes as outlines’, which

we encoded as ’text snippet’ (See table 8).

The Predocs were the only cohort to show a wide-

spread usage of notes as text snippets or both snippet

and memory aid (N=14). Postdocs, used their notes

mainly as memory aids (N=6). Among professors,

usage as a memory aid was dominant (N=2).

Table 8: Note usage.

Predoc Postdoc Professor

Cohort size 20 9 4

Use as snippets

(only)

4 0 1

Use as memory

aid (only)

6 6 1

Both 10 2 1

Other (invalid) 1 1 0

2.1.6 Training

We wanted to explore whether participants have re-

ceived training in note-taking (Q. 15). The results

show that, through all cohorts, most participants

stated that they either received no training or were

self-taught (N

Predocs

=18, N

Postdocs

=7, N

Prof essors

=4),

which could be considered the same in the context

of this question. Only the minority of participants

stated to have received training in school or univer-

sity (N

Predocs

=7, N

Postdocs

=6, N

Prof essors

=0). For a de-

tailed overview, see table 9.

Table 9: Note-taking training received.

Predoc Postdoc Professor

Cohort size 20 9 4

School 3 3 0

University 4 3 0

Self-taught 6 5 1

I did not

receive any

training

12 2 3

2.2 Discussion of Findings

Among our participants, none of the structured meth-

ods that Mosleh and Baba claimed to be widely used

(Mosleh and Baba, 2013) were found to be preva-

lent. Our participants tended to prefer unstructured

methods, that encoded information without (Sentence

Method) or with simple, hierarchical structures (Out-

line Method). While Mapping Methods, such as mind

maps, were the most structured method used in our

participants.

Furthermore, we observed that only a minority of

participants (N=10 out of 33) annotated their sources,

indicating a single step reading process, which is fur-

ther correlated by the absence of the REAP-Method.

More critically, our ﬁndings show a lack of formal

training, aligned with a conclusion of Fix and Dittman

made in 2008 (Fix and Dittmann, 2008). Similarly,

Sl˛ezak-

Swiat’s research in 2022 suggested that her

participants, Polish E2L students, had little knowl-

CSEDU 2025 - 17th International Conference on Computer Supported Education

498

edge about structured note-taking techniques and no

formal training. Thus, they relied on their intuition

(

Sl˛ezak

Swiat, 2022). The studies done by Qian et

al. and Mueller and Oppenheimer further support this

notion (Qian et al., 2020; Mueller and Oppenheimer,

2014). As outlined above, the ﬁndings of Mueller and

Oppenheimer can well be explained by a lack of train-

ing, rather than by the use of technology.

This correlates well with our ﬁndings, since the

Sentence- and Outline Methods can be considered in-

tuitive, as they do not rely on any structure that would

necessitate training and knowledge. Thus, based on

our results, we consider that more training is needed

to get more structured and reusable notes.

Taking into account that Fix and Dittmann ob-

served a lack of training as early as 2008 (Fix and

Dittmann, 2008), the deﬁcit we perceive has persisted

for quite some time. Any lack of training and knowl-

edge we observe today, we consider to be knock-on

effects of prior insufﬁcient training, since the students

of 2008 may well be teachers today.

Since a larger number of our participants con-

sider themselves self-taught (N=12), we could assume

that they read training resources themselves. There

are more recent training resources like, for instance,

Király et al.’s ’Jump-Start Your Writing’ (Király et al.,

2023), or even older manuals like Umberto Eco’s

’How to write a thesis’, originally published in 1977

and translated into English in 2015 (Eco, 2015) that

show usages of more structured techniques. Király et

al. propose four-column-reading (Király et al., 2023),

while Eco, being an older resource, does not include

computerised methods. He proposes the use of index

cards and ﬁles in ﬁling cabinets (Eco, 2015), a tech-

nique that is still employed by some researchers today

(McCarty, 2023). This list is by no means exhaustive.

However, since we observed a near absence of

structured methods present in teaching materials, we

can assume that our participants, while considering

themselves self-taught, did not consult the these ma-

terials, or did not feel the need to do so. This raises

the question if the notion of self-teaching rather more

refers to ’make it up as you go’, than actual course-

work.

While structured methods for note-taking are not

part of the daily work of our participants, we found

that a sense of efﬁcacy in note-taking was well rep-

resented. Our ﬁndings suggest that the new gener-

ation of researchers, represented by our Predocs co-

hort, use their notes as text snippets to a signiﬁcant

degree, whereas in our Postdocs cohort they were still

mainly used as memory aids.

The use of notes as parts of a new text is one of the

key concepts of Four-Column-Reading, and we argue

that it shows a concern of efﬁcacy and reusability in

note-taking. It also indicates that a degree of synthesis

that must have been taken place, if notes were consid-

ered to be incorporated into a publication. This is fur-

ther corroborated by the fact that the vast majority of

our participants included their own reasoning in their

notes. While the lack of training may still present is-

sues, we argue that it could be offset by the use of

tools that are speciﬁcally designed to reevaluate, syn-

thesise and manage notes in ways described by, for

example, Pitura, Eco, or McCarty (Pitura, 2023; Eco,

2015; McCarty, 2023). We also argue that the neces-

sary structure for reuse may also be introduced by the

use of speciﬁc tools.

Tool usage in note-taking, however, also shows

signs of knock-on effects that can be traced to a

lack of formal training in students and teachers alike.

While there is a plethora of dedicated note-taking

tools (RoamResearch, Evernote, LogSeq, Obsidian,

Google Keep, Notion.io, Zettelkasten

to name a

few), their use did not present itself in our ﬁndings.

We assume our participants used the tools they are

familiar with, which are mainly word-processors in

the form of Microsoft Word. Its use is usually taught

in schools, and it is omnipresent. This aligns well

with ﬁndings from Qian et al., who also observed that

their participants did not use dedicated note-taking

tools. Their participants often showed a ’make-do’

attitude in adapting known tools to a use they were

never designed for and which thus offered sub-par

performance on the task at hand. One participant

went as far as using a built-in sticky-note tool in their

computer’s operating system to take their notes (Qian

et al., 2020). While their participants clearly sought

and found creative ways to employ their known tools,

Qian et al. found it to be a source of friction, with

researchers switching between up to four (adapted)

tools to perform their daily work (Qian et al., 2020),

hampering their abilities.

Pitura, McCarty, Király et al. and Eco present in

their works methods that could reasonably be com-

puterized and in the case of ’Zettelkasten’ are even

available as ﬁnished product. But knowledge of these

tools did not present itself in our ﬁndings. To establish

speciﬁc reasons, further research would be required,

though we assume from anecdotal evidence that tools

might simply be unknown.

Another indicator that correlates well with a lack

of formal training is what we perceive as the employ-

ment of a single pass reading strategy. We deduce this

from the lack of annotations our participants make in

their sources. This aligns well with research done by

Sl˛ezak-

Swiat in 2022, where she found that while her

http://zettelkasten.danielluedecke.de/

Our Notes Leave too Much to Say: Investigating Note-Taking Practices and Technological Tools in Academia

499

participants still read on paper, they did not annotate

their printouts (

Sl˛ezak

Swiat, 2022). While

Sl˛ezak-

Swiat interpreted this as a strong screen inferiority ef-

fect in reading (

Sl˛ezak

Swiat, 2022), we argue that it

may also be a symptom of a lack of formal training.

Resources like Király et al. teach a multistep read-

ing process while taking notes (Király et al., 2023),

whereas Eco advises to underline and annotate im-

portant parts on a photocopy(Eco, 2015). The lack of

such annotations in a source may indicate a single-

step reading process, which would align well with

the observation that participants use intuitive meth-

ods. However, to ascertain this, more research would

be required.

To establish a measure on how our participants

perceived their own notes, we asked if they published

their notes. Our participants generally answered they

did not. They mostly considered their notes pri-

vate or containing errors as a reason for not pub-

lishing. Previous research suggested that note-takers

mainly perceived their notes to be unintelligible to

others (Mosleh and Baba, 2013; Fix and Dittmann,

2008). Our ﬁndings differ concerning on this percep-

tion. While unintelligibility may be a reason for keep-

ing notes private, ’being wrong’ seemed to be a big-

ger concern to our participants compared to previous

studies.

As a caveat, it has to be stated that our sur-

vey’s participants consisted of a rather small group

of mostly German academics. As stated above, our

sample consists of a wide range of research ﬁelds, all

of whom showed similar answers. As such, the con-

text of the education did not seem to matter, and the

issues highlighted in this paper persist in a variety of

circumstances and ﬁelds. We furthermore found that

the issues were already persistent in 2008 in German

schools (Fix and Dittmann, 2008). And judging by

the examined research, we do not expect other coun-

tries to be different. The knock-on effects described

can be expected to manifest themselves in different

countries and similar circumstances as well.

3 CONCLUSION

In general, our ﬁndings suggest that our participants

do not use their notes to their full potential, even

though small changes in behaviour could be observed

to what was concluded in previous research. We ar-

gue that the main issue is a lack of teaching and train-

ing on how to take reusable and structured notes, and

a lack of knowledge on tools that would help in this

task. If available tools were simply inadequate, could

not be ascertained.

While we argue that training and knowledge can-

not be replaced by technology, we ﬁnd that a dedi-

cated tool may help researchers in obtaining better

structured notes that can make synthesis easier and

more reliable.

The tool we envision, would need to be akin to

a ’Virtual Research Environment (VRE)’ or a Dash-

board, which would allow researchers and scholars

more efﬁcient and effective ways to remember, un-

derstand, analyse, and evaluate their notes and pos-

sibly publish them as research data alongside their

publication, allowing for other researchers to inte-

grate them in their work. We argue that with a VRE

speciﬁcally designed to work through the act of note-

taking, we could employ Natural Language Process-

ing and other computerized methods, to make annota-

tions in new transcripts, notes or machine-actionable

texts that would allow researchers to see emerging

patterns in notes and sources alike. The ability to

annotate a researcher’s own notes, as if they were a

qualitative dataset, could also enhance further analy-

sis.

While this additional step may require a change in

habit, we argue that it will make notes more power-

ful and enhance the work of researchers, while they

mostly keep working in the way they are accustomed

to, using Outline- and Sentence Methods or mind

maps. Mind maps in turn can help researchers or-

ganize their thoughts, generate ideas, and develop

concepts, which enhances their analytical and under-

standing skills (Shi et al., 2023). Similarly, ’visual

programming’ could be employed to use the visual

aspect of mind maps to visualise steps in an analysis

with different algorithms connecting to one another.

At the time of writing, we are not aware of any tool

that would implement the functionalities we envision.

An encompassing VRE could also solve another

problem in data reuse. Because, even if notes are

taken using structured methods, they are currently

neither published nor reused. We assume that in writ-

ing, analysing and learning, researchers seldomly use

all the notes they made, rather they use a portion that

pertains to a speciﬁc topic or question. With the cur-

rent tools in use, we expect the rest to fall by the way-

side, lost in some word-document somewhere never

to be seen. With dedicated tools, these unused notes

can be exported, shared or be reused and synthesised

in another context. In this sense, note-taking sup-

ports learning and thus also research, through a con-

structivist approach to learning. This approach al-

lows note-takers to use their notes in different scenar-

ios and contexts, allowing for new connections and

a broader understanding (Friedman, 2014). Further-

more, since notes created within an encompassing

CSEDU 2025 - 17th International Conference on Computer Supported Education

500

VRE share a common mode of production, we argue

that these notes are as scientiﬁcally valuable as any

qualitative, incidental data.

Following this, notes themselves may even form a

new basis for publication.

Sl˛ezak-

Swiat argues that

notes, as a stand-alone publication, act as an indi-

cator to what texts a researcher may have read and

which information they did not deem necessary to

their process. Notes can thus act as an indicator of a

researcher’s attention and focus (

Sl˛ezak

Swiat, 2022).

While this aligns with our previous arguments, it can

directly be conﬁrmed by reading "Über Gewißheit",

where Wittgenstein’s notes allow the reader a glimpse

into his thought process while examining a philosoph-

ical article, argument by argument. Also, a collection

of notes from different researchers might indicate the

attention and focus of an entire ﬁeld, show a structural

bias or blind spots or illuminate a hitherto unknown

paradigm in the sense of Thomas S. Kuhn (Kuhn and

Hacking, 2012), or expose the episteme (Foucault,

2020) or ’Weltbild’ (Wittgenstein, 2020) of a group

of researchers.

As such, evaluation of available tools is still ongo-

ing and the reuse of notes and the perception of notes

as a form of research data is something that needs to

be studied more in-depth.

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APPENDIX

Survey Questions

Q1: At what stage in your academic career are

you currently?

Answer options (Single Choice):

• Student

• PreDoc (PhD candidate, Post-grad-student)

• PostDoc

• Professor

• I don’t/no longer work in academia

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501

Q2: In what country did you receive your

academic education?

Answer options (Free text ﬁeld)

Q3: What’s the scientiﬁc discipline you currently

work in? Or, if you don’t / no longer work in

academia, what’s the ﬁeld you last worked in or

studied.

Answer options (Free text ﬁeld)

Q4: Do you take notes?

Answer options (Single Choice)

• Yes

• No

Q5: Do you prefer to read material printed on

paper, or do you primarily read on a screen?

Answer options (Single Choice)

• Print

• Screen

• Both/Can’t really say

Q6: How do you take your notes?

Answer options (Multiple Choice)

• Handwritten

• Word Processor / text editor

• Notes directly in text

• Dedicated note taking software

• Other (i.e. Sketch notes, Mindmaps, Doodles etc.)

(Free text ﬁeld)

Q7: Do you take your handwritten notes on paper

or do you take them digitally?

Answer options (Multiple Choice)

• On Paper

• Digitally

Q8:Which word processor or editor do you use?

Answer options (Multiple Choice)

• Microsoft Word

• LibreOfﬁce / OpenOfﬁce

• SublimeText

• Visual Studio Code

• Apple Pages

• Other (Free text ﬁeld)

Q9: You write your notes directly into the text

you’re reading. Do you do so on paper or

digitally?

Answer options (Multiple Choice)

• On Paper

• Digitally

Q10: What dedicated note-taking software do you

use

Answer options (Free text ﬁeld)

Q11: During note-taking, do you employ one or

more of these techniques or strategies?

Answer options (Multiple Choice)

• Four Column Reading (Quote or Paraphrase, Page

No., Comment or Reasoning, Where to use)

• Two Column (Notes and Notes-on-notes)

• Cornell Method (Three columns: Cue, Notes and

Page-summary)

• REAP Method (Read, Encode, Annotate, Ponder)

• Outline Method (Indented bullet points, grouped

by overarching subjects)

• Mapping Method (i.e. Mind Maps)

• Charting Method (Tabular notes)

• Sentence Method (Unstructured notes in full sen-

tences)

• None of the above

Q12: Do you record your chosen reading strategy

in your notes?

Hint given: Reading strategies are for instance: Skim-

ming, Close Reading, Critical Reading and the like.

Answer options (Single Choice)

• Yes

• No

Q13: Do you record your current state of mind in

your notes?

Answer options (Single Choice)

• Yes

• No

This option excluded all other answers.

CSEDU 2025 - 17th International Conference on Computer Supported Education

502

Q14: Do you include your own reasoning in your

notes?

Answer options (Single Choice)

• Yes

• No

Q15: Where did you learn to take notes?

Answer options (Multiple Choice)

• School

• University

• Self-taught

• I did not receive any training

• Other (Free text ﬁeld)

Q16: Do you publish your notes? Or,

hypothetically, if you took notes, would you

publish them?

Answer options (Single Choice)

• Yes

• No

Q17: How do you publish your notes?

Answer options (Multiple Choice)

• As research data in a repository

• As bundle with the publication

• On Github

• Other (Free text ﬁeld)

Q18: Why do you choose to not publish your

notes?

Answer options (Multiple Choice)

• My notes are private

• They may contain errors

• They may contain cues for further research

• Other (Free text ﬁeld)

Q19: When you write, how do you use your notes?

Answer options (Multiple Choice)

• As text snippets

• As a memory aid

• They may contain cues for further research

• Not at all

• Other (Free text ﬁeld)

This option excluded all other answers.

Q20: Given, you would use any software in

note-taking. Would you prefer a cloud-based

solution or would you prefer to store the notes on

your local machine?

Answer options (Multiple Choice)

• Cloud Service (OneDrive, Apple Cloud, Google

Drive or similar third party service)

• Owned Cloud (A cloud service you or your em-

ployer control, i.e. NextCloud, OwnCloud or sim-

ilar)

• Local Network storage (i.e. Your own NAS,

Shared drive at work)

• Local Device

• I don’t use software

This option excluded all other answers.

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503