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# Writers Gonna Wait: The Effectiveness of Notifications to Initiate Aversive
Action in Writing Procrastination

Chatchai Wangwiwattana

Sunjoli Aggarwal

Eric C. Larson

Southern Methodist University, Department of Computer Science
<EMAIL_ADDRESS>Southern Methodist University, Department of Computer
Science<EMAIL_ADDRESS>Southern Methodist University, Department of
Computer Science<EMAIL_ADDRESS>
###### Abstract

This paper evaluates the use of notifications to reduce aversive-task-
procrastination by helping initiate action. Specifically, we focus on aversion
to graded writing tasks. We evaluate software designs commonly used by
behavior change applications, such as goal setting and action support systems.
We conduct a two-phase control trial experiment with 21 college students
tasked to write two 3000-word writing assignments (14 students fully completed
the experiment). Participants use a customized text editor designed to
continuously collect writing behavior. The results from the study reveal that
notifications have minimal effect in encouraging users to get started. They
can also increase negative effects on participants. Other techniques, such as
eliminating distraction and showing simple writing statistics, yield higher
satisfaction among participants as they complete the writing task.
Furthermore, the incorporation of text mining decreases aversion to the task
and helps participants overcome writer’s block. Finally, we discuss lessons
learned from our evaluation that help quantify the difficulty of behavior
change for writing procrastination, with emphasis on goals for the HCI
community.

###### category:

H.5.m. Information Interfaces and Presentation (e.g. HCI) Miscellaneous

###### keywords:

Procrastination, Behavior Change, Writing

##  1 Introduction

For decades, the HCI community has researched persuasive design in behavior
change in applications ranging from health improvement [34, 38, 42], to well-
being [36, 49], to sustainability [37, 39]. These researchers seek to bridge
the gaps between practical HCI design and behavioral psychology—or,
alternatively, behavioral economics or neuroscience; nonetheless, this gap has
proven difficult to trellis [64]. Because of the generalized nature of
behavioral theory, there are many possible ways to apply the same knowledge in
practical applications [64]. That is, a technique that works well within one
context may not work in another.

One widely used mechanism in behavior change is the notification. The
notification is used to draw users’ attention to a task or part of a task with
the hope that action will be initiated. In theory, a psychological trigger,
whether internal or external, is the first step of any behavior [63].
Notifications, therefore, can be categorized as effective external cues to
initiate behavior [14]. However, many studies investigate the use of
notifications for tasks that users already have an internal motivation to
complete; tasks for which internal motivation is absent have not been studied
as thoroughly. Such tasks are also known as “aversive tasks.” High intention
to perform aversive tasks does not guarantee that the behavior will occur [7].
Thus, it is an open question to what degree notifications are effective
psychological triggers for completing a task. In this paper, we evaluate the
usage of notifications for changing behavior towards aversive tasks, in which
there is no internal motivation present. More specifically, we focus on
reducing writing procrastination among college students.

We outline our contributions as follows: (i) We investigate the role of human
computer interaction in formal psychological theories of procrastination
behavior. (ii) We evaluate the efficacy of various notification styles in
reducing procrastination of tedious writing tasks. (iii) We evaluate popular
text editor designs and their perceived effects on procrastination behavior.
(iv) We summarize lessons learned from working on procrastination research
from an HCI perspective.

Writing is considered an unpleasant activity by many individuals because it
requires tremendous effort, is susceptible to judgment, and has delayed
reward; nonetheless it is vital to succeeding in many professions and,
therefore, cannot be treated as an optional lifestyle choice. The conflict of
have to and want to, which psychologists call cognitive dissonance, elicits
negative effects such as guilt and distress [16]. These negative effects enter
into a positive feedback loop—the more a student procrastinates, the worse
he/she feels, and these negative feelings block him/her from having an
environment conducive to writing, leading to further procrastination [24]. Due
to its cyclic nature, writing procrastination is an extremely challenging
application of aversive behavior change research, but as stated, trying to
reduce this phenomenon is also extremely relevant.

In this paper, we evaluate the effectiveness of notifications and other
persuasive HCI design elements on reducing procrastination and initiating
action for writing tasks. We developed a research instrument for collecting
data and facilitating the experiment (i.e., a custom text editor that tracks
interaction and can distribute self-evaluation surveys). The custom text
editor has a number of features, including a notification system, a goal
progress bar, distraction-free mode, and a writing assistance system. All of
these features are designed based on psychological intervention theory. We
conducted an experiment with 21 college students who used the editor to
complete graded writing assignments. The evaluation lasted for eighteen days.
Students worked on two separate writing assignments: the first assignment
lasted for nine days without notifications and was used as a baseline
evaluation. In a second nine day experiment, we divided the same users into
two groups based on the type of notifications they received (normal or
actioned notifications). We recorded users’ progress using word count, writing
time, and start time, and recorded users’ interaction with notifications for
both assignments. We also collected self-reported survey data on
procrastination with PASS (Procrastination Assessment Scale), and user
satisfaction with SUS (System Usability Scale). In the follow-up study, 14
participants used the editor regularly enough for analysis. The results showed
minimal change in writing procrastination behavior regardless of the type or
number of notifications received. Surprisingly, participants who received more
notifications reported lower satisfaction than others who received fewer
notifications. In addition, we found our custom writing assistance system,
which employs text mining and concept models to help mitigate writer’s block,
reduced aversion towards the task and provided a more positive writing
experience. Other persuasive techniques, such as a simple goal progress bar
and distraction-free mode, also showed positive outcomes.

##  2 Understanding Procrastination

In order to bring the HCI community together around behavior change for
procrastination, we first describe the psychology community perspectives
(which are competing in some instances). This also helps to properly ground
our HCI methodologies in the context of current psychological research trends.

A valid question to ask before going further is: Should we be trying to reduce
procrastination behavior? In general, social psychologists argue that
procrastination is an irrational and maladaptive behavior [19]. There is
considerable evidence that procrastination not only harms productivity, but
also increases stress and contributes to a poorer quality of life. Studies
show that procrastination can affect people’s health, ranging from headaches,
body aches, and colds to tooth decay, stress, and strokes [58, 59, 60].
Moreover, in academic literature, studies have shown that academic
procrastinators are likely to engage in cheating and plagiarism, as well as
have problems with self-esteem and self-confidence [19]. Procrastinators also
have a high degree of self-handicapping behaviors, such as indecision,
rebelliousness, societal demands for perfection, and a low degree of optimism,
self-esteem, life satisfaction, and self-confidence [25]. In contrast to these
negative effects, some research suggests that procrastination exists for good
reasons. From an evolutionary perspective, procrastination yields benefit
because the long term goals that a non-procrastinator would focus on may
actually distract from short term survival goals that a procrastinator would
gravitate towards [29]. Norman argues that procrastination provides the
maximum time to think, plan, and determine alternatives, giving more
flexibility for change in the future and allowing requirement to evolve [45].
In this paper, we do not argue whether procrastination is or is not
beneficial. Instead, we argue that individuals who wish to change their
behavior should have a right to do so. Our research, thus, provides valuable
knowledge for individuals who wish to reduce their procrastination behavior
using technology aides.

Procrastination can be viewed from various perspectives. Cognitive Science
views procrastination as a subtle executive dysfunction [50]. Executive
functions rely on a number of interconnected cortical and sub-cortical brain
regions. Together, these areas are responsible for the self-regulation of
cognition and for all cognitive processes that enable planning for complex
actions [50]. In contrast to Cognitive Scientists, Evolutionary Psychologists
view procrastination as a result of human evolution. They believe that
focusing on short term survival results in a greater chance of passing on a
gene, whereas long term planning is merely a distraction. According to them,
procrastination is an evolutionary by-product of impulsiveness [29]. Social
Psychologists have a similar view to Cognitive Scientists. Piers Steel defined
procrastination as “to voluntarily delay an intended course of action despite
expecting to be worse off for the delay” [61]. To emphasize its negative
nature, Kyle further defines procrastination as “the voluntary, irrational
postponement of an intended course of action despite the knowledge that this
delay will come at a cost to or have negative affects on the individual” [35].
In short, many psychologists agree that procrastination is a form of self-
regulation failure. It is important to note that not all delays are
categorized as procrastination. For example, a planned delay or a delay from
external factors is not procrastination; procrastination must include an
irrational delay. With this definition, Norman’s argument—to maximize time to
think, plan, and determine alternatives, give more flexibility in future
change, and allow requirements to change[45])—would not be considered
procrastination; it is time management.

###  2.1 Characteristics of Procrastinators

Individuals who procrastinate often repeat procrastination behavior;
therefore, the psychology community categorizes people as procrastinators and
non-procrastinators. Procrastinators have unique characteristics compared to
non-procrastinators. For example, many procrastinators have a misbelief that
pressure motivates them to do their best work [35]; furthermore,
procrastinators have high sensitivity to immediate gratification and have
trouble focusing on tasks [17, 18, 26]. Procrastinators also typically have
low self-control and low self-reinforcement, meaning they are unable to reward
themselves for success [23]. They also have decreased ability to regulate
their performance or speed under restricted time frames [18] and reflect on
the future negatively. In the specific case of students, distractions come
easy [15, 17, 22] and the ability to estimate the amount of time necessary to
finish a task is lacking [24].

###  2.2 Causes of Procrastination

Causes of procrastination are complex. Procrastination can stem from the task
itself or from individual differences in terms of personality and genetic
uniqueness. Task Aversion, dysphoric affect [43], or task appeal [31] refer to
an action that one finds unpleasant. By this definition, the more aversive the
task, the more likely one is to avoid it. Timing, rewards, and punishments
also influence the path towards procrastination. This is known in the
behavioral economics community as intertemporal choice or discounted utility
[41]. Marketing researchers view procrastination as deciding to perform a
certain task in a certain amount of time based on the perfect compromise
between cost and value. To a procrastinator, present cost is usually perceived
as higher than future costs, while value remains constant. This leads one to
act closer to the deadline, even though the action may be an enjoyable
activity [57].

Social psychologists argue that procrastination is stimulated by negative
causes. For example, fear of failure can contribute to procrastination [53].
Ferrari, based on 20 years of research, proposed three models of
procrastination: Arousal, Avoidant, and Decisional. Avoidant procrastinators
have the tendency to avoid certain outcomes such as fear of failure, success,
social isolation, or feeling like an impostor. Arousal procrastinators rely on
pressure in order to work. Indecisive procrastinators intentionally decide not
to act [20, 21]. Indecisive procrastination is related to a lack of competence
or time urgency. It is not related to laziness, but is rather more about not
understanding the trade-off between speed and accuracy [21]. Ferrari also
argues that learned helplessness, or the situation of experiencing a series of
uncontrollable and unpredictable unpleasant events [56], contributes to
procrastination. For example, some procrastinators use procrastination as a
self-handicapping strategy. When procrastinators perceive low-competence, they
blame external factors (such as not having enough time) in order to protect
their self-esteem and themselves from social judgment for poor performance.

The behavior-intention gap, addressed in Theory of Reasoned Action, is where
there is a gap between behavioral intention and behavior. Intention is a
strong predictor of behavior; however, that behavior is not guaranteed even
when the person believes that the act is worthwhile [6, 7]. Enjoyable
activities that can be done right away have more $utility$ than non-urgent or
undesirable tasks. This result was supported by Haghbin et al. [30].

###  2.3 Possible Psychological Interventions

Examples of psychological interventions to overcome procrastination are
plentiful. A popular intervention is isolating a task and breaking it into
small and attainable steps [32]. The effect can be enhanced by incorporating
goal setting theory, entailing the creation of small sub goals and enforcing
regular deadlines. This helps users regain self-efficacy and narrow the
intention-action gap [61]. In addition, Ainslie and Haslam suggest training
procrastinators to separate negative effects from taking action [41]. This can
be seen as a combination of willpower and mindfulness training. Schouwenburg
suggests using commitment devices to limit and eliminate short-term
temptations altogether such as turning on do not disturb mode or disconnecting
the Internet [54]. Instead of trying to rely on willpower or commitment
devices, Implementation Intention exploits psychological triggers and the
power of habit. It consists of forming an intention with specific action
plans. That intention acts as a cue for triggering followed behaviors. For
example, If I go to a restroom, I will also get a cup of water. A study shows
hat this makes individuals nearly eight times more likely to follow through
with a task [46]. Time Traveling, in contrast, focuses on mood regulation.
This approach encourages individuals to flip negative and positive reflections
toward tasks by asking them to think about how they will feel after the task
is completed [48]. Recent work in psychology explores the idea of having
individuals make a relationships with their future-selves to help
procrastinators make more rational decisions [27, 28]. The idea of the future-
self focuses on how current decisions will affect one’s self in the future.
For an academic setting, Ferrari suggests (1) finding the part of the paper
with the most individual interest, (2) creating an outline, and (3) writing in
small sessions [24]. Pychyl believes that just getting started is the most
effective way to decrease procrastination [48], arguing that splitting the
task into small, manageable sub-goals, it becomes easier to start.

Although these techniques have reported success, one limitation is the
training and active commitment required to implement them into one’s life.
Like other behavioral interventions, “only knowing how” does not cause changes
in behavior [55]. Even through one may implemented it, it is still unclear how
sustainable the initial commitment will last. We argue that exploring how
technology can augment psychological interventions is a vital role for the HCI
community. In the study presented here, we build the interventions explicitly
into our text editor system, hypothesizing that the system might guide
productive behavior if it is a part of the holistic intervention process.

##  3 Is Technology a New Thief of Time?

Joseph Ferrari condemns modern technology in his book, “Technology the New
Thief of Time” [24]. There is evidence to support his claim. In 2008, office
workers spent 28% of their time managing technology interruption and 46
percent of those interruptions — nearly half — were not necessary and not
urgent [20]. This report does not include the increasing number of
notifications from applications that demand attention. Cyber-psychologists
have coined this “e-procrastination” and associate this with “attitudes like a
sense of low control over one’s time and a desire to take risks by visiting
Web sites that are forbidden” [62]. Although this evidence positions modern
technology in a bad light, it does not represent the entire story. Technology
can also be a tool, depending on how we use it. Some practitioners recognize
the problem of procrastination and offer various solutions. “Stop
Procrastination,” for example, is an application that blocks distracting sites
and emails [4]. It is designed to eliminate interruptions, which has some
positive result [47]. “Avoiding Procrastination 101” teaches users various
techniques about procrastination [2]. “Write or Die 2” allows users to choose
either negative or positive consequences when they lose focus [5]. However,
there has been little evidence to support whether or not these techniques
work. In this paper, we evaluate some popular technological techniques of
behavior change: triggers, eliminating distraction, splitting to smaller sub-
tasks, goal setting, and machine augmented intelligence.

##  4 From Theories to UI Elements

###  4.1 Notifications for Getting Started

Push notifications are common in behavior change applications. Studies show
some types of notifications are capable of creating behavior and users
appreciate having notifications as reminders [10]; nonetheless, not all
notifications are equally important, and users are more likely to react to
important notifications [52]. Eyal, the author of Hook, argues that a good
trigger should be well timed, actionable, and spark interest [10, 14].
Interestingly, these qualities are found challenging in aversive tasks such
academic writing. Aversive tasks are unlikely to spark authors’ interest. They
have the perception of requiring huge time and effort, and in-a-mood writing
time is unpredictable. We could say the notifications from aversive tasks are
aversive notifications—no one wants to get one, because it is a reminder of an
aversive task. This leads us to ask, can notifications trigger actions in
aversive tasks?.

To answer this question, we implemented standard clickable notifications in
our customized editor. We utilized psychological intervention and persuasive
techniques to guide the content of the notifications. Moreover, we compare it
with a new type of notification we call an actioned notification: focusing on
eliciting an immediate action.

####  4.1.1 Standard Clickable Notifications

We implement a standard clickable notification in our text editor that can
contain various messages. Users can click on the notification to open the
editor (see Figure 1). This notification is commonly used in behavior-change
applications. We use it to remind, inform, and motivate users. We group the
messages into five categories based upon the intent of the notification:

  1. 1.

Standard Reminder(e.g.,“It is your writing time.”): This type of notification
only acts as a reminder. This concept is used in many task management
applications such as to-dos and calendars. We require users to set their daily
writing times, and they receive reminder notifications when the time is
reached. A study shows that students who set their own deadline for their
writing assignments perform better than those who do not [9]. The strength of
this notification type is that it is intuitive—most users are already familiar
with this style of notification.

  2. 2.

Encouraging Reminder (e.g., “Great Job! You have written 2000 words”): This
type of notification is employed by many fitness and online learning
applications. It attempts to increase user’s motivation through positive
reinforcement of previous activity.

  3. 3.

Inviting Action (e.g.,“Let’s write for 2 minutes!”): Unlike the encouraging
reminder notification, Inviting Action notifications attempt to create the
perception that a task requires small effort. Wendel defines Minimum Viable
Action to refer to the smallest action of the behavior. If the action is small
enough, users are more likely to enact the behavior [63]

  4. 4.

Tips and Tricks (e.g.,“Writing Tip: An idea is nothing more nor less than a
new combination of old elements. – The Pareto Principle”): This type of
notification is based on a Knowledge Deficit Model [55]. This model suggests
that not knowing how to perform the behavior can block the behavior from
happening, even though users have the right attitude. These notifications are
meant to invoke thought about writing behavior via trying new suggested tips.

  5. 5.

Mood Regulation (e.g., “Imagine how good it will feel to finish the
project.”): This notification is based on the psychological intervention Time
Traveling. It is a mood regulation technique that attempts to convert negative
reflections on doing the task to positive feelings about task completion.

Figure 1: An example push notification (top), action notification with text
prompt (middle), and concept expansion action notification (bottom).

####  4.1.2 Actioned Notifications

Unlike standard clickable notifications, actioned notifications encourage
performing an action instead of attempting to increase motivation. We make the
system split a task into small manageable chunks, and then present this chunk
as a question-and-answer system. We hypothesized that this would reduce user’s
effort and increase the likelihood of the action occurring [33]. Actioned
notifications contain a question and a text input box (see Figure 1). Users
can answer the question right away in the text box. Furthermore, we
hypothesized that the notification would help users focus on the action rather
than on the feelings surrounding the action, potentially reducing aversion to
the notification.

Figure 2: The main user interface for our custom text editor (left), markdown
display (center), and distraction free mode (right).

###  4.2 Persuasive Elements for Retaining Behavior

In addition to notifications, we designed our text editor with elements we
hypothesized would be beneficial to reducing procrastination such as an
immersive mode, a goal progress bar, and a writing assistance system.

####  4.2.1 Immersive Mode

This feature aims to curtail impulsiveness in procrastinators (see Figure 2).
Studies show that procrastinators are sensitive to distraction [15, 17, 22].
Immersive mode is a stage in which all external user interfaces are hidden and
the editor expands itself full screen on top of other applications. Many text
editors offer immersive mode. To further encourage users to focus on writing
and not editing, the customized editor supports Markdown Language. Markdown
allows the screen to be free from tools and buttons, making the interface
simpler. All participants are computer science students, so the markdown
format is familiar to them. Note that using markdown or immersive mode is
optional.

####  4.2.2 Goal Setting Theory: Goal Progress Bar

Latham argues in his book, “Goal setting theory is among the most valid and
useful theories of motivation of organizational behavior” [40]. Nonetheless,
it is not a perfect solution. Goal Setting depends on value of the outcome,
task difficulty, specificity, and feedback [40]. In other words, a goal that
has no appealing reward, is too easy or too hard, is vague, or has no
feedback, is not an effective goal. In addition, fantasizing negatively about
approaching the goal can increase stress and anxiety [12, 13]. For example, “I
will write to demonstrate my capability” vs “I will write to avoid being
punished.” Both might produce a similar outcome, but an avoidance goal might
be more susceptible to procrastination behavior, because it is driven by
negative thoughts. Selecting appropriate goals is a challenging task by
itself. Thus, in this study we set our goal to be word-count, because it is
specific, measurable, able to give real-time feedback, and nonjudgmental. We
provide real-time feedback with a small progress bar showing the current
number of words compared to the goal word count. Users can set their own goal,
but it is optional. In addition, we intentionally place the progress bar at a
noticeable place at the top of the screen so that users can easily get access
to the information (Figure 2. We hypothesize that this progress bar increases
conscious motivation.

####  4.2.3 Writing Assistance System

Procrastinators are poor at estimating the time necessary to finish a task
[24]. Haycock suggests that splitting a task into small manageable chunks can
help users get started [32]. With this system, we help users create a
framework for their paper, as well as to divide a long paper into manageable
sections. The application has a section panel to encourage users to create an
outline. It allows users to only focus on one section at a time as opposed to
scrolling through a long document. Users can search for certain sections via a
search box, Figure 2.

As discussed, a significant difficulty about writing is writer’s block. Rose
defines it as “[…] an inability to begin or continue writing for reasons other
than a lack of basic skill or commitment.” He demonstrates that writer’s block
can be caused by lacking of creative ideas [51]. Aren, in addition, defined
writer’s block as “a condition producing a transitory inability to express
one’s thoughts on paper. It is characterized by feelings of frustration,
rather than dread, hatred or panic” [8]. To help reduce writer’s block, we
used two text mining techniques: concept mining and concept expansion. Concept
mining uses the initial content in a user’s document to build a concept graph.
These abstract concepts are used as keywords to search external sources and
expand other related concepts in order to trigger creativity. In this paper,
we used IBM Watson Concept Insight and IBM Watson Concept Extension API [3].
Once users had written 1000 words or more, we extracted the initial texts to
find the top three concepts in the student’s paper. Then, we used those
concepts to find the top three TED talks that were most relevant to those
topics. The system also uses the extracted concepts to search more adjacent
concepts in the concept graph, providing additional TED talks about related
areas. Finally, the system sends the result back to users via a clickable
notification. We hypothesized that the system would help reduce anxiety and
increase creativity, as well as provide an incentive to start writing early so
that the concept map could be generated in time for the student to use the
additional information.

Finally, the writing assistance system creates custom question sets about the
writing a student has generated. The goal was to have these questions
stimulate creativity and create structure in the paper. These questions sets
are “wizard-of-ozed”—that is, the questions are generated by researchers, but
students did not know if they came from a human or computer. The advantage of
question sets over concept maps is that these question sets can be generated
with less student writing and take less time for students to review.

##  5 Evaluation

The custom text editor tracked word count, time spent typing, and documents
versions for further analysis. To evaluate whether the design strategies
affect users’ procrastination behavior and satisfaction, we conducted a
controlled trial experiment. The experiment consisted of two phases: a
baseline phase and a follow-up phase. The baseline study was used to determine
causes of procrastination and understand users’ writing behavior without any
notification system. In the follow-up experiment, notifications were added to
the text editor. Moreover, subjects were grouped in the follow-up study by
whether thay did or did not receive actioned notifications. During both phases
of the experiment we collected information about perceived procrastination
behavior and usability of the custom text editor. We used the PASS survey and
open-ended questions to determine the level of procrastination in our study
population (discussed below). All participants were required to fill out the
PASS survey and a system usability survey (System Usability Scale or SUS). All
experiments were conducted with proper IRB approval.

###  5.1 Baseline Study Design

The objective of the baseline study was to identify potential procrastinators
and non-procrastinators and preliminarily evaluate the editor for any major
usability issues that could possibly contribute to procrastination. Based on
data collected in the baseline study, we wanted to find groupings of
participants for the follow-up experimental study (explained in the next
section). It was also meant to help familiarize participants with using the
editor. All participants received the same version of the editor, but they did
not receive any notifications. Participants were college students enrolled in
a course on ubiquitous computing. They used the editor on a graded-3000-word-
writing assignment about the history of UbiComp from Weiser’s vision to
present day. The writing also involved a creative component where students
argued if certain elements from Weiser’s vision had come to pass, been
discarded, or evolved to different elements. The participants were a mix of
undergraduate and graduate students. They used the editor for nine days
leading up to the paper turn-in deadline.

Grouping by Writing Performance: The course instructor graded all paper
assignments. Participants were separately divided into groups based on their
assignment grade, above average and below average. It should be noted that all
students showed mostly good writing skills and were motivated to perform well
because the course was elective and presumably the students had interest in
the subject matter.

Grouping by Procrastination: Once the baseline experiment had ended, two
annotators independently reviewed figures of word count and writing time for
each participant. Annotators did not have access to the performance grouping
of the participants. The annotators reviewed the graphs and settled on two
different criteria in order to divide the participants into procrastinators
and non-procrastinators: the number of days before the deadline when a user
started (Group X: More than 3 days before, Group Y: Day before) and the number
of writing sessions and length of time spent on writing (Group A: Many
sessions, Group B: A few long sessions or one long session). Using these
criteria, the participants were grouped into high procrastination and low
procrastination. The high procrastination group always started the day before
(or day of) the deadline and spent 1 or 2 long sessions writing. Both
researchers unanimously agreed on which students were in the high
procrastination group. There was some disagreement on medium versus low
procrastination for participants that started early, but only wrote a few long
sessions; therefore, it was decided to group all participants who started
early into the low procrastination group.

Final Grouping for Follow-Up: Finally, the researchers divided subjects using
both the low/high procrastination grouping and above/below average groups as
shown in Table 1. For several participants, there was not enough writing data
to divide them into high/low procrastination groups. In this case, they were
placed in the “no data” group. This could occur, for example, for participants
who never connected to the internet or whose firewall prevented the editor
from sending word count and writing time information.

| Performance Level |
---|---|---
Procrastination level | Below Average | Above Average
No Data | 2 | 3
Low | 3 | 5
High | 4 | 4
Table 1: Breakdown of the number of participants by procrastination and
performance level.

It is interesting to note that, while most low procrastinators performed well
on the assignment, many high procrastinators also did well. Furthermore, the
distinguishing of “procrastinator” here is not a perfect measure because we
cannot be sure whether or not any negative feelings or planned delays
contributed to working on the paper the day before it was due. In other words,
behavior that may have seemed like procrastination may have been planned by
the student. The PASS survey results, however, support a conclusion that this
student behavior was procrastination.

The PASS (Procrastination Assessment Scale) [44] survey instrument is well
accepted in the psychology community for self-report of procrastination
behavior. The PASS survey consists of two sections. The first section
evaluates levels of procrastination. The section consists of eighteen items
scaled 1-5. The second section identifies 13 reasons for procrastination. It
consists of twenty-six items scaled 1-5. The first section of the PASS survey
demonstrated procrastination levels (0-10). The high procrastination group had
an average of 8.2 points (sd=0.45), and the low procrastination group had an
average of 6.6 points (sd=1.52). Thus, the results of the PASS survey support
the manual grouping that was based solely from writing behavior.

To create two final experimental groups, we chose an equal number of students
from each cell in Table 1. This ensured that each experimental group had an
approximately equal level of procrastination and writing performance. That is,
each group was a representative sample of the class across procrastination
level and writing performance. These experimental groups are designated as
GRP1 and GRP2 for the remainder of this paper.

###  5.2 Baseline-Study Results

Although users were given nine days to work on the paper, Figure 3 shows that
on average, most participants started writing 2-3 days before the deadline.
While GRP2 had two students that started on the assignment more than two days
before the deadline (as opposed to GRP1 with only one student), both groups
had a similar number of writing sessions per participant and a similar total
writing time. GRP1 had an average of 2.8 writing sessions (sd=0.98), and GRP2
had an average of 2.0 writing sessions (sd=1.0).

Figure 3: Number of words written graphed over time for baseline experiment.
Each line represents a separate participant.

Figure 4 shows reasons of self-reported procrastination via the PASS survey
for both baseline and follow-up studies. The top three reasons for
procrastination were aversion to the task, laziness, and time management.
Participants had varying reasons for aversion such as “It’s hard to put my
thoughts onto paper” and “I never know how [or] where to begin.”

The result from SUS shows the software usability score is about average
(mean=65.8, std=7.07). The reason most participants liked the editor is the
cleanness and simplicity of the user interface, with quotes such as “Very
simple UI” and “I liked the clean-ness of it.”

The reasons for concern were software reliability and stability. As given by
comments such as “I just need to be guaranteed my work isn’t going to be lost
when the program crashes (which happened) otherwise I don’t have enough
confidence to use it” and “crashing at the beginning freaking me out….”

Based on the given feedback, we implemented a set of upgrades to the editor
before the second experiment. We retained the clean and simple UI while also
minimizing user concerns by allowing users to export the document. We also
conducted more extensive software testing to eliminate crashing.

Figure 4: Comparing reasons to procrastinate between two groups for baseline
and follow-up experiments.

##  6 Experimental Follow-Up Study Design

To answer whether notifications help users get started in academic writing,
the same 21 college students participated in a follow-up study. The students
were assigned another graded 3000-word writing assignment. In this paper,
students were asked to summarize two application areas of UbiComp and
hypothesize about a research or class project that could contribute to one or
both of these application areas. Students were given nine days to complete the
assignment. As described, participants were divided into two representative
groups that used the custom text editor, GRP1 and GRP2. The program recorded
the following user actions related to writing: writing content, word count,
typing time, received notifications time, and users’ responses. For the second
experiment, the word count and writing time sampling rates were increased from
once per half hour to once per two minutes. This ensured a more reliable
estimation of the length and number of writing sessions in which users
engaged; moreover, the software is always running in the background, allowing
us to continually collect data and push out notifications. Each group received
a different set of features. GRP1 received standard clickable notifications
only. In contrast, GRP2 received both standard clickable notifications and
actioned notifications. We also sent out notifications that asked users their
reasons for accepting or dismissing the notification. Finally, all
participants again completed the Procrastination Assessment Scale for Students
(PASS) after the experiment, and filled out the SUS survey after the
experiment.

##  7 Experimental Follow-Up Study Results

Over the nine-day experiment period, we closely observed participants’
behavior and provided a series of standard clickable and actioned
notifications. Although all 21 participants agreed to take part in the study,
1 person was excluded because of low writing competency, 4 participants did
not install the application, and 2 participants installed the software but
never used it, in spite of sending several reminder emails. Therefore, 14
participants successfully installed and used the software. Half of the
participants (n=7) were online regularly and the remaining 7 people were
online a few hours per day. Fortunately, the number of disqualified
participants was about the same in GRP1 and GRP2, leaving 7 people in each
notification group.

In this study, we measured procrastination in two ways: writing statistics and
standard self-reports. Writing statistics was measured by the number of
sessions, starting writing date, and time spent writing per session.

Figure 5: Time spent writing continuously versus overall time before deadline
for two example participants.

Figure 5 shows example of writing sessions for two users. The x-axis
represents the number of days before the deadline, and the y-axis represents
the amount of time spent writing continuously in minutes. These two
participants represent two different behaviors from many participants: Some
students had multiple short sessions, and some wrote in one long session close
to the deadline. We used this data to identify the number of writing sessions
for each participant. GRP1 had 2.29 sessions on average (sd=1.82, n=7), and
GRP2 had 2.43 on average (sd=0.9, n=7). GRP1 wrote for 52.45 minutes on
average (sd=44.11, n=7), and GRP2 wrote for 44.24 on average (sd=21.56, n=7).
The data show that both groups spent short sessions at the beginning of the
assignment and long sessions near the deadline.

To compare the performance of participants in both groups, the course
instructor coded grades based upon two aspects: the novelty of the content (50
points), and how well they supported their arguments (50 points). To reduce
the subjectivity of comparing point by point, we converted the range 0-100 to
the discrete range F-A, and calculated the step difference. For example, if a
participant got a B on the first paper and an A- on the second paper, we give
him/her 2 steps difference (B,A,A-). GRP1 had a 0.75 step difference on
average (sd=1.28, n=7) and GRP2 had a -0.29 step difference on average
(sd=1.50, n=7).

Figure 6: Word count versus time before deadline for each group in the follow-
up experiment. Each line represents a separate participant.

Figure 6 shows word count over the four days before the deadline. The x-axis
indicates the number of days before the deadline and the y-axis shows the
number of words over time. GRP2 does appear to have started slightly earlier
than GRP1, but the small number of participants makes statistical testing
inappropriate here. Qualitatively, GRP2 spent the full day and night before
the deadline writing, whereas GRP1 mostly started writing the night before.

Figure 7: Cumulative typing time versus time before deadline for each group in
the follow-up experiment. Each line represents a separate participant.

Figure 7 shows the time spent on writing over 4 days before the deadline. The
x-axis shows the number of days before the deadline and the y-axis shows the
cumulative amount of time spent on typing in minutes. Despite clickable and
actioned notifications being sent regularly for the full nine-day period, 5
people in GRP1 started around a day before the deadline, while 4 people in
GRP2 started around 2 days before the deadline.

Participants received 143 notifications (118 clickable and 25 actioned
notifications). All participants immediately dismissed all 118 clickable
notifications. When we asked the reasons for dismissal, all participants
claimed they were in the middle of something else (many students noted that
they had mid-terms the week of the paper deadline). For the actioned
notifications, on the other hand, 36% were responded to (9 out of 25). Of the
9 notifications, 7 were related to outline-generation or content expansion.
The last 2 notifications were short questions with a prompting text box. In
these responses, the students only entered 2-3 words. When we asked the reason
for such short answers, they also responded by saying that they were in the
middle of another task. For students having trouble starting the assignment,
we asked a random subset of the participants why they felt they did not get
started quickly. The responses are low self-efficacy related, such as “Not
settle with the topic,” “not knowing what to write about,” and “Lack of
ideas.”

Our hypothesis was that actioned notifications would bypass negative
reflection of the task by requiring users to make quick snippets of thought
that helped to make writing more manageable; however, overusing notifications
ended up increasing negative feelings. For example, “It will be better if it
knows when I am writing and then decide not to pop up questions, it is kind of
a distraction” and “Annoying notifications.”

We asked participants what features were most useful and influenced their
decision making towards the writing tasks, summarized in Figure 8.

Figure 8: Survey response summary for the notification system.

50% of participants in GRP1 agreed that clickable notifications helped them be
more aware of the task, 25% said it helped them to get started, 12.5% agreed
that it motivated them, and 25% thought writing tips were helpful. In
contrast, in GRP2 (receiving clickable and actioned notifications) 43% agreed
that notifications helped them to be more aware of the task and thought
writing tips were helpful. Only 14.29% agreed that it helped them or motivated
them to get started. The starkest difference between the groups, then, was
their opinion of writing tips, where GRP1 was mostly neutral and GRP2 had
stronger opinions about the tips, both positive and negative.

Figure 9: Survey response summary for various elements of the custom text
editor.

Both groups used distraction free mode. Figure 9 summarizes the perceptions of
goal progress and distraction free mode. The result showed that 40% agreed
that it helped them write faster, and 60% agreed that it helped them focus
more on the task. Both groups used a goal progress bar indicator. The result
showed that 80% agreed that it helped them evaluate writing time better, and
73.33% agreed that it motivated them to reach their set goal. Participants
stated “I like the word counting bar a lot!” and “I like Word count and
overall UI.”

Only GRP2 received writing assistance notifications. The result showed that
30% agreed it helped them overcome writer’s block, 40% agreed that it helped
them focus more on the task, structure their thoughts better, and be more
creative (Figure 9). Participants had particularly strong opinions about these
notifications: “The automatic content generator learning system was absolutely
amazing. I was shocked to see how accurate it was. It truly helped me when I
was stuck and motivated me to keep going. If the negative aspects of the app
are removed (listed below), I will absolutely use this app in the future,” and
“I like the earlier planning questions to help me get started,” and “The
planning questions, definitely helpful.”

SUS scores for the updated the application had a mean of 60.7 points, with the
standard deviation of 12.30 points (n=14). From qualitative comments, 11
people out of 14 participants liked the simplicity of user interface: “I
really enjoyed using it to write my paper. The UI was very simple and did not
have a lot of distractions,” “Looks very clean,” and “it’s very minimalistic
and easy to use.”

The dislike regarding the application stemmed from annoyance with the
notifications and the fact that the application was always running. The memory
usage of the application is about 60Mb (30Mb compressed), which is about 50%
less than Dropbox or Google Drive syncing service. The visibility that
application was always running without users being able to control it, led to
the increased negative feeling: “I did not like having to keep the app running
at all times” and “It will better if it knows when I am writing and then
decide not to pop up questions, it is kind of a distraction.”

The outlining system also contributed to low usability scores. Many
individuals did not understand how to use the section panel (despite attending
a tutorial on using the application). A number of comments were similar to:
“[…] I was confused by the sections/files on the left side. What were they
actually for?”

##  8 Discussion

Our results show that there is very little to no difference regarding
procrastination behavior after technological intervention; however, because we
only captured the time and word count information, it was unclear when
participants were conducting background research for their papers. Comparing
the PASS self-reported surveys taken at the end of baseline and the end of the
follow-up study, the data shows an insignificant difference between both
baseline and follow-up procrastination level; however, Figure 4 shows that the
reason for procrastination shifted from “aversion toward the task” to “time
management”. The reason for this may be that the experimental study was the
week before mid-term exams. Many course projects were due that week, including
our writing assignment. Qualitative data also supports this hypothesis, with
several participants mentioning mid-term exams. On the other hand, Writing
assistants significantly decreased task aversiveness and difficulty in
decision making compared to the baseline study (p<0.05), while other factors
remained the same. This conclusion is also supported by qualitative data from
participants. These results suggest that the perceived benefit of attending a
notification must be considerable to be perceived as positive—the actioned
notifications were the only notifications attended to, but required
considerable time and user writing data to prepare.

###  8.1 Notifications

Although use of a notification is useful for external triggers of
procrastination, the notification not only triggers memory about the task, but
it might also trigger feelings associated with the task. If the task is
aversive, those negative feelings (anxiety, guilt, or boredom) are more likely
to be triggered. Thus, an aversive notification might be more susceptible to
annoyance, guilt, and anger than the desirable ones. This is consistent with
the basic psychological concept of conditioning, exemplified by a trigger (a
door bell) associated with a particular outcome (food) [56]. In addition, our
result implied that users may perceive an aversive notification as a reminder,
regardless of motivational text written in the notification. We hypothesized
that the tips and tricks notification may help users increase writing
competency, leading to the desired amount of writing; however, it appears that
users perceived the tips and tricks notifications as a disguised version of
reminders. Thus, the number, frequency, and prominence of aversive
notifications must be carefully considered. Some users may appreciate
reminders; however, users should be given full control over whether or not
they want to be notified, postpone the task, or not interact with it at all.
Our experiment implies that only notifications by themselves are not enough to
encourage users to get started on aversive tasks.

###  8.2 UI Elements and Writing Assistance

Word count as a goal does indeed motivate users as we expected. Most users
reported high satisfaction. The reasons that word count is so effective might
be its specific, measurable, and nonjudgmental nature. More importantly, it
gives users real-time feedback. They can see clearly how much they have
invested in their work. They focus on number of words, instead of focusing on
perfecting those words. One may argue that the goal of academic writing is
quality, not quantity. However, we argue that there will be no quality without
some quantity. Quality has to start from some quantity and iterative
improvement. If users fear starting, then they are less likely to produce any
quality work [11].

A number of participants liked the distraction free mode, and self-report
shows that they feel more focused on the task when entering this mode. Since
we did not track users outside our application, it remains unclear whether or
not distraction free mode affected users on a behavioral level.

The results imply that users appreciate systems that help them minimize time
and effort required to finish a task. Writing assistant systems can reduce
writers’ anxiety. At the same time, concept extraction gives useful feedback
to users. Concept extraction is a machine operation, so there is little to no
fear of social judgment on the quality of the work. Adding semi-intelligent
systems to help users finish aversive tasks easier and faster is a promising
strategy to reduce procrastination and increase satisfaction. Human feedback
may give strong social reinforcement. This power could increasing bursts of
motivation more than any machine ever could. At the same time, social judgment
can also paralyze users from getting started. Machine intelligence, in
contrast, provides pure non-judgmental feedback. Users still get feedback
while feeling safe from losing self-efficacy and social judgment. Balancing
human and machine feedback could facilitate reducing procrastination behavior.

In our experimental design, we had no placebo group for this set of features;
nonetheless, writing is a familiar behavior among college students. Most
students have experience with text editors without special features. Any self-
evaluation is likely to be compared with this previous experience. Even so,
this was not explicitly controlled for, so changes in attitude remain unclear.

###  8.3 General Lessons Learned

A key consideration for software designers should be data transparency. In
this study, we were collecting basic user statistics such as word count,
writing time, and notification reaction time. We told users exactly what data
we collected including explicit written words through informed consent. In
addition, writing a graded assignment is extremely important information for
the user. Users have high expectations for software stability. We understood
their concerns and told them that we have versioning systems. All data was
backed up periodically; nonetheless, some users still showed some level of
discomfort with using it. This might be caused by inability to manage their
own data. Thus, offering data transparency appropriately may create more trust
among users and researchers.

###  8.4 Summary of Lessons Learned

  1. 1.

If the goal is to create an immediate action, all blockers have to be
identified and eliminated before sending triggers.

  2. 2.

Notifications also trigger emotion that are associated with the task. Be
mindful before using them.

  3. 3.

Notifications are effective to decrease user’s burden of keeping track of a
list of tasks, but they are less useful in persuading actions that are
aversive.

  4. 4.

Users may perceive aversive notifications as a negative reminder, regardless
of motivational text written in the notification.

  5. 5.

Showing users proper, measurable, and specific goal helps users evaluate their
work better.

  6. 6.

It is a good idea to keep users’ autonomy in mind. If you decide to use
notifications, make sure you provide options for users to opt-out.

  7. 7.

Adding semi-intelligent systems to help users finish aversive tasks easier and
faster is a promising strategy to reduce procrastination and increase
satisfaction.

  8. 8.

Questions are useful for users who are already motivated to answer them;
however, it backfires for users who do not. Before asking questions, it is a
good idea to make sure users have enough answers or motivation to answer them.

  9. 9.

Users are concerned for their own data. Considering data transparency helps
users trust the service and increases satisfaction overall.

##  9 Conclusion

We discussed the current psychological literature regarding procrastination
and evaluated various technological interventions to decrease writing
procrastination among college students. We also outlined the challenges and
lessons learned through conducting procrastination research. Notifications
used in this papers did little to decrease procrastination behavior; moreover,
users who get more notifications have lower satisfaction than other peers.
Helping users clear their motivation blockers is the first step in performing
any task. Goal Setting Theory has proven effective in increasing motivation.
Using machine learning aids can decrease the aversion toward the tasks. Thus,
providing tools for making aversive tasks easier and less fearful is a
promising strategy to decrease procrastination, but must be carefully
applied—especially when employing notifications as motivators.

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