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The Effects of Chronic Multitasking on Analytical Writing



Chronic multitaskers perform worse on core multitasking skills: memory management, cognitive filtering and task switching, likely due to their inability to filter irrelevant stimuli [17]. Our experiment examines effects of chronic multitasking with task-relevant and irrelevant distractors on analytical writing quality. We found a general switch cost and, when controlling for that cost, effects of chronic multitasking habits: heavy multitaskers write worse essays in the irrelevant condition and better essays in the relevant condition. Our study changes multitasking research paradigms in two fundamental ways: it studied a realistic writing scenario including access to both irrelevant and relevant distractors. We found that the effect of chronic multitasking is complex; heavy multitaskers are seduced by unrelated distractors but able to integrate multiple sources of relevant information.
The Effects of Chronic Multitasking on Analytical Writing
Danielle M. Lottridge, Christine Rosakranse, Catherine S. Oh, Sean J. Westwood,
Katherine Baldoni, Abrey S. Mann, Cliff I. Nass
Department of Communication, Stanford University
450 Serra Mall, Stanford, CA 94305-2050
lottridg | being | syoh | seanjw | kbaldoni | asmann | nass
Chronic multitaskers perform worse on core multitasking
skills: memory management, cognitive filtering and task
switching, likely due to their inability to filter irrelevant
stimuli [17]. Our experiment examines effects of chronic
multitasking with task-relevant and irrelevant distractors on
analytical writing quality. We found a general switch cost
and, when controlling for that cost, effects of chronic
multitasking habits: heavy multitaskers write worse essays
in the irrelevant condition and better essays in the relevant
condition. Our study changes multitasking research
paradigms in two fundamental ways: it studied a realistic
writing scenario including access to both irrelevant and
relevant distractors. We found that the effect of chronic
multitasking is complex; heavy multitaskers are seduced by
unrelated distractors but able to integrate multiple sources
of relevant information.
Author Keywords
Multitasking; analytical writing; distractors; chronic
multitasking; media multitasking index.
ACM Classification Keywords
H.1.2. User/Machine Systems: Human factors.
Is multitasking good or bad for you? Proponents (including
many employers) herald the ability to effectively juggle
tasks and pressure workers to respond to messages
immediately. Dissenters bemoan constant interruptions,
distractions and the inability to get engrossed. Can we
improve our ability to multitask? How does multitasking
affect our attention span and the quality of our work?
‘Practice makes perfect’—except when it comes to
multitasking. Chronic multitaskers perform worse on the
core executive functions of multitasking: taking in and
releasing items from short-term memory stores (memory
management), attending to relevant material and inhibiting
irrelevant material (cognitive filtering), and inhibiting the
cognitive structures required for one task and activating
those required for another task (task switching) [17]. These
results suggest a unique and important change in
fundamental information processing. Counterintuitively,
multitasking does not appear to be a problem of attending
to the right things; rather chronic multitaskers’ trouble
appears to be the inability to ignore the wrong things.
Multitasking is studied in two main ways: field studies
prioritizing external validity (e.g., [6]; what does
multitasking look like in the world?) and controlled
experiments prioritizing internal validity (e.g., [17]); such
experiments tend to follow cognitive psychology standards,
often with primary tasks related to basic cognitive function
and unrelated distractors. This experiment extends that
research in two fundamental ways: first, it studies
multitasking experimentally in the realistic domain of essay
writing; second, it exposes subjects to information streams
that are either relevant or irrelevant to the task at hand.
The more people are exposed to media, the more they
multitask [9]. High sensation seekers multitask more often
[13]. The impact begins at a young age; in a survey of 3,461
North American girls aged 8-12, multitasking was inversely
face-to-face communication, feelings of social success, and
sleep [19]. When ‘heavy’ (chronic) media multitaskers
(HMM) were compared with ‘light’ media multitaskers
(LMM), HMM were bad at precisely the tasks at which one
would expect them to be good [17]. Habitual and in-the-
moment multitasking both hurt cognitive performance.
Participants completing three tasks simultaneously
performed worse on a subsequent memory test when
compared to participants performing the same three tasks
serially [26]. Multitasking contributes to cognitive overload
through too much information supply and demand,
interruptions, and inadequate infrastructure, thus increasing
needs for planning, monitoring, reminding, and
reclassifying information [14]. A study on word tasks found
that people maximized productivity by switching to
prioritize a continuous rate of return (an information
foraging orientation) and to complete subgoals [18].
Salvucci et al. model multitasking behavior with cognitive
architecture, threaded cognition and memory-for-goals
theory [23]. Others suggest that people self-regulate their
interruptions to maintain a flow state [1].
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CHI 2015, April 18 - 23, 2015, Seoul, Republic of Korea.
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Task Interruption & Resumption
CHI 2015, Crossings, Seoul, Korea
The type of task (information versus non-information) and
individual differences can moderate how tasks are
combined for multitasking; for example, higher versus
lower order task, difficulty and information carry-over
affect impact [12]. If both tasks require the same cognitive
framework ('problem state'), it interferes with performance
[3]. It was proposed to be more effective to multitask with
tasks using different parts of the brain [24]. But fMRI
studies reveal that tasks using different parts of the brain
(e.g., perceptual encoding and decision-making) suffered
from temporary attention limits [25]. These costs appear to
increase with age, as older adults direct more attention
toward irrelevant stimuli [5].
Field studies reveal that multitasking is associated with
poor academic performance [22]. Multitasking students
take more time to achieve the same performance as
monotaskers [4], or to complete the same task [10]; texting
students performed worse on exams than non-texters [7];
and students with open laptops had worse memory for
lectures than those without [11]. The present research is
however the first to study the causal relationship between
multitasking and writing quality.
The effects of chronic and in-the-moment multitasking on
analytical writing quality were investigated with an essay
task accompanied by relevant or irrelevant distractors.
Undergraduates were granted course credit and categorized
using top and bottom quartiles Media Multitasking Index
(MMI) scores [17]. 40 HMM and 40 LMM participated; 37
were male. Participants were randomly assigned to the
relevant or irrelevant condition. Gender was balanced
across MMI score and condition.
Sessions consisted of groups of 5 students using laptops
separated by divider boards. The task was a 30-minute
GRE-style essay arguing for or against a statement on
whether luxuries and conveniences of modernity strengthen
character. GRE performance is a valid predictor of graduate
grade point average, comprehensive examination scores,
publication citation counts, and faculty ratings [15]. Text
was entered through a simple editor, which included an
input box for the essay and a side column with an ostensible
forum including distractor links to online content.
Participants were invited to post comments and told that the
side column displayed comments by other participants.
Predetermined comments and associated links were
displayed approximately every 2 minutes. In the relevant
condition, comments were related to the writing question,
and included links to relevant articles. In the irrelevant
condition, comments included unrelated links, such as
sports news and funny videos. We recorded the number of
switches between the writing and other applications (e.g.
browsers) and time spent writing.
Essays were scored manually based on a standard
Organization and Coherence university grading scheme.
Organization was judged by presence of 1) an introduction,
body, and conclusion; 2) paragraph structure; and 3)
appropriate arguments. Coherence was judged by 1)
connection between adjacent sentences, 2) building on
ideas, and 3) contributions to over-arching argument. On a
subset of 20 essays (25%), two raters (ignorant of the
conditions) achieved good inter-rater reliability r = .86.
Essays were also scored automatically with the Flesch-
Kincaid, a widely used (e.g., US military, MS Word)
indicator of writing complexity [8]. It is calculated from
numbers of syllables per word and words per sentence. The
lower the score, the more difficult the text to read; for
example, "The cat sat on the mat" scores 116: low
complexity and highly readable.
First, we investigate the correlation between number of
switches between writing software and browser, time spent
writing (includes editing, revising, etc), essay length and
writing quality. Then, we control for number of switches to
isolate effects of chronic multitasking. One MANCOVA
investigates effects of between-subjects variables media
multitasking (HMM/LMM) and condition (relevant and
irrelevant) on time spent writing. A second MANCOVA
controls for length, switches and time spent writing to
examine effects on dependent variables: writing quality and
Flesch-Kincaid (transformed for normality [16]). In
summary, our hypotheses are:
H1. The more switches, a) the less time spent writing, b) the
worse quality, and c) less complex essays.
H2. HMM will spend more time on distractors than LMM.
H3. HMM will write essays that are a) lower quality and b)
less complex than those written by LMM.
RQ: Will the relevance of the distractors influence H2-3?
We observed a switch cost: the more participants switch,
the less time participants spend writing (H1a: r =-.528,
p<.001) and the worse the quality of their writing (H1b: r =
-.307, p=.006). H1c was not supported. We found that time
spent writing correlated with length (r=.298, p=.01) and
higher complexity (r=-.306, p=.006). Length correlated
with quality (r=.529, p<.001). This suggests that if given
more time to write, students would likely produce longer,
more complex essays and that those who write more
independent of allotted time achieve higher quality essays.
Controlling for number of switches, we found an interaction
effect where HMM spent a quarter of their time following
irrelevant links (almost 7 min.) whereas LMM spent only
16% doing so (approx. 4.5 min.; F[1,79]=6.314, p=.01,
partial η2=0.78). In the relevant condition, both LMM and
HMM spent about one fifth of their time following links.
When controlling for the number of switches and time spent
writing, we observed a significant interaction between
media multitasking and condition on writing quality
Task Interruption & Resumption
CHI 2015, Crossings, Seoul, Korea
Figure 1a. Transformed writing quality
Figure 1b. Transformed Flesch-Kincaid writing
complexity for HMM and LMM in the relevant and
irrelevant conditions; *error bars=95% C.I.
(F[1,79]=5.859, p=.02, partial η2=.074; Figure 1a) and
Flesch-Kincaid (F[1,79]=4.348, p=.04, partial η2=.056;
Figure 1b). Complexity and quality were not correlated (r=-
.121, p=.284). There were no main effects (H2, H3a, H3b).
HMM wrote the highest quality essays in the relevant
condition and the poorest quality essays in the irrelevant
condition, whereas LMM were unaffected (mHMM-R = 4.9,
mHMM-I = 3.9, mLMM-R = 4.1, mHMM-I = 4.4). These effects are
due to chronic multitasking, as in-the-moment multitasking
(switches, time spent following links) is controlled for.
Thus, we find differences based on chronic multitasking
habits: heavy multitaskers in the irrelevant condition
suffered the most in terms of essay quality and simplistic
writing. However, HMM appear to use their multitasking
habits in a positive way in the relevant condition, where
they wrote higher quality essays with more sophisticated
prose. The quality of the LMM essays was unaffected by
condition, though the complexity of the writing was higher
in the irrelevant condition where more time was spent
writing compared to the relevant condition. The apparent
danger is that HMM’s behavior toward irrelevant links
reflects how they tend to write in the real world: a t-test
shows that HMM are much more likely than LMM to self-
report multitasking during homework (p < .001; mHMM = 2.4
(SD = 1.3); mLMM = .64 (SD = .42)).
In this study, we examined how heavy and light media
multitaskers differ in analytical writing behavior when
faced with relevant or irrelevant distractors. Our study was
designed for external validity with a realistic scenario:
writing essays online with access to both relevant and
irrelevant information. Our study was unique in
reconceptualizing switching as relevancy-dependent rather
than looking only at the effects of irrelevant stimuli.
Our findings support a multi-faceted view of costs and
benefits of multitasking. For both groups, writing quality
suffered as a function of the number of switches between
writing application and browser. Thus, in-the-moment
multitasking carries a cost for writing quality. However,
when controlling for switches and time spent writing, this
negative effect was dependent on one’s chronic
multitasking habits and the type of distractors present.
HMM benefited from the relevant condition and had higher
writing scores. In the irrelevant condition, LMM were able
to easily ignore links and spent more time writing. HMM
were seduced by irrelevant content; they spent significantly
less time writing and wrote poorer quality essays.
The relationship between complexity and quality is
nuanced. Complexity might be sophisticated when paired
with high quality but convoluted when paired with low
quality. Low complexity might mean readable when paired
with high quality, simplistic when paired with low quality.
Our results suggest complexity is expressed differently by
HMM and LMM depending on condition. HMM had high
complexity and quality in the relevant condition and low
complexity and quality in the irrelevant condition,
suggesting that relevancy increased sophistication and
irrelevancy decreased sophistication. LMM writing did not
differ in quality with condition. Lower complexity in the
relevant condition suggests simplicity did not affect quality.
High complexity in the irrelevant condition suggests
intricacy did not improve quality. The relationship between
writing complexity and quality continues to be studied (e.g.
[2]); our results add to this ongoing discussion.
Our study finds chronic multitaskers have advantages when
using multiple streams of task-related content; they appear
to have an ability to quickly integrate relevant information.
This behavior fits within the theoretical framework of
information foraging [20]; HMM may have developed
better sampling techniques that are utilized when
constrained to relevant material. Yet, as sensation seekers,
chronic multitaskers fail to ignore interesting, irrelevant
material; they lose time by consuming those media, and
their work suffers as a result. As light multitaskers consume
fewer media, the condition neither helped nor hurt.
Multitasking is good and bad for you. Our study found that
HMM benefit when media streams are relevant and suffer
when they are irrelevant. Unfortunately, HMM typically
multitask with irrelevant media streams; our finding that
students multitask during homework is corroborated by
recent research that found students often chat online while
writing essays [22]. Therefore, HMM often do not take full
advantage of their integration capacity to optimize their
performance. Careful construction of a context or digital
Task Interruption & Resumption
CHI 2015, Crossings, Seoul, Korea
environment to constrain HMM’s media intake to relevant
streams may thus greatly benefit their performance.
We thank Google for their support, Erina Dubois for her
help, Ethan Plaut for editing, and our anonymous reviewers
for their generous and constructive critiques.
1. Adler, R.F., and Benbunan-Fich, R. Self-Interruptions in
Discretionary Multitasking. Computers in Human
Behavior 29, 4 (2013), 1441-1449.
2. Beers, S.F., and Nagy, W.E. Syntactic complexity as a
predictor of adolescent writing quality: Which
measures? Which genre? Reading & Writing 22,
2(2009), 185-200.
3. Borst, J.P., Taatgen, N.A., & Van Rijn, H. The problem
state: A cognitive bottleneck in multitasking. Journal of
Experimental Psychology: Learning, Memory, &
Cognition 36, (2010), 363-382.
4. Bowman, L.L., Levine, L.E., Waite, B.M., and Gendron,
M. Can students really multi task? An experimental
study of instant messaging while reading. Computers &
Education 5, 4 (2010), 927-931.
5. Clapp, W.C., Rubens, M.T., Sabharwal, J., and
Gazzaley, A. Deficit in switching between functional
brain networks underlies the impact of multitasking on
working memory in older adults. Proc. of the National
Academy of Sciences 108, 17 (2011), 7212-7217.
6. Dabbish, L., Mark, G., and Gonzalez, V. Why do I keep
interrupting myself?: Self interruption, habit, and
environment. Proc. CHI (2011), 3127- 3130.
7. Ellis, Y., Daniels, B., and Jauregui, A. The effect of
multitasking on the grade performance of business
students. Research in Higher Education Journal 8,
(2010), 1-10.
8. Flesch, R. A new readability yardstick. Journal of
Applied Psychology 32, (1948), 221–233.
9. Foehr, U.G. Media multitasking among American
youth: Prevalence, pairings and predictors. Unpublished
doctoral dissertation (2006), Stanford, CA, USA.
10. Fox, A.B., Rosen, J., and Crawford, M. Distractions,
Distractions: Does Instant Messaging Affect College
Students’ Performance on a Concurrent Reading
Comprehension Task? Cyberpsychology & Behavior,
12, 1 (2009), 51-53.
11. Hembrooke, H., and Gay, G. The Laptop and the
Lecture: The Effects of Multitasking in Learning
Environments. Journal of Computing in Higher
Education 15, 1 (2003), 46-64.
12. Iqbal, S.T., and Bailey, B.P. Leveraging Characteristics
of task structure to predict costs of interruption. Proc.
CHI (2006), 741-750.
13. Jeong, S.H., and Fishbein, M. Predictors of Multitasking
with Media: Media Factors and Audience Factors.
Media Psychology 10, 3 (2007), 364-384.
14. Kirsch, D. A Few Thoughts on Cognitive Overload.
Intellectica 1, 30 (2000), 19-51.
15. Kuncel, N.R., Hezlett, S.A., and Ones, D.S. A
comprehensive meta-analysis of the predictive validity
of the Graduate Record Examinations: Implications for
graduate student selection and performance.
Psychological Bulletin 127, 1 (2001), 162-181.
16. LaLonde, S.M. Transforming variables for normality
and linearity—when, how, why and why not’s. SAS
NESUG (2005), 11-14.
17. Ophir, E., Nass, C., and Wagner, A. D. Cognitive
control in media multitaskers. Proc. of the National
Academy of Sciences 106, 37 (2009). 15583-15587.
18. Payne, S. J., Duggan, G. B., and Neth, H. Discretionary
task interleaving: Heuristics for time allocation in
cognitive foraging. Journal of Experimental
Psychology: General 136, 3 (2007), 370–388.
19. Pea, R., Nass, C., Meheula, L., Rance, M., Kumar, A.,
Bamford, H., Nass, M., Simha, A., Stillerman, B., Yang,
S., and Zhou, M. Media use, face-to-face
communication, media multitasking, and social well-
being among 8- to 12-year-old girls. Developmental
Psychology 48, 2 (2012), 327-336.
20. Reader, W., and Payne, S. Allocating time across
multiple texts: sampling and satisficing. Human-
Computer Interaction 22, 3 (2007), 263-298.
21. Roberts, D.F., and Foehr, U.G. Trends in Media Use.
The Future of Children. Children and Electronic Media
18, 1 (2008), 11-37.
22. Rosen, L.D., Carrier, L.M., and Cheever, N. A.
Facebook and texting made me do it: Media-induced
task-switching while studying. Computers in Human
Behavior 29, 3 (2013), 948-958.
23. Salvucci, D. D., Taatgen, N. A., and Borst, J. P. Toward
a unified theory of the multitasking continuum: from
concurrent performance to task switching, interruption,
and resumption. Proc. CHI (2009), 1819-1828.
24. Spink, A., and Park, M. Information and non-
information multitasking interplay. Journal of
Documentation 61, 4 (2005), 548–555.
25. Tombu, M.N., Asplund, C.L., Dux, P.E., Godwin, D.,
Martin, J.W., and Marois, R. A Unified attentional
bottleneck in the human brain. Proc. of the National
Academy of Sciences 108, 33 (2011), 13426–13431.
26. Vega, V., McCracken, K., Nass, C.I., and Labs, L.
Multitasking Effects on Visual Working Memory,
Working Memory and Executive Control. ICA (2008).
Task Interruption & Resumption
CHI 2015, Crossings, Seoul, Korea
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... Lab-based tasks involving distracting stimuli that do not carry particular meaning may indicate a general tendency to attend to irrelevant stimuli, but they are agnostic to the complexities of attention distribution in real-world environments where different forms of distracting stimuli are experienced as less or more salient by different individuals. Lottridge et al. (2015) consider associations between chronic media multitasking levels and analytical writing quality under conditions of either task-relevant or task-irrelevant distractors. Both forms of distractor affected performance. ...
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The rapid advancement of mobile computing devices and the ever-growing range of infotainment services they enable have cultivated high levels of media multitasking. Studies have considered the effects of this form of behaviour for cognitive control ability, with findings suggesting that chronic media multitasking is associated with reduced inhibitory control. In this study we advance knowledge in this domain by investigating differences in the attention distribution strategies of high and low media multitaskers (HMMs and LMMs) through a simple, two-dimensional game. 1 063 university students completed a web-based survey concerning their media multitasking behaviour and played the 2D game. Contributing to the ecological validity of the study the game was played within the respondent's web-browser, as part of the survey, at a time and place (and on a computer) of their choosing. During gameplay one of two different banners, both irrelevant to the game, were displayed adjacent to the game. No instructions were provided in relation to the banners. Our analysis considered respondents' performance in the game in relation to both their media multitasking and the content of the banner displayed. Our findings suggest that while HMMs attend to distracting stimuli independent of their content or salience, LMMs are more selective. This selectivity enables improved primary task performance when distracting stimuli are deemed unimportant. Additionally, we found that LMMs generally recalled banner information more accurately after the game was played.
... In this paper we are focused on a particular aspect of working practices; multitasking. Multitasking is an integral part of most working contexts [6,15,18,19,48], and while multitasking has been found to increase feelings of entertainment and relaxation [8], multitasking is more widely known for its negative effects on task performance [15,44,48]. Tools that can influence multitasking behavior by adjusting tasks or people's attitudes might be able to increase productivity in crowdworking settings. ...
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Crowdworkers receive no formal training for managing their tasks, time or working environment. To develop tools that support such workers, an understanding of their preferences and the constraints they are under is essential. We asked 317 experienced Amazon Mechanical Turk workers about factors that influence their task and time management. We found that a large number of the crowdworkers score highly on a measure of polychronicity; this means that they prefer to frequently switch tasks and happily accommodate regular work and non-work interruptions. While a preference for polychronicity might equip people well to deal with the structural demands of crowdworking platforms, we also know that multitasking negatively affects workers' productivity. This puts crowdworkers' working preferences into conflict with the desire of requesters to maximize workers' productivity. Combining the findings of prior research with the new knowledge obtained from our participants, we enumerate practical design options that could enable workers, requesters and platform developers to make adjustments that would improve crowdworkers' experiences.
... In addition, the effect of chronic multitasking on analytical writing has also been identified as negative. The writing suffered from the increasing number of switching between tasks, both when multitasked to access relevant information and irrelevant information (Lottridge et al., 2015). Email checking habits of a person are also identified as influential on their productivity based on the nature and the intensity of interruption the email checking process induce on the task being attended at the time. ...
... Experimental and field work in HCI finds the context of multitasking matters. Lottridge et al. [49] found that the performance of heavy media multitasking depended on distractors: when presented with irrelevant distractors, chronic multitaskers wrote worse quality essays but with relevant distractors, they wrote better essays. Mark et al. [52] found that college students feel less stressed when they switch to social media for entertainment but that the amount of multitasking is positively associated with stress and negatively with self-assessed productivity. ...
Mobile videochat use has been growing, especially for teens. To better understand teens' videochat practices, we conducted a two-week photo diary study with 16 teens. We found that most often, teens videochat with their closest friends from their bedrooms when they feel lonely or bored. Teens turned to videochat when understimulated but also felt understimulated during videochat. In order to manage this, they multitasked -teens moved from active chatting to co-presence while engaged in separate activities like scrolling social feeds or playing games. We uncovered social norms of reciprocity of attention, where teens match the attention level of the other and give leeway to briefly divert attention. Digital notifications did not feel disruptive to the videochat but family members' interruptions felt disruptive as teens' domestic context intruded into their virtual peer setting. We discuss these findings and their implications for research and design of videochat systems.
This book constitutes late breaking papers from the 23rd International Conference on Human-Computer Interaction, HCII 2021, which was held in July 2021. The conference was planned to take place in Washington DC, USA but had to change to a virtual conference mode due to the COVID-19 pandemic. A total of 5222 individuals from academia, research institutes, industry, and governmental agencies from 81 countries submitted contributions, and 1276 papers and 241 posters were included in the volumes of the proceedings that were published before the start of the conference. Additionally, 174 papers and 146 posters are included in the volumes of the proceedings published after the conference, as “Late Breaking Work” (papers and posters). The contributions thoroughly cover the entire field of HCI, addressing major advances in knowledge and effective use of computers in a variety of application areas.
In this study we investigated how digital leaners’ behavior could be used to identify their attentional state at the time. It was expected to map attentional states with the level of challenge presented and the level of engagement achieved by an activity related to learning. To identify the main attentional considerations and related behavior, we have administered a questionnaire among 43 participants and requested them to self-report on attentional states, the measures of motivation, and the required effort. The questionnaire was adapted from Everyday Life attentional Scale (ELAS), and tested on 6 activities related to learning, directly or indirectly. The average level of focus the participants reported on these activities ranged from 50%–65%. They also declared to feel restless (53.5%) and stressed (41.9%) when motivated to do a task. Interestingly, 67.4% of the participants attributed to social media use when distracted from the learning activity. This study opens several avenues to use behavioral data of digital learners to identify the attentional state shifts of digital learners. Relationships among the cognitive load, the behavioral interactions, and level of attention can be observed. However, the nature and the magnitude of such relationships are yet to be explored.
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Power transformations are often suggested as a means to "normalize" univariate data which may be skewed left or right, or as a way to "straighten out" a bivariate curvilinear relationship in a regression model. This talk will focus on identifying when transformations are appro-priate and how to choose the proper transformations using SAS® and new features of the ODS. There is also a discussion of why, or why not, you may choose the "optimal" transformation identified by SAS.
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This article addresses three main questions: What causes cognitive overload in the workplace? What analytical framework should be used to understand how agents interact with their work environments? How can environments be restructured to improve the cognitive workflow of agents? Four primary causes of overload are identified: too much tasking and interruption, and inadequate workplace infrastructure to help reduce the need for planning, monitoring, reminding, reclassifying information, etc… The first step in reducing the cognitive impact of these causes is to enrich classical frameworks for understanding work environments, such as Newell and Simon’s notion of a task environment, by recognizing that our actual workplace is a superposition of many specific environments – activity spaces – which we slip between. Each has its own cost structure arising from the tools and resources available, including the cognitive strategies and interpretational frameworks of individual agents. These cognitive factors are significant, affecting how easy or difficult it is to perform an action, such as finding a specific paper in a “mess” desk. A few simple examples show how work environments can be redesigned and how restructuring can alter the cost structure of activity spaces.
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In this research, multitasking with media is defined as an audience behavior that combines media use with another non-media activity. This study examines (a) the prevalence and patterns of multitasking among 14- to 16-year-olds and (b) the media and audience factors that predict such behavior. Consistent with previous research, this study found that youth frequently multitask with media. Both (a) ownership of media in bedrooms as a media factor and (b) sensation seeking as an audience factor were found to be significant predictors of multitasking with media. The theoretical and practical implications of the study are further discussed.
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The growth and expansion of communication technology have created a multitasking generation of students who believe they are utilizing time more effectively by performing two or more tasks simultaneously. Multitasking refers to the concurrent processing of two or more tasks through a process of context switching. However, research by neuroscientists show that multitasking reduces the brain’s ability to effectively retrieve information. The purpose of this study is to empirically examine whether multitasking in class affects the grade performance of business students. We conducted an experiment using 62 undergraduate business students enrolled in the first accounting principles course at a university in the Southeastern part of the United States. The students participated in a class lecture and afterwards were given a quiz covering the lecture content. One-half of the participants were allowed to multitask in the form of texting during a class lecture, while the other half of the participants were not. Our findings indicate that the exam scores of students who text in class are significantly lower than the exam scores of students who do not text in class. Thus, multitasking during class is considered a distraction that is likely to result in lower grade performance. The implications of this study can be very useful to students, instructors, administrators, and other academic stakeholders, about the effect of multitasking in a learning environment on students’ grade performance.
Human multitasking is often the result of self-initiated interruptions in the performance of an ongoing task. These self-interruptions occur in the absence of external triggers such as electronic alerts or email notifications. Compared to externally induced interruptions, self-interruptions have not received enough research attention. To address this gap, this paper develops a typology of self-interruptions based on the integration of Flow Theory and Self-regulation Theory. In this new typology, the two major categories stem from positive and negative feelings of task progress and prospects of goal attainment. The proposed classification is validated in an experimental multitasking environment with pre-defined tasks. Empirical findings indicate that negative feelings trigger more self-interruptions than positive feelings. In general, more self-interruptions result in lower accuracy in all tasks. The results suggest that negative internal triggers of self-interruptions unleash a downward spiral that may degrade performance.
We report two studies investigating readers' ability to allocate limited time adaptively across online texts of varying difficulty. In both studies participants were asked to learn about the human heart and were free to allocate time to 4 separate online texts about the heart but did not have enough time to read them all thoroughly. Of particular interest was whether readers attempted to select the best text for them (by sampling the texts before reading) or to monitor texts while reading them and continue reading any text judged good enough (a satisficing strategy). We argue that both strategies can be considered adaptive, depending on properties of readers, texts, and tasks. Experiment 1 tested readers with a range of background knowledge and allowed them either 7 or 15 min study time. It showed that participants were adaptive in how they allocated their time in that more knowledgeable readers spent more time reading more difficult texts. Satisficing was a much more common strategy than sampling. Experiment 2 showed that providing outline overviews of each text dramatically increased the number of participants using a sampling strategy so that it became the modal strategy. However, this change in strategy had no effect on learning. Outline overviews presumably changed readers' perception of the ease with which relevant dimensions of text quality can be judged.
a b s t r a c t Electronic communication is emotionally gratifying, but how do such technological distractions impact academic learning? The current study observed 263 middle school, high school and university students studying for 15 min in their homes. Observers noted technologies present and computer windows open in the learning environment prior to studying plus a minute-by-minute assessment of on-task behavior, off-task technology use and open computer windows during studying. A questionnaire assessed study strategies, task-switching preference, technology attitudes, media usage, monthly texting and phone call-ing, social networking use and grade point average (GPA). Participants averaged less than six minutes on task prior to switching most often due to technological distractions including social media, texting and preference for task-switching. Having a positive attitude toward technology did not affect being on-task during studying. However, those who preferred to task-switch had more distracting technologies avail-able and were more likely to be off-task than others. Also, those who accessed Facebook had lower GPAs than those who avoided it. Finally, students with relatively high use of study strategies were more likely to stay on-task than other students. The educational implications include allowing students short ''tech-nology breaks'' to reduce distractions and teaching students metacognitive strategies regarding when interruptions negatively impact learning.
This paper explores and speculates on a new direction in human information behavior (HIB) research. We explore the nature of HIB as a multitasking activity, the interplay between information behavior and non-information behavior tasks, and the relation between multitasking information behavior to cognitive style and individual differences. A model of multitasking between information and non-information behavior tasks is also proposed. Multitasking information behavior is emerging as an important HIB research area in need of further theoretical and empirical development.
Recent studies show that humans engage in multitasking information behaviors, often in libraries, as they seek and search for information on more than one information task. Multitasking information behaviors may consist of library search and use behaviors, or database or Web search sessions on multiple information tasks. However, few human information behavior models of seeking, searching or use, or library use models, include considerations of multitasking information behavior. This paper reports results from a case study exploring multitasking information behavior by an information seeker in a public library using diary, observation and interview data collection techniques. The information seeker sought information on four unrelated personal information tasks during two public library visits. Findings include a taxonomy of information behaviors; a sequential flowchart of the information seeker's complex and iterative processes, including multitasking information behavior, electronic searches, physical library searches, serendipitous browsing, and successive searches; and that the information seeker engaged in a process of 17 information task switches over two library visits. A model of information multitasking and information task switching is presented. Implications for library services and bibliographic instruction are also discussed.