www.ijcrsee.com

Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

Original scientific paper

Received: February 02, 2025.

Revised: April 09, 2025.

Accepted: April 12, 2025.

UDC:

159.952.4-057.875

10.23947/2334-8496-2025-13-1-63-73

Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Corresponding author: kristina.randjelovic@pr.ac.rs

Abstract: Academic media multitasking specifically refers to the phenomenon where students or academics divide their

attention between learning-related activities, such as studying or reading scholarly material, and non-learning activities like

texting friends, checking social media, or browsing unrelated websites. Studies confirm a negative correlation between media

multitasking and academic achievement, with some reporting small to moderate effects or no correlation at all. This topic is

particularly important today due to the pervasive use of media among younger generations and its impact on attention, focus,

academic performance, and cognitive load. This meta-analysis aimed to quantitatively integrate individual correlational studies

and draw general conclusions about the relationship between academic media multitasking and academic achievement. The

sample comprised studies published in English scientific journals from 2010 to the present, with methodological characteristics

matching the context of this analysis. A total of 11 studies were included in the final analysis. Correlation coefficients were used

as a measure of effect size, with both fixed and random effects models applied to calculate the overall measure of effect size.

The quality of the included studies was assessed, and potential publication bias was examined using a symmetry graph and

Trim and Fill analysis. The results confirmed a low-intensity negative correlation between digital multitasking and academic

achievement with a weighted average correlation coefficient of r=−0.252 (fixed effects model) and r=−0.246 (random effects

model) and high heterogeneity (I² = 93.98%) among the studies, suggesting variability in the findings. The present meta-

analysis also revealed high heterogeneity among the studies, suggesting variability in the findings. This heterogeneity opens

avenues for exploring potential mediating relationships or covariates that impact why students engage in digital multitasking.

Keywords: academic media multitasking, academic achievement, GPA, media use, meta-analysis.

Kristina Cvetković

, Nataša Lazović

, Jelena Krulj

, Milena Vidosavljević

, Jelena Opsenica Kostić

University of Priština in Kosovska Mitrovica, Faculty of Philosophy, Department of Psychology, Serbia, e-mail: kristina.randjelovic@pr.ac.rs

State University of Novi Pazar, Department of Psychology, Serbia, e-mail: nlazovic@np.ac.rs

University of Priština in Kosovska Mitrovica, Teachers’ Training Faculty in Prizren - Leposavić, Serbia, e-mail: jelena.krulj@pr.ac.rs

Institute of Serbian Culture Priština – Leposavić, Serbia, e-mail: mika_vido_88@yahoo.com

University of Niš, Faculty of Philosophy, Department of Psychology, Serbia, e-mail: jelena.opsenica.kostic@filfak.ni.ac.rs

The Correlation Between Academic Media Multitasking and Achievement-a

Meta-Analysis

Introduction

The digital environment provides opportunities for communicating, accessing, creating, and

sharing an abundance of information effortlessly, quickly, and almost ubiquitously. The consequence of

having so many choices is divided attention: an individual constantly switches attention between different

types of information while performing various tasks – in other words, they perform multiple tasks simultane-

ously, or multitask. Although the term “multitasking” suggests that a person is doing multiple things at once,

what actually happens is a change of activity (Wagner, 2018). Therefore, multitasking in the true sense

refers to the ability to quickly switch attention from one activity to another (Kirschner and De Bruyckere,

2017). In psychological literature, the term media multitasking refers to behaviors such as using multiple

devices like smartphones, computers, and smart TVs simultaneously, managing numerous active applica-

tions and constant notifications that redirect attention between tasks (Baumgartner et al., 2014).

Current research predominantly investigates the adverse impacts of multitasking across three pri-

mary domains: cognition and academic performance, health outcomes, and interpersonal relationships (Za-

www.ijcrsee.com

Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

manzadeh and Rice, 2021). Multitasking in educational context, or academic media multitasking (Merrill,

2018; van der Schuur et al., 2020) is engaging with another media source or media technology while primar-

ily working on academic coursework, such as checking social media while doing homework (Yeykelis et al.,

2014). Multitasking in interpersonal context may be when we use mobile phone while we talk to our partner.

The results show that even the passive presence of a phone can reduce the sense of closeness, trust, and

empathy between conversation participants (Przybylski and Weinstein, 2013). In domen of health distrac-

tions such as mobile or other media can lead to increased food intake, poor dietary choices, and a higher

risk of obesity (Robinson and Matheson, 2015). The focus of our study is on academic media multitasking.

Adolescence and early adulthood is a period when digital media are frequently used during aca-

demic activities (Carrier et al., 2015; Junco and Cotten, 2012; Wallis, 2010), therefore, our study includes

research focused on populations of high school students and college students. Young people find it difficult

to distance themselves from their phones, which is supported by the fact that the smartphone is perceived

as an “extension of the body” with a strong sense of emotional attachment (Gertz et al., 2021). The phone

is always “at hand” during young people’s daily activities, including academic ones. Students often justify

device use for course-related tasks, while significant time is spent on non-course-related activities, impact-

ing focus and potentially leading to lower academic performance (Kraushaar and Novak 2010; Rosen et

al., 2013). The use of digital media is how adolescents and young adults mostly spend their time, on aver-

age more than 7.5 hours a day – which is almost equivalent to the length of a typical workday (Rideout et

al., 2010). Students and young adults increase their digital media absorption by using two or more media

simultaneously through multitasking, experiencing 10h and 45 minutes of media content within their 7.5

hours per day. This behavior also manifests in educational institutions, where the use of digital media is

largely uncontrolled and unregulated. If students do not invest enough time in completing academic tasks,

they will not fully utilize their potential (Fox et al., 2009). Researchers who have examined the relation-

ship between media use during academic activities and academic achievement assume that media use

during academic activities can lead to negative consequences for young people’s academic performance

(Bellur et al., 2015; Fox et al., 2009; Karpinski et al., 2013; Kokoç, 2021; Kostić and Ranđelović, 2022).

Several cognitive learning theories assume that using multiple streams of information reduces information

processing as a result of the limited cognitive capacity of humans (Salvucci and Taatgen, 2010; Junco and

Cotten, 2011). Cognitive theories related to information processing (Mayer, 1998) and multimedia learning

(Mayer and Moreno, 2003) highlight that “meaningful learning” happens when individuals are actively en-

gaged with information, concentrate on new inputs, and systematically integrate this new information into

their pre-existing knowledge structures. These theories indicate that multitasking, or frequently switching

between tasks, causes individuals to be only partially engaged with each task, leading to decreased atten-

tion and poorer learning and performance outcomes (Kraushaar and Novak, 2010). The cognitive control

deficit resulting from frequent digital media multitasking can also cause difficulties in maintaining focus on

academic tasks, leading to lower achievement (Ophir et al., 2009; Wallis, 2010). Frequent multitasking is

associated with a lower GPA (Bellur et al., 2015; Junco, 2012; Rosen et al., 2013; Walsh et al., 2013) since

the time spent using digital media takes away from time devoted to academic activities. Junco (2012) found

that overall GPA dropped 0.12 points for every 93 minutes above the average of 106 minutes per day spent

on Facebook. Ophir, Nass, and Wagner (2009) suggest that high media multitaskers have poorer cogni-

tive control abilities, meaning they have more difficulty managing attention and executive functions. This

reduced self-regulation capacity makes it harder for them to focus on tasks and learn effectively, which

can result in lower GPAs. Similar research by Rosen et al., (2013), indicates that frequent task-switching

caused by media distractions can diminish the quality of studying and negatively affect GPA. Lepp et

al., (2014) confirm that the use of mobile phones and other media can pose a significant distraction that

interferes with the learning process and lowers GPA. Additionally, Langberg et al. (2013) explore how self-

regulation impacts academic success and emphasize that students with better self-regulation skills can

more effectively manage distractions, including media multitasking, and achieve better academic results.

To avoid distractions and remain focused on learning, selective attention is crucial (Dayan and Solomon,

2010). Learners need to understand their attention state and employ effective strategies to regulate their

attention. If a student has a clear and specific goal and sufficient motivation, such as studying for an up-

coming exam, they are less likely to multitask and vice versa (Judd and Kennedy, 2011).

Although numerous studies confirm a negative correlation between media multitasking and aca-

demic achievement, some also report small to moderate effects (Burak, 2012; Junco and Cotten, 2012;

www.ijcrsee.com

Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

Ravizza et al., 2014), as well as no correlation (Karpinski et al., 2012; Wei et al., 2012; Clayson and Haley,

2013). This indicates a lack of consistency among researchers regarding the correlation between media

multitasking and academic achievement in high school and college students.

This topic is crucial because it provides empirical evidence on how digital distractions impact learn-

ing outcomes, helping educators and policymakers develop effective strategies to mitigate these effects

and enhance student performance in educational settings. Our study is a meta-analysis and attempts

to systematize the results of previous studies on the topic of the correlation between academic media

multitasking for non-academic purposes and student achievement. This approach aggregates data from

various studies to provide more robust conclusions, offering insights into the consistency and strength

of the association between media multitasking behaviors and academic outcomes that individual studies

alone may not achieve. A meta-analysis is important in this study because it allows for the comprehensive

integration of findings from multiple studies, increasing statistical power and generalizability. Even though

this field began developing more than a decade ago, the present times and unique environmental factors

during the pandemic greatly increased its significance.

Materials and Methods

Variable operationalization

Academic media multitasking – operationalized through a questionnaire measuring the frequen-

cy of digital media use (social networks, email, games, websites, search engines, watching/listening to

videos, talking on the phone) during academic activities, either in class or at home, for non-academic

purposes. The scales research authors identified as adequate measures of media multitasking were also

taken into consideration. These measure the use of various digital media during academic activities or as-

sess attitudes about being able to efficiently follow lessons/complete tasks while using some of the media

(e.g. social networks). The measures are intercomparable, and higher scores indicate greater frequency/

inclination for multitasking.

Academic achievement – operationalized as the current GPA, the semester average grade, the

average grade from the previous level of education (high school), or the average grade in compulsory

subjects. All measures are equivalent.

Inclusion and Exclusion Criteria

In order to be included in the meta-analysis, the research had to meet the following criteria:

1. It was published in a scientific journal with an impact factor (Clarivate JCR).

2. The publication language of the journal is English.

3. The study is not older than 2010 (statistical data indicate a continuous increase in the use of the

internet itself, as well as social networks at the end of the first decade of the 2000s, while Instagram,

the currently most popular social network, was founded in 2010).

4. The independent variable relates to the use of media multitasking.

5. Media multitasking refers to the use of digital tools in an educational context for non-academic purposes.

6. The study must report correlation coefficients between the variables or provide sufficient data to

calculate these coefficients. The correlation coefficient was chosen as the measure of effect size

because it was consistently reported across studies, allowing for a standardized comparison of the

relationship between media multitasking and academic achievement. This approach maintains the

internal and external validity of the meta-analysis by ensuring that the effect sizes are comparable

across different studies.

7. The dependent variable must be operationalized as an average grade (GPA or equivalent measure).

GPA is used due to its standardization and comparability across different educational contexts and

time periods, providing a reliable measure of academic performance. This decision helps maintain

both internal and external validity by ensuring that the measure of academic achievement is consist-

ent and comparable across all included studies.

After all the criteria were applied, 11 correlational studies were included in the final sample. The

table with the studies contained in the sample can be seen in Appendix A.

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Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

Data Extraction Process

The data extraction process involved systematically reviewing each included study to obtain the

necessary information for the meta-analysis. This comprehensive approach ensured that we had consist-

ent and comparable data across all studies, which is crucial for maintaining the validity and reliability of

the meta-analysis. For each study, we extracted detailed information including the study title, authors,

year of publication, and the journal in which the study was published. We also recorded the impact factor

(IF) of the journal to ensure the quality and credibility of the included studies. From the sample details,

we documented characteristics such as the type of participants (e.g., students, adolescents), along with

the sample size. Regarding the measures used, we extracted specific information on media multitask-

ing, including the types of digital media use (e.g., social networks, email, games) and the context of use

(e.g., during class or at home for non-academic purposes). Similarly, we noted the measures used to

assess academic achievement, such as current GPA, semester average grade, or average grade from

the previous level of education. Importantly, each study reported the effect size measure required for our

analysis in the form of correlation coefficients. This consistency eliminated the need to use other statistics

or perform additional calculations to derive these values. Each study provided a single relevant correla-

tion measure between media multitasking and academic achievement, so there was no need to merge

multiple effect sizes from individual studies.

Quality Assessment of Studies

The quality of the included studies was assessed using established criteria to evaluate risk of

bias and methodological rigor. This process involved a thorough review of each study’s research design,

data collection methods, and analysis techniques. To ensure a comprehensive and objective assessment,

multiple researchers independently evaluated each study. Each study was first evaluated for potential

sources of bias, including the selection of participants, measurement of variables, and control of con-

founding factors. Additionally, the methodological rigor of each study was assessed based on the clarity

of research questions, appropriateness of study design, and robustness of data collection and analysis

methods. The validity of the measures used for both media multitasking and academic achievement

were also considered. To enhance the reliability of the quality assessment, three researchers indepen-

dently coded each study. This involved assigning ratings for each criterion based on predefined scales.

The initial ratings were then compared to identify any discrepancies. In cases where discrepancies were

identified, researchers discussed the differences and reached a consensus on the final ratings. This qual-

ity assessment process ensured that the included studies were evaluated consistently and objectively,

enhancing the validity and reliability of the meta-analysis.

Literature search

To ensure systematic and transparent reporting, we followed the PRISMA (Preferred Reporting

Items for Systematic Reviews and Meta-Analyses) guidelines throughout the review process. These

guidelines provided a structured approach to conducting and reporting the meta-analysis, enhancing the

reproducibility and credibility of our findings.

The literature search was conducted via available internet databases for accessing scientific pub-

lications that do not require special permissions, and are widely used in the scientific community: Google

Scholar, ResearchGate, and ERIC. The keywords used in the search were: digital multitasking, digital

distraction, media multitasking, cyberloafing, academic achievement, academic performance, GPA. The

search was narrowed down to include only full-text articles published in 2010 and later. A review of the

studies included in the analysis is shown in Graph 1:

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Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

Graph 1. Search and selection of works for analysis

Statistical Analyses

Correlation coefficients were used as a measure of the effect size of individual studies and the

overall measure of effect size. There was no need for additional conversion of measures. The sample

size was used for weighting the effect size. The participants from the original studies differ in age, level

of education, country of origin, and potentially other covariates. Due to this, it is assumed that there is

no distribution of true effects, indicating that a random effects model would be suitable for calculating the

overall measure of effect size. Regarding the assessment of the existence of a “file drawer effect,” i.e.,

the bias of the effect size measure in published versus unpublished studies, a symmetry graph of the of

studies around the overall measure of effect size is shown, along with the results of the so-called Trim

and fill analysis. The software used for calculating individual and overall measures of effect size is the trial

version of Comprehensive Meta-Analysis.

Correlation coefficients were used as a measure of the effect size of individual studies and the

overall measure of effect size. As these coefficients were consistently reported across all studies, there

was no need for additional conversion of measures. The sample size of each study was used for weight-

ing the effect size, ensuring that larger studies had a proportionately greater impact on the overall results.

The participants from the original studies varied in age, level of education, country of origin, and other

potential covariates. Due to this heterogeneity, it was assumed that there is no single distribution of true

effects, indicating that a random effects model would be suitable for calculating the overall measure of

effect size. The random effects model accounts for variability both within and between studies, providing

a more generalized estimate of the effect size. Additionally, we assessed the potential existence of a “file

drawer effect,” which refers to the bias of effect size measures in published versus unpublished studies.

This was done using a symmetry graph (funnel plot) to visualize the distribution of studies around the

overall measure of effect size. The results of the Trim and Fill analysis were also presented to adjust for

potential publication bias. The software used for calculating individual and overall measures of effect size

was the Comprehensive Meta-Analysis (CMA). CMA provided the necessary tools for conducting both

fixed and random effects models, as well as additional analyses such as the Trim and Fill method for

assessing publication bias. By using both fixed and random effects models, weighted effect sizes based

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Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

on sample size, and following PRISMA guidelines, our analysis aimed to provide a robust and reliable

synthesis of the relationship between media multitasking and academic achievement.

Results

As for the heterogeneity of the effect size measure, considering the values of the Q statistic and its

statistical significance, the hypothesis of the existence of a fixed effect can be rejected. The results suggest

that 93.98% of the total variance can be attributed to heterogeneity – variance between individual studies

= 93.985). This result can be interpreted as very high heterogeneity (Huedo-Medina et al., 2006).

Table 1. Results of heterogeneity testing

Heterogeneity

Q df p I

166.241 10 .000 93.985

Q – significance indicator of heterogeneity; I2 – percentage of total variability that can be attributed to heterogeneity

Table 2. Random effects when calculating meta-statistics of correlation between media multitasking and aca-

demic achievement

Effect size Test of Null

N GG DG Z p

11 -.246 -.347 -.140 -4.465 .000

N – number of studies included in the analysis; - weighted average correlation coefficient; GG – upper limit; DG – lower limit

The results indicate that the overall measure of effect size differs from zero after applying the

random effects model (z= -4.465, p= 0.000), meaning there is a statistically significant negative correlation

between media multitasking and academic achievement.

File Drawer Effect

The existence of the file drawer effect was also examined. This refers to the bias of studies in-

cluded in the meta-analysis compared to those not included, which could have an impact on the overall

measure of effect size. The results indicated that the overall measure of effect size does not differ with

respect to the random and fixed effect model, therefore, the results are only shown for the random effects

model in Graph 2.

Graph 2. File drawer effect for the random effects model

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Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

Graph 2 shows the file drawer effect for the random effects model. The studies included in the

meta-analysis are represented by circles. They are evenly distributed around the vertical axis, and consid-

ering the fact that 11 studies were included in the analysis, a distribution of 6:5 can be considered equal.

Therefore, a bias in the selection of studies for analysis can be excluded based on this graph.

Discussion

This meta-analysis aimed to quantitatively integrate works and draw general conclusions about the

existence of a correlation between media multitasking and academic achievement. Media multitasking in

an academic environment has been the focus of researchers’ attention in recent years. This topic is gaining

significance with the increasing application of teaching in an online environment. The idea for the research

stemmed from a thorough review of the relevant literature and the observation of inconsistencies in the ob-

tained results. Among the numerous studies that confirm a negative correlation between media multitask-

ing and academic achievement, there are also those that report small to moderate effects or no correlation.

The results of this meta-analysis confirmed the existence of a negative correlation between academic

media multitasking and academic achievement, as indicated by the obtained meta-statistics, i.e., the average

weighted Pearson correlation coefficient. A low-intensity correlation was obtained. Most individual studies in-

cluded in the meta-analysis report a low negative correlation, hence these results are within the expected range.

Analyses have shown that over 93% of the total variance can be attributed to heterogeneity, i.e.,

variance between individual studies. Such a result confirms the justification for using a random or variable

effects model. Namely, when the I

statistic is of moderate or high intensity, there is a basis for further ex-

amination of the relationship between constructs, i.e., examining the impact of moderating variables that

can explain heterogeneity (Sánchez-Meca and Marin-Martinez, 2010). In the presented meta-analysis,

heterogeneity is very high, and this result indicates the need for further research. Given the results from

the funnel plot analysis, there is no indication of a significant file drawer effect in this meta-analysis. The

distribution of effect sizes appears relatively symmetric, suggesting that studies with both positive and

non-significant results were included in the analysis without substantial bias in the selection process. This

absence of a file drawer effect strengthens the validity of the findings and supports the robustness of the

conclusions drawn from the studies included in the meta-analysis. However, while the visual inspection

does not suggest a publication bias, it is important to note that the potential for undetected bias always

exists, and further statistical tests could be employed to confirm these observations.

Today’s adolescents have easy access to digital technology and often use it during other daily

activities, which is why they can be referred to as ‘multitaskers’ (Demirbilek and Talan, 2018). Our sample

consisted of research which included respondents in the early, middle, and late adolescence period, and

the results of the meta-analysis indicate that frequent use of technology during academic activities for

non-academic purposes is negatively correlated with academic achievement. The availability of technol-

ogy, such as smartphones, allows students to switch between tasks during lectures (Ralph et al., 2020).

Additionally, some students engage in multitasking to stay connected with friends or because they believe

it is an efficient way to handle multiple tasks (Kuznekoff and Titsworth, 2013). Multitasking can also serve

as a coping mechanism for boredom or stress during lectures (Wiradhany et al., 2021), while a lack of

self-regulation may contribute to increased multitasking (Ralph et al., 2020). Furthermore, social pressure

and the desire for interaction on social media can also play a role (Liu and Gu, 2019). It is widely known

that human cognitive capacities are limited, i.e., working memory inhibits the ability of humans to process

newly acquired information (Sweller, 1988). When media multitasking is intense or prolonged, it leads to

cognitive overload, which impairs message processing and triggers stress responses, ultimately harming

academic performance (Baumgartner and Wiradhany, 2021). Switching from one task to another or per-

forming multiple tasks during academic activities requires a change in focus, cognitive work, and attention

(Demirbilek, and Talan, 2018), which can explain the negative correlation with academic achievement.

Cognitive load increases due to frequent activity changes (Paivio, 1986), performance decreases as a

result of simultaneous activities (Junco and Cotten, 2012), and the completion of activities is delayed

(Bowman et al., 2010). Previous research suggests that attention problems in the academic context,

i.e., difficulties in directing and maintaining attention, may be at the core of multitasking, and can lead to

lower academic achievement (Ophir et al., 2009). Additionally, insufficient investment of time in complet-

ing academic tasks will result in decreased use of one’s potential (Fox et al., 2009). Other correlational

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Cvetković, K. et al. (2025). The Correlation Between Academic Media Multitasking and Achievement – a Meta-Analysis,

International Journal of Cognitive Research in Science, Engineering and Education(IJCRSEE), 13(1), 63-73.

research points to a small to moderate negative correlation between academic media multitasking and

achievement (e.g., Junco and Cotten, 2012; Ravizza et al., 2014).

Conclusion

When it comes to the construct of academic media multitasking, the existence of deviations in

operationalizations and instruments used in primary research prompted the author of this meta-analytic

study to rely on journal credibility, as well as on the subjective assessment of the adequacy of operation-

alization. Only the studies which met the set quality criteria were included in the analysis. Furthermore,

the analysis of bias in the selection of primary research showed that there is no file drawer effect. Studies

included in the analysis were published in leading scientific journals with a high impact factor, which is one

of the indicators of the quality of the study. On the one hand, the limitations of this study are reflected in

the small sample of primary research which were included in the meta-analysis process (N=11), although,

on the other hand, this can be viewed as an advantage due to appropriateness, quality, and credibility of

the data contained in the final selection of articles.

Given that this meta-analysis was conducted on a sample of correlational studies, causality can be

ruled out. Other explanations and possible confounding variables should also be considered. Although it

might seem less likely, poorer achievement can negatively affect the motivation to engage in academic

activities, which in turn promotes multitasking. However, despite the aforementioned limitations, this meta-

analytic study has primarily theoretical implications in terms of its contribution to a better understanding of

the phenomenon of academic media multitasking and academic achievement. The present meta-analysis

not only confirmed the value of previous studies, but also paved the way for exploring potential mediating

relationships or covariates affecting reasons why students engage in media multitasking. Future meta-

analytic studies dealing with the topic are recommended to consider the moderating impact of some other

variables from the domain of personality, self-regulation skills, and motivation.

Acknowledgements

This study was supported by the Ministry of Science, Technological Development and Innovations

of the Republic of Serbia (Contract No. 451-03-136/2025-03/200184). Part of the results of this research

was presented in the poster section at the 71

Congress of Psychologists of Serbia, May 2023.

Conflict of interests

The authors declare no conflict of interest.

Author Contributions

Conceptualization – K. C. and N. L.; Data Curation – M. V. and J. K.; Formal analysis – K. C. and

Jelena O. K.; Investigation – N. L. and J. K.; Methodology – J. O. K. and K. C.; Project Administration – K.

C. and N. L.; Visualization – J. K. and M. V.; Writing original draft – K. C. and N. L.; All authors have read

and agreed to the published version of the manuscript.

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Appendix A:

Table 1. The studies contained in the sample

Study Authors Year Journal IF Sample

Sample

size

Multitasking Achievement r

Bellur, S., Nowak, K.

L., & Hull, K. S.

2015

Computers in Human

Behavior

6.829 Students 361

Multitasking during homework

(Bellur, Nowak, & Hull, 2015)

High school GPA −.025

Karpinski, A. C.,

Kirschner, P. A., Ozer,

I., Mellott, J. A., &

Ochwo, P.

2013

Computers in Human

Behavior

6.829 Students 857

Multitasking with SNS while

studying (Karpinski, Kirschner,

Ozer, Mellott, & Ochwo, 2013)

GPA -0.28

3 Kokoç, M. 2021

Scandinavian Journal

of Psychology

2.25 Students 637

Multitasking with Social Media

(Ozer, 2014)

GPA –0.51

4 Lau, W. W. 2017

Computers in human

behavior

6.829 Students 348

Multitasking with Social Media

(Ozer, 2014)

GPA -0.092

Luo, J., Yeung, P. S.,

& Li, H.

2020

Children and Youth

Services Review

2.393

Adolescents

(12-18)

447

Media Multitasking Scale

(MMS) (Luo

et al. 2018)

Current average

grade for all school

subjects

−0.32

Raza, M. Y., Khan, A.

N., Khan, N. A., Ali, A.,

& Bano, S.

2020

Journal of Public

Affairs

1.08 Students 248

Media multitasking (Lau, 2017

adapted from Ozer’s, 2014)

GPA −0.57

7 Uzun, A. M., & Kilis, S 2019

Computers in Human

Behavior

6.829 Students 631

Sub-dimension Multitasking

Preference of the attitudes

subscales of MTUAS (Rosen

et al., 2013)

GPA -0.164

van der Schuur, W.

A., Baumgartner, S.

E., Sumter, S. R., &

Valkenburg, P. M

2020 New media & society 8.061

Adolescents

(11-15)

1215

AMM ( van der Schuur,

Baumgartner, Sumter &

Valkenburg, 2020) based on

the Media Multitasking Index

(MMI) developed by Ophir et

al. (2009).

Academic achieve-

ment scores

−.19

Wei, F. Y. F., Wang, Y.

K., & Klausner, M.

2012

Communication

Education

1.759 Students 190

Text messaging during class

(Wei & Wang, 2010)

AP, traditional aca-

demic performance

(grade-oriented

learning)

-0.056

Legkauskas, V.,

& Steponavičiūtė-

Kupčinskė, I.

2021

Education and

Information

Technologies

2.917

High school

students

319

In-class use of social media

(Legkauskas & Steponavičiūtė-

Kupčinskė, 2021)

GPA −0.353

Clayson, D. E., &

Haley, D. A.

2013

Journal of Marketing

Education

3.122 Students 298

General attitudes

toward texting ( Clayson &

Haley, 2013)

GPA −.025