Do Students Really Use Internet Access for Learning in the Classroom?: Exploring Students’ Cyberslacking in an Indonesian University

Simanjuntak, Ermida; Nawangsari, Nur Ainy Fardana; Ardi, Rahkman

doi:10.3390/bs9120123

Cited by 15 publications

(15 citation statements)

References 34 publications

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“…Smartphones have become extensively used in our daily lives as smartphone technologies have advanced, making our lives more comfortable. Technostress (Upadhyaya, 2021 ; Wang et al, 2020 ; Qi, 2019 ), problematic smartphone use (Forster et al, 2021 ; Romero-Rodríguez et al, 2020 ; Pereira et al, 2020 ; Eichenberg et al, 2019 ; Wang et al, 2015 ), smartphone addiction, nomophobia (Essel et al, 2021 ; Márquez-Hernández et al, 2020 ; Moreno-Guerrero et al, 2020; Bartwal & Nathan, 2020 ; Jilisha et al, 2019 ; Aguilera-Manrique et al, 2018 ), cyberbullying (Abaido, 2020 ; Chan et al, 2020 ; Wang et al, 2019 ; Peled, 2019 ), and cyberslacking (Sharma, 2020 ; Simanjuntak et al, 2019 ; Rana et al, 2019 ) have all emerged due to the widespread use of smartphones. This study aimed to determine the nomophobic behaviours, the anxiety of being without mobile phone contact (SecurEnvoy, 2012), and variables influencing the nomophobia levels of preservice teachers in five Ghanaian colleges of education.…”

Section: Discussion Limitations and Recommendationsmentioning

confidence: 99%

Nomophobia among Preservice Teachers: a descriptive correlational study at Ghanaian Colleges of Education

et al. 2022

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The present study aimed at investigating nomophobia prevalence, thus, recurrence of anxiety without a smartphone, with preservice teachers in the Colleges of Education, Ghana. An actual sample of 345 preservice teachers responded to a 20-item questionnaire on nomophobia (NMP-Q). A one-way MANOVA between different groups statistics was applied in determining the differences in nomophobic behaviours among preservice teachers based on non-technology-related variables (gender, age, specialism, subjective economic status, sleep/rest hours, and religion) and technology-related variables (number of smartphones owned, smartphone ownership duration, active internet services, and daily internet usage time). The results evidenced that the vast majority of preservice teachers had mild to severe nomophobia, and their most significant anxiety was related to access to information and communication. Besides, non-technology-related variables in gender, sleep hours, and subjective economic status significantly impacted the preservice teachers’ nomophobia. Technology-related variables that significantly influenced the nomophobic behaviour of preservice teachers included the number of smartphones owned, smartphone ownership duration, and active internet service. A sizable majority of the preservice teachers showed signs of mild to severe nomophobia. The present study provides prefatory support for the prevalence of nomophobia among the Ghanaian preservice teachers.

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Section: Discussion Limitations and Recommendationsmentioning

confidence: 99%

Nomophobia among Preservice Teachers: a descriptive correlational study at Ghanaian Colleges of Education

et al. 2022

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“…A student who has both the skills and ability to engage in multitasking using technology will tend to multitask in social media during online classes. According to Simanjuntak, Nawangsari and Ardi [25], students as "digital natives" perceive the fact that their existing technical skills allow them to access the internet while simultaneously doing online classes. This self-perception is not always true since students tend to overestimate their own capacity and show over-confidence which might lead to cyberslacking.…”

Section: Media Multitasking Efficacy and Cyberslackingmentioning

confidence: 99%

Understanding cyberslacking intention during Covid-19 online classes: An fsQCA analysis

Mumu¹,

Connolly²,

Azad³

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Due to the Covid-19 pandemic, students have been restricted to their homes and forced to take online classes as an alternative to in-person classes. However, data shows that this enforced online education is resulting in a learning deficit for a generation of students and that many engage in cyberslacking behavior, which is the use of non-work-related internet use during designated work time. The cyberslacking tendency among university students in particular is on the rise.This study employed a fuzzy-set qualitative comparative analysis (fsQCA) along with sentiment analysis using Natural Language Processing (NLP). Findings show five core factors that underpin cyberslacking attention. Alternative paths have been identified based on gender and the students' current education status. The study findings contain a number of contributions, illustrating the different topology of student intention towards cyberslacking and identifying causal factors that influence cyberslacking intention, as well as illustrating student sentiment regarding this behavior.

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“…32,36,58 In the context of members of the digital generation, or millennials, students are considered to have high confidence in their ability to run several media or non-media activities simultaneously. 25,30,59 This seems to be related to their exposure to various forms of media and technology since early childhood, commonly experienced by members of the digital generation. [59][60][61] These experiences are quite intense, regarding the media multitasking which forms the strong confidence of students that they are capable of performing media multitasking.…”

Section: Social Cognition Theory (Sct) and Online Behaviormentioning

confidence: 99%

“…9,30,36 Students with high confidence on their ability to perform media multitasking have the potential to indulge in academic cyberslacking during class time. 24,25,30,57 Their confidence regarding their skills in media multitasking is observable from their behavior when being present in the class, but at the same time also accessing the internet, chatting with friends, opening social media, or reading news unrelated to the course in progress. 12,24,30,57 A study by Wu 30 found that students with high levels of media multitasking self-efficacy would consider themselves able to perform learning activities well, even though they also simultaneously open social media, such as Facebook, and chat with friends.…”

Section: Social Cognition Theory (Sct) and Online Behaviormentioning

confidence: 99%

“…37,48,63 Self-regulation should prevent students engaging in improper access to social media, resulting in their control of the behavior of social media engagement. 25,48,63 A study conducted by Khang et al, 63 with 603 subjects who were active users of social media, indicated that self-regulation played an important role in individual social engagement with social media. Individuals who were incapable of good selfregulation had difficulties in controlling their engagement with social media.…”

Section: Self-regulation and The Students' Social Media Engagementmentioning

confidence: 99%

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Academic Cyberslacking: Why Do Students Engage in Non-Academic Internet Access During Lectures?

Simanjuntak¹,

Nawangsari²,

Ardi³

2022

PRBM

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Introduction: University students, as members of the digital generation, often access the internet for non-academic purposes while attending lectures in the classroom. Internet access for non-academic purposes during lectures is known as academic cyberslacking. This study aims to test the effects of media multitasking, self-efficacy, self-regulation, social media engagement, and Attention, Relevance, Confidence, and Satisfaction (ARCS) motivation, on the engagement in academic cyberslacking by university students. Methods: The participants were 1485 university students, who had previously engaged in academic cyberslacking during lectures. The research instruments in this study were an academic cyberslacking scale, a media multitasking self-efficacy scale, a self-regulation scale, a social media engagement scale, and an ARCS motivation scale. The research model and hypotheses are tested using structural equation model (SEM) by Lisrel. Confirmatory factor analysis (CFA) is also used to analyze all the instruments. The respondents' demographic data were analyzed using SPSS. Results:The results showed that it is only media multitasking self-efficacy and social media engagement which have any significant effects regarding academic cyberslacking. Self-regulation and ARCS motivation do not have direct association with academic cyberslacking. Conclusion:Students do academic cyberslacking during lectures. Media multitasking self-efficacy and social media engagement can predict students' academic cyberslacking. It is recommended that students direct their involvement in the digital environment to more constructive efforts during lectures.

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Do Students Really Use Internet Access for Learning in the Classroom?: Exploring Students’ Cyberslacking in an Indonesian University

Cited by 15 publications

References 34 publications

Nomophobia among Preservice Teachers: a descriptive correlational study at Ghanaian Colleges of Education

Nomophobia among Preservice Teachers: a descriptive correlational study at Ghanaian Colleges of Education

Understanding cyberslacking intention during Covid-19 online classes: An fsQCA analysis

Academic Cyberslacking: Why Do Students Engage in Non-Academic Internet Access During Lectures?

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