The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?

Strategies for enhancing Chinese students' engagement in a large class learning environment: An interpretative phenomenological approach

AIM

It is common for Chinese students to sit quietly during classroom lectures, attentively following teachers' instructions without interacting or asking questions, viewed as passive engagement. This study aims to understand further the passive engagement of Chinese students in relation to classroom questioning, just-in-time feedback and collaborative activities. With objectives to formulate strategies to enhance Chinese students' engagement in a large class learning environment without undermining the cultural dimension of "face".

BACKGROUND

Engaging in collaborative educational activities between teachers and students can be challenging in a large classroom learning environment. Within the Chinese context, Confucian-heritage culture may further exacerbate the challenges teachers face. Chinese students often appear passive when responding to questions. In this situation, educators may receive insufficient student feedback to modify and optimise their teaching and learning approaches.

DESIGN

A qualitative research method, with an interpretative phenomenological approach was employed in a self-financed institute of higher education in Hong Kong.

METHODS

Eight nursing graduates were invited to participate in two focus group interviews to generate teaching and learning strategies. In addition, individual in-depth interviews were conducted with twelve nursing teachers recruited through a snowballing sampling strategy. The narratives were coded, categorised, themed, analysed and interpreted through thematic analysis.

RESULTS

Chinese students are concerned with "losing face" and the fear of being teased by their peers in a collectivist culture. Based on these findings, three teaching and learning strategies for engaging students in classroom questioning and collaborative activities were generated. These strategies include using digital learning platforms, the promotion of communication and fostering interpersonal relationships.

CONCLUSIONS

In higher education, academic managers and teachers must critically reflect on teaching and learning strategies tailor-made to different cultural and contextual settings. Collaborating on pedagogical reforms can provide solid guidance and insight on implementing student-centred learning for Chinese students in large class learning environments while respecting the cultural dimension of "face".

Determining multidimensional influences of network heterogeneity on university students' psychological and academic well-being: The mediating role of social network exhaustion

Mobile social media has become indispensable to university students' communication with various socio-demographic populations, exposing them to diverse social networks and augmenting their network heterogeneity. Although the psychological ramifications of network heterogeneity have been extensively examined, its correlated academic outcomes remain inconclusive. The current study formulated an integrated theoretical research model based on the stressor-stress-outcome framework to investigate the influence of factors associated with network heterogeneity (specifically, privacy invasion, social comparison, self-presentation, and excessive WeChat use) on social media exhaustion, psychological well-being, and academic well-being among university students. Furthermore, the research examined the mediating effect of social network exhaustion among network heterogeneity, psychological well-being, and academic well-being. A cross-sectional survey of 1128 WeChat users revealed that social comparison and excessive WeChat use had positive associations with social network exhaustion, while privacy invasion and self-presentation were negatively correlated with social network exhaustion. Additionally, social network exhaustion was negatively correlated with psychological well-being and academic well-being. Furthermore, social network exhaustion mediated the influences of network heterogeneity on psychological well-being and academic well-being. These obtained results could contribute to a more nuanced understanding of the underlying causes of social network exhaustion and the multifaceted effects of network heterogeneity. These insights may prove valuable for practitioners to enhance university students' psychological states and academic performance in the contemporary mobile media-saturated environment.

Perceived Information Overload and Intention to Discontinue Use of Short-Form Video: The Mediating Roles of Cognitive and Psychological Factors

The current study investigated the effects of Chinese young adult users' perceived information overload (i.e., the daily perception of exposure to excessive information) on their intention to stop using short-form video applications. Specifically, this study accomplished this by measuring the direct and indirect effects of social media fatigue, maladaptive coping, and life dissatisfaction in relation to users' intention to discontinue their use of short-form video applications. The data were collected using a web-based survey and validated questionnaire, with a sample of 340 young adult (18-26 years old) respondents. The results indicated that perceived information overload had a direct effect on the intention to discontinue the use of short-form video applications. Moreover, short-form video fatigue, maladaptive coping, and life dissatisfaction all played mediating roles in the relationship between perceived information overload and the intention to discontinue the use of short-form video applications among young adults in China.

Technology-Enhanced Learning and Well-being: a Contribution to the Validation of a Measure to Assess University Students' Technostress in the Italian Context

COVID-19 has forced many universities to adopt widely technology-enhanced learning (TEL), highlighting the role of technostress as a risk factor for detrimental outcomes that may be prevented through the assessment with reliable tools. Thus, the present study aimed to test the psychometric characteristics of the Italian validation of the technostress scale by Wang, Tan, and Li. A self-report online questionnaire was completed by 915 participants (aged 18-33 years) attending an online university course during the health emergency. A subsample of 301 subjects (M Age = 20.91, SD = 1.93) filled out the same questionnaire after a 3-month time interval to evaluate the test-retest reliability. Confirmatory factor analysis verified the one-factor structure of the scale, which was confirmed across academic courses considered (first-year and senior students). Moreover, the findings showed significant associations with the Italian Technostress Creators Scale and the Italian Mental Health Continuum-Short Form, as well as a satisfactory test-retest coefficient value supporting its validity and reliability. In light of the above, the study provides a useful instrument to evaluate technostress related to TEL and indications to implement preventive interventions for this type of stress by improving students' experience with learning technologies.

Effect of social media overload on college students’ academic performance under the COVID-19 quarantine

Features and relevant services of online social media have been attracting users during the COVID-19 pandemic. Previous studies have shown that college students tend to use social media more frequently than other groups. However, in being affected by social media overload, the social media use behaviors of many college students have been out of their control in terms of their capabilities or cognition. Based on the stressor–strain–outcome (SSO) model and the theory of compensatory internet use (TCIU), we developed a research model to study the causes of social media overload and its impact on college students’ academic performance during the COVID-19 pandemic. A total of 441 valid responses from college students through questionnaires in China are collected via purposive sampling and used in the data analysis. This study conducts PLS-SEM to analyze collected data, finding that boredom proneness is associated with overload (stress), which has a bearing on social media overload (strain) and the reduction in final performance (outcome). Through illustrating the psychological and behavioral conditions that hinder the academic performance of students, this study provides deeper insights into students’ uncontrollable use of social media. Moreover, with respect to the identified antecedents, this study aims to find solutions to mitigate the impact of social media overload resulting from boredom proneness on the academic performance of college students.

The Role of Quality Measurements in Enhancing the Usability of Mobile Learning Applications during COVID-19

Despite numerous studies offering some evidence about the significance of quality measurements in enhancing the success of m-learning applications, there are still limited studies about the role of quality measurements in promoting the usability of mobile learning systems. Therefore, our study explores the role of quality measurements in promoting the usability of m-learning systems during COVID-19. The results revealed that the service quality, information quality and system quality are the most important factors affecting mobile learning usability among learners during COVID-19. Moreover, these findings are valuable for classifying the significance of these quality elements, which provide guidance on assigning quality aspects to improve this mobile learning usage during COVID-19 in higher education institutions.

Dataset of international students' acceptance of online distance learning during COVID-19 pandemic: A preliminary investigation

The dataset describes factors affecting international students’ acceptance of Online Distance Learning (ODL) mode while pursuing oversea education during COVID-19 pandemic. The recruited respondents comprised of international students who were pursuing undergraduate degree programmes in the institutions of higher learning (IHLs) in Malaysia. Respondents were invited to participate in an online survey via Google Forms. A purposive sampling technique was adopted in this research whereby a total of 207 valid questionnaires were obtained and used for data analysis. Data outputs such as respondents’ profile, Partial Least Squares Structural Equation Modelling, and importance-performance matrix analysis were presented. The data can be used as a reference source to identify areas of improvement by educators, academic management, and policy makers of IHLs.

Smart Mobile Learning Success Model for Higher Educational Institutions in the Context of the COVID-19 Pandemic

Smart mobile learning (M-learning) applications have shown several new benefits for higher educational institutions during the COVID-19 pandemic, during which such applications were used to support distance learning. Therefore, this study aims to examine the most important drivers influencing the adoption of M-learning by using the technology acceptance model (TAM). The structural equation modelling (SEM) method was used to test the hypotheses in the proposed model. Data were collected via online questionnaires from 520 undergraduate and postgraduate students at four universities in Saudi Arabia. Partial least squares (PLS)–SEM was used to analyse the data. The findings indicated that M-learning acceptance is influenced by three main factors, namely, awareness, IT infrastructure (ITI), and top management support. This research contributes to the body of knowledge on M-learning acceptance practices. Likewise, it may help to facilitate and promote the acceptance of M-learning among students in Saudi universities.

Facebook/Meta usage in higher education: A deep learning-based dual-stage SEM-ANN analysis

The paper's main aim is to investigate and predict major factors in students' behavioral intentions toward academic use of Facebook/Meta as a virtual classroom, taking into account its adoption level, purpose, and education usage. In contrast to earlier social network research, this one utilized a novel technique that comprised a two-phase analysis and an upcoming the Artificial Neural Network (ANN) analysis approach known as deep learning was engaged to sort out relatively significant predictors acquired from Structural Equation Modeling (SEM). This study has confirmed that perceived task-technology fit is the most affirmative and meaningful effect on Facebook/Meta usage in higher education. Moreover, facilitating conditions, collaboration, subjective norms, and perceived ease of use has strong influence on Facebook usage in higher education. The study's findings can be utilized to improve the usage of social media tools for teaching and learning, such as Facebook/Meta. There is a discussion of both theoretical and practical implications.

Mobile Learning Acceptance Post Pandemic: A Behavioural Shift among Engineering Undergraduates

Mobile learning has become an essential telematic tool to facilitate and compliment online teaching and learning during the pandemic. This study investigates the change of behaviour and acceptance of using mobile learning specifically for engineering undergraduates due to this shift. The data collected pre-Covid19 (n = 326) and post-pandemic (n = 349) indicated an inclination for utilizing laptops than smartphones, while Telegram prevails as a popular tool for communicating and sharing information within the learning community. Next, while video conferencing tools and online learning management systems utilization increased, educational games and reading behaviour via mobile devices declined. Concurrently, behavioural intention post-pandemic were found to reduce marginally as importance were also given towards establishing learning communities via social influence compared to perceived usefulness. The outcome of this study contributes to the limited body of literature on engineering education mobile learning acceptance, and recommendations are provided for further investigation to ensure continuous sustainable use.