Mobile Learning Usage of LIS Students in Mainland China

Abstract

This study aims to explore the usage behaviors of smartphones for learning purposes by Library and Information Science (LIS) students of mainland China. A quantitative questionnaire was used for collecting the subjects' usage behavior, their perceptions on learning experience through using smartphones, and their needs of accessing library services using smartphones. The authors analyzed the results from two major universities in mainland China. This research discovered that LIS students in mainland China used smartphones for their daily-life matters more readily than for learning purposes. They were also interested in accessing library services with smartphones, but not many of them were already using these services. The undergraduate and postgraduate respondents had some differences in their usage preferences and behaviors. This paper suspected those library services are already available but the promotion has been inadequate. There are obviously opportunities for educators, librarians, and technology providers to get some insights to improve mobile learning (m-learning) in universities and for students to learn better with mobile technology and apps. This study provides insights into the users' needs and the application of m-learning in mainland China, where scant similar studies have been conducted before.

Effect of Perceived Fear, Quality, and Self-Determination on Learners’ Retention Intention on MOOCs

“…For instance, Xuetang X, built by Tsinghua University, had 313 courses and 208,000 subscribers by September 2016. 60 , 61 Meanwhile, MOOCs have also gained universal attention in Chinese academic communities, especially with the rapid development and low-cost mobile technologies. 61 We applied a non-probability sampling technique, namely the accidental sampling in which respondents answered the questionnaire according to their availability and willingness.…”

“… 60 , 61 Meanwhile, MOOCs have also gained universal attention in Chinese academic communities, especially with the rapid development and low-cost mobile technologies. 61 We applied a non-probability sampling technique, namely the accidental sampling in which respondents answered the questionnaire according to their availability and willingness. 62 , 63 We selected this technique as it was quicker and easier to manage – compared to the other techniques that needed more resources (eg, technical resources, time).…”

“…For instance, Xuetang X, built by Tsinghua University, had 313 courses and 208,000 subscribers by September 2016. 60,61 61 We applied a non-probability sampling technique, namely the accidental sampling in which respondents answered the questionnaire according to their availability and willingness. 62,63 We selected this technique as it was quicker and easier to manage -compared to the other techniques that needed more resources (eg, technical resources, time).…”

Editorial: Advances in information and knowledge management

“…COVID-19 has seriously affected many educational institutions, libraries and museums (Fasae et al ., 2021; Huang et al ., 2021, 2022, 2023; Guo et al ., 2021; Meng et al ., 2023; Yu et al ., 2023), though we are now recovering (Abbass et al ., 2022; Suh and Alhaery, 2022; Kumar et al ., 2021). Various high-quality online information services have provided information access during the lockdown (Cheng et al ., 2022; Cheng, 2022; Ding et al ., 2021b; Hsieh et al ., 2023; Lo and Chiu, 2015; Lo et al ., 2015, 2017; Suen et al ., 2020; Sun et al ., 2022; Wang et al ., 2016; Wong and Chiu, 2023b; Fan and Liu, 2022; Zuo et al ., 2023; Wang et al ., 2022a,b; Wong et al ., 2023a), as supported by ubiquitous mobile Internet services, social media, apps and devices (Dukic et al ., 2015; Ezeamuzie et al , 2022; Fan et al ., 2020; Fung et al ., 2016; Gong et al ., 2017; Hui et al ., 2023; Lau et al ., 2017, 2020; Law et al ., 2019; Ni et al ., 2022; Yip et al ., 2021).…”

Editorial: Special selections on contemporary social media and social network research

“…Wide-spread and high-quality online information services have provided alternative sources during the lockdown (Ding et al , 2021; Hsieh et al , 2023; Lo and Chiu, 2015; Lo et al , 2015, 2017; Suen et al , 2020; Dong et al , 2021; Sun et al , 2022; Wang et al , 2016; Wong and Chiu, 2023; Fan and Liu, 2022; Zuo et al , 2023; Cheng et al , 2022; Cheng, 2022; Wang et al , 2022; Wong et al , 2023) and people have further changed their information and learning habits to digital, particularly for the newer generation (Chan et al , 2022; Chan et al , 2020; Dai and Chiu, 2023; Guo et al , 2022; Shahzad and Khan, 2022; Soroya and Faiola, 2023; Sung and Chiu, 2022; Yi and Chiu, 2023; Wai et al , 2018; Wong and Chiu, 2023; Yu et al , 2022; Zhang et al , 2021). Moreover, the pandemic has accelerated service transformation (Chan et al , 2022; Cheng et al , 2022; Chin and Chiu, 2023; Khan and Ayesha, 2022; Khan et al , 2022; Li et al , 2023; Li et al , 2023; Lin et al , 2022; Lo et al ., 2020; Noh, 2022; Nwagwu and Matobako, 2022; Tseng and Chiu, 2022; Tse et al , 2022; Yao et al , 2023; Wong and Chiu, 2023; Wu et al , 2022b, 2023; Xue et al , 2023), especially supported by ubiquitous mobile Internet services, social media, apps and devices (Dukic et al , 2015; Ezeamuzie et al , 2022; Fan et al , 2020; Fung et al , 2016; Gong et al , 2017; Hui et al , 2023; Lau et al , 2017, 2020; Law et al , 2019; Ni et al , 2022; Yip et al , 2021).…”