DOI: 10.5061/dryad.nk98sf7rz
title: Data from social learning development, during COVID-19 how international students use media platforms as crowdsource technology to solve learning difficulties

description: This study lens cannot detach mobile-learning communication from efficient
 broadband, during social distance protocol, for continuous learning. The
 study aims to self-actualized knowledge-sourcing among individuals in an
 interconnected cluster of multi-community platforms. Crowdsource is
 characterized by a communication science perspective using mobile-learning
 in groups and/or clusters. Integrated TPB and Bandura’s Social Learning
 Theory (SLT) induced and investigated 361 respondents, stratified of
 students, teachers, and researchers during the COVID-19. The IBM Amos v.
 25 for the analysis found R² = 0.92 and (65.4, 34.6) for male and female
 demographic respectively. Results found significant direct and indirect
 Attitude, Self-learner usefulness, and crowdsource were positive to actual
 performance. Where broadband moderated on mobile learning behavior run-up
 significantly. Mobile learning mediation gives in magnificent interactive
 operation. Generally, crowdsource at the individual level enhanced
 collaborated problem-solving tasks pro-COVID-19. An Individual's
 sourcing knowledge is a creative task and timely routine learning in any
 critical period. Results suggested mobility of learning makes a mountain
 of molehills in knowledge interactivity among learners in groups.
 Therefore, encourages the clustering of network learning, easing learning,
 through effective broadband social intervention phenomena.
description: Participants The study population of
 students and teachers by induction of the SEM among foreigners in China,
 the participants were a cluster of foreigners in Mainland China. Due to
 the pandemic, they were lockdown however, needed to exchange knowledge
 from similar of different course areas, they multistage stratified into
 group platforms, pro-COVID-19 interconnected social learning based on
 different university campuses. Campus e-platforms were department and/or
 course-based, each group discussed and chatrooms network via mobile social
 learning exchanges of knowledge. Participants were connected via mobile
 learning as communication exception, therefore, mobile communication in
 the survey, selected social media platforms like; Tencent, WeChat, QQ, and
 Sino Weibo for the response due to commonly used in China. Using the
 stratified sampling technique to and fro students, teachers, and
 researchers (Patten et al., 2019), for the distributed 450 questions
 retrieved N=361 represented 80.2% of the respondent's rate, no
 recompense is given to avoid biases. All the
 respondence replied via online using the following; WeChat, WhatsApp, QQ
 and email. This study constructs were six with thirty items adapted from
 <i> </i>(Lin, Wang, Li, Shih, & Lin, 2016; Ho,
 Ocasio-Velázquez, & Booth, 2017). Some modifications were done to
 ensure questions suitable with crowdsourcing at the individual level. The
 constructs are; Attitude, Perceived Self-learner Usefulness, Peerceived
 Crowdsource, Broadband, Mobile Learning Behavior and Peformance
 Actualization. Each construct was measured with five or more using the
 5point Likert score from strongly agree to strongly disagree (1-5),
 respectively(Beglar & Nemoto, 2014). The reasons for more
 questions skewed were to blur off ‘halo effects,’ accurate measurement
 effects, and minimized leniency effects (Sharma & Misra, 2017). 
 These are often followed by advanced statistical analysis techniques and
 to adhered to ensure ethics responsible accuracy of data.
 Thes were coded into SPSSv.25 to sieve according to relaibility,
 correlation, and factor analyzed for CFA, the modifiied were extracted
 into Amos v. 24 for model fitness as well as estimations. The CFA went
 further to justify the structural equation model as presented in the
 paper. 
description: <strong><i>Overview
 study trend and questionnaires:</i></strong> Objectively, seeks to investigate
 students/learners respond inured in the interactive social learning nexus
 pro-COVID-19 communication crowdsourced technology in lockdown. Social
 learning in the media platforms among groups/clusters were explorative,
 behavioral developing learning communication as continuous knowledge
 sourcing mechanism. The questionnaires purposively survey international
 students in China universities during COVID-19. Achieving this, we use
 Perceived Crowdsource (PCS) integrated with Social Learning Theory
 Mediation of Mobile learning behaviors for actualizing performance. The
 researchers found major problem-solving tasks were resolved via mobile
 contents. The responses are expressed using the 5-point Likert scale,
 ranging from 1= "strong disagreed” to 5= “strong agreed”
 respectively. <strong><i>Constructs Measurements and descriptions:</i></strong> <i>Attitude </i>postulates a social learning human experience (behaviorism) to the scientific use of technology, the cognitive process juste milieu mobile learning. The forms and modelities learners always go through in technology.<i> </i>(Ajzen, Netemeyer, & Ryn, 1991<i>; </i>Schultze, U., 2002) I intend to use mobile learning anytime in the school environment. Using mobile learning eases retention and boredom during lockdown. Using mobile learning motivates my learning capacity. Mobile learning encourages my reading and discussion in chatrooms. I am always with my mobile device for information. I enjoy using mobile learning as I observed social distance protocol. <i>Perceived Self-learner Usefulness (PSLU) </i>is the learner’s belief that using the mobile device will enhance personal interactivity with learing in academic performance (knowledge-centered) <i> </i>(Venkatesh, Morris, Davis, & Davis, 2003<i>; </i> Bhattacherjee, A., Perols, J., & Sanford, 2008) Having access to my mobile inured continues knowledge-sourcing.  Mobile-learning is less difficult to search for information at fingertip. It’s easy using mobile to share questions and answers with colleagues. I effectively download learnable materials with a mobile device. Mobile-learning is companion and less stressful for reading during lockdown. <i>Perceived Crowdsourcing (PCS</i><b>) </b>is the belief that groups learning (crowd) association can source knowledge or exchange ideas in platforms discussions or  the internet.(Allen, B. J., Chandrasekaran, D., & Basuroy, 2018<b>; </b>Ho, Ocasio-Velázquez, & Booth, 2017) Crowd-based learning is network information sharing. Using mobile is easy to linkup crowd problem-solving. Mobile technology is individual based learning to solve a task. Community-based group discussions on mobile chat platforms is efficient. Teacher-learner discussed via mobile group chatting is helpful. Crowd internet content is easy way to access for knowledge. <i>Mobile Learning Behavior (MLB) </i>is the use of mobile smartphone for reading and learning anytime and anywhere.<i> </i>(Ibrahim, 2018<i>; </i>Lin, Wang, Li, Shih, & Lin, 2016) I always use a mobile device to record information and knowledge sourcing. I use mobile interactive to chat for learning outside class. I use mobile information to share knowledge with colleagues. Mobile network compliments my crowd problem-solving. Using mobile chatroom for idea exchanges is helpful learning. Mobile learning motivates group tasks discussions. Internet Broadband system (BBW) is the transmitter for effective userbility of mobile data. (Lin et al., 2016; Yan, 2019) Broadband fastens mobile internet surfing. Mobile broadband breaks edge easier than a computer. Mobile service quality is higher and user-friendly. Mobile data effectively ensure COVID-19 distance learning. The mobile system appeals to the user with effective broadband. <i>Behavior Intention Performance (BIP) </i>Behavior has a relationship with the intention of a user’s performance to influence learning in use of technology. (Ajzen et al., 1991<i>; </i>Bhattacherjee, A., Perols, J., & Sanford, 2008) I intend to use mobile learning for crowdsourcing tasks. In the future, I will continue to use a mobile device for knowledge assessment. Moving around with access to mobile facilitates my learning at any time. I will use mobile learning in solving my academic problems. Mobile learning makes reading simple and easier anywhere. I intend to link up with teachers and colleagues via a mobile smart tool.