Validation of the diagnostic tool for assessing<i>Tertiary students’ readiness for online learning</i>

Pillay, Hitendra; Irving, Kym; Tones, Megan

doi:10.1080/07294360701310821

Cited by 94 publications

(44 citation statements)

References 24 publications

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“…The following scales were integrated into the survey with sometimes small changes due to the context of distance education and language issues. These included cooperative and learning preferences (Owen & Stratton, 1982); Tertiary Student's Readiness for Online Learning (TSROL) (Pillay et al, 2007), social software expertise (inspired from Pillay et al, 2007); Distance study self-efficacy scale (DSSES, Poellhuber, 2007). In order to measure the predispositions of distance students towards collaboration vs individual learning, we adapted the Learning Preferences Scale for students from Owens & Stratton (1980).…”

Section: Methodsmentioning

confidence: 99%

Distance students' readiness for and interest in collaboration and social media

Poëllhuber

Anderson

Racette

et al. 2013

Interactive Technology and Smart Education

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Social media and social networking tools offer new educational affordances and avenues for students to interact, that may alleviate the drop-out rate problem faced by distance education institutions (Rovai, 2003). However, we know little about distance students' expertise with social media or their interest in using them to learn individually or to collaborate with peers.To investigate these issues, an online questionnaire was distributed to students from four large Canadian distance education institutions. A systematic sampling procedure lead to 3462 completed questionnaires. The results show that students have diverse views and experiences, but they also show strong and significant age and gender differences in a variety of measures, as well as an important institution effect for interest in collaboration. Males and younger students score higher on almost all indicators, including cooperative preferences. In this article we review quantitative results from the survey from earlier work (authors, 2011) and present an analysis of the qualitative data gathered from open-ended questions in the survey. Answers to open-ended questions regarding the expectation and interest in using social software in their courses, show that students have positive expectations about interactions and course quality, but also concerns about technical, time, and efficiency issues The limits of the study and future developments and research questions are outlined.

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Section: Methodsmentioning

confidence: 99%

Distance students' readiness for and interest in collaboration and social media

Poëllhuber

Anderson

Racette

et al. 2013

Interactive Technology and Smart Education

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show abstract

“…E-readiness measures have been widely researched, from Australia (Pillay et al 2007), Hong Kong (So and Swatman 2010), Indonesia (Purnomo and Lee 2010), Iran (Darab and Montazer 2011), Malaysia (Kaur and Abas 2004), Nigeria (Ditimi and Ayanda 2013), Taiwan (Hung et al 2014;Zhang and Hung 2009), Turkey (Aydin and Tasci 2005), to UK (Lou and Goulding 2010), and USA (Linos 2014;Maugis et al 2005;The World Bank 2005;Watkins et al 2004). E-readiness is a key component in health (Schreurs et al 2008), agriculture (Purnomo and Lee 2010), industrial organizations (Aydin and Tasci 2005), and the design of online learning environments (Holsapple and LeePost 2006;Keramati et al 2011;So and Swatman 2010;Yadollahi et al 2013).…”

Section: E-readiness Researchmentioning

confidence: 99%

“…It relates to expertise, the organizational culture, administrative instructions, and rules in the online environment (Keramati et al 2011). Self-managed learning and good time management skills represent important characteristics that may An assessment of online instructor e-learning readiness… predict an e-ready online instructor (Loomis 2000;Pillay et al 2007). Lifestyle readiness factors assess whether online instructors have a suitable location that could be used for extended periods to dedicate to their online tasks, have uninterrupted time that they could dedicate to their online courses, routinely communicate with other online users using electronic technologies such as e-mail, have persons or resources nearby who could assist with any technical or software problems, and their value of and need for flexibility which the online environment affords (Holsapple and Lee-Post 2006).…”

Section: E-readiness Factorsmentioning

confidence: 99%

An assessment of online instructor e-learning readiness before, during, and after course delivery

2016

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Online instructors in higher education play a key role in the success or failure of electronic learning systems (ELSs). Their expertise in and use of technology tools in ELSs influence the quality of information presented, their system use and satisfaction during course delivery. This study adapted Holsapple and LeePost's (Decis Sci J Innov Educ 4(1): [67][68][69][70][71][72][73][74][75][76][77][78][79][80][81][82][83][84][85] 2006) model to examine online instructor e-learning readiness (e-readiness) at the online campus of a Caribbean university, and to assess their levels of e-readiness and impact before, during and after course delivery. Responses from 208 online instructors were analysed from an online survey. Results show that while the cohort was 90.6 % e-ready, only 72.6 % were individually e-ready by having access to a dedicated network connection for substantial periods of time, routinely communicating with persons using electronic technologies, being self-motivated and independent learners, with a predisposition towards embracing and using new technologies. During the pre-course phase, online instructor e-readiness had a moderate impact on both technical (ELS quality and service quality) and non-technical (information quality) aspects of the ELS. During course delivery, its influence decreased with the technical aspect (ELS use) but increased with the non-technical aspect of the course (instructor satisfaction). At course completion, the main benefit was enhanced teaching skills while lack of contact with others was the main challenge. The results could be used to identify characteristics of online instructors suitable for the online environment, monitor their impact during the phases of a course, and serve as a benchmark for comparing levels of e-readiness across institutions.

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“…Although there are many potential benefits of learning via online platforms such as the availability and tracking of learning, prompt feedback and time management (Bradford, Porciello, Balkon, & Backus, 2007), there has been little research into using video technology in teaching practice to bridge the gap between online and on-campus provision of practical PE classes. Bridging the gap between online and on-campus classes is important to enhance students' satisfaction with online learning (Pillay, Irving, & Tones, 2007). Whilst technology is often used to complement and improve teaching effectiveness during the delivery of PE lessons (Juniu, 2011), this investigation was innovative by bringing all the elements of face-to-face classes to those learning practical PE content online.…”

Section: Discussionmentioning

confidence: 99%

A Simulation Pedagogical Approach to Engaging Generalist Pre-service Teachers in Physical Education Online: The GoPro Trial 1.0

Hyndman

2017

AJTE

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Validation of the diagnostic tool for assessingTertiary students’ readiness for online learning

Cited by 94 publications

References 24 publications

Distance students' readiness for and interest in collaboration and social media

Distance students' readiness for and interest in collaboration and social media

An assessment of online instructor e-learning readiness before, during, and after course delivery

A Simulation Pedagogical Approach to Engaging Generalist Pre-service Teachers in Physical Education Online: The GoPro Trial 1.0

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