Effects of Personal Characteristics on Learner Online Learning Readiness

Nowadays many educational institutions have embraced online education to cater for flexible and student-centered learning. Through online education, students have an opportunity to gain an education at their own convenience, in terms of time and place. However, it is argued that students are less satisfied with online learning than with traditional classroom learning. As online education continues to expand, the need for determining and maintaining quality online education is becoming an important issue. Therefore, it is important to discern which qualities are necessary for students‘ achievement and satisfaction in an online learning environment (OLE). While numerous studies on the qualities of online learners have been conducted, the factors that contribute to success in OLEs have not been adequately described. Therefore, it is important to examine learner characteristics to see their effects on student success in an online environment, which in turn facilitates high quality of online learning. This paper reports on what and how personal characteristics significantly affect students‘ online learning readiness at Curtin University of Technology, Sarawak Malaysia. Natural sampling was used to identify the sample and the study sample consisted of 350 voluntary participants. Quantitative method was used to collect relevant data in this study. A questionnaire was developed to gather data on learner personal characteristics, and a diagnostic tool, Tertiary Students‘ Readiness for Online Learning (TSROL), developed by Hitendra Pillay, Kym Irving and Megan Tones was adopted to assess learner online learning readiness. The TSROL has 20 items grouped into four factors: Technical skills (TS), Computer self-efficacy (CS-E), Learning preferences (LP) and Attitudes towards computers (AC). Moreover, confirmatory data analysis was adopted in this study. A one- way analysis of variance (ANOVA) was used to determine if there were significant differences in online learning readiness across the personal characteristics. The statistical results validate that some personal characteristics significantly affect learners‘ online learning readiness

The Learner Readiness for Online Learning: Scale Development and University Students’ Perceptions

The purpose of this study was to determine university students’ readiness for online learning. Mainly due to the study a multidimensional instrument for university students’ readiness for online learning (ROLS) developed and validated. The study adopted qualitative research method based on quantitative data. The participants of the study comprised 297 university students who were selected using randomly sampling model. The data were collected via readiness for online learning scale (ROLS) and analyzed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to establish the construct validity of the ROLS model. In addition, a series of one-way ANOVA were conducted to investigate the effect of demographic variables on readiness of online learning. Through confirmatory factor analysis, ROLS was validated in two dimensions: computer literacy (CL) and computer based selfconfidence (CSC). The results revealed that students’ levels of readiness were high in computer literacy and computer based self-confidence. In the study it was also found out that perception of students’ self-confidence while using computer caused significant statistical differences in two dimensions; the students who had higher level (very good, good) of selfconfident perception while using computer students exhibited significantly greater readiness in the dimensions of CL and CSC than those who had lower level of self-confident perception. There was no statistical difference in the two dimensions of ROLS in terms of gender, and the participant students at Faculties of Education had similar levels in all readiness dimensions than the other participants in other faculties

By design : negotiating flexible learning in the built environment discipline

The term ‘flexible education’ is now firmly entrenched within Australian higher education discourse, yet the term is a contested one imbued with a multiplicity of meanings. This paper describes a process designed to elucidate how the idea of flexible education can be translated into teaching models that are informed by the specific demands of disciplinary contexts. The process uses a flexible learning ‘matching’ tool to articulate the understandings and preferences of students and academics of the Built Environment to bridge the gap between student expectations of flexibility and their teacher’s willingness and ability to provide that flexibility within the limits of the pedagogical context and teaching resources. The findings suggest an informed starting point for educators in the Built Environment and other creative disciplines from which to traverse the complexities inherent in negotiating flexibility in an increasingly digital world

Health and Physical Education and the Online Tertiary Environment at Two Universities: Pre-service Teachers’ Perceived ‘Readiness’ to Teach HPE

In recent years in tertiary institutions in Australia, there has been a large increase of enrolments in Education courses delivered via an online/external mode. This has raised a number of concerns around the nexus of theory and practice and whether pre-service teachers feel ready to teach after completing Education study online. The purpose of this study is to examine pre-service teachers’ perceived readiness to teach Health and Physical Education (HPE) after engaging with the subject fully in an online tertiary environment. 26 pre-service teachers studying education online from two separate were involved in this study. Upon completion of the University semester and also after a practicum placement, qualitative data was collected detailing the pre-service teachers’ perceptions in regard to their readiness to teach HPE. Pre-service teachers’ perceptions are used as the primary data highlighting the varying levels of readiness to teach HPE

Australian tertiary learning and teaching scholarship and research 2007-2012

Research into Higher Education is strongly supported in Australia by journals and conferences. Teaching and learning awards, projects and programmes in Australia have gained a significantly larger profile over the last five years thanks, in part, to an imaginative and supportive environment fostered by the federal government through the Australian Learning and Teaching Council (ALTC) and now the Office for Learning and Teaching (OLT)

Examining the reliability and validity of a Mongolian version of the student online learning readiness instrument using exploratory and confirmatory factor analysis

This study examines the reliability and validity of a Mongolian version of the Student Online Learning Readiness (SOLR) instrument in the Mongolian context. The instrument consists of 20 items used to evaluate technical competencies, social competencies with instructor, social competencies with classmates, and communication competencies. One thousand seven hundred and eight-six undergraduate students at the National University of Mongolia in Ulaanbaatar, Mongolia, participated in this study. Data were randomly split into two groups. The four-factor structure of the SOLR instrument explained 69.355% of the variance in the pattern of relationships among the items in the first half-sample. All four competencies had high reliabilities (all Cronbach’s alpha values were .84 or higher). The validity of the four-factor structure of the Mongolian-language version of the SOLR model was confirmed with the deletion of one item that cross-loaded on multiple factors. Confirmatory factor analysis confirmed the validity of the hypothesised model of the 19-item structure of the Mongolian-language version of the SOLR instrument using the second half-sample

Psychometric properties of implementation measures for public health and community settings and mapping of constructs against the Consolidated Framework for Implementation Research: a systematic review

Background: Recent reviews have synthesised the psychometric properties of measures developed to examine implementation science constructs in healthcare and mental health settings. However, no reviews have focussed primarily on the properties of measures developed to assess innovations in public health and community settings. This review identified quantitative measures developed in public health and community settings, examined their psychometric properties, and described how the domains of each measure align with the five domains and 37 constructs of the Consolidated Framework for Implementation Research (CFIR). Methods: MEDLINE, PsycINFO, EMBASE, and CINAHL were searched to identify publications describing the development of measures to assess implementation science constructs in public health and community settings. The psychometric properties of each measure were assessed against recommended criteria for validity (face/content, construct, criterion), reliability (internal consistency, test-retest), responsiveness, acceptability, feasibility, and revalidation and cross-cultural adaptation. Relevant domains were mapped against implementation constructs defined by the CFIR. Results: Fifty-one measures met the inclusion criteria. The majority of these were developed in schools, universities, or colleges and other workplaces or organisations. Overall, most measures did not adequately assess or report psychometric properties. Forty-six percent of measures using exploratory factor analysis reported >50 % of variance was explained by the final model; none of the measures assessed using confirmatory factor analysis reported root mean square error of approximation (<0.06) or comparative fit index (>0.95). Fifty percent of measures reported Cronbach’s alpha of <0.70 for at least one domain; 6 % adequately assessed test-retest reliability; 16 % of measures adequately assessed criterion validity (i.e. known-groups); 2 % adequately assessed convergent validity (r > 0.40). Twenty-five percent of measures reported revalidation or cross-cultural validation. The CFIR constructs most frequently assessed by the included measures were relative advantage, available resources, knowledge and beliefs, complexity, implementation climate, and other personal resources (assessed by more than ten measures). Five CFIR constructs were not addressed by any measure. Conclusions: This review highlights gaps in the range of implementation constructs that are assessed by existing measures developed for use in public health and community settings. Moreover, measures with robust psychometric properties are lacking. Without rigorous tools, the factors associated with the successful implementation of innovations in these settings will remain unknown

Student Readiness for Online Learning – A case study in rural Bolivia

The present paper describes the research of the students’ online learning readiness in a rural university in Bolivia. In particular, it examines through a quantitative research the influences of some variables on the students’ attitudes toward online learning. These variables were established based on theoretical fundaments and selected and confirmed through a qualitative research based in semi-structured interviews with lecturers and directors of the university’s rural centers. This study also provides a way to predict the membership of a student in two groups: “Those who would participate in an online course” and “those who would not participate in an online course” depending on the influencing variables (technology access, technology skills, self-directed learning and online interaction). This analysis also reveals the most important factors to be considered by the university before introducing online courses. The results have shown that the perceived Internet access strongly affected the participation or the lack of participation of students in an online course. Moreover, the student’s attitude toward online learning is influenced mainly by the perception of the quality of his Internet access, by the perception about his capability to interact online (with other students, lecturers and content) and by the individual’s perception about his own computer skills. This study also provides a simple model to analyze the students’ online learning readiness based on their self-assessment