Motivation in online learning: Testing a model of self-determination theory

As high attrition rates becomes a pressing issue of online learning and a major concern of online educators, it is important to investigate online learner motivation, including its antecedents and outcomes. Drawing on Deci and Ryan’s self-determination theory, this study proposed and tested a model for online learner motivation in two online certificate programs (N = 262). Results from structural equation modeling provided evidence for the mediating effect of need satisfaction between contextual support and motivation/self-determination; however, motivation/self-determination failed to predict learning outcomes. Additionally, this study supported SDT’s main theorizing that intrinsic motivation, extrinsic motivation, and amotivation are distinctive constructs, and found that the direct effect and indirect effects of contextual support exerted opposite impacts on learning outcomes. Implications for online learner support were discussed.     

Locus of control,self-efficacy,and task value as predictors of learning outcome in an online university context

This study investigates the predictors of learner satisfaction, achievement and persistence in an online university located in South Korea. The specific predictors were learners' locus of control, self-efficacy, and task value, and the mediating effects of learner satisfaction and achievement were also tested. Structural equation modeling (SEM) was used to analyze the causation among the variables. The participants were 897 learners who enrolled in an online university in 2009 and a series of online surveys were administered. The results revealed that locus of control, self-efficacy, and task value were significant predictors of learner satisfaction, while self-efficacy and task value predicted achievement. Task value, satisfaction, and achievement were significant predictors for persistence. Lastly, learner satisfaction significantly mediated the predictors and persistence. The research findings increased our understanding of the learners and learning in an online university environment.     

Factors of learner–instructor interaction which predict perceived learning outcomes in online learning environment

Interaction in the online learning environment has been regarded as one of the most critical elements that affect learning outcomes. This study examined what factors in learner–instructor interaction can predict the learner's outcomes in the online learning environment. Learners in K Online University participated by answering the survey, and data from 654 respondents were analysed for this study. Results showed that factors related to instructional interaction predicted perceived learning achievement and satisfaction better than factors related to social interaction. However, it was revealed that social interaction such as social intimacy could negatively affect perceived learning achievement and satisfaction. This study has value because it found factors under learner–instructor interaction which predict perceived learning achievement and satisfaction with empirical evidence.     

Structural relationships among effective factors on e-learners’ motivation for skill transfer

This study investigates the structural relationships among the following factors: e-learners’ internal value, learning usefulness, learning environment, satisfaction, learner achievement, and motivation for skill transfer. To answer the research questions, the researchers administered online surveys to 584 students enrolled in two courses, Conflict Management and Negotiation and Communication Skills, at S Cyber University. According to the results of structural equation modeling, the structural relationships among e-learners’ internal value, learning usefulness, learning environment, learner satisfaction, learner achievement, and motivation for skill transfer were significant and showed positive influence. However, the relationships among learning usefulness, learning environment, learner satisfaction, and learner achievement and those of learning environment, learner satisfaction, and motivation for skill transfer were not significant. Overall, the findings suggest specific strategies to improve e-learners’ learning outcomes.     

Can more interactivity improve learning achievement in an online course? Effects of college students' perception and actual use of a course-management system on their learning achievement

This study aims to investigate how interactivity influence learners' use of interactive functions in the course-management system (CMS) and their online learning performance. A two-tier mediation framework is proposed to examine the mediating effects of different actual-use records concerning the CMS's interactive functions. Data are collected from 381 undergraduate students who enrolled in a general-education asynchronous online course from three universities in Taiwan. The results indicate that the relationships among students' self-reported use of interactive functions, students' perceptions of the usefulness of interactive functions, and students' actual-use logs have some direct influences on students' online learning performance (online-discussion scores, exam scores, and group-project scores). In addition, students' actual-use logs (the number of times of log-ins to the online course, the number of times students read learning materials, and the number of postings on the discussion board) have a mediated effect on students' self-reported frequency of logging into the CMS, students' self-reported frequency of using the learner–instructor/learner–learner interactive functions, and online learning performance. The findings and implications could constitute a useful guide for educational practitioners and designers concerned with the effective integration of interactivity into future online courses.     

Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model

Learners’ satisfaction and persistence are considered critical success factors in online universities where all of the teaching and learning activities are carried out online. This study aims to investigate the structural relationships among perceived level of presence, perceived usefulness and ease of use of the online learning tools, learner satisfaction and persistence in an online university located in South Korea. The specific predictors were teaching presence, social presence, cognitive presence, and perceived usefulness and ease of use. Structural equation modeling (SEM) was used to provide cause-and-effect inferences. The study participants were 709 learners who enrolled in a Korean online university in 2009 and responded to online surveys. The results indicated that teaching presence, cognitive presence, and perceived usefulness and ease of use were significant predictors of learner satisfaction, which was found to be a significant mediator of predictors and persistence. The findings provided substantial implications for designing and implementing teaching and learning strategies in online university environments.     

Learner readiness for online learning: Scale development and student perceptions

The purpose of this study was to develop and validate a multidimensional instrument for college students’ readiness for online learning. Through a confirmatory factor analysis, the Online Learning Readiness Scale (OLRS) was validated in five dimensions: self-directed learning, motivation for learning, computer/Internet self-efficacy, learner control, and online communication self-efficacy. Research data gathered from 1051 college students in five online courses in Taiwan revealed that students’ levels of readiness were high in computer/Internet self-efficacy, motivation for learning, and online communication self-efficacy and were low in learner control and self-directed learning. This study found that gender made no statistical differences in the five OLRS dimensions, but that higher grade (junior and senior) students exhibited significantly greater readiness in the dimensions of self-directed learning, online communication self-efficacy, motivation for learning, and learner control than did lower grade (freshman and sophomore) students.     

Self-directed learning readiness, Internet self-efficacy and preferences towards constructivist Internet-based learning environments among higher-aged adults

This article examines several research questions to establish a theory model for explaining factors that influence adult learners' preferences for constructivist Internet-based learning environments (CILE). Data were gathered from 541 individual participants enrolled in adult education institutes in Taiwan for structural equation modelling (SEM) analyses. The research results established a 10-scale instrument for assessing adult learners' preferences for CILE. Among the scales of CILE, adult students placed the highest value on relevance to life and reflective thinking, and scored the lowest for critical judgement, ease of use and student negotiation. The SEM analyses revealed that compared to Internet self-efficacy (ISE), self-directed learning readiness plays a major role in predicting adults' preferences for their learning environment, especially for the higher level of intellectual challenge. ISE plays a mediating role in the relationships between Internet usage and the participants' preferences. This result suggests that more time spent on Internet practice may increase adult learners' ISE, which may strengthen their preferences for Internet-based learning environments.     

The nature of adolescent learner interaction in a virtual high school setting

This study used survey data to measure the effect of learners' reported interactions with content, peers, and instructors on several course outcomes in two virtual high school courses that emphasized interactive learning. Surveys found that the large majority of students viewed all investigated types of interaction as educational and motivational. Students perceived learner–instructor and learner–content interactions to have significantly higher educational value (α < 0.01) than learner–learner interactions, and viewed learner–instructor interaction to be significantly more motivational (α < 0.01) than learner–content interaction. Furthermore, nine significant correlations were found involving the time students reported spending on human interaction and course outcomes. Seven of the significant correlations were related to the time students reported spending in human interaction and the more affective outcomes, such as course satisfaction and disposition towards the subject area. Outcomes also indicate that learner–learner interaction had higher correlations with course outcomes than learners' interactions with the content or their instructor. Students' perceived learning was not significantly correlated with any type of interaction, and only students' total reported time spent on learner–learner interaction and students' social learner–learner interaction were significantly correlated with their grade.     

The impact of transactional distance dialogic interactions on student learning outcomes in online and blended environments

This study measured how student interactions (as captured by Transactional Distance dialogue (Moore, 1993)) in online and blended learning environments impacted student learning outcomes, as measured by student satisfaction and student grades. Dialogue was measured as student interactions with other students (student–student interaction), the technologies used (student–technology interaction), the instructors (student–teacher interaction), and the course contents (student–content interaction). In addition, moderating effects of media and modality of interactions and individual differences on student learning outcomes were also measured. Data was obtained from 342 online and blended students between 2010 and 2013. Findings indicate that student–content interaction had a larger effect on student learning outcomes than other forms of dialogue. Implications for educational policies that require teacher-presence (student–teacher) and student–student interactions in distance learning environments are also discussed.     

Five facets of social presence in online distance education

Social presence in online learning environments refers to the degree to which a learner feels personally connected with other students and the instructor in an online learning community. Based on a 19 item Online Social Presence Questionnaire (OSPQ) given to college students in two different online learning courses, a series of exploratory and confirmatory factor analyses consistently revealed five factors representing facets of social presence in online learning environments: social respect (e.g. receiving timely responses), social sharing (e.g., sharing information or expressing beliefs), open mind (e.g., expressing agreement or receiving positive feedback), social identity (e.g., being called by name), and intimacy (e.g., sharing personal experiences). Together, the five factors accounted for 58% of the variance and were based on 19 items. Although much previous research focuses on cognitive aspects of learning in online environments, understanding the role of the learner’s sense of presence may be particularly important in distance learning situations in which students and the instructor are physically separated.     

Factors impacting university students' online learning experiences during the COVID-19 epidemic

Due to the COVID-19 epidemic crisis, students from higher education institutions around the world are forced to participate in comprehensive online curriculums. In such a scenario, it is worth investigating how students perceived their learning outcomes and satisfaction based on this method of teaching and learning online. This study aims to explore the role of six factors, namely, system quality, course design, learner-learner interaction, learner-instructor interaction, learner-content interaction, and self-discipline, on university students' perceived learning outcomes and their effect on student satisfaction with online curricula during the COVID-19 epidemic. A structural equation modelling technique was used to assess survey questionnaires obtained from 457 validated students at a Public University in China. The results demonstrated that these determinants had a positive effect on satisfaction and learning outcomes, whereas learner-instructor interaction had no significant effect. Furthermore, the strongest determinant that affected not only students' satisfaction but also their learning outcomes was the learner-content interaction.     

Motivational beliefs and perceptions of instructional quality: predicting satisfaction with online training*

Abstract Many would agree that learning on the Web – a highly autonomous learning environment – may be difficult for individuals who lack motivation and self‐regulated learning skills. Using a social cognitive view of academic motivation and self‐regulation, the objective of the present study was to investigate the relations between students' motivational beliefs, their perceptions of the learning environment and their satisfaction with a self‐paced, online course. Service academy undergraduates (n = 646) completed a questionnaire following online training. Pearson correlations indicate that task value, self‐efficacy and perceived instructional quality were significantly positively related to each other and to students' overall satisfaction with the self‐paced, online course. Additionally, results from a three‐step hierarchical regression reveal that task value, self‐efficacy and instructional quality were significant positive predictors of students' satisfaction; the final regression model accounted for approximately 54% of the variance in the outcome measure. These findings support and extend prior research in traditional classrooms and online education in university settings, indicating that military students' motivational beliefs about a learning task and their perceptions of instructional quality are related, in important ways, to their overall satisfaction with online instruction. Educational implications and suggestions for future research are discussed.     

Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom

Decrease in student satisfaction and motivation in flipped classroom (FC) model of instruction is among frequently observed problems. And these problems could reduce the efficiency of FC model. It is believed that the problems related to student satisfaction and motivation in FC model of instruction are related to the e-learning readiness of the students. The purpose of the current study was to explore the impact of the e-learning readiness of the students on student satisfaction and motivation in FC model of instruction. The study was carried out with 236 undergraduate students taking Computing I class taught using FC model of instruction. Data were collected from three self-report instruments: E-learning Readiness Scale (subscales: ‘computer self-efficacy’, ‘internet self-efficacy’, ‘online communication self-efficacy’, ‘self-directed learning’, ‘learner control’ and ‘motivation towards e-learning’), Satisfaction Scale and Motivated Strategies for Learning Questionnaire. The path analyses with structural equation modelling (SEM) further verified that students' e-learning readiness were related to their satisfaction and motivation while undertaking academic tasks in FC model of instruction. The results of the study indicated that students' e-learning readiness was a significant predictor of their satisfaction and motivation in FC model of instruction. Findings were presented and discussed for future studies and applications.     

Multi-level analysis of peer support,Internet self-efficacy and e-learning outcomes – The contextual effects of collectivism and group potency

The present study intends to explore the role of collectivism and group potency at group level in predicting individual Internet self-efficacy (ISE) and individual e-learning outcomes for people aged over 45. Group learning has been widely discussed in the research into online formats. However, less study has been carried out about how collectivism and collective group potency affect individual learning decisions, especially using the technique of Hierarchical Linear Modeling (HLM) for cross-level analysis, which provides the solution of case dependency between group members. This study examines the mediation effects of ISE between peer support and e-learning outcomes. It also explores the contextual effects of group potency, and the moderation effects of collectivism and group potency at an individual level. The results show that ISE fully mediates the relationship between peer support and learners’ persistence in e-learning, and partially mediates learners’ perceived learning and satisfaction. It is noteworthy that the findings do not support direct group-level contextual effects of group potency. Instead, the results suggest that group potency moderates ISE-perceived learning and ISE-satisfaction relationships. On the other hand, collectivism also moderates the relationship between peer support and ISE. This study highlights the group-level effects of group potency, and suggests that adult educators design and deliver e-learning courses with an emphasis on facilitating group processes.     

Sage,guide, both,or even more? An examination of instructor activity in online MBA courses

This study examined faculty characteristics and behaviors in 46 MBA courses conducted over a two-year period. We found that both formal instructor activities, referred to in the online learning literature as teaching presence, and informal instructor activities, known as immediacy behaviors, were positive predictors of student perceived learning and satisfaction with the educational delivery medium. We also found that instructor login intensity, the average amount of time spent per login session, was a negative predictor of perceived learning. Collectively, these findings suggest the need for instructors to structure and organize their courses beforehand so they can focus on efficient engagement with their students while the class is in session. Although teaching presence and instructor immediacy were significant predictors of delivery medium satisfaction, they explained only 6% of the variance. This finding should help instructors avoid taking unnecessary responsibility for students’ attitudes toward online learning. The paper concludes with a discussion of implications for training of online instructors and the appropriate use of multilevel analytical tools in online learning and education research.     

Understanding knowledge-sharing breakdowns: a meeting of the quantitative and qualitative minds

Abstract The rapid advance of distance learning and networking technology has enabled universities and corporations to reach out and educate students across time and space barriers. Although this technology enables structured collaborative learning activities, online groups often do not enjoy the same benefits as face‐to‐face learners, and their instructors often do not have time to actively support and mediate the online collaboration. This article demonstrates our capacity to computationally model, analyse, and support online student interaction, in particular knowledge sharing. A unique combination of qualitative analysis and artificial intelligence methods was designed to (a) recognize when students are having trouble learning the new concepts they share with each other, and (b) understand why they are having trouble, so that we might assist an instructor or intelligent coach in mediating group knowledge‐sharing activities.     

What type of learning style leads to online participation in the mixed-mode e-learning environment? A study of software usage instruction

Learning style is traditionally assumed to be a predictor of learning performance, yet few studies have identified the mediating and moderating effects between the two. This study extends previous research by proposing and testing a model that examines the mediating processes in the relationship between learning style and e-learning performance and the moderating effects of prior knowledge. The results show that the sensory/intuitive dimension of learning style predicts learning performance indirectly through the mediation of online participation. However, other types of learning styles do not affect online participation. Sensory students demonstrate a higher level and intuitive students a lower level of online participation. Prior knowledge plays an important role as a moderator between online participation and learning performance. This study was conducted in the context of software usage instruction using empirical data from 219 undergraduate students.     

基于尔雅通识课的大学生在线学习现状研究

尔雅通识课作为一种在线学习平台,广泛应用于高校公共选修课的教学。本文以X大学学生为样本,调查大学生在尔雅平台的在线学习情况。调查围绕学习动机、学习方法、学习时间、学习环境、学习效果以及学习过程中的重要他人等维度展开。通过调查发现,X大学学生在尔雅平台的学习动机、行为表现、学习效果等方面的特点和存在的问题并提出合理的改进建议。     

The effectiveness and acceptance of an affective information literacy tutorial

Due to the ready access to large amounts of information afforded by the Internet, information literacy (IL) has taken on an important role. Recent developments in affective computing have provided more opportunities in the way online IL education can be delivered. However, research on how affective computing can be used in IL education is lacking. The research objectives of this study are therefore twofold: to investigate the influence of affective embodied agents (EAs) on students' motivation, enjoyment, knowledge retention and intention to use; and to uncover factors influencing their intention to use an online IL tutorial with affective EAs.To achieve these objectives, 285 university students were recruited to participate in a betweensubjects experiment (text-only, non-affective EAs, and affective EAs), including completing an IL tutorial and a post-test questionnaire. The results suggested that students benefited from the added use of an affective EA in the IL tutorials, in terms of learning motivation and enjoyment. Moreover, relevance, confidence, satisfaction, affective enjoyment, and behavioral enjoyment were found to be significant predictors for intention to use an IL tutorial with affective EAs.