The influence of computer self-efficacy,metacognitive self-regulation and self-esteem on student engagement in online learning programs: Evidence from the virtual world of Second Life

While the widespread acceptance of social virtual words is being increased in the last years, little are known about how students’ personal factors can affect their engagement in online learning courses. The current study proposed and empirically examined a conceptual model that aimed to fill this gap. The main purpose is to present an extensive empirical data of 305 novice or expert students (153 graduates and 152 postgraduates) who enrolled in online courses at university level which were held in Second Life. On this occasion it was tried to be investigated, measured and finally verified the effects of computer self-efficacy, metacognitive self-regulation and self-esteem that can predict the students’ engagement as an overall multidimensional construct of factors (cognitive, emotional and behavioral). The results from the three-step hierarchical regression analysis revealed that computer self-efficacy, metacognitive self-regulation, and self-esteem in online courses were not only positively correlated with student’s cognitive and emotional engagement factors, but were also negatively correlated with behavioral factors. Educational implications from these results can provide a more expedient and meritorious instructional quality format aimed at reinforcing users’ engagement in Second Life for sequencing and pacing future-driven online courses.     

Teacher self-efficacy,academic self-efficacy,and computer self-efficacy as predictors of attitude toward applying computer-supported education

There is a large body of research regarding teacher self-efficacy, academic self-efficacy, computer self-efficacy, and attitude toward applying computer-supported education of teachers and prospective teachers. However, no study has been conducted on the correlation among the effects of teacher self-efficacy, academic self-efficacy, computer self-efficacy, and attitude toward applying computer-supported education and which additionally explains their relationships to one other. This research is conducted in order to test the effect levels among the latent variables of teacher self-efficacy, academic self-efficacy, computer self-efficacy, and attitude toward applying computer-supported education and these latent variables' ratios to each other. For this, eight hypotheses were developed in light of theoretical information by reviewing the literature. This research is done by using Academic Self-Efficacy Scale, Teacher Self-Efficacy Scale, Computer Self-Efficacy Scale, and The Attitude Scale Toward Applying Computer-Supported Education. The participant group of the research consists of 323 prospective teachers. Exploratory factor analyses of scales were analyzed via SPSS 16.0 software. For the confirmatory factor analyses of scales and the structural equation modeling, AMOS 20.0 software was used. The most significant finding of this study is that teacher self-efficacy, academic self-efficacy, and computer self-efficacy are important predictors of prospective teachers' attitude toward applying computer-supported education.     

Monitoring, planning, and self-efficacy during learning with hypermedia: The impact of conceptual scaffolds

Self-report data and think-aloud data from 37 undergraduates were used to examine the impact of conceptual scaffolds on self-efficacy, monitoring, and planning during learning with a commercial hypermedia environment. Participants, randomly assigned to either the No Scaffolding (NS) or Conceptual Scaffolding (CS) condition, used a hypermedia environment for 30 min to learn about the circulatory system. Think-aloud data collected during this learning task was used to measure participants’ self-regulated learning (SRL) with hypermedia. Additionally, participants completed a self-efficacy questionnaire at three points during the learning task (immediately prior to the 30-min hypermedia learning task, 10 min into the learning task, and 20 min into the learning task). Results indicated that participants from both conditions reported higher levels of self-efficacy immediately before the hypermedia learning task, and that they decreased their use of SRL processes related to monitoring as they progressed through the hypermedia learning task. In addition, results also indicated that participants in the CS condition used, on average, more SRL processes related to planning during the hypermedia learning task than participants in the NS condition.     

The impact of computer anxiety and self-efficacy upon performance

The relationship between computer anxiety and computer performance is examined using a self-efficacy framework. A novel database searching task was demonstrated to 50 participants using two procedures (namely, accessing the data tables directly and constructing look-up tables). Levels of computer anxiety, prior experience and perceptions of self-efficacy were recorded. The results indicate that computer anxiety directly influences the number of correct responses obtained whilst self-efficacy determines how the task is attempted. Less anxious subjects obtained more correct responses and subjects with higher perceptions of self-efficacy used more look-up tables. The results indicate that self-efficacy theory can account for around half the variance in computer performance and that how a task is attempted should be assessed in addition to accuracy and speed of performance.     

Mapping virtual communities by their visual productions: The example of the Second Life Steampunk community

In the digital age, the identities and structures of virtual communities develop outside the traditional definitions of geography and physical constraints. Among the best models to study the identification process in virtual communities are the communities of fans of imaginary universes. Steampunk—neo-Victorian fiction with a science fiction twist—has for instance given rise to a large community, which is very active both in real life and in virtual spaces, for instance in the online 3D immersive platform Second Life. By collecting and analysing hundreds of visual artifacts generated by members of the steampunk community of Second Life, we found a repertoire of visual and lexical characteristics with which to identify the community. In addition, examining the characteristics displayed by visual productions from other communities allowed us to map relationships between different communities based on their aesthetics. This data suggests that the quantification of visual clues points out to interlocking relationships between different community aesthetics, forming a network where differences are visible, but fluidity still dominates. Furthermore, our results could serve as a model to study how communities in different media (immersive universes, games, social media based on visual materials such as Pinterest or Instagram) generate their own visual identity.     

EEG in classroom: EMD features to detect situational interest of students during learning

Multimedia Tools and Applications - Situational interest is widely explored in the psychology and education domains. It is proven to have positive effect on learning and academic achievement....     

High school students' perceptions of affect and collaboration during virtual science inquiry learning

This study examined affect during high school students' face‐to‐face collaborative inquiry learning in science, supported by the web‐based software Virtual Baltic Sea Explorer. Self‐reported affective states during the inquiry process in peer groups were related to evaluations of a group's collaboration and performance in three phases of interdisciplinary science inquiry (biology and chemistry). Results indicate that despite high cognitive demands, positive affect prevailed whereas negative affect was infrequent. Structural equation modelling was used to analyse the significance of affect on collaboration and group performance. The relationship between affect, collaboration, and the groups' productive outcome revealed that self‐assurance had a significant effect on collaboration and support, intertwined with scientific understanding and group performance. Furthermore, a cross‐lagged analysis showed a reciprocal relation between positive affect, scientific understanding, collaboration, and support. These outcomes contribute to the scarce literature on the nature and importance of affect in the process of face‐to‐face computer‐supported collaborative inquiry and learning in science.     

Computer anxiety and anger: the impact of computer use, computer experience, and self-efficacy beliefs

Past research has demonstrated that the level of computer experience users have is the most valuable predictor in whether or not they will suffer computer anxiety symptoms, but this was not the case in the present study. No research was found which examined the correlates of computer anger symptoms. In the current study, the relationship between the computer use (frequency and duration), computer experience, and self-efficacy beliefs of users were analyzed as predictors for computer anxiety and anger symptoms. Questionnaire data from a sample of 242 university students were analyzed. The results indicated that computer self-efficacy beliefs, not computer experience or use, had the largest significant relationship with both computer anxiety, and anger. It is suggested that self-efficacy beliefs be increased so that users may experience lower levels of anxiety and anger. These findings are contrary to the trend of training computer users in specific computer domains. As computer anxiety and anger are negative psychological “states”, an immediate method to deal with these negative emotions should be developed. One possibility that is explored is the application of computer-based therapy that can be used while a user is experiencing negative emotional symptoms.     

Knowledge sharing behavior in virtual communities: The relationship between trust,self-efficacy,and outcome expectations

There has been a growing interest in examining the factors that support or hinder one's knowledge sharing behavior in the virtual communities. However, still very few studies examined them from both personal and environmental perspectives. In order to explore the knowledge sharing behaviors within the virtual communities of professional societies, this study proposed a social cognitive theory (SCT)-based model that includes knowledge sharing self-efficacy and outcome expectations for personal influences, and multi-dimensional trusts for environmental influences. The proposed research model was then evaluated with structural equation modeling, and confirmatory factor analysis was also applied to test if the empirical data conform to the proposed model.     

Participation in virtual academic communities of practice under the influence of technology acceptance and community factors. A learning analytics application

Participation in virtual communities of practice (vCoP) can be influenced at the same time by technology acceptance and by community factors. To overcome methodological issues connected with the analysis of these influences, learning analytics were applied. Based on a recent vCoP model, the collaborative dialogue comprising 4040 interventions in 1981 messages created by a vCoP located at a US American online university was automatically analyzed. The text-based asynchronous online discussions were scored using a cohesion-based participation and collaboration analysis. Additionally, a sample of N = 133 vCoP participants responded a technology acceptance survey. Thus, a combined research model including the vCoP model and an established technology acceptance model was verified. The results confirmed the vCoP model entirely, and the acceptance model only partially. As consequence for educational research, the CoP model was confirmed and extended to vCoP settings, while the acceptance model appears to need reconsideration. For academic practice, the study initiates the development of assessment tools fostering knowledge sharing through dialogue in vCoP. Also, it suggests how virtual classrooms can be extended to open spaces where value creation takes place through social learning. Learning analytics proved thus successful, provides information that impacts both theory and practice of technology-enhanced learning.     

The impact of self-efficacy and perceived system efficacy on effectiveness of virtual training systems

This study developed and tested a research model which examined the impact of user perceptions of self-efficacy (SE) and virtual environment (VE) efficacy on the effectiveness of VE training systems. The model distinguishes between the perceptions of one's own capability to perform trained tasks effectively and the perceptions of system performance, regarding the established parameters from literature. Specifically, the model posits that user perceptions will have positive effects on task performance and memory. Seventy-six adults participated in a VE in a controlled experiment, designed to empirically test the model. Each participant performed a series of object assembly tasks. The task involved selecting, rotating, releasing, inserting and manipulating 3D objects. Initially, the results of factor analysis demonstrated dimensionality of two user perception measures and produced a set of empirical validated factors underlining the VE efficacy. The results of regression analysis revealed that SE had a significant positive effect on perceived VE efficacy. No significant effects were found of perceptions on performance and memory. Furthermore, the study provided insights into the relationships between the perception measures and performance measures for assessing the efficacy of VE training systems. The study also addressed how well users learn, perform, adapt to and perceive the VE training, which provides valuable insight into the system efficacy. Research and practical implications are presented at the end of the paper.     

The impact of the computational inquiry based experiment on metacognitive experiences,modelling indicators and learning performance

Computational experiment approach considers modelling as the essential feature of Inquiry Based Science Education (IBSE), where the model and the computer take the place of the “classical” experimental set-up and simulation replaces the experiment (Landau, Pαez, & Bordeianu, 2008).Modelling, as a pedagogical tool, involves the model construction, the exploration of model characteristics and the model application to a specific problem, resembling authentic activities of scientists and mathematicians (Herbert, 2003).Recent developments in strategy instruction research suggest that learning in a particular discipline is enhanced by guiding students through the development of content-relevant metacognitive strategies (Wosnitza & Volet, 2009).Problem-solving is a complex process, which involves several cognitive operations such as collecting and selecting information, heuristic strategy and metacognition (De Corte, 2003, Garofalo and Lester, 1985, Schoenfeld, 1994).The purpose of this study was to explore the impact of the Computational Experiment Methodology on learners' cognitive performance, use of modelling indicators and shift of the metacognitive experiences during problem solving using computational models.Sixty prospective primary school teachers volunteered to participate in the study.Students were exposed by the Instructor to a number of computational experiments, while during the course they developed their own models of simulation.The results of the experiment show that the use of the computational experiment approach has a substantial effect on the metacognitive experiences and the use of modelling indicators.     

The impact of general and specific performance and self-efficacy on learning with computer-based concept mapping

When students learn a new and challenging task, for which they have very limited corresponding personal or vicarious experiences to refer, it is important to understand how their self-efficacy beliefs evolve during the course of sequential lessons; how they differ in the way their general learning performance and self-efficacy influence their ratings of task-specific self-efficacy and performance; and, how such differences may result in different learning outcomes and motivations for learning. By examining a group of 66 students engaged in learning to construct good concept maps with computer software, this study revealed several important findings on these questions. Students generally tended to initially overestimate their ability to successfully carry out the required task. They also varied in the way their general self-efficacy and performance were associated with their task-specific self-efficacy and performance. And, these differences did appear to be associated with different learning outcomes and motivations for learning. These results indicate that investigating individual differences in students’ patterns of association between general and specific performance and their self-efficacy may lead to a better understanding of how students differ in their levels of motivation and outcomes when learning a new and challenging task.     

The influence of self-discrepancy between the virtual and real selves in virtual communities

Virtual communities enable one to pretend to be a different person or to possess a different self-identity at little or no cost. Despite the ubiquity of such communities, there is limited theoretical and empirical research regarding the effect of taking on a different self-identity associated with one’s psychological and behavioral functioning in those communities. To address this issue, drawing on the self-concept rooted in sociopsychology, this study employs the self-discrepancy index, which assesses the degree of differences between one’s virtual and real selves; the study goes onto develop a theoretical framework that links self-discrepancy, psychological states (i.e., autonomy, recovery, and catharsis), and behavior (i.e., contribution quality and quantity). The results of an analysis involving 299 survey participants show that self-discrepancy has a significant influence on autonomy and recovery and that this, in turn, influences levels of contribution quality and quantity. It is of note that the results of this study indicate that catharsis is inversely related to contribution quality. Furthermore, subgroup analysis reveals that the effects of self-discrepancy on contribution vary depending on whether the virtual community is utilitarian or hedonic.     

The impact of organisational support,technical support,and self-efficacy on faculty perceived benefits of using learning management system

This paper examines how organisational support influences learning management system (LMS) self-efficacy, technical support, and faculty-perceived benefits. An empirical study based upon responses from 379 instructors at several universities is conducted. Structural equation modelling is applied to develop and assess the measurement model, and analyse the relationships among the factors in the structural model. The results support the hypotheses that organisational support plays a primary role in enhancing faculty’s LMS self-efficacy and technical support. In turn, improved LMS self-efficacy and technical support lead to faculty-perceived benefits from using LMS. Implications are that universities can increase the use of LMS and achieve more effective outcomes from faculty for web-based distance learning and web-assisted course curricula by structuring their organisations to better support faculty in both technical and self-efficacy areas.     

Development and evaluation of a virtual campus on Second Life: The case of SecondDMI

Video games and new communication metaphors are quickly changing today’s young people habits. Considering the actual e-learning scenarios, embedded in a fully technological enabled environment it is crucial to take advantage of this kind of capabilities to let learning process gain best results.     

Modeling computer interest in older adults: the role of age, education, computer knowledge, and computer anxiety

We proposed a mediation model to examine the effects of age, education, computer knowledge, and computer anxiety on computer interest in older adults. We hypothesized that computer knowledge and computer anxiety would fully mediate the effects of age and education on computer interest. A sample of 330 older adults from local senior-citizen apartment buildings completed a survey that included an assessment of the constructs included in the model. Using structural equation modeling, we found that the results supported the hypothesized mediation model. In particular, the effect of computer knowledge operated on computer interest through computer anxiety. The effect of age was not fully mitigated by the other model variables, indicating the need for future research that identifies and models other correlates of age and computer interest. The most immediate application of this research is the finding that a simple 3-item instrument can be used to assess computer interest in older populations. This will help professionals plan and implement computer services in public-access settings for older adults. An additional application of this research is the information it provides for training program designers.     

The role of academic emotions in the relationship between perceived academic control and self-regulated learning in online learning

Self-regulated learning is recognized as a critical factor for successful online learning, and students' perceived academic control and academic emotions are important antecedents of self-regulated learning. Because emotions and cognition are interrelated, investigating the joint relationship between perceived academic control and academic emotions on self-regulated learning would be valuable to understanding the process of self-regulated learning. Therefore, this study examined the role of academic emotions (enjoyment, anxiety, and boredom) in the relationship between perceived academic control and self-regulated learning in online learning. The path model was proposed to test the mediating and moderating effects of academic emotions. Data were collected from 426 Korean college students registered in online courses, and a path analysis was conducted. The results demonstrated that enjoyment mediated the relationship between perceived academic control and self-regulated learning, but the moderating effect of enjoyment was not significant. Boredom and anxiety did not have significant mediating effects on self-regulated learning, whereas they showed significant moderating effects in the relationship between perceived academic control and self-regulated learning. The role of academic emotions in learning and their implications for facilitating students' self-regulated learning in online learning were discussed based on the findings.