Thesis (Ph.D.)--Ohio State University, 2005. / Title from first page of PDF file. Document formatted into pages; contains x, 125 p.; also includes graphics. Includes bibliographical references (p. 113-125). Available online via OhioLINK's ETD Center

Numerous studies demonstrate the effectiveness of university-based community service programs on students' personal, social, ethical, and academic domains. These effects depend on both, the characteristics of students enrolled and the characteristics of the programs, for instance whether they are voluntary or mandatory. Our study investigates whether effects of voluntary service programs are indeed caused by the service experience or by prior self-selection. Using data from a pre-post quasi-experimental design conducted at a public university in Europe and taking students' socioeconomic background into account, our findings on self-efficacy, generalized trust, empathic concern, and attributions for poverty show that there are no participation effects. Instead, students who join in community service differ significantly from nonparticipants with regard to almost all investigated domains a priori, indicating strong self-selection. Our results underline the importance of structured group reflection, most notably with regard to attitude-related topics.

This study is attempted to the discovery critical factors of employee¡¦s e-Learning system use intention that may help companies understand for e-learning effective implement plans. It starts from literature review for getting the subjects of critical factors of enterprise e-learning and then we integrated technology acceptance model with subjective norm , system flexibility, e-Learning content richness, evaluation and records, e -Learning self-efficacy as the antecedents of perceived usefulness(PU) and perceived ease of use(PEU) Data were collected from seven implemented e-learning companies.. And analysised this structural equation model with SEM. The findings of this study present that employee¡¦s e-learning use intention and attitude are affected and guided by PU, PEOU has less influences power , Subjective norm ,system flexibility, e-Learning content richness are antecedent of PU, User support , e-Learning content richness and e-Learning self-efficacy are PEU¡¦s antecedents. Finally, we made some suggestion for practice and other researcher¡¦s base on the result

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The purpose of this exploratory study was to investigate student perceptions of the design and consistency of the online learning environment in relation to motivation, satisfaction, and self-efficacy. Through surveys, think-aloud observation sessions, and reflection interviews, data were collected concerning student perspectives of design and consistency in the online learning environment. SPSS was used to process the survey data and a multi-step process was used to code the observations and interviews. Nine categories emerged from the analysis: (1) frustration; (2) excitement; (3) feeling of being lost; (4) confusion; (5) disgust; (6) positivity; (7); anxiety; (8) understanding; (9) action. The findings are discussed and recommendations for future research are provided to inform future development of online courses.

With recent advances in technology, distance education has seen a move towards online and e-learning programmes and courses. However, many students in South Africa have limited access to computer technology and/or the Internet resources necessary for online learning. Worldwide trends have recently seen a growing emphasis on the use of mobile technology for learning purposes. High mobile penetration rates in South Africa means that mobile learning can potentially overcome many of the challenges associated with distanceand online learning. This research therefore aimed to explore adult distance education students’ mobile learning readiness in the South African context. Specifically, this study examined the influence of mobile learning self-efficacy, locus of control, subjective norm, perceived usefulness, perceived ease of use, perceived behavioural control and attitude towards mobile learning on students’ behavioural intention to adopt mobile learning. In order to test a model predicting students’ behavioural intention, the conceptual framework guiding the investigation combined the Technology Acceptance Model (TAM) and the Theory of the investigation combined the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB) and extended the model to include locus of control and mobile learning self-efficacy. A sample of 1070 students from a private higher education institution in South Africa participated in this study. Data were collected using an online survey questionnaire. Multiple regression analysis indicated that perceived ease of use contributed most significantly to behavioural intention to adopt mobile learning, followed by attitude towards mobile learning, subjective norm, perceived usefulness, perceived behavioural control and locus of control. Mobile learning self-efficacy did not significantly influence behavioural intention to adopt mobile learning. Overall, the model accounted for 44.8% of the variance in behavioural intention to adopt mobile learning. Significant differences in age, gender, race and household income existed with regard to several of the psychological constructs hypothesised to influence behavioural intention to adopt mobile learning. 4 Structural equation modelling was used to examine the fit between the data and the proposed model. The chi square goodness for fit test and the RMSEA indicated poor fit between data and model. Considering the sensitivity of the chi square statistic for sample size and the negative influence of too many variables and relationships on the RMSEA, a variety of alternative fit indices that are less dependent on the sample size and distribution were used to examine model fit. The GFI, AGFI, NFI and CFI all exceeded their respective acceptable levels, indicating a good fit with the data. / Psychology / M.A. (Psychology)