Interaction, Internet Self-Efficacy, and Self-Regulated Learning as Predictors of Student Satisfaction in Distance Education Courses

Online learning research is largely devoted to comparisons of the learning gains between face-to-face and distance students. While student learning is important, comparatively little is known about student satisfaction when engaged in online learning and what contributes to or promotes student satisfaction. Emerging research suggests there are a few strong predictors of student satisfaction, and other predictors that may or may not predict student satisfaction. None of the existing research examines predictors together, or statistically controls for course differences. This study examines the influence of various factors on student satisfaction including three types of interaction, Internet self-efficacy, and self-regulated learning. Participants (N = 180) include both undergraduate and graduate students attending exclusively online classes in education. Students responded to an online survey adapted from several different scales. A pilot test of the survey and procedures showed strong validity and reliability for the sample. To control for course differences, data analysis focused on a hierarchical linear model (HLM) with student and class level variables. Results indicate learner-instructor interaction and learner-content interaction are significant predictors of student satisfaction when class-level variables are excluded. Of the class-level predictors, only the program from which the course was offered moderates the effect of learner-content interaction on student satisfaction. There is no direct impact of class-level predictors on student satisfaction. Learner-content interaction is the sole significant predictor when class-level predictors are added to the model. Supporting analyses for the HLM, results, limitations, and significance of the findings are reported and discussed

Exploring factors influencing minority students’ perceived learning in collaborative Wiki-based learning environments

This study examined the factors affecting minority students’ learning experience in Wiki-based environments. These factors included perceived collaborative learning, sense of community, Wiki self-efficacy, and perceived learning experience. The relationships of these factors were explored. The participants were 45 African American students enrolled in two undergraduate-level management courses in which Wiki was used to facilitate the process of group work. A mixed methods approach was applied to analyze the collected data. Results indicated that sense of community and collaborative learning significantly contributed to perceived learning in Wiki-based environments. However, Wiki self-efficacy was not a good predictor of perceived learning. Most of the minority students were positive about their group learning experience that involved collaborative processes as well as the development of knowledge and skills. Emotional support and support for cognitive or meta-cognitive processing were identified as factors that had potential influences on Wiki based collaborative group learning

Internet Self-Efficacy, Self-Regulation, and Student Performance: African-American Adult Students in Online Learning

The paper intended to investigate adult students’ Internet self-efficacy, self-regulation, and performance in online learning environments. The relationships between these variables and the effect of student characteristics on Internet self-efficacy and self-regulation were explored. The participants of this study were African American students from a university in the United States. They participated in two web-based research courses offered in summer. Data were collected through an online survey and were analyzed by a quantitative approach. The results showed Internet self-efficacy was positively related to self-regulation at a significant level. Internet selfefficacy and self-regulation differed in terms of student performance. The differences of gender and age did not have a significant impact on Internet self-efficacy and self-regulation. Discussions and implications were addressed according to the major findings of this study

Plane-projection multi-photon microscopy for high-frame-rate Live Tissue Imaging

We present a wide-field multi-photon microscopy that provides optical sectioning at high frame rate under biocompatible laser dosage. Axial resolution comparable to confocal microscopy and 5-frame-per-second live tissue imaging are demonstrated

Let’s Play Cards: Multi-Component Cognitive Training With Social Engagement Enhances Executive Control in Older Adults

Cognitive training and social engagement are two of the routes that potentially improve cognitive functions in older adults. The former targets specific functions so that an intervention can trigger the plasticity and efficiency of the underpinning neural systems, and the latter also provides an environment supportive of social and emotional needs. We investigated whether an integration of the two routes could enhance cognitive functions related to executive control, because no prior research has adopted a theory-driven approach to design a group-based cognitive training program for executive control. Forty-six healthy and active older adults living in community settings were randomly assigned to a group-based training program or a group-based active control program. Twenty-three volunteers in a community center were recruited for the waitlist control group. A battery of card games was designed for the cognitive training program based on three theoretical models of executive functions. A set of commercial board games were run in the active control program. Using untrained tests as the outcome measures, we found significant improvement on executive control in the cognitive training group compared with the active and waitlist control groups while the two control groups did not differ in performance. The cognitive training group did not outperform the two groups on a test of reasoning or on a test of delayed episodic memory. The results support the idea that cognitive training with social interaction can improve performance on untrained tests that share overlapping cognitive processes. Despite the inability to adapt to each person’s performance, integrating the two routes is beneficial for improving cognitive functions in older adults

Experimental and Numerical Study on the Semi-Closed Loop Control of a Planar Parallel Robot Manipulator

This paper implements the model predictive control to fulfill the position control of a 3-DOF 3-RRR planar parallel manipulator. The research work covers experimental and numerical studies. First, an experimental hardware-in-the-loop system to control the manipulator is constructed. The manipulator is driven by three DC motors, and each motor has an encoder to measure the rotating angles of the motors. The entire system is designed as a semiclosed-loop control system. The controller receives the encoder signals as inputs to produce signals driving the motors. Secondly, the motor parameters are obtained by system identification, and the controllers are designed based on these parameters. Finally, the numerical simulations are performed by incorporating the manipulator kinematics and the motor dynamics; the results are compared with those from the experiments. Both results show that they are in good agreement at steady state. There are two main contributions in this paper. One is the application of the model predictive control to the planar parallel manipulator, and the other one is to overcome the effects of the uncertainties of the DC motors and the performance of the position control due to the dynamic behavior of the manipulator