Web-based Training Environment Research Articles

Usability testing of Google cloud applications: students' perspective

Modern information and communication technologies affect all areas of life significantly, including education and learning. Cloud storage tools are one of the forms of modern information technologies that are employed to serve the educational process. The current research aims to study the use of Google cloud applications (Google Classroom, Google Plus and Google Drive) in education and to determine the most appropriate web-based training environment in view of the level of usability. The experimental method was applied in this study using a sample of 200 students from Imam Abdul Rahman bin Faisal University. The current research found that there was some convergence in the usability of the three environments. Based on the results of the study, it was found that the environment of Google Classroom has the highest usability value (86.45), and also showed statistically significant differences in scholastic achievement in the application the service of Google Classroom in the educational process.

How can students’ academic performance in statistics be improved? Testing the influence of social and temporal-self comparison feedback in a web-based training environment

ABSTRACTThe aim of this study was to examine how social or temporal-self comparison feedback, delivered in real-time in a web-based training environment, could influence the academic performance of students in a statistics examination. First-year psychology students were given the opportunity to train for a statistics examination during a semester by doing online exercises in a web-based training environment. Once connected, students received in real-time either social comparison feedback (their score was compared to the mean score of all first-year students) or temporal-self comparison feedback (their score was compared, week by week, with their own previous score). The fact that students were free to connect to the web-based training environment heightened self-regulation differences such as academic procrastination, which was considered as a moderating variable in this study. Because academic performance was measured, the students’ background in mathematics and statistics was also controlled. Irrespective of the students’ background, the results reveal a positive influence of social comparison feedback on statistics exam performance, but only among students who did not delay doing exercises in the web-based training environment. By contrast, temporal-self comparison feedback did not have any effect on performance. Some recommendations for optimizing the efficacy of web-based training environments can be proposed, taking into account both social comparison feedback and academic procrastination.

Self-regulated learning strategies and software training

We investigated one aspect of the growing trend towards self-management within organizations by examining the learning processes that individuals use when learning computer software alone in a web-based training environment, and found that individuals learn in different ways. Software training in any context requires individuals to apply self-regulated learning strategies to achieve their learning objectives. Self-regulated learning strategies are the processes that they use to manage their own learning. As self-guided training gains popularity, self-regulated learning strategies become increasingly important, because the learner typically has more control of their training. We found that self-regulated learning strategies led to better outcomes in our study of managers and professionals learning to use an ERP system. We also gained insights into the most popular learning strategies. This work enhanced our understanding of user processes when learning computer software. It should assist organizations in maximizing the return from their investment in training employees and managing knowledge.

An Efficient Approach for Analyzing User Behaviors in a Web-Based Training Environment

Mining frequent traversal patterns is to discover the consecutive reference paths traversed by a sufficient number of users from Web logs in a Web environment where users can travel from one object to another through the corresponding hyperlinks. Previous approaches for mining frequent traversal patterns only consider the forward references, such that the information about backward references will be lost. In this paper, we propose an efficient algorithm to discover the non-simple frequent traversal patterns. The non-simple frequent traversal patterns include forward and backward references, and are used to suggest potentially interesting traversal path to the users, which are useful, especially, in a Web-based training environment. The experimental results show that the discovered patterns can present the complete browsing paths traversed by most of the users and our algorithm outperforms other algorithms in discovered information and execution times.

Lifelong training with Vincent, a web-based pedagogical agent

In this paper, we address the problem of endowing a web-based training environment (TEMAI) with a synthetic pedagogical agent. TEMAI was built to support, via the web, a small part of a training course for workers in the footwear industry. The architecture of TEMAI combines four modules a set of micro-learning environments, a trainee model, learning material and Vincent - the pedagogical agent. To help the trainees, we created a synthetic character whose job is to foster the learning process, motivating the trainees in each session. Vincent combines a set of sensors and actors that establish message-based communication with the micro-learning environments while gathering information about trainee performance. Vincent has an anthropomorphic screen representation featuring four emotional attitudes sad, happy, disappointed and impatient. These attitudes combined with spoken utterances motivate the trainee to achieve better performance. TEMAI was evaluated by trainees in shoe making factories in the North of Portugal (S. Joao da Madeira). The results showed a small improvement in the trainees' performance after just six sessions. These results highlight the importance of pedagogical agents in on-the job computer-based training environments.