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While past studies on user-interface design focused on a particular system or application using the experimental approach, we propose a theoretical model to assess the impact of perceived user-interface design (PUID) on continued usage intention (CUI) of self-paced e-learning tools in general. We argue that the impact of PUID is mediated by two variables, namely perceived functionality (PF) and perceived system support (PSS), which influence perceived usefulness (PU) and perceived ease of use (PEOU), respectively. We empirically validated the model using data collected from a survey administered to university students in Hong Kong. We found that most hypotheses are valid and PUID is an important antecedent of CUI of a self-paced e-learning tool. We also showed that PU and user satisfaction (USat) are two essential predictors of CUI. However, the impact of PEOU on CUI is indirect via PU as a mediator. Our findings enrich the theory on the continued usage of technology, and provide e-learning developers with managerial insights on how to entice learners to continue using their e-learning tools.
This study with data collected from a large sample of freshmen in 2001 and a random stratified sample of seniors in 2005 examined students perceived FITness (fluency with Information Technology). In the fall of 2001 freshmen at a medium sized research-one institution completed a survey and in spring 2005 a random sample of graduating seniors completed a similar survey. The surveys measured the student’s self-reported proficiency in basic information technology knowledge and skills such as word processing and presentation software as well as more complex applications such as digital audio. We found a significant increase in perception of skills in presentation software and browsers and although both groups reported low skill levels, a significant decrease in perception of skills in database, web animation, programming, desktop publishing, digital video, and video audio. Although one might assume an undergraduate would indicate an increase in information and communication technology skills, this study found that often student’s perceptions of ability decline. However this decrease may be due to their increased awareness of the skills needed in the workforce.
This study describes the results of a survey and a description of instructional technologies in place in the social sciences in South African Universities. Lecturers in the social sciences reported a well-established practice of information and communication technologies (ICTs) use for general purposes (although frequent use tended to be for email and searching the Internet). They had a high self-efficacy in terms of using ICTs both generally and for teaching and learning, and a high enthusiasm for the use of ICTs for teaching and learning. Half the lecturers had started using ICTs recently with the introduction of learning management systems (LMSs) whereas the other half had established practices that preceded the mainstreaming of LMSs across universities. Only about a quarter of the respondents felt able to develop and update ICTs themselves which indicates that support is a necessary part of teaching with technology. In terms of different types of use the focus was on putting content on the web and course administration. Use of ICTs for teaching of skills (whether information literacy, problem solving or critical thinking) was infrequent. There were different types of ICT use across the different sub-disciplines. Lecturers reported factors which constrained their use of ICTs for teaching and learning, such as inadequate technology, pedagogical issues (e.g. plagiarism), and students opting out of lectures when materials were available online. It is argued that user studies in are relevant to the future delivery of educational material, in terms of removing barriers to use and targeting training and supportive activities.
Modeling offers a promising form of constructivist learning for students. By making and executing models of dynamic systems in a computer environment, students are stimulated to learn about the specific domain that is modeled as well as about the process of modeling in general. However, learning by modeling also leads to characteristic student mistakes, based on a combination of faulty domain knowledge and insufficient modeling skills. In this article, we describe a method of generating advice to students during their modeling process. The on-line advice system was informed by our observations of a teacher who gave advice via a textual communication tool to students building models with a System Dynamics model editor. The first version of the on-line advice system was evaluated in two ways: first, three teachers evaluated the advice the system generated for students’ final solutions; second, we analyzed the advice the system provided as it was used by a sample of students who were building a physics model. These evaluations showed that the overall approach, including matching a student solution to a family of reference solutions together with the other mechanisms of the advice system, is valid. However, they also highlighted the difficulty of building ‘intelligent’ support to help students to improve their models and gain modeling expertise. The article concludes with a discussion of our current efforts to improve the advice system based on the lessons learnt, which suggest extension of the range of solution representations and of the operations of the advice method.
This study focuses on carrying out weighted digraph-based mathematical construction of hypermedia and user navigation on hypermedia and making a presentation of “weighted” forms of known stratum and compactness. In the instructional Web design researches, the structural analysis of navigation on the hypermedia is important in modeling the behaviors that the learners perform while using this kind of media. Therefore, new conceptions of the presented usage of new measures towards this goal are also discussed within the scope of our study.
The rapid development of computer and network technologies has attracted researchers to investigate strategies for and the effects of applying information technologies in learning activities; simultaneously, learning environments have been developed to record the learning portfolios of students seeking web information for problem-solving. Although previous research has demonstrated the benefits of applying information technologies to learning activities, the difficulties in doing so have also been revealed. One of the major difficulties is the lack of a mechanism to assist teachers in evaluating the problem-solving ability of the students, such that constructive suggestions can be given to the students, and tutoring strategies can be improved accordingly. To cope with this problem, in this paper, an auto-scoring mechanism is developed to analyze the various information searching abilities of individual students. Indicators of information searching ability (ISA) are proposed based on the famous Big6 model and are adopted in our auto-scoring mechanism. Moreover, two experiments have been conducted to demonstrate the effectiveness of this innovative approach. The experimental results show high correlation between the scores of the auto-scoring mechanism and the manual scoring. Moreover, the feedbacks from 158 teachers also show that the innovative approach is highly accepted by the teachers.
With the growing demand in e-learning, numerous research works have been done to enhance teaching quality in e-learning environments. Among these studies, researchers have indicated that adaptive learning is a critical requirement for promoting the learning performance of students. Adaptive learning provides adaptive learning materials, learning strategies and/or courses according to a student’s learning style. Hence, the first step for achieving adaptive learning environments is to identify students’ learning styles. This paper proposes a learning style classification mechanism to classify and then identify students’ learning styles. The proposed mechanism improves k-nearest neighbor (k-NN) classification and combines it with genetic algorithms (GA). To demonstrate the viability of the proposed mechanism, the proposed mechanism is implemented on an open-learning management system. The learning behavioral features of 117 elementary school students are collected and then classified by the proposed mechanism. The experimental results indicate that the proposed classification mechanism can effectively classify and identify students’ learning styles.
This paper presents a description and evaluation of Myartspace, a service on mobile phones for inquiry-led learning that allows students to gather information during a school field trip which is automatically sent to a website where they can view, share and present it, back in the classroom or at home. The evaluation focused on three levels: a micro level, concerned with issues of usability; a meso level, which examined educational effectiveness in terms of learning breakthroughs and breakdowns; and a macro level, which looked at the impact of the new technology on school museum visits practice. Issues of implementing mobile learning across school and museum settings are identified and cross-level influences are discussed. The study showed that the service was effective in enabling students to gather information in a museum and this provided resources for effective construction and reflection in the classroom. Minor usability problems did not detract from the learning, however there are significant issues concerning how to structure the visit and on the viability of Myartspace as a regular service.
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