Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Evaluation of learners’ attitude toward learning in ARIES augmented reality environments

The ARIES system for creating and presenting 3D image-based augmented reality learning environments is presented. To evaluate the attitude of learners toward learning in ARIES augmented reality environments, a questionnaire was designed based on Technology Acceptance Model (TAM) enhanced with perceived enjoyment and interface style constructs. For empirical study, a scenario of a chemistry experimental lesson was developed. The study involved students of the second grade of lower secondary school. As follows from this study, perceived usefulness and enjoyment had a comparable effect on the attitude toward using augmented reality environments. However, perceived enjoyment played a dominant role in determining the actual intention to use them. The interface style based on physical markers had significant impact on perceived ease of use. Interface style and perceived ease of use had a weak influence on perceived enjoyment. In contrast, these two constructs had a significantly stronger influence on perceived usefulness.     

Recommending suitable learning paths according to learners’ preferences: Experimental research results

The paper deals with the problem of personalising learning units with the main focus on finding personalised learning paths in learning units. Finding suitable learning paths is based on students’ needs in terms of their learning styles. It has been shown that learning path in static and dynamic learning units can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model, mainly by adapting ant colony optimisation method based on collaboration and pheromones. In the paper, experimental results of applying the proposed approach in practise are presented. The results of empirical experiment have shown that learning in the proposed prototype of e-learning system applying created recommending method improves students’ learning results and saves their learning time. This fact indicates that the developed adaptive method for personalising learning units is practically applicable in e-learning and enhances the learning quality.     

Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

Do learners’ characteristics matter? An exploration of mobile-learning adoption in self-directed learning

This paper aims to identify individual characteristics that motivate learners to use mobile-learning. It sheds light on our current knowledge by a) examining an m-learning adoption model which accounts for learners’ characteristics (learning style and personal innovativeness) in addition to previously studied mobile platform characteristics and b) considering the context in which learning occurs (formal and informal). A framework has been introduced and empirically tested. Results suggest that individuals’ learning style and perceived playfulness influence m-learning usage in both learning situations; while performance expectancy and personal innovativeness are only influential in specific learning contexts. This study highlights the role of learners’ characteristics in m-learning adoption and emphasizes the importance of distinguishing between various types of m-learning. This multi-disciplinary research enriches m-learning literature and offers practical implications for educators using mobile technologies as well as developers of virtual learning platforms.     

Smart antenna technology in 3G system

This paper introduces the operational principles of smart antenna （SA） and its key functions in mobile communications, and analyzes the application of SA in 3G communications system with some utility issues. At the end of this paper, an outlook of the applications of SA is given.     

A task–technology fit view of learning management system impact

Learning management systems (LMSs) are very widely used in higher education. However, much of the research on LMSs has had a technology focus or has been limited to studies of adoption. In order to take advantage of the potential associated with LMSs, research that addresses the role of LMSs in learning success is needed. Task–technology fit is one factor that has been shown to influence both the use of information systems and their performance impacts. The study described in this paper used the technology-to-performance chain as a framework to address the question of how task–technology fit influences the performance impacts of LMSs. The results provide strong support for the importance of task–technology fit, which influenced perceived impact on learning both directly and indirectly via level of utilization. Whilst task–technology fit had a strong influence on perceived impact of the LMS on learning it only had a weak impact on outcomes in terms of student grades. Contrary to expectations, facilitating conditions and common social norms did not play a role in the performance impacts of LMSs. However, instructor norms had a significant effect on perceived impact on learning via LMS utilization.     

An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning

Learning management system (LMS) is playing a major role in higher academic institutions worldwide. Even though full e-learning is becoming a feasible strategy for a number of institutions in the world, some institutions, especially those in developing countries, are resisting a full e-learning environment. Consequently, these academic institutions initially adopt LMS for blended learning to assess their readiness for full e-learning transformation. There are a number of studies that investigate the determinants of full e-learning, but very limited studies investigate the link between learners’ perception of blended learning and full e-learning. The objective of this study was to link learners’ adoption (perceived ease of use, perceived usefulness (PU) and satisfaction) of LMS in blended learning and their personal characteristics (self-efficacy, technology experience and personal innovativeness) to their intention to use full e-learning. Data were collected through a questionnaire from 512 learners in Oman. The study found that personal innovativeness, PU and satisfaction of LMS in blended learning are significant to learners’ intention to engage in full e-learning. Thus, learners’ adoption of LMS in blended learning boosts their intention to full e-learning. The results provide useful insights for practitioners and researchers on full e-learning planning and strategy.     

Internet technology in support of the concept of “communities-of-practice”: the case of Xerox

Work practices usually differ fundamentally from the way that organizations describe their operations in manuals, training programs, etc. This paper focuses on the way that certain work practices are supported at Xerox, and the conclusions of this effort are related to complementary investigations on learning and innovation. Here we propose that the combination of work, learning and innovation should be reconsidered within the framework of informal “communities-of-practice.” Information Technology tends to be used in order to reinforce the old work and study paradigms. This paper suggests a different use of IT, a use especially well suited to intra- and internets, with the aim of supporting informal structures rather than formal procedures. The case of Xerox Corporation is used as an example.     

Video-based learners’ observed attention estimates for lecture learning gain evaluation

Multimedia Tools and Applications - A significant problem in the field of higher education is maintaining learners’ attention during lectures, which is known to significantly affect their...     

Student teachers’ satisfaction for blended learning via Edmodo learning management system

In a digitally driven world, behaviours of future teachers for blended learning (both face-to-face and on-line classes) need to be examined. This study serves three purposes. The first is to examine student teachers’ preferences for Community-of-Inquiry model-driven blended learning via Edmodo. Second, predicting student satisfaction on b-learning from a combination of four variables (gender, having internet access, using the internet for information access, and previous experience in on-line learning) was questioned. And third, b-learning orientations of participants were investigated. One of the mixed methods, the concurrent triangulation design was employed in which both qualitative and quantitative methods were applied. The study group included 135 freshmen and junior students (29 males and 106 females) from a western Turkish educational faculty. The findings for the first question indicated that 70.4% of student teachers prefer b-learning. For the second, 15% of the variance in satisfaction on b-learning was explained by the proposed model with a medium effect. And for the third, the qualitative findings were discussed under Perceived Usefulness (PU) and Perceived Uselessness and Unease-of-Use (PU-UU) themes. Although less than a quarter of participants found b-learning useless, most held positive notions for b-learning practices via Edmodo.     

A mobile-agent-based approach to software coordination in the HOOPE system

Software coordination is central to the construction of large-scale high-performance distributed applications with software services scattered over the decentralized Internet. In this paper, a new mobile-agent-based architecture is proposed for the utilization and coordination of geographically distributed computing resources. Under this architecture, a user application is built with a set of software agents that can travel across the network autonomously. These agents utilize the distributed resources and coordinate with each other to complete their task. This approach' s advantages include the natural expression and flexible deployment of the coordination logic, the dynamic adaptation to the network environment and the potential of better application performance. This coordination architecture, together with an object-oriented hierarchical parallel application framework and a graphical application construction tool, is implemented in the HOOPE environment, which provides a systematic support for the de     

Adaptation of an automotive dialogue system to users’ expertise and evaluation of the system

Spoken dialogue systems (SDSs) can be used to operate devices, e.g. in the automotive environment. People using these systems usually have different levels of experience. However, most systems do not take this into account. In this paper, we present a method to build a dialogue system in an automotive environment that automatically adapts to the user’s experience with the system. We implemented the adaptation in a prototype and carried out exhaustive tests. Our usability tests show that adaptation increases both user performance and user satisfaction. We describe the tests that were performed, and the methods used to assess the test results. One of these methods is a modification of PARADISE, a framework for evaluating the performance of SDSs [Walker MA, Litman DJ, Kamm CA, Abella A (Comput Speech Lang 12(3):317–347, 1998)]. We discuss its drawbacks for the evaluation of SDSs like ours, the modifications we have carried out, and the test results.

Synthetic speech in foreign language learning: an evaluation by learners

Can synthetic speech be utilized in foreign language learning as natural speech? In this paper, we evaluated synthetic speech from the viewpoint of learners in order to find out an answer. The results pointed out that learners do not recognize remarkable differences between synthetic voices and natural voices for the words with short vowels and long vowels when they try to understand the meanings of the sounds. The data explicates that synthetic voice utterances of sentences are easier to understand and more acceptable by learners compared to synthetic voice utterances of words. In addition, the ratings on both synthetic voices and natural voices strongly depend upon the learners’ listening comprehension abilities. We conclude that some synthetic speech with specific pronunciations of vowels may be suitable for listening materials and suggest that evaluating TTS systems by comparing synthetic speech with natural speech and building a lexical database of synthetic speech that closely approximates natural speech will be helpful for teachers to readily use many existing CALL tools.     

Good intentions: drivers’ decisions to engage with technology on the road and in a driving simulator

Distraction-related accidents are, more often than not, due to the drivers’ voluntarily engagement with a secondary task. Therefore, the strategic management of in-vehicle tasks and the drivers’ decision to engage with them is an important aspect of the driver distraction phenomenon that needs to be addressed. While the consequences of distracting tasks are often assessed in settings where the risk of engaging is reduced (i.e., simulators), the drivers’ decision to engage with secondary tasks is often ignored. This study assessed the drivers’ decision to engage with secondary tasks using verbal protocols to provide insights into the drivers’ intention within a naturalistic driving setting, on the road, and in a simulated driving environment. This enabled an understanding of when drivers engage with technological distractions, why they choose to do so, as well as how they may go about doing it. Different road types were found to differentially impact the drivers’ intention to engage, as did the types of secondary tasks, with some tasks having an increased willingness to engage compared to others. Factors that increase and/or reduce the likelihood of engaging are presented. The decisions that drivers made to engage with secondary tasks in the simulator were found to correlate strongly to their decision to so on the road. This provides support for the use of simulators when assessing the drivers’ decision to engage with secondary tasks. The effect of verbal protocols on the drivers’ speed metrics was assessed to determine how they may have affected their driving performance.     

A decision system using fuzzy cognitive map and multi-group data envelopment analysis to estimate hospitals’ outputs level

Due to its vital role in healthcare system, performance evaluation of hospitals is indispensable. In addition, hospitals try to achieve desired and efficient conditions by careful planning based on their present facilities. Several studies have been conducted on hospital evaluation, but nearly none of them has taken into consideration the difference in the nature of performance in respect of hospitals’ managerial construction, funding, and type of services provided by them. Furthermore, hospitals’ outputs have not been estimated in respect of cause and effect relationships between inputs and outputs for achieving efficient conditions. In the present study, first, a new approach for hospital evaluation is presented according to the differences in the nature of their performances while categorized in groups. Then, optimal outputs for each hospital in its own group are dealt with using results obtained from multi-group data envelopment analysis and the method of fuzzy cognitive map. The activation Hebbian learning (AHL) algorithm is adapted to the concept of efficiency and is conducted to estimate the outputs of inefficient hospitals. In the present study, 27 hospitals located in the provincial capitals in northwest of Iran are categorized in four groups including general governmental hospitals, specialty governmental hospitals, private hospitals, and social security hospitals. Afterward, optimal outputs are estimated for the inefficient hospitals by using the proposed modified AHL algorithm. The results indicate that when the hospitals have been evaluated in groups, efficiency scores of hospitals have changed. Also, given the cause and effect relationships between inputs and outputs in each group can help to decision and policy makers to estimate the optimal outputs that have caused inefficient hospitals become efficient.

     

Can the use of cognitive and metacognitive self-regulated learning strategies be predicted by learners’ levels of prior knowledge in hypermedia-learning environments?

Research on self-regulated learning (SRL) in hypermedia-learning environments is a growing area of interest, and prior knowledge can influence how students interact with these systems. One hundred twelve (N = 112) undergraduate students’ interactions with MetaTutor, a multi-agent, hypermedia-based learning environment, were investigated, including how prior knowledge affected their use of SRL strategies. We expected that students with high prior knowledge would engage in significantly more cognitive and metacognitive SRL strategies, engage in different sequences of SRL strategies, spend more time engaging in SRL processes, and visit more pages that were relevant to their sub-goals than students with low prior knowledge. Results showed significant differences in the total use of SRL strategies between prior knowledge groups, and more specifically, revealed significant differences in the use of each metacognitive strategy (e.g., judgment of learning), but not each cognitive strategy (e.g., taking notes) between prior knowledge groups. Results also revealed different sequences of use of SRL strategies between prior knowledge groups, and that students spent different amounts of time engaging in SRL processes; however, all students visited similar numbers of relevant pages. These results have important implications on designing multi-agent, hypermedia environments; we can design pedagogical agents that adapt to students’ learning needs, based on their prior knowledge levels.     

The role of self-determination theory in explaining teachers’ motivation to continue to use e-learning technology

Based on self-determination theory, this study proposes an extended information systems continuance theory in the context of teachers’ utilization of e-learning technology in connection with on-site courses. In the proposed model teachers’ extrinsic motivation (i.e. perceived usefulness), confirmation of pre-acceptance expectations and intrinsic motivation are predicted to be influenced by perceived autonomy, perceived competence and perceived relatedness. Even though information systems continuance theory has received quite extensive attention in prior research, this study is among the first to examine the effects of self-determination theory constructs in the context of teachers’ utilization of e-learning technology. The results show that extension of IS-continuance theory with constructs that represent users’ basic psychological needs and intrinsic motivation can be useful for predicting their e-learning continuance intentions.