Gamification is often proposed as a promising solution to traditional e-learning systems by the incorporation of game elements and mechanisms to enhance the motivation, engagement and students’ learning. However, most current studies lack careful and thorough experimental evaluation on the effect of gamification and are normally applied to science learning for adults which makes it difficult to generalize the findings to other learning domains. This paper addresses this issue by offering a controlled experiment with 58 elementary school students studying a course on Arabic language to investigate the learning effect of gamification. The results indicate that gamification positively enhances the learning outcome and students’ learning motivation.
Perovskite solar cells (PSCs) have drawn significant consideration as a competing solar cell technology because of the drastic advance in their power conversion efficiency (PCE) over the last two decades. The interfaces between the electron transport layer (ETL) and the absorber layer and between the absorber layer and the hole transport layer (HTL) have a major impact on the performance of the PSCs. In this paper, we have investigated the defect interfaces between ETL/absorber layer and absorber layer/HTL of calibrated experimental lead-based and lead-free PSCs. The influence of the defect interfaces is studied in order to find the optimum value for the maximum possible PCE. While the PCE has not been enhanced considerably for the lead-based, it is boosted from 1.76% to 5.35% for lead-free PSCs. Also, bulk traps were found to have minor role in comparison with interface traps for the lead-free cell while they have a significant impact for the lead-based cell. The results presented in this work would shed some light on designing interface defects of various types of practical PSC structures and demonstrates the crucial impact of the interface defects on lead-free vs lead-based PSCs. All simulation studies are performed by using SCAPS-1D simulator.
Abstract. Designing effective adap tive e-learning systems, from a usability perspective, represents a challenge because of the complexity of adaptivity in order to meet the diverse requirements of learners. Furthermore, there is a lack of well-designed experimental evaluation of adaptive e-learning systems in general, and of their usability in particular. The aim of this paper is the presentation of an adaptive e-learning system based on learner knowledge and learning style, and of the results of an initial experimental evaluation of the usability of its two modes of operation. This involves comparing the usability of an adaptive version of the system with the usability of a non-adaptive version, in a learning environment with 75 participants. The experiment produced significant results; they indicate that an adaptive e-learning system based on learner knowledge and learning style has a higher level of perceived usability than a non-adaptive e-learning system. This may also increase the level of satisfaction, engagement and motivation of learners and therefore enhance their learning.
Abstract-Traditional e-learning systems have been, typically, designed for a generic learner, irrespective of individual knowledge, skills and learning styles. In contrast, adaptive elearning systems can enhance learning by taking into account different learner characteristics and by personalising learning material. Although a large number of systems incorporating learning style have been deployed, there is a lack of comprehensive, comparative evaluations. This paper attempts to bridge this gap by comparing a number of adaptive elearning systems. It considers three main perspectives: the learner model, the domain model and the adaptation model. A set of criteria is generated for each perspective, and applied to a representative sample of adaptive e-learning systems.
This paper proposes a gamification design model that can be used to design and develop gamified e-learning systems. Furthermore, a controlled and carefully designed experimental evaluation in terms of learning effectiveness of gamification is offered. The experiment was conducted with 44 participants randomly assigned to an experimental 'gamified' condition and a controlled 'non-gamified' condition. In both conditions the same learning material, to teach computer security, were used. The main difference between the two conditions was the integration of gamification in an e-learning system designed based on the proposed model. The results indicate that learning using the gamified version of the e-learning system produces better short-term and medium-term learning gain than learning using the non-gamified e-learning version. Future avenues of research are also provided.
Traditional e-learning systems are typically designed for generic learners irrespective of individual requirements. In contrast, adaptive e-learning systems take into account learner characteristics such as learning style and level of knowledge in order to provide more personalised learning. The contribution of this paper is threefold. First, a generic adaptive framework aimed at enhancing learning is proposed. Second, a specific approach to adaptivity based on learning style is put forward within the framework. Third, the framework is validated and the approach is evaluated in order to determine their effectiveness in learning provision in an adaptive e-learning system. An experiment conducted with 60 participants produced positive results. They indicate that adapting instructional material according to learning style yields significantly better learning outcome and learner satisfaction than without adaptation.
In this work, we report on the effect of substituting the active intrinsic i-layer on a conventional pin structure of lead-free perovskite solar cell (PSC) by a homo p-n junction, keeping the thickness of the active layer constant. It is expected that when the active i-layer is substituted by a p-n homo junction, one can increase the collection efficiency of the photo-generated electrons and holes due to the built-in electric field of the homo junction. The impact of the technological and physical device parameters on the performance parameters of the solar cell have been worked out. It was found that p-side thickness must be wider than the n-side, while its acceptor concentration should be slightly lower than the donor concentration of the n-side to achieve maximum efficiency. In addition, different absorber types, namely, i-absorber, n-absorber and p-absorber, are compared to the proposed pn-absorber, showing a performance-boosting effect when using the latter. Moreover, the proposed structure is made without a hole transport layer (HTL) to avoid the organic issues of the HTL materials. The back metal work function, bulk trap density and ETL material are optimized for best performance of the HTL-free structure, giving Jsc = 26.48, Voc = 0.948 V, FF = 77.20 and PCE = 19.37% for AM1.5 solar spectra. Such results highlight the prospective of the proposed structure and emphasize the importance of using HTL-free solar cells without deteriorating the efficiency. The solar cell is investigated by using SCAPS simulator.
Aim/Purpose: Effective e-learning systems need to incorporate student characteristics such as learning style and knowledge level in order to provide a more personalized and adaptive learning experience. However, there is a need to investigate how and when to provide adaptivity based on student characteristics, and more importantly, to evaluate its value in learning enhancement. This study aims to bridge that gap by examining the effect of different modes of learning material adaptation and their sequences to the learning style and knowledge level of students in e-learning systems. Background: E-learning systems aim to provide acceptability and interactivity between students, instructors, and learning content anytime and anywhere. However, traditional systems are typically designed for generic students irrespective of individual requirements. Successful e-learning systems usually consider student characteristics such as learning style and knowledge level to provide more personalized and adaptive student-system interaction. Methodology: A controlled experiment was conducted in a learning context with 174 subjects to evaluate the learning effectiveness of adaptivity in e-learning systems. Contribution: The main contributions of the paper are threefold. First, a novel adaptive approach is proposed based on a specific learning style model and knowledge level. Second, the approach is implemented in an e-learning system to teach computer security, the application domain. Third, a rigorous experimental evaluation of the learning effect of the adaptive approach is offered. Findings: The results indicate that adaptation according to the combination of learning style and knowledge level produces significantly better learning gains, both in the short-term and medium-term, than adaptation according to either trait individually. Recommendations for Practitioners: Practitioners should consider the combination of learning style and knowledge level when delivering and presenting learning material to their students. Recommendation for Researchers: Researchers should consider sound educational models when designing adaptive e-learning systems. Also, rigorous and carful experimental design evaluations should be taken into account. Impact on Society: Universities and e-learning industries can benefit from the proposed adaptive approach and the findings in designing and developing more personalized and adaptive e-learning systems. The incorporation of student characteristics, especially learning style and knowledge level, may be used to enhance learning. Future Research: The experiment might be duplicated with a focus on longer-term learning gains by including more subjects and more learning resources. Also, the study might be expanded to application domains other than computer security. Moreover, other variables such as student satisfaction, motivation, and affective state might be explored to further the understanding of the effect of adaptivity on learning gains.
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