Trialing cartoons: Teachers’ attitudes towards animation as an ELT instructional tool

This paper explores the attitudes of teachers, as adult learners, towards learning to do animation. A part of popular culture which second-language students enjoy, until recently, animation has been technically too demanding for non-specialists to learn. Adult learners can experience e-learning as transformative, but also as a barrier. Thus, teacher reception is crucial in exploring the feasibility of animation as an instructional tool in language teaching. In all, 44 Hong Kong and mainland Chinese teachers were taught animation over ten weeks. Subsequently, three surveys elicited both quantitative and qualitative data. Appraisal analysis indicated teachers positively realised animation as valuable, worthwhile and satisfactory, but also difficult and time-consuming, and entailed high levels of communication. Quantitative data indicated their view that animation would be well-received by both colleagues and secondary language learners, as an instructional tool.     

Cognitive effectiveness of visual instructional design languages

The introduction of learning technologies into education is making the design of courses and instructional materials an increasingly complex task. Instructional design languages are identified as conceptual tools for achieving more standardized and, at the same time, more creative design solutions, as well as enhancing communication and transparency in the design process. In this article we discuss differences in cognitive aspects of three visual instructional design languages (E²ML, PoEML, coUML), based on user evaluation. Cognitive aspects are of relevance for learning a design language, creating models with it, and understanding models created using it. The findings should enable language constructors to improve the usability of visual instructional design languages in the future. The paper concludes with directions with regard to how future research on visual instructional design languages could strengthen their value and enhance their actual use by educators and designers by synthesizing existing efforts into a unified modeling approach for VIDLs.     

Research and development of web-based virtual online classroom

To build a web-based virtual learning environment depends on information technologies, concerns technology supporting learning methods and theories. A web-based virtual online classroom is designed and developed based on learning theories and streaming media technologies. And it is composed of two parts: instructional communicating environment (ICE) and collaborative learning environment (CLE). ICE provides learners with learning materials, lecture videos, and interactive environment etc. CLE supports active learning by providing the environment with learning tools, learning materials and contextual discussion for learners. The environments are designed with event-based synchronous strategies and e-learning technologies standards.     

Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation

There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a multi-dimensional approach for LMS evaluation via six dimensions: (1) system quality, (2) service quality, (3) content quality, (4) learner perspective, (5) instructor attitudes, and (6) supportive issues. A survey instrument based on HELAM has been developed and applied to 84 learners. This sample consists of students at both undergraduate and graduate levels who are users of a web-based learning management system, U-Link, at Brunel University, UK. The survey instrument has been tested for content validity, reliability, and criterion-based predictive validity. The analytical results strongly support the appropriateness of the proposed model in evaluating LMSs through learners’ satisfaction. The explanatory factor analysis showed that each of the six dimensions of the proposed model had a significant effect on the learners’ perceived satisfaction. Findings of this research will be valuable for both academics and practitioners of e-learning systems.     

Utilizing learning process to improve recommender system for group learning support

With the rapid increasing of learning materials and learning objects in e-learning, the need for recommender system has also become more and more imperative. Although, the traditional recommendation system has achieved great success in many domains, it is not suitable to support e-learning recommender system because the approach in e-learning is hybrid and it is obtained mainly by two mechanisms: the learners’ learning processes and the analysis of social interaction. Therefore, this study proposes a flexible recommendation approach to satisfy this demand. The recommendation is designed based on a multidimensional recommendation model. Furthermore, we use Markov Chain Model to divide the group learners into advanced learners and beginner learners by using the learners’ learning activities and learning processes so that we can correctly estimate the rating which also include learners’ social interaction. The experimental result shows that the proposed system can give a more satisfying and qualified recommendation.     

Developing a Usability Evaluation Method for e-Learning Applications: Beyond Functional Usability

In this article, the development of a questionnaire-based usability evaluation method for e-learning applications is described. The method extends the current practice by focusing not only on cognitive but also affective considerations that may influence e-learning usability. The method was developed according to an established methodology in HCI research and relied upon a conceptual framework that combines Web and instructional design parameters and associates them with the most prominent affective learning dimension, which is intrinsic motivation to learn. The latter is proposed as a new usability measure that is considered more appropriate to evaluate e-learning designs. Two large empirical studies were conducted in order to evaluate usability of e-learning courses offered in corporate environments. The results provide valuable evidence for reliability and validity of the method, thus providing evidence that usability practitioners can use it with confidence when evaluating the design of e-learning applications.     

Student Behavior Modeling for an E-Learning System Offering Personalized Learning Experiences

With the advent of computing and communication technologies, it has become possible for a learner to expand his or her knowledge irrespective of the place and time. Web-based learning promotes active and independent learning. Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process. This digital learning improves the quality of teaching and also promotes educational equity. However, the challenges in e-learning platforms include dissimilarities in learner’s ability and needs, lack of student motivation towards learning activities and provision for adaptive learning environment. The quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional strategy. It is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning course. It is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest level. In this research work, a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective attainment. Catering to the demands of e-learner, an intelligent model is presented in this study for e-learning system that apply supervised machine learning algorithm. An adaptive e-learning system suits every category of learner, improves the learner’s performance and paves way for offering personalized learning experiences.     

Improving the development of instructional software: Three building-block solutions to interrelate design and production

Currently, there is a focus on authentic tasks as the driving force for learning in integrated e-learning systems. This sets new criteria for instructional software, which should become much more flexible and allow for domain modeling and pedagogical modeling. A theoretical analysis and a survey (n = 37) amongst experienced developers show that current development methods are insufficient to develop such instructional software. New development methods such as “lean production” promise to satisfy the new criteria as they emphasize mass-customization by rigorously applying a pull-principle throughout the whole development process. However, a potential bottleneck is the lack of design languages to transfer the design outcomes to the production phase. Three building-block solutions are proposed to overcome this transition problem: (1) a 3D-model to support designers in stratifying, elaborating, and formalizing design documents, (2) instructional software templates to support designers in producing software themselves, and (3) an integrative approach to support designers in reusing learning objects.     

Learning from instructional animations: How does prior knowledge mediate the effect of visual cues?

The purpose of this study was to investigate the effects of cueing and prior knowledge on learning and mental effort of students studying an animation with narration. This study employed a 2 (no cueing vs. visual cueing) × 2 (low vs. high prior knowledge) between‐subjects factorial design. The results revealed a significant interaction effect between prior knowledge and cueing on learning. Low prior knowledge learners had higher scores after studying an instructional animation with visual cues, compared to those who studied the same instructional animation without visual cues. Conversely, when cues were not provided, high prior knowledge learners outperformed those high prior knowledge learners who studied with the cued version of an instructional animation. These results indicated that the effects of cueing in an instructional animation change depending on the learners' level of prior knowledge. Specifically, low prior knowledge learners benefited more when visual cues were provided, whereas cues did not facilitate learning for high prior knowledge learners.     

Integration of metacognitive skills in the design of learning objects

Recent studies have demonstrated that specific instruction about metacognitive strategies improves achievement, the accuracy of knowledge monitoring, and the application of learning strategies in hypermedia environments. However, there are no models to date for instructional designers who design and develop learning objects for the incorporation of specific scaffolds to aid student reflection about their metacognitive skills; thus making it difficult to identify tasks to orientate learners in improving such skills. In this paper, we propose the use of specific ontologies as the basis for incorporating information about metacognition in learning objects so that a Learning Management System can select and recommend tasks designed for the development and/or improvement of the learners’ metacognitive skills within the context of e-learning.     

Experience beyond knowledge: Pragmatic e-learning systems design with learning experience

With the growing demand in e-learning system, traditional e-learning systems have dramatically evolved to provide more adaptive ways of learning, in terms of learning objectives, courses, individual learning processes, and so on. This paper reports on differences in learning experience from the learner’s perspectives when using an adaptive e-learning system, where the learner’s knowledge or skill level is used to configure the learning path. Central to this study is the evaluation of a dynamic content sequencing system (DCSS), with empirical outcomes being interpreted using Csikszentmihalyi’s flow theory (i.e., Flow, Boredom, and Anxiety). A total of 80 participants carried out a one-way between-subject study controlled by the type of e-learning system (i.e., the DCSS vs. the non-DCSS). The results indicated that the lower or medium achievers gained certain benefits from the DCSS, whilst the high achievers in learning performance might suffer from boredom when using the DCSS. These contrasting findings can be suggested as a pragmatic design guideline for developing more engaging computer-based learning systems for unsupervised learning situations.     

Towards useful and usable interaction design tools: CanonSketch

Despite all the effort dedicated to bringing better User-Centered Design (UCD) tools to market, current studies show that the industry is still dominated by tools that do not support the activities and workstyles of designers. Also, there is a growing need for interaction design tools aimed at software engineers, a problem related to bringing usability into the software engineering processes.

We propose a new workstyle model that can be effectively used to envision, design and evaluate a new generation of innovative interaction and software design tools, aimed at integrating usability and software engineering.

We illustrate the effectiveness of our model by describing a new tool, called CanonSketch, that was built in order to support UCD in terms of the dimensions in our workstyle model. We also describe an evaluation study aimed at contrasting paper prototyping with our tool as well as the level of workstyle support.     

A method toward dynamic e-learning services modeling and the cooperative learning mechanism

The advanced information technologies have made it possible for individuals to carry out cooperative learning efficiently and effectively from anywhere and at any time. To capitalize on the individual need and address the issues associated with the late entry into the e-learning area, it has great significance to study the service mechanism of CSCL on e-learning service and e-learning service computing modeling. This paper proposes an e-learning service model supporting for the life-cycle process management. The proposed model is developed by considering the learner’s behaviours during e-learning services, the scheduling policies, and the monitoring mechanism of learning activities. Business process modeling for e-learning services can be taken according to the study ordering of the knowledge points by using workflow modeling technology and process enactment mechanism. The overall life-cycle process management of knowledge is addressed by combining knowledge product modeling, knowledge resource modeling, and credit polices for member selection in research team by considering trust value of learners, advisers and providers in e-learning services. The proposed method can be used for supporting the sustainable development of e-learning services from planning and design, organizing e-learning process, maintenance of the e-learning process, to process improvement, as well as to support learners and advisers to effectively complete innovative team study and complex computation study. Lastly, an extended topic map tool has been developed by adding a knowledge requirement level and an information extraction tool to validate the proposed methodology. These tools can used to guide learners to concentrate on the required knowledge topics and drive knowledge providers to redevelop outdated knowledge hierarchy.     

How do instructional designers use automated instructional design tool?

The purpose of this study was to investigate the use of an automated design tool by naive, novice, and expert instructional designers. A talk-aloud protocol, attitude survey, performance assessment, and direct observation were used to gather data. While the expert designers used the tool, they used it as a word processor with a rich database of instructional strategies. The novice designers relied on the tool for advice, guidance, and assistance in completing all the design tasks. Non-designers used the tool for learning about design.     

A new e-learning achievement evaluation model based on RBF-NN and similarity filter

As Internet rises fast in recent decades, teaching and learning tools based on Internet technology are rapidly applied in education. Learning through Internet can make learners absorb knowledge without the limitations on learning time and distance. Therefore, in academy, e-learning is one of the popular learning assistant instruments. Recently, “student-centered” instruction has become one of the primary approaches in education, and the e-learning system, which can provide the learning environment of personalization and adaptability, is more and more popular. By using e-learning system, teachers can adjust the learning schedule instantly for learners according to their learning achievements, and build more adaptive learning environments. However, in some cases, bias assessments are given for student achievements under specific uncontrollable conditions (i.e. tiredness, preference). In dire need of overcoming this predicament, a new model based on radial basis function neural networks (RBF-NN) and similarity filter to evaluate learning achievements is proposed. The proposed model includes three phases to reduce bias assessments: (1) preprocess: select important features (attributes) to enhance classification performance by feature selection methods and utilize minimal entropy principle approach (MEPA) to fuzzify the quantitative data, (2) similarity filter: select linguistic values for each feature and delete inconsistent data by the similarity threshold (similarity filter) and (3) construct classification model and accuracy evaluation: build the proposed model based on RBF-NN and evaluate model performance. To verify the proposed model, a practical achievement dataset, collected from e-learning online examination system in a university of Taiwan, is used as experiment dataset, and the performance of the proposed model is compared with the listing models in this paper. From the empirical study, it is shown that the proposed model provided more proper achievement evaluations than the listing models.     

Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation

There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a multi-dimensional approach for LMS evaluation via six dimensions: (1) system quality, (2) service quality, (3) content quality, (4) learner perspective, (5) instructor attitudes, and (6) supportive issues. A survey instrument based on HELAM has been developed and applied to 84 learners. This sample consists of students at both undergraduate and graduate levels who are users of a web-based learning management system, U-Link, at Brunel University, UK. The survey instrument has been tested for content validity, reliability, and criterion-based predictive validity. The analytical results strongly support the appropriateness of the proposed model in evaluating LMSs through learners’ satisfaction. The explanatory factor analysis showed that each of the six dimensions of the proposed model had a significant effect on the learners’ perceived satisfaction. Findings of this research will be valuable for both academics and practitioners of e-learning systems.     

Development and application of internet of things educational tool based on peer to peer network

With growing interest in IoT across the Peer-to-Peer network industry, basic education programs on IoT for learners are expanding. The purpose of this study was to analyze the difficulties met by learners in basic IoT education, to design and develop hardware tool, and to evaluate the usability of these tool. In this study, the needs of teachers and learners on the tools were analyzed, and design guidelines established. The design guidelines, based on the analysis of needs, suggest the functions of hardware board, miniaturization of board, modularization of sensor parts, and usability and expandability of the tool. A hardware board is designed and developed based on the guidelines. The developed board is then used for basic education on IoT for learners, and the usability of the board is evaluated. The results showed that the new hardware tools provide higher usability than the existing Arduino board. This study is meaningful in that it provides a reference for future IoT educational tools, and that it highlights the importance of promoting learner-centered education.     

A comprehensive framework for the evaluation of ontology modularization

The Semantic Web and ontologies have received increased attention in recent years. The delivery of well-designed ontologies enhances the effect of Semantic Web services, but building ontologies from scratch requires considerable time and effort. Modularizing ontologies and integrating ontology modules to a given context help users effectively develop ontologies and revitalize ontology dissemination. Therefore, various tools for modularizing ontologies have been developed. However, selecting an appropriate tool to fit a given context is difficult because the assumptions for the approaches greatly vary. Therefore, a suitable framework is required to compare and help screen the most suitable modularization tool.In this research, we propose a new evaluation framework for selecting an appropriate ontology modularization tool. We present three aspects of tool evaluation as the main dimensions for the assessment of modularization tools: tool performance, data performance, and usability.This study provides an implicit evaluation and an empirical analysis of three modularization tools. It also provides an evaluation method for ontology modularization, enabling ontology engineers to compare different modularization tools and easily choose an appropriate one for the production of qualifying ontology modules.The experimental results indicate that the proposed evaluation criteria for ontology modularization tools are valid and effective. This research provides a useful method for assessing and selecting ontology modularization tools. Modularization performance, data performance, and usability are the three modularization aspects designed and applied to the context of ontology. We provide a new focus on the comprehensive framework to evaluate the performance and usability of ontology modularization tools. The proposed framework should be of value to both ontology engineers, who are interested in ontology modularization, and to practitioners, who need information on how to evaluate and select a specific type of ontology tool in accordance with the requirements of the individual environment.     

An attribute-based ant colony system for adaptive learning object recommendation

Teachers usually have a personal understanding of what “good teaching” means, and as a result of their experience and educationally related domain knowledge, many of them create learning objects (LO) and put them on the web for study use. In fact, most students cannot find the most suitable LO (e.g. learning materials, learning assets, or learning packages) from webs. Consequently, many researchers have focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and to adaptively provide learning paths. However, although most personalized learning mechanism systems neglect to consider the relationship between learner attributes (e.g. learning style, domain knowledge) and LO’s attributes. Thus, it is not easy for a learner to find an adaptive learning object that reflects his own attributes in relationship to learning object attributes. Therefore, in this paper, based on an ant colony optimization (ACO) algorithm, we proposed an attributes-based ant colony system (AACS) to help learners find an adaptive learning object more effectively. Our paper makes three critical contributions: (1) It presents an attribute-based search mechanism to find adaptive learning objects effectively; (2) An attributes-ant algorithm was proposed; (3) An adaptive learning rule was developed to identify how learners with different attributes may locate learning objects which have a higher probability of being useful and suitable; (4) A web-based learning portal was created for learners to find the learning objects more effectively.     

An exploratory study using inexpensive electroencephalography (EEG) to understand flow experience in computer-based instruction

Flow is an optimal experience that results in intense engagement in an activity. In computer-based instructional environment, flow can be used to examine learning performance. We used questionnaire survey and electroencephalography (EEG) analysis to examine the influence of challenge-skill balance on the flow experience and influence of flow experience on learning performance in a computer-based instructional environment. The results showed that the flow experience of learners depends on challenge-skill balance of learning materials. The research explored the possibility of using an inexpensive non-medical EEG device to research the association between flow experience and challenge-skill balance in educational information systems.