Mining e-Learning domain concept map from academic articles

Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials, designers need to refer to the concept map of a subject domain. Moreover, concept maps can show the whole picture and core knowledge about a subject domain. Research from literature also suggests that graphical representation of domain knowledge can reduce the problems of information overload and learning disorientation for learners. However, construction of concept maps typically relied upon domain experts in the past; it is a time consuming and high cost task. Concept maps creation for emerging new domains such as e-Learning is even more challenging due to its ongoing development nature. The aim of this paper is to construct e-Learning domain concept maps from academic articles. We adopt some relevant journal articles and conference papers in e-Learning domain as data sources, and apply text-mining techniques to automatically construct concept maps for e-Learning domain. The constructed concept maps can provide a useful reference for researchers, who are new to the e-Leaning field, to study related issues, for teachers to design adaptive learning materials, and for learners to understand the whole picture of e-Learning domain knowledge.     

What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction

E-learning is emerging as the new paradigm of modern education. Worldwide, the e-learning market has a growth rate of 35.6%, but failures exist. Little is known about why many users stop their online learning after their initial experience. Previous research done under different task environments has suggested a variety of factors affecting user satisfaction with e-Learning. This study developed an integrated model with six dimensions: learners, instructors, courses, technology, design, and environment. A survey was conducted to investigate the critical factors affecting learners’ satisfaction in e-Learning. The results revealed that learner computer anxiety, instructor attitude toward e-Learning, e-Learning course flexibility, e-Learning course quality, perceived usefulness, perceived ease of use, and diversity in assessments are the critical factors affecting learners’ perceived satisfaction. The results show institutions how to improve learner satisfaction and further strengthen their e-Learning implementation.     

Automatic generation of temporal planning domains for e-learning problems

AI Planning & Scheduling techniques are being widely used to adapt learning paths to the special features and needs of students both in distance learning and lifelong learning environments. However, instructors strongly rely on Planning & Scheduling experts to encode and review the domains for the planner/scheduler to work. This paper presents an approach to automatically extract a fully operational HTN planning domain and problem from a learning objects repository without requiring the intervention of any planning expert, and thus enabling an easier adoption of this technology in practice. The results of a real experiment with a small group of students within an e-Learning private company in Spain are also shown.     

基于.NET的毕业论文在线指导系统的设计与实现

设计和实现了一个基于校园网络的毕业论文指导系统.该系统使毕业论文指导老师高效地对学生进行指导,改变传统论文指导方式,提供快捷即时的在线答疑与交流,解决指导教师和学生的协作交互,提高工作效率,同时便于导师及时了解论文进度.以.NET为开发平台,使系统具有高安全性、可集成性和交互性.     

Writing power into online discussion

This article considers the way in which control of interaction emerges as a function of personal agency and external factors in a group of students engaged in online asynchronous text-based communication in a distance education program. It is structured around the argument that control is partly related to the power that individuals have to give effect to their wishes, but also acknowledges that this sense of agency is always in relation to the powers of others and more structural constraints. A picture emerges of the choices students make in deciding when to initiate discussion and respond to others, and about decisions concerning whose messages they would read and when. The impact of other students, of online groups, and instructors seems to play an important role in determining how participants participate in online interaction. Consideration of broader issues shows how the context in which students engage in interaction impacts the nature and extent of that interaction. The article concludes that being aware, and taking advantage of the socially grounded nature of online interaction provides the basis from which educators can act to ensure that interaction in online learning communities is enabling for the learning of all students.     

Exploring Online Learners' Interactive Dynamics by Visually Analyzing Their Time‐anchored Comments

MOOCs (Massive Open Online Courses) are increasingly prevalent as an online educational resource open to everyone and have attracted hundreds of thousands learners enrolling these online courses. At such scale, there is potentially rich information of learners' behaviors embedded in the interactions between learners and videos that may help instructors and content producers adjust the instructions and refine the online courses. However, the lack of tools to visualize information from interactive data, including messages left to the videos at particular timestamps as well as the temporal variations of learners' online participation and perceived experience, has prevented people from gaining more insights from video‐watching logs. In this paper, we focus on extracting and visualizing useful information from time‐anchored comments that learners left to specific time points of the videos when watching them. Timestamps as a kind of metadata of messages can be useful to recover the interactive dynamics of learners occurring around the videos. Therefore, we present a visualization system to analyze and categorize time‐anchored comments based on topics and content types. Our system integrates visualization methods of temporal text data, namely ToPIN and ThemeRiver, which can help people understand the quality and quantity of online learners' feedback and their states of learning. To evaluate the proposed system, we visualized time‐anchored commenting data from two online course videos, and conducted two user studies participated by course instructors and third‐party educational evaluators. The results validate the usefulness of the approach and show how the quantitative and qualitative visualizations can be used to gain interesting insights around learners' online learning behaviors.     

Mobile educational features in authoring tools for personalised tutoring

One important field where mobile technology can make significant contributions is Education. In the fast pace of modern life, students and instructors would appreciate using constructively some spare time that they may have, in order to work on lessons at any place, even when away from offices, classrooms and labs where computers are usually located. In this paper, we describe a mobile authoring tool that we have developed and is called Mobile Author. Mobile Author can be used by human instructors either from a computer or a mobile phone to create their own Intelligent Tutoring Systems (ITSs) and to distribute them to their students. After the ITSs have been created, students can also use any computer or mobile phone to have access to theory and tests. The tutoring systems can assess the students' performance, inform the data-bases that record the students' progress and provide advice adapted to the needs of individual students. Finally, instructors can monitor their students' progress and communicate with their students during the course. The mobile features of both the authoring tool itself and the resulting ITSs from it have been evaluated by instructors and students, respectively. The results of the evaluation showed that mobile features are indeed considered useful.     

Adaptive feedback generation to support teachers in web-based distance education

This work examines the application of user-adapted technologies to address problems experienced in web-based distance education. We have proposed an approach to support distance learning instructors by offering advice that points at problems faced by students and suggests possible activities to address these problems. The paper describes an original feedback generation framework which utilises student, group and class models derived from tracking data in web course management systems, and follows a taxonomy of feedback categories to recognise situations that are brought to the instructors’ attention. The results of an empirical study in an online learning course point at benefits of the generated feedback to both instructors and students. Teachers can get a better understanding of their students by knowing what problems they may be facing, when they are behind or ahead of their peers, who can help them and how, and what roles can be assigned in discussion forums. This, in turn, can have a positive effect on students who can receive feedback tailored to their needs and problems. The evaluation study points at issues that can be related in general to planning empirical evaluations of user-adapted systems in realistic web-based learning settings.     

What we have here is a failure to communicate: the criticality of writing in online instruction

This article addresses how online instructors can improve their email communications with students. The characteristics and demands of online instruction are described and characterized as depending on the instructor’s ability to communicate in writing. A model to guide instructors in their online communications, the Golden Triangles of Online Communication, is presented. The first triangle underscores the criticality of considering (a) the online learning environment context, (b) the learner, and (c) the learning task. The second triangle presents three critical questions that instructors using online communications must quickly answer (a) What is this about? (b) Why should I care? and (c) What am I supposed to do? The Golden Triangles represent an effort to provide assistance to instructors in the difficult task of providing high quality instruction with high student satisfaction in online learning. In the final analysis, we underscore the importance of instructors’ writing skills in effective and appealing online in teaching.     

Examining students’ online interaction in a live video streaming environment using data mining and text mining

This study analyses the online questions and chat messages automatically recorded by a live video streaming (LVS) system using data mining and text mining techniques. We apply data mining and text mining techniques to analyze two different datasets and then conducted an in-depth correlation analysis for two educational courses with the most online questions and chat messages respectively. The study found the discrepancies as well as similarities in the students’ patterns and themes of participation between online questions (student–instructor interaction) and online chat messages (student–students interaction or peer interaction). The results also identify disciplinary differences in students’ online participation. A correlation is found between the number of online questions students asked and students’ final grades. The data suggests that a combination of using data mining and text mining techniques for a large amount of online learning data can yield considerable insights and reveal valuable patterns in students’ learning behaviors. Limitations with data and text mining were also revealed and discussed in the paper.     

Paying attention to adult learners online: The pedagogy and politics of community

Our article profiles the evolution of a fully online writing course designed for adult learners in our university's Prior Learning Assessment Program. Based on our own observations and experiences teaching adult learners online, we question if the virtual learning environment presents different challenges and prospects for the adult learner versus the traditional student learner, along with an extension and complication of the more social metaphors of “virtual community.” Moreover, because of the changing demographic from traditional to adult students, we argue that this change also fosters a change in the relationship between teachers and students. In chronicling this relationship, we note problems when the labor of adult education becomes invisible to those supervising online instructors. Because of these “invisible” labor issues, we argue that successful online instruction must include a range of interactions between students and instructors that extend the more public concept of community to better acknowledge the importance of personal, private interaction. Thus, we conclude with a call to rethink our online writing pedagogies to be more flexible to adult learner needs and learning styles, simultaneously recognizing the impact of adult online education on faculty workload.     

Exploring creative thinking in graphically mediated synchronous dialogues

This paper reports on an aspect of the EC funded Argunaut project which researched and developed awareness tools for moderators of online dialogues. In this study we report on an investigation into the nature of creative thinking in online dialogues and whether or not this creative thinking can be coded for and recognized automatically such that moderators can be alerted when creative thinking is occurring or when it has not occurred after a period of time. We outline a dialogic theory of creativity, as the emergence of new perspectives from the interplay of voices, and the testing of this theory using a range of methods including a coding scheme which combined coding for creative thinking with more established codes for critical thinking, artificial intelligence pattern-matching techniques to see if our codes could be read automatically from maps and ‘key event recall’ interviews to explore the experience of participants. Our findings are that: (1) the emergence of new perspectives in a graphical dialogue map can be recognized by our coding scheme supported by a machine pattern-matching algorithm in a way that can be used to provide awareness indicators for moderators; (2) that the trigger events leading to the emergence of new perspectives in the online dialogues studied were most commonly disagreements and (3) the spatial representation of messages in a graphically mediated synchronous dialogue environment such as Digalo may offer more affordance for creativity than the much more common scrolling text chat environments. All these findings support the usefulness of our new account of creativity in online dialogues based on dialogic theory and demonstrate that this account can be operationalised through machine coding in a way that can be turned into alerts for moderators.     

Towards computational discourse analysis: A methodology for mining Twitter backchanneling conversations

In this paper we present a methodology to analyze and visualize streams of Social Media messages and apply it to a case in which Twitter is used as a backchannel, i.e. as a communication medium through which participants follow an event in the real world as it unfolds. Unlike other methods based on social networks or theories of information diffusion, we do not assume proximity or a pre-existing social structure to model content generation and diffusion by distributed users; instead we refer to concepts and theories from discourse psychology and conversational analysis to track online interaction and discover how people collectively make sense of novel events through micro-blogging. In particular, the proposed methodology extracts concept maps from twitter streams and uses a mix of sentiment and topological metrics computed over the extracted concept maps to build visual devices and display the conversational flow represented as a trajectory through time of automatically extracted topics. We evaluated the proposed method through data collected from the analysis of Twitter users’ reactions to the March 2015 Apple Keynote during which the company announced the official launch of several new products.     

Mobolic: An automated approach to exercising mobile application GUIs using symbiosis of online testing technique and customated input generation

The increasingly prevalent use of mobile devices has raised the popularity of mobile applications. Therefore, automated testing of mobile applications has become an extremely important task. However, it is still a challenge to automatically generate tests with high coverage for mobile applications due to their specific nontrivial structure and the highly interactive nature of graphical user interfaces (GUIs). In this paper, we propose a novel automated GUI testing technique for mobile applications, namely, Mobolic. In this approach, tests with high coverage are automatically generated and executed by combining the online testing technique and customated input generation. Employing the online testing technique, Mobolic systematically explores the app GUI without falling in a loop. It generates relevant events “on the fly” that are followed by an immediate execution. In addition, involving the customated input generation, Mobolic automatically generates relevant user inputs such as user‐predefined, concrete, or random ones. We implemented Mobolic and evaluated its performance on 10 real‐world open‐source Android applications. Our experimental results show the effectiveness and efficiency of Mobolic in terms of achieved code coverage and overall exercising time.     

Developing an assessment-centered e-Learning system for improving student learning effectiveness

This research used Web-based two-tier diagnostic assessment and Web-based dynamic assessment to develop an assessment-centered e-Learning system, named the ‘GPAM-WATA e-Learning system.’ This system consists of two major designs: (1) personalized dynamic assessment, meaning that the system automatically generates dynamic assessment for each learner based on the results of the pre-test of the two-tier diagnostic assessment; (2) personalized e-Learning material adaptive annotation, meaning that the system annotates the e-Learning materials each learner needs to enhance learning based on the results of the pre-test of the two-tier diagnostic assessment and dynamic assessment. This research adopts a quasi-experimental design, applying GPAM-WATA e-Learning system to remedial Mathematics teaching of the ‘Speed’ unit in an elementary school Mathematics course. 107 sixth-graders from four classes in an elementary school participated in this research (55 male and 52 female). With each class as a unit, they were divided into four different e-Learning models: (1) the personalized dynamic assessment and personalized e-Learning material adaptive annotation group (n = 26); (2) the personalized dynamic assessment and non-personalized e-Learning material adaptive annotation group (n = 28); (3) the non-personalized dynamic assessment and personalized e-Learning material adaptive annotation group (n = 26); and (4) the non-personalized dynamic assessment and non-personalized e-Learning material adaptive annotation group (n = 27). Before remedial teaching, all students took the prior knowledge assessment and the pre-test of the summative assessment and two-tier diagnostic assessment. Students then received remedial teaching and completed all teaching activities. After remedial teaching, all students took the post-test of the summative assessment and two-tier diagnostic assessment. It is found that compared to the e-Learning models without personalized dynamic assessment, e-Learning models with personalized dynamic assessment are significantly more effective in facilitating student learning achievement and improvement of misconceptions, especially for students with low-level prior knowledge. This research also finds that personalized e-Learning material adaptive annotation significantly affects the percentage of reading time students spend on the e-Learning materials they need to enhance learning. However, it does not appear to predict student learning achievement and improvement of misconceptions.     

Online class size, note reading, note writing and collaborative discourse

Researchers have long recognized class size as affecting students?? performance in face-to-face contexts. However, few studies have examined the effects of class size on exact reading and writing loads in online graduate-level courses. This mixed-methods study examined relationships among class size, note reading, note writing, and collaborative discourse by analyzing tracking logs from 25 graduate-level online courses (25 instructors and 341 students) and interviews with 10 instructors and 12 graduate students. The quantitative and qualitative data analyses were designed to complement each other. The findings from this study point to class size as a major factor affecting note reading and writing loads in online graduate-level courses. Class size was found positively correlated with total number of notes students and instructors read and wrote, but negatively correlated with the percentage of notes students read, their note size and note grade level score. In larger classes, participants were more likely to experience information overload and students were more selective in reading notes. The data also suggest that the overload effects of large classes can be minimized by dividing students into small groups for discussion purposes. Interviewees felt that the use of small groups in large classes benefited their collaborative discussions. Findings suggested 13 to 15 as an optimal class size. The paper concludes with a list of pedagogical recommendations and suggestions for new multimedia software features to enhance collaborative learning in online classes.     

So you are going to be an online writing instructor: issues in designing,developing, and delivering an online course

Online education is increasing exponentially in colleges and universities. In this article, writing instructors are introduced to theories of instructional design that form the foundation to support effective student learning. We present a series of guidelines, derived from these theories and our research and teaching, that writing instructors may use to design, develop and deliver their online courses. We present considerations for instructors such as the need for the course, an analysis of the learners, appropriateness of the course for online delivery, pedagogical concerns, and resources. We then discuss how best to support students in online environments. We conclude with suggestions for faculty support and training for online course delivery.     

An analysis of students’ spontaneous computer-mediated help seeking: A step toward the design of ecologically valid supporting tools

This study analyzes middle school students’ spontaneous mathematics-related help-seeking behavior, in view of making ecologically valid recommendations for the design of supporting tools or “help systems”. Our aim was to investigate the content of students’ help-seeking messages – Are there different forms of help-seeking messages and do they evolve with age? We used the archives of a French forum that provides students with free individualized help in mathematics. The data consisted of 206 messages sent by French middle school students over a period of 42 months. The constituent categories of the messages were identified. The results showed that not all middle school students use the same help-seeking “format”. Compared to sixth graders, ninth graders wrote messages containing more constituent categories, i.e., they provided the online expert with more kinds of information. A detailed analysis of the categories further showed that older students’ messages more often contained explicit help requests and contextual information than did younger students’ messages. Thus, the messages of the oldest students (age 15) were both cognitively more understandable and socially more acceptable than those of the youngest students (age 11). The interpretation of these findings and their implications for designing help systems are discussed.     

结合因子图的多目的地地图布局优化

目的提出一种结合因子图的多目的地地图生成方法。方法首先,由用户选择多个感兴趣的目的地,系统根据相应规则自动地选择与目的地最相关的路线。然后,通过定义一组衡量布局质量的约束规则,采用因子图方法将定义的每条规则编码成因子,并采用Metropolis Hastings算法对由因子图构建得到的目标分布函数进行采样得到符合约束规则的多目的地地图。结果实验结果表明,使用这种方法得到的多目的地地图,可以在同一显示空间中显示多个目的地之间的道路信息,同时又保留了各目的地区域之间的拓扑和空间关系。结论提出的多目的地地图能有效地为用户提供导航,解决了当前在线地图无法在同一视野中为用户提供空间距离较远的区域道路信息的问题。