Designing a semantic bliki system to support different types of knowledge and adaptive learning

Though blogs and wikis have been used to support knowledge management and e-learning, existing blogs and wikis cannot support different types of knowledge and adaptive learning. A case in point, types of knowledge vary greatly in category and viewpoints. Additionally, adaptive learning is crucial to improving one’s learning performance. This study aims to design a semantic bliki system to tackle such issues. To support various types of knowledge, this study has developed a new social software called “bliki” that combines the advantages of blogs and wikis. This bliki system also applies Semantic Web technology to organize an ontology and a variety of knowledge types. To aid adaptive learning, a function called “Book” is provided to enable learners to arrange personalized learning goals and paths. The learning contents and their sequences and difficulty levels can be specified according to learners’ metacognitive knowledge and collaborative activities. An experiment is conducted to evaluate this system and the experimental results show that this system is able to comprehend various types of knowledge and to improve learners’ learning performance.     

Scaffolding game-based learning: Impact on learning achievements,perceived learning,and game experiences

One of the central challenges of integrating game-based learning in school settings is helping learners make the connections between the knowledge learned in the game and the knowledge learned at school, while maintaining a high level of engagement with game narrative and gameplay. The current study evaluated the effect of supplementing a business simulation game with an external conceptual scaffold, which introduces formal knowledge representations, on learners' ability to solve financial-mathematical word problems following the game, and on learners' perceptions regarding learning, flow, and enjoyment in the game. Participants (M_age = 10.10 years) were randomly assigned to three experimental conditions: a “study and play” condition that presented the scaffold first and then the game, a “play and study” condition, and a “play only” condition. Although no significant gains in problem-solving were found following the intervention, learners who studied with the external scaffold before the game performed significantly better in the post-game problem-solving assessment. Adding the external scaffold before the game reduced learners' perceived learning. However, the scaffold did not have a negative impact on reported flow and enjoyment. Flow was found to significantly predict perceived learning and enjoyment. Yet, perceived learning and enjoyment did not predict problem-solving and flow directly predicted problem solving only in the “play and study” condition. We suggest that presenting the scaffold may have “problematized” learners' understandings of the game by connecting them to disciplinary knowledge. Implications for the design of scaffolds for game-based learning are discussed.     

An intelligent learning diagnosis system for Web-based thematic learning platform

This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners’ ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to search related learning courseware and discussing what they have learned with their colleagues. Based on the log files that record the learners’ past online learning behavior, an intelligent diagnosis system is used to give appropriate learning guidance to assist the learners in improving their study behaviors and grade online class participation for the instructor. The achievement of the learners’ final reports can also be predicted by the diagnosis system accurately. Our experimental results reveal that the proposed learning diagnosis system can efficiently help learners to expand their knowledge while surfing in cyberspace Web-based “theme-based learning” model.     

Exploring the learning effectiveness of financial literacy from the microworld perspective: Evidence from the simulated transactional interactive concurrent system

Because the microworld can create a learning environment that allows learners to interact with the real world, the view of the microworld has been widely used in education and training. In this study, the simulated transactional interactive concurrent system (STICS) was used to provide an environment that simulates the stock market trading of the Taiwan Stock Exchange; the goal is to explore the effectiveness of using STICS in enhancing the financial literacy of students. This study adopts a quasi-experimental design approach and divides students into two groups. The intervention group was made up of 42 students who learned financial knowledge aided by STICS, with a comparison group consisting of 43 students who learned with traditional lecturing and dictating methods. The study found that learners who used the STICS as an aid to learn financial knowledge had significantly better learning effectiveness than those who did not use STICS, in terms of motivation, attitude, and achievement. The intervention group also made significant improvements in average scores in learning motivation and achievement after 8 weeks of experimental teaching and learning.     

Appropriate media choice for e-learning effectiveness: Role of learning domain and learning style

As the number of online education and training programs increase, researchers and practitioners are interested in investigating ways to design and develop effective e-learning programs. One of the major design decisions that affects learning effectiveness is the choice of media to present the contents of such programs. The prevailing tendency seems to be to use “richer” medium, in the progression from text to graphics to audio to video, for designing and developing e-learning programs. It is not clear, however, if a “richer” medium provides proportionately higher learning effectiveness. To investigate this gap in our understanding, we developed an integrated research model and tested it empirically. Our results showed that the relationship between media choice in an e-learning program and the effectiveness of that program is moderated by the learning domain of the program and the learning styles of learners.     

E-Learning personalization based on hybrid recommendation strategy and learning style identification

Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper, we describe a recommendation module of a programming tutoring system - Protus, which can automatically adapt to the interests and knowledge levels of learners. This system recognizes different patterns of learning style and learners’ habits through testing the learning styles of learners and mining their server logs. Firstly, it processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the learners through mining the frequent sequences by the AprioriAll algorithm. Finally, this system completes personalized recommendation of the learning content according to the ratings of these frequent sequences, provided by the Protus system. Some experiments were carried out with two real groups of learners: the experimental and the control group. Learners of the control group learned in a normal way and did not receive any recommendation or guidance through the course, while the students of the experimental group were required to use the Protus system. The results show suitability of using this recommendation model, in order to suggest online learning activities to learners based on their learning style, knowledge and preferences.     

Lessons learned from the design of situated learning environments to support collaborative knowledge construction

The main characteristics of situated learning environments (SLEs) are: to provide authentic contexts, activities, expert performances and integrated assessment; to support multiple roles and perspectives, collaborative knowledge construction, coaching and scaffolding; and to promote reflection and articulation. However, current SLEs have two limitations: (1) not all of these characteristics are included, particularly lacking collaborative knowledge construction, in most cases; and (2) most SLEs are designed to support learning activities outdoors, but not indoors. This paper presents the implementation of an SLE that overcomes these two limitations. This SLE is based on bidirectional Quick Response (QR) codes, which are enhanced QR codes that not only provide information when scanned but also collect user-generated content. This “Bidirectional SLE” is evaluated in an experiment in which it is compared with an equivalent “Traditional SLE”, which is built upon traditional QR codes. The purpose of this comparison is to understand if using bidirectional QR codes as a mechanism to support collaborative knowledge construction in indoor settings has an impact on students' learning outcomes and on their impression of the learning experience. Two hundred fifty-three students participated in this experiment. Data collected from this experiment indicate that the students who worked in the Bidirectional SLE (1) received better scores, providing better and more complete answers, and (2) evaluated their learning experience better than their peers' who worked in the Traditional SLE. Finally, a cross-analysis of these results including teachers' opinions led to a set of lessons learned about the design of SLEs to support collaborative knowledge construction.     

基于情感学习本体的教学反馈策略生成算法的研究

研究如何采用本体建模的方法解决智能教学系统中的情感理解与情感反馈的问题。构建了一个情感学习本体用于描述在学习过程中出现的与情感相关的概念及概念之间的关系,设计了基于该本体的教学反馈策略的生成算法,可以在不需要和学生进行问答交互的情况下获得学生学习过程的感知和理解状态,可以更好地理解学生的学习状态以提供更好的基于"情感触发"的认知和情感支持。并将情感学习本体和一个C语言程序设计领域知识本体以及反馈策略生成算法应用到一个以教学视频为主体学习资料的智能教学系统中。应用实例表明,该教学反馈策略生成算法能对学习者提供有效的认知反馈和情感反馈。     

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.     

Developing early warning systems to predict students’ online learning performance

An early warning system can help to identify at-risk students, or predict student learning performance by analyzing learning portfolios recorded in a learning management system (LMS). Although previous studies have shown the applicability of determining learner behaviors from an LMS, most investigated datasets are not assembled from online learning courses or from whole learning activities undertaken on courses that can be analyzed to evaluate students’ academic achievement. Previous studies generally focus on the construction of predictors for learner performance evaluation after a course has ended, and neglect the practical value of an “early warning” system to predict at-risk students while a course is in progress. We collected the complete learning activities of an online undergraduate course and applied data-mining techniques to develop an early warning system. Our results showed that, time-dependent variables extracted from LMS are critical factors for online learning. After students have used an LMS for a period of time, our early warning system effectively characterizes their current learning performance. Data-mining techniques are useful in the construction of early warning systems; based on our experimental results, classification and regression tree (CART), supplemented by AdaBoost is the best classifier for the evaluation of learning performance investigated by this study.     

Here and now mobile learning: An experimental study on the use of mobile technology

Mobile technology opens the door for a new kind of learning called here and now learning that occurs when learners have access to information anytime and anywhere to perform authentic activities in the context of their learning. The purpose of this study was to investigate the effects of here and now mobile learning on student achievement and attitude. The research questions addressed were (1) Does “Here and Now” mobile learning significantly improve student achievement when compared with Computer based Instruction? (2) Does “Here and Now” mobile learning significantly improve student attitude when compared with Computer based Instruction? (3) Are there differences in student achievement and attitudes when “Here and Now” mobile learning is delivered using a tablet versus ipod? 109 undergraduate students enrolled in preservice instructional design and instructional technology courses at a regional southeastern university participated in the study. Participants took a pretest at the beginning of the study, and then were assigned to one of the versions of an art lesson (CBI version and iPad/iPod version) which were developed using Lectora Inspire incorporating information on five different paintings in the education building. After the lesson, they completed the posttest and an attitude survey. ANOVA was conducted on data obtained from the achievement posttest and on the attitude survey results for the Likert type items (Items 1–12). Analyses on achievement and attitude data revealed positive significant differences. The CBI treatment achieved positive posttest scores on the posttest while the iPad/iPod treatments had positive attitudes. This study has implications for those designing and implementing mobile learning.     

Community-organizing agent: An artificial intelligent system for building learning communities among large numbers of learners

Web-based (or online) learning provides an unprecedented flexibility and convenience to both learners and instructors. However, large online classes relying on instructor-centered presentations could tend to isolate many learners. The size of these classes and the wide dispersion of the learners make it challenging for instructors to interact with individual learners or to facilitate learner collaborations. Since extensive literature has confirmed that the substantial impact of learner interaction on learning outcomes, it is pedagogically critical to help distributed learners engage in community-based collaborative learning and to help individual learners improve their self-regulation. The E-learning lab of Shanghai Jiaotong University created an artificial intelligence system to help guide learners with similar interests into reasonably sized learning communities. The system uses a multi-agent mechanism to organize and reorganize supportive communities based on learners’ learning interests, experiences, and behaviors. Through effective award and exchange algorithms, learners with similar interests and experiences will form a community to support each others’ learning. Simulated experimental results indicate that these algorithms can improve the speed and efficiency in identifying and grouping homogeneous learners. Here, we will describe this system in detail and present its mechanism for organizing learning communities. We will conduct human experimentations in the near future to further perfect the system.     

《数据结构》课程知识本体构建研究

介绍当代移动学习的特点和语义网本体技术,提出利用本体技术来适应移动学习的片段式学习方式要求,并以《数据结构》课程为例阐述课程知识本体库的具体构建过程．为其在移动学习系统中的应用打下研究基础。     

Digital learners and the overlapping of their personal and educational digital engagement

Current K-12 students are considered digital learners because technology is as pervasive in their academic world as in their personal lives. Technology enthusiasts argue that these learners are the “digital natives” having sophisticated technology knowledge and skills that can be potentially harnessed for better learning engagement inside the classroom. This phenomenological study investigates how some current high school students as the digital learners engage with technology at home and school; and how these two types of engagement overlap in their learning inside the classroom. Data were gathered from phenomenological three series in-depth interviews with five participants and also field observation. Findings show that the overlap between the personal and educational digital engagement(s) of these students was not necessarily positive as portrayed by the prevalent discourses of technology enthusiasts. The overlapping had mixed roles – facilitative as well as obstructive. Pedagogical and future research implications are discussed.     

Learning with desktop virtual reality: Low spatial ability learners are more positively affected

This study aims to verify the learning effectiveness of a desktop virtual reality (VR)-based learning environment, and to investigate the effects of desktop VR-based learning environment on learners with different spatial abilities. The learning outcome was measured cognitively through academic performance. A quasi pretest–posttest experimental design was employed for this study. A total of 431 high school students from four randomly selected schools participated in this study where they were randomly assigned to either experimental or control groups based on intact classes. Findings indicate a significant difference in the performance achievement between the two groups with students performed better using desktop virtual reality. A possible explanation is that the desktop virtual reality instructional intervention has helped to reduce extraneous cognitive load and engages learners in active processing of instructional material to increase germane cognitive load. A significant interaction effect was found between the learning mode and spatial ability with regard to the performance achievement. Further analysis shows a significant difference in the performance of low spatial ability learners in the experimental and control groups, but no statistically significant difference in the performance of high spatial learners in both groups. The results signify that low spatial ability learners' performance, compared with high spatial ability learners, appeared to be more positively affected by the desktop VR-based learning environment which is supported by the ability-as-compensator hypothesis, and can be explained by the cognitive load theory.     

Implement web learning environment based on data mining

The need for providing learners with web-based learning content that match their accessibility needs and preferences, as well as providing ways to match learning content to user’s devices has been identified as an important issue in accessible educational environment. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. In order to achieve optimal efficiency in a learning process, individual learner’s cognitive learning style should be taken into account. Due to different types of learners using these systems, it is necessary to provide them with an individualized learning support system. However, the design and development of web-based learning environments for people with special abilities has been addressed so far by the development of hypermedia and multimedia based on educational content. In this paper a framework of individual web-based learning system is presented by focusing on learner’s cognitive learning process, learning pattern and activities, as well as the technology support needed. Based on the learner-centered mode and cognitive learning theory, we demonstrate an online course design and development that supports the students with the learning flexibility and the adaptability. The proposed framework utilizes data mining algorithm for representing and extracting a dynamic learning process and learning pattern to support students’ deep learning, efficient tutoring and collaboration in web-based learning environment. And experiments do prove that it is feasible to use the method to develop an individual web-based learning system, which is valuable for further study in more depth.     

The effect of learning styles on the navigation needs of Web-based learners

Web-based training with all its potential benefits is growing at a tremendous rate; however most current systems provide a “one-size-fits-all” approach to the delivery of the material. Two approaches that try to improve end-user learning have emerged: adaptation of the material content and/or adaptation of the material presentation mode. As a subset of the material presentation approach, two modes have been discussed in the literature: learner control vs. system control. It has been discussed that if the amount of learning is dependent on the material presentation mode and the learning style of the users, more effective systems that adapt to this relationship could be developed.This paper analyzes the results of an exploratory experiment completed by 58 subjects. It first measured their learning style preferences (using a version of the Kolb Learning Style Inventory Tool) and compared it to their actual visits of linked Web-pages. The study found that learners classified as “Explorers” tended to “jump” more and created their own path of learning (learner control), while subjects classified as “Observers” tended to follow the suggested path by clicking on the “Next” button (system control). In addition, test scores for explorers who did jump were higher than explorers who did not jump, while conversely observers who did not jump scored higher than observers who did jump.     

An investigation of learners' collaborative knowledge construction performances and behavior patterns in an augmented reality simulation system

The purpose of this study was to investigate how a mobile collaborative augmented reality (AR) simulation system affects learners' knowledge construction behaviors and learning performances. In this study, 40 undergraduate students were recruited and divided into dyads to discuss a given task either with the assistance of a mobile collaborative AR system or traditional 2D simulation system. The participants' knowledge acquisition regarding elastic collision was evaluated through a pre-test and a post-test comparison. Learners' knowledge construction behaviors were qualitatively identified according to an adapted three-category coding scheme including construction of problem space (PS), construction of conceptual space (CS), and construction of relations between conceptual and problem space (CPS), and were then analyzed by adopting lag sequential analysis. The results indicated that the learners who learned with the AR system showed significant better learning achievements than those who learned with the traditional 2D simulation system. Furthermore, the sequential patterns of the learners' behaviors were identified, including three sustained loops (PS→PS, CS→CS, CPS→CPS), a bi-directional path between the PS and CPS activities (PS↔CPS), and a one way path from the PS activity to the CS activity (PS→CS). The revealed behavior patterns suggest that the AR Physics system may serve as a supportive tool and enable dyad learners to respond quickly to the displayed results and support their knowledge construction processes to produce a positive outcome. Based on the behavioral patterns found in this study, suggestions for future studies and further modifications to the system are proposed.     

Effects of an ontology display with history representation on organizational memory information systems

Ontologies, as a possible element of organizational memory information systems, appear to support organizational learning. Ontology tools can be used to share knowledge among the members of an organization. However, current ontology-viewing user interfaces of ontology tools do not fully support organizational learning, because most of them lack proper history representation in their display. In this study, a conceptual model was developed that emphasized the role of ontology in the organizational learning cycle and explored the integration of history representation in the ontology display. Based on the experimental results from a split-plot design with 30 participants, two conclusions were derived: first, appropriately selected history representations in the ontology display help users to identify changes in the ontologies; and second, compatibility between types of ontology display and history representation is more important than ontology display and history representation in themselves.     

Assessing effects of information architecture of digital libraries on supporting E-learning: A case study on the Digital Library of Nature & Culture

Modern digital libraries not only contain rich digital resources, they are also required to provide an environment which integrates collection provision, information services, and academic activities to support effective learning. This work chose the Digital Library of Nature and Culture established by the National Museum of Natural Science in Taiwan to investigate whether the design of the information architecture of a digital library influences learning performance and whether learners with different learning styles have different information usage behaviors and learning performance when they use the digital library to support e-learning. This work suggested that e-learning supported by a digital library resulted in excellent learning performance. Regarding the influence of information architecture on learning performance, this work found that the organization system was crucial to learning performance. Further, learners with different learning performance exhibit different behaviors when they use the information architecture of the digital library. Another finding was that the learning performance of global learners was better than that of sequential learners. Global learners and those learners with superior learning performance relied more heavily on the organization system, while sequential learners and those learners with inferior learning performance relied more heavily on the search system.