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This study contributes to proposing the improved bird swarm algorithm optimization least squares support vector machine (IBSA-LSSVM) model to predict the remaining life of lithium-ion batteries. By improving the prediction accuracy of the model, the safety and reliability of the new energy storage system are improved. In order to avoid the bird swarm algorithm (BSA) getting into the local optimal solution, the levy flight strategy is introduced into the improved bird swarm algorithm (IBSA), which improves the convergence performance of the algorithm. Hence, this study is to verify the effectiveness of the proposed hybrid IBSA-LSSVM model. The following work has been done: (1) test functions are used to test particle swarm optimization (PSO), differential evolution algorithm (DE), BSA and IBSA; (2) the back propagation neural network (BP) model, support vector machine (SVM) model, quantum particle swarm optimization support vector machine (QPSO-SVM) model, BSA-LSSVM model and IBSA-LSSVM model are tested with the B5, B6 and B18 batteries. The following findings are obtained: (1) the five test functions are used to test the PSO, DE, BSA and IBSA algorithms in 20 dimensions, 50 dimensions and 80 dimensions. The results show that the convergence accuracy and convergence stability of IBSA algorithm is higher than those of the other three algorithms; (2) the residual life of B5, B6 and B18 batteries are predicted by the BSA-LSSVM, SVM, QPSO-SVM, BP and IBSA-LSSVM models. The test results show that the root mean square error of the IBSA-LSSVM model for B5 battery is 0.01, the root mean square error for B6 battery is 0.06, and the root mean square error for B18 battery is 0.02. The results show that the prediction accuracy of proposed model is higher than that of the other models.

The strong volatility and randomness of wind power impact the grid and reduce the voltage quality of the grid when wind power is connected to the grid in large scale. The power sector takes the wind abandonment measures to ensure the grid voltage stability. The enhanced crow search algorithm optimization-extreme learning machine (ENCSA-ELM) model is proposed to accurately forecast short-term wind power to improve the utilization efficiency of clean energy. (1) The enhanced crow search algorithm (ENCSA) is proposed and applied to short-term wind power forecast. The convergence performance test revealed that the local development and global exploration capabilities of the ENCSA were enhanced, and the test result of the proposed ENCSA algorithm outperformed other well-known nature inspired algorithms and state-of-the-art CSA variants; (2) The output and input of the forecasting models were determined by analysis of the wind power impact factors and the wind power samples in autumn, winter and spring were forecasted by the ENCSA-ELM model; and (3) The forecast results were analyzed by multiple evaluation indexes. The simulation experiments revealed that the error interval and evaluation indexes of the ENCSA-ELM model outperformed the state-of-the-art wind power forecast methods, traditional machine learning models and ELM optimized by other algorithms. The RMSE value and MAPE value of the proposed model were controlled below 20% and 4%. Accurate wind power prediction maintains the voltage stability of power grid and increases the utilization efficiency of clean energy.

This study contributes to construct the mathematical model of hybrid dynamic economic emission dispatch (HDEED) considering renewable energy generation and propose a novel solving approach based on enhanced moth-flame optimization algorithm. Renewable energy power generation technology has an important impact on reducing pollutant emissions and promoting sustainable development. Therefore, this study aims to investigate the HDEED problem in consideration of renewable energy generation and improve the economic and environmental benefits of the power system. First, a moth-flame optimization algorithm based on position disturbance updating strategy (MFO_PDU) was proposed aiming at the non-convex, non-linear and high-dimensional characteristics of HDEED problem. Second, the mathematical model of HDEED on the basis of Wind-Solar-Thermal integrated energy was constructed, while taking into account the valve point effect, equality constraints and inequality constraints. Finally, three cases including test systems of different scales were formulated and employed to verify the proposed approach, and the compromise solution was determined through membership function. The results revealed that the fuel cost obtained by the MFO_PDU algorithm was 11.31%, 4.01% and 5.27% smaller than those of HHO, TSA and MFO algorithms for small-scale test system. Accordingly, the research outcomes contribute in reducing the fuel cost and pollutant emissions of power generation system, and further improving the utilization and penetration rate of renewable energy.

This study proposes improved tunicate swarm algorithm (ITSA) for solving and optimizing the dynamic economic emission dispatch (DEED) problem. The DEED optimization target is to reduce the fuel cost and pollutant emission of the power system. In addition, DEED is a complex optimization problem and contains multiple optimization goals. To strengthen the ability of the ITSA algorithm for solving DEED, the tent mapping is employed to generate initial population for improving the directionality in the optimization process. Meanwhile, the gray wolf optimizer is used to generate the global search vector for improving global exploration ability, and the Levy flight is introduced to expand the search range. Three test systems containing 5, 10 and 15 generator units are employed to verify the solving performance of ITSA. The test results show that the ITSA algorithm can provide a competitive scheduling plan for test systems containing different units. ITSA proposed algorithm gives the optimal economic and environmental dynamic dispatch scheme for achieving more precise dispatch strategy.

The contribution is to propose a novel hybrid model based on modal reconstruction to predict short-term photovoltaic (PV) power. PV power generation large-scale grid connection causes the impact on the power system due to the instability and intermittence, and PV curtailment measures are taken to reduce the impact from voltage fluctuation. Accurate forecast is necessary to make a reasonable generation plan. A novel hybrid forecasting model is proposed, and an enhanced gray wolf optimization algorithm is proposed to improve the convergence ability and to solve the influence of extreme learning machine random parameters. The proposed algorithm has stronger convergence stability and higher convergence accuracy compared with the existing algorithms. The ensemble empirical mode decomposition algorithm is used to decompose the PV power under different weather conditions. The complexity of each component is calculated by the sample entropy, and the components are reconstructed to reduce the computational cost of forecasting models. The results revealed that mean absolute percentage error and root mean square error of the proposed model are smaller than 3% and 0.36 under various weather conditions. Meanwhile, the determination coefficient of the proposed model is more than 98%.

Under environmental excitation and based on observability, an online model to predict the state of heavy-duty machine tool–foundation systems is proposed aimed to address the difficulties of directly measuring machine tool displacement states. The aim of the model is to address the difficulties associated with directly measuring machine tool displacements in real time. In this paper, to accurately obtain contact parameters of the joint surface, three states—elasticity, plasticity, and fracture—of concrete micro-bumps were studied. To obtain the equivalent elastic modulus of the secondary pouring material and reinforced concrete material, a composite foundation constitutive model is proposed to determine the equivalent elastic modulus of the concrete foundation. Surface topography features were reconstructed by truncating the peaks of curves, force balance relationships were defined at the joint surfaces, and a metal–concrete joint contact model based on fractal theory was deduced. Based on the joint contact model, a dynamic model of the heavy-duty machine tool–foundation system was established. The dynamic parameters were detected in real time and used to reconstruct the above dynamic model based on observation theory. Further, an estimation model was established to describe the state of a heavy-duty machine tool–foundation system, and online estimation of the machine tool displacement was realized. Finally, the estimation model was validated using an experimental setup of the heavy-duty machine tool–foundation system that considers joint surface factors. In conclusion, the model provides a theoretical basis for stable online control of heavy-duty machine tools.

Photovoltaic power generation is greatly affected by weather conditions while the photovoltaic power has a certain negative impact on the power grid. The power sector takes certain measures to abandon photovoltaic power generation, thus limiting the development of clean energy power generation. This study is to propose an accurate short-term photovoltaic power prediction method. A new short-term photovoltaic power output prediction model is proposed Based on extreme learning machine and intelligent optimizer. Firstly, the input of the model is determined by correlation coefficient method. Then the chicken swarm optimizer is improved to strengthen the convergence. Secondly, the improved chicken swarm optimizer is used to optimize the weights and the extreme learning machine thresholds to improve the prediction effect. Finally, the improved chicken swarm optimizer extreme learning machine model is used to predict the photovoltaic power under different weather conditions. The testing results show that the average mean absolute percentage error and root mean square error of improved chicken swarm optimizer - extreme learning machine model are 5.54% and 3.08%. The proposed method is of great significance for the economic dispatch of power systems and the development of clean energy.

The bolted joint provides more than half of the stiffness and nearly all of the damping of the whole machine tool. It is necessary to study the dynamics mechanism and establish accurate model of joint surface. The paper proposes the model of nonlinear virtual material based on fractal theory and Hertz contact theory, the contact surface can be divided into several sections based on the pressure distribution, the elastic modulus and stress of each section can be calculated. An L-shaped specimen is designed to validate the accuracy of presented model. The maximum errors of natural frequencies between theoretical and experimental is 8.8%, suggesting that nonlinear virtual material method is appropriate for the bolted joint.

In the wake of big data and Internet plus era, continuous infiltration of digital technology has been happening in various fields of social and economic development. As the most important material carrier of historical culture, the historical value of historical buildings is produced and accumulated in its historical evolution, and it can only be protected from being created again. Based on the background of digitization of cultural resources, this paper summarizes the relevant digital technologies for the digital translation of information on buildings of historical and cultural heritage, as a means to promote the spread of the PDA+APPS mobile terminal, so as to achieve the purpose of preservation, protection, management and publicity. Meanwhile, this paper analyzes the application of digital technology in this field and the prospect of its function.

One-on-one online English tutoring provides equal educational opportunities for students living in remote areas. This study examines the learning satisfaction, attitudes, and grades of e-tutees receiving online English tutoring. Ten e-tutees and ten e-tutors participated in the study. The study found that the e-tutees were satisfied with their one-on-one online English tutoring and that they performed well on online English tests. In addition, evaluations made by e-tutors show their e-tutees learning attitudes were positive. Online English distance education not only overcomes the limitations of space and time but also facilitates e-tutees' learning and development.

The geotechnical structures will be inevitably suffered from material degradation and structural performance deterioration during the in-service operation stage. In order to acquire the on-line structural responses of each phase at the structural whole life-cycle (construction, operation, reinforcement, and rehabilitation), the structural health monitoring (SHM) systems based on the optical fiber sensing technology have been broadly implemented on a variety of geotechnical structures. The optical fiber sensors have received great concerns and been widely used in long-term geotechnical engineering monitoring due to their inherent advantages such as small size, light weight, immunity to electromagnetic interference (EMI) and corrosion, and embedding capability. Various monitoring purposes make optical fiber sensors get great advances in the manufacture and installation techniques as well as the analytical methods and theories. In this paper, the sensing principles of different types of optical fiber sensors are introduced. The applications of optical fiber sensing technology in different fields of geotechnical engineering are presented. The feasibility, reliability and effectiveness of optical fiber sensors in structural monitoring applications through laboratory tests and field experiments are described.

Geometric errors are of great influence to the machining accuracy of machine tools, so they should be given special consideration in the design of machine tools. This paper proposes an approach for error allocation of machine tools. Based on D-H and Monte Carlo simulation (MCS), the reliability and sensitivity analysis were formed into two mathematics models to calculate the machining accuracy reliability and identify the error parameters which have larger influence to the machining accuracy reliability respectively. The proposed approach was performed on a heavy-duty CNC machine tool, and then it was verified by an experiment.

The medium redundancy is achieved thanks to two different physical networks. Each node shall be linked to both physical networks via a Link Selector. Ethernet data before heading to Media Access Controller, in order to achieve the medium redundancy, there is a Link Selector functional block, it can put three physical networks of the best quality network data to the Media Access Controller. This will ensure the robustness and stability of the physical network. The data delay is only a few microseconds time, does not affect the normal operation of network. All combinations of line and star (or tree) topology are allowed. The line topology will require external hubs or internal hubs with four ports.

"Creative development" and "creativity" have become important topics in the field of education research. The assessment of creativity is a key to understanding how instructional strategies influences the creative process and the output of learners. At present, most methods of assessing creativity are paper-and-pencil tests scored by individuals. Despite the professional training of evaluators, subjectivity in scoring assessments remains inevitable. Therefore, a completely objective tool of measurement is crucial for the progress of education to eliminate the subjectivity in manual grading. This paper presents at first place a review of the literature related to the development of creativity, the assessment of creativity, and further on the means of measuring creativity, particularly in a digital game environment. Our focus is on the application of computing technologies for the assessment of creativity, while exploring the possibility of using computerized systems such as fuzzy logic and hybrid methods to produce objective measurement results. The results of Pearson correlation coefficient between the fuzzy inference scores and the Williams CAP scores is 0.805, which shows the strong construct validity. Additionally, the fuzzy inference system can eliminate subjectivity in scoring and provide analysis results to enhance creativity, unlike paper-and-pencil scores provided without explanations.

The heat generated during Titanium alloy cutting can cause bad products, which must be eliminated by Sorting System. This paper describes the design and implementation of serial communication between the automatic sorting machine and the host computer, introduces the system framework and the software flow, and gives a detailed introduction to the communication process, parameters setting and also gives part of the MFC dialog-based serial communication program. It shows that the design and implementation completely meets the requirements of systems performance and function.

In photovoltaic and wind power storage systems, the reliability of the battery directly affects the overall reliability of the energy storage system. Failed batteries can seriously affect the stable operation of energy storage systems. This paper aims to improve the reliability of the storage systems by accurately predicting battery life and identifying failing batteries in time. The current prediction models mainly use artificial neural networks, Gaussian process regression and hybrid models. Although these models can achieve high prediction accuracy, the computational cost is high due to model complexity. Least squares support vector machine (LSSVM) is a computationally efficient alternative. Hence, this study combines the improved chicken swarm optimization algorithm (ICSO) and LSSVM into a hybrid ICSO-LSSVM model for the reliability of photovoltaic and wind power storage systems. The following are the contributions of this work. First, the optimal penalty parameter and kernel width are determined. Second, the chicken swarm optimization algorithm (CSO) is improved by introducing chaotic search behavior in the hen and an adaptive learning factor in the chicks. The performance of the ICSO algorithm is shown to be better than CSO using standard test problems. Third, the prediction accuracy of the three models is compared. For NMC1 battery, the predicted relative error of ICSO-LSSVM is 0.94%, for NMC2 battery, the relative error of ICSO-LSSVM is 1%. These findings show that the proposed model is suitable for predicting the failure of batteries in energy storage systems, which can improve preventive and predictive maintenance of such systems.

According to actual needs of measurement system, the virtual instrument with functions of automatic acquisition and automatic control was built by NI data acquisition card. Then, automatic control and measurement system with modular features was set up using LabVIEW software. The mode of autonomous configuration is flexible and convenient, which can greatly improve the adaptability of the device in the actual measurement. The experimental efficiency was enhanced, and the experimental data was reliable.

Both asynchronous and synchronous discussions have advantages and limitations for online learning. This study conducts an empirical analysis of these discussion activities while applying the proposed Seamless Online Learning Integrated Discussion (SOLID) system, which can instantly integrate Facebook's asynchronous discussion function with the MSN Messenger's synchronous discussion function. This study examines two teaching activities (a problem-solving-based activity and a project-based discussion activity) within the SOLID system and compares their differences in knowledge construction phases and cognitive dimensions via a quantitative content analysis and lag sequential analysis. The results show that both cognitive and knowledge construction dimensions exhibit a higher diversity of interaction in the project-based activity than in the problem-solving-based activity. In addition, based on the results of the research, this study offers, as reference, recommendations to instructors and researchers for the implementation of online discussion activities.

The characteristic of product’s life-cycle customer environment requirements is analyzed. A customer clustering methode for green design is proposed. Conjoint analysis method is used to obtain individual customer’s environment requirements and system-clustering method is used to cluster customers in accordance with their environment requirements preference. Green product customer clustering is realized. Thus, successive development of green product can be supported. Green design oriented customer clustering of soybean milk maker is illustrated to exemplify the method.

The State of Charge (SoC)-Open Circuit Voltage (OCV) curve and the quality of estimation algorithm are two important factors that infect the accuracy of SoC estimation for lithium-ion batteries in electric vehicles. The purpose of this study is to improve the accuracy of SoC estimation for the lithium-ion battery. The battery management system is established to monitor the state of lithium-ion batteries to ensure the safety and reliability of the battery system. Firstly, the specific experiments were designed to analyze the relationship between the SoC-OCV curve and experimental conditions (e.g., ambient temperature and current rate) and battery states (e.g., State of Health and positive materials). A series of conclusions was found and used to correct the process of SoC estimation. Secondly, by analyzing the reasons that the SoC estimation error increased in the low-capacity period and the late-stage of estimation using the extended Kalman filter (EKF), an improved estimation algorithm was proposed. In the improved estimation algorithm, the ampere-hour counting was used in the low-capacity period, and the EKF was used in the rest. The accuracy of the improved estimation algorithm was verified by two experiments. Verification results show that the improved estimation algorithm makes up for the drawback of the EKF, the estimation error in constant current discharge experiment is less than 2 %, and the estimated error under dynamic conditions is less than 3 %. Therefore, the improved estimation algorithm has a higher accuracy than the EKF for the SoC estimation and can meet the operation requirements of a lithium-ion battery. This study contributes to the improvement of the safety and reliability of battery systems in electric vehicles by improving the accuracy of SoC estimation for lithium-ion batteries.

This article considers the efficacy of educational computer and video games in improving student motivation and achievement. It is stated that prior research has suggested that educational games provide positive opportunities for active learning and help develop learning skills. A content analysis approach is used to analyze 196 different games that are popular in Taiwan. A Delphi survey is given to six educational technology experts, six educational psychology experts, six game design experts, six students each from elementary, junior, and high schools, and six teachers in an attempt to reach a consensus on educational games.

The main purpose of this study was to investigate the influence of scaffolding and self-efficacy on students' programming learning performance in robotics learning environment. There were 89 junior high school students participated in the study. The results indicated that there is significant interaction between scaffolding mechanism and learning motivation on students' learning performance. The introduction of design journal did not have a significant effect on the learning performance of students with high self-efficacy, however, design journal had pronounced benefits for students with moderate self-efficacy. According to the findings, we proposed some directions for future studies.

In the traditional instructional method used in international trade, teachers provide knowledge to learners by lecturing using slides and setting assignments; however, these methods merely deliver international trade knowledge rather than facilitating student development of relevant skills. To solve these problems, we proposed a simulation-based learning system for international trade, combining international trade-process simulation and business letter writing. We investigated learner opinions toward the system and the quality of business letters by using quantitative and qualitative analyses. Regarding the results, learners perceived that the proposed system improved their knowledge of international trade and business English.

A time-delay chaotification approach can be applied to the Chua's circuit by adding a small-amplitude time-delay feedback voltage to the circuit. The chaotic dynamics of this newly derived time-delay Chua's circuit is studied by theoretical analysis, verified by computer simulations as well as by circuit experiments.

This study describes an effective web-based learning strategy, peer review, used by 143 computer science undergraduate students in an operating systems class at a Taiwanese university. Peer review, based on social constructivism, can be easily implemented via the authors' well-developed web-based peer review (WPR) system. Through peer review, the authors hope to form an authentic learning environment similar to an academic society in which a researcher submits a paper to a journal and receives reviews from society members before publication. Students using this learning strategy are expected to develop higher level thinking skills. The WPR system functioned in the following roles in this study: (1) an information distribution channel and management center for assignment submissions and peer review; (2) a forum for peer interaction and knowledge construction; and (3) storage for knowledge construction procedures. An evaluation of learning effects and students' perceptions about peer review during the spring of 1998 revealed that students not only performed better under peer review, but also displayed higher level thinking skills, i.e., critical thinking, planning, monitoring, and regulation. Students perceived peer review as an effective strategy that promoted their learning motivation. However, merely being an effective reviewer or an effective author may not excel in a peer review environment. The most effective individual appears to be the strategic adapter who effectively constructs a project, adjusts to peers' comments, and serves as a critical reviewer as well.

This study implements a networked peer assessment system based on the use of a Vee heuristic. Using this system, students submit their homework (relating to designing science activities)via the underlying network facility. They then assess each other's homework by offering suggestions – again, through the network. Students then modify their original designs based on the suggestions that they receive. This procedure is repeated for two or three consecutive rounds. In this process, each student functions as an author, a reviewer, and an adapter. This learning model allows students to further develop their critical thinking skills. Preliminary peer assessment results revealed that the networked peer-assessment model and Vee heuristic facilitated pre-service science teachers to continuously progress when designing science activities.

Synchronous discussion and asynchronous discussion have different advantages and disadvantages. However, it is unclear how students react to these two models. Thus, we developed a learning environment that combines these two models, and then examined how students selected them. The findings show that students selected different models at different discussion stages. Additionally, the mixed discussion model, which combines synchronous and asynchronous models, can achieve better performance in discussion, regardless of the types of discussion activity.

The purpose of this study was to examine the effect of design journal on studentsi¦ robotics learning and problem solving. There are forty-four junior high school students participated in this study. The quasi-experimental design was applied in the study. The result of the study found that studentsi¦ knowledge about robotics was enhanced during the robotics learning activities. However, there is no significant difference on the posttest scores between control and experimental groups. Additionally, the study found that the students in the experimental group complete the mission significantly fast than the students in the control group. The study found that reflective strategies, such as: writing the design journal was beneficial for studentsi¦ problem loving in the robotics learning.

Children actively build knowledge through experiences when they play games. Along with the development of technology, there has been more research on digital game-based leaning in recent years. Digital games contain better pictures and sound effects, but on the other hand, traditional games such as board games and card games can increase social interactions among people through playing games face to face. This study designed a card game for learning science knowledge about transportation and energy. Six fourth-grade elementary school students were tested for this game by methods of observations and interviews. The result showed that these students were all very interested in the game and would be willing to learn through the game again.

This study employs cooperative learning to create an Educational Board Game Design Course. The curriculum of activities required pre-service teachers to work cooperatively in learning-groups to complete a prototype of a board game. Group discussion via an Online Interactive Platform supported the process of the participants as they carried out the curriculum of activities. A questionnaire enabled an understanding of the pre-service teachersi¦ learning performances. The results showed that each group could completely design games that operate smoothly and have relevance to academic subjects. Pre-service teachersi¦ self-efficacy enhanced after the cooperative learning process. Control over game difficulty levels and the skill of teaching game directions need strengthening in the future. Besides, providing more specific learning content is necessary for any future course.

This study explored the impact of Technology Enabled Active Learning (TEAL) on students learning general physics, focusing on differences between genders and among various achievement levels. A quasi-experimental investigation was conducted on two semesters of courses offered in 2008. Data sources consisted of pre-tests, post-tests, self-report surveys, class observations, and interview data. The test results indicate that the learning gain achieved by the experimental group was 11% higher than that achieved by the control group in the first semester, though the margin decreased to 1% in the second semester. In the situation of the low achievement level, there was no difference found in the learning gain achieved by the two groups in the second semester. The qualitative data revealed that student academic performances were disclosed to be associated with the following factors: the instructors' teaching styles and instructional skills, the students' prior knowledge, their study habits, and the cohort atmosphere. That is, implementation of the innovative tool alone might not be sufficient to significantly improve student performance. Nonetheless, the interactive, collaborative instructional approach seemed to appeal to females more than it did to males, disclosing the potential of TEAL in narrowing the learning gap between genders.

Discussion learning activity has been one of the very important learning strategies in the current domain of learning and teaching. So far, there are studies conducted by scholars that separately focus on synchronous or asynchronous discussions; however, due to the advantages and limitations of both approaches, the integrated system which combines the synchronous discussion of MSN Messenger with the asynchronous discussion of the Facebook community was designed and developed in this study. The system posts messages of synchronous discussion from MSN Messenger on the asynchronous interface of Facebook community, and the asynchronous discussion of Facebook is sent to the synchronous interface of MSN Messenger as well. Therefore, we called our proposed system as Seamless Online Learning Integrated Discussion (SOLID). In this case study, the exploratory evaluation of Seamless Online Learning Integrated Discussion were conducted, and from the case study preliminarily focusing on the utilization of systems and discussion activities, it is found that the students would alternatively choose a proper discussion tool to use at appropriate time rather than alternate use the tools. In the discussion process, the students could choose proper tools timely in the phases of “addressed hypothesis, the definitions and clarifications of questions selections”, “possible answers of proposed solutions”, and “organized procedures and conclusions”. On the other hand, the students did not have in-depth discussion only at the phase of “aspects of comparison, discussion, and analysis of the tools”. Discussions and recommendations are given within this case study according to the findings.

This article aims to develop game-based learning and interactive peer assessment to improve college students' career goals and objectives. A total of 36 students enrolled the "Sport Guidance and Counseling" course and participated the "Job Hunting" game. Each student completed a "future resume" and played the role-play game to demonstrate their ability to find a job. Peer assessments were completed during the game as in-class activity. Self-critiques and reflections were required to post on the course blog. Participation observation and blog feedback were two major qualitative research methods to collect the data. Constant comparison was utilized to analyze the data with QSR Nvivo7. The results identified that students learned through concrete experience, reflective observation, abstract conceptualization and active experimentation in the interactive peer assessment. The finding showed that game-based learning and interactive peer assessment are viable combinations to motivate colleague students to collaborate and to improve career goals and objectives.

This article reports on research that attempted to find out how physical education professionals in the university environment are responding to the increasing importance and visibility of web 2.0 tools and social networking in Taiwan. The purpose of the study is to explore how the web 2.0 social networking and its influence on college students' learning behavior in preparing graduation events. Two hundred and sixty-nine individuals voluntarily signed up a group, "Sport Broadway in NCUE", for the annually graduation events on Facebook. Total 512 postings and responses had been posted and 2434 likes were collected and analyzed by quantitatively and qualitatively. Descriptive statistics in quantitative data and constant comparison in qualitative information were analyzed with the SPSS 15.0 and QSR Nvivo 7. The results identified that announcement, sharing feelings, encouragement, asking questions, and critiques are five major functions of posting. In addition, "like" which means "agree" and easy positive feedback in Facebook was given most frequently when critiques and sharing encouragement. The finding showed that Web 2.0 social networking are viable way to motivate colleague students to collaborate and learn to accomplish tasks and to overcome challenges. However, the quality of posts and comments were easily out of control when the levels of stress rises and emotions come. The study implicates that Web 2.0 social networking is worth to promote and to be developed as an educational tool in college levels.

The purpose of this study is to investigate the relationship between learning motivation and learning strategies in robotics learning. 37 elementary school students participated in this study. The RMSLQ questionnaire was used to collect data about student learning motivation and learning strategies in robotics learning. The results indicated that students showed high motivation and used a variety of learning strategies in learning robotics. Moreover, form the result of correlation analysis, it was found that both cognitive and meta-cognitive strategy and resource management strategy had significant positive correlation with students' control believe. In the future, more attention should be paid on developing different learning activities or learning mechanisms to improve students' control belief in learning robotics to improve their leaning strategies.

Due to the development of technology, lots of attractive multimedia effect was used in digital games and games become more and more popular. In Taiwan, a special Issue Group, Joyful Learning and Society, was developed, and one of the issues the group focuses on was how to use digital game to enhance students’ learning. One of the ongoing tasks was to review game-related studies in different journals, to realize the development of game-based learning. In this study, seven game-related studies were analyzed, and some suggestions were proposed in this study.

This literature review summarizes research on game-based learning based on the categories of research outcomes. The analysis include total of 25 research papers that are published in this decade. They are categorized into four parts: cognitive aspect, affective aspect, psychomotor skill aspect, and behavior. In spite of cross-aspect of each research, we found that more researches focus on the impact of games on cognitive and affective aspects as well as the observation on related behaviors, and less on psychomotor skill aspects. Continued study is needed to provide in-depth qualitative analysis on the theories, methods, and results of these researches, which conclusion might direct us to future trends of game-based learning researches.

Typing skill is a very important skill for students now, and it's a critical issue about how to train and improve students' typing skill. In the past, it was a common strategy to design software for students to practice their typing skill. Because of the differences in the design approaches, different types of typing software, drill-based and game-based software show up. This study compared the learning genres and the effect on typing speed. Experimental design was used to verify the statistical hypothesis in this study. The experimental group used game-based typing software, and the control group used drill-based typing software. The results of pre-test and post-test were compared to evaluate the effect of different types of typing software. The result showed that both game-based and drill-based typing software could improve students' English typing speed. Besides, different types of typing software had different advantages and disadvantages. Finally, some suggestions were proposed for typing software design.

Improving typing skill can help students use computers to deal with different kinds of tasks more efficiently. In the past, typing software was commonly used to train students' typing skill, and they usually didn't have much attractive multimedia effect. In recent years, games have become more and more popular, and one of the reasons is that games have lots of attractive elements, like lots of multimedia effect and interesting scripts. About the educational effect of typing games, game is more interesting than traditional instruction, and that's the reason why people use typing games to train their typing skill. This study tried to realize the effect on typing skill of drill-based and game-based typing software, and proposed possible design direction for typing software. There were 160 second year junior high school students participating in this study. The students studied in a junior high school in middle Taiwan, and they came from five different classes. After excluding six invalid samples, 82 students were males (53.2%) and 72 students were females (46.8%). Pretest-posttest control group design was used in this study. The independent variable was different types of typing software. There were 92 students in the control group, and they used drill-based typing software to learn typing. There were 62 students in the experimental group, and they used game-based typing software to learn typing. The dependent variable was typing speed. The difference of typing speed between pre-test and post-test and the effect on typing speed of different software would be compared. The result showed that both kinds of typing software could improve students' typing speed, but the effect on typing speed between the two kinds of software didn't reach significant difference. The result indicated that both entertainment and learning design direction were beneficial for learning typing skill, but different kinds of design also showed different disadvantages and limitations. Therefore, it is better to consider the two aspects at the same time when design edutainment software, and try to keep the balance between the two elements to produce the optimal learning effect. The future studies may confirm if the learning effect from both learning element and entertainment element is better than the learning effect only from learning element or entertainment element.

The creative spiral instruction model was applied into a LEGO® robotics course in this study. In order to understand the effect of the LEGO robotics course on students' creativities and problem solving performance, students' problem solving process and performance in the course were analyzed. Six undergraduate students participated in this study. The participants were divided into two groups, Group A and Group B, having three members per group. Results showed that during the problem solving process, students in both groups exhibited creativity and acquired knowledge about program design and assembly of LEGO robots. During the problem solving process, three strategies were mainly used by students to solve the problems: 1. Slight adjustment. 2. New elements adding. 3. Problems redefining. After analyzing the creative problem solving process, the result showed richness of data collection being beneficial for understanding the problem solving modes.

Bill Gates mentioned in Scientific America that robot will enter every home in ten year the same as personal computers have entered into almost every home in ten year. This project is to response to this trend, and to think about how robot can enhance learning, for example, robot can be as learning tools, teaching tools, learning companions, teaching partner, or some other models to enhance learning.

This study developed a multimedia educational program for teaching robotics. The program was intended to introduce robot adventure, assembly, and programming. Finally, triangulation method was applied in a pilot study to assess user satisfaction with the learning material. The evaluation results indicated that the instructional material was effective and achieved high student satisfaction.

Portfolio is a process which systematically and purposefully collects artifacts or works created by students. These works and artifacts not only can be treated as a reference to improve students' learning process, but also as a learning outcome when passing into next learning stage or seeking a job. Assessment in such a way is called authentic assessment, since it assesses students' real learning performance. Portfolio process requires administrative staffs, students, and teachers to put effort on. To keep this process working, teachers take most of burden. In this paper, we present a Web-based system which will let teachers take burden as low as possible while provide most beneficial to students. This system has been installed at an Institute of Technology in Taiwan, the result shows positive and most of students appreciate functionality of this system.