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Machine learning with active pharmaceutical ingredient/polymer interaction mechanism:Prediction for complex phase behaviors of pharmaceuticals and formulations 被引量:2
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作者 Kai Ge Yiping Huang Yuanhui Ji 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第2期263-272,共10页
The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients(APIs)with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceu... The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients(APIs)with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceutical formulations.In this work,a developed machine-learning model efficiently predicts the solubility of APIs in polymers by learning the phase equilibrium principle and using a few molecular descriptors.Under the few-shot learning framework,thermodynamic theory(perturbed-chain statistical associating fluid theory)was used for data augmentation,and computational chemistry was applied for molecular descriptors'screening.The results showed that the developed machine-learning model can predict the API-polymer phase diagram accurately,broaden the solubility data of APIs in polymers,and reproduce the relationship between API solubility and the interaction mechanisms between API and polymer successfully,which provided efficient guidance for the development of pharmaceutical formulations. 展开更多
关键词 Multi-task machine learning Density functional theory Hydrogen bond interaction MISCIBILITY SOLUBILITY
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Optimization of Interactive Videos Empowered the Experience of Learning Management System
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作者 Muhammad Akram Muhammad Waseem Iqbal +3 位作者 M.Usman Ashraf Erssa Arif Khalid Alsubhi Hani Moaiteq Aljahdali 《Computer Systems Science & Engineering》 SCIE EI 2023年第7期1021-1038,共18页
The Learning management system(LMS)is now being used for uploading educational content in both distance and blended setups.LMS platform has two types of users:the educators who upload the content,and the students who ... The Learning management system(LMS)is now being used for uploading educational content in both distance and blended setups.LMS platform has two types of users:the educators who upload the content,and the students who have to access the content.The students,usually rely on text notes or books and video tutorials while their exams are conducted with formal methods.Formal assessments and examination criteria are ineffective with restricted learning space which makes the student tend only to read the educational contents and videos instead of interactive mode.The aim is to design an interactive LMS and examination video-based interface to cater the issues of educators and students.It is designed according to Human-computer interaction(HCI)principles to make the interactive User interface(UI)through User experience(UX).The interactive lectures in the form of annotated videos increase user engagement and improve the self-study context of users involved in LMS.The interface design defines how the design will interact with users and how the interface exchanges information.The findings show that interactive videos for LMS allow the users to have a more personalized learning experience by engaging in the educational content.The result shows a highly personalized learning experience due to the interactive video and quiz within the video. 展开更多
关键词 User interface user experience learning management system linear nonlinear video interactive video visual design
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Meta-SEE:Intelligent and Interactive Learning Framework for Software Engineering Education Based on Metaverse and Metacognition
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作者 Jianguo Chen Mingzhi Mao +2 位作者 Neng Zhang Leqiu Wang Zibin Zheng 《计算机教育》 2023年第12期11-21,共11页
With the rapid evolution of technology and the increasing complexity of software systems,there is a growing demand for effective educational approaches that empower learners to acquire and apply software engineering s... With the rapid evolution of technology and the increasing complexity of software systems,there is a growing demand for effective educational approaches that empower learners to acquire and apply software engineering skills in practical contexts.This paper presents an intelligent and interactive learning(Meta-SEE)framework for software engineering education that combines the immersive capabilities of the metaverse with the cognitive processes of metacognition,to create an interactive and engaging learning environment.In the Meta-SEE framework,learners are immersed in a virtual world where they can collaboratively engage with concepts and practices of software engineering.Through the integration of metacognitive strategies,learners are empowered to monitor,regulate,and adapt their learning processes.By incorporating metacognition within the metaverse,learners gain a deeper understanding of their own thinking processes and become self-directed learners.In addition,MetaSEE has the potential to revolutionize software engineering education by offering a dynamic,immersive,and personalized learning experience.It allows learners to engage in realistic software development scenarios,explore complex systems,and collaborate with peers and instructors in virtual spaces. 展开更多
关键词 interactive learning framework Metaverse METACOGNITION Software engineering education
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The Effect of Inquiry-Based Learning Strategy on EFL Tenth-Grade Students’ Reading Comprehension
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作者 Hadeel Saleh Al-Khamaiseh 《Journal of International Education and Practice》 2023年第2期46-57,共12页
This study examined the potential effect of Inquiry-Based Learning Strategy(IBL)on the tenth-grade students’reading comprehension.Two groups and a quasi-experimental design were used.Two complete sections of grade 10... This study examined the potential effect of Inquiry-Based Learning Strategy(IBL)on the tenth-grade students’reading comprehension.Two groups and a quasi-experimental design were used.Two complete sections of grade 10 students from a public Secondary School for Girls in Irbid was randomly assigned by the researcher.The experimental group of 30 students was chosen first,and then the control group of 30 students.A pre-post reading comprehension test was designed before and after the study in order to fulfill its goals.Additionally,the experimental group was taught using the IBL strategy,whereas the control group was taught using the traditional teaching methods recommended in the tenth-grade Teacher’s Book.According to the findings,there were significant statistical differences favoring the experimental group over the control group.In light of the findings,the researcher recommended employing the IBL strategy to students with various levels and EFL skills. 展开更多
关键词 EFL Jordanian students inquiry-based learning strategy reading comprehension
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Machine learning and human‐machine trust in healthcare:A systematic survey
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作者 Han Lin Jiatong Han +4 位作者 Pingping Wu Jiangyan Wang Juan Tu Hao Tang Liuning Zhu 《CAAI Transactions on Intelligence Technology》 SCIE EI 2024年第2期286-302,共17页
As human‐machine interaction(HMI)in healthcare continues to evolve,the issue of trust in HMI in healthcare has been raised and explored.It is critical for the development and safety of healthcare that humans have pro... As human‐machine interaction(HMI)in healthcare continues to evolve,the issue of trust in HMI in healthcare has been raised and explored.It is critical for the development and safety of healthcare that humans have proper trust in medical machines.Intelligent machines that have applied machine learning(ML)technologies continue to penetrate deeper into the medical environment,which also places higher demands on intelligent healthcare.In order to make machines play a role in HMI in healthcare more effectively and make human‐machine cooperation more harmonious,the authors need to build good humanmachine trust(HMT)in healthcare.This article provides a systematic overview of the prominent research on ML and HMT in healthcare.In addition,this study explores and analyses ML and three important factors that influence HMT in healthcare,and then proposes a HMT model in healthcare.Finally,general trends are summarised and issues to consider addressing in future research on HMT in healthcare are identified. 展开更多
关键词 human-machine interaction machine learning trust
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Personalized assessment and training of neurosurgical skills in virtual reality:An interpretable machine learning approach
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作者 Fei LI Zhibao QIN +3 位作者 Kai QIAN Shaojun LIANG Chengli LI Yonghang TAI 《虚拟现实与智能硬件(中英文)》 EI 2024年第1期17-29,共13页
Background Virtual reality technology has been widely used in surgical simulators,providing new opportunities for assessing and training surgical skills.Machine learning algorithms are commonly used to analyze and eva... Background Virtual reality technology has been widely used in surgical simulators,providing new opportunities for assessing and training surgical skills.Machine learning algorithms are commonly used to analyze and evaluate the performance of participants.However,their interpretability limits the personalization of the training for individual participants.Methods Seventy-nine participants were recruited and divided into three groups based on their skill level in intracranial tumor resection.Data on the use of surgical tools were collected using a surgical simulator.Feature selection was performed using the Minimum Redundancy Maximum Relevance and SVM-RFE algorithms to obtain the final metrics for training the machine learning model.Five machine learning algorithms were trained to predict the skill level,and the support vector machine performed the best,with an accuracy of 92.41%and Area Under Curve value of 0.98253.The machine learning model was interpreted using Shapley values to identify the important factors contributing to the skill level of each participant.Results This study demonstrates the effectiveness of machine learning in differentiating the evaluation and training of virtual reality neurosurgical performances.The use of Shapley values enables targeted training by identifying deficiencies in individual skills.Conclusions This study provides insights into the use of machine learning for personalized training in virtual reality neurosurgery.The interpretability of the machine learning models enables the development of individualized training programs.In addition,this study highlighted the potential of explanatory models in training external skills. 展开更多
关键词 Machine learning NEUROSURGERY Shapley values Virtual reality Human-robot interaction
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Home-based Detection and Prediction of Diabetic Foot Ulcers at Early Stage Using Sensor Technology and Supervised Learning
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作者 Kamasamudram Bhavya Sai Rishi Raghu +2 位作者 Sai Surya Varshith Nukala Jayashree Jayaraman Vijayashree Jayaraman 《Journal of Harbin Institute of Technology(New Series)》 CAS 2024年第1期26-37,共12页
For years,foot ulcers linked with diabetes mellitus and neuropathy have significantly impacted diabetic patients’ health-related quality of life(HRQoL). Diabetes foot ulcers impact15% of all diabetic patients at some... For years,foot ulcers linked with diabetes mellitus and neuropathy have significantly impacted diabetic patients’ health-related quality of life(HRQoL). Diabetes foot ulcers impact15% of all diabetic patients at some point in their lives. The facilities and resources used for DFU detection and treatment are only available at hospitals and clinics,which results in the unavailability of feasible and timely detection at an early stage. This necessitates the development of an at-home DFU detection system that enables timely predictions and seamless communication with users,thereby preventing amputations due to neglect and severity. This paper proposes a feasible system consisting of three major modules:an IoT device that works to sense foot nodes to send vibrations onto a foot sole,a machine learning model based on supervised learning which predicts the level of severity of the DFU using four different classification techniques including XGBoost,K-SVM,Random Forest,and Decision tree,and a mobile application that acts as an interface between the sensors and the patient. Based on the severity levels,necessary steps for prevention,treatment,and medications are recommended via the application. 展开更多
关键词 diabetic foot ulcer PODIATRY diabetes mellitus healthcare footcare internet of things machine learning human⁃computer interaction
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Research on fault time prediction method for high speed rail BTM unit based on multi method interactive validation
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作者 Limin Fu Junqiang Gou +2 位作者 Chao Sun Hanrui Li Wei Liu 《High-Speed Railway》 2024年第3期164-171,共8页
The Balise Transmission Module(BTM)unit of the on-board train control system is a crucial component.Due to its unique installation position and complex environment,this unit has a higher fault rate within the on-board... The Balise Transmission Module(BTM)unit of the on-board train control system is a crucial component.Due to its unique installation position and complex environment,this unit has a higher fault rate within the on-board train control system.To conduct fault prediction for the BTM unit based on actual fault data,this study proposes a prediction method combining reliability statistics and machine learning,and achieves the fusion of prediction results from different dimensions through multi-method interactive validation.Firstly,a method for predicting equipment fault time targeting batch equipment is introduced.This method utilizes reliability statistics to construct a model of the remaining faultless operating time distribution considering uncertainty,thereby predicting the remaining faultless operating probability of the BTM unit.Secondly,considering the complexity of the BTM unit’s fault mechanism,the small sample size of fault cases,and the potential presence of multiple fault features in fault text records,an individual-oriented fault prediction method based on Bayesian-optimized Gradient Boosting Regression Tree(Bayes-GBRT)is proposed.This method achieves better prediction results compared to linear regression algorithms and random forest regression algorithms,with an average absolute error of only 0.224 years for predicting the fault time of this type of equipment.Finally,a multi-method interactive validation approach is proposed,enabling the fusion and validation of multi-dimensional results.The results indicate that the predicted fault time and the actual fault time conform to a log-normal distribution,and the parameter estimation results are basically consistent,verifying the accuracy and effectiveness of the prediction results.The above research findings can provide technical support for the maintenance and modification of BTM units,effectively reducing maintenance costs and ensuring the safe operation of high-speed railway,thus having practical engineering value for preventive maintenance. 展开更多
关键词 High speed rail BTM unit Remaining faultless operating time Machine learning Multi method interactive verification
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Stock Type Prediction Based on Multiple Machine Learning Methods
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作者 Zhonger Zhu Wansheng Wang 《Journal of Intelligent Learning Systems and Applications》 2024年第3期242-261,共20页
Stocks in the Chinese stock market can be divided into ST stocks and normal stocks, so to prevent investors from buying potential ST stocks, this paper first performs SMOTEENN oversampling data preprocessing for the S... Stocks in the Chinese stock market can be divided into ST stocks and normal stocks, so to prevent investors from buying potential ST stocks, this paper first performs SMOTEENN oversampling data preprocessing for the ST stock category, and selects 139 financial indicators and technical factor as predictive features. Then, it combines the Boruta algorithm and Copula entropy method for feature selection, effectively improving the machine learning model’s performance in ST stock classification, with the AUC values of the two models reaching 98% on the test set. In the model selection and optimization, this paper uses six major models, including logistic regression, XGBoost, AdaBoost, LightGBM, Catboost, and MLP, for modeling and optimizes them using the Optuna framework. Ultimately, XGBoost model is selected as the best model because its AUC value exceeds 95% and its running time is less. Finally, the XGBoost model is explained using the SHAP theory and the interaction between features is discovered, further improving the model’s accuracy and AUC value by about 0.6%, verifying the effectiveness of the model. 展开更多
关键词 Stock Classification Boruta Algorithm COPULA Machine learning interactION
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Research and Application of AI-Based Interactive Exhibits in Wuhan Museum of Science and Technology
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作者 Ting Yan 《Journal of Electronic Research and Application》 2024年第2期95-102,共8页
This article aims to explore the development and application of AI-based interactive exhibits in Wuhan Museum of Science and Technology.By utilizing computer vision,natural language processing,and machine learning tec... This article aims to explore the development and application of AI-based interactive exhibits in Wuhan Museum of Science and Technology.By utilizing computer vision,natural language processing,and machine learning technologies,an innovative exhibit development and application system is proposed.This system employs deep learning algorithms and data analysis methods to achieve real-time perception of visitor behavior and adaptive interaction.The development process involves designing user interfaces and interaction methods to effectively enhance visitor engagement and learning outcomes.Through evaluation and comparison in practical applications,the potential of this system in enhancing exhibit interaction,increasing visitor engagement,improving educational effectiveness,and expanding avenues for scientific knowledge dissemination are validated. 展开更多
关键词 Artificial intelligence interactive exhibits Computer vision Natural language processing Machine learning
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Spotted Hyena Optimizer Driven Deep Learning-Based Drug-Drug Interaction Prediction in Big Data Environment
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作者 Mohammed Jasim Mohammed Jasim Shakir Fattah Kak +1 位作者 Zainab Salih Ageed Subhi R.M.Zeebaree 《Computer Systems Science & Engineering》 SCIE EI 2023年第9期3831-3845,共15页
Nowadays,smart healthcare and biomedical research have marked a substantial growth rate in terms of their presence in the literature,computational approaches,and discoveries,owing to which a massive quantity of experi... Nowadays,smart healthcare and biomedical research have marked a substantial growth rate in terms of their presence in the literature,computational approaches,and discoveries,owing to which a massive quantity of experimental datasets was published and generated(Big Data)for describing and validating such novelties.Drug-drug interaction(DDI)significantly contributed to drug administration and development.It continues as the main obstacle in offering inexpensive and safe healthcare.It normally happens for patients with extensive medication,leading them to take many drugs simultaneously.DDI may cause side effects,either mild or severe health problems.This reduced victims’quality of life and increased hospital healthcare expenses by increasing their recovery time.Several efforts were made to formulate new methods for DDI prediction to overcome this issue.In this aspect,this study designs a new Spotted Hyena Optimizer Driven Deep Learning based Drug-Drug Interaction Prediction(SHODL-DDIP)model in a big data environment.In the presented SHODL-DDIP technique,the relativity and characteristics of the drugs can be identified from different sources for prediction.The input data is preprocessed at the primary level to improve its quality.Next,the salp swarm optimization algorithm(SSO)is used to select features.In this study,the deep belief network(DBN)model is exploited to predict the DDI accurately.The SHO algorithm is involved in improvising the DBN model’s predictive outcomes,showing the novelty of the work.The experimental result analysis of the SHODL-DDIP technique is tested using drug databases,and the results signified the improvements of the SHODLDDIP technique over other recent models in terms of different performance measures. 展开更多
关键词 Drug-drug interaction deep learning spotted hyena optimization feature selection CLASSIFICATION
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Research on Interactive Teaching Strategies of College English Teaching-Based on Super Star Learning Platform
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作者 李冬梅 《海外英语》 2020年第22期279-280,共2页
Super Star Learning Platform is a learning platform which meets the needs of interactive teaching mode both in and out of the classroom.This paper analyzes the advantages of interactive teaching strategies and the exi... Super Star Learning Platform is a learning platform which meets the needs of interactive teaching mode both in and out of the classroom.This paper analyzes the advantages of interactive teaching strategies and the existing problems to be solved.Super Star Learning Platform can effectively improve teaching efficiency by enhancing the interaction between teachers and students and motivating students’interest in learning. 展开更多
关键词 Super Star learning Platform college English interactive strategy
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Design of N-11-Azaartemisinins Potentially Active against Plasmodium falciparum by Combined Molecular Electrostatic Potential, Ligand-Receptor Interaction and Models Built with Supervised Machine Learning Methods
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作者 Jeferson Stiver Oliveira de Castro José Ciríaco Pinheiro +5 位作者 Sílvia Simone dos Santos de Morais Heriberto Rodrigues Bitencourt Antonio Florêncio de Figueiredo Marcos Antonio Barros dos Santos Fábio dos Santos Gil Ana Cecília Barbosa Pinheiro 《Journal of Biophysical Chemistry》 CAS 2023年第1期1-29,共29页
N-11-azaartemisinins potentially active against Plasmodium falciparum are designed by combining molecular electrostatic potential (MEP), ligand-receptor interaction, and models built with supervised machine learning m... N-11-azaartemisinins potentially active against Plasmodium falciparum are designed by combining molecular electrostatic potential (MEP), ligand-receptor interaction, and models built with supervised machine learning methods (PCA, HCA, KNN, SIMCA, and SDA). The optimization of molecular structures was performed using the B3LYP/6-31G* approach. MEP maps and ligand-receptor interactions were used to investigate key structural features required for biological activities and likely interactions between N-11-azaartemisinins and heme, respectively. The supervised machine learning methods allowed the separation of the investigated compounds into two classes: cha and cla, with the properties ε<sub>LUMO+1</sub> (one level above lowest unoccupied molecular orbital energy), d(C<sub>6</sub>-C<sub>5</sub>) (distance between C<sub>6</sub> and C<sub>5</sub> atoms in ligands), and TSA (total surface area) responsible for the classification. The insights extracted from the investigation developed and the chemical intuition enabled the design of sixteen new N-11-azaartemisinins (prediction set), moreover, models built with supervised machine learning methods were applied to this prediction set. The result of this application showed twelve new promising N-11-azaartemisinins for synthesis and biological evaluation. 展开更多
关键词 Antimalarial Design MEP Ligand-Receptor interaction Supervised Machine learning Methods Models Built with Supervised Machine learning Methods
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Enhancing EFL Students' Social Strategy Awareness and Use Through Interactive Learning Activities
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作者 高珍 《科技信息》 2011年第14期I0149-I0150,共2页
Based on prior studies and a questionnaire survey,this paper is seeking to demonstrate that interactive activities will facilitate EFL learners' social strategy awareness and use,and thus enhance their linguistic ... Based on prior studies and a questionnaire survey,this paper is seeking to demonstrate that interactive activities will facilitate EFL learners' social strategy awareness and use,and thus enhance their linguistic development.A sample lesson plan is also presented in this paper to illustrate that social strategy awareness and use can be improved through interactive learning activities. 展开更多
关键词 英语学习 学习方法 阅读 翻译
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Research and Practice of Hybrid Teaching for Software Testing based on Interactive Learning 被引量:1
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作者 Lipeng Gao Wei Zheng +2 位作者 Hongping Gan Depeng Gao Xikang Feng 《计算机教育》 2021年第12期126-131,共6页
To address the problems of insufficient number of personalized exercises and cases and teachers’lack of grasp of students’weak knowledge points in the current software testing online courses,we study the strategy of... To address the problems of insufficient number of personalized exercises and cases and teachers’lack of grasp of students’weak knowledge points in the current software testing online courses,we study the strategy of establishing and updating intelligent exercise sets and case libraries and analyze the answers and dig out the weak points of knowledge through group intelligence reasoning and interactive machine learning methods.This will help teachers to make uniform and targeted explanations,reduce manual judgment,and achieve intelligent teaching quality reform,and implement the educational concepts of“keeping up with the times”and“teaching according to students’abilities”. 展开更多
关键词 software testing hybrid teaching group intelligence reasoning interactive learning
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Approaches to Affective Computing and Learning towards Interactive Decision Making in Process Control Engineering 被引量:8
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作者 宿翀 李宏光 《自动化学报》 EI CSCD 北大核心 2013年第5期617-625,共9页
关键词 多目标决策问题 过程控制工程 情感计算 学习策略 PID参数整定 制作 法向 收敛性分析
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Development of Inquiry-Based Learning Tourism Products in Binzhou from the Perspective of Tourism Resources
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作者 MA Wenya HAN Tingting 《Journal of Landscape Research》 2019年第5期141-145,共5页
Under the macro-background of “all-for-one” tourism,this study analyzes the related concepts and characteristics of inquiry-based learning tourism to understand the significance and role of developing inquiry-based ... Under the macro-background of “all-for-one” tourism,this study analyzes the related concepts and characteristics of inquiry-based learning tourism to understand the significance and role of developing inquiry-based learning tourism in China.With Binzhou as the object of study,this study also explores the development of inquiry-based learning tourism products from the aspects of the product development idea,level,framework and marketing,with a view to providing references for implementing inquiry-based learning tourism activities in other regions. 展开更多
关键词 inquiry-based learning TOURISM TOURISM RESOURCE TOURISM PLUS Binzhou
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Foreign Language Web-Based Learning by Means of Audiovisual Interactive Activities
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作者 Catherine Kanellopoulou Minas Pergantis +2 位作者 Nikolaos Konstantinou Nikolaos Grigorios Kanellopoulos Andreas Giannakoulopoulos 《Journal of Software Engineering and Applications》 2021年第6期207-232,共26页
<p align="left"> <span style="font-family:Verdana;">Online learning has been on an upward trend for many years and is becoming more and more prevalent every day, consistently presenting... <p align="left"> <span style="font-family:Verdana;">Online learning has been on an upward trend for many years and is becoming more and more prevalent every day, consistently presenting the less privileged parts of our society with an equal opportunity at education. Unfortunately, though, it seldom takes advantage of the new technologies and capabilities offered by the modern World Wide Web. In this article, we present an interactive online platform that provides users with learning activities for students of English as a foreign language. The platform focuses on using audiovisual multimedia content and a user experience (UX) centered approach to provide learners with an enhanced learning experience that aims at improving their knowledge level while at the same time increasing their engagement and motivation to participate in learning. To achieve this, the platform uses advanced techniques, such as interactive vocabulary and pronunciation assistance, mini-games, embedded media, voice recording, and more. In addition, the platform provides educators with analytics about user engagement and performance. In this study, more than 100 young students participated in a preliminary use of the aforementioned platform and provided feedback concerning their experience. Both the platform’s metrics and the user-provided feedback indicated increased engagement and a preference of the participants for interactive audiovisual multimedia-based learning activities.</span> </p> 展开更多
关键词 Online learning MULTIMEDIA interactivity World Wide Web Education English Language Teaching learning Platform AUDIOVISUAL
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Design Principles-Based Interactive Learning Tool for Solving Nonlinear Equations
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作者 Ahad Alloqmani Omimah Alsaedi +2 位作者 Nadia Bahatheg Reem Alnanih Lamiaa Elrefaei 《Computer Systems Science & Engineering》 SCIE EI 2022年第3期1023-1042,共20页
Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer interaction.Thus,this paper aims to help s... Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer interaction.Thus,this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback,visibility,affordance,consistency,and constraints.It also compares these methods by the number of iterations and time required to display the result.This study helps students learn these methods using interactive learning tools instead of relying on traditional teaching methods.The tool is implemented using the MATLAB app and is evaluated through usability testing with two groups of users that are categorized by their level of experience with root-finding.Users with no knowledge in root-finding confirmed that they understood the root-finding concept when interacting with the designed tool.The positive results of the user evaluation showed that the tool can be recommended to other users. 展开更多
关键词 Graphical user interface(GUI) interactive learning tool design principles nonlinear equations experimental design
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URI Online Judge: A New Interactive Learning Approach
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作者 Neilor Avelino Tonin Jean Luca Bez 《Computer Technology and Application》 2013年第1期34-38,共5页
The URI online judge is a new online tool created with the main purpose of making programming practice more dynamic, interesting and stimulating for those who have just entered into the art of programming. The URI onl... The URI online judge is a new online tool created with the main purpose of making programming practice more dynamic, interesting and stimulating for those who have just entered into the art of programming. The URI online judge allows problem corrections in real time, interactivity between users, besides it allows flexibility in the choice of the programming language and it makes some supporting materials available. During the short time in which the tool has being used we have observed that it is a very good tool for self-study. As users of programming portals, the authors noticed some details that would be important to be implemented in a new tool, such as the separation of problems by categories. Another fundamental detail is the fact that this tool is available in two languages (Portuguese and English). This might facilitate the learning process for beginners, both locally and globally. 展开更多
关键词 Classroom tool programming practice online judge informatics interactive learning.
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