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  • 1
    In: SAGE Open, SAGE Publications, Vol. 12, No. 1 ( 2022-01), p. 215824402110711-
    Abstract: Air passenger traffic prediction is crucial for the effective operation of civil aviation airports. Despite some progress in this field, the prediction accuracy and methods need further improvement. This paper proposes an integrated approach to the prediction of air passenger index as follows. Firstly, the air passenger index is defined and classified by the K-means clustering method. And then, based on mutual information (MI) principle, the information entropy is used to analyze and select the key influencing factors of air passenger travel. By incorporating the MI principle into the support vector regression (SVR) framework, this paper presents an innovative MI-SVR machine learning model used to predict the air passenger index. Finally, the proposed model is validated by air passenger throughput data of the Shanghai Pudong International Airport (PVG), China. The experimental results prove MI-SVR model feasibility and effectiveness by comparing them with conventional methods, such as ARIMA, LSTM, and other machine learning models. Besides, it is shown that the prediction effect of each model could be improved by introducing influencing factors based on MI. The main findings are considered instrumental to the airport operation and air traffic optimization.
    Type of Medium: Online Resource
    ISSN: 2158-2440 , 2158-2440
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2628279-3
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  • 2
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2023
    In:  International Journal of Educational Technology in Higher Education Vol. 20, No. 1 ( 2023-04-14)
    In: International Journal of Educational Technology in Higher Education, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2023-04-14)
    Abstract: According to previous studies, traditional laboratory safety courses are delivered in a classroom setting where the instructor teaches and the students listen and read the course materials passively. The course content is also uninspiring and dull. Additionally, the teaching period is spread out, which adds to the instructor's workload. As a result, students become less motivated to learn. In contrast, artificially intelligent educational robots (AIERs), help students learn while lessening the workload on instructors by enhancing teaching strategies, using robots to substitute for teachers, giving students access to a variety of instructional content, and improving interaction with students through the use of intelligent voice interactions and Q & A systems to promote student engagement in learning. If the robot is used for a long time for learning, it may lead to a decrease in students' interest in learning. Therefore, this study introduces the GAFCC model (the theory-driven gamification goal, access, feedback, challenge, collaboration design model) as an instructional design model to guide the development of a gamified AIER system, aiming to improve students' motivation and learning effectiveness for laboratory safety courses. To test the effectiveness of the system, this study conducted an experimental study at a university in China in the summer of 2022. 53 participants participated in the research, with a random sample taken from each group. Each participant was able to choose the time of their free time to engage in the experiment. There were 18, 19, and 16 participants in experimental group 1, experimental group 2, and the traditional group, respectively. Students in experimental group 1 learned using the gamified AIER system, students in experimental group 2 learned on a general anthropomorphic robot system and the control group received traditional classroom learning. The experimental results showed that compared to the other two groups, the gamified AIER system guided by the GAFCC model significantly improved students' learning achievement and enhanced their learning motivation, flow experience, and problem-solving tendency. In addition, students who adopted this approach exhibited more positive behaviors and reduced cognitive load in the learning process.
    Type of Medium: Online Resource
    ISSN: 2365-9440
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2843150-9
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  • 3
    Online Resource
    Online Resource
    Sciedu Press ; 2017
    In:  International Journal of Higher Education Vol. 6, No. 2 ( 2017-04-12), p. 188-
    In: International Journal of Higher Education, Sciedu Press, Vol. 6, No. 2 ( 2017-04-12), p. 188-
    Abstract: Visual communication design (VCD) is a form of nonverbal communication. The application of relevant linguistic or semiotic theories to VCD education renders graphic design an innovative and scientific discipline. In this study, actual teaching activities were examined to verify the feasibility of applying narrative theory to graphic design courses. Matched group design was employed to equally divide 30 participants into experimental and control groups, who participated in distinct activities over a 4-week period. The results revealed that incorporating narrative theory into graphic design courses enabled increasing students’ poster design capabilities across various dimensions, including thematic concept, image creativity, and visual aesthetic. Narrative is a storytelling method. Applying narrative techniques to VCD not only facilitates the creativity of designers, but also elicits the audience’s visual memory, thereby encouraging a bidirectional communication between the two entities.
    Type of Medium: Online Resource
    ISSN: 1927-6052 , 1927-6044
    Language: Unknown
    Publisher: Sciedu Press
    Publication Date: 2017
    detail.hit.zdb_id: 3007023-5
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  • 4
    Online Resource
    Online Resource
    SAGE Publications ; 2022
    In:  SAGE Open Vol. 12, No. 3 ( 2022-07), p. 215824402211215-
    In: SAGE Open, SAGE Publications, Vol. 12, No. 3 ( 2022-07), p. 215824402211215-
    Abstract: This paper understands the personality traits and cluster types of physical education (PE) teachers in elementary schools. A total of 393 elementary PE teachers volunteered to participate in this study. The Personality Trait Questionnaire for PE teachers in elementary school was summarized and compiled on the basis of the theory of the Big Five personality traits. The researchers used the discriminant analysis method to analyze and obtain the data. The results show that the Big Five personality traits of PE teachers in elementary schools was agreeableness. Classification of the Big Five personality traits through discriminant analysis revealed a Wilk’s λ value of .199, an eigenvalue of 3.254, and 94.7% of the variance explained. Use of Ward’s minimum variance method indicated that the participants’ personalities were characterized by steady and pioneering type, sensitive and cautious type, and moderate and peaceful type. There were more males than females in the steady and pioneering type, more steady and pioneering type under the age of 30 years old, and more moderate and peaceful type with more than 16 years of work experience. In conclusion, most the personality traits of PE teachers in elementary school were agreeableness, moderate and peaceful type, which shows that most PE teachers have calm emotions, appropriate expressions of emotions, regularity, optimism, and enjoy interacting and collaborating with others.
    Type of Medium: Online Resource
    ISSN: 2158-2440 , 2158-2440
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2628279-3
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