本文探讨了Python数据分析在跨境电商课程中的应用,通过设计具体的案例分析,评估其实施效果。文章首先介绍了跨境电商行业背景及数据分析的重要性,随后详细阐述了基于Python的数据分析在数据采集、预处理、分析及可视化等方面的应用。通过实际案例,展示了Python数据分析在商品信息抓取、用户行为分析、销售趋势预测等方面的效果。最后,通过问卷调查和成绩分析等方法,本研究的目的是评估在跨境电子商务课程中运用Python进行数据分析的有效性,并针对这一教学方法提出相关改进建议。通过对该主题的深入探讨,本论文旨在为跨境电子商务教育领域引入创新的学习理念和实践方法,从而提升学生在数据分析技能方面的能力,以更好地适应这一行业快速发展的需求。This article explores the application of Python data analysis in cross-border e-commerce courses, and evaluates its implementation effectiveness through the design of specific case studies. The article introduces the background of the cross-border e-commerce industry and the importance of data analysis at the beginning, and then elaborates in detail on the application of Python based data analysis in data collection, preprocessing, analysis, and visualization. Through real cases, the effectiveness of Python data analysis in capturing product information, analyzing user behavior, and predicting sales trends has been demonstrated. In the end, through methods such as questionnaire surveys and grade analysis, the purpose of this study is to evaluate the effectiveness of using Python for data analysis in cross-border e-commerce courses, and to provide relevant improvement suggestions for this teaching method. Through an in-depth exploration of this topic, this paper aims to introduce innovative learning concepts and practical methods for cross-border e-commerce education, thereby enhancing students’ abilities in data analysis skills to better adapt to the rapidly developing needs of this industry.
在大数据技术日新月异的现状,高职教育正面临着前所未有的机遇和挑战。为探索新路径,教育大数据通过利用现代化前沿的科技技术和手段,在课堂上通过个性化自适应的教学研究,发掘学生的潜在特点,同时也为高职院校赋能,打造新质生产力,符合不断探索职业教育改革的前沿理念,通过在课程中的个性化自适应教学,不仅仅符合学校的专业布局以及学科定位。在这个大数据以及人工智能的时代,适应技术发展的内在趋势,满足国家对高素质技能人才的新需求。With the rapid development of big data technology, higher vocational education is facing unprecedented opportunities and challenges. In order to explore new paths, educational big data uses modern cutting-edge scientific and technological technologies and means to explore students’ potential characteristics through personalized adaptive teaching research in the classroom. At the same time, it also empowers higher vocational colleges and creates new quality productivity, which is in line with the cutting-edge concept of constantly exploring vocational education reform. Through personalized adaptive teaching in the course, it not only conforms to the school’s professional layout and subject positioning. In this era of big data and artificial intelligence, it adapts to the inherent trend of technological development and meets the country’s new needs for high-quality skilled talents.
针对传统WEB技术课程中存在的教学内容与实际岗位要求脱节、教学过程以教师为主、科学全面的考核体系尚未建立等问题,研究一种面向需求和产教融合的岗课赛证一体化教学体系,旨在培养出适应社会发展需要的高水平技术技能人才。秉承以培养目标为基础、学生发展为中心、岗位需求为导向、区域发展为依托的课程体系构建原则,通过面向需求确定对应岗位、优化教学方式、加强行业联系、以赛促教促学、将证书考试融入教学等改革方法,实现了岗课赛证的融通,构建起了新的课程体系。基于WEB技术课程的教学改革与实践,取得了一系列优秀成果,包括就业率逐年提高,毕业生企业认可度高,证书获得率提高,部分证书实现零的突破,技能大赛获得省级奖项等。In response to the problems of disconnection between teaching content and actual job requirements, teacher-centered teaching process, and the absence of a comprehensive and scientific evaluation system in traditional web technology courses. Research on an integrated teaching system that combines job positions, courses, competitions and certificates integration, as well as competitions and certificates, aiming to cultivate high-level technical and skilled talents who can adapt to the needs of social development. Adhere to the principle of constructing a curriculum system that is based on the cultivation objectives, centered on students’ development, oriented by job requirements and relying on regional development. Through reform methods such as determining corresponding positions based on demands, optimizing teaching approaches, strengthening ties with the industry, promoting teaching and learning through competitions, and integrating certificate examinations into teaching. The integration of job positions, courses, competitions and certificates has been achieved, and a new curriculum system has been established. Based on the teaching reform and practice of WEB technology courses, a series of outstanding achievements have been made, including the continuous increase in the employment rate year by year, high recognition of graduates by enterprises, the improvement in the certificate acquisition rate, the achievement of a breakthrough from zero in some certificates, and the winning of provincial awards in skills competitions.
在多模态理论的框架下课程思政融入“人工智能”课程,构造了“人工智能”课程“1 + 1 + 1”教学策略。“人工智能”课程“1 + 1 + 1”教学策略建立了一个具有系统性、知识性、高效性、划时代的教育教学体系,不仅可以完成“人工智能”课程的基本教学要求,授课效果、教师素质得到极大的提高,而且高效地将思政融合到“人工智能”课程的学习中,从而实现思政育人的基本要求,进一步完成立德树人的根本任务。Under the framework of the multimodal theory, ideological and political education is integrated into the “Artificial Intelligence” course, and the “1 + 1 + 1” teaching strategy for the “Artificial Intelligence” course has been constructed. The “1 + 1 + 1” teaching strategy for the “Artificial Intelligence” course has established an educational and teaching system that is systematic, knowledge-based, efficient and epoch-making. It can not only fulfill the basic teaching requirements of the “Artificial Intelligence” course and greatly improve the teaching effect and the quality of teachers, but also integrate ideological and political education into the learning of the “Artificial Intelligence” course in an efficient manner, thus realizing the basic requirements of educating people with ideological and political education and further fulfilling the fundamental task of fostering virtue through education.
在教育数字化转型的背景下,本研究识别混合式学习作为提高高职学生学习参与度的策略。通过理论分析,本研究确立了面授学习、实践学习、线上学习及合作学习四个关键维度。为量化这些维度的影响,设计并实施了包含相关问题的问卷,随后进行信度与效度的系统评估。研究采用探索性因子分析确定问题权重,以及多元线性回归模型来评估各维度对学习参与度的具体贡献。模型的准确性和稳定性通过残差分析、交叉验证以及多重共线性检验来验证。研究结果揭示,所有学习维度均显著正向影响学习参与度,其中合作学习的贡献最为突出。基于以上发现,提出针对性策略以优化混合式学习环境,从而提升学习参与度,并促进教育质量的提升及数字化转型的实施。In the context of the digital transformation of education, this study identifies blended learning as a strategy to enhance student engagement in vocational education. Through theoretical analysis, the study establishes four key dimensions: face-to-face learning, practical learning, online learning, and collaborative learning. To quantify the impact of these dimensions, a questionnaire containing relevant questions was designed and administered, followed by a systematic evaluation of reliability and validity. The study employs exploratory factor analysis to determine the weighting of questions and multiple linear regression models to assess the specific contributions of each dimension to learning engagement. The accuracy and stability of the models were verified through residual analysis, cross-validation, and multicollinearity tests. The results reveal that all learning dimensions significantly and positively influence learning engagement, with collaborative learning making the most substantial contribution. Based on these findings, targeted strategies are proposed to optimize the blended learning environment, thereby enhancing learning engagement and promoting the improvement of education quality and the implementation of digital transformation.
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