基于关联规则算法的英语网络教学模式与评价系统设计

IF 1.5 Q2 EDUCATION & EDUCATIONAL RESEARCH International Journal of Information and Communication Technology Education Pub Date : 2024-07-17 DOI:10.4018/ijicte.349007
Xu Sun, Ting Wang
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引用次数: 0

摘要

本研究通过应用改进的关联规则挖掘(ARM)算法,对英语网络教学进行了创新。它将 "兴趣 "参数整合到关联规则挖掘算法中,根据学习者的个人情况动态调整教学内容,提高学习者的参与度和学习效果。通过将学习内容与学习成绩(特别是 CET-4 和 CET-6 分数)相关联,跨不同在线平台的对照实验验证了 ARM 模型的有效性。全面的预处理确保了数据质量和隐私,采用了去标识化、数据扰动和聚合等技术。包括交叉验证和多元技术在内的高级数据分析增强了研究结果的可靠性。研究结果凸显了 ARM 模型生成个性化学习路径、超越传统方法的能力,以及作为数据驱动型教育改革基石的潜力。未来的研究将探索机器学习的改进和文化适应性,以扩大其影响,促进全球公平、高质量的数字英语教育。
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English Network Teaching Model and Design of Evaluation System Based on Association Rule Algorithm
This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an “interest” parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. Controlled experiments, spanning diverse online platforms, validate the ARM model's efficacy by correlating learning content with academic performance, specifically CET-4 and CET-6 scores. Comprehensive preprocessing ensures data quality and privacy, employing techniques like de-identification, data perturbation, and aggregation. Advanced data analysis, including cross-validation and multivariate techniques, bolsters findings' reliability. Results highlight the ARM model's capacity to generate personalized learning paths, transcending conventional methods, and its potential as a cornerstone for data-driven education reforms. Future research will explore machine learning refinements and cultural adaptability to broaden its impact, fostering equitable, high-quality digital English education worldwide.
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来源期刊
CiteScore
4.20
自引率
10.00%
发文量
26
期刊介绍: IJICTE publishes contributions from all disciplines of information technology education. In particular, the journal supports multidisciplinary research in the following areas: •Acceptable use policies and fair use laws •Administrative applications of information technology education •Corporate information technology training •Data-driven decision making and strategic technology planning •Educational/ training software evaluation •Effective planning, marketing, management and leadership of technology education •Impact of technology in society and related equity issues
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