Sustainable Development Goals (SDGs)
一、團隊目標 Team Goals
現今人們的日常生活與巨量資料息息相關,因此如何幫助人們應用適合的技術或方法去找出巨量資料中所存在之潛在樣式或模型變成現今重要的顯學之一。傳統理論背景課程教學方法常常讓學生在學習缺乏動機,因此如何提升學生於巨量資料分析課程的學習動機成為本研究的重要課題。在本研究之中,我們針對巨資料分析採用「始、驗、穩」教學模式去解決相關實作問題。教師於課前分享相關學思達教材給學生進行預習,課中的教學模式輪流採用即時反饋系統及鷹架模式。我們的教學模式主要是確保教師所提供之相關學習鷹架最終是可拆除及可調整,同時我們也期望學生可以達成自行解決相關實作問題之近側發展區。
Today's daily life is closely related to big data. Therefore, how to help people apply suitable technologies or methods to find out the hidden patterns or models in big data has become one of the most important explicit sciences today. Traditional, theoretical background course teaching methods often make students feel bored in learning. Therefore, how to improve students' learning motivation in big data analysis courses has become an important topic of this study. In this study, we apply the "start, test, stabilize" teaching model to solve implementation problems in big data analysis. Teachers shared relevant sharestart teaching materials to students for preview before class. The teaching mode in the class alternately adopts the interactive response system and the scaffolding modes. Our teaching model is mainly to ensure that the relevant learning scaffolding provided by teachers is ultimately removable and adjustable. At the same time, we also expect students to reach a zone of proximal development where they can solve relevant implementation problems on their own.
二、招募學生條件 Desired Disciplines & Prior Knowledge of Student Participants
本團隊主要招募的學生對象為本校資訊管理或資訊工程系學生,團隊學生主要先經由資訊或統計基礎課程(如資料結構及演算法)為基底,並且經由相關程式設計課程(如物件導向程式、網站主從架構系統)為深化,最後經由巨量資料分析課程進行解決一系列真實世界的巨量資料分析。
Our team primarily recruits students from the Department of Information Management or the Department of Computer Science and Information Engineering at our university. The students in our team typically start with foundational courses in information or statistics (such as Data Structures and Algorithms). They then deepen their knowledge through relevant programming courses (such as Object-Oriented Programming and Web Client-Server Architecture Systems). Finally, they tackle a series of real-world big data analysis problems through courses in Big Data Analytics.
三、團隊指導教師群 Team Leaders & Members
四、校外合作社區、場域或企業
五、團隊相關連結(網頁、粉絲頁、等) Other Information
六、聯絡窗口 :
李士典 同學 611235112@gms.ndhu.edu.tw
113年團隊學生經驗分享