資訊管理學報
林心慧, 邱靖棻, 曾祥景*, 廖奕雯 ;
頁: 67-91
日期: 2024/01
摘要: 教學型知識網紅的興起讓學習者可更方便地在網路上學習行銷知識，而資訊 爆炸亦讓學習者花費很多時間搜尋符合自身需求的影片。因此，藉由教育大數據 進行海量資料之分類，建立知識架構並有效推薦給學習者應是一重要趨勢。本研 究目的為以教學知識型網紅 TED x Talks 為例，建立一個行銷知識典範架構，並 透過教育大數據發展精準教育市場區隔與策略。研究方法包括質化與量化，前者 針對 TED x Talks 中行銷領域主題的影片進行文本分析，並於 YouTube 針對評論 進行情感分析，以建立行銷知識典範架構。後者建置問卷問項，使用決策樹分析 探討閱聽眾之行銷教育目標市場區隔，並搭配行銷知識典範架構，為閲聽眾制定 精準的教育策略及為學習平台之決策者提供決策建議
關鍵字: 教學/知識型網紅;TED x Tallks;精準教育;教育市場區隔;決策樹;
Abstract: The rise of instructional knowledge influencers has made it more convenient for learners to acquire marketing knowledge online. However, the information explosion has also led learners to spend a considerable amount of time searching for videos that meet their specific needs. Therefore, using educational big data to categorize massive amounts of information, establish knowledge frameworks, and effectively recommend content to learners is becoming an important trend. The purpose of this research is to use TED x Talks by instructional knowledge influencers as an example to create a marketing knowledge paradigm framework and develop precise education market segmentation and strategies through educational big data. The research methods include both qualitative and quantitative approaches. The qualitative approach involves textual analysis of marketing-related videos within TED x Talks and sentiment analysis of comments on YouTube to establish a marketing knowledge paradigm framework. The quantitative approach includes the development of survey questions and the use of decision tree analysis to explore market segmentation for marketing education goals among the audience. This is complemented by the marketing knowledge paradigm framework to formulate precise education strategies for the audience and provide decision-making recommendations for learning platform stakeholders.
Keywords: Instructional/Knowledge-based influencers, TED x Tallks, Precision education, Education market segmentation, Decision tree ;
瀏覽次數: 5303 下載次數: 176
引用 導入Endnote
頁: 67-91
日期: 2024/01
摘要: 教學型知識網紅的興起讓學習者可更方便地在網路上學習行銷知識，而資訊 爆炸亦讓學習者花費很多時間搜尋符合自身需求的影片。因此，藉由教育大數據 進行海量資料之分類，建立知識架構並有效推薦給學習者應是一重要趨勢。本研 究目的為以教學知識型網紅 TED x Talks 為例，建立一個行銷知識典範架構，並 透過教育大數據發展精準教育市場區隔與策略。研究方法包括質化與量化，前者 針對 TED x Talks 中行銷領域主題的影片進行文本分析，並於 YouTube 針對評論 進行情感分析，以建立行銷知識典範架構。後者建置問卷問項，使用決策樹分析 探討閱聽眾之行銷教育目標市場區隔，並搭配行銷知識典範架構，為閲聽眾制定 精準的教育策略及為學習平台之決策者提供決策建議
關鍵字: 教學/知識型網紅;TED x Tallks;精準教育;教育市場區隔;決策樹;
Developing a Marketing Knowledge Paradigm Framework and Precision Education Strategies for Instructional Knowledge Influencers
Abstract: The rise of instructional knowledge influencers has made it more convenient for learners to acquire marketing knowledge online. However, the information explosion has also led learners to spend a considerable amount of time searching for videos that meet their specific needs. Therefore, using educational big data to categorize massive amounts of information, establish knowledge frameworks, and effectively recommend content to learners is becoming an important trend. The purpose of this research is to use TED x Talks by instructional knowledge influencers as an example to create a marketing knowledge paradigm framework and develop precise education market segmentation and strategies through educational big data. The research methods include both qualitative and quantitative approaches. The qualitative approach involves textual analysis of marketing-related videos within TED x Talks and sentiment analysis of comments on YouTube to establish a marketing knowledge paradigm framework. The quantitative approach includes the development of survey questions and the use of decision tree analysis to explore market segmentation for marketing education goals among the audience. This is complemented by the marketing knowledge paradigm framework to formulate precise education strategies for the audience and provide decision-making recommendations for learning platform stakeholders.
Keywords: Instructional/Knowledge-based influencers, TED x Tallks, Precision education, Education market segmentation, Decision tree ;
瀏覽次數: 5303 下載次數: 176
引用 導入Endnote