Visualization and Data Presentation of Pedagogy, Learning Process & Outcome
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Author: Johnny Yuen ------------------------------ http://www.cite.hku.hk/news.php?id=501&category=cite
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Visualization and Data Presentation of Pedagogy, Learning Process & Outcome
- 1. Visualization and Data Presentation of Pedagogy, Learning Process & Outcome Johnny Yuen
- 2. BIG DATA
- 5. Big Data Analytics in sports • Predictive • Behavioral, Quantifiable data • Identical, “closed” settings with game rules • Simple goal, simple behavior • Finding patterns from lots of noises • Very different from educational settings!
- 6. Usage of IT in education • Different nature! – Year long activities, e.g. IES – Independent Enquiry Study • Individual students • The same process • Comparable participation – Topic module base activities, e.g. online discussion • Collaborative • Unequal participation – quantity and quality
- 7. Furthermore… • Differences in setting: • Pedagogy: transmission model, PBL, collaborative knowledge building… … • Pedagogical design frameworks: Contrasting cases, Predict-Observe-Explain, • Subject domain: Sciences, Languages • Cut-in point: Critical Thinking, Personal Epistemology, Motivation,
- 8. Supporting practice & reflections in educational settings, e.g. CSCL • Are students participating in the online discourse? • Are there students who made zero contribution? • Do ideas progress in the online discourse? • Can students raise questions that stimulate idea improvement? • What are the key content themes of the discussion threads? • Which notes have potential for further development? • Which aspect of the discussion can be further improved? • Is there any advancement in my students over 1 or 2 years of KB activities, in terms of question framing, evaluating and summarizing ideas, as reflected from their contributions to the online discourse?
- 9. COLODA 18 Feb 2012 Successful Pedagogies for Inquiry & Knowledge Building Collaborative Analysis Project Discussion data from any discussion platform in XML format Individual Participatory Statistics Keywords Analysis Researcher codings & further analyses Threads Analysis Social Networks Downloadable as MS Excel (.xls) format for charts or works with other student data Collaborators
- 10. Outputs can be organized into diff. levels… 18 Feb 2012 Successful Pedagogies for Inquiry & Knowledge Building : Individual students : notes : discussion threads : discussion views : date or week
- 11. Individual participatory statistics 18 Feb 2012 Successful Pedagogies for Inquiry & Knowledge Building Number of Scaffolds UsedNumber of Notes Created Percentage of notes read Percentage of Notes LinkedNumber of Revisions
- 12. Social Network Analysis 18 Feb 2012 Successful Pedagogies for Inquiry & Knowledge Building Year 1 Year 2 Year 3
- 13. Threads analysis module: 7/9/2013 0 0.5 1 1.5 2 2.5 3 Year 1 Year 2 Depthofdiscussionthread 6.5 7 7.5 Year 1 Year 2Numberofnotes Average Number of Notes per Thread Average Depth of Discussion Thread
- 14. Examples of question types • Attribute – What is the size of the smallest whale? – Where is the notice? • Definition – What is energy crisis? – What does global warming refer to? • Verification – Is it safe to drink the water only through looking at it? – Is carbon dioxide toxic and harmful?
- 15. Examples of question types • Procedure – How to make a water filter? • Reason – Why do water become brown color? – Why do we need to save water? • Mechanism – How can we protect these animals? – How do planktons give birth to the next generation?
- 16. Researcher Coding Types of questions raised in the discourse 18 Feb 2012 Successful Pedagogies for Inquiry & Knowledge Building
- 17. Keywords analysis module HK Kids discourse HK Kids Word Count 特徵(characteristic) 5 成因(cause) 4 個人(individual) 3 家長(parent) 62 傭人(maid) 42 社會(society) 15 政府(government) 51 教育制度(Education system) 15 精英制度(Elite system) 6 遺傳(inheritance ) 11 影響(influence) 6 經濟(Economics) 0 自理能力(Self- management) 20 責任(responsibility) 19 改善(improvement) 31 解決(solution) 14 訓練(training) 12 7/9/2013
- 18. Summary: Choosing the suitable type and focus of analysis for diff. types of learning • Behavior is affected by design and facilitation • Requires in-depth understanding about the design and intended learning goal of the discourse in order to interpret the visuals – Time series vs. snapshot – Whole class vs. individual – Quantity vs. quality