• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Learning Analytics for Collaborative Writing: A Prototype and Case Study
 

Learning Analytics for Collaborative Writing: A Prototype and Case Study

on

  • 301 views

 

Statistics

Views

Total Views
301
Views on SlideShare
301
Embed Views
0

Actions

Likes
0
Downloads
0
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Learning Analytics for Collaborative Writing: A Prototype and Case Study Learning Analytics for Collaborative Writing: A Prototype and Case Study Presentation Transcript

    • [ Learning Analytics for Collaborative Writing ][ A Prototype and Case Study ] Brian McNely, Paul Gestwicki, J. Holden Hill, Phillip Parli-Horne, and Erika Johnson Ball State University
    • [ Motivation ]— Writing + Collaborative Knowledge— Formative Assessment ∆ - Zone of Proximal Development in networked environments
    • [ Analytics ] Project questions: — Do learning analytics related to collaborative writingfoster greater metacognition among participants? — Does such analytic data promote both instructor andpeer opportunities for real time interventions as formative assessment?
    • [ Analytics & Collaborative Writing ]Affordances of Google Docs: — Surfacing real-time collaborative writing activity — Ample opportunities for interventions and meta-talk — Suite of publicly available APIs + Docs Gdata API + Google Visualization API
    • [ Uatu Prototype | System Design ]
    • [ Uatu Prototype | Visualizations ]
    • [ Methods ]Systematic qualitative case study over 15 weeks, usingethnographic methods of fieldwork, including: — classroom observations — semi-structured and stimulated recall interviews — out of class observations of collaborative activity + pair programming + collaborative writing — documentary photography — collection of participant artifacts — triangulation across data types and instances
    • [ Data ] Total data collected includes: — 8 participants — 20 classroom observations — 24 semi-structured and stimulated recall interviews — 14 out of class observations — 70+ photographs — 19 participant-produced written artifacts + including granular composition/revision historycaptured by Uatu — 42,000+ words of fieldnotes and analytic memos
    • [ Findings | Overview ]
    • [ Theme 1 | Collocation ]
    • [ Theme 2 | Ephemera ]
    • [ Theme 3 | What “Counts” as Writing? ] — What kinds of practices meaningfully contribute to finalwritten deliverables? — How do we measure who “writes” in collocatedcollaborations? — What role do other forms of writing work play in theconstruction of final deliverables? — How can such contributions be measured?
    • [ Implications & Opportunities ] — Our prototype worked well, but it didn’t reveal much about novice software developer’s writing-in-practice. — The real utility of a system like Uatu is in: + Fully online learning environments + Distributed collaborative teams + Complex, ongoing, multi-contributor deliverables
    • [ Questions & Discussion ] brian.mcnely@gmail.com | paul.gestwicki@gmail.com