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The Effect of Informing Agency in Self-Directed Online Learning Environments

on YouTube 14m
Talkat Learning at Scale 2020 · 2020-08-12..08-14· [ux-and-product-design]

speakers

name:Benjamin Xie
links:none on file
name:Greg L. Nelson
links:none on file
name:Harshitha Akkaraju
links:none on file
name:William Kwok
links:none on file
name:Amy J. Ko
links:none on file

resources

video:https://youtu.be/RECis5h5vuY
slides:none on file

summary

Built an online learning prototype called codits and run a one-week study with 79 novice programmers comparing three interfaces: informed high-agency, informed low-agency, and uninformed high-agency. The system uses an adapted Bayesian knowledge tracing to show skill bars and exercise recommendations. Results show added agency and adaptive information raise practice and motivation but produce no detectable learning gains; recommendations suffer distrust from cold starts and students often ignore them, reducing intended benefit.

AI-written summary · about

chapters (9)

  1. 0:00Intro
  2. 0:45how do learners navigate online experie....
  3. 2:33variations of Codeitz by agency, informa..
  4. 6:22study: one week to use Codeitz
  5. 6:53Codeitz: informing decision-making
  6. 7:54importance of features
  7. 9:14prior knowledge, self-efficacy predictive of test
  8. 10:08design implications: agency is nuanced
  9. 13:51The Effect of Informing Agency in Self- Directed Online Learning Environments

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