Micro-persistence in the acquisition of computational thinking

Rotem Israel-Fishelson, Arnon Hershkovitz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Taking a Learning Analytics approach, we study the micropersistence of students in acquiring computational thinking. Micro-persistence is the behavior characterized by being persistent in completing a task with the best possible solution. We do so by analyzing data of 1st-6th-grade children (n=119) who used an online, game-based learning platform (CodeMonkey™). Overall, we find that micro-persistence is associated with task difficulty, and that contextual variables may explain persistence better than personal attributes.

Original languageEnglish
Title of host publicationProceedings of International Conference on Computational Thinking Education, CTE 2019
EditorsSiu-cheung KONG, Kuen-fung SIN, Diana ANDONE, Gautam BISWAS, Heinz Ulrich HOPPE, Ting-chia HSU, Ronghuai-Huai HUANG, Bor-chen KUO, Kwok-yiu Robert LI, Chee-kit LOOI, Marcelo MILRAD, Josh SHELDON, Ju-ling SHIH, Ki-sang SONG, Jan VAHRENHOLD
Pages18-23
Number of pages6
StatePublished - 2019
Event3rd International Conference on Computational Thinking Education, CTE 2019 - Hong Kong, Hong Kong
Duration: 13 Jun 201915 Jun 2019

Publication series

NameProceedings of International Conference on Computational Thinking Education

Conference

Conference3rd International Conference on Computational Thinking Education, CTE 2019
Country/TerritoryHong Kong
CityHong Kong
Period13/06/1915/06/19

Keywords

  • Computational thinking
  • Game-based learning
  • Learning analytics
  • Persistence
  • State-or-trait

All Science Journal Classification (ASJC) codes

  • Education
  • Computer Science Applications

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