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Virginia Tech

Collaboratively Learning Computational Thinking

Abstract

dc:description.abstract

Skill sets such as understanding and applying computational concepts are essential prerequisites for success in the 21st century. One can learn computational concepts by taking a traditional course offered in a school or by self-guided learning through an online platform. Collaborative learning has emerged as an approach that researchers have found to be generally applicable and effective for teaching computational concepts. Rather than learning individually, collaboration can help reduce the anxiety level of learners, improve understanding and create a positive atmosphere to learning Computational Thinking (CT). There is, however, limited research focusing on how natural collaborative interactions among learners manifest during learning of computational concepts. Structured as a manuscript style dissertation, this doctoral study investigates three different but related aspects of novice learners collaboratively learning CT. The first manuscript (qualitative study) provides an overall understanding of the contextual factors and characterizes collaborative aspects of learning in a CT face-to-face classroom at a large Southeastern University. The second manuscript (qualitative study) investigates the social interaction occurring between group members of the same classroom. And the third manuscript (quantitative study) focuses on the relationship between different social interactions initiated by users and learning of CT in an online learning platform Scratch™. In the two diverse settings, Chi's (2009) Differentiated Overt Learning Activities (DOLA) has been used as a lens to better understand the significance of social interactions in terms of being active, constructive and interactive. Together, the findings of this dissertation study contribute to the limited body of CT research by providing insight on novice learner's attitude towards learning CT, collaborative moments of learning CT, and the differences in relationship between social interactions and learning CT. The identification of collaborative attributes of CT is expected to help educators in designing learning activities that facilitate such interactions within group of learners and look out for traits of such activities to assess CT in both classroom and online settings.

Degree

thesis:*
Name thesis:degree_name
PHD
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Engineering Education
Department dc:contributor.department
Engineering Education
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Chowdhury, Bushra Tawfiq
Chairs dc:contributor.committeechair
  • Lohani, Vinod K.
  • Johri, Aditya
Committee members dc:contributor.committeemember
  • Kafura, Dennis G.
  • McNair, Elizabeth D.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:12554
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/88016

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Chowdhury, Bushra Tawfiq. Collaboratively Learning Computational Thinking. doctoral thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/88016