Using social annotations to augment the learning space and learner experience

Shaveen Singh, Bernd Meyer

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

Abstract

Learning has always been considered a social and collaborative activity. From the social constructivism perspective, students learn through the process of sharing experiences and build knowledge and understanding through discussion. This pilot study demonstrates the successful integration of an online social annotation tool in a Python programming workshop that allows students to discuss learning material and code segments with their fellow classmates. We investigate how the students leveraged the tool to improve their learning and to log their sentiments while reading the material and attempting the programming activities. We find that those students who had access to the annotation tool spent an above average amount of time on the material. They also had a higher completion rate and performance compared to the control group who did not have the annotation feature available to them. Feedback from the students who used the tool was very positive. Finally, we delve deeper into analysing the annotation patterns and explore how instructors can make use of fine-grained annotation data to inform and adapt the design of CS teaching and learning materials in online or blended contexts.
Original languageEnglish
Title of host publicationProceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education
EditorsArnold Pears, Mihaela Sabin
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages527-533
Number of pages7
ISBN (Electronic)9781450368957
ISBN (Print)9781450363013
DOIs
Publication statusPublished - 2019
EventAnnual Conference on Innovation and Technology in Computer Science Education 2019 - Aberdeen, United Kingdom
Duration: 12 Jul 201917 Jul 2019
Conference number: 24th
https://iticse.acm.org/

Conference

ConferenceAnnual Conference on Innovation and Technology in Computer Science Education 2019
Abbreviated titleITiCSE 2019
CountryUnited Kingdom
CityAberdeen
Period12/07/1917/07/19
Internet address

Keywords

  • annotations
  • digital education
  • engagement
  • situated cognition

Cite this

Singh, S., & Meyer, B. (2019). Using social annotations to augment the learning space and learner experience. In A. Pears, & M. Sabin (Eds.), Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education (pp. 527-533 ). New York NY USA: Association for Computing Machinery (ACM). https://doi.org/10.1145/3304221.3319767
Singh, Shaveen ; Meyer, Bernd. / Using social annotations to augment the learning space and learner experience. Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education. editor / Arnold Pears ; Mihaela Sabin. New York NY USA : Association for Computing Machinery (ACM), 2019. pp. 527-533
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Singh, S & Meyer, B 2019, Using social annotations to augment the learning space and learner experience. in A Pears & M Sabin (eds), Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education. Association for Computing Machinery (ACM), New York NY USA, pp. 527-533 , Annual Conference on Innovation and Technology in Computer Science Education 2019, Aberdeen, United Kingdom, 12/07/19. https://doi.org/10.1145/3304221.3319767

Using social annotations to augment the learning space and learner experience. / Singh, Shaveen; Meyer, Bernd.

Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education. ed. / Arnold Pears; Mihaela Sabin. New York NY USA : Association for Computing Machinery (ACM), 2019. p. 527-533 .

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

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Singh S, Meyer B. Using social annotations to augment the learning space and learner experience. In Pears A, Sabin M, editors, Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education. New York NY USA: Association for Computing Machinery (ACM). 2019. p. 527-533 https://doi.org/10.1145/3304221.3319767