Lessons Learned From Four Computing Education Crowdsourcing Systems

Nea Pirttinen*, Paul Denny, Arto Hellas, Juho Leinonen

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

1 Sitaatiot (Scopus)
33 Lataukset (Pure)

Abstrakti

Crowdsourcing is a general term that describes the practice of many individuals working collectively to achieve a common goal or complete a task, often involving the generation of content. In an educational context, crowdsourcing of learning materials-where students create resources that can be used by other learners-offers several benefits. Students benefit from the act of producing resources as well as from using the resources. Despite benefits, instructors may be hesitant to adopt crowdsourcing for several reasons, such as concerns around the quality of content produced by students and the perceptions students may have of creating resources for their peers. While prior work has explored crowdsourcing concerns within the context of individual tools, lessons that are generalisable across multiple platforms and derived from practical use can provide considerably more robust insights. In this perspective article, we present four crowdsourcing tools that we have developed and used in computing classrooms. From our previous studies and experience, we derive lessons which shed new light on some of the concerns that are typical for instructors looking to adopt such tools. We find that across multiple contexts, students are capable of generating high quality learning content which provides good coverage of key concepts. Although students do appear hesitant to engage with new kinds of activities, various types of incentives have proven effective. Finally, although studies on learning effects have shown mixed results, no negative outcomes have been observed. In light of these lessons, we hope to see a greater uptake and use of crowdsourcing in computing education.

AlkuperäiskieliEnglanti
Sivut22982-22992
Sivumäärä11
JulkaisuIEEE Access
Vuosikerta11
DOI - pysyväislinkit
TilaJulkaistu - 2023
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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