Supporting Knowledge Sharing for the Co-design of Digital Learning Games
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 13647 LNCS, Page: 32-42
2022
- 1Citations
- 5Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
This paper deals with knowledge sharing during a collaborative and design-based research project about game-based learning. According to a literature review about serious game design, a key process for collaborative work is knowledge sharing. This process is analysed with the frames of praxeologies and boundary objects. The praxeology framework aims to identify the participants’ practice and discourse about this practice for the design of serious games. The boundary objects framework aims to identify knowledge transactions during collaborative work. We collected data from workshops dedicated to co-design of TSADK, a serious game for computer education. We performed a thematic analysis on participants’ verbatim for nine workshops. The thematic analysis focuses on one subject: the learning outcomes of the game. The analysis has identified themes on this subject: to specify, to phrase and to select the main learning outcomes. Regarding these themes, the praxeology and boundary object frameworks allow us to identify common practice but no common knowledge and thus, an obstacle to collaboration. Based on these results, we propose a tool for supporting the collaboration design through sharing knowledge.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85144436734&origin=inward; http://dx.doi.org/10.1007/978-3-031-22124-8_4; https://link.springer.com/10.1007/978-3-031-22124-8_4; https://dx.doi.org/10.1007/978-3-031-22124-8_4; https://link.springer.com/chapter/10.1007/978-3-031-22124-8_4
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know