Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and Interest
<span style="color: windowtext;">The goal of this paper is to utilize available big and open data sets to create content for a board and a digital game and implement an educational environment to improve students’ familiarity with concepts and relations in the data and, in the proces...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-10-01
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| Series: | Big Data and Cognitive Computing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-2289/4/4/30 |
| _version_ | 1797550162119229440 |
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| author | Irene Vargianniti Kostas Karpouzis |
| author_facet | Irene Vargianniti Kostas Karpouzis |
| author_sort | Irene Vargianniti |
| collection | DOAJ |
| description | <span style="color: windowtext;">The goal of this paper is to utilize available big and open data sets to create content for a board and a digital game and implement an educational environment to improve students’ familiarity with concepts and relations in the data and, in the process, academic performance and engagement. To this end, we used Wikipedia data to generate content for a Monopoly clone called Geopoly and designed a game-based learning experiment. Our research examines whether this game had any impact on the students’ performance, which is related to identifying implied ranking and grouping mechanisms in the game, whether performance is correlated with interest and whether performance differs across genders. Student performance and knowledge about the relationships contained in the data improved significantly after playing the game, while the positive correlation between student interest and performance illustrated the relationship between them. This was also verified by a digital version of the game, evaluated by the students during the COVID-19 pandemic; initial results revealed that students found the game more attractive and rewarding than a traditional geography lesson.</span> |
| first_indexed | 2024-03-10T15:25:35Z |
| format | Article |
| id | doaj.art-64b33f937b4e4627a92b7787470e5bfa |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-10T15:25:35Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-64b33f937b4e4627a92b7787470e5bfa2023-11-20T18:03:27ZengMDPI AGBig Data and Cognitive Computing2504-22892020-10-01443010.3390/bdcc4040030Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and InterestIrene Vargianniti0Kostas Karpouzis1Palladio School, 28is Oktovriou, 166 72 Vari, GreeceArtificial Intelligence and Learning Systems Lab, National Technical University of Athens, 157 80 Athens, Greece<span style="color: windowtext;">The goal of this paper is to utilize available big and open data sets to create content for a board and a digital game and implement an educational environment to improve students’ familiarity with concepts and relations in the data and, in the process, academic performance and engagement. To this end, we used Wikipedia data to generate content for a Monopoly clone called Geopoly and designed a game-based learning experiment. Our research examines whether this game had any impact on the students’ performance, which is related to identifying implied ranking and grouping mechanisms in the game, whether performance is correlated with interest and whether performance differs across genders. Student performance and knowledge about the relationships contained in the data improved significantly after playing the game, while the positive correlation between student interest and performance illustrated the relationship between them. This was also verified by a digital version of the game, evaluated by the students during the COVID-19 pandemic; initial results revealed that students found the game more attractive and rewarding than a traditional geography lesson.</span>https://www.mdpi.com/2504-2289/4/4/30big dataopen datagame-based learningeducationgeographyboard games |
| spellingShingle | Irene Vargianniti Kostas Karpouzis Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and Interest Big Data and Cognitive Computing big data open data game-based learning education geography board games |
| title | Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and Interest |
| title_full | Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and Interest |
| title_fullStr | Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and Interest |
| title_full_unstemmed | Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and Interest |
| title_short | Using Big and Open Data to Generate Content for an Educational Game to Increase Student Performance and Interest |
| title_sort | using big and open data to generate content for an educational game to increase student performance and interest |
| topic | big data open data game-based learning education geography board games |
| url | https://www.mdpi.com/2504-2289/4/4/30 |
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