Archaeology in video games: A quest to involve a wider audience in archaeology by the use of video games
Bibliographic record
Abstract
This research focuses on if and how video games could be used to reach out to and involve a wider and particularly younger audience of people between 20-45 years old in archaeology. By setting out a questionnaire among the players of three video games belonging to three major gaming genres, namely Assassin’s Creed: Origins (RPG), Battlefield 1 (FPS), and Sid Meier’s Civilization V (strategy), this research searches to investigate how the target audience perceives archaeological and historical aspects in video games (EA DICE, 2016; Firaxis Games et al., 2010; Ubisoft Montreal, 2017). The research looks to find out what gamers find important in video games and what genres are preferred to use in order to implement more real-life (virtual) archaeology. Furthermore, it researches how the target audience perceives archaeological aspects in video games and to what extent they would be interested to play video games in which a bigger focus lies on archaeology, or that are ‘archaeologically/historically accurate. Lastly, it was researched which of the selected video game genre(s) would be most suitable to use to involve a wider public in archaeology. The three set out surveys resulted in a total of 163 responses from men and women, concerning several ages and countries, including the Netherlands, the UK and the US. The results show that the participants are interested in archaeological aspects and historical accuracy in video games. A number of participants were more interested in archaeological activities than they were before playing the video game, which means that video games can indeed be used in order to reach out to and involve a wider audience in archaeology. The research shows that the participants preferred the role-playing genre to have more archaeological and historical aspects implemented in. The participants who played Assassin’s Creed: Origins were most interested in archaeology and history in video games, and also most open to archaeological activities in the real world, like visiting museums after playing the video game. In conclusion: The most preferred video game genre to use in order to reach out to a wider public is shown to be the role-playing genre.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".