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Record W2526291441

Perceptions, Perspectives and Practices: A Study of the Players of Historical Games.

2016· article· en· W2526291441 on OpenAlexaboutno aff
Sian Beavers, Elizabeth FitzGerald

Bibliographic record

VenueOpen Research Online (The Open University) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumSituatedPerceptionMathematics educationTest (biology)Situated learningRelation (database)Set (abstract data type)Class (philosophy)PsychologyPedagogySociologyEpistemologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

The aim of the paper is to disseminate the findings of an empirical study that has had over 600 adult respondents from more than 30 countries. One of the aims of the survey was to address some of the gaps left by previous research relating to historical games (games that represent a historical period, event or place in some way) as pedagogical tools. Previous research covers the use of historical games in formal education and institutions to complement formal curricula (e.g. Squire 2004), for example, playing a game set in World War 2 (WW2) while learning about WW2 in class (Fisher, 2011). The participants in these prior studies were adolescent students or those in Higher Education, and/or studying within a specific historical discipline (Houghton 2015). With the use of any visual media in formal education, the teacher is integral to the learning process (Bage, 1997), but their perceptions of the media’s authenticity and their interest in the source material may bias the learner’s approach to the content (Stoddard, 2012). The results of the current study make an original contribution to the field by identifying player practices and perspectives in relation to historical games within informal, situated contexts, i.e. without any formal teaching activities taking place or explicit learning goals specified. Furthermore, it includes only adult respondents where less than a quarter are students and over half have non-academic occupations, so in many ways it constitutes a study of the perceptions and practices of the wider general public in relation to historical games, rather than a sub-section of the population whose primary daily activity is to learn about history. In this way, the work might be considered to have much wider impact than these previous studies.
\nAt the time of writing, the survey is still being fully analysed, but the findings arising from these data are important to the empirical study of player practices both in the field of historical game studies as well as games/learning/player-reception studies more generally.
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\nAs a whole, the findings from the survey will:
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\n1. Outline players’ understandings and perceptions of the history presented in historical games.
\n2. Explore players’ motivations and practices in relation to historical games as well as with other media forms, social or otherwise.
\n3. Provide some initial understanding of the informal/incidental historical learning that occurs through digital games outside of formal contexts.
\n4. Summarise player perspectives of the digital game form, in comparison with other visual media.
\n
\nFor example, do players who report playing historical strategy games like Civilization V (Firaxis 2010) believe they are more valuable tools for learning about the past than historical action-adventure games such as Assassin’s Creed 3 (Ubisoft 2012)? Do gamers play historical games with the explicit intention of discovering more about the past (“informal learning”) or for entertainment alone, but believe they have learned something about history as a by-product of play (“incidental learning”)? Does incidental learning via games produce informal learning in other media, such as books or documentaries? Is this relationship reciprocal, i.e. does incidental learning through historical drama produce informal learning with games, for example? The study also asks participants for specific examples of historical games that they perceive to be “authentic” (and conversely “inauthentic”) and why, to try and ascertain what elements of historical games they feel contribute to their potential uses for learning, or for what reasons they should be criticised as pedagogical tools. Although it is important to ask these questions about the perceptions of the player, the history and the games, it is also important to find out about the contexts that players engage with them, i.e. do they play online with friends and/or with people they don’t know? Do they play co-located, or alone? How likely are players to post to forums or social media in relation to the historical game? What is the content of such social, online interactions? The presentation will end by summarising the findings so far and discussing some of the limitations to this approach. We will also suggest how the results from the study in its entirety will contribute to original knowledge across multiple fields, and how they will be utilised going forward in the next phase of this research.
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\nBIBLIOGRAPHY
\nBage, G. 1997. “How Can We Teach History through Television?” Journal ofEducational Media 23 (2-3): 203–14.
\nFiraxis Games. 2010. Sid Meier's Civilization V. [PC Computer, Offline Game] 2K Games. Novatao, CA. USA.
\nFisher, Stephanie. 2011. “Playing with World War II: A Small-Scale Study of Learning in Video Games.” Loading... 5 (8): 71–89.
\nHoughton, Rob. 2015. “The Influence of Modern Media on Undergraduate Students of Medieval History.” Paper presented at The Middle Ages in the Modern World Conference, Lincoln, June 29 - July 2.
\nSquire, Kurt D. 2004. “Replaying History.” Unpublished PhD thesis. Indiana University, Bloomington.
\nStoddard, J. 2012. “Film as a Thoughtful Medium for Teaching History.” Learning, Media and Technology 37 (3): 271–88.
\nUbisoft Montreal. 2012. Assassin's Creed III. [Xbox 360, Offline Game]. Ubisoft. Montreuil France.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.415
GPT teacher head0.518
Teacher spread0.104 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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