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Record W2505733408 · doi:10.21125/edulearn.2016.0538

THE ROLE OF GAME JAMS IN DEVELOPING INFORMAL LEARNING OF COMPUTATIONAL THINKING: A CROSS-EUROPEAN CASE STUDY

2016· article· en· W2505733408 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEDULEARN proceedings · 2016
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
Fundersnot available
KeywordsJAMSComputer scienceComputational thinkingArtificial intelligencePolitical science

Abstract

fetched live from OpenAlex

This paper will present a cross-European experience of game jams as part of a Horizon 2020 funded project: No-one Left Behind (NOLB). The NOLB project was created to unlock inclusive gaming creation and experiences in formal learning situations from primary to secondary level, particularly for children at risk of social exclusion. The project has engendered the concept of game jams, events organised with the aim of designing and creating small games in a short time-frame around a central theme. Game jams can support engagement with informal learning beyond schools across a range of disciplines, resulting in an exciting experience associated with strong, positive emotions which can significantly support learning goals. This paper will disseminate experience of two cross-European game jams; the first a pilot and the second having over 95 submissions from countries across Europe, America, Canada, Egypt, the Philippians and India. Data collected through these games jams supports that coding, designing, reflection, analysing, creating, debugging, persevering and application, as well as developing computational thinking concepts such as decomposition, using patterns, abstraction and evaluation. The notion of game jams provides a paradigm for creating both formal and informal learning experiences such as directed learning experience, problem-solving, hands-on projects, working collaboratively, and creative invention, within a learner-centred learning environment where children are creators of their own knowledge and learning material. This paper explores the use of a mobile app, Pocket Code, in schools across Europe in two game jams during the academic year 2015-16 with children aged 11-18. Pocket Code provides an environment which supports learners in easily creating apps directly on their smart-phones and tablets through a visual Lego-style programming language where users can put code bricks together to form scripts. We draw on a range of data to support how game jams can be used as a design research method to observe the creation of knowledge in fast-paced, collaborative environments across a range of disciplines. Our data evidences that learners can be more motivated through game jams and that learners who are less likely to create games are nevertheless more engaged in a game jam setting. We will also present the frameworks for 3 games from different disciplines: Chemistry, Languages, and Mathematics.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.322
Teacher spread0.303 · 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