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Record W4400508448 · doi:10.54337/nlc.v14i1.8017

Minecrafters

2024· article· en· W4400508448 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the International Conference on Networked Learning · 2024
Typearticle
Languageen
FieldEngineering
TopicPower Line Inspection Robots
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

In response to significant global events such as the COVID-19 pandemic, educational environments are undergoing a fundamental transformation towards collaborative online spaces and networked learning. Networked learning includes (a) the process of learning with and through other people and resources and (b) the environment (i.e., the internet) and platforms (i.e., YouTube, websites, social media, discussion forums) that support these connections or networks (Hodgson & McConnell, 2019). This shift in how learning is done necessitates a reevaluation of pedagogical methods to foster the development of students' global skills and competencies. These competencies, as defined by the Council of Ministers of Education Canada (CMEC), are recognized as essential for individuals to not only adapt but thrive in our current and future world. This world is characterized by unprecedented simultaneous challenges, often referred to as a 'polycrisis,' and rapid advancements in artificial intelligence (A.I.) that have the potential to reshape every aspect of human existence. Therefore, it is imperative that we delve into a deeper investigation and understanding of innovative pedagogical approaches to ensure students are adequately prepared for the evolving landscape. Collaboration is arguably one of the most important of the global skills and competencies as it underpins many of the essential skills youth need to thrive in educational and non-educational settings. More specifically, collaboration underpins the type of networked learning rising in popularity in formal and informal learning settings (Bülow & Nørgård, 2021). As a result, this exploratory research focuses on Minecraft: Education Edition (M:EE) as a tool for developing collaboration through critical making and team-based learning. Over a five-day spring-break camp, two cohorts of students (grades four to six and grades seven to eight) participated in open-ended design-based learning challenges online (in the virtual meeting platform, Google Meet, and in the virtual world, M:EE). Data analysis revealed that collaboration manifested itself in three primary modes: co-constructing knowledge, peer-teaching, and conflict management. Analysis further revealed that younger versus older students build and collaborate in the online environment very differently, which at times mirrored the 'real world' classroom. These findings have implications for designing age-appropriate online learning experiences to support collaboration in a networked environment, especially within virtual simulation and creation worlds like Minecraft.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.602
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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