Navigating technology in the classroom: a scoping review of technology use during peer collaboration in early educational settings
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.
Bibliographic record
Abstract
Early educational settings such as early childhood education and care and kindergarten (i.e. formal schooling) are important contexts to foster children’s peer collaboration, an important skill for the twenty-first century. The prevalence of technology in early educational settings has continued to increase rapidly in ways that can support the development of peer collaboration. The purpose of this scoping review, therefore, was to identify the types of technology used to support peer collaboration in early educational settings. The search was conducted in ERIC, PsycInfo, Education Source, and Child Development and Adolescent Studies. This scoping review is based on 24 articles that incorporate use of technology during peer collaboration in educational settings with at least one child between the ages of zero to six years of age. The results of this review found six types of technology hardware (iPads, computers, robots, Microsoft Kinect, multi-touch tables, and cameras) and seven software types (video games, digital drawing, media capture, mixed reality, tangible programming, multimedia editing, and content delivery) that were used to support the development of collaboration in early educational settings. While interacting with these hardware and software types, children were observed engaging in the following collaborative skills: exchanging ideas, turn-taking, negotiating, sharing, joint understanding of goals/processes, joint action, and other behaviours. Findings from this review synthesise empirical evidence that can serve as a tool for educators and researchers when considering the integration of technology in the classroom to foster early peer collaboration skills.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it