Serious Games as a Complementary Tool for Social Skill Development in Young People: A Systematic Review of the Literature
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
Background The use of games for social skill development in the classroom is accelerating at a tremendous rate. At the same time, the research surrounding games designed for teaching social skills remains fragmented. This systematic review summarizes the current existing literature on social skill serious games for young people ages 5 to 19 and is the first review of serious games to note the demographic and geographic component of these studies. Method This review included papers that: evaluated a game designed to teach social skills; included measurable, quantitative outcomes; have a translation or be published in English; were peer-reviewed; date from January 2010 to May 2020; and have a nonclinical study population between ages of 5 to 19. Keywords were obtained from the CASEL 5 framework. Results Our findings are mixed but suggest that serious games may improve social skills when used alongside in-person discussion. We also found potential effects of the length of time of gameplay, intervention, and follow-up on social skill serious game effectiveness. Although this review found promising research conducted in East Asian countries and with minority samples in the United States, the majority of social skill serious game research takes place in the United States and Australia, with unreported demographic information and white-majority samples. Conclusions Due to the limited number of published studies in this area and studies lacking methodological rigor, the effectiveness of using games to teach social skills and the impact of background on social skill learning require further discussion.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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