Examining the Effectiveness of Mnemonics Serious Games in Enhancing Memory and Learning: A Scoping Review
Bibliographic record
Abstract
Mnemonics hold potential for promoting long-term memory. Hence, they are being leveraged in serious games aimed to support long-term retention and retrieval of information. However, there is limited work focused on synthesizing the published research and findings on mnemonics serious games with a view to uncovering the extent of their application and effectiveness. This scoping review aims to bridge this gap. Articles were retrieved from four databases (ACM Library, IEEE Xplore, Scopus, and Web of Science). The criteria for inclusion were that the papers must be user studies that focused on mnemonics and serious games at the same time, were written in English, and were published in peer-reviewed journals or conferences. Two researchers, with the guidance of a senior researcher, independently and collaboratively assessed the eligibility of the retrieved papers using the PRISMA flowchart, elicited the relevant data, and tabulated the results in tables and charts using the GPS (game play, purpose, and scope) model. There were 12 papers that were accepted in this scoping review. Overall, most of the mnemonics serious games had a positive effect on memory, suggesting that they hold potential for promoting long-term memory, especially in memorization-intensive instructions, where a good number of students still struggle to retain taught material due to pedagogical, personal, and social challenges. However, more research still needs to be conducted, especially in the area of player-created mnemonics and teaching users how mnemonics can be effectively created using visualization and elaboration techniques.
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 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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".