A Badge Design Framework for a Gamified Learning Environment: Cases Analysis and Literature Review for Badge Design
Bibliographic record
Abstract
BACKGROUND: In the past, the educational badge was an extrinsic means of rewarding the motivation to learn. Based on continued research, however, the badge began to be recognized as a scale to measure the learner's knowledge and skill and an important means of helping learners to gradually build intrinsic motivation by using certain extrinsic motivators. As the badge's value has grown, the importance of its design has garnered attention. OBJECTIVE: The objective of this research was to establish a badge design framework that can be used in a gamified learning environment. METHODS: Data were collected from previous studies on badge design, 943 badge cases were extracted from 11 online and offline gamification in education contents, and their patterns and features were analyzed. RESULTS: Based on the analysis of results from previous studies and 943 collected badge cases, our study suggests three conditions for badge design. Through the literature review and collected badge cases, our study designed a badge design framework. First, it is necessary to distinguish whether the type of learning activity required for earning badges is physical or conceptual. Second, it is necessary to distinguish whether the scale of an activity required for earning badges requires individual learning or interaction-induced learning. Third, it is important to review whether the time and effort invested in earning badges is simple, repetitive, and short-term or continuous and long-term. Based on these three conditions, collected badge cases were analyzed. To verify self-developed badge types, we conducted a chi-square test on the collected cases and confirmed that there was a significant difference for each of the eight badge types (Pearson chi-square 1117.7, P<.001). CONCLUSIONS: Through its literature review on previous studies, this study demonstrated the badge's educational effectiveness. The badge design framework suggested in our study is expected to resolve some of the difficulties experienced during the badge design process in a gamified learning environment, encourage efficient badge design, and maximize learning effect.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.022 | 0.015 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".