Teachers’ Use of Education Dashboards and Professional Growth
Bibliographic record
Abstract
Education dashboards are a means to present various stakeholders with information about learners, most commonly regarding the learners’ activity in online learning environments. Typically, an education dashboard for teachers will include some type of visual aids that encourage teachers to reflect upon learner behavior patterns and to act in accordance to it. In practice, this tool can assist teachers to make data-driven decisions, thus supporting their professional growth, however, so far, the use of education dashboards by teachers has been greatly understudied. In this research we report on two studies related to the associations between the use of education dashboards by elementary school teachers and the teachers’ professional growth. We used the framework defined by the International Society for Technology in Education’s (ISTE) Standards for Educators. In the first study, we took a quantitative approach (N=52 teachers), using an online self-report questionnaire, and found that the use of dashboards is positively associated with professional growth in the dimensions of facilitator, analyst, designer, and citizen. In the second study, we took a qualitative approach (N=9 teachers), using semi-structured interviews, to shed light on the mechanisms through which teachers benefit from the use of education dashboards.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".