Using WebQuests to Support the Development of Digital Literacy and Other Essential Skills at the K-12 Level
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
This chapter introduces the WebQuest as one means of addressing effective technology use for developing digital literacy skills at the K-12 education levels. It argues that technology use that promotes constructivist learning principles has been found to have the greatest effect on learning. Furthermore, the WebQuest and its extension, the Web Inquiry Project, exemplify strategies that promote constructivist learning principles when they are designed to encourage student-directed learning, problem solving, higher-level thinking, perspective taking, real-world authentic issues, and collaboration. The author hopes that by providing specific examples of each of these strategies, readers will be better able to envision effective, constructivist-based technology use for their classrooms.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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