Assessment of Internet Learning for High School Students
Bibliographic record
Abstract
The generally poor academic performance of secondary school students across the United States is motivating educators to discover ways to improve school conditions of learning. Because the main source of knowledge is the Internet, helping students know how to use this tool wisely and relate their searching to cooperative learning group assignments is a focus of instructional concern. The purpose of this study was to determine how to improve Internet learning at a single high school. The principal chose to use student voice as the method and invited all students to take the Internet Learning Poll to find out how they felt about learning from the Internet. They were told that taking the poll was voluntary, not an assignment, their responses would be anonymous, and combined with other students. Of 461 students enrolled, 444 took the poll, yielding a school completion rate of 96%. Students wanted to be taught methods to improve their Internet research skills and how to evaluate website credibility. They maintained that teachers needed training to devise assignments which contribute to Internet searching and problem-solving practice in cooperative learning teams. Student polling presents evidence-based data to identify needs of students and contribute to better school practices. The elements used to establish the goals of continuous school improvement planning can be met by focusing on faculty improvement, student voice, and principal leadership.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".