An Integral Analysis of Teachers' Attitudes and Perspectives on the Integration of Technology in Teaching
Bibliographic record
Abstract
This chapters explores teachers' attitudes toward, and integration of, technology from multiple perspectives. In order to gain a rich and contextualized understanding of how teachers genuinely use technology in the classroom, Wilber's (2006) Integral methodological pluralism was used as a framework to orient the study, to organize the research questions and to provide the conceptual framework for the research methodology. Four research questions were addressed in this study: (1) What is the influence of policies on teachers' use of technology? (2) What influence does the technology infrastructure have on teachers using technology? (3) What do teachers believe and think about technology? (4) What is the technological culture that teachers' experience? This chapter is an overview of the analysis of the differing and sometimes conflicting practices, beliefs and views on the adoption of technology in the classroom, from the four quadrant perspectives of the Integral Model.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".