Bibliographic record
Abstract
Technology has become an increasingly necessary tool for human activity, causing changes in routines and practices (Mishra & Koehler, 2006). Despite an increasing amount of money spent on technology by school boards, there is a lack of understanding about what teachers need to know in order to effectively integrate technology in classrooms. Technology in the field of education is inevitable; however, Mishra and Koehler (2006) suggest educators tend to examine it at face value. There is an unresolved conflict between the use of technology to make previous goals efficient and fulfilling the status-quo, versus the ability to have technology change the nature of pedagogy (Berg, Benz, Lasley & Raisch, 1998). This qualitative study aimed to elucidate if elementary teachers were utilizing technology in ways that were conducive for student learning. Rather than focusing on the types of technology utilized, this study examined how technology was integrated into school systems. Effective integration was examined through the goals of 21st century learning that require students to be creative, collaborate, and think critically. Data was derived from semi-structured interviews with two Ontario elementary educators. Using the technological pedagogical content knowledge framework, four themes emerged: teacher attitudes, learning and instructional strategies, critical thinking, and challenges and next steps. Although teachers have positive attitudes toward technology, findings suggest there is a lack of focus and professional development infusing technology with the 21st century learning goals. Furthermore, the ineffective utilization of technology appears to provide an ease for pedagogy rather than to enhance student learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 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".