Digital Tools in Mathematics Classrooms: Norwegian Primary Teachers’ Experiences
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 article explores the integration of digital tools in Norwegian primary school mathematics classrooms, focusing on teachers’ experiences. With the increasing use of technology in education, digital tools have the potential to enhance mathematics instruction by enabling personalised learning, increasing student engagement, and offering dynamic ways to visualise mathematical concepts. However, these tools also present challenges, such as the potential for student distraction and a lack of teacher confidence in using technology effectively. Using a collective case-study approach, we conducted semi-structured interviews with eleven mathematics teachers to examine how digital tools impact student learning, instructional practices, and the nature of mathematics education. The findings reveal both the potential of digital tools to foster differentiated learning and their limitations, including concerns about over-reliance on technology and difficulties in maintaining classroom focus. This study contributes to the ongoing conversation about digitalisation in education, offering insights into the practical realities teachers encounter and recommendations for optimising the use of digital tools in mathematics classrooms. Keywords: digital tools, teachers’ experiences, didactical tetrahedron, Norway
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 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