Feeling the Slope with Augmented Reality Technology: Movements of Consciousness in the Learning of the Derivative
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
Abstract In this article, we explore how the concept of derivative is learned through a joint activity involving a tenth-grade student, an instructor, and an augmented reality application. This application, Touch the Derivative, allows users to trace a function graph with their hands and simultaneously displays the derivative function graph as they move their hands on the graph. This study is guided by the theory of knowledge objectification, which considers learning as a social, reflexive, and creative meaning-making dialectical process. The joint activity was qualitatively analyzed to answer the two research questions about the meaning of the derivative concept appearing in the joint activity and the role of contradictions. Focusing on the creative, embodied, and materialist process of becoming conscious of the function–derivative mathematical relations, in the results section we discuss the tenth-grader student’s movement of consciousness and the emerging contradictions outlining the semiotic means involved. The meaning-making process of the student progressed through four interrelated layers of consciousness, which evolved dynamically through the contradictions arising as a movement beyond the opposite perspectives of the student and the instructor. We conclude the article by emphasizing the need to understand the pedagogical potential of augmented reality in terms of the activity in which it is used.
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.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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