Instructional Technology Innovation AsTransformational Learning:Female Faculty’s Narratives Of Experience
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
Workplaces are potential learning communities that invite critical reflection on practice that can be shared with others. Higher Education (HE) may be described as a workplace in which instructional development activity may be a form of inquiry in which faculty see “the taken-for-granted with new eyes” [33, p.3], prompting them to critically reflect upon their experiences and practice and leading to a foundational reframing of their core beliefs, assumptions, and values and subsequent actions [31]. Instructional innovation in HE can be personally risky, yet this is the level at which transformational thinking and action occurs and is sustained. The incorporation of instructional technology into teaching practice extends an already complex environment, introducing an unfamiliar realm of expertise. This complexity may be increased for female faculty who already experience some degree of marginalization in HE. The study on which this paper is based is a feminist project of narrative inquiry informed by the theoretical constructs of transformative learning, and feminist pedagogy in technology-enhanced environments. In this framework narratives of experience can be understood as “statement(s) of belief, of morality” that are values-based, doing social and political work as they are told [19, p.12]. In this study 47 female faculty from Canadian universities participated in research conversations as both method and site for the construction of personal and sociocultural understanding and change. Comparative analysis of the conversations reveal several interacting themes including psychosocial issues related to female faculty teaching with technology, the role of collaborative design conversations in perspective transformation, and relational practice for action 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.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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