How Can Self-determination Theory’s Concept of “Autonomy Support” Help Address the Disconnect between Care Theory and Care Practice in Education?
Bibliographic record
Abstract
The purpose of this conceptual study is to explore the relationship between care theory (Noddings, 1984, 2005a, 2012, 2013; Tarlow, 1996) in educational contexts (Davis, 2001; Goldstein, 2002; McBee, 2007; McCroskey & Teven, 1997; Noddings, 2005a, 2013; Sugishita, 2000; Tarlow, 1996; Teven, 2007), and the concept of autonomy support , as advanced by self-determination theory (Deci & Ryan, 1985; Ryan & Deci, 2000). The author suggests that there is a gap between care theory and care practice in education. Most well-intended teachers believe they are caring, yet some students do not believe their teachers care for them. The students’ perception of teacher care is the key consideration. One of the reasons for the gap is that some well-intended teachers are unable or unwilling to relinquish control to their students and end up over-controlling their students’ behaviour. Self-determination theory’s (SDT) development of the concept of autonomy support is an important clarifier. Students need to retain agency and autonomy for their behaviour, and their teachers must be autonomy supportive. In addition to exploring the relationship between care theory and autonomy control, this paper will provide specific suggestions and strategies for enhancing the communication of care by practicing teachers and other educational leaders.
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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 | 0.002 | 0.002 |
| 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) | 0.000 | 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".