Bibliographic record
Abstract
This article addresses problems inherent in traditional science teaching and argues that the pitfalls of assimilation and exclusion can be avoided by adopting an anthropological approach: regarding scientists as a subcultural group with its own language and ways of thinking about, investigating and explaining phenomena and events, its distinctive methods for generating new knowledge and solving problems, its tradition, history, set of conventions and underlying values. Students learn why scientists think and act in these ways, and how they differ from or resemble the practices and traditions of other subcultural groups. The other element in this approach to science education is the self-conscious metacognitive dimension: students knowing that this is what they are doing. More crucially, knowing which aspects to access for particular kinds of activities and encounters, when to use science and how to use it, when to use some other way of knowing. Border Crossings and Exclusion from Science Every individual has membership of a number of social groupings, some of which are long-term associations, others of which are merely temporary. Effective participation in these social groups is, of course, dependent on possession of the appropriate cultural knowledge that is, the shared understandings, beliefs and language, codes of behaviour, values and expectations of the group. Just as each student's personal framework of understanding is unique, so also is each student's complex of social group membership, their perceptions of what that membership entails and requires and, in consequence, their profile of cultural knowledge. When students, each with a distinctive personal and cultural framework of understanding, are presented with a particular learning task set within a distinctive educational context (involving a particular class or learning group), a unique learning context is created for each individual. Appreciation of the uniqueness of personal learning contexts helps to explain why some students learn successfully, while others of supposed equal ability do not, even in apparently very similar circumstances. It helps to explain why particular students may learn on some occasions, but not on others, despite circumstances that to others may seem identical. Factors that impact on learning include the student's views of school, science and the activities associated with learning science, relationships with peers, teachers and family, learning preferences and other aspects of metacognitive awareness, self-image, aspirations and values. Some are wide-ranging and stable over time; they govern the student's overall attitude and commitment to learning science. Others are topic-specific, even lessonspecific, and influence short-term decision-making about learning behaviour. For school-age students, the major social groupings of the family, the peer group and the school create distinctive ‘social worlds’ which may or may not have common cultural knowledge. Phelan et al (1991) suggest that points of similarity and difference between these three social worlds lead to four types of transition into the culture of the school, a transition that is crucial to students’ prospects of using the education system to further their life chances and career prospects. Their conclusions are that: • Congruent worlds facilitate smooth transitions • Different worlds require transitions to be managed • Diverse worlds lead to hazardous transitions • Highly discordant worlds result in transitions being resisted or proving impossible For science students there is an additional border to cross: transition into the culture of science, or the particular school version of it. School science has its own set of beliefs, values and codes of behaviour. It has its distinctive linguistic code. There are many students for whom the rules about the conduct of lessons, the conventions concerning
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.028 | 0.001 |
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; both teacher heads agree on what is shown here.
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".