Bibliographic record
Abstract
Over the past few decades, global institutions such as the Organisation for Economic Cooperation and Development (OECD) have helped homogenize educational policy and similarities can now be seen in curricula across the globe (Priestley, 2002: Sahlberg, 2007). One feature of many new curricular models is the emphasis placed on giving students transferable, generic skills through a focus on studying ‘cross cutting themes’ which blur disciplinary boundaries e.g. France (Baillat & Niclot, 2010), Spain (Segovia et al., 2010), Canada (Hasni et al., 2015) and Australia (Long et al., 2010). It could be said that in preparing students for life in the post-industrial information age, the “what” that students require to know has now changed (Virtue et al., 2019). Interdisciplinary learning (IDL) is promoted as something which allows educators to facilitate this change and develop skills building and conceptual creativity in their pupils, factors which are crucial for the twenty-first century education system (Khadri, 2014; Kolmos, 2016). \nCritics of an integrated approach to learning argue that this can be detrimental to students because it dilutes and weakens the powerful knowledge contained within the disciplines (Young and Muller, 2010, Young et.al, 2014). The assumption, here, is that the acquisition of this ‘powerful knowledge’ is dependent on it being delivered through discrete, specialised subjects. However, others argue that the opposite it true and that by making learning experiential and allowing students to explore relevant problems and questions, knowledge is actually enhanced, memorials of events are created through the experiences and students are prepared more holistically for life beyond the school gates (Dewey: 1938, Guissani, 1995: Beane, 1997). This paper considers the purpose of schools, the nature of IDL in relation to knowledge and explores its usefulness as a tool to help educators to offer students “a response to a question one lives” (Guissani, 1995). It argues that rather than memorising facts for the purpose of passing exams for example, interdisciplinary approaches enable pupils to unitise digital technologies and memorialise learning which they can then use and apply in real life contexts.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".