Bibliographic record
Abstract
Tools for Teaching in an Educationally Mobile World examines the challenges that undergraduate and postgraduate teachers often encounter when working with students from different national and cultural backgrounds. It focuses on the consequences for interactive teaching and for course design in a world where students, ideas and courses are mobile, using examples and experiences from a wide range of disciplines and national contexts. It not only considers Anglophone countries, including the USA, Canada, the UK, Australia and New Zealand, but also the use of English as a language of instruction in countries where neither teachers nor students are native English speakers. This book offers ideas for adjusting and adapting teaching approaches for culturally and linguistically diverse student groups. Students may cross national boundaries to seek accreditation, or the courses may be ‘transnational’, being designed in one country and delivered in another using local as well as ‘fly-in’ faculty. It draws upon growing good practice recommendations using tried and tested methods alongside the extensive and varied experience of the author. The book is structured around a selection of the most common issues and statements of belief held by educators, with key topics including: the impact of educational mobility on teaching and learning; teachers as mediators between academic cultural differences; learning and teaching in English; inclusive teaching and learning; encouraging student participation; assessing diverse students. With a wealth of practical tips and tools that help deal with these issues, this book will be of value to any educator working with students from culturally and linguistically diverse backgrounds. It will also interest those involved in the design of curriculum and pedagogy.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".