A Review of Jerry Wellington’s Teaching and Learning Secondary Science: Contemporary Issues and Practical Approaches
Bibliographic record
Abstract
Jerry Wellington’s “Teaching and Learning Secondary Science: Contemporary Issues and Practical Approaches” is a resource book for the teachers and teacher educators working in the field of science education. It has introduced the recent issues and hands on activities for teaching science primarily, considering the secondary level students. Jerry Wellington taught science at the school level and is now teaching education at the university level. The author has written so many books before and this science teaching book has been published in New York, London and Canada. It has been published in the print version and e-book version for available for all. It has tried to develop teachers as trainers and mentors. It has tried to cover the ten areas such as planning and managing, differentiation and special needs, practical work…and what it is for, investigations, Information, Communication and Technology (ICT) in science teaching and learning, building on children’s prior learning, handling controversial issues, language in science education, the nature of science, why to teach science . . . and why it is to learn¿ The writer focuses on the contemporary issues of teaching science which are seen quite relevant in the context of teaching science eduaction at both the school and university levels. The book is equally useful for university-level students who are going to be school and university-level science teachers to understand the issues of teaching and to select and use the approaches and methods for teaching science. Due to changes in society and the changes in Science and Technology, science teaching has been complex for novice secondary-level science teachers. They need to understand the recent issues and be familiar with the practical approaches. In this sense, this book provides support to the trainee science teachers on how to instruct in the classroom using innovative ways, how to use new teaching strategies for successful science teaching, how to use ICT in science teaching, how to plan science teaching, what types of questioning strategies to be used in science teaching, how to motivate students 82 A Review of Jerry Wellington’s Teaching and Learning Secondary Sci... toward knowledge construction and how to develop collaborative and cooperative though among students. This book recommends a variety of techniques including field trip, laboratory techniques, science competitions, and different ways of assessments. In this review, we have focused on three pertinent themes of the book: Arguments of teaching and learning, the beneficieries/recepients of science and the science curriculum development.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".