Bibliographic record
Abstract
Students at Risk provides essential support for teachers and caregivers with interests in students' learning styles and learning psychology.The author, Cheryll DuQuette researches special education and works closely with teacher education programmes.She develops concrete and "hands on" classroom programmes for teachers that support them.The 159-page book is presented in a readable font, includes a navigation-friendly table of contents at the front, and index at the back.Its cover page encapsulates the content by depicting a 12-year-old child that is looking depressed sitting alone on the bench with books by his side in the hallway.Right after the picture, the title Students at Risk appears in a manner that (combined with the picture) attracts the attention of educators and parents who are looking for answers to their questions regarding students at risk in educational settings.In addition to these merits, Students at Risk also provides practical examples and ideas on how to mindfully handle and provide responsive care for students at risk.DuQuette speaks in detail about the concepts and relevance of diversity, inclusion, and individual learning to assess the effectiveness of inclusion of all types of students in any learning environment.She makes a case for inclusion of different kinds of learners in classrooms, focusing specifically on problems that adolescents encounter.Diversity and inclusion, as Cushner (1992) mentions, is a changing paradigm of education.DuQuette explores diversity and inclusion with the goal of supporting students with special needs.She wants to help teachers understand, accept, and practice appreciation of such students in their classrooms.Moreover, she wants teachers to address students' needs by planning and executing lessons in a manner that is engaging and constructive for such learners.She suggests that teachers "feel frustrated at their perceived inability to teach all their students, let alone meet individual needs" (p. 7).She elucidates practical guidelines for teaching and supporting students with exceptions through differentiated learning methodologies.The core objective of the book is to value inclusion in a class that has different types of learners with differing needs.DuQuette uses plain language and expressions to disseminate ideas and concepts to readers.Therefore, this book can easily be used as a handy tool by teachers, parents, or caregivers.Almost all of the chapters use case studies and describe hands-on activities to illustrate concepts.The content is clear.To make it more reader friendly, the definitions of all major concepts are provided briefly on the left side of the main text on most pages.The first three chapters of the book depict the whole process of working with students at risk, stage by stage, starting from observation of children to formulation of goals to development of strategies and, finally, to implementation and review of the action plan.These chapters
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.010 |
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".