Adolescent Literacy in the Academic Disciplines: General Principles and Practical Strategies
Bibliographic record
Abstract
Adolescent Literacy in the Academic Disciplines: General Principles and Practical Strategies edited by Tamara L. Jetton and Cynthia Shanahan New York, NY: Guildford Press, 2012, 274 pages ISBN: ISBN: 978-1-4625-0283-7 (hardcover), 978-1-4625-0280-6 (paperback) In Adolescent Literacy in the Academic Disciplines, editors Tamara L. Jetton and Cynthia Shanahan provide an overview of principles and strategies for guiding student reading in high school subject areas. The introduction and framing of the book is well researched, convincingly written, and densely packed with practical information. Chapter 1, Learning from Text: Adolescent Literacy from the Past Decade by Tamara L. Jetton and Richard Lee, describes the performance of American high school students on literacy tests and suggests that teachers need to spend more than the current 3% of classroom time on explicit reading strategies (Ness, 2007, 2009, as cited in Jetton & Shanahan, 2012, pp. 1-2). Chapters 2, 3, and 4 describe common reading challenges in the disciplines, habits of text used by disciplinary experts, and how to apply these ideas to lesson planning. Chapters 5 through 9, written by a variety of American-based scholars, are dedicated to describing the literacy strategies needed for specific high school subject areas. Chapter 1 includes a review of studies on strategies and instructional frameworks, outlining the context of each study and the key findings. For instance, concept-oriented reading instruction (CORI) is described as a framework that involves students in activating prior knowledge, generating questions, searching for information, organizing new knowledge and monitoring their comprehension (Guthrie, 2004, as cited in Jetton & Shanahan, 2012, p.10). Jetton and Lee explain that essential components that make the framework successful are student involvement in their own goal setting, reading relevant material, and engaging in discussion. They cite two studies that support CORI as effective for increasing student reading comprehension. In addition, Appendix 1.1 elaborates on further strategies and each of their associated objectives and instructions (pp. 24-33). Providing such a thorough overview of these strategies works to raise awareness of the broad range of options available and encourages readers to think about potential applications, depending on objectives and context. Jetton and Lee explain that more research is needed on which strategies work best for specific disciplines, thereby setting up the thesis for the book. The chapters that focus on language arts, math, science, history, and the arts are helpful in their level of detail and the use of classroom examples to illustrate different teaching and learning strategies in action. At their best, these chapters are well organized, relate to the thesis, clearly define assumptions and theories, and offer relevant teaching strategies. For instance, in the chapter Learning with Texts in History: Protocols for Reading and Practical Strategies, Bruce VanSledright anchors his argument in a description of the unique challenges and opportunities afforded by historical texts. He explains that they are hypertextual (draw from other texts), intertextual (require reading between different versions of the same events), and partially multimodal (span a variety of forms and media from pottery to film). …
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| 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".