Technology-mediated learning environments for young English learners : connections in and out of school
Bibliographic record
Abstract
@contents: Selected Contets: Preface and Acknowledgments List of Contributors CHAPTER 1: Introduction: Technology-Based Learning Environments for Young English Learners In and Out of School (Leann Parker, University of California, Berkeley) CHAPTER 2: Technology and Literacy Development of Latino Youth (Richard Duran, University of California, Santa Barbara) REFLECTION: Literacy and English Learners: Where Does Technology Fit? (Robert Rueda, University of Southern California) CHAPTER 3: Technology, Literacy, and Young Second Language Learners: Designing Educational Futures (Jim Cummins, University of Toronto) REFLECTION: Rules of Engagement for Achieving Educational Futures (Olga A. Vasquez, University of California, San Diego) CHAPTER 4: Developing New Literacies Among Multilingual Learners in the Elementary Grades (Jill Castek, Donald J. Leu, Jr., Julie Coiro, Mileidis Gort, Laurie A. Henry, and Clarisse O. Lima University of Connecticut) REFLECTION: Integrating Language, Culture, and Technology to Achieve New Literacies for All (Bridget Dalton, Center for Applied Special Technologies, Inc.) CHAPTER 5: Technology and Second Language Learning: Promises and Problems (Yong Zhao and Chun Lai, Michigan State University) REFLECTION: Technology and Second Language Learning: Current Resources, Tools and Techniques (Gary A. Cziko, University of Illinois at Urban-Champaign) CHAPTER 6: Technology in Support of Young English Learners In and Out of School (Leann Parker, University of California, Berkeley) REFLECTION: ELLS and Technology: Transforming Teaching and Learning (Carla Meskill, State University of New York at Albany) CHAPTER 7: Technology Opening Opportunities for ELL Students: Attending to the Linguistic Character of These Students (Eugene E. Garcia, Arizona State University) CHAPTER 8: Conclusion: Reflecting on Technology and Young English Learners (L. Leann Parker, University of California, Berkeley) Author Index Subject Index
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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".