Technology-mediated learning environments for young English learners : connections in and out of school
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it