Bibliographic record
Abstract
A great irony in this age of information technologies is that communication skills for many people have atrophied. Students take low levels of communication and high levels of information overload for granted. This state of affairs has dire consequences for education, where clear, cogent communication is a prerequisite to learning. While it is tempting to “get with the times” by reducing communication to brief, sloppy exchanges, our challenge as teachers is to contradict these trends by modeling formal communication and information skills. This chapter begins with a description of an effective teacher to remind us that teaching involves a wide range of dispositions, knowledge, and skills. The remainder of the chapter focuses on demonstrations, lesson planning, and instructional objectives. Lesson plans and objectives are fundamental tools for demonstrating the applications, explanations, and implications of technologies to your students. Demonstrations are the single most effective method for technology teachers. Organization and communication are the keys to effective demonstrations. The intent of this chapter is to provide you with the instructional tools that ground the practice of teaching technology studies. Communication, demonstrations, and lesson planning. These are the tools that will help you to immerse yourself in the craft of teaching. Recalling the model of reflective practice explained in the preface, this book takes the form of cycles that begin with you as a teacher. Over the first four chapters, you will be challenged to identify with certain instructional practices and techniques, and to choose among those with which you most identify. This chapter provides the tools for scaffolding a wide range of curriculum and instructional dispositions, knowledge, and skills. The operative word in this chapter is practice. Practice, practice, practice!Request access from your librarian to read this chapter's full text.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".