Integrating mobile devices into the computer science curriculum
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
Mobile devices such as cellular phones and smart personal digital assistants out-ship personal computers (PCs) 20 to 1, and for many students the mobile device is becoming the computer. Such devices are becoming more powerful than the PCs of twenty years ago and they represent a useful tool for conveying important computer science concepts. This calls for innovations in the computer science curriculum, not only in some specific courses but across the curriculum to create a motivating framework for computer science students. After all, students expect faculty to integrate leading edge technology in the classroom. Here we present our approach for integrating mobile devices into the Computer Science curriculum, supported by an example of our experience in integrating BlackBerry devices into two programming courses, a distributed systems course, and senior capstone projects. Some of the courses are lab-intensive where students experiment with the devices, and develop and deploy applications for them. Teaching computer science and programming in the context of mobile applications provides a motivating framework for students and inspires them to excel due to the practical experience they gain allowing them to develop applications for their own mobile devices.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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