Commentary: Just in time learning with radio frequency identification devices (RFIDs)
Bibliographic record
Abstract
Few technologies are immediately appreciated for their potential to revolutionize our lives and overturn established practices. Telephones, radio, the computer, transistors, and the polymerase chain reaction come to mind as technical advances with a significant latency period before wide adoption. Radio frequency identification device (RFID)1 technology is one that is presently relevant to inventory logistics for production and sales but may become a link in the multimedia education of the future as many technologies such as mobile phones and personal digital assistants converge. Ultimately, computers may tell students what they should do and learn (just in time for the learning to be applied), rather than the student being the active initiator. In the 1950s, the Zenith television company (in the United States) introduced a corded remote channel changer because the chief executive of the company did not like getting up to adjust his television set. However, ubiquitous remote control devices only became commonplace when truly independent affordable remote controls appeared in the 1980s. Ultimately, students carrying an RFID may become their own remote control for making progress through modules of education or training that respond seamlessly to what a student knows (stored evaluations) and deliver material that needs to be learned or revised. In employment, a laboratory worker may be granted access to a secure laboratory only when safety courses have been completed or other requirements have been met. The same RFID that looks after training would be a key pass to secure facilities. Although this scenario has been anticipated, it is yet to become a reality [1]. The current technology that can support this is an RFID-embedded Secure Digital card that can communicate with computers and mobile phones [1]. RFID tagging uses small radio frequency-activated devices for identification and tracking purposes. Increasingly, RFID tags are being used as an alternative to bar code technology, and the range of opportunities for the technology is exponentially expanding [1]. RFIDs are now small and cheap, so they can be expected to find ever more applications, and numerous descriptions can be located by a web search. The latency of application of RFIDs can be appreciated from the circumstance that practical RFIDs have been used since the 1930s. A brief history, abstracted from Wikipedia [2], is that the Identify Friend or Foe transponder was introduced by the British in 1939 and used by the Allies in World War II to identify airplanes. This application continues for air traffic control. These transponders are powered, but in 1948, Harry Stockman wrote a paper, “Communication by Means of Reflected Power” [3], that introduced passive devices that can use externally transmitted radio waves to power a transponder. This offers the potential of an unlimited service life because there is no battery. Mario Cardullo in 1973 patented a passive radio transponder with memory, the first true ancestor of modern RFIDs, and practical devices were simultaneously demonstrated at the Los Alamos Scientific Laboratory in 1973. Current applications for RFIDs are extensively catalogued in the Wikipedia article [2]. Wal-Mart and the United States Department of Defense require that their vendors place RFID tags on all shipments to improve supply chain management. In time, it is expected that all products will have RFID tags and replace bar codes, although the two systems are currently used together. Numerous transit authorities charge for travel on their systems by RFID identification of users. This application in transport followed the success of the Moscow Metro, the world's busiest underground rail system, when it pioneered RFID smartcards in 1998. Also in 1998, Malaysia introduced e-passports, and from 2006, e-passports are being issued by the United States and the United Kingdom. Our family dog in Australia has an implanted RFID that allows her to be identified if she becomes a lost dog (she has a remarkable knack for removing her conventional registration tag). Cattle in Canada are being tracked from birth to abattoir by RFIDs, particularly important for Canada after the economic impact of a case of bovine spongiform encephalitis in 2003. Inevitably, this raises the prospect of tagging humans by implant, and it has already been done. In 2004, the Mexican Attorney General's office implanted 18 of its staff members with RFIDs to confer access to a secure data room. The prospect of universal human tagging raises numerous civil liberty issues, but the momentum is building for this to take place. Education will be transformed, along with almost every other aspect of social organization, when just being somewhere will activate a responding technology.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".