Bibliographic record
Abstract
IntroductionEven the best school library will become deserted if students are not introduced systematically to its usage and the resulting opportunities to improve and strengthen their reading competency. It is the school librarian's responsibility to support students' development towards becoming proficient researchers, to provide targeted assignments to facilitate the discovery of information, and to kindle or expand their enjoyment of the library at the same time (Suhl-Strohmenger, 2012, p. 151).School librarians work at the intersection of administration and services, technical support, and teaching. I worked as the director of a multimedia library at a vocational college (Berufskolleg) in North Rhine-Westphalia for 12 years. I considered it my responsibility to contribute to and expand our students' information literacy, starting with introducing all incoming students to the services and to the staff of the school library. I believe that this is the foundation on which everything else is built. It was a great feat of strength, given that there were up to 1000 students each year and I was the only full-time employee.I constantly tried to optimize this task in terms of organization and didactic approach. I learned early on that as a librarian, I quickly gained professional authority in the eyes of our young adult target groups when they realized that I was able to use new media confidently and was not just an old-timey bookworm. It was therefore an obvious idea to increase the integration of mobile devices into learning activities, and to turn this into a project for my coursework on didactics (Educational Media) at the Learning Lab of the University of Duisburg-Essen.In addition, in early 2015 I received an inquiry from the Media Advisory Center North Rhine-Westphalia (Medienberatung Nordrhein-Westfalen), which was looking for pilot projects for an app for educational scavenger hunts that was in development. In return, they offered guidance for the development of the scavenger hunt. This seemed ideal for my purposes. I also hoped to gain additional insights on BYOD (Bring Your Own Device) teaching models for myself and for the school. For these reasons, I decided to use the app BIPARCOURS (or rather its predecessor, Actionbound, as BIPARCOURS had not yet been published) in order to implement a mobile-device supported introduction to library use for incoming students.Aspects of designing a mobile-device supported educational programPrior to implementing this type of educational program, thoughtful planning and a thorough analysis of existing resources and goals are indispensable. At a minimum, they should include the following aspects, which will be discussed below:1. Program objectives2. Target groups3. Market analysis4. Existing resources5. Learning/teaching objectives6. Effects of device-supported learning7. Organization and timetable8. Potential analysis1.Educational goals and objectivesPossible goals of the use of digital in educational programs include: image enhancement; reduced workload; conservation of resources; feedback, etc. The specific objectives for the scavenger hunt app at our vocational college are discussed below.The main educational goal was the introduction of around 40 incoming classes per year to the school center. These introductory sessions need to happen during the first few weeks of the school year, so that individual students, classes and small groups, can subsequently use the library.The main goal of the introductory session is to convey to the students that the school library - and libraries in general - is a pleasant and helpful place, to introduce them to the staff, and to lower psychological barriers around libraries as an institution. Basic rules of usage and why they exist are also introduced in a focused manner, so that they do not need to be explained to individual students and discussed repeatedly. …
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.107 | 0.067 |
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".