Bibliographic record
Abstract
Die vorliegende Arbeit untersucht, ob und wie Medienbildung im Arabischunterricht umgesetzt wird und wie man sie weiterhin fördern kann. Zu Beginn wird zwischen Medienkunde und Medienkompetenz differenziert und die Relevanz beider für den schulischen Fremdsprachenunterricht anhand Vorgaben der Kultusministerkonferenz erörtert. Daraufhin werden Lehrpläne für den schulischen Arabischunterricht aus den USA, Kanada, Australien, Frankreich und Deutschland in Bezug auf die Integration von Medienbildung und die Ausbildung konkreter Medienkompetenzen analysiert. Anschließend werden Beispiele aus der Unterrichtspraxis, vorrangig aus dem amerikanischen universitären Bereich, vorgestellt und verschiedene Sprachlernplattformen hinsichtlich ihrer Eignung für die Verwendung im Arabischunterricht miteinander verglichen. Zuletzt wird eine Unterrichtseinheit für den Arabischunterricht am Gymnasium dargestellt, die die Grundlagen der Medienbildung und Mediennutzung sowie die Zielsetzungen des schulischen Fremdsprachenunterrichts miteinander verbindet. Die vorliegende Arbeit schlussfolgert, dass Medienbildung im Arabischunterricht stärker gefördert werden muss und dass es dazu vor allem einer adäquaten Aus- und Weiterbildung für Lehrkräfte bedarf. Zudem wird festgestellt, dass im Unterricht die Mediennutzung priorisiert wird, ohne der kritischen Reflexion über diese Medien genug Beachtung zu schenken. The study at hand investigates to what extent digital media literacy plays a role in teaching Arabic and how it can be promoted further. It differentiates between the critical evaluation of digital media and their actual usage in the classroom and illustrates the importance of both aspects in language teaching. This is followed by an analysis of existing Arabic curricula from the USA, Canada, Australia, France and Germany with regard to the integration of digital media literacy principles. The study subsequently discusses examples of the application of digital media in Arabic teaching from various, mostly American universities and then continues with a comparison of existing digital learning tools for Arabic and their potential benefits for classroom teaching. Finally, a sample lesson plan is presented to illustrate how the critical evaluation of digital media and their utilization can be meaningfully connected to specific language goals. The study finds that digital media literacy must be developed further in the Arabic classroom and that in order to so, a more adequate training for teachers is needed. Moreover, it becomes clear that while digital media are frequently used in the classroom, their potential benefits and dangers are rarely considered or discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.062 | 0.013 |
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".