Training Curriculum Development for Enhancing Teacher’s Digital Literacy Ability for Classroom Management of at Nanchang Vocational University, China
Bibliographic record
Abstract
The main objective of this study is to develop a training curriculum that integrates the basic components of digital literacy and the 70-20-10 learning model to enhance the digital literacy abilities of teachers at Nanchang Vocational University. The curriculum mainly includes the following two research questions: (1) What is the current status, desirable, and needs assessment of teachers at Nanchang Vocational University in utilizing Teacher's digital literacy? (2) How to design and develop training curriculums aimed at improving the ability of teachers at Nanchang Vocational University to use digital technology for classroom management? This study used Using literature research methods, analyze the composition of teachers' digital literacy, as well as the main components of curriculum development. And used targeted questionnaires and interview outlines to survey 316 teachers and interview 8 experts at Nanchang Vocational University to analysis the level of ability and urgent needs, as well as the learning methods of training curriculums. The results of the study revealed that: 1. The following four abilities urgently need to be improved 1) Digital application 2) Digital Technology Knowledge and Skills 3) Digital awareness 4) Professional development. 2. The four elements of curriculum development: objectives, content, learning methods, and evaluation. 3. The learning method we use for training curriculum development is 70-20-10. 4. Developed a 120 hours training curriculum.
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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 | 0.001 |
| 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".