Research on the Practice of Digital Innovation Technology Enabling Family Education—Taking the Cultivation of Psychological Literacy of Primary School Students as an Example
Bibliographic record
Abstract
This paper takes the cultivation of psychological literacy of primary school students as an example to explore the practice of digital innovation technology in family education. With the rapid development of science and technology, digital innovation technology has penetrated into various fields, and family education is no exception. By analyzing the characteristics of digital innovation technology and the needs of family education, this paper proposes a method of cultivating the psychological literacy of primary school students based on digital innovation technology. First, this paper introduces the digital innovation technology, the concept of family education and related theories, including the Internet, mobile applications, virtual reality, etc. Then, the advantages of digital innovation technology in family education include convenience, interactivity, and personalization.Taking the psychological literacy cultivation of primary school students as an example, the application method and practical effect of digital innovation technology in family education are elaborated in detail. The practice shows that the method of cultivating students' psychological literacy of primary school students based on digital innovation technology has remarkable effect. On this basis, this study puts forward corresponding measures in the aspects of online emotion diary, virtual reality interactive experience, personalized psychological counseling software, digital storytelling, online game therapy, cloud home-school cooperation platform, emotion recognition training courses, big data-driven growth assessment and so on. In short, this paper proposed a method of cultivating psychological literacy of primary school students based on digital innovation technology, and achieved good results in practice. In the future, with the continuous development and popularization of digital innovation technology, it is believed that its application in family education will be more extensive and in-depth, and provide new opportunities and challenges for the development of family education.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".