Video Production in Elementary Teacher Education as a Critical Digital Literacy Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article reports on a two-year, funded, qualitative inquiry into the challenges and possibilities of integrating video production into pre-service teacher education as a critical digital literacy practice. This includes the skills, knowledge, and dispositions that lead to ability to critique and create digital texts that interrogate the self, the other, and the world (Ávila & Zacher Pandya, 2013). Video making holds out enormous potential given our increasingly diverse classrooms and the growing need to have students connect and collaborate within their own communities and globally (Dwyer, 2016; Ontario Ministry of Education, 2015, 2016; Spires, Paul, Himes, & Yuan, 2018; Watt, 2017, 2018; Watt, Abdulqadir, Siyad, & Hujaleh, 2019). Video is especially significant in light of the fact that it is replacing print text as a dominant mode of communication (Manjou, 2018). Multimodal composing such as video production is, in fact, considered by some to be the essential 21st century literacy (Miller & McVee, 2012), but much remains to be done to bring digital technologies as literacy into the elementary classroom. Qualitative data includes a focus group, questionnaires, observations, and content analysis of teacher candidate videos and instructional plans. This study considers how video production can be integrated into teacher education programs to engage cross-curricular expectations and critical digital literacy perspectives. It responds to the pressing question of how to do teacher education differently in the digital age.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it