Attentional Literacy as a New Literacy: Helping Students Deal with Digital Disarray
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
When students learn online, they do so within a wider context of digital disarray, marked by distraction, disorder and disconnection, which research shows to be far from conducive to effective learning. Specific educational issues include a lack of focus, linked to information overload in an environment characterized by misinformation and disinformation, as well as a lack of connection to the self and others. Arguing that today’s growing focus on digital literacies in education already serves as a partial response to digital disarray, this evidence-based position paper proposes the concept of attentional literacy as a macroliteracy which interweaves elements of now established literacies with the emerging educational discourse of mindfulness. Through attentional literacy, students may gain awareness of how to focus their attention intentionally on the self, the relationship with others, and the informational environment, resulting in a more considered approach to learning coupled with an appreciation of multiple shifting perspectives. Armed with this developing skillset, students stand to benefit more fully from digital educational experiences. Considerations for continuing research in this area include the need to adopt a critical stance on mindfulness, and the need to operationalize attentional literacy for the classroom.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it