Distance Education Adoption for Literacy and Skills Training of Indigenous Adult Learners
Bibliographic record
Abstract
This applied dissertation is designed to provide an understanding of opinion leaders’ views of their role in the adoption and diffusion of distance education for literacy and skills training of Indigenous adult learners. A top priority for Indigenous leaders is to achieve self-governance with each Indigenous member having access to culturally appropriate education. However, there has been inequity in funding from the government, resulting in Indigenous communities on reserves in Canada being denied the same quality of education offered to individuals living off-reserves. This has resulted in Indigenous members having a lower level of educational attainment in secondary and post-secondary completion compared to other Canadians. Indigenous peoples have lower literacy and numeracy scores than non-Indigenous people in Canada and a lower percent of its working age population are employed when compared to other Canadians. Distance education offers unique opportunities for Indigenous communities to bridge the gap that exists while receiving culturally appropriate education. Sioux-Hudson Literacy Council has been utilizing distance education through their Good Learning Anywhere program to bridge the attainment gap for Indigenous adult learners. This qualitative study explores opinion leaders’ perspectives of their role in the adoption and diffusion of distance education for adult literacy and skills training of Indigenous adult learners. A grounded theory approach was used. Data were collected with an interview protocol, observation protocol, and review of documents. Participants were selected through a purposeful sampling approach by first asking administrators and staff who have experienced the phenomenon over 5 years to participate in the study. Interviews were the main source of data collection. However, to achieve triangulation of information, data were also collected by observation and the review of documents. Opinion leaders viewed supporting the learner as their key role in the adoption and diffusion of distance education for adult literacy and skills training of Indigenous adult learners. Rogers (2003) noted a positive relationship between a leader’s ability to attain adoption and diffusion by clients and the level of the program’s compatibility with the needs of those clients. Themes emerged from the data collected to indicate eight steps utilized by opinion leaders to support the learner in the adoption and diffusion process: (1) know the learner, (2) assign an Online Mentor, (3) develop a learner plan, (4) build relationship and trust, (5) customize course content, (6) participate in online Sharing Circles, (7) build community partnerships, and (8) maintain contact with the learner after program exit.
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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 | 0.000 |
| 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".