MétaCan
Menu
Back to cohort
Record W7133063054

Digitally Mediated Support for Lifelong Culture and Language Learning

2022· dissertation· W7133063054 on OpenAlexaboutno aff
Amna Liaqat

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsLifelong learningImmigrationInformal learningAdult educationLanguage acquisitionDigital learningEducational technologyExperiential learningDigital nativeInformal education
DOInot available

Abstract

fetched live from OpenAlex

Learning to thrive in a new culture is a cognitively and emotionally demanding task that requires a lifetime of exploration, goal setting, and intentional effort. Lifelong learning is the reality for millions of immigrants in Canada, young and old, who leave behind the familiar to pursue social, economic, and education opportunities in unpaved landscapes. Learning independently in non-learning settings, such as the home, is particularly challenging because learning moments are sporadic, unstructured, and tacit. As a result, immigrants are at heightened risk of experiencing adverse consequences when they do not meet their learning goals, such as missing out on employment opportunities or facing relationship stress. The ill-defined pathways for supporting lifelong learning for immigrants creates barriers to full participation in their new society. In the absence of structural support, alternate possibilities for fostering the informal learning process must be identified. Toward this goal, I investigated two lifelong learning contexts and created tools that serve three generations of immigrants. In my first project I uncovered the dynamics of immigrant grandparent-grandchild storytelling practices, and I designed and evaluated a digital crafting tool that prompts two-way language and culture learning. In my second project I built and deployed a peer-feedback platform for adult immigrants learning to write in English. In my dissertation I integrate these two projects to answer three research questions. First, I have mapped the unique multifaceted learning landscapes faced by immigrants regarding (1) language and culture, (2) age, (3) attitudes, and (4) external structures. Second, I evaluated digital interventions informed by my mapping and showed how manipulating (1) flexibility and structure, and (2) shared spaces can springboard learning moments into meaningful engagement. Third, I reflect on the participatory approaches I adapted to better serve marginalized users. I advance knowledge in Human-Computer Interaction by validating design mechanisms that enrich social learning experiences, and the learning sciences by demonstrating how the interplay of internal psychosocial constructs and external sociocultural context influence the learning process for immigrant populations. Broadly, I contribute a body of interdisciplinary evidence for designing digital tools to capitalize on learning moments that arise from daily routine.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.501
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.329
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicICT in Developing CommunitiesFrench-language works237,207