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Record W4399668124 · doi:10.1145/3628516.3655814

A Systematic Review of the Probes Method in Research with Children and Families

2024· review· en· W4399668124 on OpenAlex
Seray Ibrahim, Alissa N. Antle, Julie A. Kientz, Graham Pullin, Petr Slovák

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typereview
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
FundersUK Research and Innovation
KeywordsComputer scienceData science

Abstract

fetched live from OpenAlex

Since their introduction, there has been wide discussion about how probes are used in human computer interaction (HCI) research. This variation can be problematic for researchers and designers who plan on using probes in the child computer interaction space, as it can be difficult to know which approach is best suited to address their design situation. In this review, we surveyed the ways that HCI researchers have used probes in studies with children and families. Based on 25 articles, we analysed the methodological decisions that researchers have taken in their empirical studies, relating to: a.) the goals for using the probes, b.) the probe itself, c.) participant involvement, and d.) the data and data use. Based on our methodological findings, we highlight four key tensions—including probes as sources of information versus creative input–and consider questions that can guide decision making for developing probes studies with children and families.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.099
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.136
GPT teacher head0.473
Teacher spread0.337 · 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

Quick stats

Citations15
Published2024
Admission routes1
Has abstractyes

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