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Record W3102026986 · doi:10.1111/mbe.12270

<scp>The Relationship between Behavioral Inattention, Meta‐Attention, and Graduate Students' Online Information Seeking</scp>

2020· article· en· W3102026986 on OpenAlexaffabout
Brittany Burek, Rhonda Martinussen

Bibliographic record

VenueMind Brain and Education · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyInformation seekingMeta-analysisGraduate studentsThe InternetIntervention (counseling)Applied psychologyInformation seeking behaviorTask (project management)Domain (mathematical analysis)Medical educationClinical psychologySocial psychologyPedagogyComputer scienceWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

Success in postsecondary education requires proficiency with academic online information seeking. Navigating the internet to find information is a complicated task that is vulnerable to lapses in attention. This study examined the relationships among Canadian graduate students' self‐reported behavioral inattention symptoms, awareness and regulation of attentional focus (meta‐attention), and online academic information seeking abilities. One‐hundred and thirteen (99 female) graduate students (83 master's level, 27 doctoral level) completed an online self‐report questionnaire examining domain‐ and strategic‐experience, behavioral inattention symptoms, meta‐attention, and online information seeking ability. Results indicated that self‐reported inattention symptoms, both components of meta‐attention and domain experience each significantly predicted unique variance in online information seeking ability. Implications for research and intervention are discussed.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.468
GPT teacher head0.473
Teacher spread0.005 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2020
Admission routes2
Has abstractyes

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