Evidence map›Paper›PMID 35893269›Full record

ArticleJournal of Intelligence2022

Examining Humans' Problem-Solving Styles in Technology-Rich Environments Using Log File Data.

Yizhu Gao, Xiaoming Zhai, Okan Bulut, Ying Cui, Xiaojian Sun

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of Intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yizhu GaoDepartment of Educational Psychology, University of Alberta, Edmonton, AB T6G 2G5, Canada.ORCID 0000-0002-7791-3700
Xiaoming ZhaiDepartment of Mathematics, Science, and Social Studies Education, University of Georgia, Athens, GA 30602, USA.ORCID 0000-0003-4519-1931
Okan BulutDepartment of Educational Psychology, University of Alberta, Edmonton, AB T6G 2G5, Canada.ORCID 0000-0001-5853-1267
Ying CuiDepartment of Educational Psychology, University of Alberta, Edmonton, AB T6G 2G5, Canada.
Xiaojian SunSchool of Mathematics and Statistics, Southwest University, Chongqing 400715, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated how one's problem-solving style impacts his/her problem-solving performance in technology-rich environments. Drawing upon experiential learning theory, we extracted two behavioral indicators (i.e., planning duration for problem solving and human-computer interaction frequency) to model problem-solving styles in technology-rich environments. We employed an existing data set in which 7516 participants responded to 14 technology-based tasks of the Programme for the International Assessment of Adult Competencies (PIAAC) 2012. Clustering analyses revealed three problem-solving styles:

Indexed as

experiential learning theoryexplanatory item response modelingk-means clusteringlog file dataproblem-solving style technology-rich environments

Identifiers

PMID35893269
PMCPMC9326689

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.