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Record W6945073331 · doi:10.20381/ruor-30729

Math Anxiety and Achievement: Investigating Parent-Child Relationships in the Homework-Helping Context

2024· dissertation· en· W6945073331 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2024
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsnot available
Fundersnot available
KeywordsMathematical anxietyAnxietyContext (archaeology)PerceptionPerspective (graphical)Observational studyQuality (philosophy)Dynamics (music)

Abstract

fetched live from OpenAlex

This dissertation investigated the multifaceted dynamics of parent-child interactions during math homework help and their influence on children's achievement and anxiety towards math. Across three studies - using Social Learning Theory, Social Referencing Theory, and Attachment Theory as theoretical frameworks - the way in which both child and parent math anxiety relate to interactions during math homework-help, emotional experiences, math achievement, and the quality of parent-child attachment was explored. Study 1 was conducted over two separate studies to explore the connection between parents' math anxiety and their perceptions of math homework-helping interactions. Surveys conducted with parents of children in grades 1 to 6 across North America (Study 1a [n = 192]: controlling for math knowledge; Study 1b [n = 214]: controlling for math knowledge and general anxiety) revealed that higher math anxiety was associated with an altogether more negative homework-helping experience from the parent's perspective (i.e., diminished confidence, increased conflict, stress, frustration, and emotional distance during math homework interactions). Building upon these results, Study 2 used a multi-method approach to assess the quality of math homework-helping interactions, including observational coding methods. The study involved 40 Canadian parents and their children (ages 10-12 years; grades 5 to 7) engaging in a simulated math homework task. Results indicated that higher quality interactions correlate with task accuracy, and the variability in the quality of the interaction is linked to parents' and children's math achievement, as well as children's math anxiety. The linguistic analysis revealed a positive correlation between parents' and children's use of negative words during the interaction. Additionally, the variability in the frequency of positive words used by parents was associated with parents' math achievement and accuracy on the math task. Using the same sample as Study 2, Study 3 extended beyond the homework-helping context by investigating the relation between parent-child attachment, math homework-helping interactions, math achievement, and math anxiety. Attachment security and the quality of the simulated math task interaction were found to be marginally correlated, while attachment insecurity was found to be associated with lower quality interactions during the simulated math task, as well as increased math anxiety in children. Taken together, these studies provide valuable insights into the influence of parent-child interactions on children's mathematical well-being, substantiated by both self-reported data and observational methods. The findings from this dissertation underscore the importance of adopting a more holistic approach that integrates the quality of parent-child relationships with individual cognitive and emotional factors. This approach is essential for gaining a deeper understanding of children's experiences with mathematics.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.191
Teacher spread0.169 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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