Evaluation, Temporality, Numerical Skill and Daily Mathematics Operations as Factors That Explain Anxiety toward Mathematics on High School Students: An Empirical Study in Tuxtepec-Oaxaca, Mã©xico
Bibliographic record
Abstract
AbstractThe aim of this research was to measure anxiety toward mathematics on Jr. High School students from Tuxtepec, Oaxaca, Mexico. It was utilized the MuA±oz and Mato (2007) (Note 1) anxiety scale to analyze five dimensions of anxiety, anxiety toward: evaluation, temporality, understanding problems, number operations and math situations of real life. 509 questionnaires were random applied face to face to boys and girls students of all high school's degrees. The statistical procedure utilized was the factorial analysis with principal component extracted. Results obtained allow us to know that variables related to the understanding of mathematical problems and evaluation have the biggest contribution to explain variance of the phenomenon studied.Keywords: evaluation, temporality, numerical skill, mathematics anxiety(ProQuest: ... denotes formulae omitted.)1. Introduction1.1 Statement of ProblemMain indicators of school performance in the European Union were obtained through two types of evaluations, the PISA test (Program for International Student Assessment) and TIMSS test (International Study of Trends in Mathematics and Science). Results of these tests allow us to see the concern because of the lack of progress in many Europeans countries in such important discipline as mathematics, considered a key to achieve countries development, which is evident in the Eurydice network's report (2011) called teaching of mathematics in Europe, common challenges and national policies, because one of the objectives for 2020 is that 15 years old people with an level of competence in reading, math and science must be less than 15%.TIMSS test for European countries focus on four levels and a maximum score of 625 points, with an average score of 519 points. In 2011, this test's result showed that countries like Australia, Italy, Spain and Poland were below average (519 points), in total, 22 of 35 countries were below average. About levels, 19 countries were on level three (54%), 14 countries were on level two, (40%) and only two countries were in the optimal level of one (6%). In the last PISA test's report (2012), countries from European Union were located below the average of the Organization for Economic Cooperation and Development (OECD) with 489 points of 494, but countries like Spain, Portugal and Italy had a score even below.The Latin American countries, Chile and Mexico, members of the OECD, occupied the last places of the PISA test (2012). Mexico in particular got a score of 413 points in mathematics, when the average score is 494. Mexico presented a relapse respect the previous 2009 test when it gained 419 points in mathematics test.In Mexico, there is a basic academic evaluation called ENLACE (National Assessment of Academic Achievement in Schools). 78.1% of the secondary schools that were evaluated in 2013 got an insufficient and elemental level, while only 21.9% were good to excellent. In the state of Oaxaca, good to excellent level was reached only by 4.7% schools. This situation motivates the analysis that could explain why the level of learning in mathematics is so low, especially in some regions of the southeast of Mexico, because there is evidence that it is a global problem but the situation is more serious in some regions of the third world. In addition, some variables have showed that the cause of the problem is not only cognitive, but there is an important implication about emotional anxiety toward mathematics.The EURYDICE network's report (2011) try to explain the phenomenon of low performance in tests, highlighting the concept and distinguishing intrinsic motivation of extrinsic motivation (Deci & Ryan, 1985). Intrinsic motivation leads to self-efficacy, which predicts the ability to succeed (Bandura, 1986), and in the area of math, self-efficacy is a predictor of academic performance (Mousoulides & Phillippou, 2005; Pintrich, 1999), in this way, motivation is related with student's self-esteem, their stress and anxiety, among other concepts (Lord et al. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".