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
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».