Achieving and Underachieving Students' Problem-Solving Performance: Detection of Linguistic Ambiguity, Reflection-Impulsivity, Tolerance-Intolerance of Ambiguity, and Hypothesis Testing
Notice bibliographique
Résumé
ABSTRACT \nThis study is an investigation of problem solving in achieving and underachieving fourth and eighth grade students. Using a regression-referenced procedure, 30 students at each grade level were identified as achievers or underachievers on the basis of their scores on the Canadian Cognitive Abilities Test and the Canadian Test of Basic Skills. A multidimensional approach to problem solving resulted in the assessment of students' ability to deal with problems through the detection of (a) linguistic ambiguity in problems, (b) perceptual ambiguity as measured by the Matching Familiar Figures-20 test, (c) perceptual ambiguity in problem situations by the "How I Feel About Problems" scale, and by (d) hypothesis testing in discrimination learning problems. \nThe data for the four experiments were initially analyzed separately. Results of the experiments on linguistic ambiguity and hypothesis testing revealed that achieving students are better able to deal with linguistic ambiguity in riddles are are better focusers as evidenced by their more efficient use of feedback and a greater percentage of logically correct hypotheses than are underachieving students. Eighth grade students are better problem solvers than fourth grade students as indicated by (a) superior detection of ambiguity in riddles, (b) efficiency as measured by the MFF-20 test, (c) greater tolerance of ambiguity, and (d) better focusing as revealed by their proportion of logically correct hypotheses. \nIntercorrelations among linguistic ambiguity, ambiguity tolerance, reflection-impulsivity, efficiency-inefficiency, hypotheses logically correct, and hypotheses latency resulted in several significant correlations in the direction expected. For achievers, linguistic ambiguity was negatively correlated with ambiguity tolerance and with hypotheses logically correct; ambiguity tolerance was negatively correlated with hypothesis latency. For underachievers, linguistic ambiguity was negatively correlated with ambiguity tolerance and positively correlated with reflection-impulsivity and efficiency; reflection impulsivity was positively correlated with efficiency and negatively correlated with hypotheses logically correct and hypothesis latency. \nDiscriminant analysis permitted examination of the combined data on the four variables for the fourth, eighth, and fourth and eighth grade students combined. For the fourth grade students, linguistic ambiguity and hypotheses logically correct accounted for 13% of the discriminatory power of the discriminant function which differentiated achievers from underachievers. Sixty-five of the students were classified correctly. For the eighth grade students, linguistic ambiguity, reflection-impulsivity, and hypotheses logically correct accounted for 19% of the discriminatory power of the discriminant function which differentiated achievers from underachievers. Sixty-seven percent of the students were correctly classified. For the fourth and eighth grades combined, hypotheses logically correct, linguistic ambiguity, and the ambiguity tolerance accounted for 11% of the discriminatory power of the discriminant function which differentiated achievers from underachievers. Seventy-one percent of students were correctly identified. \nFindings from the present study indicate that problem solving is related to academic achievement. They also suggest that achieving students are using different strategies as indicated by their superior focusing on discrimination learning problems. The anticipated developmental improvement in performance from the fourth to eighth grade was also found.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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.
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