Using Concept Mapping to Aid African American Students' Understanding in Middle Grade Science
Notice bibliographique
Résumé
This article reports on the results of a nine-week investigation that examined the effectiveness of concept mapping on science achievement of 182 African American middle grade science students, distributed into eight intact earth science classes (by ability levels). Ability level was examined as a covariate on student achievement. For this sample of students, analyses of covariance indicated no significant overall effects of treatment on science achievement. A statistically significant effect was found between concept mapping and student achievement among the average students measured by combined performance assessment items. The results suggest that concept mapping has a positive effect on average (lower) ability level African American science students. Several years ago, science educators recommended major reforms regarding the teaching of science in the nation's public schools (National Research Council, 1996). Science educators issued this request for reform because a growing number of students were graduating from public schools without demonstrating competent scientific literacy enabling them to function in a technological and scientific community. Since the reform measures were initiated, data reported by the National Assessment of Educational Progress (NAEP, 2001) indicated that students in fourth and eighth grades performed better in 2000 than previous years, and overall, American students showed academic improvement in science compared to students in Canada and several European and Asian countries. Although gains were indicated overall, eighth-grade science students did not perform as well as fourth-grade science students. In spite of overall gains, African American eighth-grade science students still lag behind other eighth graders in achieving an adequate level of scientific literacy. This assertion is based on several factors. First, as noted in the NAEP report (2001), African American students lag far behind White and Asian students enrolled in the sciences. Second, these data indicate that fewer African American students take advance science courses in high school. Third, African American students are underrepresented in science majors at the college level (Fouad, 1995; Gates, 2001). Fourth, for most African American students, the only courses available are science classes designed to award credit without expectations to learn (DeBacker & Nelson, 2000; Fouad, 1995; Gates, 2001). This lack of achievement by African American middle school science students is further addressed in The Center for Research on Education Diversity and Excellence (CREDE, 2002) investigation involving middle school students to determine what and how students learn about scientific ideas. This investigation reports that classroom practices designed to engage diverse students (African American and Hispanic) in exploring the potential meaning and functions of their own ideas about scientific phenomena resulted in higher levels of participation and a deeper understanding of scientific phenomena. These ideas from CREDE suggest teaching science via scientific inquiry, which is at the heart of the National Science Education Standards (American Association for the Advancement in Science, 1995; Odom & Kelly, 1998), is a more effective methodology for these students. Since an important part of scientific inquiry involves students communicating an understanding of the evidence collected and an explanation about the evidence, students need to understand the relationships between explanation and evidence derived from investigations (Ruiz-Primo & Shavelson, 1996). Odom and Kelly (1998) stated that concept mapping, an inquiry-oriented and student-centered tool, may be an effective tool to enable African American students to learn science via scientific inquiry. A concept map is a diagram indicating a student's understanding of the interrelationship among concepts. Concepts are arranged in a hierarchy (from general to specific), connected with a label line. …
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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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| 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 ».