The impact of three instructional modes of computer tutoring on student learning in algebra /
Notice bibliographique
Résumé
This research investigated the impact of "embedded teaching" and "learner-controlled" instruction on student learning of algebra in a controlled computer-tutoring environment. Three versions of a computer tutor were developed to establish three experimental conditions. Condition 1 corresponds to a conventional "lecture-demonstration-practice" in which conceptual knowledge is presented by the computer tutor as a coherent entity prior to engagement in problem-solving activities (Lecture-Demonstration-Practice). Condition 2 reflects "embedded teaching" in which before students begin practice, the computer tutor uses examples to demonstrate problem-solving processes, introducing concepts and principles, as they become relevant (Embedded-Teaching Condition). Condition 3 is a "learner-controlled" instruction in which students engage directly in problem-solving activities without receiving any prior formal instruction, but in which they are provided with instructional assistance and demonstrations upon request (Learner-Controlled Instruction). Twenty-seven high-school students participated in the experiment over a 1-month period. Students were divided into three groups based on their pre-test scores, each group was then assigned randomly to one of the three experimental conditions. The computer tutor was used as the sole source of instruction. Pre- and posttests were administered to measure the changes in students' algebraic abilities. A multivariate analysis of the pre- and posttest results indicates that overall student performance in all three conditions improved significantly over time, as measured by the ability to construct algebraic representations and the ability to made estimates using the various representations ( F (2, 23) = 46.6, p < 0.01). In particular, students in Lecture-Demonstration-Practice Condition demonstrated a higher level of accuracy (89.51%) than students in the Embedded-Teaching and Learner-Controlled Instruction did (61.1% and 63.3% respectively). Moreover, all students in Lecture-Demonstration-Practice Condition completed the posttest successfully, whereas only 56% of students in the other two conditions passed the posttest. This research demonstrates that students learn more effectively from instruction that emphasizes the coherent representations of the symbol system of algebra. It is postulated that such coherent representations enable students to make sense of the subsequent examples to be studied and the problems to be solved thus leading to better problem-solving performance. This research has implications for the development of instructional theories and educational computer applications.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».