The impact of three instructional modes of computer tutoring on student learning in algebra /
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".