Teaching Educational Research to Student Teachers: The Pros and Cons of Using Information and Communication Technology.
Bibliographic record
Abstract
This study was designed to better understand the motivational impact of a compulsory Web-based course, Introduction to Educational Research, on student teachers' enrollment in a four-year teacher education program in a Quebec, Canada university. The hypothesis was that this course, which promoted self-determination, feelings of competence, and affiliation, would have a positive impact on student motivation. Results from quantitative and qualitative data on nine groups of student teachers taking the course indicated that the course had a positive impact on students' motivation to learn. However, the results also suggested that all students may not be ready to handle such autonomy or self-determination, and that the gap between the university classroom and the virtual classroom is substantial and often difficult to bridge. The gap was particularly evident in light of the significant decrease in students' motivation after only 4 weeks of the course. Despite obstacles, the results noted advantages of integrating information and communications technology into teacher education programs (e.g., greater autonomy, more access to information and knowledge, increased motivation to learn, and improved and more frequent communication among educators and learners, among learners themselves, and among educators) . (Contains 43 references.) (SM) Reproductions supplied by EDRS are the best that can be made from the original document. Teaching Educational Research to Student Teachers : The Pros and Cons of Using Information and Communication Technology Thierry Karsenti, Universite de Montreal Gilles Thibert, Universite du Quebec a Montreal DRAFT PLEASE, DO NOT QUOTE ABSTRACT The goal of this research is to better understand the motivational impact of the implementation of a compulsory Web-based course (Introduction to Educational Research) on student-teachers enrolled in a four-year teacher education program (n = 429) in a Quebec (Canada) university. Our starting hypothesis was that this course (Introduction to Educational Research), with its nature promoting self-determination, feelings of competence and affiliation, would have a positive impact on the motivation of the students. The results presented are drawn from both quantitative and qualitative data analysis.The goal of this research is to better understand the motivational impact of the implementation of a compulsory Web-based course (Introduction to Educational Research) on student-teachers enrolled in a four-year teacher education program (n = 429) in a Quebec (Canada) university. Our starting hypothesis was that this course (Introduction to Educational Research), with its nature promoting self-determination, feelings of competence and affiliation, would have a positive impact on the motivation of the students. The results presented are drawn from both quantitative and qualitative data analysis.
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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 | 0.093 | 0.171 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".