TEACHING SCIENCE THROUGH ONLINE EDUCATION DURING THE COVID-19 PANDEMIC: SCIENCE TEACHERS’ PRACTICES, SELF-EFFICACY BELIEFS, AND ATTITUDES TOWARD THE CHANGE
Bibliographic record
Abstract
The COVID-19 pandemic has had a remarkable impact on school (K-12) education worldwide. Institutions and teacher educators had to quickly respond to an unexpected and obligatory transition from face-to-face to remote teaching. During this teaching transition science teachers faced various challenges, particularly to inquiry-based activities as well as laboratory experiments employing online tools. Better understanding of the COVID-19 teaching situation of science teachers can aid teachers and various stakeholders concerned with providing quality science teaching and learning. Hence, this study explored science teachers’ practices through the description of their experiences in the current context of COVID-19. Since teachers’ perception of self-efficacy and attitudes affect teachers’ pedagogical beliefs and teaching practices, this study also investigated teachers’ perceptions of self-efficacy concerning teaching online remotely and teachers’ attitudes toward the change of teaching transitions resulting from the COVID-19 pandemic. The instrument used to measure the three scales (teaching practices, self-efficacy, and attitudes toward the change) was a 39-item, web-based survey that was given to in-service Saskatchewan science teachers within seven Saskatchewan district school boards. The option for open-ended survey comments were kept ascertaining if teachers had any comments, or concerns in addition to the survey responses. Descriptive statistics, and inferential statistical tests were used to explore the differences of teaching practices, self-efficacy, and attitudes toward the change according to teachers’ demographic characteristics. The study results indicated that teachers had to spend additional time in planning lessons, designing inquiry-based activities, and preparing assignments for online teaching during COVID-19 emergency remote teaching. Teachers had a low perception of self-efficacy for maintaining engagement with families and strengthening trust-based communication through online tools. Also, science teachers perceived that they had a moderate level of self-efficacy to perform the tasks related to their teaching practices during COVID-19 pandemic. Moreover, teachers reported less favorable attitudes toward the change that occurred during COVID-19 teaching. The study results are intended to be useful to the school divisions for planning and implementing adequate professional development training to enhance teachers’ skills and knowledge for teaching science in online remote context.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".