A TECHNOLOGY-ENHANCED INQUIRY-BASED CHEMISTRY CURRICULUM UNIT (ACIDS & BASES) DESIGNED TO INCREASE HIGH SCHOOL STUDENTS’ INTEREST IN STEM FIELDS AND STEM-RELATED CAREERS
Bibliographic record
Abstract
Although a strong Science, Technology, Engineering, and Mathematics (STEM) education offers a pathway to a brighter future, opening up a wide range of interesting and exciting career opportunities, more than 50% of Canadian students do not complete the Grades 11 and 12 Mathematics and Science courses that allow them access to post-secondary STEM programs, apprenticeships, or entry- level employment positions (Amgen Canada Inc. & Let’s Talk Science, 2013). Therefore, it is vital to develop interest in STEM and enhance engagement in STEM areas at high school for students to build the strong foundation that is necessary to pursue advanced studies in STEM and participate in a future STEM-based workforce (Christensen, Knezek, & Tyler-Wood, 2014). \nThe purpose of this project was to develop a chemistry unit that demonstrates how content, pedagogy, and technology can be integrated to encourage study and careers in STEM. Using Ralph Tyler’s rationale (Tyler, 1949), backward design model (Wiggins & McTighe, 2011), constructivist views of teaching and learning (Kalpana, 2014), and the most advanced technological lab tools; the unit was developed to provide an implementable resource for teachers wanting to use inquiry-based activities in a high-tech environment. Ongoing formative assessment as students learn and for students to learn is emphasized throughout the unit using authentic lab activities that pique students’ interest in chemistry and support the development of a realistic vision of a STEM future that includes themselves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".