“Systems Thinking (ST) Encourages a Safe Space to Offer Different Perspectives and Insights”: Student Perspectives and Experiences with ST Activities
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Researchers and educators have been exploring systems thinking (ST) in chemistry education to better equip citizens for 21st century challenges; however, little is known about students’ perspectives and experiences. In this study, we investigated students’ perspectives of ST and their experiences with ST activities. We designed and implemented a ST intervention, performed individually and collaboratively, as well as follow up interviews. Twenty-four university undergraduate and graduate students participated in this study and reported a variety of experiences and perspectives. For students’ experiences, we found that (1) while collaborating, participants recognized and appreciated different perspectives, (2) participants included chemistry concepts and connections in their system maps despite having difficulties, (3) system maps emphasized problems/solutions and causes/effects and differed in terms of organization and intended purpose, and (4) limitations to system map construction included time, knowledge, and technology skills. Students also expressed positive perspectives of a ST approach based on their experience engaging with the ST intervention and believed a ST approach (1) is beneficial to learning, (2) captures interest and engagement, (3) allows perspectives to be shared and gained, and (4) provides personal, social, and professional relevance. Based on these findings, we suggest aspects to consider when planning and implementing ST activities and identify future research required to better understand the impacts of ST in chemistry education.
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 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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".