Bibliographic record
Abstract
Soufan, Ziad. STEM Buddies EN. Project Hikaya, 2018. Vers. 1.1.2. Google Play Store, https://play.google.com/store/apps/details?id=com.stem_buddies.en This educational application uses a combination of multimedia elements such as video, audio, and text to create an engaging and interactive storytelling experience that teaches children about Science, Technology, Engineering, and Maths (STEM) topics. The app consists of three parts: an animated story, a short quiz, and downloadable colouring pages. Upon opening the app, the user is prompted to watch the animation first, with learning objectives presented for the chosen topic. After the short, subtitled, five-minute video, in which the viewer has the opportunity to pause and rewind, the user is then directed to either the quiz or the colouring pages, which reflect the material presented in the video. This intuitive and logical organization ensures that the informative video is a precursor for the interactive activities and consequently enables learning through reflection and repetition. Through accessible language, the current module, “Water Cycle,” seamlessly integrates an original, engaging story and memorable characters with pedagogical elements that explain how rain forms (evaporation, condensation, precipitation), the importance of water, and the problems associated with the lack of rain. The simple, five-question quiz contains multiple question types and uses audio, text, and pictures to provide children with multiple avenues for identification and learning. Through the quiz, children are required to make intelligent decisions regarding what they have learned. Feedback is given in the form of gamification, with correct answers being positively reinforced by the attainment of gold stars, and completion of the quiz resulting in a personalized certificate of achievement for that module. A myriad of colouring pages, available for use within the app or for individual download, reflect familiar themes and characters and continue to provide some interactivity after the module has been completed. Available in English and Arabic, this new, free application currently only contains one subject module, with more scheduled to be released in the future. With superior graphic design, no ads, and no in-app purchases, the possibility for distractions and unintended purchases are removed. Despite these desirable features, the video and narrative itself could be more interactive on the textual and visual level by incorporating hotspots for touching, swiping, and exploring. I would recommend it for use in public libraries and by teachers in elementary schools for children aged 5 to 9. Recommended: 3 out of 4 stars Reviewer: Raven Germain Raven Germain is a second year MLIS student at the University of Alberta with a love of children’s literature. When not studying, she enjoys travelling, playing piano, and immersing herself in fantasy novels.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.391 | 0.280 |
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".