Abstract
This paper presents the Pharmacology Inter-Leaved Learning-Cells (PILL-Cells) environment. This is a suite of multi-scale agent-based computer models that enable nursing students to investigate the biochemical processes of diabetes and its related medications. These range from the molecular to the cellular to the interactions between organs within a sick or healthy cell-organ. The participants were nursing students who learned about the pharmacology related to diabetes either with computer models (experimental group; n = 94) or via a lecture-based curriculum (comparison group; n = 54). The results revealed significantly higher conceptual learning gains following learning with the PILL-Cells environment compared to studying via the lecture-based curriculum (U=940, p<0.001). It was found that the highest conceptual learning gains were for the medication treatment subscale and the highest complex systems learning gains were at the micro-level. These results suggest that learning with the PILL-Cells is highly effective and enhances a micro-level molecular view of the biochemical phenomena, and that this understanding is then related to macro-level phenomena such as medication actions. Additionally, the scores of the course final exam were higher in the experimental group (unpaired t=–2.9, p < 0.05), which suggest that the environment continues to provide a more general reasoning scheme for biochemical processes, and thus enhances the pharmacology curriculum. (מתוך המאמר)
Translated title of the contribution | בעקבות מולקולת הסוכר: ללמוד פרמקולוגיה באמצעות חקירת מודלים ממוחשבים מבוססי סוכנים המדמים תהליכים ביוכימיים ברמת התא וברמת האיבר |
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Original language | English |
Title of host publication | האדם הלומד בעידן הטכנולוגי: כנס צ'ייס למחקרי טכנולוגיות למידה (קובץ) |
Publisher | האוניברסיטה הפתוחה ושה"ם |
Pages | 12 (2017), 21E-30E |
Number of pages | 19 |
State | Published - 2017 |
Bibliographical note
למאמר מצורף נספח הכולל שלוש שאלות לדוגמא הלקוחות מהשאלון שבו נעשה שימוש במסגרת המחקר.IHP Publications
- ihp
- Diabetes
- Medicine -- Data processing
- Nurses -- Training of
- Pharmacy