How Instructional Sequence and Personalized Support Impact Diagnostic Strategy Learning
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866912498981011456 |
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| author | Güreş, Fatma Betül Nazaretsky, Tanya Radmehr, Bahar Rau, Martina Käser, Tanja |
| author_facet | Güreş, Fatma Betül Nazaretsky, Tanya Radmehr, Bahar Rau, Martina Käser, Tanja |
| contents | Supporting students in developing effective diagnostic reasoning is a key challenge in various educational domains. Novices often struggle with cognitive biases such as premature closure and over-reliance on heuristics. Scenario-based learning (SBL) can address these challenges by offering realistic case experiences and iterative practice, but the optimal sequencing of instruction and problem-solving activities remains unclear. This study examines how personalized support can be incorporated into different instructional sequences and whether providing explicit diagnostic strategy instruction before (I-PS) or after problem-solving (PS-I) improves learning and its transfer. We employ a between-groups design in an online SBL environment called PharmaSim, which simulates real-world client interactions for pharmacy technician apprentices. Results indicate that while both instruction types are beneficial, PS-I leads to significantly higher performance in transfer tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_17760 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | How Instructional Sequence and Personalized Support Impact Diagnostic Strategy Learning Güreş, Fatma Betül Nazaretsky, Tanya Radmehr, Bahar Rau, Martina Käser, Tanja Computers and Society Artificial Intelligence Human-Computer Interaction K.3.1 Supporting students in developing effective diagnostic reasoning is a key challenge in various educational domains. Novices often struggle with cognitive biases such as premature closure and over-reliance on heuristics. Scenario-based learning (SBL) can address these challenges by offering realistic case experiences and iterative practice, but the optimal sequencing of instruction and problem-solving activities remains unclear. This study examines how personalized support can be incorporated into different instructional sequences and whether providing explicit diagnostic strategy instruction before (I-PS) or after problem-solving (PS-I) improves learning and its transfer. We employ a between-groups design in an online SBL environment called PharmaSim, which simulates real-world client interactions for pharmacy technician apprentices. Results indicate that while both instruction types are beneficial, PS-I leads to significantly higher performance in transfer tasks. |
| title | How Instructional Sequence and Personalized Support Impact Diagnostic Strategy Learning |
| topic | Computers and Society Artificial Intelligence Human-Computer Interaction K.3.1 |
| url | https://arxiv.org/abs/2507.17760 |