PICA: A Data-driven Synthesis of Peer Instruction and Continuous Assessment
Fuente:
arXiv
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866911966417649664 |
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| author | Geinitz, Steve |
| author_facet | Geinitz, Steve |
| contents | Peer Instruction (PI) and Continuous Assessment(CA) are two distinct educational techniques with extensive research demonstrating their effectiveness. The work herein combines PI and CA in a deliberate and novel manner to pair students together for a PI session in which they collaborate on a CA task. The data used to inform the pairing method is restricted to the most previous CA task students completed independently. The motivation for this data-driven collaborative learning is to improve student learning, communication, and engagement. Quantitative results from an investigation of the method show improved assessment scores on the PI CA tasks, although evidence of a positive effect on subsequent individual CA tasks was not statistically significant as anticipated. However, student perceptions were positive, engagement was high, and students interacted with a broader set of peers than is typical. These qualitative observations, together with extant research on the general benefits of improving student engagement and communication (e.g. improved sense of belonging, increased social capital, etc.), render the method worthy for further research into building and evaluating small student learning communities using student assessment data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_17633 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PICA: A Data-driven Synthesis of Peer Instruction and Continuous Assessment Geinitz, Steve Computers and Society Peer Instruction (PI) and Continuous Assessment(CA) are two distinct educational techniques with extensive research demonstrating their effectiveness. The work herein combines PI and CA in a deliberate and novel manner to pair students together for a PI session in which they collaborate on a CA task. The data used to inform the pairing method is restricted to the most previous CA task students completed independently. The motivation for this data-driven collaborative learning is to improve student learning, communication, and engagement. Quantitative results from an investigation of the method show improved assessment scores on the PI CA tasks, although evidence of a positive effect on subsequent individual CA tasks was not statistically significant as anticipated. However, student perceptions were positive, engagement was high, and students interacted with a broader set of peers than is typical. These qualitative observations, together with extant research on the general benefits of improving student engagement and communication (e.g. improved sense of belonging, increased social capital, etc.), render the method worthy for further research into building and evaluating small student learning communities using student assessment data. |
| title | PICA: A Data-driven Synthesis of Peer Instruction and Continuous Assessment |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2407.17633 |