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| Main Author: | |
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| Format: | Recurso educativo Open Access |
| Language: | en |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://eric.ed.gov/?id=EJ1388687 |
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| _version_ | 1867181687525343232 |
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| author | Leung, Javier |
| author_facet | Leung, Javier Leung, Javier |
| collection | Education Resources Information Center |
| contents | Mapping Self-Regulated Learning Events and Actions in Online Teacher Professional Development with Process Mining Techniques Leung, Javier Self Management Learning Strategies Electronic Learning Faculty Development Data Collection Data Analysis Visual Aids Algorithms Programming Languages COVID-19 Pandemics Profiles Learning Analytics Use Studies This study aimed to visualize self-regulated learning (SRL) behaviors performed by users from an online teacher professional development platform called the EdHub Library using the pm4py algorithm in Python to parse event data during the first 30 days of the school year and the first 90 days of the COVID-19 pandemic in March 2020. Process mining techniques were implemented to visualize the user profiles of frequent users in case-based decompositions and identify critical SRL events and actions of all users in activity-based decompositions for three school years (2018, 2019, and 2020). SRL events and actions were measured for all pageviews. |
| format | Recurso educativo Open Access |
| id | eric_EJ1388687 |
| institution | ERIC Institute of Education Sciences |
| language | en |
| publishDate | 2022 |
| record_format | eric |
| spellingShingle | Mapping Self-Regulated Learning Events and Actions in Online Teacher Professional Development with Process Mining Techniques Leung, Javier Self Management Learning Strategies Electronic Learning Faculty Development Data Collection Data Analysis Visual Aids Algorithms Programming Languages COVID-19 Pandemics Profiles Learning Analytics Use Studies Mapping Self-Regulated Learning Events and Actions in Online Teacher Professional Development with Process Mining Techniques Leung, Javier Self Management Learning Strategies Electronic Learning Faculty Development Data Collection Data Analysis Visual Aids Algorithms Programming Languages COVID-19 Pandemics Profiles Learning Analytics Use Studies This study aimed to visualize self-regulated learning (SRL) behaviors performed by users from an online teacher professional development platform called the EdHub Library using the pm4py algorithm in Python to parse event data during the first 30 days of the school year and the first 90 days of the COVID-19 pandemic in March 2020. Process mining techniques were implemented to visualize the user profiles of frequent users in case-based decompositions and identify critical SRL events and actions of all users in activity-based decompositions for three school years (2018, 2019, and 2020). SRL events and actions were measured for all pageviews. |
| title | Mapping Self-Regulated Learning Events and Actions in Online Teacher Professional Development with Process Mining Techniques |
| topic | Self Management Learning Strategies Electronic Learning Faculty Development Data Collection Data Analysis Visual Aids Algorithms Programming Languages COVID-19 Pandemics Profiles Learning Analytics Use Studies |
| url | https://eric.ed.gov/?id=EJ1388687 |