Real-Time Scaffolding of Students’ Online Data Interpretation During Inquiry with Inq-ITS Using Educational Data Mining
| Autor: | Haiying Li, Rachel Dickler, Raha Moussavi, Michael Sao Pedro, Janice D. Gobert |
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| Rok vydání: | 2018 |
| Předmět: |
Computer science
User modeling 05 social sciences 050301 education Data interpretation Context (language use) 02 engineering and technology Educational data mining Intelligent tutoring system Virtual lab 020204 information systems ComputingMilieux_COMPUTERSANDEDUCATION 0202 electrical engineering electronic engineering information engineering Mathematics education Bayesian Knowledge Tracing 0503 education |
| Zdroj: | Cyber-Physical Laboratories in Engineering and Science Education ISBN: 9783319769349 |
| Popis: | This chapter addresses students’ data interpretation, a key NGSS inquiry practice, with which students have several different types of difficulties. In this work, we unpack the difficulties associated with data interpretation from those associated with warranting claims. We do this within the context of Inq-ITS (Inquiry Intelligent Tutoring System), a lightweight LMS, providing computer-based assessment and tutoring for science inquiry practices/skills. We conducted a systematic analysis of a subset of our data to address whether our scaffolding is supporting students in the acquisition and transfer of these inquiry skills. We also describe an additional study, which used Bayesian Knowledge Tracing (Corbett and Anderson. User Model User-Adapt Interact 4(4):253–278, 1995), a computational approach allowing for the analysis of the fine-grained sub-skills underlying our practices of data interpretation and warranting claims. |
| Databáze: | OpenAIRE |
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