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Content Provider | ACM Digital Library |
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Author | Huang, Po-Kai Murphy, Hannah Hsiao, I-Han |
Abstract | In this paper, we study students' learning effectiveness through their use of a homegrown educational technology, Web Programming Grading Assistant (WPGA), which facilitates grading and feedback delivery of paper-based assessments. We designed a classroom study and collected data from a lower-division blended-instruction computer science class. We tracked and modeled students' reviewing and reflecting behaviors from WPGA. The results show that students demonstrated an effort and desire to review assessments regardless of if they were graded for academic performance or for attendance. Hardworking students achieved higher exam scores on average and were found to review their exams and the correct questions frequently. Additionally, student cohorts exhibited similar initial reviewing patterns, but different in-depth reviewing and reflecting strategies. Ultimately, this work contributes to the aggregation of multidimensional learning analytics across the physical and cybersphere. |
Starting Page | 319 |
Ending Page | 328 |
Page Count | 10 |
File Format | |
ISBN | 9781450348706 |
DOI | 10.1145/3027385.3027415 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2017-03-13 |
Publisher Place | New York |
Access Restriction | Subscribed |
Subject Keyword | Blended instruction classes Orchestration technology Cross lak Feedback Computing education Programming learning Reflection |
Content Type | Text |
Resource Type | Article |
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