Characterizing Collaboration in the Pair Program Tracing and Debugging Eye-Tracking Experiment: A Preliminary Analysis
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| Title: | Characterizing Collaboration in the Pair Program Tracing and Debugging Eye-Tracking Experiment: A Preliminary Analysis |
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| Language: | English |
| Authors: | Villamor, Maureen M., Rodrigo, Mercedes T. |
| Source: | International Educational Data Mining Society. 2017. |
| Availability: | International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org |
| Peer Reviewed: | Y |
| Page Count: | 6 |
| Publication Date: | 2017 |
| Document Type: | Speeches/Meeting Papers Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Programming, Eye Movements, Prior Learning, Computer Assisted Instruction, Educational Technology, Foreign Countries, College Students, Cooperative Learning |
| Geographic Terms: | Philippines |
| Abstract: | This paper characterized the extent of collaboration of pairs of novice programmers as they traced and debugged fragments of code using cross-recurrence quantification analysis (CRQA). This was a preliminary analysis that specifically aimed to compare and assess the collaboration of pairs consisting of two individuals who may have different or same level of prior knowledge given a task. We performed a CRQA to build cross-recurrence plots using eye tracking data and computed for the CRQA metrics, such as recurrence rate (RR), determinism (DET), average diagonal length (L), longest diagonal length (LMAX), entropy (ENTR), and laminarity (LAM) using the CRP toolbox for MATLAB. Results showed that low prior knowledge pairs (BL) collaborated better compared to high prior knowledge pairs (BH) and mixed prior knowledge (M) pairs because of its high RR and DET implying that they had more recurrent fixations and matching scanpaths. However, the BL pairs' high ENTR and LAM could mean that they seemed to have more difficulty in understanding and debugging the programs. All pairs regardless of category had more or less exerted the same level of attunement when asked to debug the programs as evident in their L values. The mixed pairs seemed to have struggled with eye coordination the most as it had the most incidences of low LMAX. [For the full proceedings, see ED596512.] |
| Abstractor: | As Provided |
| Entry Date: | 2019 |
| Accession Number: | ED596586 |
| Database: | ERIC |
| Abstract: | This paper characterized the extent of collaboration of pairs of novice programmers as they traced and debugged fragments of code using cross-recurrence quantification analysis (CRQA). This was a preliminary analysis that specifically aimed to compare and assess the collaboration of pairs consisting of two individuals who may have different or same level of prior knowledge given a task. We performed a CRQA to build cross-recurrence plots using eye tracking data and computed for the CRQA metrics, such as recurrence rate (RR), determinism (DET), average diagonal length (L), longest diagonal length (LMAX), entropy (ENTR), and laminarity (LAM) using the CRP toolbox for MATLAB. Results showed that low prior knowledge pairs (BL) collaborated better compared to high prior knowledge pairs (BH) and mixed prior knowledge (M) pairs because of its high RR and DET implying that they had more recurrent fixations and matching scanpaths. However, the BL pairs' high ENTR and LAM could mean that they seemed to have more difficulty in understanding and debugging the programs. All pairs regardless of category had more or less exerted the same level of attunement when asked to debug the programs as evident in their L values. The mixed pairs seemed to have struggled with eye coordination the most as it had the most incidences of low LMAX. [For the full proceedings, see ED596512.] |
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