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This study examined Chinese EFL researchers' English abstract writing in language education. Using open-ended questionnaires, it first investigated 24 Chinese EFL researchers' perceptions of their challenges in writing English abstracts. Using generalizability theory and follow-up interviews, it then invited 16 experienced English journal reviewers to assess 27 published English abstracts written by Chinese EFL researchers to identify common errors and suggest improvement tips. Finally, it examined eight selected Chinese EFL researchers' critical reflections on the English journal reviewers' assessment of the 27 English abstracts. The results indicated that Chinese EFL researchers experienced several challenges in writing English abstracts. Further, the English reviewers' assessment of the 27 abstracts was consistent and reliable. The common errors were associated with the accuracy, non-evaluative nature, coherence and readability, and conciseness of an English abstract. The English reviewers provided tips for improvement, and Chinese EFL researchers expressed their critical reflections on their assessment. Educational implications are discussed. [ABSTRACT FROM AUTHOR]

This study implemented a data-driven approach to identify Chinese high school students' common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students' error-related behaviors were also analyzed, and their relationships to success in introductory programming were investigated. This study identified 15 common compilation errors and 6 common test errors. The results showed that these common errors accounted for a large proportion of all errors, so identifying the common errors is important to help students succeed in introductory programming courses. Based on these common errors, five underlying student difficulties were identified and are discussed. In addition, after analyzing existing measures of students' error-related behaviors, we developed a measure called improvement rate to quantify students' success in fixing errors. The results of our study suggest that students' competence of improving code is important to their success in introductory programming. We recommend researchers design and develop automated assessment tools that provide feedback messages for common student errors and instructors who explicitly teach knowledge and skills of improving code in class. [ABSTRACT FROM AUTHOR]