<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pingping Zhao</style></author><author><style face="normal" font="default" size="100%">Zhi Liu</style></author><author><style face="normal" font="default" size="100%">Hao Zhou</style></author><author><style face="normal" font="default" size="100%">Yueyang Shao</style></author><author><style face="normal" font="default" size="100%">Jian Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PREDICTIVE EFFECT OF PROJECT-BASED LEARNING QUALITY ON SCIENTIFIC PROBLEM-SOLVING ABILITY</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Baltic Science Education</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">hierarchical linear modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">Project-based learning</style></keyword><keyword><style  face="normal" font="default" size="100%">scientific problem-solving ability</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2026</style></year><pub-dates><date><style  face="normal" font="default" size="100%">February/2026</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.indexcopernicus.com/search/article?articleId=4765179</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">continuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Many studies have examined the relationship between project-based learning (PBL) and scientific problem-solving ability, but few have addressed the issue of the quality of PBL (QPBL). This study analyzed two-wave data collected from 4,568 seventh-grade Chinese students. Pretest and posttest of scientific problem-solving ability were conducted through computer-based assessment featuring interactive tasks, and the students’ QPBL scores were collected through a questionnaire. Hierarchical linear modeling (HLM) indicated that QPBL positively predicted students’ scientific problem-solving ability. Specifically, “authenticity” positively predicted all three subcomponents of scientific problem-solving ability (design of scientific inquiry, scientific reasoning, and scientific explanation); “autonomy in research questions” negatively predicted all three subcomponents; and “group collaboration” and “project demonstration” positively predicted some of the subcomponents. These findings enrich the literature on the predictive effects of QPBL on scientific problem-solving ability in specific educational and cultural contexts and have practical implications for teachers seeking to apply PBL more effectively to enhance students’ scientific problem-solving ability.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">190-206</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pingping Zhao</style></author><author><style face="normal" font="default" size="100%">Chang, C. Y.</style></author><author><style face="normal" font="default" size="100%">Yueyang Shao</style></author><author><style face="normal" font="default" size="100%">Zhi Liu</style></author><author><style face="normal" font="default" size="100%">Hao Zhou</style></author><author><style face="normal" font="default" size="100%">Jian Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">UTILIZATION OF PROCESS DATA IN CHINA: EXPLORING STUDENTS’ PROBLEM-SOLVING STRATEGIES IN COMPUTER-BASED SCIENCE ASSESSMENT FEATURING INTERACTIVE TASKS</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Baltic Science Education</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">China</style></keyword><keyword><style  face="normal" font="default" size="100%">computer-based assessment</style></keyword><keyword><style  face="normal" font="default" size="100%">process data</style></keyword><keyword><style  face="normal" font="default" size="100%">scientific problem-solving</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October/2023</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://oaji.net/articles/2023/987-1697654133.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">Continuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Students’ problem-solving strategies and the differences among strategy groups were explored by analyzing the process data collected during student interactions with computer-based science items. Data were gathered from 1516 eleventh-grade students from 4 schools in China. Analyses of the sequences of students’ response actions revealed that the students were divided into four strategy groups when designing experiments to solve scientific problems: the scientific and rigorous strategy (18.5%), scientific and less rigorous strategy (25.4%), incomplete strategy (31.5%), and chaotic strategy (24.6%). The heatmaps of response actions for each strategy and the frequencies of the most representative response sequences were further explored to understand the students’ detailed trajectories. The results showed that successful problem solvers were generally inclined to explore all possibilities of experimental combinations and design experiments scientifically and rigorously based on the relevant scientific principles. Moreover, the timestamps of response actions were explored to show that the students who adopted the scientific and rigorous strategy spent more time seeking solutions, suggesting that students may need sufficient time to solve complex and authentic scientific problems. The findings enrich the literature on using process data to address theoretical issues in educational assessment and provide students with individualized instructional needs for teachers to improve students’ scientific problem-solving competency.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">929-944</style></section></record></records></xml>