Data Science (DS) is an interdisciplinary topic that is applicable to many domains. In this preliminary investigation, we use caselet, a mini-version of a case study, as a learning tool to allow students to practice data science problem solving (DSPS). Using a dataset collected from a real-world classroom, we performed correlation analysis to reveal the structure of cognition and metacognition processes. We also explored the similarity of different DS knowledge components based on students’ performance. In addition, we built a predictive model to characterize the relationship between metacognition, cognition, and learning gain.
As the number of bilingual students in Saudi Arabia continues to grow, it is important to determine how this could impact language fluency. This study explored bilingualism and language fluency among Saudi Arabian students. Specifically, it aimed to determine the impact of bilingualism on language fluency. In doing so, it explored some of the strategies that could be used to enhance fluency as more students continue to learn a second or even third language. Qualitative research methodology was used because it is generally applied to collect data that is descriptive of people's experiences to understand meaning from the perspective of the participants. Data was collected through semi-structured interviews and analyzed using thematic analysis. For this study, a total of 15 teachers who educate elementary students in Saudi Arabia were selected randomly from a pool of a purposively selected population. The coding process revealed three major themes: the impact of bilingualism on language fluency, the main benefits of bilingualism among students, and the major factors that affect language fluency. The conclusion highlights steps that can be taken to enhance language fluency as the number of bilingual (and multilingual) students continues to rise.
KEYWORDS
Bilingualism, monolingual, fluency, cognitive development, learning skills, ability of students, thematic analysis, bilingual students
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