This study investigated the effect of peer leadership on students' cognitive achievement in online asynchronous discussions. Undergraduate students from a large online course were randomly assigned into groups for four asynchronous discussions, with each group having two to three peer leaders. Results of the mixed-method analysis revealed that the quality of student leaders' lower-order cognitive achievement in online discussion was significantly better than that of student responders. Student leaders' higher-order cognitive level achievement in online discussion had at least the same quality as that of student responders. Moreover, both students' higher-order and lower-order cognitive achievement in discussions had positive and moderate correlation with students' course achievement. Further study should focus on methods to maximize student responders' cognitive achievement in online peer-led discussions.

Computer science and computational thinking (CT) education in K-12 schools have been escalating in recent years. A couple of CT instructional models have been proposed to depict the roles of CT in K-16 education. Yet, neither of them discussed CT infusion into a subject course. In this article, we proposed a CT-integration model called TPC²T. In this model, we suggested considering CT as a second subject and using an appropriate technological pedagogical approach to make students’ learning of two subjects meaningful and engaging. We implemented this model in a CT-integrated lesson in two sections of a high-school Spanish course. Students worked in small groups and coded three small and one comprehensive digital Spanish-culture stories in Scratch. Results showed that students taking the CT-integrated lesson had the same degree of improvement in their Spanish culture knowledge as their peers who did not take the CT-integrated lesson. Besides, students taking the CT-integrated lesson had a significant improvement in their CT knowledge. At the same time, their CT self-efficacy outperformed those who did not take the CT-integrated lesson. We discussed the results and offered suggestions for researchers and educators at the end of the article.

Artificial intelligence (AI) has gained widespread public interest in recent years. However, as AI literacy remained excluded from the standard academic curricula, AI education in the US was predominantly offered through extra-curricular activities, which limited AI learning exposure to only a select group of students. Given these limitations, the need to integrate AI literacy education into the standard curricula is increasingly evident. This study investigated the integration of AI learning in an advanced biology course. Thirty-seven students participated in four lessons embedding AI learning in biology contexts. The interplay of students’ AI learning and biology knowledge was examined from the quantitative measure of conceptual understanding and qualitative analysis of interdisciplinary reasoning. This concurrent triangulation research design utilized results from both quantitative and qualitative analyses to develop a comprehensive understanding of students’ AI learning in the biology context. The results of the study showed a significant improvement in students’ AI concepts. Students’ biology knowledge had a slight increase, but it was not statistically significant. Both quantitative and qualitative results underscored a close connection between students’ AI learning and their biology knowledge, though the quantitative findings were not conclusive in some lessons. The article concluded with a discussion of the potential reasons for those discrepancies. In addition, suggestions were provided for future research and practitioners who are interested in integrating AI education across curricula.