Amidst the global quest for top-notch online education, asynchronous discussions have emerged as a cornerstone, critical to online education systems and socio-economic progress.  These discussions facilitate knowledge sharing, emotional bonds, and the cultivation of higher-order thinking, pivotal for learners' holistic and personalized growth.  The advent of technologies like cloud computing, big data, and deep learning, coupled with the widespread use of intelligent devices, has transformed online learning, making asynchronous discussions a new norm in the era of educational informatization.  Researchers have delved into the theoretical foundations, interaction mechanisms, and emotional nuances of online learning, with a key emphasis on exploring learners' interaction patterns, discourse emotions, and their subsequent impact on learning outcomes, utilizing interactive data and qualitative analysis.  However, further exploration is needed into discussion quality, knowledge construction, and cognitive presence patterns to enhance learning outcomes.  Analyzing cognitive presence in asynchronous online discussions aids teachers in understanding learners' cognitive levels and discourse quality.  This data provides insights to identify learners' cognitive levels, enabling intelligent guidance, and enhancing online learning effectiveness.  Learners' interaction data offers more insights into cognitive presence.  This study pivots on the asynchronous online discussion landscape, meticulously examining the interactive discourse data generated by learners as they collaborate, solve problems, and offer mutual assistance in the online learning realm.  The research probes into learners' perceptual approaches, salient features, underlying mechanisms of cognitive presence, and strategic intervention methods.

Zhi Liu is the PI of affective computing research group, associate researcher and doctoral supervisor at the National Engineering Research Center of Educational Big Data, Central China Normal University. His focuses include learning analytics and educational data mining. He was a guest researcher at the Institute of Computer Science of Humboldt University of Berlin from 2017 to 2018. He is an expert for National Graduate Education Evaluation and Monitoring, an evaluation expert of the National Natural Science Foundation and an evaluation expert for Hubei Provincial Department of Science and Technology, and the leader of the National Science and Technology Innovation 2030 Major Project and National Natural Science Foundation.

He is currently the guest associate editor of the international journal “Frontiers in Artificial Intelligence”, the editorial board member of “Frontiers in Psychology”, and the chair of the special Conference on Learning Analytics of the Learning Science Research Branch of the Chinese Association of Higher Education, the organizing committee chair of International Conference of Educational Technology (ICET).