Enhancing English Learning Efficiency with AI-Assisted Conversational Tools: A Hybrid SEM–NCA Approach Considering Cognitive Processing Depth and Learner Ability

Title: Dataset for “Machine Learning-Based Evaluation of AI-Driven Learning Effectiveness in Chinese Secondary Education” Description:This dataset was collected as part of a quantitative study investigating the impact of artificial intelligence (AI) capabilities and perceived ease of use on learning effectiveness among secondary school students in Northeastern China. The data were obtained via a structured questionnaire distributed both online and offline, comprising items adapted from validated measurement scales (e.g., Parasuraman et al., 1988; Biggs & Tang, 2007). The dataset includes key constructs such as Artificial Intelligence Capability (AIC), Perceived Ease of Use (PEoU), Perceived Usefulness (PU), and Learning Effectiveness (LEF), as well as interaction terms and demographic control variables. The cleaned dataset contains [insert number] valid responses and has been anonymized to protect participant privacy. This dataset supports the results presented in the article submitted to journal and is intended for replication, reuse, and secondary analysis by researchers in educational data science, technology acceptance, and AI ethics in education. Format: CSV (Comma-Separated Values) License: CC-BY 4.0