The impact of digital technology on learning outcomes, specifically deep learning, has been a subject of considerable debate and scrutiny in educational settings. This study aims to provide clarity by conducting a meta-analysis of empirical publications that examine students' deep learning outcomes in relation to digital technology. A comprehensive search of databases and a thorough literature review yielded 60 high-quality, peer-reviewed journal articles that met the inclusion criteria. Using Review Manager 5.4.1 software, a meta-analysis was conducted to assess the overall effectiveness of digital technology. The calculated effect size indicates a positive influence of digital technology on students' deep learning outcomes. Furthermore, a moderator variable analysis revealed several significant findings: 1. Different categories of digital technology tools have a favorable impact on deep learning outcomes; 2. The duration of digital technology treatment does not significantly affect deep learning outcomes; 3. Digital technology demonstrates a highly positive influence on deep learning within the humanities and social sciences disciplines; 4. Combining online and offline utilization of digital technology in education leads to a substantially greater enhancement in deep learning compared to relying solely on online methods; 5. The effectiveness of digital technology on deep learning is enhanced when accompanied by appropriate instructional guidance; 6. Utilizing digital technology in a systematic manner produces different outcomes compared to fragmented approaches, highlighting the importance of a cohesive implementation; 7. Integrating digital technology with collaborative learning has a more pronounced effect on deep learning compared to independent learning. These findings contribute to our understanding of the impact of digital technology on deep learning outcomes and underscore the importance of thoughtful integration and instructional support in educational contexts.

This study investigates the configurational impact of generative artificial intelligence (GenAI) tools on self-regulated learning (SRL) across various educational levels using a 28-week fuzzy-set qualitative comparative analysis (fsQCA) approach. The research explores how factors such as technological proficiency, user engagement, research skills, and feedback quality interact with the functionalities of GenAI tools to enhance SRL capacities. Data were collected through semi-structured surveys and qualitative assessments from a diverse sample of undergraduate and postgraduate students. The findings reveal that the synergistic relationship between learner characteristics and GenAI tool affordances significantly boosts SRL skills. Key configurations identified include the critical role of high-quality feedback and tool functionalities, the importance of positive user attitudes and engagement, and the moderating effect of user interface experience. This study underscores the necessity of tailoring GenAI tools to meet individual learner needs and highlights the potential of these technologies to create adaptive, personalized learning environments. The results advocate for the strategic integration of GenAI tools in educational practices to support diverse learning pathways, contributing to the global discourse on digital pedagogy and the enhancement of self-regulated learning.

Project-based learning (PBL) has been found to exert a positive influence on learners' academic achievements, while also fostering their intrinsic motivation and playing a crucial role in nurturing sustainable learning capacities. Understanding individual differences in self-regulated learning (SRL) within project-based foreign language learning can guide language teachers in delivering personalized instruction. This study utilized a blended learning management system to collect and analyze data on SRL from 95 learners enrolled in a project-based College English course. Through microanalysis, latent profile analysis (LPA), and epistemic network analysis (ENA), the study identified distinct learner profiles and traced their developmental trajectories in project-based language learning. The findings revealed that PBL facilitates the occurrence of SRL behaviors and strengthens connections across different regulation phases. Notably, learners with diverse profiles displayed variations in their SRL epistemic network structures and developmental trajectories. These results highlight the dynamic nature of SRL within the PBL context, underscoring the significance of considering individual differences and supporting learners’ evolving self-regulatory behaviors and strategies throughout their engagement in PBL activities. To enhance SRL in PBL, educators are encouraged to provide scaffolding support, promote help-seeking behaviors, and implement interventions targeting metacognitive processes and reflective practices.