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Merit-All Online Learning Lab
Past Projects
Epistemic beliefs under self-regulated remote learning: a review
This project explores how individual beliefs about knowledge affect their learning motivation and confidence in online learning from a theoretical point of view.
Motivation mediates the prediction of academic stress for epistemic beliefs: a comparison between science and literature
This project verifies the effect of knowledge model on academic stress in different subjects.
Self-regulated learning and epistemic beliefs in remote learning during a lockdown
This project establishes the quantitative relationship between knowledge beliefs and students’ online learning engagement and academic stress using evidence gathered from 396 students.
Ongoing Projects
Enhance eLearning/Teaching human-computer interaction experience with programs that reduce cognitive load
This project enhances the Easy-Teach platform by introducing interactive modules to reduce cognitive load during learning process.
Computer-assisted game-based instruction of mathematics
This project draws inspiration from previous research in knowledge model. It aims to help student build more sophisticated knowledge beliefs through games.
A vocabulary instruction curriculum tailored to learner’s individual differences
In partnership with Merit-All LA, this project proposes a vocabulary instruction framework that fosters the development of students with different motivational, cognitive, and socio-affective learning tendencies.
Online Learning
Online learning is an essential component of Qianli’s remote instruction and is gaining importance globally post-covid. Improving student engagement and learning experience is essential given the uniqueness of online learning environment.
Merit-All Online Learning Lab offers courses to help students adapt to online learning mode and conducts research to improve the understanding of online learning.
Pathway to eLearning
We offer courses centering on learning strategies in online course settings to help students navigate online learning.
Easy-Teach
Easy-Teach is a platform developed by Merit-All OL. It is built to allow students to access online learning in a self-paced manner through the module-based course structure.
Additionally, we designed a drag-and-drop mechanism to facilitate course creation. An inbuilt textbook2course AI was also available.
To access Easy-Teach:https://www.easy-teach-interactive-learning.com
Next-Gen Initiative
Next-Gen initiative is dedicated to nurture the next generation of learning science researchers and practitioners. Participants are guided by professionals to conduct evidence-based research based on Qianli’s courses and students.
The initiative recruits 10-20 students who have an interdisciplinary interests in education, psychology, linguistics, computer science, etc. Participants will receive 10 units of training and join OL’s ongoing projects.
This initiative is still open to application. Please contact tinogao@ecits.ac.
Our Impact
To date, OL has initiate 6 research projects. Three of them have been published. Pathway to eLearning courses covered 70 students in three schools. The Easy-Teach platform has covered three schools with 200 users and our inbuilt AI has been invited to Intel’s AI impact forum.
Build a better Qianli
Merit-All OL contributes to Qianli’s research and development. OL’s research in epistemic beliefs leads to in-depth discussion on how to foster the development of subject-specific knowledge model. Easy-Teach upgrades the instructor team’s toolkit and increases the accessibility of our project. Together, OL constitutes an essential component of Tech support.
Moving Forward
We aim to expand Easy-Teach to more schools and regions. This growth will be supported by forming new partnerships with educational institutions and improving accessibility to broaden student access. To further engage users, we plan to introduce gamification elements, interactive assessments, and personalized learning paths, creating a more motivating and immersive learning experience.