| A scoping review of empirical research on recent computational thinking assessments M Cutumisu, C Adams, C Lu Journal of Science Education and Technology 28 (6), 651-676, 2019 | 142 | 2019 |
| A scoping review of computational thinking assessments in higher education C Lu, R Macdonald, B Odell, V Kokhan, C Demmans Epp, M Cutumisu Journal of Computing in Higher Education 34 (2), 416-461, 2022 | 75 | 2022 |
| Online engagement and performance on formative assessments mediate the relationship between attendance and course performance C Lu, M Cutumisu International journal of educational technology in higher education 19 (1), 2, 2022 | 71 | 2022 |
| Analyzing students’ performance in computerized formative assessments to optimize teachers’ test administration decisions using deep learning frameworks J Shin, F Chen, C Lu, O Bulut Journal of Computers in Education 9 (1), 71-91, 2022 | 44 | 2022 |
| Integrating Deep Learning into an Automated Feedback Generation System for Automated Essay Scoring. C Lu, M Cutumisu International Educational Data Mining Society, 2021 | 29 | 2021 |
| Measuring K-12 computational thinking concepts, practices and perspectives: An examination of current CT assessments C Adams, M Cutumisu, C Lu Society for Information Technology & teacher education international …, 2019 | 22 | 2019 |
| Using structural equation modeling to examine the relationship between preservice teachers’ computational thinking attitudes and skills M Cutumisu, C Adams, F Glanfield, C Yuen, C Lu IEEE transactions on education 65 (2), 177-183, 2021 | 20 | 2021 |
| Health care providers’ performance, mindset, and attitudes toward a neonatal resuscitation computer-based simulator: empirical study M Cutumisu, SK Ghoman, C Lu, SD Patel, C Garcia-Hidalgo, C Fray, ... JMIR Serious Games 8 (4), e21855, 2020 | 13 | 2020 |
| A scoping review of empirical studies on theory-driven learning analytics Q Wang, A Mousavi, C Lu Distance Education 43 (1), 6-29, 2022 | 12 | 2022 |
| Unsupervised machine learning algorithms examine healthcare providers' perceptions and longitudinal performance in a digital neonatal resuscitation simulator C Lu, SK Ghoman, M Cutumisu, GM Schmölzer Frontiers in pediatrics 8, 544, 2020 | 12 | 2020 |
| Examining adults’ behavioral patterns in a sequence of problem solving tasks in technology-rich environments Q Wang, A Mousavi, C Lu, Y Gao Computers in Human Behavior 147, 107852, 2023 | 10 | 2023 |
| Mindset moderates healthcare providers' longitudinal performance in a digital neonatal resuscitation simulator C Lu, SK Ghoman, M Cutumisu, GM Schmölzer Frontiers in Pediatrics 8, 594690, 2021 | 9 | 2021 |
| Learning outcome modeling in computer-based assessments for learning: A sequential deep collaborative filtering approach F Chen, C Lu, Y Cui, Y Gao IEEE Transactions on Learning Technologies 16 (2), 243-255, 2022 | 5 | 2022 |
| Discovering clusters of support utilization in the Canadian community health survey–mental health M Cutumisu, J Southcott, C Lu International Journal of Mental Health and Addiction 22 (1), 394-416, 2024 | 3 | 2024 |
| Automated Feedback Generation for Learner Modeling in Intelligent Tutoring Systems C Lu | 2 | 2021 |
| Speed of processing: Tests and factor structure JP Das, C Lu JEP 13 (30), 30-11, 2022 | 1 | 2022 |
| Professional Education in China C Lu, B Peng, X Chen Education in China and the World: National Development and Global …, 2024 | | 2024 |
| Using learners’ problem-solving processes in computer-based assessments for enhanced learner modeling: A deep learning approach F Chen, C Lu, Y Cui Education and Information Technologies 29 (11), 13713-13733, 2024 | | 2024 |
| Impacts of engagement on academic outcomes in technology-enhanced learning C Lu, O Bulut, C Demmans Epp, M Gierl Distance Education, 1-20, 2024 | | 2024 |
| Growth mindset mediates the relationship between computational thinking and programming self-efficacy C Wang, C Lu, F Chen, X Liu, Q Zhao, S Wang Education and Information Technologies, 1-24, 2024 | | 2024 |
