Referred Publications

Journal Papers   Conference Papers & Book Chapters   Short Papers & Posters


Journal Papers

  1. Xing, W., Huang, X., Li, C., & Xie, C. (2023). Teaching thermodynamics with augmented interaction and learning analytics. Computers & Education. [IF: 12, SSCI]
  2. Xing, W., & Du, H. (2023). Mining Large Open Online Learning Networks: Exploring Community Dynamics and Communities of Performance. Journal of Educational Computing Research. [IF: 4.345, SSCI]
  3. Du, H., Xing, W., & Zhu, G. (2023). Mining teacher informal online learning networks: Insights from massive educational chat tweets. Journal of Educational Computing Research, 127-150. [IF: 4.8, SSCI]
  4. Du, H., Xing, W., & Pei, B. (2023). Leveraging explainability for discussion forum classification: Using confusion detection as an example. Distance Education, 1-16. [IF: 7.3, SSCI]
  5. Pei, B., Xing, W., Zhu, G., Zlatkovic, K., & Xie, C. (2023). Integrating infrared technologies in science learning: An evidence-based reasoning perspective. Education and Information Technologies. [IF: 5.5, SSCI]
  6. Zhu, G., Xing, W., Popov, V., Li, Y., Xie, C., & Horwitz, P. (2022). Using Learning Analytics to Understand Students’ Discourse and Behaviors in STEM Education. Artificial Intelligence in STEM Education: The Paradigmatic Shifts in Research, Education, and Technology
  7. Xing, W., Zhu, G., Arslan, O., Shim, J., & Popov, V. (2022). Using learning analytics to explore the multifaceted engagement in collaborative learning. Journal of Computing in Higher Education. [IF: 5.6, SSCI]
  8. Li, C., Xing, W., & Leite, W. (2022). Using fair AI to predict students’ math learning outcomes in an online platform. Interactive Learning Environments. [IF: 5.4, SSCI]
  9. Leite, W., Xing, W., Fish, G., & Li, C. (2022). Teacher strategies to use virtual learning environments to facilitate algebra learning during school closures. Journal of Research on Technology in Education. [IF: 5.1, SSCI]
  10. Xing, W. (2022). Does the early bird catch the worm? A large-scale examination of the effects of early participation in online learning. Distance Education. [IF: 2.952, SSCI]
  11. Li, C., & Xing, W., Leite, W. (2022). Building socially responsible conversational agents using big data to support online learning: A case with algebra nation. British Journal of Educational Technology. [IF: 4.929, SSCI]
  12. Li, C., & Xing, W., Leite, W. (2022). Towards Building a Fair Peer Recommender to Support Help-Seeking in Online Learning. Distance Education. [IF: 2.952, SSCI]
  13. Liu, B.g, Xing, W., Zeng, Y., & Wu, Y. (2022). Linking cognitive processes and learning outcomes: The influence of cognitive presence on learning performance in MOOCs. British Journal of Educational Technology. [IF: 4.929, SSCI]
  14. Tang, H., Arslan, O., Xing, W., & Kamali‑Arslantas, T. (2022). Exploring collaborative problem solving in virtual laboratories: a perspective of socially shared metacognition. Journal of Computing in Higher Education. [IF: 2.627, SSCI]
  15. Xing, W., Du, D., Bakhshi, A., Chiu, K. C., & Du, H. (2021). Designing a Transferable Predictive Model for Online Learning Using a Bayesian Updating Approach. IEEE Transactions on Learning Technologies, 14(4), 474-485. [IF: 3.720, SCI & SSCI]
  16. Arslan, O., Xing, W., Inan, F. A., & Du, H. (2021). Understanding topic duration in Twitter learning communities using data mining. Journal of Computer Assisted Learning. 1-13. [IF: 3.862, SSCI]
  17. Xing, W., Li, C., Chen, G., Huang, X., Chao, J., Massicotte, J., & Xie, C. (2021). Automatic Assessment of Students’ Engineering Design Performance Using a Bayesian Network Model. Journal of Educational Computing Research, 59(2), 230-256. [IF: 3.088, SSCI]
  18. Li, C., & Xing, W. (2021). Natural Language Generation Using Deep Learning to Support MOOC Learners. International Journal of Artificial Intelligence in Education, 1-29.
  19. Xing, W., & Wang, X. (2021). Understanding students’ effective use of data in the age of big data in higher education. Behaviour & Information Technology, 1-18. [IF: 3.086, SCI & SSCI]
  20. Du, H., Xing, W., & Pei, B. (2021). Automatic text generation using deep learning: providing large-scale support for online learning communities. Interactive Learning Environments, 1-16. [IF: 3.928, SSCI]
  21. Pei, B., & Xing, W. (2021). An Interpretable Pipeline for Identifying At-Risk Students. Journal of Educational Computing Research, 07356331211038168. [IF: 3.088, SSCI]
  22. Zhu, G., Zeng, Y., Xing, W., Du, H., & Xie, C. (2021). Reciprocal Relations between Students’ Evaluation, Reformulation Behaviors, and Engineering Design Performance Over Time. Journal of Science Education and Technology, 1-13. [IF: 2.315, SSCI]
  23. Tang, H., & Xing, W. (2021). Massive open online courses for professional certificate programs? Perspectives on professional learners’ longitudinal participation patterns. Australasian Journal of Educational Technology, 136-147. [IF: 3.067, SSCI]
  24. Pei, B.g, Xing, W., & Wang, M. (2021). Academic development of multimodal learning analytics: a bibliometric analysis. Interactive Learning Environments, 1-19. [IF: 3.928, SSCI]
  25. Liu, B.g, Xing, W., Zeng, Y., & Wu, Y. (2021). Quantifying the Influence of Achievement Emotions for Student Learning in MOOCs. Journal of Educational Computing Research, 59(3), 429-452. [IF: 3.088, SSCI]
  26. Wang, X., & Xing, W. (2021). Supporting Youth with Autism Learning Social Competence: A Comparison of Game-and Nongame-Based Activities in 3D Virtual World. Journal of Educational Computing Research, 07356331211022003. [IF: 3.088, SSCI]
  27. Liu, B.g, Wu, Y., Xing, W., Cheng, G., & Guo, S. (2021). Exploring behavioural differences between certificate achievers and explorers in MOOCs. Asia Pacific Journal of Education, 1-13. [IF: 1.057, SSCI]
  28. Zhu, G., Raman, P., Xing, W., & Slotta, J. (2021). Curriculum design for social, cognitive and emotional engagement in Knowledge Building. International Journal of Educational Technology in Higher Education, 18(1), 1-19. [IF: 4.944, SSCI]
  29. Xing, W., Lee, H. S., & Shibani, A. (2020). Identifying patterns in students' scientific argumentation: content analysis through text mining using Latent Dirichlet Allocation. Educational Technology Research & Development, 68(5). [IF: 3.565, SSCI]
  30. Zheng, J., Xing, W., Zhu, G., Chen, G., Zhao, H., & Xie, C. (2020). Profiling self-regulation behaviors in STEM learning of engineering design. Computers & Education. [IF: 8.538, SSCI]
  31. Li, S., Du, H., Xing, W., Zheng, J., Chen, G., & Xie, C. (2020). Examining temporal dynamics of self-regulated learning behaviors in STEM learning: A network approach. Computers & Education, 158, 103987. [IF: 8.538, SSCI]
  32. Zheng, J., Xing, W., Huang, X., Li, S., Chen, G., & Xie, C. (2020). The role of self-regulated learning on science and design knowledge gains in engineering projects. Interactive Learning Environments, 1-13. [IF: 3.928, SSCI]
  33. Li, S., Chen, G., Xing, W., Zheng, J., & Xie, C. (2020). Longitudinal clustering of students’ self-regulated learning behaviors in engineering design. Computers & Education, 153, 103899. [IF: 8.538, SSCI]
  34. Xing, W., Pei, B., Li, S., Chen, G., & Xie, C. (2019). Using learning analytics to support students’ engineering design: the angle of prediction. Interactive Learning Environments, 1-18. [IF: 1.938, SSCI]
  35. Xing, W., Tang, H., & Pei, B. (2019). Beyond positive and negative emotions: Looking into the role of achievement emotions in discussion forums of MOOCs. Internet and Higher Education, 43, 100690. [IF: 6.566, SSCI]
  36. Pei, B., Xing, W., & Lee, H.S (2019). Using automatic image processing to analyze visual artifacts created by students in scientific argumentation. British Journal of Educational Technology, 50(6), 3391-3404. [IF: 2.951, SSCI]
  37. Xing, W., Popov, V., Zhu, G., Horwitz, P., & McIntyre, C. (2019). The effects of transformative and non-transformative discourse on individual performance in collaborative-inquiry learning. Computers in Human Behavior, 98, 267-276. [IF: 5.003, SSCI]
  38. Xing, W., & Du, D. P. (2019). Dropout prediction in MOOCs: Using deep learning for personalized intervention. Journal of Educational Computing Research, 57(3), 755-776. [IF: 2.180, SSCI]
  39. Xing, W. (2019). Large-scale path modeling of remixing to computational thinking. Interactive Learning Environments, 1-14. [IF: 1.938, SSCI]
  40. Xing, W. (2019). Exploring the influences of MOOC design features on student performance and persistence. Distance Education, 40(1), 98-113. [IF: 1.702, SSCI]
  41. Zhu, G., Xing, W., Costa, S., Scardamalia, M., & Pei, B. (2019). Exploring emotional and cognitive dynamics of knowledge building in grades 1 and 2. User Modeling and User-Adapted Interaction (UMUAI), 29(4), 789-820. [IF: 4.682, SCI]
  42. Tang, H., Xing, W., & Pei, B. (2019). Time really matters: Understanding the temporal dimension of online learning using educational data mining. Journal of Educational Computing Research, 57(5), 1326-1347. [IF: 2.180, SSCI]
  43. Liu, B., Xing, W., Wu, Y., Li, R., Tian, Y., & Ma, X. (2019). Students’ Interaction and Perceptions in a Large Enrolled Blended Seminar Series Course. The Turkish Online Journal of Educational Technology. 18(03), 88-96 [SSCI]
  44. Zheng, J., Xing, W., & Zhu, G. (2019). Examining sequential patterns of self-and socially shared regulation of STEM learning in a CSCL environment. Computers & Education, 136, 34 – 48. [IF: 5.296, SSCI]
  45. Wang, X., & Xing, W. (2019). Understanding elementary students’ use of digital textbooks on mobile devices: A structural equation modeling approach. Journal of Educational Computing Research, 57(3), 755-776. [IF: 2.180, SSCI]
  46. Zhu, G., Xing, W., & Popov, V. (2019). Uncovering the sequential patterns in transformative and non-transformative discourse during collaborative inquiry learning. Internet and Higher Education, 41, 51-61. [IF: 6.566, SSCI]
  47. Xing, W., & Gao, F. (2018). Exploring the relationship between online discourse and commitment in Twitter professional learning communities. Computers & Education, 126, 388-398. [IF: 5.627, SSCI]
  48. Xing, W., Goggins, S., & Introne, J. (2018). Quantifying the effect of informational Support on membership retention in online communities through large-scale data analytics. Computers in Human Behavior, 86, 227-234. [IF: 4.306, SSCI]
  49. Tang, H., Xing, W., & Pei, B. (2018). Exploring the temporal dimension of forum participation in MOOCs. Distance Education, 39(3), 353-372. [IF: 1.729, SSCI]
  50. Wang, X., & Xing, W. (2018). Autistic youth in 3D game-based collaborative virtual learning: Associating avatar interaction patterns with embodied social presence. British Journal of Educational Technology, 49(4), 742-760. [IF: 2.588, SSCI]
  51. Tawfik, A., Law, V., Xun, G. Xing, W., & Kyung K. (2018). The effect of sustained vs. faded scaffolding on students’ argumentation in ill-structured problem solving. Computers in Human Behavior, 87, 436-449. [IF: 4.306, SSCI]
  52. Wang, X., & Xing, W. (2018). Exploring the influence of parental involvement and socioeconomic status on teen digital citizenship: a path modeling approach. Educational Technology & Society. 21(1), 186-199. [IF: 2.133, SSCI]
  53. Wang, X., Laffey, J., Xing, W., Galyen, K., & Stichter, J. (2017). Fostering verbal and non-verbal social interactions in a 3D collaborative virtual learning environment: A case study of youth with autism spectrum disorders learning social competence in iSocial. Educational Technology Research & Development 65(4), 1015-1039. [IF: 2.115, SSCI]
  54. Xing, W., Chen, X., Stein, J., & Marcinkowski, M. (2016). Temporal predication of dropouts in MOOCs: Reaching the low hanging fruit through stacking generalization. Computers in Human Behavior, 58, 119-129. [IF: 3.435, SSCI]
  55. Goggins, S., & Xing, W. (2016). Building models explaining student participation behavior in asynchronous online discussion. Computers & Education, 94, 241-251. [IF: 3.819, SSCI]
  56. Wang, X., Laffey, J., Xing, W., & Ma, Y. (2016). Exploring embodied social presence of youth with Autism in 3D collaborative virtual learning environment: A case study. Computers in Human Behavior, 55, 310-321. [IF: 3.435, SSCI]
  57. Xing, W., Guo, R., Petakovic, E., & Goggins, S. (2015). Participation-based student final performance prediction model through interpretable genetic programming: Integrating learning analytics, educational data mining and theory. Computers in Human Behavior. 47, 168-181. [IF: 3.435, SSCI]
  58. Xing, W., Wadholm, B., & Goggins, S. (2015) Group learning assessment: Developing theory-informed analytics. Educational Technology & Society. 18(2), 110-128. [IF: 1.34, SSCI]
  59. Goggins, S., Xing, W., Chen, X., Chen, B., & Wadholm, B. (2015). Learning analytics at ”small scale“: Exploring a complexity-grounded model for assessment automation. Journal of Universal Computer Science. 21(1), 66-92. [IF: 1.066, SCI]

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Conference Papers & Book Chapters

  1. Du, H., Xing, W., Pei, B., Zeng, Y., Lu, J., & Zhang, Y. (2023, August). A Descriptive and Historical Review of STEM + C Research: A Bibliometric Study. In book: Computer Supported Education
  2. Song, Y.,Xing, W., Barron, A., Oh, H., Li, C., & Minces, V. (2023, June). M-flow: a Flow-based Music Creation Platform Improves Underrepresented Children’s Attitudes toward Computer Programming. In 22nd annual ACM Interaction Design and Children (IDC) Conference (pp. 233-238). Chicago, Illinois
  3. Minces, V., Xing, W., & Chenglu, L. (2023, March). Work in Progress: Mflow, a Flow-based Music Programming Platform for Young Children. In 2023 IEEE World Engineering Education Conference (EDUNINE) (pp. 599-605). Bogota, Colombia
  4. Fan, Z., Xing, W., & Chenglu, L. (2023, March). Predicting Students' Algebra I Performance using Reinforcement Learning with Multi-Group Fairness. In LAK23: 13th International Learning Analytics and Knowledge Conference (pp. 657-662). Arlington, Texas
  5. Song, Y., Xing, W., Tian, X., & Chenglu, L. (2022, March). Are We on the Same Page? Modeling Linguistic Synchrony and Math Literacy in Mathematical Discussions. In LAK23: 13th International Learning Analytics and Knowledge Conference (pp. 599-605). Arlington, Texas
  6. Zhu, G., Xing, W., Popov, V., Li, Y., & Xie, C. (2022, December). Using Learning Analytics to Understand Students' Discourse and Behaviors in STEM Education. In book: Artificial Intelligence in STEM Education.
  7. Du, H., Xing, W., & Zhang, Y. (2022, August). Misconception of Abstraction: When to Use an Example and When to Use a Variable? In ICER 2022: ACM Conference on International Computing Education Research. Lugano, Switzerland
  8. Hansen, Z., Du, H., Xing, W., Eckel, R., Lugo, J., & Zhang, Y. (2022, August). A Preliminary Data-driven Analysis of Common Errors Encountered by Novice SPARC Programmers. In 38th International Conference on Logic Programming. Haifa, Israel
  9. Li, C., & Xing, W., (2022, June). Revealing Factors Influencing Students' Perceived Fairness: A Case with a Predictive System for Math Learning. In Learning@Scale: 2022 ACM Conference on Learning at Scale. New York City, New York
  10. Li, C., Xing, W., & Leite, W. (2022, March). Do Gender and Race Matter? Supporting Help-Seeking with Fair Peer Recommenders in an Online Algebra Learning Platform. In LAK22: 12th International Learning Analytics and Knowledge Conference (pp. 432-437). Virtual. [Acceptance rate: 29.5%]
  11. Du, H. Xing, W., & Zhang, Y. (2021). A Debugging Learning Trajectory for Text-Based Programming Learners.In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 2.
  12. Li, C. Xing, W., & Leite, W. (2021). Using Fair AI with Debiased Network Embeddings to Support Help Seeking in an Online Math Learning Platform.International Conference on Artificial Intelligence in Education.
  13. Li, C. Xing, W., & Leite, W. (2021). Yet Another Predictive Model? Fair Predictions of Students’ Learning Outcomes in an Online Math Learning Platform.LAK21: 11th International Learning Analytics and Knowledge Conference.
  14. Nguyen, V. T., Zhang, Y., Jung, K., Xing, W., & Dang, T. (2020, January). VRASP: A Virtual Reality Environment for Learning Answer Set Programming. In International Symposium on Practical Aspects of Declarative Languages (pp. 82-91). Springer, Cham.
  15. Huang, X., Xing, W., Zhao, H., Chao, J., Schimpf, C., Chen, G. & Xie, C. (2020, June). Understanding science learning through writings on engineering design. In Proceedings of the 2020 International Conference of the Learning Sciences (ICLS, 2020), (Vol. 1, pp. 1771-1773), Nashville, TN: International Society of the Learning Sciences.
  16. Du, H., Nguyen, L., Yang, Z., Abu-Gellban, H., Zhou, X., Xing, W., ... & Jin, F. (2019, July). Twitter vs News: Concern Analysis of the 2018 California Wildfire Event. In 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) (Vol. 2, pp. 207-212). IEEE.
  17. Zheng, J., Xing, W., Zhu, G., Chen, G., Zhao, H. g, & Huang, X. (2019). Person-oriented approach to profiling learnings’ self-regulation in STEM learning. In Proceedings of the 9th International Conference on Learning Analytics and Knowledge - LAK ’19 (pp. 245-246). Tempe, Arizona.
  18. Tang, H. & Xing, W. (2019). Achievement emotions and attritions in Massive Open Online Courses: Using machine learning models, In Proceedings of the 9th International Conference on Learning Analytics and Knowledge - LAK ’19 (368-373). Tempe, Arizona.
  19. Pei, B., Zhao, H., Xing, W., & Lee, H. S. (2019). The Exploration of Automated Image Processing Techniques in the Study of Scientific Argumentation. In Cognitive Computing in Technology-Enhanced Learning (pp. 175-190). IGI Global.
  20. Popov, V., Xing, W., Zhu, G., Horwitz, P., & McIntyre, C. (2018, June). The influence of students’ transformative and non-transformative contributions on their problem solving in collaborative inquiry learning. In J, Key, & R. Luckin (Eds.), rethinking Learning in the Digital Age. Making the Learning Sciences Count: In Proceedings of The International Conference of the Learning Sciences (ICLS, 2018), (Vol. 3, pp. 855-862). London, UK: International Society of the Learning Sciences. [Acceptance rate: 32%; ~5000 words]
  21. Arslan, O.g, Xing, W., Horwitz, P, & McIntyre, C. (2018). Examining the influence of socially shared metacognition on group problem solving. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge - LAK ’18 (pp. 1-3). Sydney, Australia.
  22. Guo, Y., Xing, W., & H., Lee. Identifying students’ mechanistic explanations in textual responses to science questions with association rule mining. In Proceedings of the 2015 International Conference on Data Mining (ICDM). Atlantic City, NJ: IEEE.
  23. Xing, W., Kim, S. & Goggins, S. (2015). Modeling performance in asynchronous CSCL: An exploration of social ability, collective efficacy and social interaction. Exploring the Material Conditions of Learning: Proceedings of The Computer Supported Collaborative Learning (CSCL 2015), (Vol, pp. 276-283). Gothenburg, Sweden: International Society of the Learning Sciences. [Acceptance rate: 36%; ~5500 words]
  24. Xing, W., & Goggins, S. (2015). Learning analytics in outer space:a Hidden Naive Bayes model for automatic student off-task behavior detection. In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge - LAK'15 (pp. 176-183). New York, NY, USA: ACM. [Acceptance rate: 27%; ~7000 words]
  25. B. Chen, X. Chen,& Xing, W.,(2015), "Twitter Archeology" of learning analytics and knowledge conferences In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge - LAK'15 (pp. 340-349). New York, NY, USA: ACM. [Acceptance rate: 27%; ~8000 words]
  26. Xing, W., Wadholm, B., & Goggins, S. (2014). Learning analytics in CSCL with a focus on assessment: An exploratory study of activity theory-informed cluster analysis. In Proceedings of the Fourth International Conference on Learning Analytics And Knowledge- LAK'14 (pp. 59-67). ACM. New York, NY, USA: ACM.[Acceptance rate: 30%; ~7000 words]
  27. Xing, W., & Wu, Y. (2014). Assessment intelligence in small group learning. IADIS international conference on cognition and exploratory learning in the digital age (CELDA 2014) (pp. 47-54). Porto, Portugal: IADIS. [Acceptance rate: 30%; ~5000 words]
  28. Xing, W., Guo, R., Richardson, B., & Kochtanek, T. (2014). Google Analytics spatial data visualization: Thinking outside of the box. In S. Yamamoto (Ed.), Human Interface and the Management of Information: Information and Knowledge Design and Evaluation (pp. 120-127). New York, NY: Springer. ISBN 978-3-319-07730-7.
  29. Xing, W., Guo, R., Lowrance, N., & Kochtanek, T. (2014). Decision support based on time-series analytics: A cluster methodology. In Human Interface and the Management of Information: Information and Knowledge in Applications and Services (pp. 217-225). New York, NY: Springer. ISBN 978-3-319-07862-5.

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Short Papers & Posters

  1. Aragon, C., Huang, Y., Neff, G., & Xing, W.,. Developing a research agenda for Human-centered data scienc. In Proceedings of the 2016 Computer Supported Cooperative Work and Social Computing (CSCW). San Francisco, CA: ACM.
  2. Xing, W., & Goggins, S. (2015). Student assessment in small groups: A spectral clustering model. In iConference 2015 Proceedings (pp. 1-5). Newport Beach, CA: IDEALS.
  3. Xing, W., Wadholm, B., & Goggins, S. (2014). Assessment analytics in CSCL: Activity theory based method. Learning and Becoming in Practice: Proceedings of the 11th International Conference of the Learning Sciences (ICLS 2014), (Vol. 3, pp. 1535-1536). Boulder, CO: International Society of the Learning Sciences.
  4. Xing, W., Goggins, S. (2014). Automated CSCL group assessment: activity theory based computational method. In LAK Workshops: Computational Approaches to Connecting Levels of Analysis in Networked Learning Communities.
  5. Ma, Y., Friel, C., & Xing, W.,(2014).Instructional activities in a discussion board forum of an e-leaning management system. In HCI International 2014-Posters' Extended Abstracts (pp. 112-116). Crete, Greece: Springer International Publishing.
  6. Ma, Y.,Xing, W.,& Friel, C. (2013). Factors and cues impacting user information selection and processing performance in kiosk touch screen interfaces. In HCI International 2013-Posters' Extended Abstracts (pp. 56-60). Las Vegas, Nevada: Springer Berlin Heidelberg.

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