Publications

Bradley, Steven & Akrida, Eleni (2022), Narrowing and Stretching: Addressing the Challenge of Multi-track Programming, English, Rosanne *Stewart, Craig Computing Education Practice 2022. Durham, England, ACM, 1-4.

Morrison, Briana B., Quinn, Beth A., Bradley, Steven, Buffardi, Kevin, Harrington, Brian, Hu, Helen H., Kallia, Maria, McNeill, Fiona, Ola, Oluwakemi, Parker, Miranda, Rosato, Jennifer & Waite, Jane (2021), Evidence for Teaching Practices that Broaden Participation for Women in Computing, Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education. ACM, 57-131.

Wang, Jingyun & Ogata, Hiroaki (2021). An Evaluation of a Meaningful Discovery Learning Support System for Supporting E-book User in Pair Learning. In Intelligent Tutoring Systems (ITS 2021). Springer. 12677: 107-111.

Na Nongkhai, Lalita, Wang, Jingyun & Mendori, Takahiko (2021), A Framework of Exercise Recommendation for Novice Learners in Computer Programming, ICCE 2021: The 29th International Conference on Computers in Education. Online, Asia-Pacific Society for Computers in Education.

Ryan Crosby. (2021). Student Perceptions of Assessment and Feedback – are they valid? In Proceedings of 5th Conference on Computing Education Practice (CEP ’21). Association for Computing Machinery, New York, NY, USA, 5–8. https://doi.org/10.1145/3437914.3437970

Valente, Andrea Marchetti, Emaneuala & Wang, Jingyun (2020), Design of an educational multimedia library to teach Python to non-technical university students, International Conference on Learning Technologies and Learning Environments (LTLE) 2020. Online, International Institute of Applied Informatics.

Wang, Jingyun & Yamada, Yuki (2020), What Should be Considered in Group Formation for Open-end Tasks?, International Conference on Learning Technologies and Learning Environments (LTLE) 2020. Online, International Institute of Applied Informatics.

Bradley, Steven (2020), Creative Assessment in Programming: Diversity and Divergence, Durham, England, ACM, 1.

Wang, Jingyun, Chao, Ching-ju & Liu, Likun (2020). The Learning Behaviors Analysis in a Language Learning Support System – A Pilot Study. In HCI International 2020 – Posters. 1225: 349. 10.1007/978-3-030-50729-9_50

Wang, Jingyun, Shimada, Atsushi, Oi, Misato, Ogata, Hiroaki & Tabata, Yoshiyuki (2020). Development and evaluation of a visualization system to support meaningful e-book learning. Interactive Learning Environments 1-18.

Bradley, Steven (2019), Addressing Bias to Improve Reliability in Peer Review of Programming Coursework, Koli Calling 2019. Finland, ACM, New York, 1-19.

Alamri, Ahmed, Alshehri, Mohammad, Cristea, Alexandra I., Pereira, Filipe D., Oliveira, Elaine, Shi, Lei & Stewart, Craig (2019). Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week’s Activities. In Intelligent Tutoring Systems. ITS 2019. Coy, Andre, Hayashi, Yugo & Chang, Maiga Cham: Springer. 11528: 163-173.

Wang, Jingyun (2019). Ontology Technique and Meaningful Learning Support Environments. In Learning Technologies for Transforming Large-Scale Teaching, Learning, and Assessment. Sampson, Demetrios Spector, J. Michael Ifenthaler, Dirk Isaías, Pedro & Sergis, Stylianos Springer. 215-229.

Jingyun, Wang & Kentaro, Kojima (2019). Exploring heterogeneous grouping strategies from the learning analytic perspective. International Journal of Learning Technologies and Learning Environments 2(2): 21-34.

Ryan Crosby, Marie Devlin, and Lindsay Marshall. (2019). Computing Ipsative Assessment. Improving the Student Experience in Higher Education Using Personalised Assessment and Feedback. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ’19). Association for Computing Machinery, New York, NY, USA, 300. https://doi.org/10.1145/3304221.3325565

Kaneko, Kosuke & Wang, Jingyun (2018), Behavior Analysis of Learning Methods to Overcome Stress or Pressure on Learning Situation, 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI). 256.

Wang, Jingyun & Kojima, Kentaro (2018), Exploring an Approach for Grouping through Predicting Group Performance from Analysis of Learner Characteristics, 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI). 288.

Wang, Jingyun, Mendori, Takahiko & Hoel, Tore (2018). Strategies for Multimedia Learning Object Recommendation in a Language Learning Support System: Verbal Learners Vs. Visual Learners. International Journal of Human–Computer Interaction 35(4-5): 345.

Wang, Jingyun, Ogata, Hiroaki & Shimada, Atsushi (2017), A meaningful discovery learning environment for e-book learners, 2017 IEEE Global Engineering Education Conference (EDUCON). 1158.

Bradley, Steven (2016), Managing Plagiarism in Programming Assignments with Blended Assessment and Randomisation, in Sheard, Judy & Suero Montero, Calkin eds, 16th Koli Calling Conference on Computing Education Research. Koli, Finland, Association for Computing Machinery (ACM), New York, NY, 21-30.

Wang, Jingyun, Ho, Hong-Fa & Ono, Yuichi (2016), Enhancing Personalized Feedback System by Visual Biometric Data Analysis, 2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI). 410.

Wang, Jingyun, Ogata, Hiroaki & Shimada, Atsushi (2016). A Knowledge Comparison Environment for Supporting Meaningful Learning of E-Book Users. Systems 4(2): 21.

Shi, Lei, Cristea, Alexandra I. & Stewart, Craig (2015). Students as Customers: Participatory Design for Adaptive Web 3.0. In The Evolution of the Internet in the Business Sector: Web 1.0 to Web 3.0. Isaías, Pedro, Kommers, Piet & Issa, Tomayess IGI Global. 306-331.

Wang, Jingyun & Mendori, Takahiko (2015). The Reliability and Validity of Felder- Silverman Index of Learning Styles in Mandarin Version. Information Engineering Express 1(3): 1-8.

Wang, Jingyun, Mendori, Takahiko & Xiong, Juan (2014). A language learning support system using course-centered ontology and its evaluation. Computers & Education 78: 278.

Rees, S.W., Bruce, M. & Bradley, S. (2014). Utilising Data-driven Learning in Chemistry Teaching: a Shortcut to Improving Chemical Language Comprehension. New Directions 10(1): 12-19.