The 2020 International Conference on Artificial Intelligence and Big Data in Education was held in Beijing on December 11-12.
The conference, jointly organised by The National Center for Educational Technology, China, Beijing Normal University, and iFlytek, was the fourth consecutive annual gathering of experts in psychometrics, educational research, measurement and policy and related fields. This year, due to the COVID-19 pandemic, the conference took a blended approach, complementing the 10 off-line panel sessions with 4 online symposiums.
Over the two days, more than 100 talks covered a wide range of topics, including recent advancement in smart assessment, lessons learnt from the teaching practices amid the pandemic, education administration empowered by IT, novel methods in mental health evaluation and intervention, application of neuroscience and AI in language assessment, and innovative research based on process data, smartphone data, sensor data, geographic data, text data, and open data. Among the speakers were local government officials, academic researchers, education practitioners, and technology company representatives.
The conference was streamed online, with an estimate of over 22 million viewings. The success of the conference was covered by major press in China (e.g. https://finance.sina.com.cn/money/insurance/health/2020-12-14/doc-iiznezxs6876587.shtml, http://news.sciencenet.cn/htmlnews/2020/12/450204.shtm, https://www.sohu.com/a/438224212_243614).
The Psychometrics Centre, as a long-term collaborator with Beijing Normal University, co-organised two sessions of the conference. Additionally, Executive Director Mr Vesselin Popov presented a case study, which overviewed the entire process from curriculum design to CAT development in Northern Ireland. For those who are interested in more details of the conference, please visit the website https://aide.changyan.cn/web/web.html. Specifically, information about the talks delivered in English can be found below:
Time stamp | Speaker | Organisation | Talk |
03:00:17 | Andreas Schleicher | OECD | Educating learners for their future, not our past |
03:33:35 | Thierry Rocher | DEPP, MoE, France | Digital revolution and educational assessment: what future for assessment tools, objects and fuctions? |
01:03:55 | Ying Cui | University of ALberta | A survey of predictive learning analytics of student success in higher education |
03:12:30 | Ma. Mercedes T. Rodrigo | Ateneo de Manila University | Eye tracking for novice programmer research |
03:07:17 | Kalifa Damani | EdTech Hub | Potential of educational technology for accelerated learning |
02:17:50 | Lei Liu | ETS | AI applications to support K12 science learning and teaching |
02:12:00 | Markus Buehner | LMU Munich | The Phone Study Project |
00:17:50 | Bruce McCandliss | Standord University | Sensitive periods for neural responses in speech perception: implications for second language learning and reading development. |
00:14:55 | Beverly Woolf | UMass Amherst | How are you feeling? Emotion recognition in intelligent tutors |
00:37:40 | Alina von Davier | Duolingo | Test score comparability for digital-first assessments in a computational psychometrics framework |
01:09:05 | Christopher Harris | WestEd | Designing technology-enhanced science assessment tasks that focus on knowledge-in-use |
01:30:10 | Mingyu Feng | WestEd | Considerations in design and evaluation of intelligence systems for learning |
02:10:07 | Shuai Wang | SRI International | When is adaptive learning effective learning? |
02:34:20 | Vesselin Popov | University of Cambridge | From curriculum design to CAT development: A Northern Irish case study |
03:00:30 | Sandra Matz | Columbia University Business School | Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
00:33:10 | James Pennebaker | University of Texas at Austin | Analyzing words: Personality, thinking styles, and behaviors |
01:03:30 | Jason Rentfrow | University of Cambridge | Geographical psychology: Causes and consequences of the spatial clustering of personality |
01:40:45 | Michal Kosinski | Stanford University | Educational assessment: Using big data and artificial intelligence |
02:18:45 | Jenny Gibson | University of Cambridge | Using sensor-based movement and location data to understand social development in children |
02:59:17 | Samuel Gosling | University of Texas at Austin | Dissolving the distinction between teaching and research via online classes and smartphone sensing |
03:23:27 | Neil Heffernan | Worcester Polytechnic Institute | ASSISTments: A vision of crowdsourcing |
03:51:50 | William Revelle | Northwestern University | Open science <=> open methods + open data |