Computational Thinking Education Meets Artificial Intelligence
Prof. ABELSON, Hal
Massachusetts Institute of Technology, The United States
Prof. Abelson is Class of 1922 Professor of Electrical Engineering and Computer Science at MIT and a Fellow of the IEEE. He holds an A.B. degree from Princeton University and a Ph.D. degree in mathematics from MIT. In 1992, he was designated as one of MIT's six inaugural MacVicar Faculty Fellows, in recognition of his significant and sustained contributions to teaching and undergraduate education. He won numerous education awards conferred by MIT, IEEE, ACM, etc.
Also, he has played key roles in fostering MIT institutional educational technology initiatives including MIT Open CourseWare and DSpace, and has served as co-chair of the MIT Council on Educational Technology, which oversees MIT's strategic educational technology activities and investments. He is a leader in the worldwide movement towards openness and democratization of culture and intellectual resources. He is a founding director of Creative Commons, Public Knowledge, and the Free Software Foundation, and a former director of the Center for Democracy and Technology – organizations that are devoted to strengthening the global intellectual commons.
Over the past decade innovations such as social networks, online news and Internet commerce have made information technology omnipresent in daily life for much of the world’s population. This has driven the call for K-12 school education to include computational thinking as an essential topic in preparing students for a world increasingly shaped by information technology. Yet even as educators are assimilating the calls to include computing in K-12, the environment for educational computing is being upended by the global explosion of interest in artificial intelligence. While AI builds on CT foundations, its influence on CT education is transformative. Abstraction and modularity remain key, but algorithmic concepts like sequencing and conditionals become less critical in light on increased emphasis on statistical methods. More fundamentally, progress in AI demands that CTE pay attention to the societal impact of computing. AI practitioners in industry and academia are starting to come to grips with their responsibility for the consequences of their work. Many technology companies have adopted policies around “responsible AI” and university courses in AI increasingly include units on ethical design. That same concern is moving into CTE, and K-12 education is beginning to draw on ideas from ethics and sociology alongside traditional technical disciplines.
CT in the Disciplines: Realizing the promise and potential of integrating computational thinking into school learning
Dr. GROVER, Shuchi
Senior Research Scientist, Looking Glass Ventures (Palo Alto, California) &
Visiting Scholar, Stanford University, (United States)
A computer scientist and learning scientist by training, Dr. Shuchi Grover’s work in computing education in both formal and informal learning settings has spanned US, India and Europe. Her current research centers on computational thinking (CT), computer science (CS) education, and STEM+Computing integration mainly in formal K-12 settings.
Formerly a senior research scientist at SRI International, Dr. Grover is a recipient of several grants from the US National Science Foundation to conduct research on CT learning and assessment in varied PK-12 contexts including introductory CS education and STEM classrooms that integrate CS and CT. She also works at the intersectional space between learning, assessment and big data analytics to shape future environments for deeper learning with embedded assessment.
Dr. Grover’s commitment to shaping both research and practice is evident in her outreach work. She has authored highly cited scholarly papers, book chapters, blog posts, and mainstream articles on the topic of CT and CS education in K-12 education. She is advisor to the national K-12 CS Framework (k12cs.org) in the US, a member of the ACM Education Council and the Computer Science Teachers Association’s task force on Computational Thinking, on the editorial board of ACM Transactions on Computing Education, and an advisor to K-12 school districts on CS implementation/integration.
She has a Ph.D. in Learning Sciences and Technology Design (focused on computer science education) from Stanford University, an Ed.M (Technology, Innovation, and Education) from Harvard University, and undergraduate and graduate degrees in computer science.
It is in all the contexts outside of CS classrooms that Computational Thinking (CT) truly shines with its generativity. From music, mathematics, social studies, history, language arts and throughout the sciences and engineering, curricular ideas can come alive with CT. Just as in disciplinary research in each of these fields, where computational thinking advances both everyday practice and its innovations, there is a role for pedagogical innovation in curriculum design and teaching of other subjects through integration in subject classrooms, while also providing rich and varied contexts for developing CT competencies. Drawing on a rich palette of real classroom examples from her own extensive research spanning PreK-12 as well as the field more broadly, Dr. Grover will share a suite of pedagogical strategies for meaningful integration of CT in disciplinary learning in K-12 classrooms. The keynote also highlight the challenges that are commonly encountered in this endeavor— including (but not limited to) teacher preparation and assessment of learning in such integrated settings—and ideas to address them.
Computational Thinking, why is it important and when to learn what?
Prof. SPECHT, Marcus
Technical University of Delft, The Netherlands
Prof. Dr. Marcus Specht is Professor for Digital Education at the Technical University of Delft and Director of the Leiden-Delft-Erasmus Center for Education and Learning. He received his Diploma in Psychology in 1995 and a Dissertation from the University of Trier in 1998 on adaptive information technology. From 2001 he headed the department "Mobile Knowledge" at the Fraunhofer Institute for Applied Information Technology (FIT). From 2005 to 2018 he was Professor for Learning Technologies at the Open Universiteit Nederland and head of the Learning Innovation Lab. His research focus is on Computational Thinking, Learning Analytics, AI in Education, and Virtual and Augmented Reality for Education. Prof. Specht is an Apple Distinguished Educator and was President (2013-2015) of the International Association of Mobile Learning.
The talk will discuss some background on programming education and the embedding of programming education mainly in secondary and higher education. The talk will give some examples of learning programming in higher education and what the relation to underlying concepts and the different facets of computational concepts to the actual use in the BSc and MSc studies are. The embedding of CT concepts in higher education in that sense is related to questions of student motivation, task and assignment design, as also changes towards a digital curriculum. The talk should conclude with refection on some lessons learned on important components for building sustainable student motivation for using computational means in their study and later job.
Assessing computational thinking in PISA
Dr. PIACENTINI, Mario
Senior Analyst, Programme for International Student Assessment (PISA), Organisation for Economic Cooperation and Development (OECD), France
Mario Piacentini is a senior analyst working in the Programme for International Student Assessment (PISA) at the OECD. An expert in measurement, Mario leads the work on the PISA innovative assessments. He coordinates interdisciplinary groups of experts working together on defining complex, transversal competences and designing digital tasks that elicit valid evidence on these competences. This project aims to broaden and deepen how we define successful education systems.
He is the main author of the Global Competence (PISA 2018) and Creative Thinking (PISA 2021) assessment frameworks. He is now leading the development of the PISA 2024 assessment of Learning in the Digital World, that focuses on computational thinking. He also coordinates research aimed at making a better use of technology in assessment.
Before joining PISA, he worked for the Public Governance Directorate and the Statistics Directorate of the OECD, the University of Geneva, the World Bank and the Swiss Development Cooperation. Mario led international measurement projects on education, gender, urbanisation, migration and entrepreneurship. He authored several peer-reviewed articles and reports, including the first PISA report on the well-being of students. Mario holds a PhD in economics from the University of Geneva.
The presentation will illustrate current work to integrate computational thinking in the Programme for International Student Assessment (PISA). PISA is the largest comparative study of student performance, and now collects at each cycle data for over 600.000 students in 80 countries. As such, it continues to have a significant impact on the definition of the competences that education systems should prioritise. Including computational thinking in the PISA frameworks can thus provide more impetus to reforms of curricula and teacher training that assign a greater focus to this crucial set of skills, within and outside computer science courses.
The presentation will focus on two developments. The first is the inclusion of a limited number of items targeting computational thinking in the PISA 2021 mathematics test. The second, more comprehensive effort is the design of the innovative assessment of ‘Learning in the Digital World’ for the PISA 2024 cycle.
In this new domain, students will be asked to develop computational models of complex phenomena and produce or debug algorithmic solutions to problems, using a combination of thinking skills that include abstraction, generalisation and decomposition. The presentation will present some of the approaches and tools that are being experimented, and engage participants in reviewing prototypes of assessment tasks.
How students experience the computational thinking process when playing the board game-Robot City
Distinguished Professor Ting-Chia HSU
Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taiwan
Ting-Chia Hsu (also known as Ching-Kun Hsu) is a Distinguished Professor in the Department of Technology Application and Human Resource Development in National Taiwan Normal University. Her research interests include educational technology and computer education. She was granted a research project at the National Institute of Education, Singapore in 2011 by the Taiwan Ministry of Education. She was a visiting faculty at the Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, USA in 2019, and was granted an abroad research project by Taiwan Ministry of Science and Technology. She was a recipient of the National Taiwan Normal University Academic Excellence Awards from 2014 to 2020. Dr. Hsu is also the editor of the official set of text books for the compulsory education of the Information Technology subject in junior high schools in Taiwan, the market share of which exceeds 30% among the four publishers passing the text-book reviews. The Ministry of Science and Technology granted her the Distinguished Young Scholars Project from August 1, 2014 to July 31, 2016 and from August 1 2016 to July 31, 2019. She gained the Special Outstanding Talent Award from the Ministry of Science and Technology from August 1, 2015 to July 31, 2020. She received the Ta-You Wu Memorial Award from the Ministry of Science and Technology in Taiwan in 2018. She was also selected as the winner of the Early Career Researcher Award 2018 in the Asia-Pacific Society for Computers in Education.
This talk will share the development process of the computational thinking board game. Then, the empirical studies will be shared. The studies utilized the computational thinking educational board game named “Robot City” as the instructional material. The purpose was to achieve high interaction and high-level thinking with the board game, and to help students learn the logics of structural programming and cultivate their computational thinking. The board game was able to provide students with additional augmented reality and multimedia teaching. After several instructional experiments were conducted, the students were found to make significant progress. The studies found that the creative self-efficacy of the students was presented well when playing the computational thinking board game. These studies revealed that proper cognitive load was helpful for learning achievement, but if the students are provided with too much information, such as integration of teacher-centered multimedia instruction and a student-centered augmented-reality learning system to support computational thinking learning at the same time, the students would be given too much information, which would interfere with their concentration on paired logic thinking and collaboration. In addition to human-computer interaction, the studies suggest that the game should mainly strengthen the interaction between people and prevent students from ignoring the connection or collaboration among humans, resulting in dispersing the learning effectiveness of the original board games when they are confronted with too much multimedia. How the students experience the computational thinking process when playing the board games was also explored.
The Five Issues to Facilitate Students Develop Innovative Algorithm for Solving Complex Authentic Problems
Prof. HUANG, Ronghuai
Beijing Normal University, China
Ronghuai Huang is a Professor in Faculty of Education of Beijing Normal University (BNU). He has being engaged in the research on smart learning environment, artificial intelligence in education, educational technology as well as knowledge engineering. He received ‘Chang Jiang Scholar’ award in 2016, which is the highest academic award presented to an individual in higher education by the Ministry of Education of China. He serves as Co-Dean of Smart Learning Institute, Director of UNESCO International Rural Educational and Training Centre, and Director of China National Engineering Lab for Cyber learning Intelligent Technology. He is very active in academic organizations both at home and abroad. He is also Committeeman of the Science Subject Expert Committee of the National Textbook Committee, Co-Leader of Information and Communication Technology Course Standard Group in Ordinary Senior High School, Vice-Chairman of China Educational Technology Association, Vice-Chairman of Teaching Guidance Committee of Educational Technology at Institutions of Higher Education, Vice-Chairman of Beijing Education Informatization Expert Committee, and Expert of MOE AI Innovation Panel. He is also President of The Global Chinese Society for Computers in Education, Vice President of International Association of Smart Learning Environments, and Editor-in-Chief of Springer’s Journal of Smart Learning Environment and Journal of Computers in Education. Till now, he has accomplished and is working on over 100 projects, and his ideas have been widely spread, with about 400 academic papers and over 40 books published at home and aboard.
Artificial intelligence (AI) is the science and engineering of making intelligent machines, especially intelligent computer programs that exhibit characteristics associated with intelligence in human behavior including among other faculties of reasoning, learning, goal seeking, problem solving, and adaptability. With the development of AI technology and widely use of AI technology in lots of sectors in society, it is urgent to prepare students for an “Intelligent” world by arming them with AI theories and practices.
However, lots of problems in curriculum, teachers, and algorithm cases exist for conducting AI education in schools. Firstly, the curriculum includes too much theories and frameworks, but few practical cases which may not suitable for pupils; secondly, teachers often don’t have the basic knowledge and practical experience of AI, and lack methods to implement computational thinking in teaching; thirdly, algorithm cases are often complex and the applicable scenarios are generally not connected with students’ life.
In order to solve the above problems and to facilitate students to develop innovative algorithm, the five issues of open data sets, authentic problem sets, basic algorithm sets, open source platform, and incentive mechanism are considered as the core matters. The keynote will discuss the five issues, and showcase the “Youth Artificial Intelligence Innovation Initiatives” platform that is designed under the guidance of the five issues.
Fostering Digital Creativity in Primary School: Lessons Learned from a Large-scale Longitudinal Study of the CoolThink@JC Pilot
Ms. SHEAR, Linda
Director of Commercial and International Studies, SRI Education
SRI International, The United States
Linda Shear is the Director of Commercial and International Studies in SRI Education at SRI International, and leads evaluation research for CoolThink@JC. She has directed numerous studies of educational technology evaluation and school/system reform, both in the U.S. and internationally, and has supported foundations and nonprofits in strategic planning and theory of change development. She directed research and professional development for ITL Research, a multinational research collaboration to investigate and promote innovative teaching and learning, and has brought related professional development programs to countries around the world. She is currently leading a large-scale study of the adoption of 1:1 technology in over 100 of the most economically challenged schools and communities in the United States. Linda was an undergraduate at Princeton University and did her graduate training in Education at the University of California, Berkeley.
In 2016, the CoolThink@JC Pilot initiative set an ambitious agenda: to bring computational thinking (CT) education and digital creativity to students in 32 of Hong Kong’s primary schools. With a comprehensive suite of lessons, extensive and ongoing professional development opportunities, and in-class teaching supports, CoolThink@JC aims to create a new paradigm for CT at the primary level, both within and beyond Hong Kong, that will prepare students to be active contributors to society in the digital age.
This talk will report on the findings from a rigorous study of this pilot initiative over three years of instruction for students in Primary 4-6. This comprehensive study evaluated the outcomes of the initiative in terms of students’ computational thinking concepts, practices, and perspectives, along with an implementation study that captured the voices of teachers, principals, and students to inform both the ongoing continuous improvement of the CoolThink resources and the supports that will be needed for successful adoption at scale.
The presentation will also introduce the novel set of assessments that this study used to measure not only students’ programming knowledge, but also their developing abilities in logical thinking, problem solving, and other important skills that are key to students’ productive futures as innovators and digital creators.