The state of the field in computational thinking assessment

While interest in computational thinking (CT) education has grown globally in the past decade, there lacks a single unified definition of CT. This can pose significant challenges for researchers, teachers, and policy makers trying to decide which assessment methods are appropriate for their specific CT interventions. Rather than trying to create a single unified definition of CT, this symposium brings together a broad spectrum of leading CT researchers to share what CT means for them, how it influenced their learning designs, and the methods for assessing CT learning. This interactive session will showcase these different views of CT in a single place and serve as a rich opportunity for comparison and discussion.

[1]  Rebecca Ferguson,et al.  Social Learning Analytics , 2012, J. Educ. Technol. Soc..

[2]  Paula Hooper,et al.  Tinkering , Learning & Equity in the After-School Setting , 2013 .

[3]  Linda Darling-Hammond,et al.  Powerful Learning: What We Know About Teaching for Understanding , 2008 .

[4]  David F. Feldon,et al.  Electrifying Engagement in Middle School Science Class: Improving Student Interest Through E-textiles , 2017 .

[5]  Gautam Biswas,et al.  Assessing Student Performance in a Computational-Thinking Based Science Learning Environment , 2014, Intelligent Tutoring Systems.

[6]  J. Pellegrino,et al.  Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century , 2013 .

[7]  Eric Roberts,et al.  Assisting and assessing the development of technological fluencies: insights from a project-based approach to teaching computer science , 2002, CSCL.

[8]  Michael S. Horn,et al.  Bringing Computational Thinking Into High School Mathematics and Science Classrooms , 2016, ICLS.

[9]  Michael S. Horn,et al.  Interactive Assessment Tools for Computational Thinking in High School STEM Classrooms , 2014, INTETAIN.

[10]  Josh Sheldon,et al.  Critical computational empowerment: Engaging youth as shapers of the digital future , 2017, 2017 IEEE Global Engineering Education Conference (EDUCON).

[11]  Michael S. Horn,et al.  Defining Computational Thinking for Mathematics and Science Classrooms , 2016 .

[12]  Allan Fisher,et al.  Unlocking the Clubhouse : Women in Computing by Allan Fisher , 2015 .

[13]  Brigid Barron Interest and Self-Sustained Learning as Catalysts of Development: A Learning Ecology Perspective , 2006, Human Development.

[14]  Taylor Martin,et al.  Using Learning Analytics to Understand the Learning Pathways of Novice Programmers , 2013 .

[15]  Andrea A. diSessa,et al.  Changing Minds: Computers, Learning, and Literacy , 2000 .

[16]  Yuning Xu,et al.  Principled Assessment of Student Learning in High School Computer Science , 2017, ICER.

[17]  Shuchi Grover,et al.  Computational Thinking in K–12 , 2013 .

[18]  Jeannette M. Wing An introduction to computer science for non-majors using principles of computation , 2007, SIGCSE.

[19]  Shuchi Grover,et al.  Assessing Algorithmic and Computational Thinking in K-12: Lessons from a Middle School Classroom , 2017, Emerging Research, Practice, and Policy on Computational Thinking.

[20]  Michael S. Horn,et al.  Fostering computational literacy in science classrooms , 2014, CACM.

[21]  Caitlin K. Martin,et al.  Digital youth divas: A program model for increasing knowledge, confidence, and perceptions of fit in stem amongst black and brown middle school girls , 2017 .

[22]  Beth Simon,et al.  Evaluating a new exam question: Parsons problems , 2008, ICER '08.

[23]  Robert J. Mislevy,et al.  Implications of Evidence‐Centered Design for Educational Testing , 2007 .