Computational Thinking as an Emergent Learning Trajectory of Mathematics

n the 21st century, the skills of computational thinking complement those of traditional math teaching. In order to gain the knowledge required to teach these skills, a cohort of math teachers participated in an in-service training scheme conducted as a massive open online course (MOOC). This paper analyses the success of this training scheme and uses the results of the study to focus on the skills of computational thinking, and to explore how math teachers expect to integrate computing into the K-12 math syllabus. The coursework and feedback from the MOOC course indicate that they readily associate computational thinking with problem solving in math. In addition, some of the teachers are inspired by the new opportunities to be creative in their teaching. However, the set of programming concepts they refer to in their essays is insubstantial and unfocused, so these concepts are consolidated here to form a hypothetical learning trajectory for computational thinking.Peer reviewe

PENGEMBANGAN PERANGKAT PEMBELAJARAN MODEL SSCS DENGAN PENDEKATAN RME DAN PENGARUHNYA TERHADAP KEMAMPUAN BERPIKIR KOMPUTASIONAL

  This study aims to develop a mathematics learning tool consisting of a Learning Implementation Plan (RPP), Student Worksheet (LKS), and a Computational Thinking Test (CT Test) using the Search, Solve, Create, and Share (SSCS) learning model with a Realistic approach. Mathematics Education (RME) which is valid, practical and effective and examines its effect on the computational thinking ability of junior high school students. This research combines development research (R&D) and experimental research. Data collection techniques in this study used interviews, observation of student activities, observation of the implementation of learning devices, student response questionnaires, and learning outcomes tests in the form of CT tests. The results showed that the learning tools met the criteria of being valid, practical, and effective. The validity coefficients for lesson plans, worksheets, and CT tests were 3.80, respectively; 3.80; and 3.81. The value of practicality seen from the results of observations of the implementation of learning devices is in the very practical category with a percentage of 98%. The value of the effectiveness of learning tools shows that 92% of students are active, 98% of students respond positively to learning, and 77% of students complete learning. Based on the t-test on the results of experimental research, it was found that the SSCS model learning device with the RME approach had a significant effect on students' computational thinking abilities

From Legos and Logos to Lambda: A Hypothetical Learning Trajectory for Computational Thinking

This thesis utilizes design-based research to examine the integration of computational thinking and computer science into the Finnish elementary mathematics syllabus. Although its focus is on elementary mathematics, its scope includes the perspectives of students, teachers and curriculum planners at all levels of the Finnish school curriculum. The studied artifacts are the 2014 Finnish National Curriculum and respective learning solutions for computer science education. The design-based research (DBR) mandates educators, developers and researchers to be involved in the cyclic development of these learning solutions. Much of the work is based on an in-service training MOOC for Finnish mathematics teachers, which was developed in close operation with the instructors and researchers. During the study period, the MOOC has been through several iterative design cycles, while the enactment and analysis stages of the 2014 Finnish National Curriculum are still proceeding.The original contributions of this thesis lie in the proposed model for teaching computational thinking (CT), and the clarification of the most crucial concepts in computer science (CS) and their integration into a school mathematics syllabus. The CT model comprises the successive phases of abstraction, automation and analysis interleaved with the threads of algorithmic and logical thinking as well as creativity. Abstraction implies modeling and dividing the problem into smaller sub-problems, and automation making the actual implementation. Preferably, the process iterates in cycles, i.e., the analysis feeds back such data that assists in optimizing and evaluating the efficiency and elegance of the solution. Thus, the process largely resembles the DBR design cycles. Test-driven development is also recommended in order to instill good coding practices.The CS fundamentals are function, variable, and type. In addition, the control flow of execution necessitates control structures, such as selection and iteration. These structures are positioned in the learning trajectories of the corresponding mathematics syllabus areas of algebra, arithmetic, or geometry. During the transition phase to the new syllabus, in-service mathematics teachers can utilize their prior mathematical knowledge to reap the benefits of ‘near transfer’. Successful transfer requires close conceptual analogies, such as those that exist between algebra and the functional programming paradigm.However, the integration with mathematics and the utilization of the functional paradigm are far from being the only approaches to teaching computing, and it might turn out that they are perhaps too exclusive. Instead of the grounded mathematics metaphor, computing may be perceived as basic literacy for the 21st century, and as such it could be taught as a separate subject in its own right