Reflecting on Computational Thinking Studies for High School Education

Berpikir komputasional telah diakui sebagai suatu kebutuhan dalam menyelesaikan masalah yang kompleks. Beberapa penelitian telah dilakukan untuk memperkenalkan keterampilan ini ke semua tingkat pendidikan. Penelitian ini bertujuan untuk meninjau penelitian tentang berpikir komputasi pada tingkat sekolah menengah. Khususnya, penelitian ini mengkaji domain penelitian, mengidentifikasi metode-metode untuk memperkenalkan berpikir komputasional, serta konsep-konsep berpikir komputasional yang diajarkan kepada pelajar. Tinjauan literatur sistematik dilakukan untuk mencapai tujuan tersebut. Hasil penelitian menunjukkan: penelitian berpikir komputasional mencakup kajian teori, pengembangan kurikulum, pengukuran, dan pengembangan alat. Kajian teori ditujukan untuk memformulasikan konsep. Selain keterampilan teknis, soft-skills telah dinyatakan sebagai elemen berpikir komputasional. Namun, perhatian untuk melibatkan soft-skills dalam penelitian masih kurang. Sebagian besar penelitian difokuskan pada integrasi berpikir komptasional ke dalam kurikulum. Coding menjadi metode yang paling banyak digunakan untuk mengajarkan berpikir komputasional. Sehingga, algorithmic thinking dan abstraction muncul sebagai keterampilan yang paling sering diajarkan atau diukur. Akhirnya, penelitian ini menggarisbawahi adanya kesenjangan untuk dikaji lebih lanjut yaitu berkaitan dengan pengukuran keterampilan berpikir komputasional dan untuk menyertakan soft-skills pada penelitian berpikir komputasional.   Kata Kunci—Berpikir komputasional, Sekolah menengah, Penyelesaian masala

Including neurodiversity in computational thinking

IntroductionThe foundational practices of Computational Thinking (CT) present an interesting overlap with neurodiversity, specifically with differences in executive function (EF). An analysis of CT teaching and learning materials designed for differentiation and support of EF show promise to reveal problem-solving strengths of neurodivergent learners.MethodsTo examine this potential, studies were conducted using a computer-supported, inclusive, and highly interactive learning program named INFACT that was designed with the hypothesis that all students, including neurodivergent learners, will excel in problem solving when it is structured through a variety of CT activities (including games, puzzles, robotics, coding, and physical activities) and supported with EF scaffolds. The INFACT materials were used in 12 treatment classrooms in grades 3–5 for at least 10  h of implementation. Pre-post assessments of CT were administered to treatment classes as well as 12 comparison classes that used 10  h of other CT teaching and learning materials. EF screeners were also used with all classes to disaggregate student results by quartile of EF.FindingsStudents using INFACT materials showed a significant improvement in CT learning as compared to comparison classes. Students with EF scores in the lower third of the sample showed the greatest improvement.DiscussionThis study shows promising evidence that differentiated activities with EF scaffolds situated across several contexts (e.g., games, puzzles, physical activities, robotics, coding) promote effective CT learning in grades 3–5