Exploring Trends in Middle School Students\u27 Computational Thinking in the Online Scratch Community: A Pilot Study

Teaching computational thinking has been a focus of recent efforts to broaden the reach of computer science (CS) education for today’s students who live and work in a world that is heavily influenced by computing principles. Computational thinking (CT) essentially means thinking like a computer scientist by using principles and concepts learned in CS as part of our daily lives. Not only is CT essential for the development of computer applications, but it can also be used to support problem solving across all disciplines. Computational thinking involves solving problems by drawing from skills fundamental to CS such as decomposition, pattern recognition, abstraction, and algorithm design. The present study examined how Dr. Scratch, a CT assessment tool, functions as an assessment for computational thinking. This study compared strengths and weaknesses of the CT skills of 360 seventh- and eighth-grade students who were engaged in a Scratch programming environment through the use of Dr. Scratch. The data were collected from a publicly available dataset available on the Scratch website. The Mann-Whitney U analysis revealed that there were specific similarities and differences between the seventh- and eighth-grade CT skills. The findings also highlight affordances and constraints of Dr. Scratch as a CT tool and address the challenges of analyzing Scratch projects from young Scratch learners. Recommendations are offered to researchers and educators about how they might use Scratch data to help improve students’ CT skills

INVESTIGATING FACTORS PREDICTING EFFECTIVE LEARNING IN A CS PROFESSIONAL DEVELOPMENT PROGRAM FOR K-12 TEACHERS

The demand for K-12 Computer Science (CS) education is growing and there is not an adequate number of educators to match the demand. Comprehensive research was carried out to investigate and understand the influence of a summer two-week professional development (PD) program on teachers’ CS content and pedagogical knowledge, their confidence in such knowledge, their interest in and perceived value of CS, and the factors influencing such impacts. Two courses designed to train K-12 teachers to teach CS, focusing on both concepts and pedagogy skills were taught over two separate summers to two separate cohorts of teachers. Statistical and SWOT analyses were then performed using measures such as attitudinal surveys and knowledge assessments. Findings showed the PD program had a significant impact on the teachers, there was a positive correlation between teachers’ pre-program confidence and knowledge, and additional insights on how to deliver such PD programs more effectively. Results will help inform K-12 CS PD program design. Advisor: Leen-Kiat So

Design and Programming Procces of an Educational Video Game in Primary Education.

The incorporation of new technologies into the field of education has meant a transformation (Gómez-Galán, 2020) and a challenge for teachers. The continuous appearance of applications and technological devices requires teachers committed to their use and in continuous training.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Computational Thinking Skills Indicators in Number Patterns

This research aims to examine a) what computational thinking indicators have been developed by researchers, b) what computational thinking indicators can be used in learning mathematics appropriately, and c) how to describe the development of student computational thinking indicators from the answers of computational thinking tests. This research is a qualitative descriptive study through a process of collecting data from literature reviews, integrated computational thinking math tests, and interviews. Data collection instruments used research notes, interview sheets, and CT question sheets. The results showed that a) 20 computational thinking indicators had been studied by researchers, b) computational thinking indicators that could be used in learning mathematics include problem decomposition, abstraction, pattern recognition, procedural algorithms, and generalizations, and c) From the student answers, five proposed computational thinking indicators can be developed even though they were not perfect. The general implication of this research is that there are five indicators of computational thinking skills that can be used in mathematics learning, specifically in number patterns, which include problem decomposition, abstraction, pattern recognition, pattern recognition, procedural algorithm, and generalization. The researchers developed all five computational thinking skills indicators in the instructional designs of not only the number pattern concept but also combination, geometry, combinatorics, etc