STEAM (Science, Technology, Engineering, Arts & Mathematics) integrated instructional approach not only increases students' interest in learning hard science but also enhances their understanding in arts. We proposed a five-step STEAM interdisciplinary-integrated instructional model to teach student programming, which are: choosing an art example, inspiring creativity, hands-on design, programming implementation, optimizing and sharing. We used the model to design materials to teach middle school student modular programming with the Mandala Art design. The results showed that the proposed STEAM model promoted students' learning, enhanced their understanding of art concepts, and inspired students' thinking.

In this study, we applied STEM approach to teach high school students Internet of Things (IoT) and Artificial Intelligence (AI) concepts with an air quality example. The learning activities include assembling IoT devices for air quality detection, connecting to the MQTT app for data visualization, and applying raw data to build an AI model using TensorFlow to predict air quality. The results showed that the STEM (Science, Technology, Mathematics, and Technology) approach helped students learn data transmission in IoT architecture, modeling process of AI, and enhanced students' motivation in learning.

In this study, we developed an instructional module consisting of four units to help high school students understand the 4V concepts of big data by exploring air pollution. The instructional module enabled students to explore air quality data on specific websites, and asked students to create a "calendar heat map" using open dataset. We taught the module in a high school class and the results demonstrated that students gained knowledge about big data, and became more aware of the impact of air pollution in their lives.

We have developed a quantitative tool for assessing senior high school students' computational thinking skills and administered it in the Taipei metropolitan area of Taiwan. Our CT test is language/tool/knowledge-independent and focuses on four key CT concepts: decomposition, data representation, algorithms, and pattern generalization. Our paper outlines the development process of the CT test, including its constructs, reliability, and validity, and discusses its educational implications for computing courses. This CT test provides a valuable resource for computing teachers who wish to assess their students' CT abilities and tailor their teaching methods accordingly.

In this study we developed three hands-on activities to teach high school students computational thinking (CT) and, specifically, the decomposition skills. The activities were designed to enable students to solve problems by using application tools. The computer science concepts utilized in the activities included binary search, quick sort and iteration. We evaluated the effect of the activities utilizing a post-activity questionnaire, a post-test, students' worksheets, and semi-structured interviews with the participating students. The results indicated that the hands-on activities developed in this study improved students' CT ability.