The Sustainable Development Goals (SDGs) deliver a concept aimed at addressing social, economic, and environmental challenges that require collaborative efforts from everyone. The actions often involve conflicts of interest between businesses, governments, social organizations, and citizens. This study develops an inquiry-based learning system aiming to illustrate SDGs issues. Students play different roles and simulate future social scenarios based on their positions and action decisions. This assists students in understanding the concepts of sustainability.

The Internet of Things (IoT) technology has found widespread application in various facets of daily life, including education. Through the integration of IoT technology and authentic open data into educational materials, students can engage in more interactions and develop a sense of participation. This, in turn, enhances their learning interests and motivation. Additionally, students can gain a more lifelike and tangible learning encounter in the classroom, particularly through scenario-based gaming. This research endeavors to utilize the Sustainable Development Goals (SDGs) as content for the creation of IoT-integrated classroom games. These games aim to immerse participants in the intricate web of social and environmental conflicts. Employing an exploratory learning approach, the goal is to augment students' awareness of SDG issues and cultivate multiple representation literacies.

The inquiry-based learning model is an instructional approach tailored to students' exploration of both the natural world and society. By integrating prominent Sustainable Development Goals (SDGs) and leveraging open data, this approach nurtures students' scientific literacy and data analysis proficiencies. In this context, the current study devised an online inquiry learning system named , enabling students to engage with data and independently delve into socioscientific issues through an open inquiry learning model. The findings underscore that students exhibited a high level of immersion throughout the activity, along with adept data collection and summarization skills.

We formulate the Huffman decoding as a root-solving problem so that powerful numerical techniques such as the Newton method and the bisection method are employed for solution. The sectioning technique that narrows the searching scope for solution is further proposed for increasing the decoding speed. The numerical decoder is fast and memory efficient; it is also simple to realize and suitable for integrated circuit implementation.