Computer Science (CS) Unplugged activities are designed to engage students with CS concepts. It is an active learning approach combining physical interaction with visual representation. This research article investigates the impact of CS Unplugged on students' understanding of the bubble sort algorithm. Algorithm visualization, traditionally…

This study examines the effects of plugged and unplugged programming tools used in algorithm teaching at the K-12 level on student computational thinking skills and to determine whether gender is a factor in this process. The study group was designed with a control group pre-test--post-test; quasi-experimental model, that consisted of 109 students…

In the context of our rapidly digitizing society, computational thinking stands out as an essential attribute for cultivating aptitude and expertise. Through the prism of computational thinking, learners are more adeptly positioned to dissect and navigate real-world challenges, poising them effectively to meet the exigencies of future societal…

This study sought to compare the effectiveness of teaching with manipulatives versus algorithms and procedures. Assessment data were collected before instruction, after instruction with algorithms and procedures, and after instruction with modeling and manipulatives. Data were collected from 113 students from the 5th, 6th, and 7th grades within…

Infrared (IR) technologies have been universally acknowledged as a valuable pedagogical tool for exploring novel and abstract scientific subjects in science education. This study explores the roles of IR images played in middle school students' Evidence-based Reasoning (EBR) process in support of the understanding of the heat radiation process.…

This study examined whether socially shared regulation of learning (SSRL) enhances students' algorithmic thinking performance, promotes learning participation and improves students' learning attitudes through game-based collaborative learning. The students learned algorithmic knowledge and completed programing tasks using Kodu, a new visual…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…