Educational sensor-based visual programming environments (VPEs) tend to focus on directly connecting input and output sources. However, limited educational tools are designed to expose novice programmers to basic preprocessing techniques often needed to convert raw sensor data into interpretable commands. This paper presents our preliminary design process for LITI, a VPE designed to expose students to basic processing techniques used for time-series data analysis. We leveraged an iterative design process that began with focus group sessions involving local high school teachers and students. Based on educators' and students' feedback, LITI was designed to reinforce graphing and data processing concepts used in physiological computing. Afterward, we conducted usability studies with high school students in grades 10 - 12. Results from our initial user studies suggest that LITI may increase students' physiological computing self-efficacy.

Computer science (CS) has been a growing and increasingly lucrative field for some time. The demand of job applicants in this field, especially in industry, are high. Yet, the supply of CS candidates to fill these positions are low. One notable reason for this phenomenon is based on the high dropout rate of majors as they matriculate through a CS curriculum. Another reason is their failure to showcase the appropriate skill-sets and related expectations needed as candidates for tech-based job opportunities. When emphasizing the latter reason, it is important to examine the current educational practices that may influence such discrepancies as students matriculate through a CS curriculum. This extended abstract discusses one way to address this discrepancy by exploring the impact of exposing early CS majors to coding interview practices in the form of whiteboard problem solving. A virtual assessment was conducted on 30 CS students enrolled in one of two different intro level computer courses at an institution in the mid-Atlantic region of the United States. The results of this assessment revealed that students mostly struggled with their ability to conceptualize a given problem in order to apply the appropriate concepts to solve it effectively.

Due to the increased demand for computer scientists in the, the importance to improve the retention rate of CS majors who could potentially fill such positions has been ongoing. Literature has produced many efforts for increasing the engagement of CS majors in the field while also exploring ways to improve their ability to develop the ideal skill sets for success. In such efforts, our research explores the impact of visual and/or command-line based programming editors and their ability to shape the students' mental model as they learn to program. This abstract discusses a "think-aloud" protocol assessment that was conducted on two entry level programming courses at a university in the United States during the 2018-2019 school year. The objective of this assessment was to determine whether Repl.IT, a web-based IDE, and Cygwin/Nano Editor, a command line-based tool, impacted student performance while being used for programming. Our preliminary results showed that 41% of the students using Repl.IT completed the assigned task for the assessment, while 53% of the students using the Cygwin/Nano editor did the same. The results concerning assignment incompletion revealed that students who did not complete their assignment and used Repl.IT did so because of assignment complexity and programming language difficulty, whereas assignment complexity and tool usage difficulty lead to assignment incompletion for students using Cygwin/Nano. This assessment also revealed that Repl.IT students exhibited a higher comfort, confidence, and fondness for using their editor than the Cygwin/Nano students.