Concept inventories are diagnostic instruments designed to assess student understanding and identify common misconceptions in a specific domain or discipline. They consist of multiple-choice questions or tasks that target key concepts and principles in the subject matter. The ECCD was developed to diagnose student misconceptions of electric concepts like power, energy, and potential difference. For concept inventories to be effective in measuring misconceptions, the items on the test must possess two essential qualities: validity and reliability. We administered the ECCD to 270 undergraduate engineering students in the summer and fall of 2023 and the test items are examined using the classical test theory framework. Results from the analysis show that most of the items on the test perform well in terms of item difficulty, item discrimination, and reliability. Findings from this work-in-progress analysis pointed to a few items that might need revision or be discarded on the final test. The implication of these findings is also reported.

This work-in-progress research paper investigates students' cognitive engagement in collaborative virtual reality (VR) statics activities. The use of VR in engineering education is increasing with the advance in technology. To maximize the affordance of the VR for engineering education, it is important to understand how active learning enfolds in the VR environment since the level of student engagement during active learning is a vital indicator for the effectiveness of the learning environment. Using content analysis, this study investigates the modes of cognitive engagement of students working collaboratively to solve engineering problems in a VR learning environment. The video-recorded collaboration and the transcribed verbal interaction of the students in the VR learning environment were analyzed based on the Interactive-Constructive-Active-Passive (ICAP) framework. The analysis coded the patterns of the observed cognitive engagement based on the video recording and transcripts of the groups' conversation at each phase of the task. The analysis revealed that the active and constructive modes dominated the students' conversation while the interactive mode was the least observed mode of cognitive engagement during the task. The implications of the findings for further research and practice are discussed.

Students' misconceptions of electric circuits are common and are well documented in the literature. Misconceptions are students' conceptions that are against the accepted scientifically correct explanations, however, held tenaciously. Research has shown that misconceptions act as barriers to learning science and engineering concepts. In order to remediate students' misconceptions, there is a need for their accurate detection and measurement. While there have been concept inventories developed to measure students' misconceptions in electric circuits, most of them lack the ability to discriminate between students who lack prior knowledge and those who have ingrained misconceptions. Hence, the need for the development of the Electric Circuits Concept Diagnostic (ECCD). In this study, 30 items designed to test students' conceptual understanding of basic electric circuit concepts (such as Voltmeter and Ammeter, Nodes and Loops, Sequential Reasoning, Voltage and Potential Difference etc.) were administered to participants via Qualtrics Survey Software. The test has three tiers: multiple-choice content tier (O), open-ended reason tier (C), and multiple-choice confidence level tier(H). Data from 35 engineering undergraduate students who took part in the pilot test were analyzed, and the initial analysis and results of the data generated during the summer of 2022 show students' clusters based on their responses to the items on ECCD. This work-in-progress reports these results and outlines the next phase of the project.

Academic belonging is an important construct essential for student success in engineering. It involves a sense of connectedness, acceptance, and identification within the learners' academic environment. Students may disengage and ultimately drop out of their program of study where the sense of academic belonging is lacking. This work in progress bridges the gap by examining the correlates of academic belonging in order to understand the processes by which graduate engineering students develop a sense of belonging within their chosen programs. 227 graduate students from six universities in the United States completed the Postsecondary Student Engagement (PosSE) survey. Using Pearson Correlation, we evaluated the relationships between major valuing, achievement striving, major satisfaction, peer interaction, positive faculty relations, passion, perseverance, and academic belonging. The results show that major satisfaction has a positive strong relationship with academic belonging, while major valuing and positive faculty relations have a significant positive medium relationship with academic belonging. It was noted that achievement striving, and peer interaction has small positive but significant relationships with academic belonging. The theoretical and practical implications of this study will be discussed.

Many students have misconceptions about fundamental engineering concepts that interfere with their ability to accurately grasp more advanced engineering concepts. Misconceptions are particularly ubiquitous in counterintuitive and complex subjects, such as electric circuits. Although several efforts have been directed at diagnosing students' misconceptions of electric circuits and designing instructional approaches for remediating identified misconceptions, there has been no effort to systematically synthesize and summarized the literature on students' misconceptions of electricity and electric circuit concepts. As such, the purpose of this study, which is a work in progress, is to conduct a systematic literature review of empirical studies that have examined students' misconceptions about electric circuits and electricity concepts. A comprehensive literature search returned 3365 articles, out of which 93 passed the inclusion and exclusion criteria. We randomly selected 17 of the included articles for this work in progress study. The results of the analysis of the coding show that most of the studies were published between 2011 and 2021, and that about 47% of them focused on college students. Furthermore, the result reveals that most students still believe that battery is a source of constant current. Other results and the implications for this study's findings will be discussed.

This work in progress investigates the role of self-efficacy in mediating the effect of mastery and performance goals on student achievement. The role of achievement goals on academic achievement has received considerable empirical support. However, the mediating role of self-efficacy belief has not been explored within the engineering context. One hundred and seventy-one undergraduate students in the college of engineering in a public university in the United States completed questionnaires that assessed their goal orientations, and self-efficacy belief for learning and performance. The result of the structural equation modeling conducted in MPLUS shows a good fit: Chi-square = 206.76(df=95), TLI=.90, CFI=.92, RMSEA=.08, SRMR=0.06. Both performance and mastery goals significantly predicted self-efficacy for learning, and performance goal is both direct and indirect predictor of performance score through self-efficacy. The theoretical, practical implications and future direction of this study are discussed.

This research full paper examines the relationship between achievement goal orientations, task value, self-efficacy for learning, and students' achievement. Participants were 171 undergraduate students from the college of engineering. The students completed measures that assessed achievement goal orientations, self-efficacy for learning performance, and task value. The results show that while mastery, performance approach, self-efficacy, and task value correlate significantly with the students' achievement, only self-efficacy for learning performance significantly predicts students' achievement when combined with prior knowledge and absence in a complete hierarchical regression model. The findings highlight the impact of objective measures (class attendance) on student achievement scores relative to their task or self-efficacy beliefs, and achievement goal orientations.