In this Work In Progress (WIP) research paper we explore the experiences of Latina engineering students during their industry placements, focusing on the factors that contribute to their success or hinder their progress. Latina engineering students face unique challenges when navigating industry placements, as they often confront issues related to gender, race, and cultural background. Using a qualitative research approach, semi-structured interviews were conducted with a group of 12 Latina engineering students who had completed industry placements in their undergraduate studies. The data was analyzed using Illeris' Model of Learning as a theoretical framework. Illeris postulated that learning happens on an individual dimension yet is always set in a social context. We used a combination of deductive and inductive coding to analyze the transcripts. The participants shared their thoughts and reflections on their experiences, discussing the challenges they faced, the support they received, and the value they believed they brought to the organization they worked for. The findings reveal that Latina engineering students report learning on the individual, cognitive, and affective dimensions of the Illeris' model. Yet they often encounter interactions that communicate stereotypes and biases in the workplace, which lead to some reporting feelings of isolation and imposter syndrome as the work cultures are not always welcoming to this group of students. The students highlight the importance of mentorship, networking, and self-advocacy in overcoming these barriers and thriving in their industry placements. Moreover, the study sheds light on the role of cultural background and identity in shaping the experiences of Latina engineering students in industry placements. Participants discussed how their heritage and values influenced their interactions with colleagues and supervisors, as well as their approach to problem-solving and teamwork. Overall, this research contributes to a better understanding of the unique challenges and opportunities faced by Latina engineering students in industry placements, offering insights for educators, employers, and policymakers on how to support and empower this underrepresented group in the engineering workforce.

This research paper aimed to evaluate the effectiveness of AI bots in simulating human subjects for research purposes. In recent years, the use of artificial intelligence (AI) in education has gained significant attention. While most approaches explore possibilities for teaching and learning, the possibilities for human subject research have been under-explored. By utilizing AI bots as a tool for data collection and analysis, researchers can potentially reduce costs, increase efficiency, and improve overall accuracy in their studies. This project focused on replicating a traditional qualitative research study on the topic of “humility in engineering“ with real human subjects in a simulated study using several publicly available generative AI tools - ChatGPT, Gemini, DebateAI, MasterDebater - to evaluate the effectiveness of AI bots as simulators of human subject research. The project assessed the “personalities“ and response patterns of AI tools leading to ethical implications of using AI bots as research simulators. In addition to evaluating the effectiveness and ethical implications of AI bots as simulators of human subject research, the project also explored the potential benefits and limitations of this approach. Overall, this project represents an important step towards understanding the role of AI bots in research and their potential impact on the engineering education research community. By evaluating the use of AI bots as simulators of human subject research, researchers can gain valuable insights into the benefits, limitations, and ethical considerations of this approach. Ultimately, this project seeks to advance the field of research methodology and contribute to the ongoing dialogue surrounding the use of AI in scientific studies.

This full paper reports on research into feedback perceptions. In recent years enrolment in Engineering Education went up and the number of international students increased, leading to larger classes and greater variety in prior education within the classroom. Literature review reveals large classes lead to fewer opportunities for students to interact with their teachers and receive high quality formative feedback. Feedback helps students to reflect on the quality of their work. Engineering Education is characterized by overloaded, heavily scaffolded curricula, and learning activities; it is paramount to provide students with feedback they perceive as useful and meaningful. The larger diversity in the classroom means there is a larger diversity in feedback perceptions that needs to be taken into account when providing feedback. In this work we present the preliminary outcomes of a study that was informed by the following research question: How do first-year bachelor students perceive feedback? We performed multiple semistructured interviews with 17 first-year students in computer science during their first semester, and aimed to collect data on the students' lived experiences and the spread of student realities, using a phenomenological approach. The preliminary results show that there are many essential aspects that influence students' feedback perceptions. Study shows that such aspects as large class and relationships with teacher play very important role in developing certain feedback perceptions amongst students.

This work-in-progress reports on a project to establish differences between STEM education, and specifically Engineering Education, and other education fields/disciplines based on empirical observations. In this study we report on first steps towards a literature overview of such differences and on the development of an analytical framework to analyze the publications.

This workshop invites discussion about peer review of journal manuscripts in the field of engineering education. The aim is to generate advice for reviewers on how to make effective reviews, which can help editors make appropriate decisions and support authors in improving their manuscripts. The workshop is facilitated by editors of three leading engineering education journals.