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Background. There are long-held concerns about how graduate research programs prepare engineering Ph.D. students for professional practice. Suitable instruments are lacking to effectively assess how research experiences contribute to the success of graduate students becoming professionals. Purpose. The purpose of this work is to examine evidence of internal reliability and validity of using the Research Experiences Instrument (REI) scores as a measure of engineering Ph.D. students’ professional practice opportunities in their research experiences. Method. REI was constructed using an ontological framework. REI was administered twice to engineering Ph.D. students, once to a single university (n = 236) and once to multi-universities (n = 215). Psychometric analyses were conducted related to validity and reliability evidence, including exploratory and confirmatory factor analyses, and group score comparisons between genders, race/ethnicity, and engineering disciplines. Results. Results of both factor analyses aligned with the theoretical five-factor structure, with a second-order Opportunity factor. Mean scores were the same between women and men, and for three engineering disciplines, but significantly lower for racially/ethnically minoritized groups. Factor scores indicate that students often lack opportunities to engage with professionals, a likely cause of students’ professional practice struggles. Conclusions. Evidence of validity has been provided to justify the use of REI to assess the unique research experiences of engineering Ph.D. students as these relate to preparedness for professional practice. REI scores can be used for gender and race/ethnicity comparisons and are generalizable across engineering disciplines. Where students’ REI scores show a lack of opportunities, remedial strategies can be implemented.

There is a large variation in background and purpose of massive open online course (MOOC) learners. To improve the overall MOOC learning experience, it is important to identify which MOOC characteristics are most important for learners. For this purpose, in this article, we analyzed about 150 000 open-ended learner responses from 810 MOOCs to three postcourse survey questions about their learning experience: (Q1) What was your most favorite part and why? (Q2) What your least favorite part and why? (Q3) How could the course be improved? We used the latent Dirichlet allocation topic model to identify prominent topics present in learner responses to each question. We determined the theme of each identified topic through qualitative analysis. Our results show that the following aspects of MOOCs can significantly impact the learning experience: quality of course content, accurate description of prerequisites and required time commitment in course syllabus, quality of assessment and feedback, meaningful interaction with peers and educators, engaging instructor and videos, accessibility of learning materials, and usability of platform.

This study investigates the relationship between two related computational thinking practices: data practices and computational problem-solving practices in acquiring related computational thinking practices during a first-year undergraduate engineering course. While computational thinking theory is still developing, empirical studies can help further understand how students demonstrate this knowledge and their progression in attaining the practices. Therefore, with this empirical study, the following questions are addressed. RQ1: What are the differences in students’ computational thinking practices at the beginning of an undergraduate introductory programming course? RQ 2: How do these differences correspond to the acquisition of more advanced computational thinking practices? The use of a descriptive non-experimental design that aims to understand the correlation between practices related to data and computational problem-solving is presented. A machine learning technique is employed, utilizing historical data from introductory programming for a problem-solving course with more than 1000 first-year engineering students. After identifying groups of students defining different profiles, data from posterior performance in more advanced programming topics were descriptively analyzed. This study supports the characterization of four different student profiles demonstrating differences in their performance at the beginning of the semester. From these four profiles, two of them show a subsequent differential progression besides their similarity at the beginning of the semester. In this particular case, troubleshooting and debugging appear as a relevant competency when distinguishing these two learners’ groups. These findings suggest that previous knowledge or exposure to different practices can result in different progressions of more complex computational practices, emphasizing the relevance of troubleshooting and debugging as a practice required for a successful and timely progression on the acquisition of other computational thinking practices.

This research-to-practice WIP (Work In Progress) presents the design and assessment of online Model-Based Systems Engineering (MBSE) modules for practicing engineers using social constructivism as a theoretical framework. Despite many advantages of MBSE, experts in this field are still scarce in the current engineering workforce. To address this need, an online module that will be deployed in the summer of 2020 targets practicing engineers as its learners to equip them with MBSE-related knowledge and skills. In industry, teams working on MBSE-related projects usually collaborate across multidisciplinary units. Therefore, social interaction plays an integral role in MBSE training programs. To understand how group interaction could foster learning in online engineering modules, we apply social constructivism as a theoretical framework to engage learners in meaningful interactions and facilitate the acquisition and application of knowledge. The modules will utilize deep-level, student-centered, small-group discussions, and peer review between student groups as forms of social learning in authentic engineering assignments. The assessment of the modules will focus on the effectiveness of social learning in promoting the mastery and application of content knowledge.

This research Work-In-Progress presents a survey of advanced learners’ motivation in highly-technical advanced engineering MOOCs. Advanced engineering courses as MOOCs are increasingly prevalent in graduate and professional learning and are gaining importance for credentialing and accredited degrees. However, these courses are open to the public as well as formal learners, making it difficult to generalize experiences for all. To understand what prevents advanced learners from reaching their goals and to better support them in meeting goals, there is a need for more sensitive tools to measure motivation. We have revised the Expectancy-Value-Cost scale and examined its functioning on pilot data to begin looking at validity evidence for using the revised scale with professional engineers. We analyze motivations, intentions, and course ratings of learners from two online MOOCs who are enrolled in formal degree programs at a four-year institution, learners completing a MOOC master’s degree, and independent learners. We also perform bivariate correlation of motivation items to test the performance of the instrument. Preliminary results show high motivation for all learner groups, but greater differences between independent and formal learners, with formal learners reporting a wider range of costs.

Assessment of students‘ critical thinking and problem solving in engineering is a real challenge for classroom teachers and researchers. Yet, students demonstrate evidence of learning through multiple means, including written reflections. The purpose of this study was to explore how students in grades 5 and 7 reflect on what they had learned about engineering design practices in comparison to their previous understandings. The researchers applied qualitative content analysis to analyze student responses to engineering notebook prompts that asked students to reflect on their understanding of the problem and how to design solutions. Data were collected from two classrooms (n = 47) that had implemented integrated STEM curricula. The results of this study indicate that students were able to reflect meaningfully on their engineering practices and how their understanding of what it meant to design had changed. The notebooks provided an opportunity for students to demonstrate evidence of their learning through reflection on their own design practices. The findings suggest that teachers and curriculum developers can use reflection as a means to help students connect their own learning to informed design practices, which may help students move toward being independent informed designers. Future research should consider how teachers can use notebooks to provide feedback on engineering practices.

Although engineering design is dependent upon the use of science and mathematics, the actual prototype, model, or solution that pre-college students generate can be accomplished without the students explicitly using scientific or mathematical concepts. It is therefore important to explore how students apply science and mathematics concepts when engaged in a curriculum that was purposefully developed to foster student understanding of standards-based content. The purpose of this research is to apply the case study method to explore the following research question: How do middle school students use scientific and mathematical concepts that were explored during the problem scoping lessons of an engineering design-based STEM integration unit to generate ideas and make design decisions? Researchers collected data from one 7th-grade team during an integrated STEM unit and applied qualitative content analysis methods to examine the data. The findings show that students meaningfully used science and mathematics concepts taught within the unit to defend their engineering design ideas/decisions. It also revealed incomplete understanding of certain concepts. Engineering design can provide opportunities for teachers to assess how well students have learned scientific and mathematical concepts, provided that the curricula are carefully designed to prompt students‘ use of content to make design decisions.