This work in progress research paper presents findings from a survey conducted about ChatGPT that was circulated in both spring 2023 and 2024 at an R1 engineering university, with responses from faculty doubling from the first to the second year. As Generative Artificial Intelligence (GAI) and online tools continue to reshape engineering education, it can be difficult for educators to keep up. Emerging technologies like ChatGPT by OpenAI have spurred conversations across academia, and questions about its capabilities and potential uses in the classroom have led to countless ethical discussions about academic integrity and how educators need to adapt to rapid growth in technological advancement. Understanding faculty perceptions of emerging technologies like ChatGPT by OpenAI becomes an essential part of embracing these advancements. This study aims to answer the following research question: What are the current perceptions of faculty towards emerging technologies like ChatGPT by OpenAI in engineering education, as assessed by the Technology Acceptance Model (TAM), and what factors influence their attitudes towards its potential integration into engineering curricula? The TAM assesses survey data by examining responses related to perceived usefulness and ease of use of a technology. It analyzes the extent to which these factors influence attitudes towards, and intention to use the technology, thus predicting its acceptance. Applied to the context of this survey instrument developed by the authors we should glean a good understanding of how faculty may have begun to accept the technology of GAI from the initial survey to the most current survey. Preliminary results shed light on faculty familiarity with ChatGPT and their perspectives on its potential utility for student learning as well as their concerns. By examining faculty attitudes towards integrating ChatGPT into engineering curricula, this research contributes to ongoing discussions on the role of GAI in higher education and provides insight into the extent of which educators currently embrace advancements in a technology-enhanced world.

This is a WIP progress paper belongs to innovative practice section. According to Bandura, self-efficacy refers to “beliefs in one's capabilities to organize and execute the courses of action required to produce given attainments.” Self-efficacy plays an essential role in skill development and engineering education. Sketching is a critical skill for engineering students, and it has various benefits, especially in developing spatial visualization skills. Sketching enables students to effectively communicate graphically, represent ideas, and brainstorm ideas, especially in the early design stages. No formal research has been conducted concerning the role of self-efficacy in learning to sketch. An instrument that measures sketching self-efficacy is beneficial for gaining insight into the levels of sketching self-efficacy of engineering students. A sketching self-efficacy instrument was developed for high school students, however it needs revision and validation for use in undergraduate engineering classrooms. This work-in-progress study aims to revise the sketching self-efficacy survey instrument items based on expert feedback to ensure the validity of the instrument's content. We have gathered feedback from nine engineering instructors from various disciplines who are experts in sketching on the items of the current sketching self-efficacy instrument. Our research question is: In what areas do engineering students need to develop self-efficacy in sketching according to engineering instructors, and how do these areas vary across mechanical and industrial engineering disciplines? We conducted five interviews virtually and semi-structured through the Zoom platform. The interview transcripts were anonymized, cleaned, and loaded into qualitative data analysis software, MAXQDA. Qualitative contnet analysis was utilized to analyze the interview data. Based on the interview analysis results, we will discuss the recommended changes to the sketching self-efficacy instrument. Our final study will include psychometric analysis, such as exploratory Factor analysis and Confirmatory factor analysis, to test the instrument's validity for college students.

The Engineer of 2050 requires a multidimensional education that not only incorporates advanced technical knowledge but also emphasizes global competence, growth miudset, and a proactive approach to lifelong learning. This workshop will explore how the DANCE (Designing Adaptations for the Next Changes in Education) model facilitates such development through a structured yet adaptable framework. The model emphasizes the need for faculty to not simply respond to changes but to anticipate and prepare for them, enabling a dynamic and forward-thinking educational environment.

In this work in progress we explain the development of a process or changing the teaching culture at the department of mechanical engineering of Texas A&M. The Strategy is based on addressing (a) development of reflective teachers (b) developing shared vision (c) considering policy and (d) faculty initiated curricular innovations. Teachers were trained in lean startup (incremental innovation) approaches to educational innovation. A community of practice was developed to build trust, share learning from innovations and to develop accountability. A systematic approach is being developed to evaluate the efficacy of this change strategy especially with engaging late adopters and sceptics. Preliminary results indicate that that creating and nurturing a teaching community of practice (a part of a comprehensive change strategy) is very effective in promoting a culture of innovation in teaching.

How innovative are you? High levels of innovativeness are correlated with high-value creation, and today's rapid pace of change requires new skills for lifelong learning, curiosity, innovation, and continuous improvement. To what level can personal innovativeness be improved through curricular innovations and how do we improve students' practical skills for ongoing discovery? Innovation Mind and Skill Sets for Design and Research is a new course that focuses on providing STEM students the broader mind and skill sets that will help them connect their specialized work to the larger system and the society it impacts and effectively experiment, discover, and create value in the highly dynamic and uncertain environment of breakthrough innovation. This paper will discuss the development of the course which Hipwell based on both innovation literature and her own two decades of experience applying and improving innovation business processes with her teams in a fast-paced, high-tech industry. An educational class structure and learning outcomes are developed based upon the theory that innovation is itself a learning process and can be improved through the known learning science concepts of improvement of student metacognition about their innovation process and incorporation of intention and reflection in their learning cycles. Further, the model incorporates literature on teaching system thinking and Transformative Learning Theory for adults. Content is developed that teaches the students practical techniques that scaffold their innovation process and increase their metacognition. Movement up levels of Bloom's Taxonomy and long-term habits are developed through the practice of the innovation process in a team project with expert feedback from an experienced innovation practitioner. Learning is increased through reflection on the process during class presentations. Measurement of student improvement results compared to control design curricula using the Innovator Mindset® Assessment is also discussed.

Understanding the current curricular state of undergraduate engineering program curricula is essential to the growth and evolution of engineering as a discipline. By characterizing various institutions that exist in our nation we can better understand how those programs might be uniquely affecting the training of engineering students. Currently little work has been done to explicitly compare engineering degree program curricula in mechanical, electrical, and civil engineering, but the work that has been done is limited in scope and depth. More importantly, no work as of yet has attempted to examine whether there are significant differences in how minority serving universities might be uniquely preparing their students or if there are innate advantages at more “prestigious”, degree programs of some universities. Understanding the differences between degree programs of universities of varying minority serving levels and university types could bring some insight as to how all universities might better serve diverse student populations on their campuses. This work will examine an assortment of university types that provide mechanical, civil, and electrical engineering program options for their students. These universities span a range of institutional types such as the Morrill Act of 1862 Land Grant institutions, Historically Black College and Universities (HBCUs), Hispanic Serving Institutions (HSIs), and Association of American Universities (AAU) membership universities. This work in progress aims to begin an inquiry into this topic with an ultimate goal of developing a repeatable methodology to assess engineering curricula from the three largest degree granting disciplines of Mechanical, Electrical, and Civil engineering.

A group of engineering educators at Texas A&M University participating in a book club professional development experience. This book club has listened to and discussed several books and movies including the books “Uncomfortable Conversations With a Black Man” by Emmanuel Acho, “Pedagogy of the Oppressed” by Paulo Friere, “Inclusive Conversations” by Mary-Frances Winters, and the movies “Picture a Scientist” and “Coded Bias.” Engineering in the academe is at a critical juncture considering the frequency and acceptance of difficult conversations related to society and social justice having a place in the discipline. Historically, Engineering has steered away from uncomfortable difficult conversations, but it is time to shed our old skin of a habitual depoliticization and emerge free from this restriction to develop our next generation of engineers. Not only are these types of discussions and conversations essential to ensure that the disci-pline continues to become more diverse, inclusive, and equitable, but these discussions better prepare engineers to consider societal factors when they ultimately are designing products, services, and tools for society as a whole. Several thousand engineers are graduating from undergraduate programs every year with little to no discussion of social justice in their programs This study will identify the impact participation in this book club has had in professionally developing faculty participants to engage in uncomfortable discussions and how they might have attempted to integrate societal issues into the courses that they teach at Texas A&M University. Interviews were conducted with members of this book club via Zoom and transcribed automatically. Those transcripts were then analyzed using thematic analysis to identify the major recurrent themes amongst participants. This work builds upon a previous publication by the authors that utilized a focus group design paired with a quantitative Likert scale survey to gauge perceptions of the book club itself, but did not focus on how faculty participants were taking this information and experiential learning into their own classrooms This work will expand the researcher's understanding of the impact of this book club to include this concept of classroom integration of societal challenges that often is overlooked by engineering as a discipline.

This Research Work In Progress Paper examines empirical evidence on the impacts of feedback from an intelligent tutoring software on sketching skill development. Sketching is a vital skill for engineering design, but sketching is only taught limitedly in engineering education. Teaching sketching usually involves one-on-one feedback which limits its application in large classrooms. To meet the demands of feedback for sketching instruction, SketchTivity was developed as an intelligent tutoring software. SketchTivity provides immediate personalized feedback on sketching freehand practice. The current study examines the effectiveness of the feedback of SketchTivity by comparing students practicing with the feedback and without. Students were evaluated on their motivation for practicing sketching, the development of their skills, and their perceptions of the software. This work in progress paper examines preliminary analysis in all three of these areas.

Diversity statements are becoming mandatory in increasing numbers of job searches by increasing numbers of institutions. However, how to use diversity statements is seldom discussed with search committee members or persons interviewing the potential candidate. Some institutions, even if required, do not provide guidance or expectation to the use of the statement. Some institutions and/or search committees use diversity statements in a very basic way as tiebreakers. Institutions seeking improved inclusivity and convergent thinking have found that by reading the diversity statement first, higher numbers of traditionally underrepresented candidates are remaining in the pool at each stage of the hiring process [1], [2]. This workshop provides participants with a framework to create and use rubrics to evaluate diversity statements for improved inclusivity.

This panel session combines principles from graduate student socialization and intergenerational mentorship to provide a unique opportunity for early career scholars and pioneers in engineering education to interact face-to-face. Pioneers will serve as panelists and give their personal tips and reflections on networking and mentorship. Session attendees will then meet with the pioneers in a roundtable format, to ask questions, seek advice, and get feedback. This work builds on the National Science Foundation-funded Engineering Education Pioneers Project, which documented the stories of more than 40 engineering education pioneers through online profiles. The intended audience for this panel includes graduate students, junior faculty, and other individuals interested in the engineering education community. Expected benefits include better understanding, increased belonging, and new or enhanced interest in engineering education. Future efforts associated with this session include understanding the impact of such exposure to the pioneers on attendees and exploring the possibility of offering this event at future engineering education conferences.

The data compression based on dictionary techniques works by replacing phrases in the input string with indexes into some dictionary. The dictionary can be static or dynamic. In static dictionary compression, the dictionary contains a predetermined fixed set of entries. In dynamic dictionary compression, the dictionary changes its entries during compression. We present parallel algorithms for two parsing strategies for static dictionary compression. One is the optimal parsing strategy with dictionaries that have the prefix properly, for which our algorithm requires O(L+log n) time and O(n) processors, where n is the number of symbols in the input string, and L is the maximum length of the dictionary entries, while previous results run in O(L+log n) time using O(n/sup 2/) processors or in O(L+log/sup 2/ n) time using O(n) processors. The other is the longest fragment first (LFF) parsing strategy, for which our algorithm requires O(L+log n,) time and O(n log L) processors, while a previous result obtained an O(L log n) time performance on O(n/log n) processors. For both strategies, we derive our parallel algorithms by modifying the on-line algorithms using a pointer doubling technique.

Studies parallel algorithms for two static dictionary compression strategies. One is the optimal dictionary compression with dictionaries that have the prefix property, for which our algorithm requires O(L+log n) time and O(n) processors, where L is the maximum allowable length of the dictionary entries, while previous results run in O(L+log n) time using O(n/sup 2/) processors, or in O(L+log/sup 2/n) time using O(n) processors. The other algorithm is the longest-fragment-first (LFF) dictionary compression, for which our algorithm requires O(L+log n) time and O(nL) processors, while the previous result has O(L log n) time performance on O(n/log n) processors. We also show that the sequential LFF dictionary compression can be computed online with a lookahead of length O(L/sup 2/).

Testing of one-dimensional (1-D) unilateral iterative logic arrays (ILA's) of combinational cells with constant test vectors is studied and the concept of one repetition length (ORL) within the tests used for testing C-testable arrays is described. The impact of ORL on the test set size and the design of the test generator are discussed. ORL can dramatically reduce the on-chip test generator size with a negligible increase in the test set size. ORL, coupled with a single distinguishing sequence (DS) for ILA's with cell vertical outputs has proved to be attractive in terms of both reduced test set size and reduced test generator size. ORL testability can be used for C-testable arrays with single faulty cell and multiple faulty cells. The technique for using a single linear finite state machine (LFSM) for generating the necessary deterministic test patterns followed optionally by pseudorandom patterns from the same automaton is discussed. Use of an LFSM as a built-in test generator for only deterministic tests for 1-D ILA's is covered. With ORL, a compact LFSM based built-in self test (BIST) generator can deliver the test vectors to all the cells in the array. The exact probability distribution equation has been developed for additional bits needed to map a nonlinear machine (FSM) definition into a LFSM definition. The distribution clearly shows that the expected number of additional bits is very small, often zero.>

This paper proposes a new rearrangeable algorithm in a multistage reverse shuffle/exchange network. Currently, the best upper bound for the rearrangeability of a shuffle/exchange network in nonsymmetric networks is 3logN-3 stages. We describe the rearrangeability of reverse shuffle/exchange multistage interconnection network on every arbitrary permutation with N\leqslant16. It can be established by setting two more stages in the middle stage of the network to allow the reduced network to be topological equivalent to a class of rearrangeable networks. The results enable us to establish an upper bound, 2logN+l stages for reverse shuffle/exchange network with N\leqslant16, and leads to the possibility of this bound when N\ge16.

Linear Finite State Machine for One Dimensional (1D) Iterative Logic Arrays (ILAs) is described. The technique for modifying the Linear Feedback Shift Register (LFSR) based test generator called Linear Finite State Machine (LFSM) for deterministic test pattern generation is discussed and extended for generating the test vectors for 1D unilateral ILAs. One Repetition Length (ORL) of C-testable ILAs and unique characteristics of the C-testable test patterns are used for the compact design of the LFSM based at-speed Built-in Self Test (BIST). Such LFSM based BIST occupies small silicon area, simplifies the design of the controller and does at-speed testing of the ILAs. This results in reduced time and cost of testing. In addition, the exact probability distribution equations are developed for additional bits needed to map a Finite State Machine (FSM) into an LFSM. The distribution clearly shows that the expected number of additional bits is very small, often zero. The probability distribution equations are equally valid for any LFSR based test generator for other circuits.>

Testing of one dimensional unilateral iterative logic arrays (ILAs) of combinational cells under multiple faults is discussed. It has been shown that it is possible to generate a test set for ILAs with primary outputs under multiple faults. Some ILAs have a constant number of test vectors independent of the size of the array. These types of arrays are called C-testable arrays. Present work proves that all useful one dimensional unilateral ILAs with only boundary outputs are not C-testable under multiple faults.>

A deterministic test pattern generator for BIST, based on linear feedback shift registers is discussed. A method of designing the test pattern generator in order that it generates deterministic as well as pseudo random patterns is presented. One application of this method is illustrated where deterministic at-speed testing of C-testable ILAs, covering all possible single and multiple combinational faults is achieved. Response analysers are discussed including one with zero aliasing probability. The algorithms for synthesizing the small amount of BIST hardware are explained.>