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1. Correlation between Asynchronous Module Comprehension and Traditional Comprehension Assessments

   Youssef, S. ( August 2021 , First-Year Engineering Experience)

   Over the past year, institutions have explored various manners to advance education while remaining socially distant, namely, through online and hybrid delivery methods. While these methods are actively employed now, the question regarding their effectiveness on student comprehension of the concepts highlighted remains. The aim of this work is to establish how effective online, asynchronous modules are for such. With respect to first-year programs geared towards establishing the foundational concepts of engineering design, two asynchronous, interactive modules were developed and deployed. Specifically, these modules introduced the foundational design concepts of stakeholders, need statements, information gathering, and design specifications. They were also developed in such a way that required student input such as identifying stakeholders or matching need statements. Student responses for each input was recorded and previously utilized to complete basic statistical analysis and derive preliminary trends. Upon completion of both modules, students completed an individual homework assignment that assessed their comprehension of the content covered in both modules. The assignment was comprised of several sections with multiple questions per section. Each question highlighted various aspects of the engineering problem framing process such as stakeholders or need statements. Basic statistical analysis was conducted for the scored items followed by correlation analysis with student performance on the modules previously completed. This work was intended to establish student comprehension of fundamental engineering design concepts after learning such through distance-learning methods, namely, asynchronous, interactive modules. Conclusions drawn from this work will possess broad ramifications and enable educators to determine if such methods are as sufficient as traditional in-person methods, if portions of the modules must be modified to enhance student comprehension, or if alternative methods must be employed altogether. 

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2. Assessing Problem-Framing Skills in Secondary School Students Using the Needs Identification Canvas

   https://doi.org/10.18260/1-2--34178  

   Herak, Patrick J ; Wellman, Bruce ; France, Todd ; West, Meg E ; Hylton, J Blake ( June 2020 , 2020 ASEE Virtual Conference)

   With programs like Project Lead The Way, engineering activities and curricula have increased in frequency in secondary school programs. In 2013, Next Generation Science Standards were published formalizing the importance of science and engineering practices in secondary schools as part of the ‘Three Dimensions of Science Learning’. For a typical secondary science department, the current engineering options can either be very expensive and/or very time consuming (often requiring engineering courses outside of traditional science courses). The purpose of a broader NSF-funded project is to create and evaluate a more accessible system for engaging students in one of the key components of engineering design: problem framing. This work presents one tool developed as part of that effort, the Need Identification Canvas (NIC), and the assessment methods developed for evaluating students’ engineering problem-framing skills using the NIC. The NIC is a tool for guiding novice designers through the need identification process, specifically addressing four key subcategories: stakeholders, stakeholder needs, a need statement, and information gathering. Student responses in each category were evaluated using a rubric, developed as part of this effort. The canvas has been implemented with suburban high school biology, chemistry, physics, and physical science classes (N=55) as well as first-year engineering students (N=18) at a private undergraduate university to provide a basis of comparison for the higher levels of achievement. In addition to comparisons between grade levels, secondary students that have and have not been taking supplemental engineering courses as part of their program of study were compared. Significant differences were found amongst a variety of these subgroups. 

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3. Towards Development of an Engineering Design Value-expectancy Scale (EDVES)

   Hylton, J. Blake ; Herak, Patrick ; France, Todd ; Youssef, Sherri ( January 2021 , 2021 ASEE Virtual Annual Conference)

   null (Ed.)

   As high school programs are increasingly incorporating engineering content into their curricula, a question is raised as to the impacts of those programs on student attitudes towards engineering, in particular engineering design. From a collegiate perspective, there is a related question as to how first-year engineering programs at the college level should adapt to a greater percentage of incoming students with prior conceptions about engineering design and how to efficaciously uncover what those conceptions may be. Further, there is a broader question within engineering design as to how various design experiences, especially introductory experiences, may influence student attitudes towards the subject and towards engineering more broadly. Student attitudes is a broad and well-studied area and a wide array of instruments have been shown to be valid and reliable assessments of various aspects of student motivation, self-efficacy, and interests. In terms of career interests, the STEM Career Interest Survey (STEM-CIS) has been widely used in grade school settings to gauge student intentions to pursue STEM careers, with a subscale focused on engineering. In self-efficacy and motivation, the Value-Expectancy STEM Assessment Scale (VESAS) is a STEM-focused adaptation of the broader Values, Interest, and Expectations Scale (VIES), which in turns builds upon Eccles’ Value-Expectancy model of self-efficacy. When it comes to engineering design, there have been a few attempts to develop more focused instruments, such as Carberry’s Design Self-Efficacy Instrument. For the purposes of this work, evaluating novice and beginning designer attitudes about engineering design, the available instruments were not found to assess the desired attributes. Design-focused instruments such as Carberry’s were too narrowly focused on the stages of the design process, many of which required a certain a priori knowledge to effectively evaluate. Broader instruments such as the VESAS were too focused on working and studying engineering, rather than doing or identifying with engineering. A new instrument, the Engineering Design Value-Expectancy Scale (EDVES) was developed to meet this need. In its current form the EDVES includes 38 items across several subscales covering expectancy of success in, perceived value of, and identification with engineering and design. This work presents the EDVES and discusses the development process of the instrument. It presents validity evidence following the Cook validation evidence model, including scoring, generalization, and extrapolation validity evidence. This validation study was conducted using pre- and post-course deployment with 192 first-year engineering students enrolled in a foundational engineering design course. 

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4. Conducting the Pilot Study of Integrating AI: An Experience Integrating Machine Learning into Upper Elementary Robotics Learning (Work in Progress)

   Xu, G. ; Zabner, D. ; Cross, J. ; Nadler, D. ; Coxon, S. ; Engelkenjohn, K. ( June 2023 , ASEE annual conference exposition proceedings)

   Artificial Intelligence (AI) enhanced systems are widely adopted in post-secondary education, however, tools and activities have only recently become accessible for teaching AI and machine learning (ML) concepts to K-12 students. Research on K-12 AI education has largely included student attitudes toward AI careers, AI ethics, and student use of various existing AI agents such as voice assistants; most of which has focused on high school and middle school. There is no consensus on which AI and Machine Learning concepts are grade-appropriate for elementary-aged students or how elementary students explore and make sense of AI and ML tools. AI is a rapidly evolving technology and as future decision-makers, children will need to be AI literate[1]. In this paper, we will present elementary students’ sense-making of simple machine-learning concepts. Through this project, we hope to generate a new model for introducing AI concepts to elementary students into school curricula and provide tangible, trainable representations of ML for students to explore in the physical world. In our first year, our focus has been on simpler machine learning algorithms. Our desire is to empower students to not only use AI tools but also to understand how they operate. We believe that appropriate activities can help late elementary-aged students develop foundational AI knowledge namely (1) how a robot senses the world, and (2) how a robot represents data for making decisions. Educational robotics programs have been repeatedly shown to result in positive learning impacts and increased interest[2]. In this pilot study, we leveraged the LEGO® Education SPIKE™ Prime for introducing ML concepts to upper elementary students. Through pilot testing in three one-week summer programs, we iteratively developed a limited display interface for supervised learning using the nearest neighbor algorithm. We collected videos to perform a qualitative evaluation. Based on analyzing student behavior and the process of students trained in robotics, we found some students show interest in exploring pre-trained ML models and training new models while building personally relevant robotic creations and developing solutions to engineering tasks. While students were interested in using the ML tools for complex tasks, they seemed to prefer to use block programming or manual motor controls where they felt it was practical. 

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5. Talk (Engineering) Ethics to Me: Student Group Discussions about Ethical Scenarios.

   Cimino, R. ; Pascal, J. ; Chadha, A. ; Girgis, K. ; Khan, A. ; Ortiz, M. ( August 2022 , ASEE Annual Conference proceedings)

   The past twenty years have seen the blossoming of ethics education in undergraduate engineering programs, largely as a response to the large-scale and high-impact engineering disasters that have occurred since the turn of the century. The functional form of this education differs significantly among institutions, and in recent years active learning that demonstrates a strong impact on students’ retention and synthesis of new material have taken hold as the preferred educational methodology. Among active learning strategies, gamified or playful learning has grown in popularity, with substantial evidence indicating that games can increase student participation and social interaction with their classmates and with the subject matter. A key goal of engineering ethics education is for students to learn how to identify, frame, and resolve ethical dilemmas. These dilemmas occur naturally in social situations, in which an individual must reconcile opposing priorities and viewpoints. Thus, it seems natural that as a part of their ethics education, students should discuss contextualized engineering ethical situations with their peers. How these discussions play out, and the manner in which students (particularly first-year engineering students) address and resolve ethical dilemmas in a group setting is the main topic of this research paper. In this study, first-year engineering students from three universities across the northeastern USA participated in group discussions involving engineering ethical scenarios derived from the Engineering Ethics Reasoning Instrument (EERI) and Toxic Workplaces: A Cooperative Ethics Card Game (a game developed by the researchers). Questions were posed to the student groups, which center upon concepts such as integrity, conflicting obligations, and the contextual nature of ethical decision making. An a priori coding schema based on these concepts was applied to analyze the student responses, based upon earlier iterations of this procedure performed in previous years of the study. The primary results from this research will aim to provide some insight about first-year engineering students' mindsets when identifying, framing, and resolving ethical dilemmas. This information can inform ethics education design and development strategies. Furthermore, the experimental procedure is also designed to provide a curated series of ethical engineering scenarios with accompanying discussion questions that could be adopted in any first-year classroom for instructional and evaluative purposes. 

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