This innovative practice WIP paper describes the implementation of a five-year mentoring initiative for science and engineering programs at an urban, private institution with the goals of providing holistic programming and opportunities for early career preparation for all first-year students. In partnership with Mentor Collective, peer mentor programming was designed to include data collection from mentees to better understand their needs and to support their academic training with meaningful experiences that support career readiness. Data over a five-year period from mentees demonstrate the following: (1) expectations from program participants vary significantly from learning how to maintain healthy work-life balance to succeeding in classes and participation in co-curricular activities, (2) graduation rates at and above 80% are achievable and sustainable, which is significantly higher than the national average and (3) closing of the opportunity gap can be accomplished for populations that have traditionally low graduation rates. Feedback from the mentors (industry professionals) reveal very high interest in their willingness to continue participation, which suggests that mentoring initiatives are mutually beneficial, sustainable, and scalable across institutions. Additional data from this report also demonstrate that the impact of linking first-year students with industry professionals can serve as a scalable mentoring solution.
This research-to-practice WIP paper describes an approach to engage high school students in research through the utilization of citizen science tools embedded with Machine Learning (ML) models. In the context of fostering early engagement in scientific research among high school students, this paper explores the integration of citizen science and ML using SmartCS, an existing platform for creating citizen science smartphone applications. The process requires no prior programming knowledge, making it accessible to a broad range of students. For our approach, a group of high school students participated in a two-month-long summer research program, where they were introduced to the principles of citizen science as a method for data collection across diverse scientific projects from different research domains. The program's initial task involved students in the conceptualization of a citizen science project, adopted based on a thorough literature review, followed by the practical task of developing a smartphone application for data collection and educational purposes. Students either created new datasets or curated existing ones to train lightweight ML models for computer vision tasks, specifically focused on providing visual guidance within these mobile apps. The final task involved deploying these applications for public use and collecting user feedback. Our experience suggests that this approach not only enabled students to learn aspects of computer science and engineering, particularly in the area of ML model training and mobile application software development, but also allowed them to experience firsthand the significant role citizen science can play in collecting and analyzing scientific data.
Rapid technological evolution and the advent of the Internet of Things (IoT) are reshaping the necessary competencies for professionals in different fields, including engineering that focuses on networking, telecommunications, IoT, or embedded systems. This research project proposes an in-depth analysis of the benefits brought about by the inclusion of LoRaWAN technology in the curriculum of courses offered by the Instituto Federal do Amazonas (IFAM), focusing on both technical skills (hard skills) and interpersonal and cognitive competencies (soft skills) of students participating in research, development and innovation project (R,D&I). LoRaWAN, a low power long-range communication technology, has significant potential for applications in smart cities, precision agriculture, natural resource management, and smart power meters, underscoring its relevance to current and technical education. LoRaWAN technology integrates various engineering disciplines in the curriculum, challenging the update process. The paper suggests a method to assess the performance of 12 students in three R, D, I projects for the improvement of the curriculum. Identifies the impact on students' education and provides guidance for educational institutions based on students' task difficulties and interaction with the development team.
Contribution: In this full research paper, we offer a quantitative analysis of how gamification influences students' gameful experience within a mobile online learning gamified platform, specifically Duolingo. We explored how these effects vary based on students' self-declared gender, providing valuable insights into the intricate dynamics within gamified educational environments. Background: The use of gameful environments as educational tools has been acknowledged for its potential to yield diverse outcomes in students' learning achievements, encompassing both advantageous and disadvantageous effects. Among the hypotheses regarding the observed diverse outcomes is that gamification may influence individuals' experiences differently based on their inherent traits, such as gamer type, age, and gender. While recent research has made strides in exploring this hypothesis, knowledge regarding how gamification can affect users' experience in gameful environments remains limited. Research Questions: This study aims to address the following question: How does gamification affect students' gameful experience (i.e., accomplishment, challenge, competition, guided, immersion, playfulness, and social experience) according to their self-declared gender? Methodology: To answer this research question, we conducted a quasi-experimental study (i.e., involving the comparison of groups without random assignment), organized in three steps. In the first step, we invited technology students to utilize the gamified platform, Duolingo, for a minimum of 20 minutes. In the second step, participants completed the GAME-FULQUEST, a scale comprising 56 items across seven dimensions, designed to measure their gameful experience while using the platform. They also answered a demographic questionnaire to indicate their gender (following ethical recommendations, we included the options: “male”,”female”, “non-binary” and “I prefer to not disclose”). In the third step, we employed Structural Equation Modeling to analyze the effects of gamification on students' gameful experience, according to their gender. Our sample comprised 110 students, with 42 self-identified as females and 68 as males. Findings: Our results indicate that learners' gender did not affect any of the dimensions of the gameful experience. This result opens up space for several insights into how gamification can affect the learners' experience according to different variables.
This research-to-practice full paper compares data science education strategies in China and the United States, exploring whether different approaches can achieve similar educational outcomes. In the U.S., data science programs are typically developed by individual schools to meet labor market demands, integrating data science as an interdisciplinary subject. In contrast, Chinese universities follow a uniform plan set by the education department, resulting in specialized fields like ‘Big Data Management and Application’ and ‘Data Science and Big Data Technology.’ This research collected data on course offerings and university rankings in China and the U.S., analyzing curriculum content and program characteristics. Major findings indicate that in the U.S., Data Science and Business Analytics programs focus on technical skills and are primarily found in top-ranking universities, while in China, Data Science and Big Data Management programs emphasize management and are more widely distributed across different ranking groups. Despite these differences, both countries show similar geographic concentration patterns in data science programs. The study concludes that China and the U.S. adopt different educational strategies but achieve comparable effectiveness in data science education.
This Innovative Practice Work in Progress paper presents a novel educational platform that is both free and open-source, specifically designed to enrich the learning experience. Our system enables educators to create customizable educational learning experiences, accommodating the diverse structures of classroom settings. Acknowledging the constraints of a one-size-fits-all approach, our initiative was motivated by the demand for a versatile tool that is flexible enough to support a range of teaching objectives-be it fostering collaboration, increasing individual engagement, or pursuing any other pedagogical aims the instructor may have. The core of our innovation lies in the system's exceptional adaptability, offering instructors the ability to tailor the educational content to their precise objectives. This adaptability extends to creating a diverse range of learning scenarios, from interactive quizzes to collaborative challenges, each designed to enrich the educational journey. Furthermore, our platform simplifies the transition to digital learning environments by providing a fully managed, ready-to-use website, eliminating the complexities of code modification or the necessity for self-hosting. Our system is designed with contemporary educational interactions in mind, showcasing full mobile compatibility. This allows students to engage seamlessly with the educational material, whether through smartphones or computers, ensuring the tool's accessibility and convenience for a digitally native generation. The user-friendly interface and the interactive nature of the platform may remind some of Kahoot, but our system distinguishes itself with its extensive customizability and open-source framework. To view our project's progress, please visit our repositories: the back-end at https://github.com/uncc-hice/edukona_backend and the front-end at https://github.com/uncc-hice/edukona_frontend.
Generative AI tools are becoming more widely available and have increasing functionality. Students are beginning to integrate AI into their current practice and will need to be able to ethically use AI in their future careers. Instead of banning AI in an undergraduate biomedical instrumentation instructional laboratory course at a large public university, it was intentionally added with awareness of privacy, equity, and accountability. An assignment was adapted to walk students through comparing data analysis by hand, with mathematical software, and with generative AI. The goal of the updated assignment was for students to be able to think critically about the difference between doing analysis by hand, with purpose-built and validated software, and with a generic tool based on a large language model. The submitted post-lab assignments were analyzed by the research team to understand the students' approach to this assignment and what they learned about each method. All the students were able to complete the assignment, however there was mixed feedback on the usefulness of the assignment. Details about the assignment development and analysis of student work on the assignment are included in this paper.
This full paper in the innovative practice category introduces a uniquely novel visual privacy themed game, which is meant to be used as an experiential learning tool for teaching plus demonstration of fundamental data privacy concepts and basic security concepts. To our knowledge, this new, innovative visual privacy themed game, as presented in this paper, is the first of its kind gamified educational tool, which makes use of the privacy through visual anonymity i.e. VPET (Visual Privacy Enhancing Technology) theme for effective illustration of privacy concepts along with basic security concepts. This paper describes our nifty, visually interactive VPET game, which teaches privacy plus security concepts through the PET illustration and demonstrates applied cryptography for privacy-driven de-identification through obscuration-based disguise tasks during the game play. It also discusses how we have successfully used a pilot, proof of concept prototype version of this game over the last few years for cybersecurity education and outreach primarily at the K-12 level. Over the last few years, we have surveyed several VPET game players, who are from a large, diverse group of K-12 community members, consisting mainly of high school students and teachers, who have played the VPET game, as part of several cybersecurity training camps and outreach workshop sessions, and have benefited from this exercise in terms of learning, as well as developing awareness plus interest in privacy and security topics. This paper shares and analyze the preliminary data collected from all these survey responses to evaluate the prospects of our unique VPET game as a potential educational and outreach tool for engaging K-12 learners, for teaching privacy plus security concepts, and for creating awareness plus interest in cybersecurity. In summary, we demonstrate how our unique VPET gamification approach for educational purposes can successfully engage students for effective learning of data privacy and cybersecurity concepts.
Since the introduction of generative artificial intelligence (GenAI), education in computer science has prompted efforts to incorporate it into the educational curriculum. This innovative practice full paper presents a study into using GenAI to enhance student learning of software engineering. It outlines the initiatives to introduce GenAI into a graduate-level software engineering course in Software Verification and Validation (SV&V). The paper presents the educational goals, methodologies and findings of these endeavors in this course. The primary education goal of this course is that students have a solid understanding of principles and practices of software quality assurance and seek to introduce students to diverse techniques employed for SV&V. The study presented in this paper centers on the practical application of GenAI within the domain of testing strategies. The paper introduces the findings of an exercise where GenAI was used to apply testing strategies for unit testing. The exercise consisted of the use of GenAI in the development of unit tests for an algorithm. Rigorous assessments were conducted to gauge the effectiveness of the unit tests developed for validating the accurate implementation of the algorithm. This exploration shed light on the tangible impact of GenAI on the precision and efficiency of unit testing procedures. The findings underscore the significance of encouraging students to actively explore emerging trends and methodologies in the realm of software verification and validation. By incorporating GenAI into the educational framework, students not only gain insights into the capabilities and limitations of this technology but also foster a mindset of continuous learning in software quality assurance. The paper demonstrates that it is not sufficient to use the test cases developed by GenAI for software validation since test cases recommended by GenAI do not cover corner cases which causes gaps in coverage in unit testing. The majority of the students were able to understand the limitation of GenAI in SV&V but appreciated its support in suggesting test cases for the most common cases. This exercise allowed students to enhance their creative problem-solving through human-guided AI partnership which is pivotal in cultivating a new generation of professionals capable of contributing to the ongoing evolution of software quality.
This research-to-practice full paper presents a series of brief engineering ethics case studies, all inspired by actual incidents recounted during interviews with early career engineers. Current ABET accreditation requirements include ethics-related outcomes for engineering graduates, and most engineering professional societies and employers maintain their own ethics codes. Yet we have limited knowledge about what kinds of ethical situations and issues are faced by practicing engineers, both in general and during early career phases. More nuanced understandings about the ethical dimensions of engineering work could inform training interventions designed to better prepare engineering graduates for workplace realities. This paper aims to bridge research and practice by presenting a series of brief case studies covering a variety of ethical situations encountered by early career engineers. The case studies are adapted from interviews conducted with a stratified sample of 29 technical professionals, all with at least one degree in engineering and 1-3 years of full-time work experience. The interviews were carried out as part of a larger mixed-methods research study investigating how engineering students and early career professionals perceive and experience ethics, social responsibility, and related concerns. The case studies presented in this paper were intentionally selected and developed to reflect different job roles and industry settings, as well as diverse ethical issues encountered by our participants. We present cases that reflect more commonplace or everyday situations that are "microethical" in nature, i.e., involving localized interactions among individual professionals. We also include some suggested scaffolds and resources for instructors seeking to use such cases in their teaching. We intend that this paper will be relevant and useful for instructors who want to bring early career ethics cases into their courses, as well as for those wishing to write short ethics case studies.
This research-to-practice paper presents a novel pedagogical tool for hardware cybersecurity education and workforce development. The growing importance of hardware security has made it essential for individuals and organizations to understand hardware security principles and best practices. However, the current educational curriculum falls short of fulfilling these emerging demands due to the rapidly changing hardware security landscape and limited opportunities for hands-on training. To address these challenges, we propose and have developed the Interactive Hardware and Cybersecurity (I-HaC) Educational Framework, a pedagogical educational framework that supplements existing courses by leveraging generative AI for individualized instruction related to hardware and cybersecurity, data mining, and applied Machine Learning (ML), as well as data visualization to enhance cybersecurity education and workforce development. The framework is designed to be utilized by graduate and undergraduate Electrical and Computer Engineering (ECE) and Computer Science (CS) students for a comprehensive introduction to cybersecurity exploits and countermeasures in an interactive manner with hands-on components. Using I-HaC, we have developed tailored lab components for a diverse range of students and intend to release I-HaC as open-source for the benefit of the ECE and CS education community.
This Innovative Practice Full Paper outlines the findings of a survey conducted at the Robert Gordon University (Scotland, UK), focusing on feedback from faculty members and reflections subsequent to the introduction of a Pass/Fail grading system in the CS1 curriculum within the School of Computing, complementing previous work done focussing on the same implementation from the student perspective. This study aims to understand the impact of this grading model on teaching and assessment practices, student engagement, and motivation from the perspective of the module coordinators involved in the foundation year modules where this grading model was implemented. Analysis of the data indicates a generally positive reception of the Pass/Fail grading model among staff members. They reported streamlined marking processes and simplified grading grids as notable advantages. However, concerns were voiced regarding potential student demotivation and the ambiguity in determining the Pass/Fail threshold, which matched results from the student survey. Staff also encountered challenges in adapting assessment designs, particularly in shifting away from traditional grading paradigms. By shedding light on these observations, this paper contributes insights into the intricacies and consequences of integrating a Pass/Fail grading system into the early stages of an undergraduate computing curriculum. It not only underscores the need for careful consideration of pedagogical shifts but also provides valuable guidance for future implementation strategies. In summary, this research delves into the experiences and perspectives of staff members directly involved in implementing the Pass/Fail grading model. By addressing both the benefits and challenges encountered, it offers a comprehensive understanding of the implications of such a grading system within the context of undergraduate computing education. This, in turn, can inform decision-making processes and refine pedagogical approaches for enhanced faculty experience. Moving forward, exploring longitudinal effects of the Pass/Fail grading model on student retention rates could offer deeper insights into its efficacy in preparing students for future endeavors. Moreover, investigating potential variations in perceptions and outcomes across different academic settings and/or contexts could yield valuable comparative analyses.
This research full paper describes a web-based online learning platform that delivers financial literacy lessons via talking head videos of AI-generated personas with two additional core features: LLM-powered proactive chat-based question-and-answer interactivity, and personal choice of the AI instructor from a list of distinct personas. We conducted two comparative studies with a total of 233 Thai students aged 1825, which aim to 1) investigate the impact of interactivity and instructor selection on the learning experience, and 2) further explore the underlying factors at play with instructor selection by introducing AI instructors' backstories as an extra intervention. We found that enabling interactivity significantly enhanced learning motivation, perceived learning facilitation, engagement, and virtual instructors' humanness compared to the passive setting. Providing learners with a choice of AI instructors provided minimal additional benefit. However, the learner's feeling of relatedness toward the instructor is a significant positive predictor of learning motivation, positive emotion, and agent credibility, while goal alignment with the agent correlates with perceived learning facilitation, and admiration corresponds with perceived agent humanness. These findings underscore the potential of interactive virtual instructors-ones that interactively encourage learners to reflect on the teaching materials throughout the lesson through two-way interaction-in enhancing motivational and experiential aspects of remote education, even if they do not significantly impact comprehension, and the importance of promoting learner's relatedness and goal alignment with the agent in boosting other aspects of the learning experience.
This innovative practice full paper describes ConceptualTales, a conversational AI that explains STEM and social science concepts using analogies from popular story worlds and Socratic reasoning. The disconnect between conventional teaching strategies and student engagement is a persistent challenge in educational systems, particularly STEM fields. Traditional methods often fail to resonate with students, rendering the learning process monotonous and detached from their personal interests. Concurrently, students are enthusiastic about and dedicated to fictional worlds such as Marvel, Harry Potter, and Disney. This observation forms the basis for our innovative practice: integrating these beloved narratives into educational content through generative AI. ConceptualTales was tried with middle and high school students in the USA and China and received overwhelmingly positive feedback. Our system combines fiction-inspired learning, analogical reasoning, and Socratic questions, to make educational content personal and interesting to students.
This innovative practice work-in-progress paper describes using H5P-based activities to support student learning and engagement in face-to-face courses.
Contribution: This full innovative practice paper presents a series of pedagogical interventions implemented to enhance student engagement, preparedness, and writing skills in a laboratory setting. It integrates Perusall assignments, peer reviews, peer mentoring, and a specification grading system into the curriculum, offering a structured but still flexible approach to laboratory education. Background: Many students struggle with scientific writing and find the lab work process challenging and disengaging. Previous works have utilized peer-assisted learning and digital tools, but there remains a need for the use of new strategies to address these challenges in a laboratory environment. Intended Outcomes: The primary goal is to improve students' readiness for lab sessions, increase engagement through collaborative learning, and enhance their scientific writing skills. The interventions are designed to create a supportive learning environment that encourages active participation. Application Design: The interventions were implemented over three academic quarters. Students were required to prepare for lab sessions by annotating lab manuals via the Perusall platform, which grades engagement automatically. Peer reviews were conducted with structured rubrics. Peer mentoring was incorporated into lab sessions, with initial guidance from the instructor followed by student-led training. To provide opportunities for report revision based on feedback, the specification grading system was used by categorizing lab reports as complete or incomplete. Findings: Student performance and a Likert scale survey were used to measure the outcome of the interventions. Over 80% of students reported that Perusall assignments enhanced their understanding of lab concepts, and more than 70% felt they learned effectively from their peers. Peer review was not received favorably with only 25% finding it helpful. The majority felt that peer mentoring significantly increased lab engagement. The specification grading approach resulted in a higher rate of reports meeting initial submission standards, particularly in later sessions, indicating improved writing quality. Overall, these methods demonstrated a positive impact on student learning and engagement in laboratory courses.
This work-in-progress research paper analyzes student activity as captured by the sequence of programming submissions they make. Although students who complete assignments in a computing course are often assessed in a summative way through the submission of a completed program, their activities during development provide additional insights into their work and problem-solving processes that cannot otherwise be captured. In the context of a data structures & algorithms course taught at the sophomore level, we first examined the number of attempts that students made while completing assignments throughout the semester. We then examined the cumulative portion of the class that had submitted an assignment relative to the due date, and the time periods after assignment release that students are active. Our work helps to illustrate how a programming activity trace provides a unique source of information on how a submission evolves. It was found that even with only feedback as motivation, students made many submissions and that number increased during the semester. Our initial work indicates that a substantial amount of data is available and helps suggest what aspects might provide information useful for further analytics using traditional statistics or machine-learning approaches.
This innovative practice full paper describes a two-semester capstone experience that trains students in agile software engineering principles and incorporates the material into building an actual product for an industry partner. Recently, teaching agile software engineering has garnered considerable attention, and research has focused on effective pedagogical approaches, challenges, and outcomes. However, while computer science students are exposed to agile methodologies in their curriculum, and students even use the approach in a project, the experience tends to be brief and non-real-world. In this work, we believe our approach provides a more cohesive learning experience, better prepares students for jobs in industry, and introduces them to incorporating an overall agile mind set. We outline specific activities, timelines, and best practices for managing team projects and providing a better experience for the students. The results of our efforts are reported through retrospectives and reflections with the students over five years.
This work-in-progress paper reports on a new innovation model that extends Pasteur's Quadrant by adding an axis called Contemplation of Sentiment, which reflects the human-centered aspects of innovation. Human-centered designers and artists have played an integral role in innovation throughout history up to the present day. However, engineering education programs have not often included this integration - relying on a focus on “STEM” even though leaders in industry from Amazon and Apple to Qualcomm and SpaceX have left this exclusionary approach behind. Pasteur's Quadrant is a model adopted by industry and US government agencies to point to the relationship between basic and applied scientific research. To describe the implications of this model, we share the qualitative methodology and early results collected in over 30 individual interviews with thought leaders in industry reacting to da Vinci's Cube. We are exploring the question, “What is the connection between artists, designers, and broad societal innovation in relation to economic and job growth?” Early findings show that managers place themselves, their company, and their hires on relational intersections that include our added axis of “contemplation of sentiment”. We discuss these findings in the context of an NSF-RED team that developed a notable exception to the narrow curricula typical of electrical and computer engineering undergraduate programs.
This research WIP paper describes the impact of faculty mobility in engineering colleges, resulting from mandatory rules in a State Government set up, particularly in Kerala State in India. It affects not only the faculty members themselves but also students, academic programs, and institutional culture. However, there are also potential benefits associated with this practice, viz; knowledge exchange, professional and individual growth, enhanced networking opportunities, institutional development and diversity and inclusion. Faculty members bring with them diverse perspectives, teaching methodologies, and research insights, enriching the academic environment and contributing to professional development among peers. The paper highlights this distinctive challenge faced within the engineering education sector in Kerala State, which is not commonly observed in other regions of India or globally. In contrast to elsewhere, where faculty members usually enjoy the autonomy to select their preferred workplace, such as colleges or universities, this situation presents a different dynamic. The paper also mentions the methodology to be adopted for a comprehensive investigation in this direction, to understand the pros and cons of the unique aspect A basic initial step in this research is carried out and the preliminary results and discussion are included in the paper.
