Category: Hard Questions: Education

Hard Questions: Education

  • Investigating Transition Phases: An Autoethnographic Study of International Women of Color Engineering Educators in the US

    Investigating Transition Phases: An Autoethnographic Study of International Women of Color Engineering Educators in the US

    The study aims to explore the transitions experienced by international Women of Color (IWoC) engineers in the US as they navigate their academic and professional lives. Motivated by the lack of research on IWoC’s experiences, specifically around transition points of their lives, four international Women of Color participated in this qualitative auto-ethnographic deep-dive. All four researchers have attended college in the United States for their high educational degrees focused on education/engineering education and are currently involved in engineering education scholarship work.

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  • Making Space for Critical Action: Re-visioning Computational Thinking

    Making Space for Critical Action: Re-visioning Computational Thinking

    While school makerspaces promise to inspire and excite, the challenge of meaningfully integrating them into schools remains. Guided by a philosophy of praxis that stresses the need for education to interweave theory, action, and reflection to advance positive social change in our communities (Freire, 1970), this paper reports on the co-design of a school space called the Critical Action Learning Lab (CALL) for inclusive making to support computational thinking and critical action through curriculum-informed learning

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  • World AI: Women in AI

    World AI: Women in AI

    A collaborative event with Women in AI. We asked conference participants to tell us about their hard questions in AI, and had many fruitful conversations for future collaborations.

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  • Outsiders: Pathways and Perspectives from Engineering Education PhDs Outside Academia

    Outsiders: Pathways and Perspectives from Engineering Education PhDs Outside Academia

    This article presents a critical exploration and recommendation based on the lived experiences of PhD graduates in Engineering Education who have ventured into non-academic career paths. The work is rooted in an auto-ethnographic research approach, and the report aims to mimic a live virtual panel. It seeks to elucidate the experiences and challenges faced by PhD graduates who diverged from traditional academic roles to pursue careers in industry, entrepreneurship, consulting, and pre-college leadership. These narratives reveal a complex landscape of motivations, perceived hierarchical barriers, and under-recognition within academic and non-academic sectors, highlighting a divide between industry and academia. The paper delves into the unique challenges faced by non-academic engineering educators, such as confronting a culture that often questions their value outside traditional faculty roles and the overarching perception that non-research roles are less significant. Despite these challenges, the authors argue for the vital role these professionals play in bridging the gap between research, instruction, and practical application in engineering education. They emphasize the importance of ASEE or similar professional societies in recognizing and leveraging the diverse contributions of non-academic engineering educators to foster a more inclusive and supportive community. Key takeaways and recommendations include the necessity for ASEE and similar bodies to shift normative expectations, create inclusive and equitable environments, and actively value diverse career trajectories. The paper calls for actionable strategies to build more inclusive professional communities, create safe spaces for discussing career diversity, and establish stronger connections between current students and diverse alums. The overarching goal is to cultivate an environment where all forms of contribution to engineering education are valued, encouraging a broader spectrum of career considerations among graduates and professionals. The authors seek not only to share insights but also to galvanize a nascent community of like-minded engineering educators aspiring or working outside the traditional academic sphere.

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  • (Multi-disciplinary) Teamwork makes the (real) dream work: Pragmatic recommendations from industry for engineering classrooms

    (Multi-disciplinary) Teamwork makes the (real) dream work: Pragmatic recommendations from industry for engineering classrooms

    Many students choose to major in engineering to join the community of professional engineers and gain exposure to the field through their college experience. However, research suggests that engineering graduates may not be adequately prepared for the workplace due to the complexities of engineering work. Engineering work involves complexity, ambiguity, and contradictions, and developing innovation skills requires analyzing real-world problems that are often ill-defined and multifaceted. Therefore, it is essential for engineering students to have opportunities to work in multi-disciplinary teams to develop their skills in problem-solving and innovation. This emphasis on the need for exposure to multi-disciplinary problem solving holds true not only for undergraduate engineers in training, but also for graduate students focused on engineering education.

    This paper draws from experiences of a multi-disciplinary team (including engineers, scientists, UX researchers, Industrial-Organization (I-O) psychologists, economists, and program and product managers) studying talent management in the tech industry, to present lessons learned from leading with science to understand, inform, and improve employee experiences at a large private technology company. Our paper exemplifies how projects in industry leverage multi-disciplinary expertise and presents recommendations for new graduates and engineering professionals. Ultimately, this paper affords an opportunity for educators to expand on examples of how multiple disciplines come together to study engineers in the workforce.

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  • A Review of AI-Enhanced Personalized Learning Systems: Implications for the Learning Sciences

    A Review of AI-Enhanced Personalized Learning Systems: Implications for the Learning Sciences

    This research focuses on recent studies of AI-Enhanced Personalized Learning, organized into three main sections: understanding key aspects, investigating practical methodologies, and elucidating motivations for AI integration into personalized learning to provide insights for future research in learning science. The methodology involves a rapid literature review, emphasizing eligibility criteria and a precise study selection process. The conclusion underscores the importance of seamlessly integrating AI analytics with humancentric approaches in personalized learning, enriching data, and training algorithms for efficiency, alongside emphasizing the role of human oversight.

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  • Beyond the algorithm: Empowering ai practitioners through liberal education

    Beyond the algorithm: Empowering ai practitioners through liberal education

    As AI technology continues to transform society, there is a growing need for engineers and technologists to develop interdisciplinary skills to address complex, society-wide problems. However, there is a gap in understanding how to effectively design and deliver inter-disciplinary education programs for AI-related training. This paper addresses this gap by reporting on a successful summer school program that brought together specialists from around the world to engage in deliberations on responsible AI, as part of a Summer School in Responsible AI led by Mila – Quebec Artificial Intelligence Institute. Through deep dive auto-ethnographic reflections from five individuals, who were either organizers or participants, augmented with end-of-program feedback, we provide a rich description of the program’s planning, activities, and impact. Specifically, our study draws from engineering education research, bridging the gap between research and practice to answer three research questions related to the program: (1) How did the program design enable a more effective understanding of interdisciplinary problem-sets? (2) How did participants experience the interdisciplinary work of the program? (3) Did the program affect participants’ impact on interdisciplinary problem-sets after the program? Our findings highlight the benefits of interdisciplinary, holistic, and hands-on approaches to AI education and provide insights for fellow engineering education researchers on how to design effective programs in this field.

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  • Reimagining AI Conference Mission Statements to Promote Inclusion in the Emerging Institutional Field of AI

    Reimagining AI Conference Mission Statements to Promote Inclusion in the Emerging Institutional Field of AI

    AI conferences play a crucial role in education by providing a platform for knowledge sharing, networking, and collaboration, shaping the future of AI research and applications, and informing curricula and teaching practices. This work-in-progress, innovative practice paper presents preliminary findings from textual analysis of mission statements from select artificial intelligence (AI) conferences to uncover information gaps and opportunities that hinder inclusivity and accessibility in the emerging institutional field of AI. By examining language and focus, we identify potential barriers to entry for individuals interested in the AI domain, including educators, researchers, practitioners, and students from underrepresented groups. Our paper employs the use of the Language as Symbolic Action (LSA) framework [1] to reveal information gaps in areas such as no explicit emphasis on DEI, undefined promises of business and personal empowerment and power, and occasional elitism. These preliminary findings uncover opportunities for improvement, including the need for more inclusive language, an explicit commitment to diversity, equity, and inclusion (DEI) initiatives, clearer communications about conference goals and expectations, and emphasis on strategies to address power imbalances and promote equal opportunities for participation. The impact of our work is bi-fold: 1) we demonstrate preliminary results from using the Language as Symbolic Action framework to text-analysis of mission statements, and 2) our preliminary findings will be valuable to the education community in understanding gaps in current AI conferences and consequently, outreach. Our work is thus of practical use for conference organizers, engineering and CS educators and other AI-related domains, researchers, and the broader AI community. Our paper highlights the need for more intentional and inclusive conference design to foster a diverse and vibrant community and community of AI professionals.

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  • Bridging the Gap: Exploring Semiconductors Exposure and Motivation among Multidisciplinary Engineering Students

    Bridging the Gap: Exploring Semiconductors Exposure and Motivation among Multidisciplinary Engineering Students

    Several educational initiatives are currently underway to address workforce challenges in the semiconductors industry. Assessing students’ exposure to and motivation for semiconductors-related topics is an essential initial step toward recognizing areas where primary efforts should be concentrated. The primary objective of this study is to assess students’ awareness and motivation concerning semiconductors in the context of a multidisciplinary introduction to electrical engineering course. Through quantitative analysis and the administration of an existing validated survey instrument, we aim to explore students’ exposure to semiconductors-related topics and potential correlations between awareness, motivation, and demographic variables, including gender and class standing. The instrument was administered to a cohort of 255 students enrolled in a multidisciplinary course covering the fundamentals of electrical engineering. Preliminary data indicates that only 9% of the students in this cohort haven taken a class about semiconductors and only 3% have some interest in pursuing a career in the semiconductors field. The results of this analysis hold several significant implications for engineering education and the semiconductor industry. Firstly, the limited exposure to and interest in semiconductors among engineering students suggest the need for curriculum alignment with the demands of the semiconductor industry and interdisciplinary education. By doing so, we empower students from diverse disciplines to contribute to technological advancements, innovation, and problem-solving fostering a more inclusive, diverse, and well-rounded workforce within the semiconductor sector.

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  • Teaching Future-Makers: Outcomes of an International Design Workshop for Critical Action Educators

    Teaching Future-Makers: Outcomes of an International Design Workshop for Critical Action Educators

    This paper reports on recent developments of the Critical Action Learning Exchange (Carvalho et al., 2021), an international community of educators who seek to respond to social and environmental issues that affect their students. We report on an international design workshop that engaged a cohort of teachers in designing Critical Action Learning activities for their students in the Summer of 2023. Participants (n=39) completed 16 curriculum designs for grade levels from kindergarten to university, addressing a broad range of socio-environmental issues and adopting diverse approaches, such as Arts-Based Critical Action, Community Engagement, Critical Making, Games for Critical Action, and Storytelling. This paper examines our Professional Development model, together with an analysis of teacher participants’ ideas and their design products. We investigate what forms of scaffolding can facilitate the changes of practice needed for teachers to become critical action educators and support their Critical Action Learning designs.

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  • Leveraging AI in education

    Leveraging AI in education

    To stay ahead, it is essential to adapt to the rise of AI by intelligently incorporating it into all levels of the education process

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  • The Usefulness of Big Data and IoT/AI at Dubai University. Kurdish Studies, 12(2), pp.6198-6220

    The Usefulness of Big Data and IoT/AI at Dubai University. Kurdish Studies, 12(2), pp.6198-6220

    Digital transformation is disrupting most sectors and most so the education sector. Universities across the world are using technology to reach out to students and to deliver classes remotely enabling students and staff to adopt modern emerging technologies. Dubai University, based in the heart of a technological hub, has the unique opportunity to leverage cutting-edge technologies like Big Data, the Internet of Things (IoT), and Artificial Intelligence (AI) to revolutionize its academic and operational landscape. This research study explores the usefulness of emerging technologies in enhancing Educational Experiences by analyzing Big Data of student learning patterns, engagement levels, and performance to unlock personalized learning pathways, adaptive courseware, and targeted interventions. AI-powered tutoring systems and virtual labs offer immersive and customized learning experiences shortly. IoT sensors can monitor and manage energy consumption, building security, and resource allocation, leading to sustainable and efficient campus operations. AI-powered systems can automate administrative tasks, streamline processes, and provide predictive maintenance for facilities. The main contribution of the study is using PLS-SEM modeling to analyze Big Data enabling researchers to extract insights from vast datasets and make data-driven discoveries. AI-powered tools can aid in research design, data analysis, and scientific simulation, fostering a culture of innovation. This study will employ a mixed-method approach, utilizing quantitative data analysis of existing university data sets and qualitative interviews with stakeholders. The findings will contribute to developing a strategic roadmap for the optimal integration of Big Data, IoT, and AI within Dubai University’s ecosystem. This research aims to position Dubai University as a pioneer in education and innovation, setting a benchmark for higher education institutions in the region and beyond. The study aims to provide insights to empower decision-makers at Dubai University to make well-informed choices regarding the adoption and integration of emerging technologies. The study facilitates strategic planning by comprehensively grasping the challenges and opportunities presented by digital transformation. Moreover, it guides resource allocation and offers recommendations for leveraging data analytics to support students who may be at risk.

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