Category: Sector: Education

Hard Questions: Education

  • (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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  • 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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  • Board 164: Engineering Interventions in My Science Classroom: What’s My Role?

    Board 164: Engineering Interventions in My Science Classroom: What’s My Role?

    This work in progress paper draws on data from year one of a multi-year project aimed at integrating engineering into middle-school science classes. The expectation that middle school teachers integrate engineering into their science curriculum may be challenging as engineering related content has not historically been part of teacher preparation. Particularly in rural areas, in service teacher training related to engineering may be absent or difficult to access due to proximity or financial or time costs. Therefore, it is important to develop effective professional development (PD) that works within the actual teaching context and makes few demands on teachers beyond their regular workload. In partnership with teachers and local industry workers in rural and Appalachian areas, the Virginia Tech Partnering with Educators and Engineers in Rural Schools (VT-PEERS) project developed extended classroom engineering activities for students that also served as teacher PD related to teaching engineering in locally relevant ways. As part of this work, a qualitative analysis was conducted to understand how teachers, from their perspectives, envisioned their role during the interventions. Data were collected prior to and after interventions (within an academic year) to further understand if, and if so, how, teacher perspectives of their role changed. Results reveal three initial roles; classroom manager, learner, helper, and unsure. The post intervention data revealed all teachers indicated being a “learner”.

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  • Board 192: Identifying and addressing the barriers to advancement for women in the engineering professoriate: A systematic review of literature

    Board 192: Identifying and addressing the barriers to advancement for women in the engineering professoriate: A systematic review of literature

    This work-in-progress paper shares ongoing findings from a mixed-methods systematic literature review that seeks to examine the retention of women in the engineering professoriate. We identified literature from EBSCOHost and Engineering Village that discussed women in the engineering professoriate in relation to either retention or persistence or both, as explicitly stated in their abstract. Following an initial review of 191 titles, 48 papers passed our inclusion criteria; further qualitative analysis of abstracts yielded 31 papers, which underwent a full paper review. Our ongoing findings suggest the following: a) research on the retention of women in engineering professoriate is being supported by grants and funding opportunities; b) the reviewed literature documented six barriers faced by women in the engineering professoriate: isolation of women faculty, work/life balance, inequitable distribution of service, underrepresentation of women faculty, implicit bias, and departmental resources; and c) although journal scholarship on this topic is not limited to popular engineering education publishing venues, conference scholarship are mainly from those popular in the field, such as the ASEE Annual Conference and the Frontiers in Education Conference. Future work will share the extent to which the reviewed literature discussed interventions to recruit or retain women in the engineering professoriate, and whether these interventions vary by the type of institution.

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  • Using Science to Support and Develop Employees in the Tech Workforce—An Opportunity for Multidisciplinary Pursuits in Engineering Education

    Using Science to Support and Develop Employees in the Tech Workforce—An Opportunity for Multidisciplinary Pursuits in Engineering Education

    The majority of students who choose to major in engineering do so to become a part of the community of practice of professional engineers (Johri & Olds, 2011), meaning that they want to have adequate exposure to what a career as a professional engineer could potentially be as part of their college experience. However, according to Jonassen (2014), engineering graduates are not well trained to contribute to the workplace due to the complexities associated with engineering work. Stevens, Johri, and O’Connor (2014) described engineering work as that which involves complexity, ambiguity, and contradictions. Since developing the skills for innovation involves analysis of complex, ambiguous, ill-defined, real-world problems (Daly, Mosyjowski, & Seifert, 2014; Newell, 2010), students must have an opportunity to, at the very least, be exposed to multidisciplinary teams. 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.

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  • Work in progress: Coloring Outside the Lines-Exploring the Potential for Integrating Creative Evaluation in Engineering Education

    Work in progress: Coloring Outside the Lines-Exploring the Potential for Integrating Creative Evaluation in Engineering Education

    Extant cultures within academic institutions that educate and train the next generations of STEM professionals tend to privilege long-held majority perspectives of knowing, thinking, and doing in science and engineering. To more intentionally recruit and include diverse groups of students into our educational programs, it is imperative that we develop and adopt unique pedagogical and assessment approaches that move beyond didactics, leverage experiential learning, and embrace a variety of student backgrounds and identities. In this paper, we demonstrate how visual methods-based assessments can serve as an impactful alternative to more traditional forms. We start by introducing three examples currently used in STEM curricula, and then by describing how these assessments promote autonomy and creativity as students make meaning of STEM and of themselves as STEM professionals. We conclude the description of each assessment example by identifying key considerations for STEM instructors when attempting to implement such assessments in their own contexts.

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  • Preparing engineering students to find the best job fit: Starting early with the career development process

    Preparing engineering students to find the best job fit: Starting early with the career development process

    In spite of the vast amount of literature that focuses on the need for significantly more science, technology, engineering, and mathematics (STEM) graduates, the importance of a student finding a good career fit, and what makes a student employable, little research exists on undergraduate engineering students’ understanding of the process of how to find, qualify for, and secure a preferred first position after graduation (FPAG). Likewise, it is important for research to consider nuanced distinctions within STEM fields to assist research to practice transitions. Competition in securing jobs upon graduation is expected to continue, including for engineering positions. In fact, even in a market of high demand for STEM graduates, employers need candidates that display the skills, interests, and readiness to be successful employees.

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  • From the classroom to the newsroom: A critical route to introduce AI in journalism education

    From the classroom to the newsroom: A critical route to introduce AI in journalism education

    From a computer vision application to monitor elections transparency in Argentina to automated real estate texts in Norway, and everything in between, Artificial Intelligence powered tools are changing journalism. Scholars have taken note, and the academic production of AI in journalism has gained considerable ground in the last five years. However, research on how journalism education deals with AI influence in the industry is scarce. Based on a self-training method using available online free courses for journalists and a review of university teaching initiatives, this article proposes key elements to trace teaching trajectories to introduce AI into journalism curriculum. Included are recommendations for drawing a path to teaching journalism students to think critically about AI and, at the same time, to understand the available tools for reporting and investigating in a complex context where journalism lives in a profound state of crisis.

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