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.
Category: Sector: Education
Hard Questions: Education
-
Decoding the Diversity: A Review of the Indic AI Research Landscape
This review paper provides a comprehensive overview of large language model (LLM) research directions within Indic languages. Indic languages are those spoken in the Indian subcontinent, including India, Pakistan, Bangladesh, Sri Lanka, Nepal, and Bhutan, among others. These languages have a rich cultural and linguistic heritage and are spoken by over 1.5 billion people worldwide. With the tremendous market potential and growing demand for natural language processing (NLP) based applications in diverse languages, generative applications for Indic languages pose unique challenges and opportunities for research. Our paper deep dives into the recent advancements in Indic generative modeling, contributing with a taxonomy of research directions, tabulating 84 recent publications. Research directions surveyed in this paper include LLM development, fine-tuning existing LLMs, development of corpora, benchmarking and evaluation, as well as publications around specific techniques, tools, and applications. We found that researchers across the publications emphasize the challenges associated with limited data availability, lack of standardization, and the peculiar linguistic complexities of Indic languages. This work aims to serve as a valuable resource for researchers and practitioners working in the field of NLP, particularly those focused on Indic languages, and contributes to the development of more accurate and efficient LLM applications for these languages.
-
Exploring and Expanding Support for International Students in Engineering: Faculty Reflections Beyond Academic Boundaries
This is a student paper:
Expanding upon our previous work in the blinded for review paper, this research seeks to delve into the realm of self-reflection among engineering faculty members who regularly interact with international students. The primary objective is to investigate how these faculty members address the unique needs of the international student community. The Challenge and Support model by Nevitt Sanford serves as our guiding framework for this research, and we employ narrative analysis due to its potential in analyzing differences in cases and describing the dynamics of individual narratives within their distinct contexts (Floersch et al., 2010; Simons et al., 2008).
This paper aims to answer the following research question: How do engineering faculty members address the multifaceted and distinct needs of international students? It is important to understand these perspectives when considering how to support international engineering students given that each student has unique and intricate experiences in both academic and non-academic aspects.
-
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.
-
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
-
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.
-
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.
-
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
-
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.
-
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.